Integrating forensic information in a crime intelligence database

Since 2008, Intelligence units of six states of the western part of Switzerland have been sharing a common database for the analysis of high volume crimes. On a daily basis, events reported to the police are analysed, filtered and classified to detect crime repetitions and interpret the crime environment. Several forensic outcomes are integrated in the system such as matches of traces with persons, and links between scenes detected by the comparison of forensic case data. Systematic procedures have been settled to integrate links assumed mainly through DNA profiles, shoemarks patterns and images. A statistical outlook on a retrospective dataset of series from 2009 to 2011 of the database informs for instance on the number of repetition detected or confirmed and increased by forensic case data. Time needed to obtain forensic intelligence in regard with the type of marks treated, is seen as a critical issue. Furthermore, the underlying integration process of forensic intelligence into the crime intelligence database raised several difficulties in regards of the acquisition of data and the models used in the forensic databases. Solutions found and adopted operational procedures are described and discussed. This process form the basis to many other researches aimed at developing forensic intelligence models.

Quantitative analysis of postnatal neurogenesis and neuron number in the macaque monkey dentate gyrus

The dentate gyrus is one of only two regions of the mammalian brain where substantial neurogenesis occurs postnatally. However, detailed quantitative information about the postnatal structural maturation of the primate dentate gyrus is meager. We performed design-based, stereological studies of neuron number and size, and volume of the dentate gyrus layers in rhesus macaque monkeys (Macaca mulatta) of different postnatal ages. We found that about 40% of the total number of granule cells observed in mature 5-10-year-old macaque monkeys are added to the granule cell layer postnatally; 25% of these neurons are added within the first three postnatal months. Accordingly, cell proliferation and neurogenesis within the dentate gyrus peak within the first 3 months after birth and remain at an intermediate level between 3 months and at least 1 year of age. Although granule cell bodies undergo their largest increase in size during the first year of life, cell size and the volume of the three layers of the dentate gyrus (i.e. the molecular, granule cell and polymorphic layers) continue to increase beyond 1 year of age. Moreover, the different layers of the dentate gyrus exhibit distinct volumetric changes during postnatal development. Finally, we observe significant levels of cell proliferation, neurogenesis and cell death in the context of an overall stable number of granule cells in mature 5-10-year-old monkeys. These data identify an extended developmental period during which neurogenesis might be modulated to significantly impact the structure and function of the dentate gyrus in adulthood.

The encouragement of the open access movement: an essential realm for health information professionals in the 21st century

According to the Bethesda Statement on Open Access Policy for libraries and the recommendations of the BOAI10, libraries and librarians have an important role to fulfil in the encouragement of open access. Taking into account the Competencies for Information Professionals of the 21st Century, elaborated by the Special Libraries Association, and the Librarians’ Competencies Profile for Scholarly Publishing and Open Access, we shall identify the competencies and new areas of knowledge and expertise that have been involved in the process of the development and upkeep of our institutional repository (Repositorio SSPA).

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

Examining the information content of time-lapse crosshole GPR data collected under different infiltration conditions to estimate unsaturated soil hydraulic properties

Time-lapse geophysical data acquired during transient hydrological experiments are being increasingly employed to estimate subsurface hydraulic properties at the field scale. In particular, crosshole ground-penetrating radar (GPR) data, collected while water infiltrates into the subsurface either by natural or artificial means, have been demonstrated in a number of studies to contain valuable information concerning the hydraulic properties of the unsaturated zone. Previous work in this domain has considered a variety of infiltration conditions and different amounts of time-lapse GPR data in the estimation procedure. However, the particular benefits and drawbacks of these different strategies as well as the impact of a variety of key and common assumptions remain unclear. Using a Bayesian Markov-chain-Monte-Carlo stochastic inversion methodology, we examine in this paper the information content of time-lapse zero-offset-profile (ZOP) GPR traveltime data, collected under three different infiltration conditions, for the estimation of van Genuchten-Mualem (VGM) parameters in a layered subsurface medium. Specifically, we systematically analyze synthetic and field GPR data acquired under natural loading and two rates of forced infiltration, and we consider the value of incorporating different amounts of time-lapse measurements into the estimation procedure. Our results confirm that, for all infiltration scenarios considered, the ZOP GPR traveltime data contain important information about subsurface hydraulic properties as a function of depth, with forced infiltration offering the greatest potential for VGM parameter refinement because of the higher stressing of the hydrological system. Considering greater amounts of time-lapse data in the inversion procedure is also found to help refine VGM parameter estimates. Quite importantly, however, inconsistencies observed in the field results point to the strong possibility that posterior uncertainties are being influenced by model structural errors, which in turn underlines the fundamental importance of a systematic analysis of such errors in future related studies.

Le système d'information dirigeant des Hospices: conception générale

[Table des matières] 1. Introduction. 2. Structure (introduction, hiérarchie). 3. Processus (généralités, flux de clientèle, flux d'activité, flux de ressources, aspects temporels, aspects comptables). 4. Descripteurs (qualification, quantification). 5. Indicateurs (définitions, productivité, pertinence, adéquation, efficacité, effectivité, efficience, standards). 6. Bibliographie.

Respiratory quotient evolution during normal pregnancy: what nutritional or clinical information can we get out of it?

Food intake increases to a varying extent during pregnancy to provide extra energy for the growing fetus. Measuring the respiratory quotient (RQ) during the course of pregnancy (by quantifying O2 consumption and CO2 production with indirect calorimetry) could be potentially useful since it gives an insight into the evolution of the proportion of carbohydrate vs. fat oxidized during pregnancy and thus allows recommendations on macronutrients for achieving a balanced (or slightly positive) substrate intake. A systematic search of the literature for papers reporting RQ changes during normal pregnancy identified 10 papers reporting original research. The existing evidence supports an increased RQ of varying magnitude in the third trimester of pregnancy, while the discrepant results reported for the first and second trimesters (i.e. no increase in RQ), explained by limited statistical power (small sample size) or fragmentary data, preclude safe conclusions about the evolution of RQ during early pregnancy. From a clinical point of view, measuring RQ during pregnancy requires not only sophisticated and costly indirect calorimeters but appears of limited value outside pure research projects, because of several confounding variables: (1) spontaneous changes in food intake and food composition during the course of pregnancy (which influence RQ); (2) inter-individual differences in weight gain and composition of tissue growth; (3) technical factors, notwithstanding the relatively small contribution of fetal metabolism per se (RQ close to 1.0) to overall metabolism of the pregnant mother.

Engaging students in an e-learning experience : how to manage information resources through wikis and web blogs

The purpose of this paper is to describe the collaboration between librarians and scholars, from a virtual university, in order to facilitate collaborative learning on how to manage information resources. The personal information behaviour of e-learning students when managing information resources for academic, professional and daily life purposes was studied from 24 semi-structured face-to-face interviews. The results of the content analysis of the interview' transcriptions, highlighted that in the workplace and daily life contexts, competent information behaviour is always linked to a proactive attitude, that is to say, that participants seek for information without some extrinsic reward or avoiding punishment. In the academic context, it was observed a low level of information literacy and it seems to be related with a prevalent uninvolved attitude.

Information overload, choice deferral, and moderating role of need for cognition: Empirical evidence

ABSTRACT Choice deferral due to information overload is an undesirable result of competitive environments. The neoclassical maximization models predict that choice avoidance will not increase as more information is offered to consumers. The theories developed in the consumer behavior field predict that some properties of the environment may lead to behavioral effects and an increase in choice avoidance due to information overload. Based on stimuli generated experimentally and tested among 1,000 consumers, this empirical research provides evidence for the presence of behavioral effects due to information overload and reveals the different effects of increasing the number of options or the number of attributes. This study also finds that the need for cognition moderates these behavioral effects, and it proposes psychological processes that may trigger the effects observed.