On the Schoenberg Transformations in Data Analysis: Theory and Illustrations

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on the arc lengths, angles and curvature of the transformations are proposed, and visualized on artificial data sets by classical multidimensional scaling. A simple distance-based discriminant algorithm illustrates the theory, intimately connected to the Gaussian kernels of Machine Learning

Global shifts, theoretical shifts: changing geographies of religion

10.1177/0309132510362602Progress in Human Geography346755-77

Including all voices in international data-sharing governance

Background Governments, funding bodies, institutions, and publishers have developed a number of strategies to encourage researchers to facilitate access to datasets. The rationale behind this approach is that this will bring a number of benefits and enable advances in healthcare and medicine by allowing the maximum returns from the investment in research, as well as reducing waste and promoting transparency. As this approach gains momentum, these data-sharing practices have implications for many kinds of research as they become standard practice across the world. Main text The governance frameworks that have been developed to support biomedical research are not well equipped to deal with the complexities of international data sharing. This system is nationally based and is dependent upon expert committees for oversight and compliance, which has often led to piece-meal decisionmaking. This system tends to perpetuate inequalities by obscuring the contributions and the important role of different data providers along the data stream, whether they be low- or middle-income country researchers, patients, research participants, groups, or communities. As research and data-sharing activities are largely publicly funded, there is a strong moral argument for including the people who provide the data in decision-making and to develop governance systems for their continued participation. Conclusions We recommend that governance of science becomes more transparent, representative, and responsive to the voices of many constituencies by conducting public consultations about data-sharing addressing issues of access and use; including all data providers in decision-making about the use and sharing of data along the whole of the data stream; and using digital technologies to encourage accessibility, transparency, and accountability. We anticipate that this approach could enhance the legitimacy of the research process, generate insights that may otherwise be overlooked or ignored, and help to bring valuable perspectives into the decision-making around international data sharing.</p

Safety, feasibility and effects of an individualised walking intervention for women undergoing chemotherapy for ovarian cancer: a pilot study

Background: Exercise interventions during adjuvant cancer therapy have been shown to increase functional capacity, relieve fatigue and distress and may assist rates of chemotherapy completion. These studies have been limited to breast, gastric and mixed cancer groups and it is not yet known if a similar intervention is even feasible among women with ovarian cancer. We aimed to assess safety, feasibility and potential effect of a walking intervention in women undergoing chemotherapy for ovarian cancer

An effectiveness analysis of healthcare systems using a systems theoretic approach

<p>Abstract</p> <p>Background</p> <p>The use of accreditation and quality measurement and reporting to improve healthcare quality and patient safety has been widespread across many countries. A review of the literature reveals no association between the accreditation system and the quality measurement and reporting systems, even when hospital compliance with these systems is satisfactory. Improvement of health care outcomes needs to be based on an appreciation of the whole system that contributes to those outcomes. The research literature currently lacks an appropriate analysis and is fragmented among activities. This paper aims to propose an integrated research model of these two systems and to demonstrate the usefulness of the resulting model for strategic research planning.</p> <p>Methods/design</p> <p>To achieve these aims, a systematic integration of the healthcare accreditation and quality measurement/reporting systems is structured hierarchically. A holistic systems relationship model of the administration segment is developed to act as an investigation framework. A literature-based empirical study is used to validate the proposed relationships derived from the model. Australian experiences are used as evidence for the system effectiveness analysis and design base for an adaptive-control study proposal to show the usefulness of the system model for guiding strategic research.</p> <p>Results</p> <p>Three basic relationships were revealed and validated from the research literature. The systemic weaknesses of the accreditation system and quality measurement/reporting system from a system flow perspective were examined. The approach provides a system thinking structure to assist the design of quality improvement strategies. The proposed model discovers a fourth implicit relationship, a feedback between quality performance reporting components and choice of accreditation components that is likely to play an important role in health care outcomes. An example involving accreditation surveyors is developed that provides a systematic search for improving the impact of accreditation on quality of care and hence on the accreditation/performance correlation.</p> <p>Conclusion</p> <p>There is clear value in developing a theoretical systems approach to achieving quality in health care. The introduction of the systematic surveyor-based search for improvements creates an adaptive-control system to optimize health care quality. It is hoped that these outcomes will stimulate further research in the development of strategic planning using systems theoretic approach for the improvement of quality in health care.</p

The effects of aging of scientists on their publication and citation patterns

The average age at which U.S. researchers get their first grant from NIH has increased from 34.3 in 1970, to 41.7 in 2004. These data raise the crucial question of the effects of aging on the scientific creativity and productivity of researchers. Those who worry about the aging of scientists usually believe that the younger they are the more creative and productive they will be. Using a large population of 13,680 university professors in Quebec, we show that, while scientific productivity rises sharply between 28 and 40, it increases at a slower pace between 41 and 50 and stabilizes afterward until retirement for the most active researchers. The average scientific impact per paper decreases linearly until 50-55 years old, but the average number of papers in highly cited journals and among highly cited papers rises continuously until retirement. Our results clearly show for the first time the natural history of the scientific productivity of scientists over their entire career and bring to light the fact that researchers over 55 still contribute significantly to the scientific community by producing high impact papers.Comment: 12 pages, 4 figure

Towards a new generation of Research Impact Assessment approaches

In the literature, most of the authors agree that addressing “grand challenges” implies systems transformation and requires social, economic and technological changes. It involves new policy rationales and design and consequently new approaches of research impact assessment (RIA). The challenge is to develop methods able to improve our understanding of the impact generating mechanisms, to assess a broader set of impacts, and to incorporate a mix of complementary approaches (combining qualitative and quantitative evaluation, achieving a multi-objective evaluation, and evaluating impacts at various level of aggregation). The six papers in this Special Issue present, discuss and even assess a new generation of RIA approaches. None of the papers covers all the RIA challenges highlighted above. At this stage, it would be illusive to develop a common evaluation approach, with standardized methods and metrics. We contend that the availability of a diversity of tools is a precious asset if impact assessment allows a conscientious attention to the transformative effects of research