AXA Research Fund RSS Feed http://www.axa-research.org AXA Research Fund RSS Feed 1369282784 en hourly 1 4117 /launch-of-the-axa-university-of-tokyo-chair-for-health-and-human-security 2013-04-24T00:00:00 Launch of the AXA–University of Tokyo Chair for Health and Human Security <p style="text-align: justify;" class="title_06"><font size="3">&nbsp;</font><b><font size="3">Risk factor trends for Japanese</font></b></p> <p style="text-align: justify;"><font size="3">How has Japan achieved the longest life expectancy at birth in the world? Ranked first in terms of life expectancy at birth for women since 1986, recording the highest ever worldwide figure of 86 years in 2008, Japan seems to hold the secret of longevity. Understanding what factors have contributed to making the Japanese population healthy is important for global health policy, particularly for countries struggling to improve public health.</font></p> <p style="text-align: justify;"><font color="#000000"><font size="3">That’s why Prof Inoue, together with Nayu Ikeda, Project Lecturer, intends to get a firm grasp on the interplay of selected risk factors in the burden of disease and injury over in the past few decades in Japan. In that perspective, Prof Inoue will study the distributions of risks across population subgroups based on age, sex, geography and socio-economic status, with a particular focus on ageing. She will also lead an analysis of risk factor trends, which is important for multiple reasons. First, for some risks that have a long lag-time of accumulated hazard between exposure and health outcomes (e.g. smoking), risk factor trends offer a better illustration of accumulated hazard than current prevalence. Secondly, risk factor trends can be used to assess the role of social, policy, and technological determinants of exposure. Thirdly, comparative assessment of trends in multiple risk factors would allow for a health policies ranking.</font></font></p> <p style="text-align: justify;" class="title_06"><b><font size="3">Identify the most cost-effective health policies</font></b></p> <p style="text-align: justify;"><font size="3">Consequently, the comparison of simultaneous trends in multiple risk factors and the focus on the disparities in mortality rates will empirically contribute to understand how socioeconomic and technological changes, as well as public health policy, have affected risk factor and disease patterns. Furthermore, the comparison of cost-efficiency of <font color="#000000">each of these factors (clinical, public health, and social measures in mitigating the effects) will help identify which type of risk can be reduced relatively easily, at low cost, and which cannot.</font></font></p> <p style="text-align: justify;"><font size="3">Results will therefore be helpful to inform the allocation of available resources and could lead to <font color="#000000">policy recommendations, providing inputs to programs that aim to prevent disease and injury. Once the most cost-effective interventions are identified, it will be easier to illustrate how decision makers can begin the policy debate on priorities with information about which interventions would yield the greatest possible improvements in population health. The results of this research project will thus be relevant for doctors, public health professionals, insurers and governmental decision-makers. It will also be<b> </b>of interest to international organizations such as the World Health Organization, with which University researchers have multiple ties, more generally in helping to plan responses to major risks. </font></font></p> <p style="text-align: justify;" class="title_06"><b><font size="3">A chair based in one of the most prestigious Japanese Universities</font></b></p> <p style="text-align: justify;"><font color="#000000"><font size="3">The University of Tokyo was established in 1877 as the first national university in Japan. It is unquestionably the leading university in Japan, ranking among the very finest universities in the world. It has a well-established reputation for research excellence across a wide range of disciplines. The University’s deep and longstanding presence in the areas of medicine and health science is allied with a strong commitment to research and teaching excellence. It promotes harmonious and fruitful collaboration among scholars from different disciplines. The University of Tokyo has links to the Japanese government, international organizations, Asian governments and universities.</font></font></p> <p style="text-align: justify;"><font color="#000000"><font size="3">Nowadays, its priority is to build up its role internationally. The AXA support is therefore particularly timely: it will contribute to fulfill the wish of the University to carry out world-class research in pursuit of academic excellence and the expansion of human knowledge. It will also promote the integration of academic research across traditional boundaries and spearhead the creation of new fields of academic learning. Thanks to the new chair, the institution will carry on her strong involvement in designing and advising the government and other organizations on responses to major health issues in Japan. In the global health community, the development of health policies and health insurance coverage has become the top agenda and the assessment of risks and the way to finance the interventions to tackle them will become a central theme of many comparative health system analyses across countries.</font></font></p> <p style="text-align: justify;" class="title_06"><font size="3">&nbsp;</font><b><font size="3">A chair held by a world-class scientist</font></b></p> <p style="text-align: justify;"><font color="#000000"><font size="3">The newly appointed Chair holder is Professor Manami Inoue. After graduating from School of Medicine, University of Tsukuba, and obtaining doctorate of PhD at Nagoya University, Japan, she has pursued her training in the Harvard School of Public Health. She has developed a strong expertise on crucial topics directly related to ageing such as cardiovascular and cancer epidemiology. Awarded by authoritive academic societies in Japan (Japan Epidemiological Association, Japanese Cancer Association, etc.), she has worked in many prestigious institutions of Japan, gaining a deep knowledge on her country’s reality on longevity. This made her particularly suitable to become the holder of the AXA Chair, an opportunity to strengthen her role as intellectual leader in the emerging field of comparative life risk assessment.</font></font></p> <p style="text-align: justify;" class="title_06"><font size="3">&nbsp;</font><b><font size="3">A Chair acknowledged by the AXA Research Fund for its excellence</font></b></p> <p style="text-align: justify;"><font color="#000000"><font size="3">As an insurer, it is part of AXA’s corporate responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect people against their consequences. This knowledge is first produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. To this end, AXA also wishes to help academics share their discoveries to better inform public debate.</font></font></p> <p style="text-align: justify;"><font size="3" color="#000000">&nbsp;</font></p> <p style="text-align: justify;"><font color="#000000"><font size="3"><b>Mitsugi S</b><b>u</b><b>m</b><b>i</b><b>ya, </b><b>Executive Officer and C</b><b>hief Financial Officer,</b><b> </b><b>AXA Life Japan and Sponsor of this Chair</b>, commented: “<i>AXA is very proud to support the University of Tokyo in its wish to launch a new academic chair: its selection by the AXA Research Fund Scientific Board is yet another proof of the world-class Research performed in Japan. Furthermore, as an insurer, </i><i>medical, protection </i><em>and retirement </em><i>is an area of strategic importance for AXA Life</i><i> and I do hope that this Chair will lead to a better understanding of longevity factors. Indeed</i><i> protecting people against those risks is </i><i>one of the important</i><i> </i><i>missions</i><i> for an insurer, and this protection begins with basic research.</i><i> We also hope to leverage the result and expertise generated through this research to further develop prevention to the benefit of the population. </i></font></font></p> <p style="text-align: justify;"></p> <p style="text-align: justify;" class="title_01"><b><font color="#000000">About AXA Research Fund</font></b></p> <p style="text-align: justify;"><font color="#000000">Created in 2007, the AXA Research Fund provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of April 1<sup>st</sup>, 2013, Euro 99 million have been committed and the AXA RF has given its support to 367 research projects, implemented in 27 countries by researchers of 49 nationalities. In Japan and for Japanese researcher working abroad, it has so far committed a sum of Euro 1.79 million for 7 projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, the AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the supported researchers, of the funding schemes, and biographies of the Scientific Board members, are available on our website.</font></p> <p style="text-align: justify;"><a href="http://www.axa-research.org/"><font color="#800080">www.axa-research.org</font></a><font color="#000000">. </font></p> <p style="text-align: justify;" class="title_01"><font color="#000000"><b>About </b><b>The </b><b>University of Tokyo</b></font></p> <p style="text-align: justify;"><font color="#000000">The University of Tokyo, also known as "Todai" was established in 1877 as the first national university in Japan. As a leading research university, Todai offers courses in essentially all academic disciplines at both undergraduate and graduate levels and conducts research across the full spectrum of academic activity. The Faculty of Medicine and the Graduate School of Medicine have their roots in an inoculation facility established in 1858 and are the oldest medical schools in Japan. They both carry out education and research in basic and clinical medicine and integrated health sciences. Each year, the School of Medicine and School of Integrated Health Sciences admit approximately 100 and 40 new undergraduate students respectively, while the Graduate School accepts a total of 150 to 200 students on master’s and doctoral programs. The Faculty and the Graduate School will continue to contribute to society through the achievement of outstanding and advanced research outcomes in a variety of fields in medical sciences, ranging from elucidation of disease mechanisms, development of new treatment of diseases, elaboration of social medicine, health sciences and nursing sciences. </font></p> <p><a href="http://www.u-tokyo.ac.jp/en/about/index.html"><font face="Times New Roman" color="#0000ff">http://www.u-tokyo.ac.jp/en/about/index.html</font></a><font color="#000000">, </font><a href="http://www.m.u-tokyo.ac.jp/english/index.html"><font face="Times New Roman" color="#0000ff">http://www.m.u-tokyo.ac.jp/english/index.html</font></a><font color="#000000"> </font></p> <p class="title_01"><b><u><font color="#000000">About AXA Life</font></u></b></p> <p style="text-align: justify;"><font color="#000000">AXA Life is the Japanese arm of the AXA Group established in 1994. AXA Life serves 2 million customers &amp; 2,500 corporate clients, offering a wide range of products, including death protection, medical/cancer protection, annuities, and asset accumulation, through multi channels by utilizing the global expertise and experience of the AXA Group. In fiscal 2011, the company supported customers by paying 251.0 billion yen in claims and in annuity and maturity payouts. Further details are on the Website; </font><u><font color="#0000ff">&nbsp;</font></u><a href="http://www.axa.co.jp/"><font face="Times New Roman" color="#0000ff">http://www.axa.co.jp/life</font></a></p> <p class="title_01"><b><u><font color="#000000">About AXA Group</font></u></b></p> <p style="text-align: justify;"><font color="#000000">The AXA Group is a worldwide leader in insurance and asset management, with more than 160,000 employees serving 102 million clients in 57 countries. In 2012, IFRS revenues amounted to Euro 90.1 billion and IFRS underlying earnings to Euro 4.3 billion. AXA had Euro 1,116 billion in assets under management as of December 31, 2012. The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISN FR 0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depository Share is also quoted on the OTC QX platform under the ticker symbol AXAHY. The AXA Group is included in the main international SRI indexes, such as Dow Jones Sustainability Index (DJSI) and FTSE4GOOD. It is a founding member of the UN Environment Programme’s Finance Initiative (UNEP FI) Principles for Sustainable Insurance and a signatory of the UN Principles for Responsible Investment. Further details are on the website: </font><a href="http://www.axa.com/"><font face="Times New Roman" color="#0000ff">www.axa.com</font></a></p> <p><b><font color="#000000"><span class="title_01">Media Relations Contacts&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</span>&nbsp;&nbsp; </font></b></p> <p><u><font color="#000000">AXA Research Fund Media Relations in Paris </font></u></p> <p><font color="#000000">Guillaume Saintagne - +33 1 40 75 58 73 - </font><a href="mailto:guillaume.saintagne@axa.com"><font face="Times New Roman" color="#0000ff">guillaume.saintagne@axa.com</font></a><font color="#000000"> </font></p> <p><font color="#000000">&nbsp;</font></p> <p>Graduate School of Medicine and Faculty of Medicine, the University of Tokyo - General Affairs Office</p> <p>Tel: 03-5841-3304 <u>ishomu@m.u-tokyo.ac.jp</u></p> <p><u><font color="#000000">&nbsp;</font></u></p> <p><u><font color="#000000">AXA Life Japan Media Relations in Tokyo</font></u></p> <p><font color="#000000">Communication, Phone: 03-6737-7140 Fax: 03-6737-5964<br /><br /></font></p> <p><u><font color="#000000">&nbsp;</font></u></p> <p><u><font color="#000000">AXA Group Media Relations in Paris</font></u></p> <p><font color="#000000">Hélène Caillet - +33 1 40 75 55 51 - </font><a href="mailto:helene.caillet@axa.com"><font face="Times New Roman" color="#0000ff">helene.caillet@axa.com</font></a><font color="#000000"> </font></p> <p><font color="#000000">Guillaume Borie - +33 1 40 75 49 98 - </font><a href="mailto:guillaume.borie@axa.com"><font face="Times New Roman" color="#0000ff">guillaume.borie@axa.com</font></a><font color="#000000"> </font></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/212ib_b_amb_garden_gi_tx300_1.jpg" alt="" title="" class="imagecache imagecache-contentimage" />  Risk factor trends for Japanese

How has Japan achieved the longest life expectancy at birth in the world? Ranked first in terms of life expectancy at birth for women since 1986, recording the highest ever worldwide figure of 86 years in 2008, Japan seems to hold the secret of longevity. Understanding what factors have contributed to making the Japanese population healthy is important for global health policy, particularly for countries struggling to improve public health.

That’s why Prof Inoue, together with Nayu Ikeda, Project Lecturer, intends to get a firm grasp on the interplay of selected risk factors in the burden of disease and injury over in the past few decades in Japan. In that perspective, Prof Inoue will study the distributions of risks across population subgroups based on age, sex, geography and socio-economic status, with a particular focus on ageing. She will also lead an analysis of risk factor trends, which is important for multiple reasons. First, for some risks that have a long lag-time of accumulated hazard between exposure and health outcomes (e.g. smoking), risk factor trends offer a better illustration of accumulated hazard than current prevalence. Secondly, risk factor trends can be used to assess the role of social, policy, and technological determinants of exposure. Thirdly, comparative assessment of trends in multiple risk factors would allow for a health policies ranking.

Identify the most cost-effective health policies

Consequently, the comparison of simultaneous trends in multiple risk factors and the focus on the disparities in mortality rates will empirically contribute to understand how socioeconomic and technological changes, as well as public health policy, have affected risk factor and disease patterns. Furthermore, the comparison of cost-efficiency of each of these factors (clinical, public health, and social measures in mitigating the effects) will help identify which type of risk can be reduced relatively easily, at low cost, and which cannot.

Results will therefore be helpful to inform the allocation of available resources and could lead to policy recommendations, providing inputs to programs that aim to prevent disease and injury. Once the most cost-effective interventions are identified, it will be easier to illustrate how decision makers can begin the policy debate on priorities with information about which interventions would yield the greatest possible improvements in population health. The results of this research project will thus be relevant for doctors, public health professionals, insurers and governmental decision-makers. It will also be of interest to international organizations such as the World Health Organization, with which University researchers have multiple ties, more generally in helping to plan responses to major risks.

A chair based in one of the most prestigious Japanese Universities

The University of Tokyo was established in 1877 as the first national university in Japan. It is unquestionably the leading university in Japan, ranking among the very finest universities in the world. It has a well-established reputation for research excellence across a wide range of disciplines. The University’s deep and longstanding presence in the areas of medicine and health science is allied with a strong commitment to research and teaching excellence. It promotes harmonious and fruitful collaboration among scholars from different disciplines. The University of Tokyo has links to the Japanese government, international organizations, Asian governments and universities.

Nowadays, its priority is to build up its role internationally. The AXA support is therefore particularly timely: it will contribute to fulfill the wish of the University to carry out world-class research in pursuit of academic excellence and the expansion of human knowledge. It will also promote the integration of academic research across traditional boundaries and spearhead the creation of new fields of academic learning. Thanks to the new chair, the institution will carry on her strong involvement in designing and advising the government and other organizations on responses to major health issues in Japan. In the global health community, the development of health policies and health insurance coverage has become the top agenda and the assessment of risks and the way to finance the interventions to tackle them will become a central theme of many comparative health system analyses across countries.

 A chair held by a world-class scientist

The newly appointed Chair holder is Professor Manami Inoue. After graduating from School of Medicine, University of Tsukuba, and obtaining doctorate of PhD at Nagoya University, Japan, she has pursued her training in the Harvard School of Public Health. She has developed a strong expertise on crucial topics directly related to ageing such as cardiovascular and cancer epidemiology. Awarded by authoritive academic societies in Japan (Japan Epidemiological Association, Japanese Cancer Association, etc.), she has worked in many prestigious institutions of Japan, gaining a deep knowledge on her country’s reality on longevity. This made her particularly suitable to become the holder of the AXA Chair, an opportunity to strengthen her role as intellectual leader in the emerging field of comparative life risk assessment.

 A Chair acknowledged by the AXA Research Fund for its excellence

As an insurer, it is part of AXA’s corporate responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect people against their consequences. This knowledge is first produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. To this end, AXA also wishes to help academics share their discoveries to better inform public debate.

 

Mitsugi Sumiya, Executive Officer and Chief Financial Officer, AXA Life Japan and Sponsor of this Chair, commented: “AXA is very proud to support the University of Tokyo in its wish to launch a new academic chair: its selection by the AXA Research Fund Scientific Board is yet another proof of the world-class Research performed in Japan. Furthermore, as an insurer, medical, protection and retirement is an area of strategic importance for AXA Life and I do hope that this Chair will lead to a better understanding of longevity factors. Indeed protecting people against those risks is one of the important missions for an insurer, and this protection begins with basic research. We also hope to leverage the result and expertise generated through this research to further develop prevention to the benefit of the population.

About AXA Research Fund

Created in 2007, the AXA Research Fund provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of April 1st, 2013, Euro 99 million have been committed and the AXA RF has given its support to 367 research projects, implemented in 27 countries by researchers of 49 nationalities. In Japan and for Japanese researcher working abroad, it has so far committed a sum of Euro 1.79 million for 7 projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, the AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the supported researchers, of the funding schemes, and biographies of the Scientific Board members, are available on our website.

www.axa-research.org.

About The University of Tokyo

The University of Tokyo, also known as "Todai" was established in 1877 as the first national university in Japan. As a leading research university, Todai offers courses in essentially all academic disciplines at both undergraduate and graduate levels and conducts research across the full spectrum of academic activity. The Faculty of Medicine and the Graduate School of Medicine have their roots in an inoculation facility established in 1858 and are the oldest medical schools in Japan. They both carry out education and research in basic and clinical medicine and integrated health sciences. Each year, the School of Medicine and School of Integrated Health Sciences admit approximately 100 and 40 new undergraduate students respectively, while the Graduate School accepts a total of 150 to 200 students on master’s and doctoral programs. The Faculty and the Graduate School will continue to contribute to society through the achievement of outstanding and advanced research outcomes in a variety of fields in medical sciences, ranging from elucidation of disease mechanisms, development of new treatment of diseases, elaboration of social medicine, health sciences and nursing sciences.

http://www.u-tokyo.ac.jp/en/about/index.html, http://www.m.u-tokyo.ac.jp/english/index.html 

About AXA Life

AXA Life is the Japanese arm of the AXA Group established in 1994. AXA Life serves 2 million customers & 2,500 corporate clients, offering a wide range of products, including death protection, medical/cancer protection, annuities, and asset accumulation, through multi channels by utilizing the global expertise and experience of the AXA Group. In fiscal 2011, the company supported customers by paying 251.0 billion yen in claims and in annuity and maturity payouts. Further details are on the Website;  http://www.axa.co.jp/life

About AXA Group

The AXA Group is a worldwide leader in insurance and asset management, with more than 160,000 employees serving 102 million clients in 57 countries. In 2012, IFRS revenues amounted to Euro 90.1 billion and IFRS underlying earnings to Euro 4.3 billion. AXA had Euro 1,116 billion in assets under management as of December 31, 2012. The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISN FR 0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depository Share is also quoted on the OTC QX platform under the ticker symbol AXAHY. The AXA Group is included in the main international SRI indexes, such as Dow Jones Sustainability Index (DJSI) and FTSE4GOOD. It is a founding member of the UN Environment Programme’s Finance Initiative (UNEP FI) Principles for Sustainable Insurance and a signatory of the UN Principles for Responsible Investment. Further details are on the website: www.axa.com

Media Relations Contacts       

AXA Research Fund Media Relations in Paris

Guillaume Saintagne - +33 1 40 75 58 73 - guillaume.saintagne@axa.com

 

Graduate School of Medicine and Faculty of Medicine, the University of Tokyo - General Affairs Office

Tel: 03-5841-3304 ishomu@m.u-tokyo.ac.jp

 

AXA Life Japan Media Relations in Tokyo

Communication, Phone: 03-6737-7140 Fax: 03-6737-5964

 

AXA Group Media Relations in Paris

Hélène Caillet - +33 1 40 75 55 51 - helene.caillet@axa.com

Guillaume Borie - +33 1 40 75 49 98 - guillaume.borie@axa.com

]]>
3856 /launch-of-the-axa-university-of-strasbourg-chair-in-supramolecular-chemistry 2013-01-31T00:00:00 Launch of the AXA-University of Strasbourg Chair in Supramolecular Chemistry <p><span class="title_06">An experimental science to better understand age-related diseases</span></p> <p style="text-align: justify;">Supramolecular chemistry might seem mysterious but in fact it is one of today’s most sophisticated sciences. Spanning the fields of biology and medical sciences, it has radically transformed how chemists grasp the world and approach their subject. Indeed, as the discipline made its way into laboratories, scientists no longer saw matter as composed of separate atoms but as entire molecules interacting with each other, by way of specific active sites. Although supramolecular chemistry is an experimental science, the AXA Research Fund has chosen to fund this Chair as the rewards it can deliver to society are huge. It has indeed proven to be a fundamental gateway to providing new therapeutic solutions to important health concerns. Numerous new molecules are designed and synthetized, then tested for potential activities on targets such as cancer, Alzheimer’s, HIV, autoimmune diseases, orphan diseases, allergies and obesity. Thus, the scope of this Chair will naturally contribute to the development of the understanding of age-related pathologies.</p> <p><span class="title_06">A Chair based in one of the world most prestigious chemistry centers</span></p> <p style="text-align: justify;">Universally recognized as one of the world’s top centers for chemistry, the University of Strasbourg has produced a number of leading scientists who have shaped the progress of chemical sciences. This is true of researchers in the distant past like Pasteur, von Baeyer and Fischer, and also of researchers in the present such as Jean-Pierre Sauvage and Nobel Prize laureate Jean-Marie Lehn who have both founded whole new fields of chemistry. In recognition of this unique position in France, the French Government selected Strasbourg as the center of excellence in chemistry for the country. The International Center for Frontier Research in Chemistry (FRC) was then established in 2007 to enable the University of Strasbourg to further strengthen its position to face global competition from highly ranked institutes in such countries as the US, the Netherlands, Japan and the UK.</p> <p><span class="title_06">A Chair held by a world-class woman scientist in the field of chemistry</span></p> <p style="text-align: justify;">Thanks to the AXA Research Fund’s support, the University of Strasbourg and the FRC wish to build on the pioneering work of Professor Lehn to expand into new areas of supramolecular chemistry by attracting Professor Luisa De Cola, a top world class researcher in the field. Professor De Cola has had an international career, studying in Italy and the USA and has held several professorships, in Switzerland, the Netherlands, and Germany. In 2011 she was the recipient of the Distinguished Women in Chemistry Award. Her presence will ensure that Strasbourg continues to be a center of excellence and will help the University to lead the way in the coming decades. Since transferring knowledge to society is an important mission of scientists today, she will ensure that society benefits from the advances acquired by her team, and thus help in the progress to overcome age-related diseases and significantly contribute to long-term care and well-being in our ever longer-lived society.</p> <p><span class="title_06">A Chair acknowledged by the AXA Research Fund for its excellence</span></p> <p><iframe height="315" src="http://www.youtube.com/embed/Pi5A0GoYNmk?list=PLbLfQYSzQ-h3oYbEG59wTMH8WuPX9Bs_T" frameborder="0" width="560" allowfullscreen=""></iframe></p> <p style="text-align: justify;"><em>Filming by UTV for Fondation Unistra</em></p> <p style="text-align: justify;">&nbsp;As an insurer, it is part of AXA’s corporate responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect people against their consequences. This knowledge is first produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. To this end, AXA also wishes to help academics share their discoveries to better inform public debate. Véronique Weill, AXA Group Chief Operating Officer, Management Board Member of the AXA Group, and Sponsor of this Chair, commented: “AXA is very proud to support the University of Strasbourg in its wish to launch a new academic chair: its selection by the AXA Research Fund Scientific Board is yet another proof of the world-class Research performed in France. Furthermore, as an insurer, I do hope that this Chair will lead to a better understanding of age related pathologies. Indeed protecting people against longevity risks is a major concern for an insurer, and this protection begins with basic research. ”</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/strasbourg.gif" alt="" title="" class="imagecache imagecache-contentimage" /> An experimental science to better understand age-related diseases

Supramolecular chemistry might seem mysterious but in fact it is one of today’s most sophisticated sciences. Spanning the fields of biology and medical sciences, it has radically transformed how chemists grasp the world and approach their subject. Indeed, as the discipline made its way into laboratories, scientists no longer saw matter as composed of separate atoms but as entire molecules interacting with each other, by way of specific active sites. Although supramolecular chemistry is an experimental science, the AXA Research Fund has chosen to fund this Chair as the rewards it can deliver to society are huge. It has indeed proven to be a fundamental gateway to providing new therapeutic solutions to important health concerns. Numerous new molecules are designed and synthetized, then tested for potential activities on targets such as cancer, Alzheimer’s, HIV, autoimmune diseases, orphan diseases, allergies and obesity. Thus, the scope of this Chair will naturally contribute to the development of the understanding of age-related pathologies.

A Chair based in one of the world most prestigious chemistry centers

Universally recognized as one of the world’s top centers for chemistry, the University of Strasbourg has produced a number of leading scientists who have shaped the progress of chemical sciences. This is true of researchers in the distant past like Pasteur, von Baeyer and Fischer, and also of researchers in the present such as Jean-Pierre Sauvage and Nobel Prize laureate Jean-Marie Lehn who have both founded whole new fields of chemistry. In recognition of this unique position in France, the French Government selected Strasbourg as the center of excellence in chemistry for the country. The International Center for Frontier Research in Chemistry (FRC) was then established in 2007 to enable the University of Strasbourg to further strengthen its position to face global competition from highly ranked institutes in such countries as the US, the Netherlands, Japan and the UK.

A Chair held by a world-class woman scientist in the field of chemistry

Thanks to the AXA Research Fund’s support, the University of Strasbourg and the FRC wish to build on the pioneering work of Professor Lehn to expand into new areas of supramolecular chemistry by attracting Professor Luisa De Cola, a top world class researcher in the field. Professor De Cola has had an international career, studying in Italy and the USA and has held several professorships, in Switzerland, the Netherlands, and Germany. In 2011 she was the recipient of the Distinguished Women in Chemistry Award. Her presence will ensure that Strasbourg continues to be a center of excellence and will help the University to lead the way in the coming decades. Since transferring knowledge to society is an important mission of scientists today, she will ensure that society benefits from the advances acquired by her team, and thus help in the progress to overcome age-related diseases and significantly contribute to long-term care and well-being in our ever longer-lived society.

A Chair acknowledged by the AXA Research Fund for its excellence

Filming by UTV for Fondation Unistra

 As an insurer, it is part of AXA’s corporate responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect people against their consequences. This knowledge is first produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. To this end, AXA also wishes to help academics share their discoveries to better inform public debate. Véronique Weill, AXA Group Chief Operating Officer, Management Board Member of the AXA Group, and Sponsor of this Chair, commented: “AXA is very proud to support the University of Strasbourg in its wish to launch a new academic chair: its selection by the AXA Research Fund Scientific Board is yet another proof of the world-class Research performed in France. Furthermore, as an insurer, I do hope that this Chair will lead to a better understanding of age related pathologies. Indeed protecting people against longevity risks is a major concern for an insurer, and this protection begins with basic research. ”

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3616 /launch-of-the-axa-sciences-po-chair-of-economic-sociology-0 2012-12-04T00:00:00 Launch of the AXA – Sciences Po Chair of Economic Sociology <p>Over the last 40 years, economic inequalities have soared in Western countries. The rich have become richer. The living standards of everyone else have stagnated or regressed. This shift has, importantly, coincided with a credit boom of epic proportions, fueled by the deregulation of financial markets. Corporations, states and households were allowed to accumulate debt at previously unseen levels, and under increasingly unfavorable terms. When their ability to repay recently faltered, many individuals, institutions and countries were suddenly not creditworthy anymore. People were forced into bankruptcy or foreclosure. States were forced into austerity. Often, both were held responsible for their woes. </p><p><strong>The AXA – Sciences Po Chair will study the implications of these transformations in terms of inequality and solidarity. The AXA – Sciences Po newly appointed Chair Holder, Professor Marion Fourcade, will investigate the social dislocations, political crises, and moral battles that multiply as people face new market risks with less social protections.</strong> She will focus on marginal populations, such as the poor, immigrants, ethnic or racial minorities, who are especially vulnerable to these processes. Her research will shed a light on the drivers of inequality and contribute to rethink the role of markets in modern society. </p><p class="title_01 title_06">A Chair within a Franco-German Research Center </p><p>Through its connection with the Max Planck Sciences Po Center, the AXA Chair is thus centrally located to contribute to our understanding of the new terms of the political debate, as well as the possibly post-neoliberal frameworks that will emerge to rethink the role of markets in modern society.MaxPo researchers will investigate the impact of increasing liberalization, technological advances, and cultural change on industrialized Western societies. Sociologist Prof Marion Fourcade and political scientist Cornelia Woll are the heads of the center. Along with a small group of internationally recruited junior researchers, they will examine the profound transformation of the industrialized world and analyze how individuals, families, organizations, and societal subsystems are coping with increasing instability. </p><p>The AXA Chair will enable Sciences Po to offer a full professorship to Marion Fourcade, and thus get enriched with the expertise and network she collected after almost twenty years in US academia. After completing her studies in Sociology and Economics at the University of Paris, the Ecole des Hautes Etudes en Sciences Sociales and the Ecole Normale Supérieure, Paris, Prof Marion Fourcade received her doctorate in Sociology at Harvard University in 2000. She has been teaching at the University of California at Berkeley since 2003. She becomes now research leader at MaxPo in Paris. In past research, Marion Fourcade has studied how culture and institutions shape actors’ self-perceptions, dispositions and actions in domains ranging from professions to political mobilization to relations with the natural environment. </p><p class="title_06">A Chair acknowledged by the AXA Research Fund for its excellence </p><p>As an insurer, it is part of AXA’s responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect its customers against their consequences. This knowledge is firstly produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. In this perspective, AXA also wish to help academics share their discoveries to better inform public debate. </p><p>Cyrille de Montgolfier, AXA Group Senior Vice President of European and Public Affairs, commented: “<em>I’m proud to underline the audacious and ambitious research strategy of Sciences Po. Indeed all the AXA Research Fund Chairs have been selected because of their academic excellence acknowledged by peers on an international competition basis and I believe that this is a label of excellence. Secondly, as an insurer, protecting people, notably unprivileged populations, is a major concern for AXA, and I do hope that supporting this research will help us better understand the reality of risks they face. And at last, as an expert of European Affairs within a worldwide Group, I’m happy to see this label awarded within a Franco- German center, proving once again that good science has no boundaries</em>.”</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/sciencespo.png" alt="" title="" class="imagecache imagecache-contentimage" /> Over the last 40 years, economic inequalities have soared in Western countries. The rich have become richer. The living standards of everyone else have stagnated or regressed. This shift has, importantly, coincided with a credit boom of epic proportions, fueled by the deregulation of financial markets. Corporations, states and households were allowed to accumulate debt at previously unseen levels, and under increasingly unfavorable terms. When their ability to repay recently faltered, many individuals, institutions and countries were suddenly not creditworthy anymore. People were forced into bankruptcy or foreclosure. States were forced into austerity. Often, both were held responsible for their woes.

The AXA – Sciences Po Chair will study the implications of these transformations in terms of inequality and solidarity. The AXA – Sciences Po newly appointed Chair Holder, Professor Marion Fourcade, will investigate the social dislocations, political crises, and moral battles that multiply as people face new market risks with less social protections. She will focus on marginal populations, such as the poor, immigrants, ethnic or racial minorities, who are especially vulnerable to these processes. Her research will shed a light on the drivers of inequality and contribute to rethink the role of markets in modern society.

A Chair within a Franco-German Research Center

Through its connection with the Max Planck Sciences Po Center, the AXA Chair is thus centrally located to contribute to our understanding of the new terms of the political debate, as well as the possibly post-neoliberal frameworks that will emerge to rethink the role of markets in modern society.MaxPo researchers will investigate the impact of increasing liberalization, technological advances, and cultural change on industrialized Western societies. Sociologist Prof Marion Fourcade and political scientist Cornelia Woll are the heads of the center. Along with a small group of internationally recruited junior researchers, they will examine the profound transformation of the industrialized world and analyze how individuals, families, organizations, and societal subsystems are coping with increasing instability.

The AXA Chair will enable Sciences Po to offer a full professorship to Marion Fourcade, and thus get enriched with the expertise and network she collected after almost twenty years in US academia. After completing her studies in Sociology and Economics at the University of Paris, the Ecole des Hautes Etudes en Sciences Sociales and the Ecole Normale Supérieure, Paris, Prof Marion Fourcade received her doctorate in Sociology at Harvard University in 2000. She has been teaching at the University of California at Berkeley since 2003. She becomes now research leader at MaxPo in Paris. In past research, Marion Fourcade has studied how culture and institutions shape actors’ self-perceptions, dispositions and actions in domains ranging from professions to political mobilization to relations with the natural environment.

A Chair acknowledged by the AXA Research Fund for its excellence

As an insurer, it is part of AXA’s responsibility to build knowledge on risks to better prevent them and, if they occur, to better protect its customers against their consequences. This knowledge is firstly produced by AXA experts using field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. In this perspective, AXA also wish to help academics share their discoveries to better inform public debate.

Cyrille de Montgolfier, AXA Group Senior Vice President of European and Public Affairs, commented: “I’m proud to underline the audacious and ambitious research strategy of Sciences Po. Indeed all the AXA Research Fund Chairs have been selected because of their academic excellence acknowledged by peers on an international competition basis and I believe that this is a label of excellence. Secondly, as an insurer, protecting people, notably unprivileged populations, is a major concern for AXA, and I do hope that supporting this research will help us better understand the reality of risks they face. And at last, as an expert of European Affairs within a worldwide Group, I’m happy to see this label awarded within a Franco- German center, proving once again that good science has no boundaries.”

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3484 /book-of-knowledge-socioeconomic-risks 2012-11-30T00:00:00 Book of Knowledge - Socioeconomic Risks <p><span style="text-decoration: underline;"><strong>Foreword by Eric Chaney, Chief Economist AXA Group, AXA Investment Managers SA</strong></span><br /><br />If I were cynical, I would say that the global debt/credit crisis that erupted in the US in 2007 and is now wreaking havoc in Europe is a boon for researchers. Crises of this magnitude do not happen that often, fortunately. Not only do they raise new challenging questions for professional economists, from academia as well as from business, but they also bring in an enormous amount of new data, from real economies as well as from the financial markets. </p><p>[…] I think the debt crisis is likely to shift the mainstream views among economists into directions that are too early to predict. There are nevertheless some interesting hints coming from ongoing research.</p><p>[…] Now, the question is: how can we best work with fundamental science to challenge our models and renew our knowledge? Of course, we do work in practice with Academic Centers, exchanging interns, PhD students, post-docs, academics on sabbatical, listening to each other in conferences and seminars, and of course recruiting employees from the best research universities or having our workforce trained by the best specialists. But this relationship focuses on our immediate needs and the continuous improvement of our models. It originates in our structure more than in the scientific world. However, in some cases – such as the present situation – solutions can only be reached through a common deep understanding of the crisis mechanism, its origins, and the way out of it. This is why AXA chose to complement its expertise with a bold endeavor to finance fundamental research from a philanthropic stance. We help the best scientists not only to focus on the risks the economic world faces today – by giving them the financial means to do so – but also to be more present in public debates on those matters. We totally respect their autonomy, which is the source of their value in such debates. As member of the Scientific Board of the AXA Research Fund, I help focus on the applications with the best potential for scientific breakthroughs, and for a redefinition of the common knowledge about risks. And then I try and listen to them!</p><p>&nbsp;<a target="_blank" href="http://asp-indus.secure-zone.net/v2/index.jsp?id=1281/1675/3097&amp;lng=en" title="Leaf through it !"><img src="http://www.axa-research.org/sites/dev/files/u/image/Couv%20BOK%20SE.jpg" style="vertical-align: middle; margin-left: 170px; margin-right: 170px;" /></a></p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/couv_bok_se.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Foreword by Eric Chaney, Chief Economist AXA Group, AXA Investment Managers SA

If I were cynical, I would say that the global debt/credit crisis that erupted in the US in 2007 and is now wreaking havoc in Europe is a boon for researchers. Crises of this magnitude do not happen that often, fortunately. Not only do they raise new challenging questions for professional economists, from academia as well as from business, but they also bring in an enormous amount of new data, from real economies as well as from the financial markets.

[…] I think the debt crisis is likely to shift the mainstream views among economists into directions that are too early to predict. There are nevertheless some interesting hints coming from ongoing research.

[…] Now, the question is: how can we best work with fundamental science to challenge our models and renew our knowledge? Of course, we do work in practice with Academic Centers, exchanging interns, PhD students, post-docs, academics on sabbatical, listening to each other in conferences and seminars, and of course recruiting employees from the best research universities or having our workforce trained by the best specialists. But this relationship focuses on our immediate needs and the continuous improvement of our models. It originates in our structure more than in the scientific world. However, in some cases – such as the present situation – solutions can only be reached through a common deep understanding of the crisis mechanism, its origins, and the way out of it. This is why AXA chose to complement its expertise with a bold endeavor to finance fundamental research from a philanthropic stance. We help the best scientists not only to focus on the risks the economic world faces today – by giving them the financial means to do so – but also to be more present in public debates on those matters. We totally respect their autonomy, which is the source of their value in such debates. As member of the Scientific Board of the AXA Research Fund, I help focus on the applications with the best potential for scientific breakthroughs, and for a redefinition of the common knowledge about risks. And then I try and listen to them!

 

 

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3485 /book-of-knowledge-environmental-risks 2012-11-30T00:00:00 Book of Knowledge - Environmental Risks <p><br /><span style="text-decoration: underline;"><strong>Foreword by Jean-Christophe Ménioux, Chief Risk Officer, AXA Group Risk Management </strong></span><br /><br />Prevention is at the heart of insurance due to the role of insurance companies in society as people protectors, and because the best risk for the company is the risk our clients avoid. In this regard, environmental risks are no exception. </p> <p>[…] The economic losses associated with natural disasters are following an increasing trend—they nearly tripled from the 1980s to the 2000s. The burden on insurers also is growing. Although this increase in losses is primarily due to a growth in economic exposure, we, as insurers, are more and more concerned about prevention in order to continue to play our role as people protectors vis-a-vis our clients.</p> <p>[…]Prevention goes hand in hand with knowledge. In my opinion, the role of a global insurer such as AXA, today, is no longer limited to paying for damage. Part of its core mission is to develop understanding and knowledge about risks and, through this enhanced expertise, to support our clients, people and industries in becoming better prepared for evolving potential threats. However, environmental risks are very complex in nature, and the evolution of such risks is extremely difficult to predict. […]This is especially true since new effects, such as global warming, are coming into play, which may have a material impact in the future. The past may be less and less a reliable predictive indicator for the future, as new emerging risks are likely to step in. Thus, constant progress and update of knowledge are essential to insurers’ risk management and solvency in the long term. </p> <p>This is where the AXA Research Fund comes into play. By supporting academic research, it contributes to a deeper understanding of environmental risks, aiming to better assess of all their dimensions. […]The topics supported by the AXA Research Fund are extremely relevant for today’s insurance challenges and give interesting perspectives on likely risk evolutions.</p> <p><a target="_blank" href="http://asp-indus.secure-zone.net/v2/index.jsp?id=1281/1675/3263&amp;lng=fr" title="Leaf through it!"><img src="http://www.axa-research.org/sites/dev/files/u/image/Couv%20BOK%20ENV.jpg" style="margin-left: 170px; margin-right: 170px;" /></a></p> <p>&nbsp;</p> <script type="text/javascript"></script> <script type="text/javascript">// <![CDATA[ launchMini("1281/1675/3097", "true", "0x002e6e", "330", "243", "en"); // ]]></script><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/couv_bok_env.jpg" alt="" title="" class="imagecache imagecache-contentimage" />
Foreword by Jean-Christophe Ménioux, Chief Risk Officer, AXA Group Risk Management

Prevention is at the heart of insurance due to the role of insurance companies in society as people protectors, and because the best risk for the company is the risk our clients avoid. In this regard, environmental risks are no exception.

[…] The economic losses associated with natural disasters are following an increasing trend—they nearly tripled from the 1980s to the 2000s. The burden on insurers also is growing. Although this increase in losses is primarily due to a growth in economic exposure, we, as insurers, are more and more concerned about prevention in order to continue to play our role as people protectors vis-a-vis our clients.

[…]Prevention goes hand in hand with knowledge. In my opinion, the role of a global insurer such as AXA, today, is no longer limited to paying for damage. Part of its core mission is to develop understanding and knowledge about risks and, through this enhanced expertise, to support our clients, people and industries in becoming better prepared for evolving potential threats. However, environmental risks are very complex in nature, and the evolution of such risks is extremely difficult to predict. […]This is especially true since new effects, such as global warming, are coming into play, which may have a material impact in the future. The past may be less and less a reliable predictive indicator for the future, as new emerging risks are likely to step in. Thus, constant progress and update of knowledge are essential to insurers’ risk management and solvency in the long term.

This is where the AXA Research Fund comes into play. By supporting academic research, it contributes to a deeper understanding of environmental risks, aiming to better assess of all their dimensions. […]The topics supported by the AXA Research Fund are extremely relevant for today’s insurance challenges and give interesting perspectives on likely risk evolutions.

 

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2998 /launch-of-the-axa-bocconi-chair-in-risk 2012-06-12T00:00:00 Launch of the AXA – Bocconi Chair in Risk <p>Uncertainty reigns nowadays. Financiers have a hard time trying to ensure effective risk management and portfolio allocations. The picture is not softened by a context of financial crisis. Until recently, probability lenses were used to look at the world and describe reality. But, alas, this suitable approach for gambling does not seem to apply to the current economic events.</p> <p>The advancement and diffusion of modeling techniques to capture and manage the new and different categories of risks in the social sciences will be at the core of the activity of the new AXA-Bocconi Chair in Risk. This dedicated and permanent chair has been established thanks to a donation of the AXA Research Fund to Università Bocconi of an endowment of 2 million euro. The chair has been assigned to Pr Massimo Marinacci in recognition of his research work in the field of Decision theory.</p> <p><em>“The partnership with AXA Research Fund represents a very significant step in our strategy of internationalization of our teaching and research and fits into the frame of our fundraising activity in support of the Strategic Plan for the development of our university,” says Guido Tabellini, rector of Università Bocconi. “Thanks to the financing of the Chair in Risk and the activity of prof. Marinacci, Bocconi will pursue a field of study at the frontier of research and of a very significant impact.”</em></p> <p>Decision theory is an area of economics at the intersection between psychology and statistics that studies economic choices under uncertainty.<em> “We don’t provide solution nor percentages,”</em> Pr Marinacci explains, <em>we formalize models that clarify what alternatives decision makers face and how they should handle them. Then it’s up to them to choose.”</em> Some of these models have been used in a variety of applications, from environmental issues (where they have been used to formalize the often mentioned, but conceptually elusive, precautionary principle) to finance and insurance applications (where they can help explain the trading choices of financial intermediaries in these days of high uncertainty, otherwise hard to explain with traditional risk theories), to risk management in financial institutions and central banks.</p> <p>Thanks to an international career and a solid background in economics and applied mathematics, Pr Marinacci is one of the leaders in decision theory. Along with Pr Itzhak Gilboa (AXA Chair at HEC-Paris), Pr Marinacci delivered an invited lecture on these topics at the 2010 World Congress of the Econometric Society, the most prestigious meeting in economics. Pr Marinacci was also awarded one of the European Research Council’s competitive and prestigious Advanced Grants. Pr Marinacci performs his research at the Department of Decision Sciences of Università Bocconi, a private university founded in 1902 in Milan and internationally known as an excellent research and teaching institution specializing in economics, finance, management and law. The department has a distinguished tradition in decision theory, with some of the key players in the area as faculty or alumni.</p> <p>A major contribution from Pr Marinacci comes from the importance of emotions impacting individual decision making in contemporary societies. This new approach suggests a choice model which includes two attitudes toward peers’ choices: envy and pride. <em>“These social emotions are not systematically taken into account by economic theory, yet they play a key role in individual choices: when incorporated in the model analyzing individual preference, they have a direct impact on decision making. Is envy the prevailing attitude? Social equilibrium will dwell on conformism and workaholism. Or is it pride? Anticonformism and diversification of consumption will arise instead. This model applies not only at an individual level, but on a larger scale: societies in which pride prevails present high diversity in consumption and income, whereas conformism in consumption choices is the rule in societies characterized by envy”</em>, declared Pr Marinacci.</p> <p>Andrea Rossi, CEO of AXA Assicurazioni and sponsor of the chair, commented: <em>“uncertainty has become the real protagonist of our times: it has hit heavily the world we live in, generating a hunger for answers to the doubts the society is plagued by. We need effective and influential solutions that might help us interpret and understand what is happening, anticipating what we are moving towards. The private sector should play a key role in encouraging progress in this field, promoting research as an investment for the future, coherently with corporate responsibility efforts. Researching on risk and trying to understand those phenomena that feature our dynamic and complex world is part of the challenge of a major Group like AXA. Understanding and managing risks goes beyond business, it is a social duty for an insurance Group to finance top level research on global risks. We believe in knowledge as the starting point to make a good job: studying long term risks means knowing them to be in the position of managing them, protecting people at any stage and situation of their life”</em>.</p> <p><span class="title_06">About Prof Massimo Marinacci, Chair holder</span></p> <p>Since he started his career in 1996 as assistant professor of Economics at the University of Toronto (Canada), Professor Marinacci has published 48 articles in peer reviewed international journals, including leading journals in Economics (<em>such as Econometrica, Review of Economic Studies, Games and Economic Behavior, Journal of Economic Theory, and Theoretical Economics</em>), Quantitative Finance and Insurance (<em>Mathematical Finance and Insurance: Mathematics and Economics</em>), and Applied Mathematics (<em>Annals of Probability and Mathematics of Operations Research</em>). His papers have received many citations. He is also in the editorial board of leading international journals (<em>Games and Economic Behavior, Journal of Economic Theory, Journal of the European Economic Association, Mathematics of Operations Research, and Theoretical Economics</em>), and has given seminars in many international research institutions.</p> <p><span class="title_06">About the Università commerciale Luigi Bocconi</span></p> <p>Founded in 1902 and located at the heart of Europe and in Italy’s business and financial centre, Università Bocconi is widely recognized as the leading university in Italy for economics and management. The university’s mission is to strive in providing top-level teaching and research with a truly international outlook through a highly-qualified and dedicated faculty. Today, Bocconi is a university of international standing in business, economics and law and offers an extensive range of programs through its five schools – including undergraduate, Masters of Science, PhD and MBA. Bocconi currently has around 200 partner schools worldwide and also draws strength from its network of alumni which consists of more than 80,000 graduates around the world. <a href="http://www.unibocconi.eu" target="_blank">http://www.unibocconi.eu</a></p> <p><span class="title_06">About AXA Research Fund</span></p> <p>Created in 2008, the AXA Research Fund (AXA RF) provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of May 1st, 2012, Euro 79 million have been committed and the AXA RF has given its support to 291 research projects, implemented in 24 countries by researchers of 43 nationalities. In Italy and for Italian researchers, it has so far committed a sum of Euro 3.5 million for various projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the funding vehicles, the list of all our grantees and biographies of the Scientific Board members, are available on the website <a href="http://axa-research.org" target="_blank">www.axa-research.org</a>.</p> <p><span class="title_06">About AXA in Italy</span></p> <p>AXA is present throughout Italy in a multi-distribution perspective. AXA Assicurazioni (www.axa.it) operates throughout a network of about 700 agencies and distributes its insurance products providing ad hoc consulting service to ensure a complete protection. AXA MPS (www.axa-mps.it), the strategic partnership established in 2007 with Montepaschi banking group, distributes its insurance solutions through over 3000 branches in Italy, setting itself as a comprehensive “service company”. AXA is also present with further insurance companies, that include Quixa, a direct company of new generation, and the specialized entities AXA Art (protection of cultural heritage), AXA Corporate Solutions (large corporations and groups), AXA Assistance (assistance in different sectors), as well as AXA IM (asset management), AXA Private Equity (private equity operations) and AXA REIM (real estate investment management).</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/3883922245_ee1775d3ca_z.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Uncertainty reigns nowadays. Financiers have a hard time trying to ensure effective risk management and portfolio allocations. The picture is not softened by a context of financial crisis. Until recently, probability lenses were used to look at the world and describe reality. But, alas, this suitable approach for gambling does not seem to apply to the current economic events.

The advancement and diffusion of modeling techniques to capture and manage the new and different categories of risks in the social sciences will be at the core of the activity of the new AXA-Bocconi Chair in Risk. This dedicated and permanent chair has been established thanks to a donation of the AXA Research Fund to Università Bocconi of an endowment of 2 million euro. The chair has been assigned to Pr Massimo Marinacci in recognition of his research work in the field of Decision theory.

“The partnership with AXA Research Fund represents a very significant step in our strategy of internationalization of our teaching and research and fits into the frame of our fundraising activity in support of the Strategic Plan for the development of our university,” says Guido Tabellini, rector of Università Bocconi. “Thanks to the financing of the Chair in Risk and the activity of prof. Marinacci, Bocconi will pursue a field of study at the frontier of research and of a very significant impact.”

Decision theory is an area of economics at the intersection between psychology and statistics that studies economic choices under uncertainty. “We don’t provide solution nor percentages,” Pr Marinacci explains, we formalize models that clarify what alternatives decision makers face and how they should handle them. Then it’s up to them to choose.” Some of these models have been used in a variety of applications, from environmental issues (where they have been used to formalize the often mentioned, but conceptually elusive, precautionary principle) to finance and insurance applications (where they can help explain the trading choices of financial intermediaries in these days of high uncertainty, otherwise hard to explain with traditional risk theories), to risk management in financial institutions and central banks.

Thanks to an international career and a solid background in economics and applied mathematics, Pr Marinacci is one of the leaders in decision theory. Along with Pr Itzhak Gilboa (AXA Chair at HEC-Paris), Pr Marinacci delivered an invited lecture on these topics at the 2010 World Congress of the Econometric Society, the most prestigious meeting in economics. Pr Marinacci was also awarded one of the European Research Council’s competitive and prestigious Advanced Grants. Pr Marinacci performs his research at the Department of Decision Sciences of Università Bocconi, a private university founded in 1902 in Milan and internationally known as an excellent research and teaching institution specializing in economics, finance, management and law. The department has a distinguished tradition in decision theory, with some of the key players in the area as faculty or alumni.

A major contribution from Pr Marinacci comes from the importance of emotions impacting individual decision making in contemporary societies. This new approach suggests a choice model which includes two attitudes toward peers’ choices: envy and pride. “These social emotions are not systematically taken into account by economic theory, yet they play a key role in individual choices: when incorporated in the model analyzing individual preference, they have a direct impact on decision making. Is envy the prevailing attitude? Social equilibrium will dwell on conformism and workaholism. Or is it pride? Anticonformism and diversification of consumption will arise instead. This model applies not only at an individual level, but on a larger scale: societies in which pride prevails present high diversity in consumption and income, whereas conformism in consumption choices is the rule in societies characterized by envy”, declared Pr Marinacci.

Andrea Rossi, CEO of AXA Assicurazioni and sponsor of the chair, commented: “uncertainty has become the real protagonist of our times: it has hit heavily the world we live in, generating a hunger for answers to the doubts the society is plagued by. We need effective and influential solutions that might help us interpret and understand what is happening, anticipating what we are moving towards. The private sector should play a key role in encouraging progress in this field, promoting research as an investment for the future, coherently with corporate responsibility efforts. Researching on risk and trying to understand those phenomena that feature our dynamic and complex world is part of the challenge of a major Group like AXA. Understanding and managing risks goes beyond business, it is a social duty for an insurance Group to finance top level research on global risks. We believe in knowledge as the starting point to make a good job: studying long term risks means knowing them to be in the position of managing them, protecting people at any stage and situation of their life”.

About Prof Massimo Marinacci, Chair holder

Since he started his career in 1996 as assistant professor of Economics at the University of Toronto (Canada), Professor Marinacci has published 48 articles in peer reviewed international journals, including leading journals in Economics (such as Econometrica, Review of Economic Studies, Games and Economic Behavior, Journal of Economic Theory, and Theoretical Economics), Quantitative Finance and Insurance (Mathematical Finance and Insurance: Mathematics and Economics), and Applied Mathematics (Annals of Probability and Mathematics of Operations Research). His papers have received many citations. He is also in the editorial board of leading international journals (Games and Economic Behavior, Journal of Economic Theory, Journal of the European Economic Association, Mathematics of Operations Research, and Theoretical Economics), and has given seminars in many international research institutions.

About the Università commerciale Luigi Bocconi

Founded in 1902 and located at the heart of Europe and in Italy’s business and financial centre, Università Bocconi is widely recognized as the leading university in Italy for economics and management. The university’s mission is to strive in providing top-level teaching and research with a truly international outlook through a highly-qualified and dedicated faculty. Today, Bocconi is a university of international standing in business, economics and law and offers an extensive range of programs through its five schools – including undergraduate, Masters of Science, PhD and MBA. Bocconi currently has around 200 partner schools worldwide and also draws strength from its network of alumni which consists of more than 80,000 graduates around the world. http://www.unibocconi.eu

About AXA Research Fund

Created in 2008, the AXA Research Fund (AXA RF) provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of May 1st, 2012, Euro 79 million have been committed and the AXA RF has given its support to 291 research projects, implemented in 24 countries by researchers of 43 nationalities. In Italy and for Italian researchers, it has so far committed a sum of Euro 3.5 million for various projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the funding vehicles, the list of all our grantees and biographies of the Scientific Board members, are available on the website www.axa-research.org.

About AXA in Italy

AXA is present throughout Italy in a multi-distribution perspective. AXA Assicurazioni (www.axa.it) operates throughout a network of about 700 agencies and distributes its insurance products providing ad hoc consulting service to ensure a complete protection. AXA MPS (www.axa-mps.it), the strategic partnership established in 2007 with Montepaschi banking group, distributes its insurance solutions through over 3000 branches in Italy, setting itself as a comprehensive “service company”. AXA is also present with further insurance companies, that include Quixa, a direct company of new generation, and the specialized entities AXA Art (protection of cultural heritage), AXA Corporate Solutions (large corporations and groups), AXA Assistance (assistance in different sectors), as well as AXA IM (asset management), AXA Private Equity (private equity operations) and AXA REIM (real estate investment management).

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2969 /launch-of-the-axa-university-of-bristol-chair-in-volcanology 2012-05-30T00:00:00 Launch of the AXA – University of Bristol Chair in Volcanology <p>The recent eruption of the volcano Eyafjallajokull in Iceland severely disrupted global air travel and highlighted the risks of volcanic eruptions to both local and distant populations. Fundamental gaps were recognized in the scientific understanding of volcanic plumes, how they are formed, and how their composition might be predicted. Their composition is critical for risk assessment as different particle sizes have dramatically different consequences for jet engine safety.</p> <p><span class="title_06">A new Research Initiative on Volcanic Plumes</span></p> <p>New research is now underway thanks to the AXA Research Fund, a scientific philanthropy initiative that helps more than 350 researchers based in 26 countries to understand and prevent risks. Through a €617,000 grant, the AXA Research Fund has created a new chair in volcanology at the University of Bristol in the UK to lead a programme of research into volcanic plumes that will help local communities prepare better, as well as improve predictions of how plumes may affect aircraft in flight. The person selected for the chair is Professor Katharine Cashman, from the Department of Geological Sciences at the University of Oregon and an expert volcanologist with more than 30 years’ experience around the world. At Bristol she is teaming up with other acknowledged experts in volcanic processes and hazards, as well as specialists in the sociological aspects of communicating volcano risks.</p> <p><span class="title_06">A Novel Approach</span></p> <p>The team will be conducting experiments using laboratory materials that behave in similar ways to magma. These experiments will help understand phenomena such as crystallization in the magma, providing detailed and practical insights into a process that happens under great temperature and pressure, beyond reach beneath the ground. <em>“What’s pleasing is that AXA Research Fund is very forward looking. They are funding basic research and basic science as well as more short-term risk related research,”</em> Professor Cashman notes. The novel approach she and her team are taking involves considering how the physical characteristics of a volcanic ash cloud depend on an evolving set of internal and extensive parameters such as magma composition, temperature and pressure or magma ascent path, regional stress field, and ice-cap melting. The research is scheduled to run for three years, after which it is hoped the team will have developed better scientific methods for predicting how volcanic plumes behave. This should benefit local communities who live near volcanoes, as well as airlines that need to know if it is going to be safe to fly.</p> <p><span class="title_06">A Prestigious University</span></p> <p>The University of Bristol is consistently ranked among the leaders in UK higher education. Research-intensive and with an international reputation for quality and innovation, the University has 17,000 students from over 100 countries, together with more than 5,500 staff. In terms of the number of applications per undergraduate place, Bristol is one of the most popular universities in the country.</p> <p>The Chair is based in the School of Earth Sciences at the University of Bristol, one of the leading centres for research and teaching in the Earth Sciences, having been ranked in the top four UK departments of its kind since 2001. Research activity is organised into <a href="http://www.bristol.ac.uk/earthsciences/research/">six groups</a> covering everything from climate and environmental change, to palaeobiology and geochemistry; volcanic hazards and risks is one of the School’s leading interests and areas of expertise. The Chair is also part of the Cabot Institute at the University of Bristol, which brings together the University’s fundamental and responsive research on risks and uncertainties in a changing environment across science, social science and engineering. The Institute is co-sponsoring the launch of the AXA Chair on 29 May.</p> <p><span class="title_06">A Sensible Support for an Insurance Company</span></p> <p>As an insurer, AXA has a role to build knowledge on risks to better prevent them and, if they occur, to better protect its customers against their consequences. This knowledge is firstly produced by AXA experts from field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. In this perspective, AXA also challenges its internal expertise by scientific knowledge produced independently by academics, and wishes to help academics share their discoveries to better inform public debate.</p> <p>Paul Goswamy, Head of Property &amp; Casualty Risk in AXA UK and sponsor of the chair, commented: <em>“I am very proud to be the AXA sponsor of this chair, and I look forward to a fruitful and long-term intellectual partnership between AXA and University of Bristol. As Head of Property and Casualty Risk in AXA UK, better understanding of the impact of volcanic eruptions on our societies is crucial to help me better cover our clients and thus protect them: the recent Icelandic eruption recalled the importance for an insurer to develop a model, which could clearly link likelihood and impact of plume activity with its associated costs due to damages and business interruption; because volcanoes are not only threatening people living in their surroundings. AXA and its risk management experts will contribute to Prof Cashman’s research on volcanic plume mitigation by sharing our insurance expertise. Furthermore, the AXA Research Fund will help Prof Cashman disseminate her discoveries through its world-wide network to enrich the public’s scientific knowledge for a better mitigation of volcanic plumes in the world.”</em></p> <p><span class="title_06">About Prof Katharine Cashman, Chair holder</span></p> <p>Katharine Cashman is a volcanologist with a long interest in the connection between chemical processes that control the formation of bubbles and crystals in rising magma, and the physical processes that control volcanic eruptions. At the same time, her early work as Public Information Scientist for the US Geological Survey during the 1980-1986 eruption of Mount St. Helens introduced her to both the challenges and importance of not only improving volcanic hazard assessment, but also developing effective channels of communication to public officials and communities. She has spent most of her career as a professor at the University of Oregon, USA. Her work has taken her to volcanoes around the world to study lava flows in Hawaii and Italy, cinder cone eruptions in Mexico and Oregon, explosive eruptions in Alaska and Ecuador, and eruptions under the ocean in the western Pacific.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/_mg_7109.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> The recent eruption of the volcano Eyafjallajokull in Iceland severely disrupted global air travel and highlighted the risks of volcanic eruptions to both local and distant populations. Fundamental gaps were recognized in the scientific understanding of volcanic plumes, how they are formed, and how their composition might be predicted. Their composition is critical for risk assessment as different particle sizes have dramatically different consequences for jet engine safety.

A new Research Initiative on Volcanic Plumes

New research is now underway thanks to the AXA Research Fund, a scientific philanthropy initiative that helps more than 350 researchers based in 26 countries to understand and prevent risks. Through a €617,000 grant, the AXA Research Fund has created a new chair in volcanology at the University of Bristol in the UK to lead a programme of research into volcanic plumes that will help local communities prepare better, as well as improve predictions of how plumes may affect aircraft in flight. The person selected for the chair is Professor Katharine Cashman, from the Department of Geological Sciences at the University of Oregon and an expert volcanologist with more than 30 years’ experience around the world. At Bristol she is teaming up with other acknowledged experts in volcanic processes and hazards, as well as specialists in the sociological aspects of communicating volcano risks.

A Novel Approach

The team will be conducting experiments using laboratory materials that behave in similar ways to magma. These experiments will help understand phenomena such as crystallization in the magma, providing detailed and practical insights into a process that happens under great temperature and pressure, beyond reach beneath the ground. “What’s pleasing is that AXA Research Fund is very forward looking. They are funding basic research and basic science as well as more short-term risk related research,” Professor Cashman notes. The novel approach she and her team are taking involves considering how the physical characteristics of a volcanic ash cloud depend on an evolving set of internal and extensive parameters such as magma composition, temperature and pressure or magma ascent path, regional stress field, and ice-cap melting. The research is scheduled to run for three years, after which it is hoped the team will have developed better scientific methods for predicting how volcanic plumes behave. This should benefit local communities who live near volcanoes, as well as airlines that need to know if it is going to be safe to fly.

A Prestigious University

The University of Bristol is consistently ranked among the leaders in UK higher education. Research-intensive and with an international reputation for quality and innovation, the University has 17,000 students from over 100 countries, together with more than 5,500 staff. In terms of the number of applications per undergraduate place, Bristol is one of the most popular universities in the country.

The Chair is based in the School of Earth Sciences at the University of Bristol, one of the leading centres for research and teaching in the Earth Sciences, having been ranked in the top four UK departments of its kind since 2001. Research activity is organised into six groups covering everything from climate and environmental change, to palaeobiology and geochemistry; volcanic hazards and risks is one of the School’s leading interests and areas of expertise. The Chair is also part of the Cabot Institute at the University of Bristol, which brings together the University’s fundamental and responsive research on risks and uncertainties in a changing environment across science, social science and engineering. The Institute is co-sponsoring the launch of the AXA Chair on 29 May.

A Sensible Support for an Insurance Company

As an insurer, AXA has a role to build knowledge on risks to better prevent them and, if they occur, to better protect its customers against their consequences. This knowledge is firstly produced by AXA experts from field data and in-house analysis. Nevertheless, in a constantly changing world, our societies cannot only rely on the past to explain the future, nor on mere incremental adaptation of existing models. The AXA Research Fund therefore supports new independent academic research to challenge local or historical consensus and truly understand the current reality of risks. In this perspective, AXA also challenges its internal expertise by scientific knowledge produced independently by academics, and wishes to help academics share their discoveries to better inform public debate.

Paul Goswamy, Head of Property & Casualty Risk in AXA UK and sponsor of the chair, commented: “I am very proud to be the AXA sponsor of this chair, and I look forward to a fruitful and long-term intellectual partnership between AXA and University of Bristol. As Head of Property and Casualty Risk in AXA UK, better understanding of the impact of volcanic eruptions on our societies is crucial to help me better cover our clients and thus protect them: the recent Icelandic eruption recalled the importance for an insurer to develop a model, which could clearly link likelihood and impact of plume activity with its associated costs due to damages and business interruption; because volcanoes are not only threatening people living in their surroundings. AXA and its risk management experts will contribute to Prof Cashman’s research on volcanic plume mitigation by sharing our insurance expertise. Furthermore, the AXA Research Fund will help Prof Cashman disseminate her discoveries through its world-wide network to enrich the public’s scientific knowledge for a better mitigation of volcanic plumes in the world.”

About Prof Katharine Cashman, Chair holder

Katharine Cashman is a volcanologist with a long interest in the connection between chemical processes that control the formation of bubbles and crystals in rising magma, and the physical processes that control volcanic eruptions. At the same time, her early work as Public Information Scientist for the US Geological Survey during the 1980-1986 eruption of Mount St. Helens introduced her to both the challenges and importance of not only improving volcanic hazard assessment, but also developing effective channels of communication to public officials and communities. She has spent most of her career as a professor at the University of Oregon, USA. Her work has taken her to volcanoes around the world to study lava flows in Hawaii and Italy, cinder cone eruptions in Mexico and Oregon, explosive eruptions in Alaska and Ecuador, and eruptions under the ocean in the western Pacific.

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2927 /axa-announces-eu2-million-endowment-to-establish-axa-cnio-chair-in-molecular-oncology 2012-05-09T00:00:00 AXA announces €2 million endowment to establish AXA-CNIO Chair in Molecular Oncology <p class="title_01"><strong>4 May 2012</strong>, Madrid - The AXA Research Fund, a global initiative of scientific philanthropy supported by the worldwide insurance Group AXA, is awarding 2 million euros to the Spanish National Cancer Research Centre (CNIO) to create a permanent Chair in Molecular Oncology, to be held by Dr. Mariano Barbacid. This Chair AXA-CNIO is the fifth Chair in the world created by AXA Research Fund in Life Sciences.</p><p>&nbsp;</p><p><em>"This type of chairs is something completely new in Spain, which makes the philanthropic contribution made by AXA even more relevant " says Dr. Barbacid, who explains that "the first thing we are going to do with the resources generated by this endowment will be to establish a platform for clinical mouse trials using genetically engineered models that reproduces faithfully human lung adenocarcinoma".</em></p> <p>For Javier de Agustín, CEO of AXA Spain, and sponsor of this Chair: <em>“the AXA Research Fund support to Spanish research in these years shows the high level of excellence of Spanish Scientists. I’m also honored to become the sponsor of this chair and I look forward to a fruitful intellectual relationship with Dr. Barbacid: Cancer is a crucial threat to human life for an insurer and we are proud both to support a better understanding of this disease and to mutually nurture our expertise on this issue. We hope this may help to prevent it better.”</em></p> <p>The philanthropic contribution of the AXA Research Fund supporting this Permanent Endowed Chair ensures the economic viability of the research over time due to the continued flow of resources derived from the interest generated by the 2 million euros endowment.</p> <p>For Prof. María Blasco, Director of the CNIO since June 2011,<em> "The CNIO needs now more than ever the generosity of such philanthropic initiative to be among the best research centers in the world in the fight against cancer. And I feel very proud and very grateful that AXA Research Fund so generously helped us take steps in that direction.”</em></p> <p>Dr Barbacid´s research group is proposing to use a new generation of genetically modified animal tumors models that faithfully reproduce the development of human cancers to validate novel therapeutic strategies using both genetic approaches and pharmacological approaches. Specifically, Dr. Barbacid and colleagues will focus their studies on K-Ras oncogene-driven lung and pancreatic adenocarcinomas, two tumors types with some of the worst prognosis and survival. Indeed, despite the efforts dedicated over the last three decades, there are no selective drugs against these cancers yet.</p> <p>Dr. Barbacid is one of the key contributors to the elucidation of the molecular mechanisms of cancer. In the spring of 1982, while at the National Cancer Institute in the USA, he led one of three laboratories that independently discovered the first human cancer-causing gene (oncogene), H-Ras. This discovery opened up a new field in cancer biology and provided the first experimental evidence to establish the molecular bases of human cancer. In the same year, Dr. Barbacid also discovered that cancer was a genetic disease, that is to say a disease caused by mutations in our own genes.</p> <p>His strategy is based on the successful use of multi-drug therapies to fight the AIDS virus. Yet, Dr. Barbacid warns that “lung cancer is much a more complex disease than AIDS. […] We expect the first results in 12 or 18 months."</p> <p><span class="title_06">Spain, an important place for world-class research acknowledged by the AXA Research Fund</span></p> <p>Others researchers supported on a worldwide academic competition basis by the AXA Research Fund in Spain include: Prof <strong>Albert Marcet</strong>, AXA Chair on Macroeconomic Risk (Permanent chair 2009, Barcelona GSE); Prof <strong>Joan Esteban</strong>, AXA Project on Social Conflicts (Project 2008, U. Autónoma de Barcelona); <strong>Fabian Rinnen</strong>, Forecasting Risk: Realized Quantile Approach (PhD 2010, U. Carlos III de Madrid); <strong>Anatoli Segura</strong>, Roll-over Risk and debt maturity (PhD 2010, CEMFI).</p> <p>Taking into account seven Spanish researchers supported abroad, the philanthropic support of the AXA Research Fund to Spanish research accounts for € 3.6 million.</p> <p><span class="title_06">About CNIO</span></p> <p>The National Research Centre on Oncology (CNIO) was created by the Instituto de Salud Carlos III in 1998. Its mission is to develop excellent research and provide innovative technologies in the field of oncology at the Sistema Nacional de Salud.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_researchfund_tcm5-7294.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> 4 May 2012, Madrid - The AXA Research Fund, a global initiative of scientific philanthropy supported by the worldwide insurance Group AXA, is awarding 2 million euros to the Spanish National Cancer Research Centre (CNIO) to create a permanent Chair in Molecular Oncology, to be held by Dr. Mariano Barbacid. This Chair AXA-CNIO is the fifth Chair in the world created by AXA Research Fund in Life Sciences.

 

"This type of chairs is something completely new in Spain, which makes the philanthropic contribution made by AXA even more relevant " says Dr. Barbacid, who explains that "the first thing we are going to do with the resources generated by this endowment will be to establish a platform for clinical mouse trials using genetically engineered models that reproduces faithfully human lung adenocarcinoma".

For Javier de Agustín, CEO of AXA Spain, and sponsor of this Chair: “the AXA Research Fund support to Spanish research in these years shows the high level of excellence of Spanish Scientists. I’m also honored to become the sponsor of this chair and I look forward to a fruitful intellectual relationship with Dr. Barbacid: Cancer is a crucial threat to human life for an insurer and we are proud both to support a better understanding of this disease and to mutually nurture our expertise on this issue. We hope this may help to prevent it better.”

The philanthropic contribution of the AXA Research Fund supporting this Permanent Endowed Chair ensures the economic viability of the research over time due to the continued flow of resources derived from the interest generated by the 2 million euros endowment.

For Prof. María Blasco, Director of the CNIO since June 2011, "The CNIO needs now more than ever the generosity of such philanthropic initiative to be among the best research centers in the world in the fight against cancer. And I feel very proud and very grateful that AXA Research Fund so generously helped us take steps in that direction.”

Dr Barbacid´s research group is proposing to use a new generation of genetically modified animal tumors models that faithfully reproduce the development of human cancers to validate novel therapeutic strategies using both genetic approaches and pharmacological approaches. Specifically, Dr. Barbacid and colleagues will focus their studies on K-Ras oncogene-driven lung and pancreatic adenocarcinomas, two tumors types with some of the worst prognosis and survival. Indeed, despite the efforts dedicated over the last three decades, there are no selective drugs against these cancers yet.

Dr. Barbacid is one of the key contributors to the elucidation of the molecular mechanisms of cancer. In the spring of 1982, while at the National Cancer Institute in the USA, he led one of three laboratories that independently discovered the first human cancer-causing gene (oncogene), H-Ras. This discovery opened up a new field in cancer biology and provided the first experimental evidence to establish the molecular bases of human cancer. In the same year, Dr. Barbacid also discovered that cancer was a genetic disease, that is to say a disease caused by mutations in our own genes.

His strategy is based on the successful use of multi-drug therapies to fight the AIDS virus. Yet, Dr. Barbacid warns that “lung cancer is much a more complex disease than AIDS. […] We expect the first results in 12 or 18 months."

Spain, an important place for world-class research acknowledged by the AXA Research Fund

Others researchers supported on a worldwide academic competition basis by the AXA Research Fund in Spain include: Prof Albert Marcet, AXA Chair on Macroeconomic Risk (Permanent chair 2009, Barcelona GSE); Prof Joan Esteban, AXA Project on Social Conflicts (Project 2008, U. Autónoma de Barcelona); Fabian Rinnen, Forecasting Risk: Realized Quantile Approach (PhD 2010, U. Carlos III de Madrid); Anatoli Segura, Roll-over Risk and debt maturity (PhD 2010, CEMFI).

Taking into account seven Spanish researchers supported abroad, the philanthropic support of the AXA Research Fund to Spanish research accounts for € 3.6 million.

About CNIO

The National Research Centre on Oncology (CNIO) was created by the Instituto de Salud Carlos III in 1998. Its mission is to develop excellent research and provide innovative technologies in the field of oncology at the Sistema Nacional de Salud.

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2845 /axa-research-fund-press-release 2012-04-12T00:00:00 AXA Research Fund Press Release <p>In 2011, AXA strongly expanded its support to scientific research on the global risks on the environment, human health and societies. According to its unique global philanthropic scheme, <strong>the AXA Research Fund selected 83 new academic teams</strong> and gave them a support globally amounting to 22 million euros.</p> <p><span class="title_06">3 new AXA Research Chairs have been created</span></p><p>For instance, the<a title="Launch of the AXA-Nanyang Technological University Chair on Natural Hazards" href="http://www.axa-research.org/the-axa-research-fund-launches-its-first-chair-in-asia" target="_blank"> AXA-Nanyang Technological University Chair on Natural Hazards </a>(Singapour), held by world-known American geologist Pr. Kerry Sieh, will strengthen the application of earth science to create safer and more sustainable societies in a region where millions of people are exposed to earthquakes, tsunamis, volcanic eruptions, changing sea levels and other natural hazards. It has been endowed with 3 million Euros.</p> <p><span class="title_06">14 new research projects have been granted</span></p><p>such as Pr. Peter Carmeliet’s project at the Katholieke Universiteit Leuven (Belgium), which explores tumor cell growth to unravel mechanisms which could offer new therapeutic avenues for cancer. It has been granted 1 million Euros.</p> <p><span class="title_06">66 postdoctoral and doctoral fellowships</span></p><p>to contribute to the development of a new generation of scientific excellence (120,000 Euros each). Among them, Dr. Asuka Komiya, from Kobe University (Japan), explores how the practice of apologies maintains the social fabric of society and, therefore, allows for personal risk-taking.</p> <p><em>“As a leading insurer, our key expertise lies in understanding and managing risk, our key responsibility in protecting people. This means that we have an essential and active role to play in making sure the ever-evolving risk landscape – the greatest risk coming from where it is least expected – is understood by the society as a whole. I am very proud and delighted that the AXA Research Fund contributes more and more to this noble purpose and thus to the engine of human progress.”</em> <strong>said Henri de Castries, Chairman and CEO of AXA.</strong></p> <p>The AXA Research knowledge community now consists of <strong>289 teams and researchers of 47 nationalities.</strong> AXA support amounts to 76 million Euros since 2008.</p> <p>The 2011 supported initiatives have been selected on the basis of excellence through a rigorous process supervised by the AXA Research Fund Scientific Board, which is chaired by Pr. Ezra Suleiman (Princeton University) and on which eminent figures from the scientific world sit.</p> <p><span class="title_06">About the AXA Research Fund</span></p><p>Created in 2008, the AXA Research Fund provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. It is a major initiative within AXA’s Corporate Responsibility strategy to support risk research and education. As of February 1st, 2012, Euro 76 million have been committed and the AXA Research Fund has given its support to 289 research projects, implemented in 26 countries by researchers of 47 nationalities. The funds are granted based on a decision by the Scientific Board.</p> <p><span class="title_06">About the AXA Group</span></p><p>The AXA Group is a worldwide leader in insurance and asset management, with 163,000 employees serving 101 million clients in 57 countries. In 2011, IFRS revenues amounted to Euro 86.1 billion and IFRS underlying earnings to Euro 3.9 billion. AXA had Euro 1,079 billion in assets under management as of December 31, 2011. The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISN FR 0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depository Share is also quoted on the OTC QX platform under the ticker symbol AXAHY. The AXA Group is included in the main international SRI indexes, such as Dow Jones Sustainability Index (DJSI) and FTSE4GOOD.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_fund_corpo_sign_rgb.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> In 2011, AXA strongly expanded its support to scientific research on the global risks on the environment, human health and societies. According to its unique global philanthropic scheme, the AXA Research Fund selected 83 new academic teams and gave them a support globally amounting to 22 million euros.

3 new AXA Research Chairs have been created

For instance, the AXA-Nanyang Technological University Chair on Natural Hazards (Singapour), held by world-known American geologist Pr. Kerry Sieh, will strengthen the application of earth science to create safer and more sustainable societies in a region where millions of people are exposed to earthquakes, tsunamis, volcanic eruptions, changing sea levels and other natural hazards. It has been endowed with 3 million Euros.

14 new research projects have been granted

such as Pr. Peter Carmeliet’s project at the Katholieke Universiteit Leuven (Belgium), which explores tumor cell growth to unravel mechanisms which could offer new therapeutic avenues for cancer. It has been granted 1 million Euros.

66 postdoctoral and doctoral fellowships

to contribute to the development of a new generation of scientific excellence (120,000 Euros each). Among them, Dr. Asuka Komiya, from Kobe University (Japan), explores how the practice of apologies maintains the social fabric of society and, therefore, allows for personal risk-taking.

“As a leading insurer, our key expertise lies in understanding and managing risk, our key responsibility in protecting people. This means that we have an essential and active role to play in making sure the ever-evolving risk landscape – the greatest risk coming from where it is least expected – is understood by the society as a whole. I am very proud and delighted that the AXA Research Fund contributes more and more to this noble purpose and thus to the engine of human progress.” said Henri de Castries, Chairman and CEO of AXA.

The AXA Research knowledge community now consists of 289 teams and researchers of 47 nationalities. AXA support amounts to 76 million Euros since 2008.

The 2011 supported initiatives have been selected on the basis of excellence through a rigorous process supervised by the AXA Research Fund Scientific Board, which is chaired by Pr. Ezra Suleiman (Princeton University) and on which eminent figures from the scientific world sit.

About the AXA Research Fund

Created in 2008, the AXA Research Fund provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. It is a major initiative within AXA’s Corporate Responsibility strategy to support risk research and education. As of February 1st, 2012, Euro 76 million have been committed and the AXA Research Fund has given its support to 289 research projects, implemented in 26 countries by researchers of 47 nationalities. The funds are granted based on a decision by the Scientific Board.

About the AXA Group

The AXA Group is a worldwide leader in insurance and asset management, with 163,000 employees serving 101 million clients in 57 countries. In 2011, IFRS revenues amounted to Euro 86.1 billion and IFRS underlying earnings to Euro 3.9 billion. AXA had Euro 1,079 billion in assets under management as of December 31, 2011. The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISN FR 0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depository Share is also quoted on the OTC QX platform under the ticker symbol AXAHY. The AXA Group is included in the main international SRI indexes, such as Dow Jones Sustainability Index (DJSI) and FTSE4GOOD.

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2741 /launch-of-the-axa-eief-chair-on-household-finance-and-insurance-0 2012-03-19T00:00:00 Launch of the AXA-EIEF Chair on Household finance and insurance <p>Without trust, the economy would, in the end, fail to work. Trust is in particular crucial when someone chooses to buy an insurance product or to invest in a corporation's stock. What is more the recent times have shown that the collapse in trust can lead to severe tensions in the loan system. Professor Guiso believes that the importance of trust has been underplayed in economics and especially in finance. By bringing trust back to the attention of economists, his research shows that trust and beliefs matter considerably for people’s reliance on financial instruments and for the development of financial markets. Trust is even more important for households, because, lacking knowledge and information, they often need to rely on it when asking for advice to make their financial decisions. That is why expanding existing models of households financial decisions to allow for diversity in peoples beliefs towards other people behavior, along with differences in risk attitudes, will better capture households interactions with financial markets. Professor Guiso is therefore studying new models of behavior in the face of risk and uncertainty that might take into account a richer characterization of preferences and additional dimensions of risk, including social risk.</p> <p>Professor Guiso works at the Einaudi Institute for Economics and Finance (EIEF), an independent research institute created in 2008 by the Bank of Italy, which aims at producing frontier research in economics and finance, to generate ideas that could be useful in the policy debate. The AXA Research Fund decided to lend its support to this highly ambitious strategy.</p> <p><strong>Prof Luigi Guiso, Chair holder declared:</strong> <em>“There are a number of features that I consider extremely valuable in AXA’s funding scheme. Selection criteria are based solely on academic merit, and AXA is extremely respectful of the research freedom of the beneficiary of the funds, while monitoring the use of these funds. All these elements are key features for successful funding because they provide the right incentives to the researchers involved”</em>.</p> <p>Commenting on AXA’s commitment to this Chair, <strong>Frédéric de Courtois, AXA MPS CEO and sponsor of the Chair, said:</strong> <em>“The launch of this Chair at EIEF is a concrete example of AXA’s commitment to risk research and education. Risk management, the core of our business, is also a key pillar of economic development and the private sector must play an important role in advancing knowledge of the field, promoting, in line with its larger social responsibilities, meaningful academic research as an investment for the future. The ambitious research project conducted under the Chair will contribute to stimulate and advance the public debate on key topics, related to the role of financial literacy and the regulation of intermediaries offering financial products to households. We are also proud to announce this new concrete initiative in Italy, a sign of attention towards the country of origin of mecenatism. Today Italy lacks funds for research but is rich of talents whose promotion is key for the future of the country”</em>.</p><p><span class="title_06">About the AXA Research Fund</span></p><p>Created in 2008, the AXA Research Fund (AXA RF) provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of February 1st, 2012, Euro 76 million have been committed and the AXA RF has given its support to 289 research projects, implemented in 24 countries by researchers of 47 nationalities. In Italy and for Italian researchers, it has so far committed a sum of Euro 3.5 million for various projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the funding vehicles, guidelines and biographies of the Scientific Board members, are available on the website <a href="http://www.axa-research.org" target="_blank">www.axa-research.org</a>.</p> <p><span class="title_06">About the AXA Group</span></p> <p>The AXA Group is a worldwide leader in insurance and asset management serving 101 million clients. For full year 2011, IFRS revenues amounted to Euro 86.1 billion and IFRS underlying earnings to Euro 3.9 billion. AXA had Euro 1,079 billion in assets under management as of December 31, 2011.</p> <p>The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISIN FR0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depositary Share is also quoted on the OTC QX platform under the ticker symbol AXAHY.</p> <p><span class="title_06">About Einaudi Institute for Economics and Finance (EIEF)</span></p><p>The Einaudi Institute for Economics and Finance (EIEF, <a href="http://www.eief.it" target="_blank">www.eief.it</a>) is an independent research institute, created in 2008 by the Bank of Italy. EIEF aims to produce frontier research in economics and finance, to generate ideas that can be useful in the policy debate. It offers a research environment that, adopting the standards of the best international academia, helps reversing Italy’s “brain drain”, by attracting both the best foreign scholars and Italian scholars trained abroad to come back to Italy. EIEF also aims to complement the programs offered by Italian universities, focusing on graduate researchoriented courses and on supervision of selected PhD students.</p> <p><span class="title_06">About Prof Luigi Guiso, Chair holder</span></p><p>Luigi Guiso is full professor at the Einaudi Institute for Economics and Finance since January 2012. He has moved to EIEF to take the AXA chair in Household Finance and Insurance form the European University Institute. He has directed for five years the Finance Programme at CEPR of which he is a fellow. Luigi Guiso obtained a Msc in Economics at the London School of Economics (1980) and Mphil in Economics at University of Essex (1982). He has been visiting professor at the London School of Economics and Imperial College in London and has held teaching positions at the University of Rome and at the University of Chicago, Graduate School of Business, besides those at the European University Institute. He is a recipient of several publishing awards. Luigi Guiso has broad research interests. Besides his work in the field of households finance he has contributed research in the field of labor economics, firms investment and financial decisions, entrepreneurship and banking, political economy and institutions and in the recent field of culture and economics. His research has been published in the major scholarly journal such as the Review of Economic Studies, the Journal of Monetary Economics, the Quarterly Journal of Economics, the Journal of Political Economy, and the American Economic Review.</p> <p><span class="title_06">About AXA in Italy</span></p><p>AXA is present throughout Italy in a multi-distribution perspective. AXA Assicurazioni (www.axa.it) operates throughout a network of about 700 agencies and distributes its insurance and financial products providing ad hoc consulting service to ensure a complete protection. AXA MPS (www.axa-mps.it), the strategic partnership established in 2007 with Montepaschi banking group, distributes its insurance solutions through over 3000 branches in Italy, setting itself as a comprehensive “service company”. AXA is also present with further insurance companies, that include Quixa, a direct company of new generation, and the specialized entities AXA Art (protection of cultural heritage), AXA Corporate Solutions (large corporations and groups), AXA Assistance (assistance in different sectors), as well as AXA IM (asset management), AXA Private Equity (private equity operations) and AXA REIM (real estate investment management).</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/eief.png" alt="" title="" class="imagecache imagecache-contentimage" /> Without trust, the economy would, in the end, fail to work. Trust is in particular crucial when someone chooses to buy an insurance product or to invest in a corporation's stock. What is more the recent times have shown that the collapse in trust can lead to severe tensions in the loan system. Professor Guiso believes that the importance of trust has been underplayed in economics and especially in finance. By bringing trust back to the attention of economists, his research shows that trust and beliefs matter considerably for people’s reliance on financial instruments and for the development of financial markets. Trust is even more important for households, because, lacking knowledge and information, they often need to rely on it when asking for advice to make their financial decisions. That is why expanding existing models of households financial decisions to allow for diversity in peoples beliefs towards other people behavior, along with differences in risk attitudes, will better capture households interactions with financial markets. Professor Guiso is therefore studying new models of behavior in the face of risk and uncertainty that might take into account a richer characterization of preferences and additional dimensions of risk, including social risk.

Professor Guiso works at the Einaudi Institute for Economics and Finance (EIEF), an independent research institute created in 2008 by the Bank of Italy, which aims at producing frontier research in economics and finance, to generate ideas that could be useful in the policy debate. The AXA Research Fund decided to lend its support to this highly ambitious strategy.

Prof Luigi Guiso, Chair holder declared: “There are a number of features that I consider extremely valuable in AXA’s funding scheme. Selection criteria are based solely on academic merit, and AXA is extremely respectful of the research freedom of the beneficiary of the funds, while monitoring the use of these funds. All these elements are key features for successful funding because they provide the right incentives to the researchers involved”.

Commenting on AXA’s commitment to this Chair, Frédéric de Courtois, AXA MPS CEO and sponsor of the Chair, said: “The launch of this Chair at EIEF is a concrete example of AXA’s commitment to risk research and education. Risk management, the core of our business, is also a key pillar of economic development and the private sector must play an important role in advancing knowledge of the field, promoting, in line with its larger social responsibilities, meaningful academic research as an investment for the future. The ambitious research project conducted under the Chair will contribute to stimulate and advance the public debate on key topics, related to the role of financial literacy and the regulation of intermediaries offering financial products to households. We are also proud to announce this new concrete initiative in Italy, a sign of attention towards the country of origin of mecenatism. Today Italy lacks funds for research but is rich of talents whose promotion is key for the future of the country”.

About the AXA Research Fund

Created in 2008, the AXA Research Fund (AXA RF) provides philanthropic support for research focused on understanding and preventing the risks threatening the environment, human life and our societies. As of February 1st, 2012, Euro 76 million have been committed and the AXA RF has given its support to 289 research projects, implemented in 24 countries by researchers of 47 nationalities. In Italy and for Italian researchers, it has so far committed a sum of Euro 3.5 million for various projects. The funds are granted based on a decision by the Scientific Board. By supporting top-tier researchers working on risks all over the world and helping them to share their discoveries, AXA RF tries to enrich the public debate and AXA’s own expertise with academic knowledge. Through research philanthropic sponsorship, AXA aims to foster a safer and stronger society over the long term. More details about the AXA Research Fund, including presentation of the funding vehicles, guidelines and biographies of the Scientific Board members, are available on the website www.axa-research.org.

About the AXA Group

The AXA Group is a worldwide leader in insurance and asset management serving 101 million clients. For full year 2011, IFRS revenues amounted to Euro 86.1 billion and IFRS underlying earnings to Euro 3.9 billion. AXA had Euro 1,079 billion in assets under management as of December 31, 2011.

The AXA ordinary share is listed on compartment A of Euronext Paris under the ticker symbol CS (ISIN FR0000120628 – Bloomberg: CS FP – Reuters: AXAF.PA). AXA’s American Depositary Share is also quoted on the OTC QX platform under the ticker symbol AXAHY.

About Einaudi Institute for Economics and Finance (EIEF)

The Einaudi Institute for Economics and Finance (EIEF, www.eief.it) is an independent research institute, created in 2008 by the Bank of Italy. EIEF aims to produce frontier research in economics and finance, to generate ideas that can be useful in the policy debate. It offers a research environment that, adopting the standards of the best international academia, helps reversing Italy’s “brain drain”, by attracting both the best foreign scholars and Italian scholars trained abroad to come back to Italy. EIEF also aims to complement the programs offered by Italian universities, focusing on graduate researchoriented courses and on supervision of selected PhD students.

About Prof Luigi Guiso, Chair holder

Luigi Guiso is full professor at the Einaudi Institute for Economics and Finance since January 2012. He has moved to EIEF to take the AXA chair in Household Finance and Insurance form the European University Institute. He has directed for five years the Finance Programme at CEPR of which he is a fellow. Luigi Guiso obtained a Msc in Economics at the London School of Economics (1980) and Mphil in Economics at University of Essex (1982). He has been visiting professor at the London School of Economics and Imperial College in London and has held teaching positions at the University of Rome and at the University of Chicago, Graduate School of Business, besides those at the European University Institute. He is a recipient of several publishing awards. Luigi Guiso has broad research interests. Besides his work in the field of households finance he has contributed research in the field of labor economics, firms investment and financial decisions, entrepreneurship and banking, political economy and institutions and in the recent field of culture and economics. His research has been published in the major scholarly journal such as the Review of Economic Studies, the Journal of Monetary Economics, the Quarterly Journal of Economics, the Journal of Political Economy, and the American Economic Review.

About AXA in Italy

AXA is present throughout Italy in a multi-distribution perspective. AXA Assicurazioni (www.axa.it) operates throughout a network of about 700 agencies and distributes its insurance and financial products providing ad hoc consulting service to ensure a complete protection. AXA MPS (www.axa-mps.it), the strategic partnership established in 2007 with Montepaschi banking group, distributes its insurance solutions through over 3000 branches in Italy, setting itself as a comprehensive “service company”. AXA is also present with further insurance companies, that include Quixa, a direct company of new generation, and the specialized entities AXA Art (protection of cultural heritage), AXA Corporate Solutions (large corporations and groups), AXA Assistance (assistance in different sectors), as well as AXA IM (asset management), AXA Private Equity (private equity operations) and AXA REIM (real estate investment management).

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2655 /the-axa-research-fund-launches-its-first-chair-in-asia 2012-02-28T00:00:00 The AXA Research Fund Launches its First Chair in Asia <p class="title_01">28 February, 2012 Singapore - The AXA Research Fund, a global initiative of scientific philanthropy supported by the worldwide insurance group AXA, is awarding 3 million Euros (S$5M) to the <em>Nanyang Technological University</em> of Singapore (NTU) to create a permanent Chair in Natural Hazards held by Prof Kerry Sieh. This is the first AXA Chair in Asia.</p><p>&nbsp;</p><p><span class="title_06">Inspired by the need to build sustainable societies</span></p><p>The enormous growth of the human population in Southeast Asia over the past six decades has exposed millions of people to natural hazards such as earthquakes, tsunamis, volcanic eruptions, changing sea levels, climate change and other geological hazards. To build sustainable societies, it's become crucial to have a comprehensive panorama of natural hazards in the region combining both solid geological and social sciences.</p> <p>With the endowment awarded by the AXA Research Fund, <em>Nanyang Technological University</em> will establish the AXA-NTU Chair in Natural Hazards at the <em>Earth Observatory of Singapore</em> (EOS). These funds will strengthen the Observatory's ability to become an enduring pillar in the application of earth science to create safer and more sustainable societies in the region. The Observatory will apply the support from the endowment to focus on the areas of risk assessment and management, policy and economic issues, and education. These integrations will occur largely through joint appointments and engagements with other NTU departments and institutes.</p> <p><span class="title_06">Engaging the Community</span></p> <p>The AXA Research Fund encourages its supported researchers to have a voice in the public debate, sharing their knowledge with their peers and improving their analysis through a multidisciplinary approach. This includes working with journalists and the media to help them inform people about the risks they are exposed to; providing government agencies with the necessary information to make accurate public decisions and working with risk experts of multiple industries – including insurance. This ensures the ongoing growth of the scientific knowledge base.</p> <p>Beyond the long-term financial resources the AXA Research Fund provides, the Chair is also given the opportunity to connect to the research community of more than 300 supported researchers all around the world. Tapping on this extensive worldwide network, the AXANTU Chair can also further disseminate its research and enrich the public’s scientific knowledge for a better awareness and mitigation of natural hazards in South East Asia.</p> <p><span class="title_06">A partnership built on shared ideals</span></p> <p>On AXA’s generous support to bolster earth sciences at the university, NTU President Professor Bertil Andersson said:<em> “EOS rates as one of the best research institutes of its kind in the world. It is making great strides in the field of sustainability with its unique blend of geoscience and social science excellence blended into a single institution. We are proud to find a partner who has faith in our research capabilities. We are confident that NTU is a good match for AXA’s aspiration in this partnership and together, we can achieve great things for a sustainable earth.”</em></p> <p>Prof Kerry Sieh, Chair holder and Director of the Earth Observatory, declared: <em>“Creating connections with industry partners such as AXA will be critical to our success in contributing to a ‘Sustainable Earth,’ one of NTU's five strategic, inter-disciplinary Peaks of Excellence. These partnerships will help governments, communities and businesses anticipate and adapt creatively to environmental challenges, as well as develop and implement visionary policies to mitigate risks that Nature poses to human infrastructure."</em></p> <p>Commenting on AXA’s commitment to this Chair, Denis Duverne, AXA Group Deputy CEO said: <em>“The AXA Research Fund is committed to supporting countries that make academic research a cardinal point of their economic development, and that’s the case for Singapore. Therefore, in addition to supporting two Singaporean researchers working in Europe and one outstanding and innovative research project at the National University of Singapore, we are now funding the first Asian AXA Chair at the Nanyang Technological University. I think it acknowledges the international recognition and academic excellence of the Singaporean research institutions as well as AXA's long term commitment to the region. This new Chair is exactly the kind of excellence that the AXA Research Fund wants to support and to partner with to better understand and prevent risks for the society at large.”</em></p> <p>Gaëlle Olivier, CEO of AXA Asia General Insurance and sponsor of the Chair, added: <em>“As the AXA sponsor of the Chair, I look forward to a fruitful and long-term intellectual partnership between AXA and NTU. AXA will benefit from the EOS' researchers’ expertise on natural hazards in the region as the work is likely to bring new vision and analysis of mid to long term trends that will enhance awareness of emerging risks for risk management experts. AXA will contribute to Prof Sieh’s research by sharing our insurance expertise concerning such risks. Finally, AXA will help Prof. Sieh disseminate his discoveries through AXA’s world-wide network to enrich the public’s scientific knowledge for a better mitigation of natural hazards in South East Asia.”</em></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/ntu_logo.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> 28 February, 2012 Singapore - The AXA Research Fund, a global initiative of scientific philanthropy supported by the worldwide insurance group AXA, is awarding 3 million Euros (S$5M) to the Nanyang Technological University of Singapore (NTU) to create a permanent Chair in Natural Hazards held by Prof Kerry Sieh. This is the first AXA Chair in Asia.

 

Inspired by the need to build sustainable societies

The enormous growth of the human population in Southeast Asia over the past six decades has exposed millions of people to natural hazards such as earthquakes, tsunamis, volcanic eruptions, changing sea levels, climate change and other geological hazards. To build sustainable societies, it's become crucial to have a comprehensive panorama of natural hazards in the region combining both solid geological and social sciences.

With the endowment awarded by the AXA Research Fund, Nanyang Technological University will establish the AXA-NTU Chair in Natural Hazards at the Earth Observatory of Singapore (EOS). These funds will strengthen the Observatory's ability to become an enduring pillar in the application of earth science to create safer and more sustainable societies in the region. The Observatory will apply the support from the endowment to focus on the areas of risk assessment and management, policy and economic issues, and education. These integrations will occur largely through joint appointments and engagements with other NTU departments and institutes.

Engaging the Community

The AXA Research Fund encourages its supported researchers to have a voice in the public debate, sharing their knowledge with their peers and improving their analysis through a multidisciplinary approach. This includes working with journalists and the media to help them inform people about the risks they are exposed to; providing government agencies with the necessary information to make accurate public decisions and working with risk experts of multiple industries – including insurance. This ensures the ongoing growth of the scientific knowledge base.

Beyond the long-term financial resources the AXA Research Fund provides, the Chair is also given the opportunity to connect to the research community of more than 300 supported researchers all around the world. Tapping on this extensive worldwide network, the AXANTU Chair can also further disseminate its research and enrich the public’s scientific knowledge for a better awareness and mitigation of natural hazards in South East Asia.

A partnership built on shared ideals

On AXA’s generous support to bolster earth sciences at the university, NTU President Professor Bertil Andersson said: “EOS rates as one of the best research institutes of its kind in the world. It is making great strides in the field of sustainability with its unique blend of geoscience and social science excellence blended into a single institution. We are proud to find a partner who has faith in our research capabilities. We are confident that NTU is a good match for AXA’s aspiration in this partnership and together, we can achieve great things for a sustainable earth.”

Prof Kerry Sieh, Chair holder and Director of the Earth Observatory, declared: “Creating connections with industry partners such as AXA will be critical to our success in contributing to a ‘Sustainable Earth,’ one of NTU's five strategic, inter-disciplinary Peaks of Excellence. These partnerships will help governments, communities and businesses anticipate and adapt creatively to environmental challenges, as well as develop and implement visionary policies to mitigate risks that Nature poses to human infrastructure."

Commenting on AXA’s commitment to this Chair, Denis Duverne, AXA Group Deputy CEO said: “The AXA Research Fund is committed to supporting countries that make academic research a cardinal point of their economic development, and that’s the case for Singapore. Therefore, in addition to supporting two Singaporean researchers working in Europe and one outstanding and innovative research project at the National University of Singapore, we are now funding the first Asian AXA Chair at the Nanyang Technological University. I think it acknowledges the international recognition and academic excellence of the Singaporean research institutions as well as AXA's long term commitment to the region. This new Chair is exactly the kind of excellence that the AXA Research Fund wants to support and to partner with to better understand and prevent risks for the society at large.”

Gaëlle Olivier, CEO of AXA Asia General Insurance and sponsor of the Chair, added: “As the AXA sponsor of the Chair, I look forward to a fruitful and long-term intellectual partnership between AXA and NTU. AXA will benefit from the EOS' researchers’ expertise on natural hazards in the region as the work is likely to bring new vision and analysis of mid to long term trends that will enhance awareness of emerging risks for risk management experts. AXA will contribute to Prof Sieh’s research by sharing our insurance expertise concerning such risks. Finally, AXA will help Prof. Sieh disseminate his discoveries through AXA’s world-wide network to enrich the public’s scientific knowledge for a better mitigation of natural hazards in South East Asia.”

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724 /marco-springmann 2011-08-02T00:00:00 Marco SPRINGMANN <p><a href="http://www.axa-research.org/project/marco-springmann"><span class="link_01">Click here to find out more about this research supported by the AXA Research Fund</span></a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/marco_springmann.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Click here to find out more about this research supported by the AXA Research Fund

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725 /rachel-white 2011-08-02T00:00:00 Rachel WHITE <p class="link_01"><a title="Rachel WHITE, AXA Research Fellow" href="/project/rachel-white">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/rachel_white.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Click here to find out more about this research supported by the AXA Research Fund

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805 /sir-brian-hoskins-member-of-the-scientific-board 2011-08-02T00:00:00 Sir Brian Hoskins, member of the Scientific Board <p>Sir Brian Hoskins, member of the <a href="/composition-of-the-scientific-board">Scientific Board</a> of the AXA Research Fund.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/sir_brian_hoskins.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Sir Brian Hoskins, member of the Scientific Board of the AXA Research Fund.

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806 /abdul-barakat-when-biology-meets-engineering 2011-08-02T00:00:00 Abdul Barakat: When biology meets engineering <p>Cardiovascular diseases are the leading cause of mortality in the world. The subject is particularly important in the Western world, and its relevance is increasing worldwide. Abdul Barakat has launched a new program at the <a href="/project/abdul-barakat">Ecole Polytechnique</a> to help understand the basic mechanisms of these diseases and to bring engineering expertise to the design of drug delivery devices and strategies that can help to find a cure.</p><ul><li><strong>Could you briefly describe what are cardiovascular diseases?</strong></li><li>The two main cardiovascular diseases are coronary heart disease and stroke. In their early stages, these pathologies involve dysfunction of a type of cell in the arterial wall called the endothelium. Endothelial cells form the interface between the bloodstream and the arterial wall, and dysfunction of these cells is critical to the formation of atherosclerosis, which leads to thickening of the arterial wall and blockage of arteries by lipid-rich plaques. In Europe, 25% of male deaths and 27% of female deaths are attributable to atherosclerosis (2005 BHF Report), and the financial burden of the</li></ul> <p>disease in both direct health care and non health care costs has been estimated at 200 billion € per year. So there are huge human and financial costs. <strong>&nbsp;</strong></p><p><strong>What is “Cellular Engineering”?</strong></p> <p>Cellular Engineering is the application of engineering for understanding and manipulating cellular function. Engineers bring a quantitative view of pathologies such as cardio vascular disease. What we have learned over the past 25 years is that cardiovascular disease is controlled not only by genetic and lifestyle factors but also by mechanical considerations such as pressure forces, frictional forces and stretch forces to which endothelial cells are subjected. Engineers’ expertise is critical to understanding the mechanical environment within the arterial system. Engineers are also uniquely positioned to study the effect of mechanical stimuli on the cells of the arterial wall. One other aspect engineers contribute to is the design and implementation of devices and drug delivery systems to treat the disease. So engineers can bring a highly original approach to biology and medicine.</p><p><img style="float: right; border: 0; margin-left: 20px; margin-right: 20px;" src="/sites/dev/files/upload/abdul_barakat_1.jpg" alt="" width="318" height="268" /></p> <p><strong>Why does this approach bring new possibilities for cell biology?</strong></p> <p>Applying engineering to cell biology promises to provide a much more quantitative and exact understanding. Modern tools, particularly at the micro- and nano-scale, allow us to apply engineering science to cells in much the same way that it has traditionally been applied to various areas such as aeronautics, structures, manufacturing, the environment, etc. This promises to enhance our understanding of normal cellular function as well as dysfunction in disease. Biological engineering also allows the discovery of new therapeutic strategies and thus contributes to extending life expectancy. A goal of the AXA-Ecole Polytechnique Chair is to develop a generation of young engineers sufficiently versed in biology to pose physiologically- relevant questions and to formulate original approaches. Top engineering universities in the United States such as MIT, Stanford and UC Berkeley have invested massively in biological engineering programs. There has also been significant investment in some European countries including the United Kingdom, Switzerland, and the Netherlands. However, this interdisciplinary approach combining biology and engineering has not developed nearly as much in France, and we wish to change that. We believe that we are in the right place to make significant breakthroughs since Ecole Polytechnique attracts some of the best engineers in France who will be future academic and industrial leaders.</p> <p><strong>Do you aim for a change of mindset?</strong></p> <p><strong>&nbsp;</strong>Yes, we aim to change the current mindset that limits interactions between engineers and biologists. We have to convince people that these two fields can go hand in hand and benefit from one another. France has strong expertise in biology and in engineering, but they have remained mostly separate fields. The goal of this new initiative is to build a world-class program which fosters highly interdisciplinary collaboration.</p> <p><strong>How do you plan to overcome differences in ways of thinking?</strong></p><p><strong>&nbsp;</strong>The Chair has several elements. In addition to a strong basic research program, there is an extensive teaching and mentoring component. We are going to launch a new Master’s degree and new classes at the interface between biology and engineering. We need to develop a generation of young engineers who are able to formulate original and quantitative approaches to cardiovascular science. In addition, graduate students with both engineering and biology backgrounds will meet regularly to discuss research papers and learn one another’s vocabulary. We will set up a seminar series, the AXA Distinguished Cellular Engineers seminar series, which will expose our students to out - standing work in this field. Other activities of the Chair will include a European exchange program for our students to get a feel for the type of research in this field in various other European countries as well as public outreach activities with the goal of making high school students aware of the field of Cellular Engineering and the outstanding career opportunities it provides. ■</p><p><img style="float: left; margin-left: 20px; margin-right: 20px;" src="/sites/dev/files/upload/abdul_barakat_4.jpg" alt="" width="94" height="114" /></p><p>Professor Abdul Barakat is researcher at the Ecole Polytechnique’s Hydrodynamics Laboratory (LadHyX) and holder of the <a href="/project/abdul-barakat">AXA Chair for Cardiovascular Cellular Engineering</a>.</p><p>&nbsp;</p><p><span style="text-decoration: underline;">Image 1 :</span> Endothelial cells under the microscope. The blue staining denotes the cell nuclei and&nbsp; the green and red staining denote structural proteins within the cytoplasm (cytoskeletal elements). Early atherosclerosis is characterized by dysfunctional endothelial cells. Image courtesy of cell-wars.blogspot.com </p><p><span style="text-decoration: underline;">Image 2 :</span> Professor Abdul Barakat with his students.&nbsp;</p> <p><span style="text-decoration: underline;">Image 3 :</span> The Chair in Cardiovascular Cellular Engineering is held at Ecole Polytechnique located in Palaiseau, south of Paris, France. Photo credit: Collection François Lacour</p><p>&nbsp;</p><p><img style="vertical-align: middle;" src="/sites/dev/files/upload/abdul_barakat_2_collection_francois_lacour.jpg" alt="Ecole Polytechnique" width="542" height="403" /></p><p>Photo credit: Collection François Lacour</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/0006_barakat_01062010.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Cardiovascular diseases are the leading cause of mortality in the world. The subject is particularly important in the Western world, and its relevance is increasing worldwide. Abdul Barakat has launched a new program at the Ecole Polytechnique to help understand the basic mechanisms of these diseases and to bring engineering expertise to the design of drug delivery devices and strategies that can help to find a cure.

  • Could you briefly describe what are cardiovascular diseases?
  • The two main cardiovascular diseases are coronary heart disease and stroke. In their early stages, these pathologies involve dysfunction of a type of cell in the arterial wall called the endothelium. Endothelial cells form the interface between the bloodstream and the arterial wall, and dysfunction of these cells is critical to the formation of atherosclerosis, which leads to thickening of the arterial wall and blockage of arteries by lipid-rich plaques. In Europe, 25% of male deaths and 27% of female deaths are attributable to atherosclerosis (2005 BHF Report), and the financial burden of the

disease in both direct health care and non health care costs has been estimated at 200 billion € per year. So there are huge human and financial costs.  

What is “Cellular Engineering”?

Cellular Engineering is the application of engineering for understanding and manipulating cellular function. Engineers bring a quantitative view of pathologies such as cardio vascular disease. What we have learned over the past 25 years is that cardiovascular disease is controlled not only by genetic and lifestyle factors but also by mechanical considerations such as pressure forces, frictional forces and stretch forces to which endothelial cells are subjected. Engineers’ expertise is critical to understanding the mechanical environment within the arterial system. Engineers are also uniquely positioned to study the effect of mechanical stimuli on the cells of the arterial wall. One other aspect engineers contribute to is the design and implementation of devices and drug delivery systems to treat the disease. So engineers can bring a highly original approach to biology and medicine.

Why does this approach bring new possibilities for cell biology?

Applying engineering to cell biology promises to provide a much more quantitative and exact understanding. Modern tools, particularly at the micro- and nano-scale, allow us to apply engineering science to cells in much the same way that it has traditionally been applied to various areas such as aeronautics, structures, manufacturing, the environment, etc. This promises to enhance our understanding of normal cellular function as well as dysfunction in disease. Biological engineering also allows the discovery of new therapeutic strategies and thus contributes to extending life expectancy. A goal of the AXA-Ecole Polytechnique Chair is to develop a generation of young engineers sufficiently versed in biology to pose physiologically- relevant questions and to formulate original approaches. Top engineering universities in the United States such as MIT, Stanford and UC Berkeley have invested massively in biological engineering programs. There has also been significant investment in some European countries including the United Kingdom, Switzerland, and the Netherlands. However, this interdisciplinary approach combining biology and engineering has not developed nearly as much in France, and we wish to change that. We believe that we are in the right place to make significant breakthroughs since Ecole Polytechnique attracts some of the best engineers in France who will be future academic and industrial leaders.

Do you aim for a change of mindset?

 Yes, we aim to change the current mindset that limits interactions between engineers and biologists. We have to convince people that these two fields can go hand in hand and benefit from one another. France has strong expertise in biology and in engineering, but they have remained mostly separate fields. The goal of this new initiative is to build a world-class program which fosters highly interdisciplinary collaboration.

How do you plan to overcome differences in ways of thinking?

 The Chair has several elements. In addition to a strong basic research program, there is an extensive teaching and mentoring component. We are going to launch a new Master’s degree and new classes at the interface between biology and engineering. We need to develop a generation of young engineers who are able to formulate original and quantitative approaches to cardiovascular science. In addition, graduate students with both engineering and biology backgrounds will meet regularly to discuss research papers and learn one another’s vocabulary. We will set up a seminar series, the AXA Distinguished Cellular Engineers seminar series, which will expose our students to out - standing work in this field. Other activities of the Chair will include a European exchange program for our students to get a feel for the type of research in this field in various other European countries as well as public outreach activities with the goal of making high school students aware of the field of Cellular Engineering and the outstanding career opportunities it provides. ■

Professor Abdul Barakat is researcher at the Ecole Polytechnique’s Hydrodynamics Laboratory (LadHyX) and holder of the AXA Chair for Cardiovascular Cellular Engineering.

 

Image 1 : Endothelial cells under the microscope. The blue staining denotes the cell nuclei and  the green and red staining denote structural proteins within the cytoplasm (cytoskeletal elements). Early atherosclerosis is characterized by dysfunctional endothelial cells. Image courtesy of cell-wars.blogspot.com

Image 2 : Professor Abdul Barakat with his students. 

Image 3 : The Chair in Cardiovascular Cellular Engineering is held at Ecole Polytechnique located in Palaiseau, south of Paris, France. Photo credit: Collection François Lacour

 

Ecole Polytechnique

Photo credit: Collection François Lacour

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807 /erwan-michel-kerjean-defining-better-financial-cover-for-extreme-events 2011-08-02T00:00:00 Erwan-Michel Kerjean: Defining better financial cover for extreme events <p>As a French economist living in the United&nbsp;States, Erwann Michel-Kerjan is one of the&nbsp;world’s top specialists in disaster risk management. </p> <p>His main area of interest is financial cover&nbsp;for natural disasters.&nbsp;The last few years have been characterised by&nbsp;a series of large-scale natural disasters that&nbsp;have caused hundreds of billions of euros in&nbsp;loss. Unfortunately, it does not look like there&nbsp;will be any improvement in the future. Who will&nbsp;bear these costs? Who will be able to bear&nbsp;them? A closer look at the situation in the United&nbsp;States and the lessons to be learned. </p> <p class="title_09">The number of natural disasters has&nbsp;increased in the United States over the&nbsp;past few years. What have been the&nbsp;consequences for the insurance&nbsp;industry?</p> <p>The September 11 attacks in 2001 and a rapid&nbsp;succession of extreme weather events have&nbsp;led to a crisis for disaster insurance. Financial&nbsp;cover for these risks is now being majorly&nbsp;redefined. Private insurers never anticipated&nbsp;such a string of devastating natural disasters,&nbsp;nor did they forsee the government getting so&nbsp;radically involved.</p><p class="title_09">How has responsibility shifted from&nbsp;insurance companies to states?</p><p>The debate between the public and private&nbsp;sector is heated. Private insurers are looking to&nbsp;increase their premiums to reflect this new era&nbsp;of natural disasters, but regulators are against&nbsp;this, since they seek to minimize the consequences&nbsp;for local economies. Certain major&nbsp;companies, such as insurance giant State&nbsp;Farm in Florida, have left the coastal regions to&nbsp;reduce their exposure to risks. This has strongly&nbsp;reinforced the role of public insurers, who&nbsp;offer low-cost cover. In just three years, after&nbsp;Hurricane Katrina hit in 2005, the insurance&nbsp;corporation Citizens, which is run by the state&nbsp;of Florida, became the number one insurer in&nbsp;the area. That’s a big deal for the US, where&nbsp;insurance is run by the private sector!</p><p class="title_09">Does the growing public sector pose&nbsp;a problem?</p><p>The problem is that these state-run insurers do&nbsp;not have enough reserves to face a new series&nbsp;of natural disasters. Their prices are much too&nbsp;low. If there is a deficit, all insurers operating in&nbsp;Florida will have to pay, as required by law. So&nbsp;it’s not surprising that their private competitors&nbsp;are picking up and leaving.</p><p class="title_09">Several governments you have&nbsp;worked with have put these subjects&nbsp;exposition&nbsp;on the agenda. What solutions have&nbsp;emerged?</p><p>An “alternative” method to traditional insurance&nbsp;is gaining in popularity, by issuing catastrophe&nbsp;bonds, commonly referred to as “cat bonds”,&nbsp;on the financial markets. Last October, the&nbsp;Mexican government sold $290 million in cat&nbsp;bonds to cover exposure to hurricanes and&nbsp;earthquakes. This has become a very active&nbsp;sector as a direct consequence of strong&nbsp;population growth and increasing wealth&nbsp;throughout the world.</p><p class="title_09">But doesn’t placing risk assets&nbsp;on financial markets seem like&nbsp;an unpopular idea since the subprime&nbsp;crisis?</p><p>Maybe, but the index of these bonds has continued&nbsp;to rise since 2005... In any case, the&nbsp;public and private sectors need to develop&nbsp;new solutions for financial cover that is better&nbsp;suited to today’s risks.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/disaster2-person_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> As a French economist living in the United States, Erwann Michel-Kerjan is one of the world’s top specialists in disaster risk management.

His main area of interest is financial cover for natural disasters. The last few years have been characterised by a series of large-scale natural disasters that have caused hundreds of billions of euros in loss. Unfortunately, it does not look like there will be any improvement in the future. Who will bear these costs? Who will be able to bear them? A closer look at the situation in the United States and the lessons to be learned.

The number of natural disasters has increased in the United States over the past few years. What have been the consequences for the insurance industry?

The September 11 attacks in 2001 and a rapid succession of extreme weather events have led to a crisis for disaster insurance. Financial cover for these risks is now being majorly redefined. Private insurers never anticipated such a string of devastating natural disasters, nor did they forsee the government getting so radically involved.

How has responsibility shifted from insurance companies to states?

The debate between the public and private sector is heated. Private insurers are looking to increase their premiums to reflect this new era of natural disasters, but regulators are against this, since they seek to minimize the consequences for local economies. Certain major companies, such as insurance giant State Farm in Florida, have left the coastal regions to reduce their exposure to risks. This has strongly reinforced the role of public insurers, who offer low-cost cover. In just three years, after Hurricane Katrina hit in 2005, the insurance corporation Citizens, which is run by the state of Florida, became the number one insurer in the area. That’s a big deal for the US, where insurance is run by the private sector!

Does the growing public sector pose a problem?

The problem is that these state-run insurers do not have enough reserves to face a new series of natural disasters. Their prices are much too low. If there is a deficit, all insurers operating in Florida will have to pay, as required by law. So it’s not surprising that their private competitors are picking up and leaving.

Several governments you have worked with have put these subjects exposition on the agenda. What solutions have emerged?

An “alternative” method to traditional insurance is gaining in popularity, by issuing catastrophe bonds, commonly referred to as “cat bonds”, on the financial markets. Last October, the Mexican government sold $290 million in cat bonds to cover exposure to hurricanes and earthquakes. This has become a very active sector as a direct consequence of strong population growth and increasing wealth throughout the world.

But doesn’t placing risk assets on financial markets seem like an unpopular idea since the subprime crisis?

Maybe, but the index of these bonds has continued to rise since 2005... In any case, the public and private sectors need to develop new solutions for financial cover that is better suited to today’s risks.

]]>
808 /david-stephenson-tracking-future-windstorms-in-europe 2011-08-02T00:00:00 David Stephenson: Tracking future windstorms in Europe <p>Professor David Stephenson is an internationally renowned expert of the statistical analysis of weather and climate. He has developped advanced methodologies that provide deeper understanding of climate variations and improve the quality of forecasts. Since 1998, he has worked with catastrophe modellers in the global reinsurance industry. In 2006, he was also a key founding member of the Willis Research Network, the world’s largest partnership between academia and insurance companies. Professor Stephenson has received Axa funding for his RACEWIN project, which will assess the impact of climate change on European windstorms. </p><p><img style="margin-left: 20px; margin-right: 20px; float: right;" src="/sites/dev/files/upload/communication/tempete.jpg" alt="" width="270" height="405" /></p> <p><strong>Climate change is a vast area of research. But how precise can mathematical projections be? </strong></p> <p>We can now make adaptive forecasting of climate change. And instead of just saying “by the end of the XXIe Century, it will be 5 degrees warmer”, we are now trying to make predictions for the next year or the next ten years. It is important for the insurance sector because it allows us to look at the changing rate of hazards. Historical catastrophe models assume that the risk is stationary, but we know that weather events and their rates do change in time. So our predictions get more dynamic. </p> <p><strong>What do we know of the impact of climate change on storms in Europe? </strong></p> <p>I'm one of the lead authors for the chapter on “Regional Climate and Extremes” in the next Intergovernmental Panel on Climate Change (IPCC) report. One of our problems today is making statements on that more local scale for the future. Today, the different models get very different answers. </p> <p><strong>&nbsp;To what extent can we really predict a storm today ? </strong></p> <p>There is some predictability of the strong wind patterns in the atmosphere at least a month ahead, a couple of months maximum. We can say whether there is a higher risk of having storms, but we cannot predict exactly where it is going to happen or how many storms there will be. For example, the severe storms that impacted France in December 1999 were due to the persistence of a strong upper level jet stream. We know that this condition provides the energy needed for explosive growth of damaging windstorms. But we could not go further. It is a probabilistic prediction. </p> <p><strong>&nbsp;Your RACEWIN project aims at improving these projections. How will you proceed ? </strong></p> <p>&nbsp;Starting in October, we will collaborate with the UK Met Office to statistically analyse the storm tracks (which trace the central pressure of a storm all along its way) from a set of high-resolution regional climate model projections for the 21<sup>st</sup> century. This will allow us to better quantify trends and clustering in future European windstorms. Clustering measures the tendency of storms to occur together over a short time in a particular region, rather than being randomly distributed. We will look at the dependency between successive storms and between extreme wind speeds and extreme precipitation. In addition, our project will set up a European windstorms research network to help bring together critical mass in this important area of climate science.<em> <br /></em><br />&nbsp;<em>* Note : the IPPC is a scientific intergovernmental body of the United Nations, in charge of assessing the risks of climate change. Its fifth report, a reference document, is due in 2014.</em></p><p><img style="margin-left: 20px; margin-right: 20px; float: left;" src="/sites/dev/files/upload/communication/stephenson.jpg" alt="" width="97" height="120" />Professor David Stephenson, Director of Exeter Climate Systems University of Exeter, UK<br /><br />Principal investigator of the AXA RACEWIN project :<br /> <a href="/project/david-stephenson">European Windstorms in a Changing Climate: Storm Tracks, Clustering and Multi-peril Extremes</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/stephenson.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Professor David Stephenson is an internationally renowned expert of the statistical analysis of weather and climate. He has developped advanced methodologies that provide deeper understanding of climate variations and improve the quality of forecasts. Since 1998, he has worked with catastrophe modellers in the global reinsurance industry. In 2006, he was also a key founding member of the Willis Research Network, the world’s largest partnership between academia and insurance companies. Professor Stephenson has received Axa funding for his RACEWIN project, which will assess the impact of climate change on European windstorms.

Climate change is a vast area of research. But how precise can mathematical projections be?

We can now make adaptive forecasting of climate change. And instead of just saying “by the end of the XXIe Century, it will be 5 degrees warmer”, we are now trying to make predictions for the next year or the next ten years. It is important for the insurance sector because it allows us to look at the changing rate of hazards. Historical catastrophe models assume that the risk is stationary, but we know that weather events and their rates do change in time. So our predictions get more dynamic.

What do we know of the impact of climate change on storms in Europe?

I'm one of the lead authors for the chapter on “Regional Climate and Extremes” in the next Intergovernmental Panel on Climate Change (IPCC) report. One of our problems today is making statements on that more local scale for the future. Today, the different models get very different answers.

 To what extent can we really predict a storm today ?

There is some predictability of the strong wind patterns in the atmosphere at least a month ahead, a couple of months maximum. We can say whether there is a higher risk of having storms, but we cannot predict exactly where it is going to happen or how many storms there will be. For example, the severe storms that impacted France in December 1999 were due to the persistence of a strong upper level jet stream. We know that this condition provides the energy needed for explosive growth of damaging windstorms. But we could not go further. It is a probabilistic prediction.

 Your RACEWIN project aims at improving these projections. How will you proceed ?

 Starting in October, we will collaborate with the UK Met Office to statistically analyse the storm tracks (which trace the central pressure of a storm all along its way) from a set of high-resolution regional climate model projections for the 21st century. This will allow us to better quantify trends and clustering in future European windstorms. Clustering measures the tendency of storms to occur together over a short time in a particular region, rather than being randomly distributed. We will look at the dependency between successive storms and between extreme wind speeds and extreme precipitation. In addition, our project will set up a European windstorms research network to help bring together critical mass in this important area of climate science.

 * Note : the IPPC is a scientific intergovernmental body of the United Nations, in charge of assessing the risks of climate change. Its fifth report, a reference document, is due in 2014.

Professor David Stephenson, Director of Exeter Climate Systems University of Exeter, UK

Principal investigator of the AXA RACEWIN project :
European Windstorms in a Changing Climate: Storm Tracks, Clustering and Multi-peril Extremes

]]>
809 /sophie-murray-the-space-weather 2011-08-02T00:00:00 Sophie Murray: the Space weather <p><strong>Could you briefly describe the goals of your research project?</strong> </p> <p>I study the physics of the Sun, specifically looking at sunspots and solar flares. My research topic is ’Understanding the complex magnetic topologies of solar active regions’. Basically what this means is that I am hoping to better predict solar flares by looking at the magnetic fields of sunspots. I use data from satellites that observe the Sun to look at how the magnetic field changes over time before a flare occurs and then how it is changed by the flare. This has implications on Earth due to space weather, which can disrupt communications and electronics both on the ground and on satellites. </p> <p><strong>What is “space weather”?</strong> <img style="float: right; margin-left: 20px; margin-right: 20px;" src="/sites/dev/files/upload/communication/terre_et_soleil.jpg" alt="Crédit photo NASA/courtesy of nasaimages.org" width="334" height="260" /></p> <p>Space weather describes the interaction of magnetic fields and particles, which have been ejected from the Sun, with the Earth’s upper atmosphere and surrounding magnetic field. The particles form what is known as the solar wind. As the solar wind travels through the solar system, the Earth’s magnetic field acts as an obstacle and deflects the particles around the planet, rather than bombarding the atmosphere or surface. </p> <p>Space weather has a number of effects on the space surrounding the Earth; the most re cognisable might be the aurorae, also called the ’Northern Lights’. Sometimes not all the par ticles are deflected and they launch downwards into our atmosphere at the polar regions where they interact, resulting in emissions that give the aurora’s multicoloured glowing appearance in the skies. In periods of higher activity on the Sun, many more solar flares occur than normal, increasing the amount of particles and radio emissions ejected from the Sun. This increased activity can cause geomagnetic storms, which are formed when the solar flare causes the solar wind to hit the Earth’s magnetic field much more strongly, causing a temporary disturbance in the upper atmosphere. This can cause severe disruptions to communications and power grids across the globe. The increased activity can also cause aurorae to form in even lower latitudes, as far down as the equator in very strong events. </p> <p><strong>What are the impacts of space weather on aviation and space flight? </strong></p> <p>In terms of aviation, flight crews, passengers and on board electronics are all under direct exposure to space weather on transpolar flights. Here, they are exposed to higher levels of radiation, which increases during periods of high solar activity. Too much exposure can cause illness so flight crews must limit the number of flights they make yearly. Radio communications between pilots and the ground can also be affected, causing diverted flights if a storm occurs. The more accurately we can predict these storms, the better for the airlines operating these routes. Astronauts’ lives can be threatened due to the high dosages of solar radiation they are exposed to and to the energetic particles from the Sun bombarding the space shuttle. The spacecraft shielding and protection from their spacesuits must be sufficient or an increased dose of radiation and particles due to a solar flare could be lethal. Solar activity monitoring systems are imperative to keep the astronauts safe. </p> <p><strong>Why does solar activity affect human technologies such as GPS, satellites, or weather monitoring?</strong></p> <p><img style="float: left; margin-left: 20px; margin-right: 20px;" src="/sites/dev/files/upload/communication/suns-impacts_earth.jpg" alt="Crédit photo : NASA/Goddard Space Flight Center Scientific Visualization Studio." width="351" height="226" />The particles accelerated during solar flares can damage and degrade electronics on board spacecraft. For example, microchips can be damaged, causing errors in software commands. Geomagnetic storms can also blind sensors on board the craft and interfere with electronics. Sufficient shielding for instruments on board satellites is necessary to prevent degradation and is an area of continuous research to improve the materials used. The signal propagation of GPS and other satellite navigational systems are also affected in a similar fashion, as well as the disruption to the electronics on board the satellites. The impact of this on the ground could be wide-spread, disrupting shortwave radio broadcasts, mobile phone networks and transport navigation systems. </p> <p><strong>What are the long-term perspectives on that topic? </strong></p> <p>In order to minimise the impact of space weather on our technologies, a solar activity-forecasting infrastructure must be developed between governmental and commercial sectors. But first, we as scientists must understand the fundamental physical processes involved in driving space weather, such as sunspot magnetic fields. The more we know about these processes, the more we can improve statistical models to predict when a flare will occur. The accuracy of prediction methods available presently needs to be increased, in order to be able to predict solar activity over shorter time scales of hours rather than days. Scientists do need as near-real time solar data as possible for space weather predictions. ■</p><p><em>Sunspots are regions on the surface of the Sun that appear as dark spots and have very strong magnetic field. Solar flares are a very releases of large amounts of energy, which is stored in the solar atmosphere. The flares can hurtle towards Earth in the form of very energetic particles, X-rays, ultraviolet and radio emissions, amongst others.</em></p><p><span style="text-decoration: underline;">Image 1 :</span> Crédit photo NASA/courtesy of nasaimages.org<br />Image of the sun taken by the NASA “SOHO” spacecraft in 2003. </p><p><span style="text-decoration: underline;">Image 2 :</span> Collection of images depicting the Sun’s impact on Earth: starting with a solar flare eruption on the Sun on the left, causing changes in the Earth’s atmosphere in the centre leading to the occurrence of the aurora in Alaska in the image on the right. </p><p>&nbsp;</p> <p><a href="/project/sophie-murray"><img style="float: left; margin-left: 20px; margin-right: 20px;" src="/sites/dev/files/upload/communication/sophie_murray_0.jpg" alt="" width="115" height="138" /></a></p><p>Sophie Murray is a AXA PhD fellow at the School of Physics, Trinity College Dublin (Ireland).</p><p><a class="link_01" title=" Sophie MURRAY, AXA Research Fellow" href="/project/sophie-murray">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/sophie_murray_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Could you briefly describe the goals of your research project?

I study the physics of the Sun, specifically looking at sunspots and solar flares. My research topic is ’Understanding the complex magnetic topologies of solar active regions’. Basically what this means is that I am hoping to better predict solar flares by looking at the magnetic fields of sunspots. I use data from satellites that observe the Sun to look at how the magnetic field changes over time before a flare occurs and then how it is changed by the flare. This has implications on Earth due to space weather, which can disrupt communications and electronics both on the ground and on satellites.

What is “space weather”? Crédit photo NASA/courtesy of nasaimages.org

Space weather describes the interaction of magnetic fields and particles, which have been ejected from the Sun, with the Earth’s upper atmosphere and surrounding magnetic field. The particles form what is known as the solar wind. As the solar wind travels through the solar system, the Earth’s magnetic field acts as an obstacle and deflects the particles around the planet, rather than bombarding the atmosphere or surface.

Space weather has a number of effects on the space surrounding the Earth; the most re cognisable might be the aurorae, also called the ’Northern Lights’. Sometimes not all the par ticles are deflected and they launch downwards into our atmosphere at the polar regions where they interact, resulting in emissions that give the aurora’s multicoloured glowing appearance in the skies. In periods of higher activity on the Sun, many more solar flares occur than normal, increasing the amount of particles and radio emissions ejected from the Sun. This increased activity can cause geomagnetic storms, which are formed when the solar flare causes the solar wind to hit the Earth’s magnetic field much more strongly, causing a temporary disturbance in the upper atmosphere. This can cause severe disruptions to communications and power grids across the globe. The increased activity can also cause aurorae to form in even lower latitudes, as far down as the equator in very strong events.

What are the impacts of space weather on aviation and space flight?

In terms of aviation, flight crews, passengers and on board electronics are all under direct exposure to space weather on transpolar flights. Here, they are exposed to higher levels of radiation, which increases during periods of high solar activity. Too much exposure can cause illness so flight crews must limit the number of flights they make yearly. Radio communications between pilots and the ground can also be affected, causing diverted flights if a storm occurs. The more accurately we can predict these storms, the better for the airlines operating these routes. Astronauts’ lives can be threatened due to the high dosages of solar radiation they are exposed to and to the energetic particles from the Sun bombarding the space shuttle. The spacecraft shielding and protection from their spacesuits must be sufficient or an increased dose of radiation and particles due to a solar flare could be lethal. Solar activity monitoring systems are imperative to keep the astronauts safe.

Why does solar activity affect human technologies such as GPS, satellites, or weather monitoring?

Crédit photo : NASA/Goddard Space Flight Center Scientific Visualization Studio.The particles accelerated during solar flares can damage and degrade electronics on board spacecraft. For example, microchips can be damaged, causing errors in software commands. Geomagnetic storms can also blind sensors on board the craft and interfere with electronics. Sufficient shielding for instruments on board satellites is necessary to prevent degradation and is an area of continuous research to improve the materials used. The signal propagation of GPS and other satellite navigational systems are also affected in a similar fashion, as well as the disruption to the electronics on board the satellites. The impact of this on the ground could be wide-spread, disrupting shortwave radio broadcasts, mobile phone networks and transport navigation systems.

What are the long-term perspectives on that topic?

In order to minimise the impact of space weather on our technologies, a solar activity-forecasting infrastructure must be developed between governmental and commercial sectors. But first, we as scientists must understand the fundamental physical processes involved in driving space weather, such as sunspot magnetic fields. The more we know about these processes, the more we can improve statistical models to predict when a flare will occur. The accuracy of prediction methods available presently needs to be increased, in order to be able to predict solar activity over shorter time scales of hours rather than days. Scientists do need as near-real time solar data as possible for space weather predictions. ■

Sunspots are regions on the surface of the Sun that appear as dark spots and have very strong magnetic field. Solar flares are a very releases of large amounts of energy, which is stored in the solar atmosphere. The flares can hurtle towards Earth in the form of very energetic particles, X-rays, ultraviolet and radio emissions, amongst others.

Image 1 : Crédit photo NASA/courtesy of nasaimages.org
Image of the sun taken by the NASA “SOHO” spacecraft in 2003.

Image 2 : Collection of images depicting the Sun’s impact on Earth: starting with a solar flare eruption on the Sun on the left, causing changes in the Earth’s atmosphere in the centre leading to the occurrence of the aurora in Alaska in the image on the right.

 

Sophie Murray is a AXA PhD fellow at the School of Physics, Trinity College Dublin (Ireland).

Click here to find out more about this research supported by the AXA Research Fund

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811 /pr-thomas-kirkwood-ageing-is-everyones-concern 2011-08-02T00:00:00 Pr Thomas Kirkwood: Ageing is everyone's concern <p>Pr Thomas Kirkwood, Director of the Institute for Ageing and Health at Newcastle University.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/kirkwood-thomas.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Pr Thomas Kirkwood, Director of the Institute for Ageing and Health at Newcastle University.

]]>
799 /pierre-andre-chiappori-quoted-axa-research-fund-as-a-model-of-corporate-funding-of-research 2011-07-07T00:00:00 Pierre-André Chiappori quoted AXA Research Fund as a model of corporate funding of research <p>&nbsp;</p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <img src="/sites/dev/files/upload/communication/logo_institut-entreprise.jpg" alt="" width="226" height="78" /></p><p>The study can be downloaded <a href="http://www.institut-entreprise.fr/fileadmin/Docs_PDF/travaux_reflexions/Notes_de_Institut/financement_enseignement_web.pdf">here</a> (french only).</p><p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <img src="/sites/dev/files/upload/communication/logo-bfm-radio-eco.jpg" alt="" width="189" height="83" /></p><p>The interview can be listened <a href="http://podcast.bfmradio.fr/channel11/20110706_interview_2.mp3">here</a> (french only).</p><p>You can also download the english summary of this study below.</p><p>&nbsp;</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/chiappori.jpg" alt="" title="" class="imagecache imagecache-contentimage" />  

                         

The study can be downloaded here (french only).

                              

The interview can be listened here (french only).

You can also download the english summary of this study below.

 

 

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797 /results-of-2011-post-doc-and-phd-fellowship-campaigns-are-online 2011-07-01T00:00:00 Results of 2011 Post-Doc and PhD fellowship campaigns are online! <p>We thank all the applicants for having participated to these campaigns. We have received a very high number of applications and were very impressed by their excellent quality (290 for the PhD fellowships and 280 for the Post-doc fellowships). The selection process for these campaigns were therefore highly competitive (10% for the PhD and 7% for the Post-Doc).</p><p>The results are available <a href="http://www.axa-research.org/publication-of-results">here</a>.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/bulles.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> We thank all the applicants for having participated to these campaigns. We have received a very high number of applications and were very impressed by their excellent quality (290 for the PhD fellowships and 280 for the Post-doc fellowships). The selection process for these campaigns were therefore highly competitive (10% for the PhD and 7% for the Post-Doc).

The results are available here.

 

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793 /echo-magazine 2011-05-12T00:00:00 Echo Magazine <p><br /><span style="text-decoration: underline;"><strong>Editorial by Dr Jean-Marie Robine</strong></span><br /><br />The decrease in old age mortality started in the 1930s in the most advanced countries but it was only noticed in the 1970s. </p><p>It led to the formulation of three main theories about the expected changes in the health status of the populations, the compression of morbidity, the pandemic of disability, and the dynamic equilibrium.</p><p> According to the first theory morbidity is compressed at the end of life due to the adoption of<br />healthy behaviors and the hypothesis of strong limitations on longevity. According to the second theory, we are merely keeping the sick people alive longer increasing the prevalence of chronic diseases and disability. </p><p>According to the third theory we are keeping the sick people alive longer but we are also slowing down the development of the chronic diseases and postponing the onset of disability. However, the most surprising observation during the last decades was the strong decrease in oldest old mortality, leading to an unexpected increase in the number of nonagenarians and centenarians.</p><p> The previous theories do not help to understand the relationship between the level of mortality selection (how easy or difficult it is to survive to a given age) and the functional health status of the survivors (i.e. the people reaching this given age). </p><p>This is the new frontier in healthy and active longevity research and it where the 5-Country Oldest Old Project (5-COOP) is going with the help of AXA Research Fund.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/une-echo5.jpg" alt="" title="" class="imagecache imagecache-contentimage" />
Editorial by Dr Jean-Marie Robine

The decrease in old age mortality started in the 1930s in the most advanced countries but it was only noticed in the 1970s.

It led to the formulation of three main theories about the expected changes in the health status of the populations, the compression of morbidity, the pandemic of disability, and the dynamic equilibrium.

According to the first theory morbidity is compressed at the end of life due to the adoption of
healthy behaviors and the hypothesis of strong limitations on longevity. According to the second theory, we are merely keeping the sick people alive longer increasing the prevalence of chronic diseases and disability.

According to the third theory we are keeping the sick people alive longer but we are also slowing down the development of the chronic diseases and postponing the onset of disability. However, the most surprising observation during the last decades was the strong decrease in oldest old mortality, leading to an unexpected increase in the number of nonagenarians and centenarians.

The previous theories do not help to understand the relationship between the level of mortality selection (how easy or difficult it is to survive to a given age) and the functional health status of the survivors (i.e. the people reaching this given age).

This is the new frontier in healthy and active longevity research and it where the 5-Country Oldest Old Project (5-COOP) is going with the help of AXA Research Fund.

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810 /echo-5-march-2011 2011-04-20T00:00:00 ECHO 5 - March 2011 <p><br /><span style="text-decoration: underline;"><strong>Editorial by Dr Jean-Marie Robine</strong></span><br /><br />The decrease in old age mortality started in the 1930s in the most advanced countries but it was only noticed in the 1970s. </p><p>It led to the formulation of three main theories about the expected changes in the health status of the populations, the compression of morbidity, the pandemic of disability, and the dynamic equilibrium.</p><p>According to the first theory morbidity is compressed at the end of life due to the adoption of<br />healthy behaviors and the hypothesis of strong limitations on longevity. According to the second theory, we are merely keeping the sick people alive longer increasing the prevalence of chronic diseases and disability. </p><p>According to the third theory we are keeping the sick people alive longer but we are also slowing down the development of the chronic diseases and postponing the onset of disability. However, the most surprising observation during the last decades was the strong decrease in oldest old mortality, leading to an unexpected increase in the number of nonagenarians and centenarians.</p><p>The previous theories do not help to understand the relationship between the level of mortality selection (how easy or difficult it is to survive to a given age) and the functional health status of the survivors (i.e. the people reaching this given age). </p><p>This is the new frontier in healthy and active longevity research and it where the 5-Country Oldest Old Project (5-COOP) is going with the help of AXA Research Fund.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/une-echo5_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" />
Editorial by Dr Jean-Marie Robine

The decrease in old age mortality started in the 1930s in the most advanced countries but it was only noticed in the 1970s.

It led to the formulation of three main theories about the expected changes in the health status of the populations, the compression of morbidity, the pandemic of disability, and the dynamic equilibrium.

According to the first theory morbidity is compressed at the end of life due to the adoption of
healthy behaviors and the hypothesis of strong limitations on longevity. According to the second theory, we are merely keeping the sick people alive longer increasing the prevalence of chronic diseases and disability.

According to the third theory we are keeping the sick people alive longer but we are also slowing down the development of the chronic diseases and postponing the onset of disability. However, the most surprising observation during the last decades was the strong decrease in oldest old mortality, leading to an unexpected increase in the number of nonagenarians and centenarians.

The previous theories do not help to understand the relationship between the level of mortality selection (how easy or difficult it is to survive to a given age) and the functional health status of the survivors (i.e. the people reaching this given age).

This is the new frontier in healthy and active longevity research and it where the 5-Country Oldest Old Project (5-COOP) is going with the help of AXA Research Fund.

]]>
792 /brand-new-facebook-page 2011-03-25T00:00:00 Brand new Facebook page! <p>Watch out the brand new page AXA Research Alumni : a good way to stay tuned with our AXA fellows, young and seniors academics from 20 countries.&nbsp; </p><p><a href="https://www.facebook.com/pages/AXA-Research-Alumni/186009014776969?sk=wall">Click on "Like" and be part of our community!</a></p><p>You will see our latest updates, it a enthusiastic yet scientific page!</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/facebook2.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Watch out the brand new page AXA Research Alumni : a good way to stay tuned with our AXA fellows, young and seniors academics from 20 countries. 

Click on "Like" and be part of our community!

You will see our latest updates, it a enthusiastic yet scientific page!

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718 /march-21st-british-council-science-po-conference-on-uncertainty-in-decision-making-with-denis 2011-03-21T00:00:00 March 21st : British Council -Science Po conference on Uncertainty in Decision Making with Denis Duverne ! <div class="box_columns_02 clear_fix"><div class="column_01"> <div class="event_intro clear_fix"><strong>The British Council in France and the Institute for Sustainable Development and International Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion: “Scientific uncertainty in decision-making”</strong> </div> <p><strong><em>The British Council in France and the </em></strong><em><em>Institute for Sustainable</em></em><strong><em> Development and <em><em>International</em></em></em></strong><em> <strong>Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion:</strong></em><strong><em> <br /></em></strong></p> <p><strong>“Scientific uncertainty in decision-making”<em> <br /></em></strong></p> <p><strong><em>Panel members:</em> Professor Sir Michael Rawlins, </strong>Chairman of the National Institute for Health and Clinical Excellence (UK)</p> <p><strong>Denis Duverne, </strong>Deputy Chief Executive Officer of AXA </p> <p>The panel will be chaired by <strong>Laurence Tubiana</strong>, Director of the Institute for Sustainable Development and International Relations (IDDRI) </p> <p><strong>Monday 21<sup>st</sup> March, 2011 – from 6:00 p.m to 8:00 p.m</strong><em> Amphithéâtre Boutmy, Sciences Po, 27, rue Saint Guillaume, 75007 Paris</em></p> <p>Recent debate on the role of human activity in climate change, on the efficacy of the H1N1 vaccine or on renewable energies policy, has brought the concept of scientific uncertainty to the forefront of public and media attention. But this debate has also brought to light the misunderstanding surrounding the concept and the dangers of its possible misappropriation.</p> <p>With decision-makers required to take ever-increasing account of scientific uncertainties, the conference’s panellists will discuss their own experience of high-level decision-making and will explain how they have had to deal with scientific uncertainty whilst making strategic decisions. How do decision-makers – be they in the political, public or economic sphere – make decisions when they are confronted with uncertainty? What lessons can be drawn from recent experiences in France and in the United Kingdom where uncertainty has played a major role in supporting or discrediting a given position? What are the respective roles and responsibilities of scientists and the media in the public understanding of scientific uncertainty?</p> <p>Professor Sir Michael Rawlins and Denis Duverne will address these questions and will then open up the discussion to the public.<strong><br /></strong></p><p><strong>Please register for the debate on <a href="http://www.iddri.org/Activites/Conferences-internationales/Scientific-uncertainty-in-decision-making/">IDDRI website</a> or by email to Julie Cohen – <a href="mailto:julie.cohen@iddri.org">julie.cohen@iddri.org</a> </strong></p> <p class="Default"><strong>Professor Sir Michael Rawlins</strong> has been chairman of the National Institute of Health &amp; Clinical Excellence (NICE) since its formation in 1999. NICE is an independent organisation responsible for providing national guidance on promoting good health and preventing and treating ill health. Sir Michael Rawlins is also Honorary Professor at the London School of Hygiene and Tropical Medicine, University of London, and Emeritus Professor at the University of Newcastle upon Tyne. He was the Ruth and Lionel Jacobson Professor of Clinical Pharmacology at the University of Newcastle upon Tyne from 1973 to 2006 .At the same time he held the position of consultant physician and consultant clinical pharmacologist to the Newcastle Hospitals NHS Trust. He was vice-chairman (1987-1992) and chairman (1993-1998) of the Committee on Safety of Medicines; and chairman of the Advisory Council on the Misuse of Drugs (1998 - 2008).<em></em></p><p class="Default"><em> </em><strong>Denis Duverne</strong> has been Deputy Chief Executive Officer of AXA, in charge of Finance, Strategy and Operations since April 2010. He is a graduate of the École des Hautes Études Commerciales (HEC). After graduating from the École Nationale d'Administration (ENA), he started his career in 1984 as commercial counsellor for the French Consulate General in New York before becoming director of the Corporate Taxes Department for the French Ministry of Finance in 1986. In 1988, he became Deputy Assistant Secretary for Tax Policy for the French Ministry of Finance and, in 1991, he was appointed Corporate Secretary of Compagnie Financière IBI. In 1992, he became a member of the Executive Committee of Banque Colbert, in charge of operations. In 1995, Denis Duverne joined the AXA Group and assumed responsibility for supervision of AXA's operations in the US and the UK and managed the reorganization of AXA companies in Belgium and the United Kingdom. Since February 2003, Denis Duverne has been a member of the AXA Management Board. From February 2003 to December 2009, he was the Management Board member in charge of Finance, Control and Strategy. From January 2010 to April 2010, he assumed broader responsibilities as Management Board member in charge of Finance, Strategy and Operations.</p> <p> <strong>Laurence Tubiana</strong> is founder of the Institute for Sustainable Development and International Relations&nbsp;(IDDRI) in Paris. She follows and participates in the international negotiations on climate change, in which IDDRI is highly involved. She is also professor and director of the Sustainable Development Centre at Sciences Po Paris. From May 2009 to May 2010, Laurence Tubiana was asked to set up the new direction of Global Publics Goods of the French Ministry of Foreign and European Affairs. She is a member of several scientific boards of major research institutions such as the French Agricultural Research Centre for International Development&nbsp;(CIRAD), the India Council for Sustainable Development and the China Council for International Cooperation on Environment and Development. From 1997 to 2002, Laurence Tubiana served as senior advisor to the Prime Minister, Lionel Jospin, on environmental issues and conducted a number of international negotiations on this subject. She was also member of the French Council of Economic Analysis and research director for the French National Institute for Agricultural Research&nbsp;(INRA). She has been a representative of the European NGOs at the World Bank and directed the French-based NGO Solagral. Founder of the journal <em>Le Courrier de la Planète,</em> she has published a number of articles and books on environment, development and international issues. Since 2007, she has co-directed the publication of the annual review <em>Sustainable Development in Action – A Planet for Life</em>.</p></div></div><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/logo_bc_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" />
The British Council in France and the Institute for Sustainable Development and International Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion: “Scientific uncertainty in decision-making”

The British Council in France and the Institute for Sustainable Development and International Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion:

“Scientific uncertainty in decision-making”

Panel members: Professor Sir Michael Rawlins, Chairman of the National Institute for Health and Clinical Excellence (UK)

Denis Duverne, Deputy Chief Executive Officer of AXA

The panel will be chaired by Laurence Tubiana, Director of the Institute for Sustainable Development and International Relations (IDDRI)

Monday 21st March, 2011 – from 6:00 p.m to 8:00 p.m Amphithéâtre Boutmy, Sciences Po, 27, rue Saint Guillaume, 75007 Paris

Recent debate on the role of human activity in climate change, on the efficacy of the H1N1 vaccine or on renewable energies policy, has brought the concept of scientific uncertainty to the forefront of public and media attention. But this debate has also brought to light the misunderstanding surrounding the concept and the dangers of its possible misappropriation.

With decision-makers required to take ever-increasing account of scientific uncertainties, the conference’s panellists will discuss their own experience of high-level decision-making and will explain how they have had to deal with scientific uncertainty whilst making strategic decisions. How do decision-makers – be they in the political, public or economic sphere – make decisions when they are confronted with uncertainty? What lessons can be drawn from recent experiences in France and in the United Kingdom where uncertainty has played a major role in supporting or discrediting a given position? What are the respective roles and responsibilities of scientists and the media in the public understanding of scientific uncertainty?

Professor Sir Michael Rawlins and Denis Duverne will address these questions and will then open up the discussion to the public.

Please register for the debate on IDDRI website or by email to Julie Cohen – julie.cohen@iddri.org

Professor Sir Michael Rawlins has been chairman of the National Institute of Health & Clinical Excellence (NICE) since its formation in 1999. NICE is an independent organisation responsible for providing national guidance on promoting good health and preventing and treating ill health. Sir Michael Rawlins is also Honorary Professor at the London School of Hygiene and Tropical Medicine, University of London, and Emeritus Professor at the University of Newcastle upon Tyne. He was the Ruth and Lionel Jacobson Professor of Clinical Pharmacology at the University of Newcastle upon Tyne from 1973 to 2006 .At the same time he held the position of consultant physician and consultant clinical pharmacologist to the Newcastle Hospitals NHS Trust. He was vice-chairman (1987-1992) and chairman (1993-1998) of the Committee on Safety of Medicines; and chairman of the Advisory Council on the Misuse of Drugs (1998 - 2008).

Denis Duverne has been Deputy Chief Executive Officer of AXA, in charge of Finance, Strategy and Operations since April 2010. He is a graduate of the École des Hautes Études Commerciales (HEC). After graduating from the École Nationale d'Administration (ENA), he started his career in 1984 as commercial counsellor for the French Consulate General in New York before becoming director of the Corporate Taxes Department for the French Ministry of Finance in 1986. In 1988, he became Deputy Assistant Secretary for Tax Policy for the French Ministry of Finance and, in 1991, he was appointed Corporate Secretary of Compagnie Financière IBI. In 1992, he became a member of the Executive Committee of Banque Colbert, in charge of operations. In 1995, Denis Duverne joined the AXA Group and assumed responsibility for supervision of AXA's operations in the US and the UK and managed the reorganization of AXA companies in Belgium and the United Kingdom. Since February 2003, Denis Duverne has been a member of the AXA Management Board. From February 2003 to December 2009, he was the Management Board member in charge of Finance, Control and Strategy. From January 2010 to April 2010, he assumed broader responsibilities as Management Board member in charge of Finance, Strategy and Operations.

Laurence Tubiana is founder of the Institute for Sustainable Development and International Relations (IDDRI) in Paris. She follows and participates in the international negotiations on climate change, in which IDDRI is highly involved. She is also professor and director of the Sustainable Development Centre at Sciences Po Paris. From May 2009 to May 2010, Laurence Tubiana was asked to set up the new direction of Global Publics Goods of the French Ministry of Foreign and European Affairs. She is a member of several scientific boards of major research institutions such as the French Agricultural Research Centre for International Development (CIRAD), the India Council for Sustainable Development and the China Council for International Cooperation on Environment and Development. From 1997 to 2002, Laurence Tubiana served as senior advisor to the Prime Minister, Lionel Jospin, on environmental issues and conducted a number of international negotiations on this subject. She was also member of the French Council of Economic Analysis and research director for the French National Institute for Agricultural Research (INRA). She has been a representative of the European NGOs at the World Bank and directed the French-based NGO Solagral. Founder of the journal Le Courrier de la Planète, she has published a number of articles and books on environment, development and international issues. Since 2007, she has co-directed the publication of the annual review Sustainable Development in Action – A Planet for Life.

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784 /appointment-of-the-new-head-of-the-axa-research-fund 2011-03-07T00:00:00 Appointment of the new Head of the AXA Research Fund <p>He replaces Anne-Juliette Hermant, appointed Global Head of Learning and Development.<br /><br />“<em>I would like to thank Anne-Juliette for her engagement since the creation of the AXA Research Fund in 2008. Thanks to her determination, more than 200 researchers are currently working to enhance understanding and prevention of risks throughout the world with the support of AXA. Looking at Godefroy’s experience and his great knowledge of the academic world, I am confident that he will further develop the AXA Research Fund in full accordance with AXA’s corporate responsibility strategy. We welcome him to the Group and wish him every success in his new role.</em>” said Guillaume Floquet, Deputy Head of AXA Group Human Resources.</p><p><br /><span style="text-decoration: underline;">Biography</span><br />Godefroy Beauvallet, 39, graduated from Ecole Polytechnique in 1994 and from Télécom ParisTech in 1997. He began his career as an IT Project Manager with Gemplus, then became Associate Banker for the European Bank for Reconstruction and Development (EBRD). He joined the French Ministry of Industry in 1997. Between 2000 and 2002, he was Adviser to the Minister for Public Service and State Reform, Michel Sapin. In 2002, he became Assistant Professor and Team Manager at Telecom ParisTech. In 2007, he became CFO and Deputy CEO of Institut Télécom, a group of 6 French engineering and management schools specialized in IT. He is the author of several books and many scientific papers about the use of digital groupware tools in project management and Lean Management.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/godefroybeauvallet_copyright_franck_dunouau.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> He replaces Anne-Juliette Hermant, appointed Global Head of Learning and Development.

I would like to thank Anne-Juliette for her engagement since the creation of the AXA Research Fund in 2008. Thanks to her determination, more than 200 researchers are currently working to enhance understanding and prevention of risks throughout the world with the support of AXA. Looking at Godefroy’s experience and his great knowledge of the academic world, I am confident that he will further develop the AXA Research Fund in full accordance with AXA’s corporate responsibility strategy. We welcome him to the Group and wish him every success in his new role.” said Guillaume Floquet, Deputy Head of AXA Group Human Resources.


Biography
Godefroy Beauvallet, 39, graduated from Ecole Polytechnique in 1994 and from Télécom ParisTech in 1997. He began his career as an IT Project Manager with Gemplus, then became Associate Banker for the European Bank for Reconstruction and Development (EBRD). He joined the French Ministry of Industry in 1997. Between 2000 and 2002, he was Adviser to the Minister for Public Service and State Reform, Michel Sapin. In 2002, he became Assistant Professor and Team Manager at Telecom ParisTech. In 2007, he became CFO and Deputy CEO of Institut Télécom, a group of 6 French engineering and management schools specialized in IT. He is the author of several books and many scientific papers about the use of digital groupware tools in project management and Lean Management.

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780 /echo-4-february-2011 2011-02-22T00:00:00 Echo 4 - February 2011 <p><span style="text-decoration: underline;">Editorial</span></p><p><strong>Florence Noble is a researcher in the Neuropsychology of addiction laboratory of the French National Centre for Research (CNRS) in Paris and teaches courses in Neurobiology at the University of Paris Descartes. She is strongly involved in the quest for new treatments through basic research and clinical trials.</strong></p><p><br />Drug users were long stigmatised as people who were lacking in willpower and incapable of curbing their use. Doctors and scientists have helped allow this vision to evolve, and addiction is now considered to be an illness, on par with other disorders such as depression. Public authorities have taken this into consideration, though to greatly varying extents depending on the country, with certain governments creating research centres dedicated to the illness and others remaining much more reticent. Fortunately, however, research on addiction has greatly increased, even though public funding has remained much lower than expected.</p><p><br />A person who is addicted to a substance no longer uses this substance for pleasure, but rather to avoid the suffering caused by withdrawal and difficulty to adapt to the world around them. Recent progress in research has allowed us to identify the areas of the brain and the chemical molecules that play a role in the onset of addiction. Scientists, however, have their work cut out for them with major issues at stake, such as understanding how addiction starts, identifying the health problems associated with excessive use of a substance (and therefore trying to prevent them), and understanding why many patients relapse after sometimes long periods of abstinence. This knowledge is essential in order to offer efficient treatments to cure patients. The AXA Research Fund plays an important role in sustaining successful research in this area.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/une_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Editorial

Florence Noble is a researcher in the Neuropsychology of addiction laboratory of the French National Centre for Research (CNRS) in Paris and teaches courses in Neurobiology at the University of Paris Descartes. She is strongly involved in the quest for new treatments through basic research and clinical trials.


Drug users were long stigmatised as people who were lacking in willpower and incapable of curbing their use. Doctors and scientists have helped allow this vision to evolve, and addiction is now considered to be an illness, on par with other disorders such as depression. Public authorities have taken this into consideration, though to greatly varying extents depending on the country, with certain governments creating research centres dedicated to the illness and others remaining much more reticent. Fortunately, however, research on addiction has greatly increased, even though public funding has remained much lower than expected.


A person who is addicted to a substance no longer uses this substance for pleasure, but rather to avoid the suffering caused by withdrawal and difficulty to adapt to the world around them. Recent progress in research has allowed us to identify the areas of the brain and the chemical molecules that play a role in the onset of addiction. Scientists, however, have their work cut out for them with major issues at stake, such as understanding how addiction starts, identifying the health problems associated with excessive use of a substance (and therefore trying to prevent them), and understanding why many patients relapse after sometimes long periods of abstinence. This knowledge is essential in order to offer efficient treatments to cure patients. The AXA Research Fund plays an important role in sustaining successful research in this area.

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697 /video-of-the-talent-day-on-environmental-risks-second-edition 2011-01-14T00:00:00 Video of the Talent Day on Environmental Risks, Second Edition <p><a class="link_01" href="/talent-days-environmental-risks-second-edition">Check out the event page</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/talent_day_-3r13.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Check out the event page

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264 /natural-disasters-using-science-to-overcome-risks 2011-01-08T00:00:00 Natural disasters: using science to overcome risks <p><strong>Haiti, January 2010</strong>: two&nbsp;earthquakes devastated the country, causing&nbsp;thousands of casualties.<br /><strong>Pakistan, August&nbsp;2010:</strong> torrential rain flooded two-thirds of the&nbsp;country, leaving millions homeless. <br /><strong>West Africa,&nbsp;summer 2010:</strong> the long-lasting drought that&nbsp;struck several Sahelian countries triggered one&nbsp;of the worst famines in the past thirty years.</p><p>Closer to home, <strong>major storm Xynthia</strong> hit the&nbsp;<strong>Atlantic coast of France in February 2010,</strong> killing&nbsp;more than 50 people and creating €2.5 billion&nbsp;worth of damage.&nbsp;Certain examples remain definitively ingrained&nbsp;in the collective memory.&nbsp;<br /><br />Who could forget <strong>the&nbsp;tsunami</strong> that swept through the Indian Ocean <strong>in&nbsp;2004?</strong> How could anyone in the <strong>United States</strong>&nbsp;forget the flooded streets of New Orleans after&nbsp;<strong>Hurricane Katrina</strong>? Even Hurricane Katrina was&nbsp;no isolated disaster. In fact, between 2004 and&nbsp;2005, seven major hurricanes struck the United&nbsp;States over fifteen months, causing more than&nbsp;$120 billion of insured loss and damage, three&nbsp;times more than the September 11 terrorist&nbsp;attacks in 2001.<br /><br />Beyond the shocking images, these disasters&nbsp;raise a number of questions. What conclusions&nbsp;should be drawn? Are these disasters the&nbsp;inevitable result of climate change and disorder?&nbsp;Or are they the serious consequences of a&nbsp;growing global population that has become&nbsp;increasingly concentrated in cities and on&nbsp;coasts? How can we bear the costs of destruction?&nbsp;<br />According to the German reinsurance&nbsp;company, Munich Re, costs related to natural&nbsp;disasters reached $50 billion in 2009 and four&nbsp;times this amount in 2008.<br />A number of uncertainties remain, however&nbsp;researchers of all disciplines continue to advance&nbsp;knowledge, in order to find solutions and help&nbsp;prepare for future extreme weather events.<br />Measures include better identifiying vulnerable&nbsp;areas, attempting to predict the impact of climate&nbsp;change, finding new tools to face financial loss,&nbsp;and bringing prevention measures to the centre&nbsp;of policies. These measures, and many others,&nbsp;should be urgently explored.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/cata_naturelles.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Haiti, January 2010: two earthquakes devastated the country, causing thousands of casualties.
Pakistan, August 2010: torrential rain flooded two-thirds of the country, leaving millions homeless.
West Africa, summer 2010: the long-lasting drought that struck several Sahelian countries triggered one of the worst famines in the past thirty years.

Closer to home, major storm Xynthia hit the Atlantic coast of France in February 2010, killing more than 50 people and creating €2.5 billion worth of damage. Certain examples remain definitively ingrained in the collective memory. 

Who could forget the tsunami that swept through the Indian Ocean in 2004? How could anyone in the United States forget the flooded streets of New Orleans after Hurricane Katrina? Even Hurricane Katrina was no isolated disaster. In fact, between 2004 and 2005, seven major hurricanes struck the United States over fifteen months, causing more than $120 billion of insured loss and damage, three times more than the September 11 terrorist attacks in 2001.

Beyond the shocking images, these disasters raise a number of questions. What conclusions should be drawn? Are these disasters the inevitable result of climate change and disorder? Or are they the serious consequences of a growing global population that has become increasingly concentrated in cities and on coasts? How can we bear the costs of destruction? 
According to the German reinsurance company, Munich Re, costs related to natural disasters reached $50 billion in 2009 and four times this amount in 2008.
A number of uncertainties remain, however researchers of all disciplines continue to advance knowledge, in order to find solutions and help prepare for future extreme weather events.
Measures include better identifiying vulnerable areas, attempting to predict the impact of climate change, finding new tools to face financial loss, and bringing prevention measures to the centre of policies. These measures, and many others, should be urgently explored.

 

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255 /the-axa-research-fund-awards-its-first-grant-in-asia-to-nus 2010-12-02T00:00:00 The AXA Research Fund Awards its First Grant in Asia to NUS <p>The AXA Research Fund, a major and innovative initiative of scientific philanthropy supported by the worldwide insurance group AXA, is awarding 517,000 Euros (S$904, 079) over a period of 3 years, to the National University of Singapore (NUS) to undertake a research project on the "Biology of Decision Making under Risk". This marks the first time the AXA Research Fund has awarded a grant to a university in Asia.</p><p>The research project seeks a deeper understanding of the biological mechanisms underpinning individual differences in how people take risks by bringing together methodologies from behavioral and experimental economics and the biological sciences. The study will generate quantitative phenotypes that can propel advances in understanding the molecular architecture of human decision making in a risky environment.</p><p>The research study will be led by Prof Richard P. Ebstein and Prof Chew Soo Hong of NUS' Department of Psychology and Department of Economics respectively.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/5D7CATQqGxPZZ8Cimage.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> The AXA Research Fund, a major and innovative initiative of scientific philanthropy supported by the worldwide insurance group AXA, is awarding 517,000 Euros (S$904, 079) over a period of 3 years, to the National University of Singapore (NUS) to undertake a research project on the "Biology of Decision Making under Risk". This marks the first time the AXA Research Fund has awarded a grant to a university in Asia.

The research project seeks a deeper understanding of the biological mechanisms underpinning individual differences in how people take risks by bringing together methodologies from behavioral and experimental economics and the biological sciences. The study will generate quantitative phenotypes that can propel advances in understanding the molecular architecture of human decision making in a risky environment.

The research study will be led by Prof Richard P. Ebstein and Prof Chew Soo Hong of NUS' Department of Psychology and Department of Economics respectively.

 

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269 /echo-3-november-2010 2010-11-01T00:00:00 Echo 3 - November 2010 <p><strong><font face="Times New Roman">Honored as a Young Global Leader by the </font></strong><strong><font face="Times New Roman">World Economic Forum (Davos), Dr Erwann </font></strong><strong><font face="Times New Roman">Michel-Kerjan teaches at the Wharton </font></strong><font face="Times New Roman"><strong>Business</strong><strong> School (USA) and is research </strong></font><strong><font face="Times New Roman">associate at the Ecole Polytechnique (France).</font></strong></p><p><strong></strong><font face="Times New Roman">The series of truly devastating natural disasters </font><font face="Times New Roman">in recent years demonstrated we have </font><font face="Times New Roman">entered a totally new era of catastrophes. </font><font face="Times New Roman">Whether we suffer from them as direct victims </font><font face="Times New Roman">or witness them live on TV, none of us can </font><font face="Times New Roman">remain indifferent. </font><font face="Times New Roman">Globalization has brought immense benefits </font><font face="Times New Roman">to billions of people. But because of highspeed </font><font face="Times New Roman">economic, social and demographic </font><font face="Times New Roman">development in many parts of the world exposed </font><font face="Times New Roman">to natural hazards, those “natural” catastrophes </font><font face="Times New Roman">are becoming less and less natural.</font></p><p><font face="Times New Roman">As such, the 21st century will either be the best </font><font face="Times New Roman">century ever, where we overcome the great </font><font face="Times New Roman">challenges of better dealing with large-scale </font><font face="Times New Roman">disasters, or it will be a lost century because </font><font face="Times New Roman">we fail to learn and act.</font></p><p><font face="Times New Roman">If we fail, these events will not only create </font><font face="Times New Roman">massive destruction and impede economic </font><font face="Times New Roman">growth in rich countries, they will become true </font><font face="Times New Roman">poverty traps in countries where preparedness </font><font face="Times New Roman">and risk transfer instruments are terribly </font><font face="Times New Roman">lacking. In the interdependent world we all live i</font><font face="Times New Roman">n today, this would have major ripple effects </font><font face="Times New Roman">around the globe.</font></p><p><font face="Times New Roman">As such, better risk assessment, better risk </font><font face="Times New Roman">management and better risk financing will be </font><font face="Times New Roman">critical in the years to come. There are also </font><font face="Times New Roman">gigantic unrevealed opportunities for innovation </font><font face="Times New Roman">and value creation here: new technologies, </font><font face="Times New Roman">new insurance products, and improved </font><font face="Times New Roman">public policies. </font><font face="Times New Roman">Faithful to its vision of leveraging the best </font><font face="Times New Roman">knowledge to help make informed decisions, </font><font face="Times New Roman">the AXA Research Fund has been very active </font><font face="Times New Roman">in supporting state-of-the-art research in this </font><font face="Times New Roman">multi-disciplinary and growing sphere.</font></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/echo.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> Honored as a Young Global Leader by the World Economic Forum (Davos), Dr Erwann Michel-Kerjan teaches at the Wharton Business School (USA) and is research associate at the Ecole Polytechnique (France).

The series of truly devastating natural disasters in recent years demonstrated we have entered a totally new era of catastrophes. Whether we suffer from them as direct victims or witness them live on TV, none of us can remain indifferent. Globalization has brought immense benefits to billions of people. But because of highspeed economic, social and demographic development in many parts of the world exposed to natural hazards, those “natural” catastrophes are becoming less and less natural.

As such, the 21st century will either be the best century ever, where we overcome the great challenges of better dealing with large-scale disasters, or it will be a lost century because we fail to learn and act.

If we fail, these events will not only create massive destruction and impede economic growth in rich countries, they will become true poverty traps in countries where preparedness and risk transfer instruments are terribly lacking. In the interdependent world we all live in today, this would have major ripple effects around the globe.

As such, better risk assessment, better risk management and better risk financing will be critical in the years to come. There are also gigantic unrevealed opportunities for innovation and value creation here: new technologies, new insurance products, and improved public policies. Faithful to its vision of leveraging the best knowledge to help make informed decisions, the AXA Research Fund has been very active in supporting state-of-the-art research in this multi-disciplinary and growing sphere.

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284 /launch-of-the-axa-newcastle-chair-on-longevity-and-healthy-active-life 2010-10-08T00:00:00 Launch of the AXA - Newcastle Chair on Longevity and Healthy Active Life <p>Life expectancy is still increasing in the UK at the rate of around 2 years each decade. This is a remarkable achievement but it is often viewed negatively, not least because of the greater numbers of those aged 85 years and older, the so-called'oldest old', with their high rates of age-related diseases and disability. However we have little firm evidence of whether the extra years of life we are now enjoying are spent in good or poor health and the impact that the greater numbers of the oldest old will have on health and care services.</p><p>In recognition of its leading role in ageing research world-wide, the AXA Research Fund has recently funded Professor Carol Jagger to a permanent Chair in the Institute for Ageing and Health at Newcastle University to further research on understanding trends, causes and consequences of Longevity and Healthy Active Life for future health and social care policy.</p><p>&nbsp;</p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <mce:style><! /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} --> <!--[endif] --> <p class="MsoNormal"><a class="link_01" href="http://www.axa-research.org/project/carol-jagger">Click here to find out more about this research supported by the AXA Research Fund</a></p> <p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/newcastle.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> Life expectancy is still increasing in the UK at the rate of around 2 years each decade. This is a remarkable achievement but it is often viewed negatively, not least because of the greater numbers of those aged 85 years and older, the so-called'oldest old', with their high rates of age-related diseases and disability. However we have little firm evidence of whether the extra years of life we are now enjoying are spent in good or poor health and the impact that the greater numbers of the oldest old will have on health and care services.

In recognition of its leading role in ageing research world-wide, the AXA Research Fund has recently funded Professor Carol Jagger to a permanent Chair in the Institute for Ageing and Health at Newcastle University to further research on understanding trends, causes and consequences of Longevity and Healthy Active Life for future health and social care policy.

 

Click here to find out more about this research supported by the AXA Research Fund

 

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285 /the-axa-research-fund-is-funding-a-chair-in-supramolecular-chemistry-at-the-university-of-strasbourg 2010-09-22T00:00:00 The AXA Research Fund is funding a Chair in Supramolecular Chemistry at the University of Strasbourg <p>This permanent chair is intended to welcome a world-renowned researcher to the University of Strasbourg, whose work will follow on from the supramolecular chemistry research began by Professor Jean-Marie Lehn, Nobel Prize Laureate for Chemistry in 1987, within France's only network of excellence for chemistry: the International Centre for Frontier Research in Chemistry.</p><p>This chair's first objective will be to further strengthen fundamental research into supramolecular chemistry. This branch of chemistry is based on the study of molecular bricks which, brought together under controlled conditions, self-assemble to give more complex structures. There are numerous applications, particularly for new materials, in medicine, green chemistry or even IT storage systems.</p><p>This chair will develop the applications of supramolecular chemistry for medical sciences and will more specifically help find new solutions for treating ageing-related illnesses.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/strasbourg.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> This permanent chair is intended to welcome a world-renowned researcher to the University of Strasbourg, whose work will follow on from the supramolecular chemistry research began by Professor Jean-Marie Lehn, Nobel Prize Laureate for Chemistry in 1987, within France's only network of excellence for chemistry: the International Centre for Frontier Research in Chemistry.

This chair's first objective will be to further strengthen fundamental research into supramolecular chemistry. This branch of chemistry is based on the study of molecular bricks which, brought together under controlled conditions, self-assemble to give more complex structures. There are numerous applications, particularly for new materials, in medicine, green chemistry or even IT storage systems.

This chair will develop the applications of supramolecular chemistry for medical sciences and will more specifically help find new solutions for treating ageing-related illnesses.

 

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698 /launch-of-the-axa-hec-paris-chair-for-decision-science 2010-06-29T00:00:00 Launch of the AXA - HEC Paris Chair for Decision Science <p>This new Chair seeks to improve our understanding of how decisions are made and how we can support better decision making, in light of cognitive limits and psychological constraints. It will also explore the links between effective decision making and successful leadership.</p><p><br />« Life is full of decisions, most of which have unknown consequences », explains inaugural Chair holder Itzhak Gilboa. « As individuals and societies, when we decide whether to buy insurance, undergo a medical treatment, or cope with global warming, we make decisions without knowing what will actually happen ».</p><p><br />The AXA-HEC Paris Chair for Decision Science will be devoted to sponsoring academic research, workshops and conferences, and will bring together researchers from various disciplines. It builds on HEC Paris’ research capacity in decision making and will integrate the latest research developments into its leadership training curriculum.</p><p>&nbsp;</p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} </style> <![endif]--> <p class="MsoNormal"><a class="link_01" href="http://89.31.145.183/project/itzhak-gilboa">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/hec_logo.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> This new Chair seeks to improve our understanding of how decisions are made and how we can support better decision making, in light of cognitive limits and psychological constraints. It will also explore the links between effective decision making and successful leadership.


« Life is full of decisions, most of which have unknown consequences », explains inaugural Chair holder Itzhak Gilboa. « As individuals and societies, when we decide whether to buy insurance, undergo a medical treatment, or cope with global warming, we make decisions without knowing what will actually happen ».


The AXA-HEC Paris Chair for Decision Science will be devoted to sponsoring academic research, workshops and conferences, and will bring together researchers from various disciplines. It builds on HEC Paris’ research capacity in decision making and will integrate the latest research developments into its leadership training curriculum.

 

Click here to find out more about this research supported by the AXA Research Fund

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699 /launch-of-the-axa-ecole-polytechnique-chair-for-cardiovascular-cellular-engineering 2010-06-14T00:00:00 Launch of the AXA - École Polytechnique Chair for Cardiovascular Cellular Engineering <p>Heart disease and stroke are the two leading causes of death in Europe today. These diseases are caused by atherosclerosis, or thickening of the arterial walls which leads to arterial blockage by lipid-rich plaques. The chair will for the first time study atherosclerosis through a transdisciplinary approach combining biology and engineering.</p><p><br />The AXA - École Polytechnique Chair aims to develop a new generation of engineers sufficiently versed in biology to formulate original approaches to these diseases.</p><p>&nbsp;</p><p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} </style> <![endif]--> </p><p class="MsoNormal"><a class="link_01" href="http://89.31.145.183/project/abdul-barakat">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/ecole_polytechnique.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Heart disease and stroke are the two leading causes of death in Europe today. These diseases are caused by atherosclerosis, or thickening of the arterial walls which leads to arterial blockage by lipid-rich plaques. The chair will for the first time study atherosclerosis through a transdisciplinary approach combining biology and engineering.


The AXA - École Polytechnique Chair aims to develop a new generation of engineers sufficiently versed in biology to formulate original approaches to these diseases.

 

Click here to find out more about this research supported by the AXA Research Fund

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281 /echo-2-june-2010 2010-06-01T00:00:00 Echo 2 - June 2010 <p>Our regular feature, "Helping the world advance" is devoted to Abdul Barakat and discusses how bioengineering can provide pioneering treatments for cardiovascular diseases.</p><p>&lt;p&gt; &lt;p&gt; These two projects, as well as all of those you will discover in these pages and upcoming editions, are among the 157 research efforts the AXA Research Fund have decided to support in 15 countries thus far. All of them illustrate our commitment of&nbsp;AXA&nbsp;to research as well the determination to create an environment that fosters the emergence of path-breaking scientific discoveries.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/echo2.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> Our regular feature, "Helping the world advance" is devoted to Abdul Barakat and discusses how bioengineering can provide pioneering treatments for cardiovascular diseases.

<p> <p> These two projects, as well as all of those you will discover in these pages and upcoming editions, are among the 157 research efforts the AXA Research Fund have decided to support in 15 countries thus far. All of them illustrate our commitment of AXA to research as well the determination to create an environment that fosters the emergence of path-breaking scientific discoveries.

 

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700 /second-year-results-of-the-axa-research-fund-return-on-2009 2010-05-04T00:00:00 Second year results of the AXA Research Fund: return on 2009 <p>As with the previous year, the AXA Research Fund has chosen to support both outstanding<br />world-class scientists and brilliant young researchers.</p><p><br />“Risk is the core of our business and, as a major actor of economic development, it is our<br />responsibility to help understand and prevent risk. This is the raison d’être of the AXA<br />Research Fund which provides researchers with the means to further improve knowledge<br />and understanding of the risks that we are facing” said Henri de Castries, Chairman and<br />CEO of AXA.</p><p><br />Thanks to a broad diversity of funding vehicles and a wide geographical scope, the AXA<br />Research Fund selected 71 new research projects in 10 countries. This selection was<br />determined by the Scientific Board, which is chaired by Ezra Suleiman and made up of both<br />eminent figures from the scientific world and AXA Group experts.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_fund_sign_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> As with the previous year, the AXA Research Fund has chosen to support both outstanding
world-class scientists and brilliant young researchers.


“Risk is the core of our business and, as a major actor of economic development, it is our
responsibility to help understand and prevent risk. This is the raison d’être of the AXA
Research Fund which provides researchers with the means to further improve knowledge
and understanding of the risks that we are facing” said Henri de Castries, Chairman and
CEO of AXA.


Thanks to a broad diversity of funding vehicles and a wide geographical scope, the AXA
Research Fund selected 71 new research projects in 10 countries. This selection was
determined by the Scientific Board, which is chaired by Ezra Suleiman and made up of both
eminent figures from the scientific world and AXA Group experts.

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282 /echo-1-april-2010 2010-04-01T00:00:00 Echo 1 - April 2010 <p><em><u><font color="#000000">On a quarterly basis, the magazine Echo receives an expert to discuss an important current issue.</font></u></em></p><p><font color="#000000">Thomas Kirkwood heads the Institute for Aging and Health at Newcastle University</font></p><p><font color="#000000">Aging is humanity’s greatest success story! But there is an urgency to understand why and how we are getting old… In particular, Aging includes a demographic issue: life expectancy is continuing to increase at an astonishing speed. Each and every one of us gains every day about five hours of life expectancy! That rate is enormous. </font></p><p><font color="#000000">Aging and its global implications are a hot topic. The consequences of life-expectancy will be massive, perhaps even more than Climate change or Terrorism. Population aging is going to affect almost every aspect of our lives as well as the obvious matters about healthcare, social care, retirement pensions, etc. It is a success story but we have to work in order to prepare ourselves !</font></p><p><font color="#000000">People are ambivalent: do they really want to cope with all the issues involved with aging? Public opinion is generally very negative about aging. People seem to think it only concerns old persons and the public policy makers are slow to address this matter. </font></p><p><font color="#000000">In reality, aging is fantastic news for economy! They will be more consumers, who will help growth on a global scale. People are making big mistakes about aging: it is a big question for everyone, and research in that field will benefit today’s babies as well as adults.</font></p><p><font face="Times New Roman" size="3" color="#000000">&nbsp;</font></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/echo1.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> On a quarterly basis, the magazine Echo receives an expert to discuss an important current issue.

Thomas Kirkwood heads the Institute for Aging and Health at Newcastle University

Aging is humanity’s greatest success story! But there is an urgency to understand why and how we are getting old… In particular, Aging includes a demographic issue: life expectancy is continuing to increase at an astonishing speed. Each and every one of us gains every day about five hours of life expectancy! That rate is enormous.

Aging and its global implications are a hot topic. The consequences of life-expectancy will be massive, perhaps even more than Climate change or Terrorism. Population aging is going to affect almost every aspect of our lives as well as the obvious matters about healthcare, social care, retirement pensions, etc. It is a success story but we have to work in order to prepare ourselves !

People are ambivalent: do they really want to cope with all the issues involved with aging? Public opinion is generally very negative about aging. People seem to think it only concerns old persons and the public policy makers are slow to address this matter.

In reality, aging is fantastic news for economy! They will be more consumers, who will help growth on a global scale. People are making big mistakes about aging: it is a big question for everyone, and research in that field will benefit today’s babies as well as adults.

 

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777 /newsletter-3-november-2009 2009-11-01T00:00:00 Newsletter 3 - November 2009 <p><strong><font face="Times New Roman">What can we expect from current debates on </font><font face="Times New Roman">climate change, and from the United Nations </font><font face="Times New Roman">conference in Copenhagen?</font></strong></p><p><em></em><font face="Times New Roman">The goal of the Copenhagen summit is to find a new agreement </font><font face="Times New Roman">on climate, in order to provide continuity after the </font><font face="Times New Roman">Kyoto Protocol, which expires in 2012. </font><font face="Times New Roman">The first objective will be to agree on an emission reduction </font><font face="Times New Roman">of greenhouse gases in order to prevent a rise of more </font><font face="Times New Roman">than 2°C in the overall planetary temperature by the end </font><font face="Times New Roman">of the century. Afterwards, the negotiators will have to </font><font face="Times New Roman">agree on the best method to share the financial effort that </font><font face="Times New Roman">will be necessary for the adaptation of countries that are </font><font face="Times New Roman">vulnerable to future disruptions. The key to the agreement </font><font face="Times New Roman">lies in the hands of a few countries, including the United </font><font face="Times New Roman">States and China.</font></p><p><font face="Times New Roman">The stakes of the Copenhagen conference are much higher </font><font face="Times New Roman">than in the Kyoto conference of 1997, since the goal is </font><font face="Times New Roman">to plan the course of the national economies until 2050. </font><font face="Times New Roman">Its importance exceeds the question of greenhouse gases: </font><font face="Times New Roman">the relations between North and South are also at stak</font></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/photo_newsletter3.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> What can we expect from current debates on climate change, and from the United Nations conference in Copenhagen?

The goal of the Copenhagen summit is to find a new agreement on climate, in order to provide continuity after the Kyoto Protocol, which expires in 2012. The first objective will be to agree on an emission reduction of greenhouse gases in order to prevent a rise of more than 2°C in the overall planetary temperature by the end of the century. Afterwards, the negotiators will have to agree on the best method to share the financial effort that will be necessary for the adaptation of countries that are vulnerable to future disruptions. The key to the agreement lies in the hands of a few countries, including the United States and China.

The stakes of the Copenhagen conference are much higher than in the Kyoto conference of 1997, since the goal is to plan the course of the national economies until 2050. Its importance exceeds the question of greenhouse gases: the relations between North and South are also at stak

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701 /risk-management-and-regulation-of-financial-institutions-research-programme-launched-by-lse-and-axa 2009-10-13T00:00:00 Risk management and regulation of financial institutions research programme launched by LSE and AXA Research Fund <p>Professor David Webb, Director of LSE’s Financial Markets Group which will<br />undertake the research, said: ‘The current financial crisis has revealed a distance<br />between our understanding of the interconnected behaviour of banks, the structure of<br />the banking systems and layers of regulation. We aim to gain a better understanding<br />of the weakness of the current financial architecture and to assess the scope for<br />greater financial stability through governance and regulation.’</p><p><br />Eric Chaney, Chief Economist of the AXA Group said: ‘While this research will focus<br />on filling gaps in the academic understanding of these issues it will clearly also be<br />extremely relevant to the development of knowledge informed policy.’</p><p><br />LSE academics undertaking the AXA Research Programme, will, for example,<br />assess the performance of the global regulatory framework during the current crisis<br />to analyse changes in regulation that could help reduce the risks of such crises in the<br />future. They will look at the whole structure of capital standards, leverage ratios,<br />accounting principles for bank assets and liquidity provision to the market. They will<br />also examine the use of risk models and balance sheet information in managing risk<br />at the level of intuitions, and for system-wide regulation.</p><p><br />Another strand of the research programme will scrutinise the governance of banks<br />looking at board and ownership structure and how the top management are<br />remunerated. This will aim to learn more about the skill-set and financial knowledge<br />of non-executive directors, the board’s function when seen in competition with<br />banking regulation and ultimately its impact on bank performance.</p><p><br />High-powered incentive pay, the limited penalties when something goes wrong and<br />the way this encourages excessive risk taking by financial institutions will also be<br />examined.</p><p><br />To launch the research programme, a public panel discussion on the future of<br />banking and financial regulation will take place at LSE on Monday 19 October.</p><p>The panel will be Chief Economist of the AXA Group Eric Chaney, Dominique Carrel-<br />Billiard, CEO of AXA Investment Managers and LSE Professors Charles Goodhart<br />and David Webb. This event is free and open to all (1). For more information see<br />www.lse.ac.uk</p><p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <mce:style><! /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} --> <!--[endif]--> </p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} </style> <![endif]--> <p class="MsoNormal"><a class="link_01" href="http://89.31.145.183/project/david-webb">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/lse_copie.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Professor David Webb, Director of LSE’s Financial Markets Group which will
undertake the research, said: ‘The current financial crisis has revealed a distance
between our understanding of the interconnected behaviour of banks, the structure of
the banking systems and layers of regulation. We aim to gain a better understanding
of the weakness of the current financial architecture and to assess the scope for
greater financial stability through governance and regulation.’


Eric Chaney, Chief Economist of the AXA Group said: ‘While this research will focus
on filling gaps in the academic understanding of these issues it will clearly also be
extremely relevant to the development of knowledge informed policy.’


LSE academics undertaking the AXA Research Programme, will, for example,
assess the performance of the global regulatory framework during the current crisis
to analyse changes in regulation that could help reduce the risks of such crises in the
future. They will look at the whole structure of capital standards, leverage ratios,
accounting principles for bank assets and liquidity provision to the market. They will
also examine the use of risk models and balance sheet information in managing risk
at the level of intuitions, and for system-wide regulation.


Another strand of the research programme will scrutinise the governance of banks
looking at board and ownership structure and how the top management are
remunerated. This will aim to learn more about the skill-set and financial knowledge
of non-executive directors, the board’s function when seen in competition with
banking regulation and ultimately its impact on bank performance.


High-powered incentive pay, the limited penalties when something goes wrong and
the way this encourages excessive risk taking by financial institutions will also be
examined.


To launch the research programme, a public panel discussion on the future of
banking and financial regulation will take place at LSE on Monday 19 October.

The panel will be Chief Economist of the AXA Group Eric Chaney, Dominique Carrel-
Billiard, CEO of AXA Investment Managers and LSE Professors Charles Goodhart
and David Webb. This event is free and open to all (1). For more information see
www.lse.ac.uk

Click here to find out more about this research supported by the AXA Research Fund

]]>
702 /the-axa-research-fund-commits-to-top-level-research-on-the-challenges-of-longevity 2009-10-07T00:00:00 The AXA Research Fund commits to top-level research on the challenges of longevity <p>Convinced that basic research is essential to advancing knowledge, the AXA Group, via the AXA<br />Research Fund, is providing support to the scientific community to develop cutting-edge<br />research that will provide a clearer understanding of the challenges posed by the increase in<br />lifespan.</p><p><br />Endowed with €1,250,000 for a five-year period, the AXA-Paris Descartes Chair in "A systems<br />approach to individual differences in longevity" aims to train a new generation of researchers<br />with a scientific understanding of a longer lifespan, approached from a multidisciplinary point of<br />view. Indeed, the major innovation of this Chair resides in the multidisciplinary approach it<br />proposes, which to date is unique in the world. The holders of the Chair, Linda Partridge,<br />Thomas Kirkwood, François Taddei and James Vaupel, have different scientific backgrounds:<br />demographics, genetics, nutrition, biology, etc. This diversity of approaches should make it<br />possible to study accurately the numerous parameters that affect the longevity of an individual.</p><p><br />By providing its support for the AXA-Paris Descartes Chair, the AXA Research Fund hopes it will<br />offer researchers the resources necessary to advance knowledge on the mechanisms of ageing.</p><p>&nbsp;</p><p><span style="text-decoration: underline;">What is longevity?</span><br />Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research.<br /><em>Prof. Thomas Kirkwood,</em><br /><em>Director of the Institute for Ageing and Health, Newcastle, UK.</em></p><p><em><br /></em></p><p><span style="text-decoration: underline;">What are the approaches and objectives of this Chair?</span><br />At present, no explanation provided by a single discipline is sufficient to understand individual differences in longevity. Indeed, the main problem faced by research on longevity resides in the complexity of ageing, which is a phenomenon dependent on numerous parameters, such as genetic heritage, social background or the environment. In this context, the multidisciplinary careers of the Chair holders constitute a major asset and valuable foundations for the work considered. This Chair also has an actual educational objective: it aims to disseminate knowledge and promote vocations. One of our major aims is to train a new generation of researchers with a scientific understanding of ageing, approached from a multidisciplinary point of view and in an integrated manner. We hope to enable the emergence of joint research projects involving Master's and PhD students and postdoctoral fellows from our different institutions and of different nationalities.<br /><em>François Taddei,</em><br /><em>Instigator and holder of the AXA-Paris Descartes Chair</em></p><p>&nbsp;</p><p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} </style> <![endif]--> </p><p class="MsoNormal"><a class="link_01" href="http://89.31.145.183/project/kirkwoodpartridgevaupeltaddei">Click here to find out more about this research supported by the AXA Research Fund</a></p> <p><!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:HyphenationZone>21</w:HyphenationZone> <w:PunctuationKerning /> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:SnapToGridInCell /> <w:WrapTextWithPunct /> <w:UseAsianBreakRules /> <w:DontGrowAutofit /> </w:Compatibility> <w:BrowserLevel>MicrosoftInternetExplorer4</w:BrowserLevel> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="156"> </w:LatentStyles> </xml><![endif]--><!--[if gte mso 10]> <style> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tableau Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} </style> <![endif]--> </p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/logorvb_iutdescartes.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Convinced that basic research is essential to advancing knowledge, the AXA Group, via the AXA
Research Fund, is providing support to the scientific community to develop cutting-edge
research that will provide a clearer understanding of the challenges posed by the increase in
lifespan.


Endowed with €1,250,000 for a five-year period, the AXA-Paris Descartes Chair in "A systems
approach to individual differences in longevity" aims to train a new generation of researchers
with a scientific understanding of a longer lifespan, approached from a multidisciplinary point of
view. Indeed, the major innovation of this Chair resides in the multidisciplinary approach it
proposes, which to date is unique in the world. The holders of the Chair, Linda Partridge,
Thomas Kirkwood, François Taddei and James Vaupel, have different scientific backgrounds:
demographics, genetics, nutrition, biology, etc. This diversity of approaches should make it
possible to study accurately the numerous parameters that affect the longevity of an individual.


By providing its support for the AXA-Paris Descartes Chair, the AXA Research Fund hopes it will
offer researchers the resources necessary to advance knowledge on the mechanisms of ageing.

 

What is longevity?
Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research.
Prof. Thomas Kirkwood,
Director of the Institute for Ageing and Health, Newcastle, UK.


What are the approaches and objectives of this Chair?
At present, no explanation provided by a single discipline is sufficient to understand individual differences in longevity. Indeed, the main problem faced by research on longevity resides in the complexity of ageing, which is a phenomenon dependent on numerous parameters, such as genetic heritage, social background or the environment. In this context, the multidisciplinary careers of the Chair holders constitute a major asset and valuable foundations for the work considered. This Chair also has an actual educational objective: it aims to disseminate knowledge and promote vocations. One of our major aims is to train a new generation of researchers with a scientific understanding of ageing, approached from a multidisciplinary point of view and in an integrated manner. We hope to enable the emergence of joint research projects involving Master's and PhD students and postdoctoral fellows from our different institutions and of different nationalities.
François Taddei,
Instigator and holder of the AXA-Paris Descartes Chair

 

Click here to find out more about this research supported by the AXA Research Fund

]]>
775 /newsletter-2-june-2009 2009-06-01T00:00:00 Newsletter 2 - June 2009 <p><strong><font face="Times New Roman">“The issue of global warming is subject </font><font face="Times New Roman">to controversy in the scientific community. </font><font face="Times New Roman">Can you round up the different “schools </font><font face="Times New Roman">of thought”?”</font></strong></p><p><font face="Times New Roman">Faced with the uncertainty surrounding the various global </font><font face="Times New Roman">warming scenarios, many experts at least agree on the </font><font face="Times New Roman">benefit of a “no regret” policy which consists in adopting </font><font face="Times New Roman">measures that are useful whether or not the severe global </font><font face="Times New Roman">warming scenario is confirmed. Nonetheless, this scenario </font><font face="Times New Roman">is less and less controversial: reality has already matched </font><font face="Times New Roman">or exceeded the most alarming hypothesis examined by </font><font face="Times New Roman">the IPCC. So, the debate today revolves around the size </font><font face="Times New Roman">and shape that public policies should take. In my opinion, </font><font face="Times New Roman">there are two pitfalls: a relativist view resigned to the current</font><font face="Times New Roman">state of affairs, and an apocalyptic view. In any case, </font><font face="Times New Roman">we will need to consider the impact and cost to society of </font><font face="Times New Roman">the measures taken – to avoid, for example, taxes that will </font><font face="Times New Roman">be tougher on underprivileged communities.</font></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/newsletter2_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> “The issue of global warming is subject to controversy in the scientific community. Can you round up the different “schools of thought”?”

Faced with the uncertainty surrounding the various global warming scenarios, many experts at least agree on the benefit of a “no regret” policy which consists in adopting measures that are useful whether or not the severe global warming scenario is confirmed. Nonetheless, this scenario is less and less controversial: reality has already matched or exceeded the most alarming hypothesis examined by the IPCC. So, the debate today revolves around the size and shape that public policies should take. In my opinion, there are two pitfalls: a relativist view resigned to the currentstate of affairs, and an apocalyptic view. In any case, we will need to consider the impact and cost to society of the measures taken – to avoid, for example, taxes that will be tougher on underprivileged communities.

]]>
703 /first-year-results-of-the-axa-research-fund-over-euro-13-million-allocated-for-research-in-2008 2009-03-24T00:00:00 First year results of the AXA Research Fund: Over Euro 13 million allocated for research in 2008 <p>The purpose of the Fund is to promote the understanding and prevention of major<br />risks in the world by supporting cutting edge scientific research. The AXA<br />Research Fund has been endowed with Euro 100 million over five years, making it<br />a major initiative in the realm of scientific philanthropy in Europe.</p><p><br />“The current environment only reinforces our conviction that academic research is<br />critical to meeting the challenges of a global society”, noted Henri de Castries,<br />Chairman of the AXA Group Management Board. “We are particularly proud of the<br />work accomplished by the Fund over the course of this first year, and we confirm<br />AXA’s long-term commitment to contributing to emergence of the talents and<br />technologies needed to ensure the development of our societies. Researching<br />today is protecting tomorrow”.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_fund_sign.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> The purpose of the Fund is to promote the understanding and prevention of major
risks in the world by supporting cutting edge scientific research. The AXA
Research Fund has been endowed with Euro 100 million over five years, making it
a major initiative in the realm of scientific philanthropy in Europe.


“The current environment only reinforces our conviction that academic research is
critical to meeting the challenges of a global society”, noted Henri de Castries,
Chairman of the AXA Group Management Board. “We are particularly proud of the
work accomplished by the Fund over the course of this first year, and we confirm
AXA’s long-term commitment to contributing to emergence of the talents and
technologies needed to ensure the development of our societies. Researching
today is protecting tomorrow”.

]]>
773 /newsletter-1-mars-2009 2009-03-01T00:00:00 Newsletter 1 - Mars 2009 <p><strong><font face="Times New Roman">“Why did AXA decide to devote </font><font face="Times New Roman">100 million euros to research?”</font></strong></p><p><em><font face="Times New Roman">The reasoning is simple: AXA’s business is to support </font></em><em><font face="Times New Roman">customers by providing them with insurance, personal </font></em><em><font face="Times New Roman">protection and savings products and services. We are </font></em><em><font face="Times New Roman">proud of the contribution our business makes to economic </font></em><em><font face="Times New Roman">and social growth in the countries in which we operate, </font></em><em><font face="Times New Roman">and we conduct it responsibly.</font></em></p><p><em><font face="Times New Roman">What could be more natural than for AXA to support and </font></em><em><font face="Times New Roman">promote research, which is a catalyst of economic and </font></em><em><font face="Times New Roman">social progress? We created the AXA Research Fund in </font></em><em><font face="Times New Roman">early 2008 to implement this idea. </font></em><em><font face="Times New Roman">On a more global scale, I am convinced that businesses </font></em><em><font face="Times New Roman">play a major role alongside governments in financing academic </font></em><em><font face="Times New Roman">research, and I hope with all my heart that we will </font></em><em><font face="Times New Roman">inspire others to do the same</font></em></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/une-newsletter1_0.png" alt="" title="" class="imagecache imagecache-contentimage" /> “Why did AXA decide to devote 100 million euros to research?”

The reasoning is simple: AXA’s business is to support customers by providing them with insurance, personal protection and savings products and services. We are proud of the contribution our business makes to economic and social growth in the countries in which we operate, and we conduct it responsibly.

What could be more natural than for AXA to support and promote research, which is a catalyst of economic and social progress? We created the AXA Research Fund in early 2008 to implement this idea. On a more global scale, I am convinced that businesses play a major role alongside governments in financing academic research, and I hope with all my heart that we will inspire others to do the same

]]>
704 /axa-research-fund-applications-open-and-financing-available 2008-03-18T00:00:00 AXA Research Fund: Applications open and financing available <p>As announced on October 10, 2007 the AXA Research Fund will be allocated a five-year 100<br />million Euro budget and will be managed by a Scientific Board chaired by Ezra Suleiman,<br />Professor in Political Sciences at Princeton University (U.S.A.) and member of the AXA<br />Supervisory Board.</p><p><br />AXA believes that part of its engagements as a good corporate citizen means that the private<br />sector can and must help public funding to promote academic research.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_fund_sign_1.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> As announced on October 10, 2007 the AXA Research Fund will be allocated a five-year 100
million Euro budget and will be managed by a Scientific Board chaired by Ezra Suleiman,
Professor in Political Sciences at Princeton University (U.S.A.) and member of the AXA
Supervisory Board.


AXA believes that part of its engagements as a good corporate citizen means that the private
sector can and must help public funding to promote academic research.

]]>
705 /axa-launches-euro-100-million-research-fund-to-promote-academic-research 2007-10-10T00:00:00 AXA launches Euro 100 Million Research Fund to promote academic research <p>Top-rate academic research is crucial to the continued development of the global economy and<br />to the technologies and talents that will drive this development in future generations.<br />Ensuring that adequate funding is available for academic research projects is not the exclusive<br />domain or responsibility of governmental and academic institutions. AXA believes that the<br />private sector can, and should, play an important role in promoting meaningful academic<br />research consistent with its larger social responsibilities.</p><p><br />In this context, the AXA Group has decided to launch the AXA RESEARCH FUND managed by<br />a Scientific Board chaired by Ezra Suleiman professor of political science at Princeton University<br />and independent member of the AXA Supervisory Board.</p><p><br />AXA has committed a total of € 100,000,000 to the Fund over 5 years.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_fund_sign_2.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Top-rate academic research is crucial to the continued development of the global economy and
to the technologies and talents that will drive this development in future generations.
Ensuring that adequate funding is available for academic research projects is not the exclusive
domain or responsibility of governmental and academic institutions. AXA believes that the
private sector can, and should, play an important role in promoting meaningful academic
research consistent with its larger social responsibilities.


In this context, the AXA Group has decided to launch the AXA RESEARCH FUND managed by
a Scientific Board chaired by Ezra Suleiman professor of political science at Princeton University
and independent member of the AXA Supervisory Board.


AXA has committed a total of € 100,000,000 to the Fund over 5 years.

]]>
11 /launch-of-the-axa-hec-chair-for-decision-science Launch of the AXA - HEC Chair for Decision Science <p>This new Chair seeks to improve our understanding of how decisions are made and how we can support better decision making, in light of cognitive limits and psychological constraints. It will also explore the links between effective decision making and successful leadership.</p><p><br />« Life is full of decisions, most of which have unknown consequences », explains inaugural Chair holder Itzhak Gilboa. « As individuals and societies, when we decide whether to buy insurance, undergo a medical treatment, or cope with global warming, we make decisions without knowing what will actually happen ».</p><p><br />The AXA-HEC Paris Chair for Decision Science will be devoted to sponsoring academic research, workshops and conferences, and will bring together researchers from various disciplines. It builds on HEC Paris’ research capacity in decision making and will integrate the latest research developments into its leadership training curriculum.</p><p>&nbsp;</p><p><a class="link_01" href="http://89.31.145.183/project/itzhak-gilboa">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/_hec2877.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> This new Chair seeks to improve our understanding of how decisions are made and how we can support better decision making, in light of cognitive limits and psychological constraints. It will also explore the links between effective decision making and successful leadership.


« Life is full of decisions, most of which have unknown consequences », explains inaugural Chair holder Itzhak Gilboa. « As individuals and societies, when we decide whether to buy insurance, undergo a medical treatment, or cope with global warming, we make decisions without knowing what will actually happen ».


The AXA-HEC Paris Chair for Decision Science will be devoted to sponsoring academic research, workshops and conferences, and will bring together researchers from various disciplines. It builds on HEC Paris’ research capacity in decision making and will integrate the latest research developments into its leadership training curriculum.

 

Click here to find out more about this research supported by the AXA Research Fund

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279 /talent-days-life-risks-first-edition Talent Days - Life Risks - First Edition <p>19 AXA grantees, from 7 different countries, were brought together to discuss and compare their points of view on a common field of research that is highly important for our society: the increasing mean lifespan.</p><p>"Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research"<br /><em>Prof. Thomas Kirkwood,</em><br /><em>Director of the Institute for Ageing and Health, Newcastle, UK.</em></p><p><br />Our fellows attended a Master Class by Miroslav Radman : "Stayiong Alive : in search of healthy Longevity".</p><p>Prof. Radman was a Member of our Scientific Board, Member of the French Academy of Sciences, Professor of Cell Biology at "Necker - Enfants Malades" Medical schol.</p><p class="Default">They also attended the <strong><span class="title_01"><a href="http://89.31.145.183/launch-of-the-axa-paris-descartes-chair-in-a-systems-approach-to-individual-differences-in-longevity">launch of the AXA-Paris Descartes Chair on Longevity</a>,</span> “A systems approach to individual differences in longevity”, </strong>in the presence of<strong>&nbsp;</strong></p><ul><li><strong>Henri de Castries, Chairman of the Management Board and CEO –AXA</strong></li><li><strong>Axel Kahn, President of Paris Descartes University</strong></li><li>E. Suleiman, President of the Scientific Board of the AXA Research Fund</li><li>T. Kirkwook, Biologist, Director of the Institute for Ageing and Health –Newcastle</li><li>L. Partridge, Geneticist, Director of the Institute of Healthy Ageing –London</li><li>J. W.Vaupel, Demographer, Founding Director of the Max Planck Institute forDemographic Research –Rostock</li><li>A. Baudisch, Biodemographer, Independent Junior Research Group Leader at the Max Planck Institute for Demographic Research –Rostock</li><li>F. Taddei, Geneticist, Research Director at Inserm, Director of the Centre de Recherche Interdisciplinaire at Paris Descartes University –Paris </li><li>J.-C. Menioux, Group Chief Risk Officer –AXA</li><li>L.Taleyson, Head of Life Risks –AXA.</li></ul> <p>&nbsp;</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/talentday2.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> 19 AXA grantees, from 7 different countries, were brought together to discuss and compare their points of view on a common field of research that is highly important for our society: the increasing mean lifespan.

"Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research"
Prof. Thomas Kirkwood,
Director of the Institute for Ageing and Health, Newcastle, UK.


Our fellows attended a Master Class by Miroslav Radman : "Stayiong Alive : in search of healthy Longevity".

Prof. Radman was a Member of our Scientific Board, Member of the French Academy of Sciences, Professor of Cell Biology at "Necker - Enfants Malades" Medical schol.

They also attended the launch of the AXA-Paris Descartes Chair on Longevity, “A systems approach to individual differences in longevity”, in the presence of 

  • Henri de Castries, Chairman of the Management Board and CEO –AXA
  • Axel Kahn, President of Paris Descartes University
  • E. Suleiman, President of the Scientific Board of the AXA Research Fund
  • T. Kirkwook, Biologist, Director of the Institute for Ageing and Health –Newcastle
  • L. Partridge, Geneticist, Director of the Institute of Healthy Ageing –London
  • J. W.Vaupel, Demographer, Founding Director of the Max Planck Institute forDemographic Research –Rostock
  • A. Baudisch, Biodemographer, Independent Junior Research Group Leader at the Max Planck Institute for Demographic Research –Rostock
  • F. Taddei, Geneticist, Research Director at Inserm, Director of the Centre de Recherche Interdisciplinaire at Paris Descartes University –Paris
  • J.-C. Menioux, Group Chief Risk Officer –AXA
  • L.Taleyson, Head of Life Risks –AXA.

 

 

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280 /talent-days-environmental-risks-first-edition Talent Days - Environmental Risks - First Edition <p>The AXA Research Fund invited 14 doctoral and post-doctorla fellows, from the Climate Change cluster, in order to<strong> build an AXA Research Fund Community</strong> and to present them&nbsp;informally the AXA Group.</p><p>&nbsp;</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/talent1.jpeg" alt="" title="" class="imagecache imagecache-contentimage" /> The AXA Research Fund invited 14 doctoral and post-doctorla fellows, from the Climate Change cluster, in order to build an AXA Research Fund Community and to present them informally the AXA Group.

 

]]>
283 /launch-of-the-axa-ecole-polytechnique-chair-in-cardiovascular-cellular-engineering Launch of the AXA - Ecole Polytechnique Chair in Cardiovascular Cellular Engineering <p>The major interest of this chair will be to build a bridge between mechanics and biology to formulate new approaches and thus fight against cardiovascular diseases, which remain the leading cause of mortality in the world.<br />« Heart disease and stroke are the two leading causes of death in Europe today. These diseases are caused by atherosclerosis, or thickening of the arterial walls which leads to arterial blockage by lipid-rich plaques.</p><p>In addition to genetic and lifestyle factors, there is a mechanical element related to arterial blood flow which is critical to the development of atherosclerosis. This is the focus of our cellular engineering approach which will enhance our understanding of the disease as well as lead to the development of new therapeutic strategies which will contribute to extending life expectancy.» Abdul Barakat</p><p>By endowing the École Polytechnique to create this permanent chair, the AXA Research Fund wanted to support an ambitious and cutting edge programme. Indeed the chair will for the first time study atherosclerosis through a transdisciplinary approach combining biology and engineering. It also aims to develop a new<br />generation of engineers sufficiently versed in biology to formulate original approaches to these diseases. This partnership expresses our wish both to encourage innovative science and to help institutions attract the best talent to reinforce their research and training capacity at the highest level.</p><p>&nbsp;</p><p><a class="link_01" href="http://89.31.145.183/project/abdul-barakat">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/0003_chaire_axa_14062010pl.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> The major interest of this chair will be to build a bridge between mechanics and biology to formulate new approaches and thus fight against cardiovascular diseases, which remain the leading cause of mortality in the world.
« Heart disease and stroke are the two leading causes of death in Europe today. These diseases are caused by atherosclerosis, or thickening of the arterial walls which leads to arterial blockage by lipid-rich plaques.

In addition to genetic and lifestyle factors, there is a mechanical element related to arterial blood flow which is critical to the development of atherosclerosis. This is the focus of our cellular engineering approach which will enhance our understanding of the disease as well as lead to the development of new therapeutic strategies which will contribute to extending life expectancy.» Abdul Barakat

By endowing the École Polytechnique to create this permanent chair, the AXA Research Fund wanted to support an ambitious and cutting edge programme. Indeed the chair will for the first time study atherosclerosis through a transdisciplinary approach combining biology and engineering. It also aims to develop a new
generation of engineers sufficiently versed in biology to formulate original approaches to these diseases. This partnership expresses our wish both to encourage innovative science and to help institutions attract the best talent to reinforce their research and training capacity at the highest level.

 

Click here to find out more about this research supported by the AXA Research Fund

]]>
707 /launch-of-the-axa-nus-project-on-biology-of-decision-making-under-risk Launch of the AXA - NUS Project on Biology of Decision making under risk <p>AXA Research Fund, a major and innovative initiative of scientific philanthropy<br />supported by the worldwide insurance group AXA, is awarding 517,000 Euros<br />(S$904, 079) over a period of 3 years, to the National University of Singapore (NUS)<br />to undertake a research project on the “Biology of Decision Making under Risk”. This<br />marks the first time the AXA Research Fund has awarded a grant to a university in<br />Asia.</p><p><br />The research project seeks a deeper understanding of the biological mechanisms<br />underpinning individual differences in how people take risks by bringing together<br />methodologies from behavioral and experimental economics and the biological<br />sciences. The study will generate quantitative phenotypes that can propel advances<br />in understanding the molecular architecture of human decision making in a risky<br />environment.</p><p><br />The research study will be led by Prof Richard P. Ebstein and Prof Chew Soo Hong<br />of NUS’ Department of Psychology and Department of Economics respectively.<br />John R. Dacey, CEO of AXA Japan-Asia-Pacific Region and Member of the AXA<br />Group Executive Committee, declared: “I am very pleased to announce the first<br />Asian grant by the AXA Research Fund to the National University of Singapore, for<br />an outstanding and innovative research project led by Professor Ebstein and<br />Professor Chew.<br />“As a global leader in insurance business, AXA actively promotes the understanding<br />and prevention of risks. We are convinced that basic research is essential for the<br />development of knowledge in this area and thus contributes to building stronger and<br />safer societies.<br />“AXA teams in Singapore share with me the pride of this extension of the AXA<br />Research Fund outside of Europe. I believe it is a very strong sign of our long term<br />commitment to the region and its strategic importance for the Group.<br />“I sincerely wish all the best to Professor Ebstein and his team and I really hope this<br />first step will encourage more Asian institutions to apply.”</p><p><br />Prof Barry Halliwell, Deputy President (Research and Technology), NUS, said: “We<br />are pleased to receive this esteemed gift from the AXA Research Fund which will<br />support the work of NUS researchers to identify and explain the biological<br />underpinnings of risk-taking in human choice and behavior.<br />“The gift is recognition of NUS as a leading global university centred in Asia, and the<br />University’s relentless drive to contribute to holistic understanding of critical issues<br />for Asia and the rest of the world.”</p><p><br />Principal Investigator of the study, Prof Richard P. Ebstein, Department of<br />Psychology, Faculty of Arts and Social Sciences at NUS, said: “We believe that<br />human decision making in a risky environment has its roots in the early evolution of<br />life itself. The specific aim of our project is to identify and unravel the basic biological<br />mechanism underpinning decision making under risk.”</p><p><br />Several problems that afflict the world today remain obscure due to an almost<br />complete ignorance of the biological architecture of human decision making. These<br />problems can be viewed in terms of breakdowns in decision making ranging from<br />economic meltdowns, driven in large measure by widespread breakdowns in trust<br />between individuals and institutions freezing commerce worldwide, to disorders in<br />individuals where the primary symptoms are more dramatic and often involve<br />pathological changes in decision making behavior, e.g. drug addiction, pathological<br />gambling, eating disorders, borderline personality disorders and extreme mistakes in<br />saving and spending.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/ebstein_halliwell_hermant_chew_williams.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> AXA Research Fund, a major and innovative initiative of scientific philanthropy
supported by the worldwide insurance group AXA, is awarding 517,000 Euros
(S$904, 079) over a period of 3 years, to the National University of Singapore (NUS)
to undertake a research project on the “Biology of Decision Making under Risk”. This
marks the first time the AXA Research Fund has awarded a grant to a university in
Asia.


The research project seeks a deeper understanding of the biological mechanisms
underpinning individual differences in how people take risks by bringing together
methodologies from behavioral and experimental economics and the biological
sciences. The study will generate quantitative phenotypes that can propel advances
in understanding the molecular architecture of human decision making in a risky
environment.


The research study will be led by Prof Richard P. Ebstein and Prof Chew Soo Hong
of NUS’ Department of Psychology and Department of Economics respectively.
John R. Dacey, CEO of AXA Japan-Asia-Pacific Region and Member of the AXA
Group Executive Committee, declared: “I am very pleased to announce the first
Asian grant by the AXA Research Fund to the National University of Singapore, for
an outstanding and innovative research project led by Professor Ebstein and
Professor Chew.
“As a global leader in insurance business, AXA actively promotes the understanding
and prevention of risks. We are convinced that basic research is essential for the
development of knowledge in this area and thus contributes to building stronger and
safer societies.
“AXA teams in Singapore share with me the pride of this extension of the AXA
Research Fund outside of Europe. I believe it is a very strong sign of our long term
commitment to the region and its strategic importance for the Group.
“I sincerely wish all the best to Professor Ebstein and his team and I really hope this
first step will encourage more Asian institutions to apply.”


Prof Barry Halliwell, Deputy President (Research and Technology), NUS, said: “We
are pleased to receive this esteemed gift from the AXA Research Fund which will
support the work of NUS researchers to identify and explain the biological
underpinnings of risk-taking in human choice and behavior.
“The gift is recognition of NUS as a leading global university centred in Asia, and the
University’s relentless drive to contribute to holistic understanding of critical issues
for Asia and the rest of the world.”


Principal Investigator of the study, Prof Richard P. Ebstein, Department of
Psychology, Faculty of Arts and Social Sciences at NUS, said: “We believe that
human decision making in a risky environment has its roots in the early evolution of
life itself. The specific aim of our project is to identify and unravel the basic biological
mechanism underpinning decision making under risk.”


Several problems that afflict the world today remain obscure due to an almost
complete ignorance of the biological architecture of human decision making. These
problems can be viewed in terms of breakdowns in decision making ranging from
economic meltdowns, driven in large measure by widespread breakdowns in trust
between individuals and institutions freezing commerce worldwide, to disorders in
individuals where the primary symptoms are more dramatic and often involve
pathological changes in decision making behavior, e.g. drug addiction, pathological
gambling, eating disorders, borderline personality disorders and extreme mistakes in
saving and spending.

]]>
708 /launch-of-the-axa-newcastle-chair-on-longevity-and-healthy-active-life-0 Launch of the AXA – Newcastle Chair on Longevity and Healthy Active Life <p>Life expectancy is still increasing in the UK at the rate of around 2 years each decade. This is a remarkable achievement but it is often viewed negatively, not least because of the greater numbers of those aged 85 years and older, the so-called ‘oldest old’, with their high rates of age-related diseases and disability. However we have little firm evidence of whether the extra years of life we are now enjoying are spent in good or poor health and the impact that the greater numbers of the oldest old will have on health and care services.</p><p><br />In recognition of its leading role in ageing research world-wide, the AXA Research Fund has recently funded Professor Carol Jagger to a permanent Chair in the Institute for Ageing and Health at Newcastle University to further research on understanding trends, causes and consequences of Longevity and Healthy Active Life for future health and social care policy.</p><p><br />Carol Jagger, AXA Professor of Epidemiology of Ageing, Institute for Ageing &amp; Health (IAH), Newcastle University, said: “This is a fabulous opportunity for me. It will allow me to carry out extra work and it has already started to make a difference.</p><p><br />“This position will allow me to develop my programme in a place where there is a great resource. Working in the IAH offers a great opportunity for collaboration with others and will enable me to carry my work forward.</p><p><br />“I have been working with the 85+ study for the past five years and we have made some interesting findings already and I am sure there are more to come.”</p><p>&nbsp;</p><p><a class="link_01" href="http://89.31.145.183/project/carol-jaegger">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/newcastle_university_jpeg.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Life expectancy is still increasing in the UK at the rate of around 2 years each decade. This is a remarkable achievement but it is often viewed negatively, not least because of the greater numbers of those aged 85 years and older, the so-called ‘oldest old’, with their high rates of age-related diseases and disability. However we have little firm evidence of whether the extra years of life we are now enjoying are spent in good or poor health and the impact that the greater numbers of the oldest old will have on health and care services.


In recognition of its leading role in ageing research world-wide, the AXA Research Fund has recently funded Professor Carol Jagger to a permanent Chair in the Institute for Ageing and Health at Newcastle University to further research on understanding trends, causes and consequences of Longevity and Healthy Active Life for future health and social care policy.


Carol Jagger, AXA Professor of Epidemiology of Ageing, Institute for Ageing & Health (IAH), Newcastle University, said: “This is a fabulous opportunity for me. It will allow me to carry out extra work and it has already started to make a difference.


“This position will allow me to develop my programme in a place where there is a great resource. Working in the IAH offers a great opportunity for collaboration with others and will enable me to carry my work forward.


“I have been working with the 85+ study for the past five years and we have made some interesting findings already and I am sure there are more to come.”

 

Click here to find out more about this research supported by the AXA Research Fund

]]>
709 /talent-days-life-risks-second-edition Talent Days - Life Risks - Second Edition <p>Longevity is one of the main challenges for the future of our societies. Both as an expert and as a<br />global socio-economic player, AXA wants to promote a renewed vision of longevity through a global, transdisciplinary and positive approach of this demographical change.</p><p>20 selected AXA fellows will attend the AXA Forum for Longevity on Monday, March 28th, and then will participate on two-days workshops and Master Class. </p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/une_echo_gettyimage-webs.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Longevity is one of the main challenges for the future of our societies. Both as an expert and as a
global socio-economic player, AXA wants to promote a renewed vision of longevity through a global, transdisciplinary and positive approach of this demographical change.

20 selected AXA fellows will attend the AXA Forum for Longevity on Monday, March 28th, and then will participate on two-days workshops and Master Class.

]]>
713 /talent-day-socio-economic-risks-first-edition Talent Day - Socio-economic risks - First Edition <p>About 12 post-doctoral and doctoral fellows, from about 15 international institutions, came to Paris.<br /><br /> One highlight of the Talent Day is the Poster session. Attendees present visually and oraly their research work to their peer and discuss about it.<br /><br />The grantees attended the <a class="title_01" href="https://sites.google.com/a/greg-hec.com/d-tea-workshop/" target="_blank"><strong>D-TEA</strong> </a>(Decision: Theory, Experiments, and Applications) Symposium 2010 organized at AXA headquarters</p><p>and the <a href="http://89.31.145.183/launch-of-the-axa-hec-chair-for-decision-science"><span class="title_01"><strong>launch of the HEC - AXA Chair for Decision Science</strong></span></a> organized at AXA headquarters, with the participation of Pr. Mohammed Abdellaoui, Itzhak Gilboa, Gerd Gigerenzer and Henri de Castries, Chairman &amp; CEO - AXA Group.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/td3-1.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> About 12 post-doctoral and doctoral fellows, from about 15 international institutions, came to Paris.

One highlight of the Talent Day is the Poster session. Attendees present visually and oraly their research work to their peer and discuss about it.

The grantees attended the D-TEA (Decision: Theory, Experiments, and Applications) Symposium 2010 organized at AXA headquarters

and the launch of the HEC - AXA Chair for Decision Science organized at AXA headquarters, with the participation of Pr. Mohammed Abdellaoui, Itzhak Gilboa, Gerd Gigerenzer and Henri de Castries, Chairman & CEO - AXA Group.

]]>
714 /talent-days-environmental-risks-second-edition Talent Days - Environmental Risks - Second Edition <p>This event aims at boosting the young researchers' career and help them to network with peers, share knowledge and best practice.<br /> This second edition on the environmental theme involved both new and long-run sponsored AXA fellows. <br /> <br /> The key event of these Talent Days is a plenary session by a world class academic. This specific session is highly appreciated by attendees as is a privileged opportunity to learn from a leading scientist in the field. <br /> <br /> Sir Brian Hoskins and Professor Hervé Le Treut were the Key speakers for this session.</p> <p>Please see our <a href="http://89.31.145.183/sites/dev/files/talentdayprogram_4.pdf" target="_blank"><strong>Program page</strong></a> to have more details about the Talent Day, and have a look on the <a href="http://89.31.145.183/sites/dev/files/whos_who_talent_day_environmental_risk_4.pdf" target="_blank">Facebook document</a> !</p> <p><strong>This session participants so far: 7 Post-Doctoral and 13 Doctoral Fellows selected in 2008, 2009 and 2010, of 13 nationalities and from 18 international institutions.&nbsp;</strong></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/talent_day-environnment.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> This event aims at boosting the young researchers' career and help them to network with peers, share knowledge and best practice.
This second edition on the environmental theme involved both new and long-run sponsored AXA fellows.

The key event of these Talent Days is a plenary session by a world class academic. This specific session is highly appreciated by attendees as is a privileged opportunity to learn from a leading scientist in the field.

Sir Brian Hoskins and Professor Hervé Le Treut were the Key speakers for this session.

Please see our Program page to have more details about the Talent Day, and have a look on the Facebook document !

This session participants so far: 7 Post-Doctoral and 13 Doctoral Fellows selected in 2008, 2009 and 2010, of 13 nationalities and from 18 international institutions. 

]]>
715 /launch-of-the-axa-lse-project-on-risk-management-and-regulation-of-financial-institutions Launch of the AXA - LSE Project on Risk management and regulation of financial institutions <p>Professor David Webb, Director of LSE’s Financial Markets Group which will<br />undertake the research, said: ‘The current financial crisis has revealed a distance<br />between our understanding of the interconnected behaviour of banks, the structure of<br />the banking systems and layers of regulation. We aim to gain a better understanding<br />of the weakness of the current financial architecture and to assess the scope for<br />greater financial stability through governance and regulation.’</p><p><br />Eric Chaney, Chief Economist of the AXA Group said: ‘While this research will focus<br />on filling gaps in the academic understanding of these issues it will clearly also be<br />extremely relevant to the development of knowledge informed policy.’</p><p><br />LSE academics undertaking the AXA Research Programme, will, for example,<br />assess the performance of the global regulatory framework during the current crisis<br />to analyse changes in regulation that could help reduce the risks of such crises in the<br />future. They will look at the whole structure of capital standards, leverage ratios,<br />accounting principles for bank assets and liquidity provision to the market. They will<br />also examine the use of risk models and balance sheet information in managing risk<br />at the level of intuitions, and for system-wide regulation.</p><p><br />Another strand of the research programme will scrutinise the governance of banks<br />looking at board and ownership structure and how the top management are<br />remunerated. This will aim to learn more about the skill-set and financial knowledge<br />of non-executive directors, the board’s function when seen in competition with<br />banking regulation and ultimately its impact on bank performance.</p><p><br />High-powered incentive pay, the limited penalties when something goes wrong and<br />the way this encourages excessive risk taking by financial institutions will also be<br />examined.</p><p><br />To launch the research programme, a public panel discussion on the future of<br />banking and financial regulation will take place at LSE on Monday 19 October.</p><p>The panel will be Chief Economist of the AXA Group Eric Chaney, Dominique Carrel-<br />Billiard, CEO of AXA Investment Managers and LSE Professors Charles Goodhart<br />and David Webb.</p><p>&nbsp;</p><p><a class="link_01" href="http://89.31.145.183/project/david-webb">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/_mg_7319-2.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Professor David Webb, Director of LSE’s Financial Markets Group which will
undertake the research, said: ‘The current financial crisis has revealed a distance
between our understanding of the interconnected behaviour of banks, the structure of
the banking systems and layers of regulation. We aim to gain a better understanding
of the weakness of the current financial architecture and to assess the scope for
greater financial stability through governance and regulation.’


Eric Chaney, Chief Economist of the AXA Group said: ‘While this research will focus
on filling gaps in the academic understanding of these issues it will clearly also be
extremely relevant to the development of knowledge informed policy.’


LSE academics undertaking the AXA Research Programme, will, for example,
assess the performance of the global regulatory framework during the current crisis
to analyse changes in regulation that could help reduce the risks of such crises in the
future. They will look at the whole structure of capital standards, leverage ratios,
accounting principles for bank assets and liquidity provision to the market. They will
also examine the use of risk models and balance sheet information in managing risk
at the level of intuitions, and for system-wide regulation.


Another strand of the research programme will scrutinise the governance of banks
looking at board and ownership structure and how the top management are
remunerated. This will aim to learn more about the skill-set and financial knowledge
of non-executive directors, the board’s function when seen in competition with
banking regulation and ultimately its impact on bank performance.


High-powered incentive pay, the limited penalties when something goes wrong and
the way this encourages excessive risk taking by financial institutions will also be
examined.


To launch the research programme, a public panel discussion on the future of
banking and financial regulation will take place at LSE on Monday 19 October.

The panel will be Chief Economist of the AXA Group Eric Chaney, Dominique Carrel-
Billiard, CEO of AXA Investment Managers and LSE Professors Charles Goodhart
and David Webb.

 

Click here to find out more about this research supported by the AXA Research Fund

]]>
716 /launch-of-the-axa-paris-descartes-chair-in-a-systems-approach-to-individual-differences-in-longevity Launch of the AXA - Paris Descartes Chair in A systems approach to individual differences in longevity <p>Convinced that basic research is essential to advancing knowledge, the AXA Group, via the AXA<br />Research Fund, is providing support to the scientific community to develop cutting-edge<br />research that will provide a clearer understanding of the challenges posed by the increase in<br />lifespan.</p><p><br />Endowed with €1,250,000 for a five-year period, the AXA-Paris Descartes Chair in "A systems<br />approach to individual differences in longevity" aims to train a new generation of researchers<br />with a scientific understanding of a longer lifespan, approached from a multidisciplinary point of<br />view. Indeed, the major innovation of this Chair resides in the multidisciplinary approach it<br />proposes, which to date is unique in the world. The holders of the Chair, Linda Partridge,<br />Thomas Kirkwood, François Taddei and James Vaupel, have different scientific backgrounds:<br />demographics, genetics, nutrition, biology, etc. This diversity of approaches should make it<br />possible to study accurately the numerous parameters that affect the longevity of an individual.</p><p><br />By providing its support for the AXA-Paris Descartes Chair, the AXA Research Fund hopes it will<br />offer researchers the resources necessary to advance knowledge on the mechanisms of ageing.</p><p>&nbsp;</p><p><span style="text-decoration: underline;">What is longevity?</span><br />Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research.<br /><em>Prof. Thomas Kirkwood,</em><br /><em>Director of the Institute for Ageing and Health, Newcastle, UK.</em></p><p><em><br /></em></p><p><span style="text-decoration: underline;">What are the approaches and objectives of this Chair?</span><br />At present, no explanation provided by a single discipline is sufficient to understand individual differences in longevity. Indeed, the main problem faced by research on longevity resides in the complexity of ageing, which is a phenomenon dependent on numerous parameters, such as genetic heritage, social background or the environment. In this context, the multidisciplinary careers of the Chair holders constitute a major asset and valuable foundations for the work considered. This Chair also has an actual educational objective: it aims to disseminate knowledge and promote vocations. One of our major aims is to train a new generation of researchers with a scientific understanding of ageing, approached from a multidisciplinary point of view and in an integrated manner. We hope to enable the emergence of joint research projects involving Master's and PhD students and postdoctoral fellows from our different institutions and of different nationalities.<br /><em>François Taddei,</em><br /><em>Instigator and holder of the AXA-Paris Descartes Chair</em></p><p>&nbsp;</p><p><a class="link_01" href="http://89.31.145.183/project/kirkwoodpartridgevaupeltaddei">Click here to find out more about this research supported by the AXA Research Fund</a></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/axa_-_168.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Convinced that basic research is essential to advancing knowledge, the AXA Group, via the AXA
Research Fund, is providing support to the scientific community to develop cutting-edge
research that will provide a clearer understanding of the challenges posed by the increase in
lifespan.


Endowed with €1,250,000 for a five-year period, the AXA-Paris Descartes Chair in "A systems
approach to individual differences in longevity" aims to train a new generation of researchers
with a scientific understanding of a longer lifespan, approached from a multidisciplinary point of
view. Indeed, the major innovation of this Chair resides in the multidisciplinary approach it
proposes, which to date is unique in the world. The holders of the Chair, Linda Partridge,
Thomas Kirkwood, François Taddei and James Vaupel, have different scientific backgrounds:
demographics, genetics, nutrition, biology, etc. This diversity of approaches should make it
possible to study accurately the numerous parameters that affect the longevity of an individual.


By providing its support for the AXA-Paris Descartes Chair, the AXA Research Fund hopes it will
offer researchers the resources necessary to advance knowledge on the mechanisms of ageing.

 

What is longevity?
Within a period of eight generations (about 200 years), life expectancy has doubled. In the UK and France, it has been increasing at a rate of two years per decade. So for each hour that elapses, your lifespan could be increasing by 12 minutes, i.e. 5 hours per day! We commonly refer to this phenomenon as longevity. Alongside global warming, longevity, or the increasing mean lifespan of a living being, has become one of the major challenges of modern society, and must be a key priority for research.
Prof. Thomas Kirkwood,
Director of the Institute for Ageing and Health, Newcastle, UK.


What are the approaches and objectives of this Chair?
At present, no explanation provided by a single discipline is sufficient to understand individual differences in longevity. Indeed, the main problem faced by research on longevity resides in the complexity of ageing, which is a phenomenon dependent on numerous parameters, such as genetic heritage, social background or the environment. In this context, the multidisciplinary careers of the Chair holders constitute a major asset and valuable foundations for the work considered. This Chair also has an actual educational objective: it aims to disseminate knowledge and promote vocations. One of our major aims is to train a new generation of researchers with a scientific understanding of ageing, approached from a multidisciplinary point of view and in an integrated manner. We hope to enable the emergence of joint research projects involving Master's and PhD students and postdoctoral fellows from our different institutions and of different nationalities.
François Taddei,
Instigator and holder of the AXA-Paris Descartes Chair

 

Click here to find out more about this research supported by the AXA Research Fund

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717 /axa-academie-des-sciences-2010-award AXA - Académie des Sciences 2010 award <p>The Académie des Sciences invited 6 young biologists to present the results of their research work as published in the best world science journals in 2009-2010. Each laureate's presentation was preceded by a short talk of their advisor to briefly describe the research field each projects takes part.</p><p>With this original initiative,&nbsp;the Académie des sciences seeks to promote young researchers. This initiative has been launched by Pascale Cossart, Member of the Académie des sciences, Director of the <em>Interactions Bactéries-Cellules</em> Unit at the Institut Pasteur, Paris, and Member of the AXA Research Fund Scientific Board.</p><p>Committed to support world-class innovative research, the AXA Research Fund encourages this young researchers with a € 2.000 grant for each of them.</p><p><img src="/sites/dev/files/upload/communication/2010/logo.jpg" alt="" width="400" height="133" /></p><p>Here is the list of the laureates.</p><p><strong>Jan-Hendrik Hehemann</strong><br />UMR 7139 (CNRS/UPMC), Végétaux Marins et Biomolécules, Station Biologique de Roscoff<em>,</em> France<br /><em>Le « sushi factor » : transfert de gènes, impliqués dans la digestion des algues rouges, de bactéries marines vers la microflore intestinale des Japonais</em><strong>&nbsp;</strong></p><p><strong>Mathieu Coureuil</strong><br />INSERM U1002, Laboratoire de Pathogénie des Infections Systémiques, France<br /><em>Neisseria meningitidis adhère aux cellules endothéliales cérébrales</em><br /><em>et envahit les méninges</em><strong>&nbsp;</strong></p><p><strong>Sandrine Sarrazin</strong><br />Centre d’Immunologie de Marseille-Luminy, (CIML), CNRS/ INSERM/Université de la Méditerranée, France<br /><em>Le fabuleux destin d’une cellule souche</em><strong>&nbsp;</strong></p><p><strong>Isabelle d’Erfurth </strong><br />INRA, Institut Jean-Pierre Bourgin, France<br /><em>Comment transformer la méiose en mitose</em><strong>&nbsp;</strong></p><p><strong>Gabrielle Girardeau </strong><br />Laboratoire de Physiologie de la Perception et de l’Action, CNRS - Collège de France, France<br /><em>La nuit porte conseil : comment le cerveau renforce la mémoire pendant le sommeil</em><strong>&nbsp;</strong></p><p><strong>François Ghiringhelli </strong><br />INSERM, Institut Gustave Roussy, France<br /><em>La chimiothérapie anticancéreuse : pas simplement des agents toxiques, mais aussi des traitements immunologiques</em></p><p>&nbsp;</p><p>To see the video of this conference, please visit <a href="http://www.academie-sciences.fr/video/v080610.htm">the Académie des Sciences website</a>.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/salle_seances_mlm.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> The Académie des Sciences invited 6 young biologists to present the results of their research work as published in the best world science journals in 2009-2010. Each laureate's presentation was preceded by a short talk of their advisor to briefly describe the research field each projects takes part.

With this original initiative, the Académie des sciences seeks to promote young researchers. This initiative has been launched by Pascale Cossart, Member of the Académie des sciences, Director of the Interactions Bactéries-Cellules Unit at the Institut Pasteur, Paris, and Member of the AXA Research Fund Scientific Board.

Committed to support world-class innovative research, the AXA Research Fund encourages this young researchers with a € 2.000 grant for each of them.

Here is the list of the laureates.

Jan-Hendrik Hehemann
UMR 7139 (CNRS/UPMC), Végétaux Marins et Biomolécules, Station Biologique de Roscoff, France
Le « sushi factor » : transfert de gènes, impliqués dans la digestion des algues rouges, de bactéries marines vers la microflore intestinale des Japonais 

Mathieu Coureuil
INSERM U1002, Laboratoire de Pathogénie des Infections Systémiques, France
Neisseria meningitidis adhère aux cellules endothéliales cérébrales
et envahit les méninges 

Sandrine Sarrazin
Centre d’Immunologie de Marseille-Luminy, (CIML), CNRS/ INSERM/Université de la Méditerranée, France
Le fabuleux destin d’une cellule souche 

Isabelle d’Erfurth
INRA, Institut Jean-Pierre Bourgin, France
Comment transformer la méiose en mitose 

Gabrielle Girardeau
Laboratoire de Physiologie de la Perception et de l’Action, CNRS - Collège de France, France
La nuit porte conseil : comment le cerveau renforce la mémoire pendant le sommeil 

François Ghiringhelli
INSERM, Institut Gustave Roussy, France
La chimiothérapie anticancéreuse : pas simplement des agents toxiques, mais aussi des traitements immunologiques

 

To see the video of this conference, please visit the Académie des Sciences website.

]]>
787 /march-21st-british-council-science-po-conference-on-uncertainty-in-decisoin-making-with-denis March 21st : British Council -Science Po conference on Uncertainty in Decisoin Making with Denis Duverne ! <p>To see the video of the conference, please visit this <a href="http://www.axa-research.org/faq-register-an-institution" target="_blank">page</a>.</p><p><strong><em>The British Council in France and the </em></strong><em><em>Institute for Sustainable</em></em><strong><em> Development and <em><em>International</em></em></em></strong><em> <strong>Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion:</strong></em><strong><em> <br /></em></strong></p> <p><strong>“Scientific uncertainty in decision-making”<em> <br /></em></strong></p> <p><strong><em>Panel members: </em></strong></p> <p><strong>Professor Sir Michael Rawlins, </strong>Chairman of the National Institute for Health and Clinical Excellence (UK)</p> <p><strong>Denis Duverne, </strong>Deputy Chief Executive Officer of AXA </p> <p>The panel will be chaired by <strong>Laurence Tubiana</strong>, Director of the Institute for Sustainable Development and International Relations (IDDRI) </p> <p><strong>Monday 21<sup>st</sup> March, 2011 – from 6:00 p.m to 8:00 p.m</strong></p> <p><em>Amphithéâtre Boutmy, Sciences Po, 27, rue Saint Guillaume, 75007 Paris</em></p> <p>Recent debate on the role of human activity in climate change, on the efficacy of the H1N1 vaccine or on renewable energies policy, has brought the concept of scientific uncertainty to the forefront of public and media attention. But this debate has also brought to light the misunderstanding surrounding the concept and the dangers of its possible misappropriation.</p> <p>With decision-makers required to take ever-increasing account of scientific uncertainties, the conference’s panellists will discuss their own experience of high-level decision-making and will explain how they have had to deal with scientific uncertainty whilst making strategic decisions. How do decision-makers – be they in the political, public or economic sphere – make decisions when they are confronted with uncertainty? What lessons can be drawn from recent experiences in France and in the United Kingdom where uncertainty has played a major role in supporting or discrediting a given position? What are the respective roles and responsibilities of scientists and the media in the public understanding of scientific uncertainty?</p> <p>Professor Sir Michael Rawlins and Denis Duverne will address these questions and will then open up the discussion to the public. </p> <p><strong>Simultaneous interpretation into French and English will be available during the discussion <br /></strong></p> <p><strong>Please register for the debate on <a href="http://www.iddri.org/Activites/Conferences-internationales/Scientific-uncertainty-in-decision-making/">IDDRI website</a></strong></p> <p><strong>or by email to Julie Cohen – <a href="mailto:julie.cohen@iddri.org">julie.cohen@iddri.org</a> </strong></p> <p class="Default"><strong>Professor Sir Michael Rawlins</strong> has been chairman of the National Institute of Health &amp; Clinical Excellence (NICE) since its formation in 1999. NICE is an independent organisation responsible for providing national guidance on promoting good health and preventing and treating ill health. Sir Michael Rawlins is also Honorary Professor at the London School of Hygiene and Tropical Medicine, University of London, and Emeritus Professor at the University of Newcastle upon Tyne. He was the Ruth and Lionel Jacobson Professor of Clinical Pharmacology at the University of Newcastle upon Tyne from 1973 to 2006 .At the same time he held the position of consultant physician and consultant clinical pharmacologist to the Newcastle Hospitals NHS Trust. He was vice-chairman (1987-1992) and chairman (1993-1998) of the Committee on Safety of Medicines; and chairman of the Advisory Council on the Misuse of Drugs (1998 - 2008).</p> <p class="Default"><em><br /> </em><strong>Denis Duverne</strong> has been Deputy Chief Executive Officer of AXA, in charge of Finance, Strategy and Operations since April 2010. He is a graduate of the École des Hautes Études Commerciales (HEC). After graduating from the École Nationale d'Administration (ENA), he started his career in 1984 as commercial counsellor for the French Consulate General in New York before becoming director of the Corporate Taxes Department for the French Ministry of Finance in 1986. In 1988, he became Deputy Assistant Secretary for Tax Policy for the French Ministry of Finance and, in 1991, he was appointed Corporate Secretary of Compagnie Financière IBI. In 1992, he became a member of the Executive Committee of Banque Colbert, in charge of operations. In 1995, Denis Duverne joined the AXA Group and assumed responsibility for supervision of AXA's operations in the US and the UK and managed the reorganization of AXA companies in Belgium and the United Kingdom. Since February 2003, Denis Duverne has been a member of the AXA Management Board. From February 2003 to December 2009, he was the Management Board member in charge of Finance, Control and Strategy. From January 2010 to April 2010, he assumed broader responsibilities as Management Board member in charge of Finance, Strategy and Operations.</p> <p class="Default">&nbsp;</p><p> <strong>Laurence Tubiana</strong> is founder of the Institute for Sustainable Development and International Relations&nbsp;(IDDRI) in Paris. She follows and participates in the international negotiations on climate change, in which IDDRI is highly involved. She is also professor and director of the Sustainable Development Centre at Sciences Po Paris. From May 2009 to May 2010, Laurence Tubiana was asked to set up the new direction of Global Publics Goods of the French Ministry of Foreign and European Affairs. She is a member of several scientific boards of major research institutions such as the French Agricultural Research Centre for International Development&nbsp;(CIRAD), the India Council for Sustainable Development and the China Council for International Cooperation on Environment and Development. From 1997 to 2002, Laurence Tubiana served as senior advisor to the Prime Minister, Lionel Jospin, on environmental issues and conducted a number of international negotiations on this subject. She was also member of the French Council of Economic Analysis and research director for the French National Institute for Agricultural Research&nbsp;(INRA). She has been a representative of the European NGOs at the World Bank and directed the French-based NGO Solagral. Founder of the journal <em>Le Courrier de la Planète,</em> she has published a number of articles and books on environment, development and international issues. Since 2007, she has co-directed the publication of the annual review <em>Sustainable Development in Action – A Planet for Life</em>.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/document_acrobat_2.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> To see the video of the conference, please visit this page.

The British Council in France and the Institute for Sustainable Development and International Relations (IDDRI), in collaboration with the AXA Research Fund are pleased to invite you to attend a public panel discussion:

“Scientific uncertainty in decision-making”

Panel members:

Professor Sir Michael Rawlins, Chairman of the National Institute for Health and Clinical Excellence (UK)

Denis Duverne, Deputy Chief Executive Officer of AXA

The panel will be chaired by Laurence Tubiana, Director of the Institute for Sustainable Development and International Relations (IDDRI)

Monday 21st March, 2011 – from 6:00 p.m to 8:00 p.m

Amphithéâtre Boutmy, Sciences Po, 27, rue Saint Guillaume, 75007 Paris

Recent debate on the role of human activity in climate change, on the efficacy of the H1N1 vaccine or on renewable energies policy, has brought the concept of scientific uncertainty to the forefront of public and media attention. But this debate has also brought to light the misunderstanding surrounding the concept and the dangers of its possible misappropriation.

With decision-makers required to take ever-increasing account of scientific uncertainties, the conference’s panellists will discuss their own experience of high-level decision-making and will explain how they have had to deal with scientific uncertainty whilst making strategic decisions. How do decision-makers – be they in the political, public or economic sphere – make decisions when they are confronted with uncertainty? What lessons can be drawn from recent experiences in France and in the United Kingdom where uncertainty has played a major role in supporting or discrediting a given position? What are the respective roles and responsibilities of scientists and the media in the public understanding of scientific uncertainty?

Professor Sir Michael Rawlins and Denis Duverne will address these questions and will then open up the discussion to the public.

Simultaneous interpretation into French and English will be available during the discussion

Please register for the debate on IDDRI website

or by email to Julie Cohen – julie.cohen@iddri.org

Professor Sir Michael Rawlins has been chairman of the National Institute of Health & Clinical Excellence (NICE) since its formation in 1999. NICE is an independent organisation responsible for providing national guidance on promoting good health and preventing and treating ill health. Sir Michael Rawlins is also Honorary Professor at the London School of Hygiene and Tropical Medicine, University of London, and Emeritus Professor at the University of Newcastle upon Tyne. He was the Ruth and Lionel Jacobson Professor of Clinical Pharmacology at the University of Newcastle upon Tyne from 1973 to 2006 .At the same time he held the position of consultant physician and consultant clinical pharmacologist to the Newcastle Hospitals NHS Trust. He was vice-chairman (1987-1992) and chairman (1993-1998) of the Committee on Safety of Medicines; and chairman of the Advisory Council on the Misuse of Drugs (1998 - 2008).


Denis Duverne has been Deputy Chief Executive Officer of AXA, in charge of Finance, Strategy and Operations since April 2010. He is a graduate of the École des Hautes Études Commerciales (HEC). After graduating from the École Nationale d'Administration (ENA), he started his career in 1984 as commercial counsellor for the French Consulate General in New York before becoming director of the Corporate Taxes Department for the French Ministry of Finance in 1986. In 1988, he became Deputy Assistant Secretary for Tax Policy for the French Ministry of Finance and, in 1991, he was appointed Corporate Secretary of Compagnie Financière IBI. In 1992, he became a member of the Executive Committee of Banque Colbert, in charge of operations. In 1995, Denis Duverne joined the AXA Group and assumed responsibility for supervision of AXA's operations in the US and the UK and managed the reorganization of AXA companies in Belgium and the United Kingdom. Since February 2003, Denis Duverne has been a member of the AXA Management Board. From February 2003 to December 2009, he was the Management Board member in charge of Finance, Control and Strategy. From January 2010 to April 2010, he assumed broader responsibilities as Management Board member in charge of Finance, Strategy and Operations.

 

Laurence Tubiana is founder of the Institute for Sustainable Development and International Relations (IDDRI) in Paris. She follows and participates in the international negotiations on climate change, in which IDDRI is highly involved. She is also professor and director of the Sustainable Development Centre at Sciences Po Paris. From May 2009 to May 2010, Laurence Tubiana was asked to set up the new direction of Global Publics Goods of the French Ministry of Foreign and European Affairs. She is a member of several scientific boards of major research institutions such as the French Agricultural Research Centre for International Development (CIRAD), the India Council for Sustainable Development and the China Council for International Cooperation on Environment and Development. From 1997 to 2002, Laurence Tubiana served as senior advisor to the Prime Minister, Lionel Jospin, on environmental issues and conducted a number of international negotiations on this subject. She was also member of the French Council of Economic Analysis and research director for the French National Institute for Agricultural Research (INRA). She has been a representative of the European NGOs at the World Bank and directed the French-based NGO Solagral. Founder of the journal Le Courrier de la Planète, she has published a number of articles and books on environment, development and international issues. Since 2007, she has co-directed the publication of the annual review Sustainable Development in Action – A Planet for Life.

]]>
795 /2011-axa-academie-des-sciences-award 2011 AXA - Académie des sciences award <p>The Académie des Sciences invited 6 young biologists to present the results of their research work as published in the best world science journals in 2010-2011. Each laureate's presentation was preceded by a short talk of their advisor to briefly describe the research field each projects takes part.</p><p>With this original initiative,&nbsp;the Académie des sciences seeks to promote young researchers. This initiative has been launched by Pascale Cossart, Member of the Académie des sciences, Director of the <em>Interactions Bactéries-Cellules</em> Unit at the Institut Pasteur, Paris, and Member of the AXA Research Fund Scientific Board.</p><p>Committed to support world-class innovative research, the AXA Research Fund encourages this young researchers with a € 2.500 grant for each of them.</p><p><font face="Arial" size="1" color="#373A53">© </font>Gérard Blot - RMN - Institut de France<br /><br /></p><p><img src="/sites/dev/files/upload/communication/2010/logo.jpg" alt="" width="538" height="178" /></p><p>Here is the list of laureates:</p><p><strong>L’étiquetage des neurones du cortex…</strong><em> </em><br />par <strong>Edith Lesburguères et Bruno Bontempi</strong><em>,<strong> </strong></em>Institut des Maladies Neurodégénératives, CNRS - Université de Bordeaux&nbsp;&nbsp;&nbsp; &nbsp;<em>(Science 2011)<br />De l’acquisition à la stabilisation des souvenirs. Une expérience chez le rat permet de décrypter un processus neurobiologique&nbsp; nécessaire à la formation de la mémoire à long terme.</em></p> <p><em>&nbsp;</em></p> <p><strong>Structure atomique de deux anesthésiques généraux liés à leur cible…</strong> <br />par<strong> </strong><strong>Hugues Nury</strong><strong> et Pierre-Jean Corringer</strong>, CNRS, Institut Pasteur, Paris<em> &nbsp;&nbsp;&nbsp;&nbsp;(Nature 2011)<br />La révélation de la structure fine &nbsp;du site d’action des anesthésiques généraux ouvre la voie à la conception de nouvelles classes de ces composés, mieux tolérés par l’organisme. </em></p> <p>&nbsp;</p> <p><strong>Contrôle du développement embryonnaire par des petits ARNs issus de transposons<br /> </strong>par<strong> Catherine Papin et Martine Simonelig,</strong> Institut de Génétique Humaine, CNRS, Montpellier&nbsp;&nbsp; <em>&nbsp;</em><em>&nbsp;(Nature 2010)<br />Ce nouvel éclairage sur la fonction des éléments transposables, longtemps considérés comme des parasites du génome, renforce la notion de co-évolution étroite entre ces éléments et le génome hôte.</em></p><p>&nbsp;</p><p><strong>Le métabolisme cérébral à la loupe biphotonique </strong><br />par <strong>Jérôme Lecoq et Serge Charpak,</strong><strong> </strong>Inserm, CNRS, Paris <em>&nbsp;&nbsp;&nbsp;&nbsp;(Nature Medicine,</em><em> </em>sous presse)<br /><em>Chacune de nos pensées se traduit par une consommation importante d'oxygène par les neurones. Une nouvelle technique d’imagerie permet de mesurer cette consommation et les changements de flux sanguins associés</em></p> <p>&nbsp;</p> <p><strong>Comment sont choisis les sites d’échanges entre chromosomes lors de la méiose ?</strong> <br />par <strong>Frédéric Baudat et Bernard de Massy</strong>, Institut de Génétique Humaine, CNRS, Montpellier &nbsp;&nbsp;&nbsp;<em>(Science 2010)<br />La recombinaison des chromosomes lors de la méiose augmente la diversité génétique à chaque génération. Les échanges ont lieu en des sites précis du génome&nbsp;; une protéine en contrôle la distribution...</em></p> <p>&nbsp;</p> <p><strong>La perception du nitrate par le transporteur NRT1.1 contrôle le développement de la plante…</strong> <br />par<strong> </strong><strong>Gabriel Krouk et Alain Gojon</strong>, CNRS/INRA/Supagro/Université de Montpellier &nbsp;&nbsp;&nbsp;<em>(Dev Cell 2010)<br />Un mécanisme de perception de l’environnement totalement original est mis en lumière&nbsp;: il permet à la plante de favoriser la colonisation racinaire dans les zones du sol perçues comme étant riches en nitrate.</em></p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/institut_exterieur_jour_blot_rmn_0010.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> The Académie des Sciences invited 6 young biologists to present the results of their research work as published in the best world science journals in 2010-2011. Each laureate's presentation was preceded by a short talk of their advisor to briefly describe the research field each projects takes part.

With this original initiative, the Académie des sciences seeks to promote young researchers. This initiative has been launched by Pascale Cossart, Member of the Académie des sciences, Director of the Interactions Bactéries-Cellules Unit at the Institut Pasteur, Paris, and Member of the AXA Research Fund Scientific Board.

Committed to support world-class innovative research, the AXA Research Fund encourages this young researchers with a € 2.500 grant for each of them.

© Gérard Blot - RMN - Institut de France

Here is the list of laureates:

L’étiquetage des neurones du cortex…
par Edith Lesburguères et Bruno Bontempi, Institut des Maladies Neurodégénératives, CNRS - Université de Bordeaux     (Science 2011)
De l’acquisition à la stabilisation des souvenirs. Une expérience chez le rat permet de décrypter un processus neurobiologique  nécessaire à la formation de la mémoire à long terme.

 

Structure atomique de deux anesthésiques généraux liés à leur cible…
par Hugues Nury et Pierre-Jean Corringer, CNRS, Institut Pasteur, Paris     (Nature 2011)
La révélation de la structure fine  du site d’action des anesthésiques généraux ouvre la voie à la conception de nouvelles classes de ces composés, mieux tolérés par l’organisme.

 

Contrôle du développement embryonnaire par des petits ARNs issus de transposons
par Catherine Papin et Martine Simonelig, Institut de Génétique Humaine, CNRS, Montpellier     (Nature 2010)
Ce nouvel éclairage sur la fonction des éléments transposables, longtemps considérés comme des parasites du génome, renforce la notion de co-évolution étroite entre ces éléments et le génome hôte.

 

Le métabolisme cérébral à la loupe biphotonique
par Jérôme Lecoq et Serge Charpak, Inserm, CNRS, Paris     (Nature Medicine, sous presse)
Chacune de nos pensées se traduit par une consommation importante d'oxygène par les neurones. Une nouvelle technique d’imagerie permet de mesurer cette consommation et les changements de flux sanguins associés

 

Comment sont choisis les sites d’échanges entre chromosomes lors de la méiose ?
par Frédéric Baudat et Bernard de Massy, Institut de Génétique Humaine, CNRS, Montpellier    (Science 2010)
La recombinaison des chromosomes lors de la méiose augmente la diversité génétique à chaque génération. Les échanges ont lieu en des sites précis du génome ; une protéine en contrôle la distribution...

 

La perception du nitrate par le transporteur NRT1.1 contrôle le développement de la plante…
par Gabriel Krouk et Alain Gojon, CNRS/INRA/Supagro/Université de Montpellier    (Dev Cell 2010)
Un mécanisme de perception de l’environnement totalement original est mis en lumière : il permet à la plante de favoriser la colonisation racinaire dans les zones du sol perçues comme étant riches en nitrate.

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890 /pop-day-socio-economic-risks POP Day - Socio-economic risks <p>Explaining in simple terms our work to a researcher at the begining of his career can be a difficult task. However, it is a crucial skill in order to be able to convince a research advisor, to dialogue with coworkers from other fields or sensibilizing research managers to our work&nbsp;; it is even more necessary to be able, when we get results, to play a role of expert in the public debate or with the economical actors.</p> <p>This is why, for the first time, the AXA Research Funds has organized a "Pop Day" to help its granted fellows to popularize their work. After a day of breathing, elocution, writing, and layout or illustration techniques exercises to help them explaining simply and clearly their work and preventing them from loosing their consitency, five of them chosed to present the subject of their research before an audience built of board of directors from the AXA Group. Each researcher has illustrated its presentation with pictures, examples, charts and concrete anecdotes. Both the public and the jury enjoyed presentations on the following subjects. (Click on the names to see the presentations)&nbsp; :</p> <ol><li><em>1.&nbsp;&nbsp;&nbsp;&nbsp; </em><em>Probabilities in Decision Trees: the impact of action on uncertainty</em>, by <a href="http://www.axa-research.org/project/shweta-agarwal" target="_blank">Shweta AGARWAL</a> (PhD at the London School of Economics)<br /> <br /> </li><li><em>2.&nbsp;&nbsp;&nbsp;&nbsp;</em><em>The Opium Market, Revenue Opportunities and Insurgency in Afghanistan’s Provinces</em>, by<em> </em><a href="http://www.axa-research.org/project/bove-vincenzo" target="_blank">Vincent BOVE</a> (Post-Doc at the University of Essex)<br /> <br /> </li><li><em>3.&nbsp;&nbsp;&nbsp;&nbsp; </em><em>The Risks of Greed and Fear in Financial Decision Making</em>, by <a href="http://www.axa-research.org/project/elena-pikulina" target="_blank">Helena PIKULINA</a> (PhD at the Tilburg University)<br /> <br /> </li><li><em>4.&nbsp;&nbsp;&nbsp;&nbsp;</em><em>Leading by example : an evolutionary perspective on group-decision making </em>by<em> </em><a href="http://www.axa-research.org/project/andrew-king" target="_blank">Andrew KING</a> (Post-Doc at Institute of Zoology of London)&nbsp;;<br /> <br /> </li><li><em>5.&nbsp;&nbsp;&nbsp;&nbsp;</em><em>Robustness in managing risk uncertainty </em>by<em> </em><a href="http://www.axa-research.org/project/sandberg-anders" target="_blank">Anders SANDBERG</a> (Post-Doc at the University of Oxford)</li></ol><p>&nbsp;</p> <p>Through this event, AXA gives the proof of its will for contributing risk education from the source of the fundamental research.</p><img src="http://www.axa-research.org/sites/dev/files/imagecache/contentimage/u/image/poday_einstein_0.jpg" alt="" title="" class="imagecache imagecache-contentimage" /> Explaining in simple terms our work to a researcher at the begining of his career can be a difficult task. However, it is a crucial skill in order to be able to convince a research advisor, to dialogue with coworkers from other fields or sensibilizing research managers to our work ; it is even more necessary to be able, when we get results, to play a role of expert in the public debate or with the economical actors.

This is why, for the first time, the AXA Research Funds has organized a "Pop Day" to help its granted fellows to popularize their work. After a day of breathing, elocution, writing, and layout or illustration techniques exercises to help them explaining simply and clearly their work and preventing them from loosing their consitency, five of them chosed to present the subject of their research before an audience built of board of directors from the AXA Group. Each researcher has illustrated its presentation with pictures, examples, charts and concrete anecdotes. Both the public and the jury enjoyed presentations on the following subjects. (Click on the names to see the presentations)  :

  1. 1.     Probabilities in Decision Trees: the impact of action on uncertainty, by Shweta AGARWAL (PhD at the London School of Economics)

  2. 2.    The Opium Market, Revenue Opportunities and Insurgency in Afghanistan’s Provinces, by Vincent BOVE (Post-Doc at the University of Essex)

  3. 3.     The Risks of Greed and Fear in Financial Decision Making, by Helena PIKULINA (PhD at the Tilburg University)

  4. 4.    Leading by example : an evolutionary perspective on group-decision making by Andrew KING (Post-Doc at Institute of Zoology of London) ;

  5. 5.    Robustness in managing risk uncertainty by Anders SANDBERG (Post-Doc at the University of Oxford)

 

Through this event, AXA gives the proof of its will for contributing risk education from the source of the fundamental research.

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922 /from-volcanoes-to-vineyards-how-lava-flows-shape-the-landscape From Volcanoes to Vineyards: how lava flows shape the landscape <p><strong>This lecture will take place at the <a>School of Chemistry</a> of Bristol University on November 10 at 4 pm.</strong></p><p>Basaltic lava flows cover much of the Earth’s surface, as well as the surfaces of the other terrestrial planets; thus basalt forms the substrate of many volcanic landscapes (and, often, associated vineyards). The frequency of lava flow activity both threatens nearby communities and provides unique opportunities for volcanologists to study active volcanic processes.</p> <p>For this reason, two of the earliest volcano observatories were founded at volcanoes with frequent lava flow activity (Vesuvius, Italy, in 1841; and Kilauea, Hawaii, in 1912). These dual motivations – hazard and opportunity – have also made locations of frequent lava flow activity the focal point for testing and applying new innovations in volcano monitoring technology, particularly new methods of remote sensing.</p> <p>Professor Cashman will review some of these new techniques and place their contribution in the context of the challenges associated with monitoring and predicting lava flow behaviour, which relate not only to the high temperatures and spatial extents of active flows, but also to their dramatic changes in physical properties during emplacement (from liquids with included gas bubbles to dense solids).</p> <p>Remote sensing observations are also providing us with new perspectives on the post-emplacement evolution of basaltic landscapes, including both their unique hydrological characteristics and key controls on flow revegetation.</p><p><img style="vertical-align: middle;" src="data:image/png;base64,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