IMPatienT: An Integrated Web Application to Digitize, Process and Explore Multimodal PATIENt daTa.

Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is problematic as the ecosystem of analysis tools is fragmented according to the type of data (images, text, genetics), the task (processing, exploration) and domain of interest (clinical phenotype, histology).

Human-environment feedback and the consistency of proenvironmental behavior.

Addressing global environmental crises such as anthropogenic climate change requires the consistent adoption of proenvironmental behavior by a large part of a population. Here, we develop a mathematical model of a simple behavior-environment feedback loop to ask how the individual assessment of the environmental state combines with social interactions to influence the consistent adoption of proenvironmental behavior, and how this feeds back to the perceived environmental state. In this stochastic individual-based model, individuals can switch between two behaviors, 'active' (or actively proenvironmental) and 'baseline', differing in their perceived cost (higher for the active behavior) and environmental impact (lower for the active behavior).

Spliceator: multi-species splice site prediction using convolutional neural networks.

Background: Ab initio prediction of splice sites is an essential step in eukaryotic genome annotation. Recent predictors have exploited Deep Learning algorithms and reliable gene structures from model organisms. However, Deep Learning methods for non-model organisms are lacking.

Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes.

Background: Recent advances in sequencing technologies have led to an explosion in the number of genomes available, but accurate genome annotation remains a major challenge. The prediction of protein-coding genes in eukaryotic genomes is especially problematic, due to their complex exon-intron structures. Even the best eukaryotic gene prediction algorithms can make serious errors that will significantly affect subsequent analyses.

Addressing temporal considerations in life cycle assessment.

In life cycle assessment (LCA), temporal considerations are usually lost during the life cycle inventory calculation, resulting in an aggregated "snapshot" of potential impacts. Disregarding such temporal considerations has previously been underlined as an important source of uncertainty, but a growing number of approaches have been developed to tackle this issue. Nevertheless, their adoption by LCA practitioners is still uncommon, which raises concerns about the representativeness of current LCA results.

A benchmark study of ab initio gene prediction methods in diverse eukaryotic organisms.

Background: The draft genome assemblies produced by new sequencing technologies present important challenges for automatic gene prediction pipelines, leading to less accurate gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction methods in the face of incomplete genome assemblies, low genome coverage and quality, complex gene structures, or a lack of suitable sequences for evidence-based annotations.

Results: We describe the construction of a new benchmark, called G3PO (benchmark for Gene and Protein Prediction PrOgrams), designed to represent many of the typical challenges faced by current genome annotation projects.

Modelling dynamic soil organic carbon flows of annual and perennial energy crops to inform energy-transport policy scenarios in France.

Low carbon strategies recently focus on soil organic carbon (SOC) sequestration potentials from agriculture and forestry, while Life Cycle Assessment (LCA) increasingly becomes the framework of choice to estimate the environmental impacts of these activities. Classic LCA is limited to static carbon neutral approaches, disregarding dynamic SOC flows and their time-dependent GHG contributions. To overcome such limitation, the purpose of this study is to model SOC flows associated with agricultural land use (LU) and the provision of agricultural substrates to transport biofuels, thus generating dynamic inventories and comparatively assessing energy policy scenarios and their climate consequences in the context of dynamic LCA.

Guided active particles.

To account for the possibility of an externally driven taxis in active systems, we develop a model of a guided active drift which relies on the presence of an external guiding field and a vectorial coupling between the mechanical degrees of freedom and a chemical reaction. To characterize the ability of guided active particles to carry cargo, we generalize the notion of Stokes efficiency extending it to the case of stall conditions. To show the generality of the proposed mechanism, we discuss guided electric circuits capable of turning fluctuations into a directed current without a source of voltage.

Data and non-linear models for the estimation of biomass growth and carbon fixation in managed forests.

The data and analyses presented support the research article entitled "Coupling partial-equilibrium and dynamic biogenic carbon models to assess future transport scenarios in France" (Albers et al., 2019). Carbon sequestration and storage in forestry products (e.

Cerberus, an Access Control Scheme for Enforcing Least Privilege in Patient Cohort Study Platforms : A Comprehensive Access Control Scheme Applied to the GENIDA Project - Study of Genetic Forms of Intellectual Disabilities and Autism Spectrum Disorders.

Cohort Study Platforms (CSP) are emerging as a key tool for collecting patient information, providing new research data, and supporting family and patient associations. However they pose new ethics and regulatory challenges since they cross the gap between patients and medical practitioners. One of the critical issues for CSP is to enforce a strict control on access privileges whilst allowing the users to take advantage of the breadth of the available data.

The effect of competition and horizontal trait inheritance on invasion, fixation, and polymorphism.

Horizontal transfer (HT) of heritable information or 'traits' (carried by genetic elements, plasmids, endosymbionts, or culture) is widespread among living organisms. Yet current ecological and evolutionary theory addressing HT is scant. We present a modeling framework for the dynamics of two populations that compete for resources and horizontally exchange (transfer) an otherwise vertically inherited trait.

A rigorous model study of the adaptive dynamics of Mendelian diploids.

Adaptive dynamics (AD) so far has been put on a rigorous footing only for clonal inheritance. We extend this to sexually reproducing diploids, although admittedly still under the restriction of an unstructured population with Lotka-Volterra-like dynamics and single locus genetics (as in Kimura's in Proc Natl Acad Sci USA 54: 731-736, 1965 infinite allele model). We prove under the usual smoothness assumptions, starting from a stochastic birth and death process model, that, when advantageous mutations are rare and mutational steps are not too large, the population behaves on the mutational time scale (the 'long' time scale of the literature on the genetical foundations of ESS theory) as a jump process moving between homozygous states (the trait substitution sequence of the adaptive dynamics literature).

Boosting theoretical zeolitic framework generation for the determination of new materials structures using GPU programming.

Evolutionary algorithms have proved to be efficient for solving complicated optimization problems. On the other hand, the many-core architecture in graphical cards "General Purpose Graphic Processing Unit" (GPGPU) offers one of the most attractive cost/performance ratio. Using such hardware, the manuscript shows how an efficiently implemented genetic algorithm with a simple fitness function allows boosting the determination of zeolite structures.

Life-cycle assessment of microalgae culture coupled to biogas production.

Due to resource depletion and climate change, lipid-based algal biofuel has been pointed out as an interesting alternative because of the high productivity of algae per hectare and per year and its ability to recycle CO(2) from flue gas. Another option for taking advantage of the energy content of the microalgae is to directly carry out anaerobic digestion of raw algae in order to produce methane and recycle nutrients (N, P and K). In this study, a life-cycle assessment (LCA) of biogas production from the microalgae Chlorella vulgaris is performed and the results are compared to algal biodiesel and to first generation biodiesels.

Nonequilibrium stationary state of a truncated stochastic nonlinear Schrödinger equation: formulation and mean-field approximation.

We investigate the stationary state of a model system evolving according to a modified focusing truncated nonlinear Schrödinger equation used to describe the envelope of Langmuir waves in a plasma. We restrict the system to have a finite number of normal modes each of which is in contact with a Langevin heat bath at temperature T . Arbitrarily large realizations of the field are prevented by restricting each mode to a maximum amplitude.