Chiennes de vies : la relation anthropozoologique, un angle mort de l'intervention en itinérance?

Fidèle compagnon de galère, ami et confident, l’animal non-humain peut devenir un allié irremplaçable pour les personnes en situation d’itinérance. Pourtant, cette relation hybride semble échapper aux enjeux du travail social. Malgré l’émergence des pratiques de soin par le contact animalier, il n’est pas rare que l’animal itinérant en soit exclu, et que les enjeux de sa présence soient marginalisés, considérés hors-mandat par les équipes d’intervention. Cette situation paradoxale entraîne du même coup l’exclusion des personnes qui, refusant la séparation, ne peuvent bénéficier des ressources disponibles: les partenaires humains-animaux itinérants deviennent alors déviants parmi les déviants. Est-il possible de redonner une place légitime à l’animal non-humain dans ce contexte? Peut-il à la fois agir sur, et bénéficier de, l’intervention? Finalement, de quelle(s) manière(s) la relation anthropozoologique (RAZ) peut-elle être prise en compte dans les enjeux de l’intervention auprès des populations en situation d’itinérance? Dans le cadre de cette étude sociologique de la déviance et des RAZ, nous nous intéressons au cas du chien à l’époque contemporaine et, plus particulièrement, à sa présence et à sa participation dans les milieux communautaires accueillant les personnes itinérantes de la ville de Montréal. Après avoir dégagé les enjeux et les obstacles de la prise en compte de cette relation par le travail social, nous présenterons et analyserons deux projets-pilotes illustrant les conditions et les modalités possibles de l’hybridation des pratiques d’intervention.As loyal companions, friends and confidants, nonhuman animals can become irreplaceable allies for homeless people. Yet this hybrid relationship does not seem to be addressed in social work issues. Despite the emergence of animal assisted care, it is not uncommon for the homeless animals to be excluded from those practices, and their presence to be marginalized, considered by social workers to fall outside their mandate. This paradoxical situation leads at the same time to the exclusion of people who, refusing separation from their animal mate, can not benefit from available resources: the homeless human-animal partners then become deviant among the deviants. Is it possible to give a legitimate place back to nonhuman animals in this context? Can they be both beneficial to social work, and at the same time benefit from it? Finally, in what way(s) can the human-animal relation (HAR) be considered in social work practices with homeless people? As part of this sociological study of deviance and HAR, we focus on the case of dogs in contemporary times, and more specifically their presence and participation in the community services welcoming homeless people in Montreal. After having identified the issues and the obstacles of taking HAR into account, we present and analyze two pilot initiatives illustrating the conditions and possible modalities of the hybridization of social work practices

How does viscosity contrast influence phase mixing and strain localization?

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 125 (2020): e2020JB020323, doi: 10.1029/2020JB020323.Ultramylonites—intensely deformed rocks with fine grain sizes and well‐mixed mineral phases—are thought to be a key component of Earth‐like plate tectonics, because coupled phase mixing and grain boundary pinning enable rocks to deform by grain‐size‐sensitive, self‐softening creep mechanisms over long geologic timescales. In isoviscous two‐phase composites, “geometric” phase mixing occurs via the sequential formation, attenuation (stretching), and disaggregation of compositional layering. However, the effects of viscosity contrast on the mechanisms and timescales for geometric mixing are poorly understood. Here, we describe a series of high‐strain torsion experiments on nonisoviscous calcite‐fluorite composites (viscosity contrast, ηca/ηfl ≈ 200) at 500°C, 0.75 GPa confining pressure, and 10−6–10−4 s−1 shear strain rate. At low to intermediate shear strains (γ ≤ 10), polycrystalline domains of the individual phases become sheared and form compositional layering. As layering develops, strain localizes into the weaker phase, fluorite. Strain partitioning impedes mixing by reducing the rate at which the stronger (calcite) layers deform, attenuate, and disaggregate. Even at very large shear strains (γ ≥ 50), grain‐scale mixing is limited, and thick compositional layers are preserved. Our experiments (1) demonstrate that viscosity contrasts impede mechanical phase mixing and (2) highlight the relative inefficiency of mechanical mixing. Nevertheless, by employing laboratory flow laws, we show that “ideal” conditions for mechanical phase mixing may be found in the wet middle to lower continental crust and in the dry mantle lithosphere, where quartz‐feldspar and olivine‐pyroxene viscosity contrasts are minimized, respectively.This work was funded through a National Science Foundation grant (EAR‐1352306) awarded to P. S., with additional support for A. J. C. provided by the McDonnell Center for the Space Sciences (Washington University in St. Louis), the J. Lamar Worzel Assistant Scientist Fund (WHOI), and the Penzance Endowed Fund in Support of Assistant Scientists (WHOI). Partial support for electron microscopy was provided by the Institute of Materials Science and Engineering (Washington University in St. Louis).2021-02-0

Effect of nanostructuration on compressibility of cubic BN

Compressibility of high-purity nanostructured cBN has been studied under quasi-hydrostatic conditions at 300 K up to 35 GPa using diamond anvil cell and angle-dispersive synchrotron X-ray powder diffraction. A data fit to the Vinet equation of state yields the values of the bulk modulus B0 of 375(4) GPa with its first pressure derivative B0' of 2.3(3). The nanometer grain size (\sim20 nm) results in decrease of the bulk modulus by ~9%

Low-dimensional controllability of brain networks

Network controllability is a powerful tool to study causal relationships in complex systems and identify the driver nodes for steering the network dynamics into desired states. However, due to ill-posed conditions, results become unreliable when the number of drivers becomes too small compared to the network size. This is a very common situation, particularly in real-world applications, where the possibility to access multiple nodes at the same time is limited by technological constraints, such as in the human brain. Although targeting smaller network parts might improve accuracy, challenges may remain for extremely unbalanced situations, when for example there is one single driver. To address this problem, we developed a mathematical framework that combines concepts from spectral graph theory and modern network science. Instead of controlling the original network dynamics, we aimed to control its low-dimensional embedding into the topological space derived from the network Laplacian. By performing extensive simulations on synthetic networks, we showed that a relatively low number of projected components is enough to improve the overall control accuracy, notably when dealing with very few drivers. Based on these findings, we introduced alternative low-dimensional controllability metrics and used them to identify the main driver areas of the human connectome obtained from N=6134 healthy individuals in the UK-biobank cohort. Results revealed previously unappreciated influential regions compared to standard approaches, enabled to draw control maps between distinct specialized large-scale brain systems, and yielded an anatomically-based understanding of hemispheric functional lateralization. Taken together, our results offered a theoretically-grounded solution to deal with network controllability in real-life applications and provided insights into the causal interactions of the human brain

A comparison between early presentation of dementia with Lewy Bodies, Alzheimer's disease and Parkinson's disease: evidence from routine primary care and UK Biobank data

OBJECTIVE: To simultaneously contrast prediagnostic clinical characteristics of individuals with a final diagnosis of dementia with Lewy Bodies, Parkinson's disease, Alzheimer's disease compared to controls without neurodegenerative disorders. METHODS: Using the longitudinal THIN database in the UK, we tested the association of each neurodegenerative disorder with a selected list of symptoms and broad families of treatments, and compared the associations between disorders to detect disease-specific effects. We replicated the main findings in the UK Biobank. RESULTS: We used data of 28,222 patients with PD, 20,214 with AD, 4,682 with DLB and 20,214 controls. All neurodegenerative disorders were significantly associated with the presence of multiple clinical characteristics before their diagnosis including sleep disorders, falls, psychiatric symptoms and autonomic dysfunctions. When comparing DLB patients with patients with PD and AD patients, falls, psychiatric symptoms and autonomic dysfunction were all more strongly associated with DLB in the five years preceding the first neurodegenerative diagnosis. The use of statins was lower in patients who developed PD and higher in patients who developed DLB compared to AD. In PD patients, the use of statins was associated with the development of dementia in the five years following PD diagnosis. INTERPRETATION: Prediagnostic presentations of falls, psychiatric symptoms and autonomic dysfunctions were more strongly associated with DLB than PD and AD. This study also suggests that whilst several associations with medications are similar in neurodegenerative disorders, statin usage is negatively associated with Parkinson's Disease but positively with DLB and AD as well as development of dementia in PD

Linear Mixed Models Minimise False Positive Rate and Enhance Precision of Mass Univariate Vertex-Wise Analyse of Grey-Matter

International audienceWe evaluated the statistical power, family wise error rate (FWER) and precision of several competing methods that perform mass-univariate vertex-wise analyses of grey-matter (thickness and surface area). In particular, we compared several generalised linear models (GLMs, current state of the art) to linear mixed models (LMMs) that have proven superior in genomics. We used phenotypes simulated from real vertex-wise data and a large sample size (N=8,662) which may soon become the norm in neuroimaging. No method ensured a FWER<5% (at a vertex or cluster level) after applying Bonferroni correction for multiple testing. LMMs should be preferred to GLMs as they minimise the false positive rate and yield smaller clusters of associations. Associations on real phenotypes must be interpreted with caution, and replication may be warranted to conclude about an association

Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture

© 2020, The Author(s). Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD