Deciphering the impact of uncertainty on the accuracy of large wildfire spread simulations

Predicting wildfire spread is a challenging task fraught with uncertainties. ‘Perfect’ predictions are unfeasible since uncertainties will always be present. Improving fire spread predictions is important to reduce its negative environmental impacts. Here, we propose to understand, characterize, and quantify the impact of uncertainty in the accuracy of fire spread predictions for very large wildfires. We frame this work from the perspective of the major problems commonly faced by fire model users, namely the necessity of accounting for uncertainty in input data to produce reliable and useful fire spread predictions. Uncertainty in input variables was propagated throughout the modeling framework and its impact was evaluated by estimating the spatial discrepancy between simulated and satellite-observed fire progression data, for eight very large wildfires in Portugal. Results showed that uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy.We argue that uncertainties in these variables should be integrated in future fire spread simulation approaches, and provide the necessary data for any firemodel user to do soinfo:eu-repo/semantics/publishedVersio

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings. Methods: Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data. Results and discussion: The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of −0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, −0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

Une 'toxicité' sous-estimée :les impacts psychosociaux des traitements sur les proches aidants principaux

Dans le cadre d’une étude belge multicentrique, cet article rapporte l’évaluation qualitative et quantitative des besoins psychosociaux des proches aidants principaux des patients atteints d’un cancer, ainsi que les difficultés vécues par ces proches à faire face aux besoins psychosociaux des malades. De janvier à novembre 2004, l’ensemble des proches aidants principaux des patients atteints d’un cancer et hospitalisés au sein de sept unités de soins en oncologie, ainsi que le proche aidant principal d’un patient sur deux consultant au sein de ces mêmes unités ont étéinvités à prendre part à l’étude. Les proches aidants principaux ont rempli une adaptation du questionnaire Cancer Rehabilitation Evaluation System (CARES) permettant l’investigation de 24 types de difficultés ayant pu être rencontrées au cours du dernier mois, ainsi qu’une seconde adaptation du CARES permettant d’évaluer leur perception de 38 types de difficultés potentielles chez leur proche malade au cours du dernier mois. Les sujets ont également étéinvités à indiquer s’ils avaient eu des difficultés à faire face à chaque difficulté perçue chez leur proche malade. Les informations médicales relatives aux patients ont étérécoltées auprès de leurs oncologues. Parmi les 284 proches aidants principaux inclus, une grande majoritéa rencontré au cours du dernier mois une à plusieurs difficultés physiques, psychosociales, sexuelles de même que des difficultés de communication avec leur partenaire. La majorité des proches aidants principaux perçoit de nombreuses difficultés chez leur proche malade et 20 à 60 % d’entre eux rapportent éprouver au moins un peu de difficulté à faire face à ces difficultés. À côtéde leurs nombreuses difficultés personnelles, les proches aidants principaux des patients atteints d’un cancer perçoivent donc de nombreuses difficultés psychosociales chez leur proche malade. Les proches aidants principaux éprouvent également de nombreuses difficultés à gérer ces difficultés perçues. Le nombre et l’importante variété des difficultés rapportéesdans cette étude reflètent une « toxicité » sous-estimée :celle liée aux impacts et conséquences psychosociaux des traitements sur les proches aidants principaux.info:eu-repo/semantics/publishe