A Probabilistic Framework for Security Scenarios with Dependent Actions

This work addresses the growing need of performing meaningful probabilistic analysis of security. We propose a framework that integrates the graphical security modeling technique of attack–defense trees with probabilistic information expressed in terms of Bayesian networks. This allows us to perform probabilistic evaluation of attack–defense scenarios involving dependent actions. To improve the efficiency of our computations, we make use of inference algorithms from Bayesian networks and encoding techniques from constraint reasoning. We discuss the algebraic theory underlying our framework and point out several generalizations which are possible thanks to the use of semiring theory

An Algebraic Theory for Data Linkage

There are countless sources of data available to governments, companies, and citizens, which can be combined for good or evil. We analyse the concepts of combining data from common sources and linking data from different sources. We model the data and its information content to be found in a single source by an ordered partial monoid, and the transfer of information between sources by different types of morphisms. To capture the linkage between a family of sources, we use a form of Grothendieck construction to create an ordered partial monoid that brings together the global data of the family in a single structure. We apply our approach to database theory and axiomatic structures in approximate reasoning. Thus, ordered partial monoids provide a foundation for the algebraic study for information gathering in its most primitive form

BMJ Open

INTRODUCTION: The prevalence of postnatal depression (PND) is significant: reaching up to 20% in the general population. In mechanistic terms, the risk of PND lies in an interaction between a maternal psychophysiological vulnerability and a chronic environmental context of stress. On the one hand, repetition of stressor during pregnancy mimics a chronic stress model that is relevant to the study of the allostatic load and the adaptive mechanisms. On the other hand, vulnerability factors reflect a psychological profile mirroring mindfulness functioning (psychological quality that involves bringing one's complete and non-judgemental attention to the present experience on a moment-to-moment basis). This psychological resource is linked to protective and resilient psychic functioning. Thus, PND appears to be a relevant model for studying the mechanisms of chronic stress and vulnerability to psychopathologies.In this article, we present the protocol of an ongoing study (started in May 2017). METHODS AND ANALYSIS: The study is being carried out in five maternities and will involve 260 women. We aim to determine the predictive psychobiological factors for PND emergence and to provide a better insight into the mechanisms involved in chronic stress during pregnancy. We use a multidisciplinary approach that encompasses psychological resources and biophysiological and genetic profiles in order to detect relevant vulnerability biomarkers for chronic stress and the development of PND. To do so, each woman will be involved in the study from her first trimester of pregnancy until 12 months postdelivery. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Ile de France III Ethics Committee, France (2016-A00887-44). We aim to disseminate the findings through international conferences and international peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03088319; Pre-results

In Situ Dividing and Phagocytosing Retinal Microglia Express Nestin, Vimentin, and NG2 In Vivo

BACKGROUND: Following injury, microglia become activated with subsets expressing nestin as well as other neural markers. Moreover, cerebral microglia can give rise to neurons in vitro. In a previous study, we analysed the proliferation potential and nestin re-expression of retinal macroglial cells such as astrocytes and Müller cells after optic nerve (ON) lesion. However, we were unable to identify the majority of proliferative nestin(+) cells. Thus, the present study evaluates expression of nestin and other neural markers in quiescent and proliferating microglia in naïve retina and following ON transection in adult rats in vivo. METHODOLOGY/PRINCIPAL FINDINGS: For analysis of cell proliferation and cells fates, rats received BrdU injections. Microglia in retinal sections or isolated cells were characterized using immunofluorescence labeling with markers for microglia (e.g., Iba1, CD11b), cell proliferation, and neural cells (e.g., nestin, vimentin, NG2, GFAP, Doublecortin etc.). Cellular analyses were performed using confocal laser scanning microscopy. In the naïve adult rat retina, about 60% of resting ramified microglia expressed nestin. After ON transection, numbers of nestin(+) microglia peaked to a maximum at 7 days, primarily due to in situ cell proliferation of exclusively nestin(+) microglia. After 8 weeks, microglia numbers re-attained control levels, but 20% were still BrdU(+) and nestin(+), although no further local cell proliferation occurred. In addition, nestin(+) microglia co-expressed vimentin and NG2, but not GFAP or neuronal markers. Fourteen days after injury and following retrograde labeling of retinal ganglion cells (RGCs) with Fluorogold (FG), nestin(+)NG2(+) microglia were positive for the dye indicating an active involvement of a proliferating cell population in phagocytosing apoptotic retinal neurons. CONCLUSIONS/SIGNIFICANCE: The current study provides evidence that in adult rat retina, a specific resident population of microglia expresses proteins of immature neural cells that are involved in injury-induced cell proliferation and phagocytosis while transdifferentiation was not observed

[Preserving fertility and future death].

International audienc

Observer‐independent assessment of psoriasis affected area using machine learning

Background Assessment of psoriasis severity is strongly observer‐dependent and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate‐to‐severe psoriasis motivates the development of higher quality assessment tools. Objective To establish an accurate and objective psoriasis assessment method based on segmenting images by machine learning technology. Methods In this retrospective, non‐interventional, single‐centered, interdisciplinary study of diagnostic accuracy 259 standardized photographs of Caucasian patients were assessed and typical psoriatic lesions were labelled. 203 of those were used to train and validate an assessment algorithm which was then tested on the remaining 56 photographs. The results of the algorithm assessment were compared with manually marked area, as well as with the affected area determined by trained dermatologists. Results Algorithm assessment achieved accuracy of more than 90% in 77% of the images and differed on average 5.9% from manually marked areas. The difference between algorithm predicted and photo based estimated areas by physicians were 8.1% on average. Conclusion The study shows the potential of the evaluated technology. In contrast to the Psoriasis Area and Severity Index (PASI) it allows for objective evaluation and should therefore be developed further as an alternative method to human assessment