Building capacity for evidence-based public health: Reconciling the pulls of practice and the push of research

Timely implementation of principles of evidence-based public health (EBPH) is critical for bridging the gap between discovery of new knowledge and its application. Public health organizations need sufficient capacity (the availability of resources, structures, and workforce to plan, deliver, and evaluate the preventive dose of an evidence-based intervention) to move science to practice. We review principles of EBPH, the importance of capacity building to advance evidence-based approaches, promising approaches for capacity building, and future areas for research and practice. Although there is general agreement among practitioners and scientists on the importance of EBPH, there is less clarity on the definition of evidence, how to find it, and how, when, and where to use it. Capacity for EBPH is needed among both individuals and organizations. Capacity can be strengthened via training, use of tools, technical assistance, assessment and feedback, peer networking, and incentives. Modest investments in EBPH capacity building will foster more effective public health practice

Políticas de descentralização e desenvolvimento da educação em saúde

How the policy of action and professional standards have influenced the development and decentralization of health education is discussed. It is concluded that a review of policies both of developing as well as of developed countries could help to put some observations into a perspective that is closer to the Brazilian reality.Discute-se como a política de ação e os padrões profissionais têm influenciado o desenvolvimento e a descentralização da Educação em Saúde. Conclui-se que estudos sobre política de ação em países desenvolvidos e em desenvolvimento contribuem para observações a partir de uma perspectiva mais próxima à realidade brasileira

Dimensional Duality

We show that string theory on a compact negatively curved manifold, preserving a U(1)^{b_1} winding symmetry, grows at least b_1 new effective dimensions as the space shrinks. The winding currents yield a "D-dual" description of a Riemann surface of genus h in terms of its 2h dimensional Jacobian torus, perturbed by a closed string tachyon arising as a potential energy term in the worldsheet sigma model. D-branes on such negatively curved manifolds also reveal this structure, with a classical moduli space consisting of a b_1-torus. In particular, we present an AdS/CFT system which offers a non-perturbative formulation of such supercritical backgrounds. Finally, we discuss generalizations of this new string duality.Comment: 25 pages, harvmac. v2: fixed typo. v3: fixed typos and added ref

The swansong in context: long-timescale X-ray variability of NGC 4051

On 9-11 May 1998, the highly-variable, low luminosity Seyfert 1 galaxy NGC4051 was observed in an unusual low flux state by BeppoSAX (Guainazzi et al. 1998) RXTE and EUVE. We present fits of the 4-15 keV RXTE spectrum and BeppoSAX MECS spectrum obtained during this observation, which are consistent with the interpretation that the source had switched off, leaving only the spectrum of pure reflection from distant cold matter. We place this result in context by showing the X-ray lightcurve of NGC4051 obtained by our RXTE monitoring campaign over the past two and a half years, which shows that the low state lasted for ~150 days before the May observations (implying that the reflecting material is > 10^17 cm from the continuum source) and forms part of a lightcurve showing distinct variations in long-term average flux over timescales > months. We show that the long-timescale component to X-ray variability is intrinsic to the primary continuum and is probably distinct from the variability at shorter timescales, possibly associated with variations in the accretion flow of matter onto the central black hole. As the source approaches the low state, the variability process becomes non-linear. NGC4051 may represent a microcosm of all X-ray variability in radio quiet active galactic nuclei (AGNs), displaying in a few years a variety of flux states and variability properties which more luminous AGNs may pass through on timescales of decades to thousands of years.Comment: 5 pages, accepted for publication in MNRA

Development of a Prototype Model-Form Uncertainty Knowledge Base

Uncertainties are generally classified as either aleatory or epistemic. Aleatory uncertainties are those attributed to random variation, either naturally or through manufacturing processes. Epistemic uncertainties are generally attributed to a lack of knowledge. One type of epistemic uncertainty is called model-form uncertainty. The term model-form means that among the choices to be made during a design process within an analysis, there are different forms of the analysis process, which each give different results for the same configuration at the same flight conditions. Examples of model-form uncertainties include the grid density, grid type, and solver type used within a computational fluid dynamics code, or the choice of the number and type of model elements within a structures analysis. The objectives of this work are to identify and quantify a representative set of model-form uncertainties and to make this information available to designers through an interactive knowledge base (KB). The KB can then be used during probabilistic design sessions, so as to enable the possible reduction of uncertainties in the design process through resource investment. An extensive literature search has been conducted to identify and quantify typical model-form uncertainties present within aerospace design. An initial attempt has been made to assemble the results of this literature search into a searchable KB, usable in real time during probabilistic design sessions. A concept of operations and the basic structure of a model-form uncertainty KB are described. Key operations within the KB are illustrated. Current limitations in the KB, and possible workarounds are explained

The Challenges of Credible Thermal Protection System Reliability Quantification

The paper discusses several of the challenges associated with developing a credible reliability estimate for a human-rated crew capsule thermal protection system. The process of developing such a credible estimate is subject to the quantification, modeling and propagation of numerous uncertainties within a probabilistic analysis. The development of specific investment recommendations, to improve the reliability prediction, among various potential testing and programmatic options is then accomplished through Bayesian analysis

Development of a Bayesian Belief Network Runway Incursion and Excursion Model

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper

Analysis of Runway Incursion Data

A statistical analysis of runway incursion (RI) events was conducted to ascertain relevance to the top ten challenges of the National Aeronautics and Space Administration Aviation Safety Program (AvSP). The information contained in the RI database was found to contain data that may be relevant to several of the AvSP top ten challenges. When combined with other data from the FAA documenting air traffic volume from calendar year 2000 through 2011, the structure of a predictive model emerges that can be used to forecast the frequency of RI events at various airports for various classes of aircraft and under various environmental conditions