L'évolution des frontières de l'état français et de l'identité culturelle basque : perspectives anthropologiques

1. Introduction Le Pays Basque se situe à la périphérie géographique et culturelle de la France, et nous offre un scénario où divergences entre identités nationales et locales accentuent le caractère hétérogène de l'état français. Cette problématique peut être éclaircie en cadrant l'identité culturelle basque en tant que symptôme de tensions historiques entre le centre et sa périphérie qui se manifestent en zones frontalières. Nous suggérons donc trois objectifs dans ce travail : premièrement..

Contested Commons: The Historical Ecology of Continuity and Change in Basque Agro-pastoralism in the Baigorri Valley (France)

This dissertation examines long-term changes in the management and use of Commons in the Baigorri valley in the Basque region of southwestern France. This research identifies the various political challenges and socio-economic pressures confronting farmers there since the 18th-century. Diachronic, multi-scalar influences include persistent contestation over common-pool resources, profound shifts in the political economy, and fissures in the social fabric of Basque farming communities. By investigating the role of households and communal institutions in addressing historical contestations in the Baigorri valley, this dissertation reveals the influence of external polities like the French state in local governance and use of the Commons. This research also situates more recent processes of modernization and the effect of mechanization on agro-pastoralism within their historical contexts. These socio-economic transformations now allow farmers to depend less on the assistance of neighbors, thus reshaping individual and collective farming practices in the Commons of the Baigorri valley and weakening local networks for cooperation. Finally, this research problematizes the influence of the Common Agricultural Policy on Basque agro-pastoralism, analyzes how these changes are contested through new transborder initiatives, and discusses the future sustainability of management practices in the Commons of the Baigorri valley

Dundee ADHD continuing care proforma (revised)

These are two proforma (one for males the other for females) that facilitate the recording of clinical information about the ongoing clinical status of children and adolescents receiving treatment for ADHD. Whilst the Dundee ADHD care pathway has recorded similar clinical information in a standardised way for the last 10 years the previous clinical records required a new document for each clinic visit. This made it more difficult to assess the development of clinical response over time and increased the time required by clinicians to make evidence based treatment decisions. These revised proforma allow the clinician to view the information from up to 12 clinic visits at the same time and therefore simplify the clinical task and improving clinical care. The proforma were designed as a part of a collaboration between graphic and product designers and clinicians that was made possible through the wider ADHD Behavioural Clinical Data (ABCD) data visualisation collaboration funded through and award from the University of Dundee

The FaceBase Consortium: A comprehensive program to facilitate craniofacial research

The FaceBase Consortium consists of ten interlinked research and technology projects whose goal is to generate craniofacial research data and technology for use by the research community through a central data management and integrated bioinformatics hub. Funded by the National Institute of Dental and Craniofacial Research (NIDCR) and currently focused on studying the development of the middle region of the face, the Consortium will produce comprehensive datasets of global gene expression patterns, regulatory elements and sequencing; will generate anatomical and molecular atlases; will provide human normative facial data and other phenotypes; conduct follow up studies of a completed genome-wide association study; generate independent data on the genetics of craniofacial development, build repositories of animal models and of human samples and data for community access and analysis; and will develop software tools and animal models for analyzing and functionally testing and integrating these data. The FaceBase website (http://www.facebase.org) will serve as a web home for these efforts, providing interactive tools for exploring these datasets, together with discussion forums and other services to support and foster collaboration within the craniofacial research community

Mammals adjust diel activity across gradients of urbanization

Time is a fundamental component of ecological processes. How animal behavior changes over time has been explored through well-known ecological theories like niche partitioning and predator–prey dynamics. Yet, changes in animal behavior within the shorter 24-hr light–dark cycle have largely gone unstudied. Understanding if an animal can adjust their temporal activity to mitigate or adapt to environmental change has become a recent topic of discussion and is important for effective wildlife management and conservation. While spatial habitat is a fundamental consideration in wildlife management and conservation, temporal habitat is often ignored. We formulated a temporal resource selection model to quantify the diel behavior of 8 mammal species across 10 US cities. We found high variability in diel activity patterns within and among species and species-specific correlations between diel activity and human population density, impervious land cover, available greenspace, vegetation cover, and mean daily temperature. We also found that some species may modulate temporal behaviors to manage both natural and anthropogenic risks. Our results highlight the complexity with which temporal activity patterns interact with local environmental characteristics, and suggest that urban mammals may use time along the 24-hr cycle to reduce risk, adapt, and therefore persist, and in some cases thrive, in human-dominated ecosystems

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1-the summer 2015 and winter 2016 growing seasons-of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project's goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs

Plant Science Decadal Vision 2020–2030: Reimagining the Potential of Plants for a Healthy and Sustainable Future

Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and green infrastructure. Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a parts store that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people\u27s natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

The effect of artificial selection on phenotypic plasticity in maize

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0–5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements

Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury

Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q \u3c 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age-dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans