492 research outputs found
Ab Initio Derived Force Fields for Zeolitic Imidazolate Frameworks: MOF-FF for ZIFs
International audienceIn this paper, we parametrized in a consistent way a new force field for a range of different zeolitic imidazolate framework systems (ZIF-8, ZIF-8(H), ZIF-8(Br), and ZIF-8(Cl)), extending the MOF-FF parametrization methodology in two aspects. First, we implemented the possibility to use periodic reference data in order to prevent the difficulty of generating representative finite clusters. Second, a new optimizer based on the covariance matrix adaptation evolutionary strategy (CMA-ES) was employed during the parametrization process. We confirmed that CMA-ES, as a state-of-the-art black box optimizer for problems on continuous variables, is more efficient and versatile for force field optimization than the previous genetic algorithm. The obtained force field was then validated with respect to some static and dynamic properties. Much effort was spent to ensure that the FF is able to describe the crucial linker swing effect in a large number of ZIF-8 derivatives. For this reason, we compared our force field to ab initio molecular dynamic simulations and found an accuracy comparable to those obtained by different exchange–correlation functionals
Ontogenic appearance of Ca2+ channels characterized as binding sites for nitredipine during development of nervous, skeletal and cardiac muscle systems in the rat
AbstractThe appearance of specific receptors for the Ca2+ channel antagonist nitrendipine has been followed during the fetal and post-natal development of rat brain without cerebellum, cerebellum, skeletal muscle and cardiac muscle. The number of nitrendipine receptors is low at the fetal stage and increases drastically during post-natal development of brain, cerebellum, skeletal muscle and cardiac muscle. The time course of this increase is different for each type of tissue studied. No significant change in receptor ligand dissociation constant (Kd) can be detected over the development period studied. The results are discussed in relation with the known properties of the differentiation process in the four types of excitable tissues studied
Stability and Control of Spiral Vortex Breakdown
The physical origin of spiral vortex
breakdown is investigated using the direct and adjoint Navier-Stokes equations
linearized around axisymmetric vortex breakdown. The wave modes region, defined as the
overlap region between adjoint and direct global mode, allows us to determine whether
the wake of the recirculation region or the recirculation region itself causes the
spiral vortex breakdown
Comparison of statistical models performance in case of segmentation using a small amount of training datasets
International audienceModel-based image segmentation has been extensively used in medical imaging to learn both shape and appearance of anatomical structures from training datasets. The more training datasets are used, the more accurate is the segmented model as we account for more information about its variability. However, training datasets of large size with a proper sampling of the population may not always be available. In this paper, we compare the performance of statistical models in the context of lower limb bones segmentation using MR images when only a small number of datasets is available for training. For shape, both PCA-based priors and shape memory strategies are tested. For appearance, methods based on intensity profiles are tested, namely mean intensity profiles, multivariate Gaussian distributions of pro- files and multimodal profiles from EM clustering. Segmentation results show that local and simple methods perform the best when a small number of datasets is available for training. Conversely, statistical methods feature the best segmentation results when the number of training datasets is increased
Reconstruction 3D des structures anatomiques des membres inférieurs
National audienceDans cet article, nous nous intéressons à la modélisation des structures anatomiques des membres inférieurs telles que les os, les muscles et les tendons. La méthode proposée commence par une acquisition d'images IRM durant laquelle les membres inférieurs d'un sujet sont scannés. Des modèles 3D sont ensuite générés après une segmentation manuelle des structures anatomiques. Cependant, la surface des modèles générés n'est pas lisse. De plus, les modèles ne sont pas attachés alors qu'ils devraient l'être anatomiquement. Nous décrivons donc les différentes étapes pour contraindre les modèles à être corrects au niveau anatomique et nous discutons de leur validation. L'objectif de cette méthode est de pouvoir réutiliser ces modèles dans des méthodes de segmentation automatique
No distributed quantum advantage for approximate graph coloring
We give an almost complete characterization of the hardness of -coloring
-chromatic graphs with distributed algorithms, for a wide range of models
of distributed computing. In particular, we show that these problems do not
admit any distributed quantum advantage. To do that: 1) We give a new
distributed algorithm that finds a -coloring in -chromatic graphs in
rounds, with . 2) We prove that any distributed
algorithm for this problem requires rounds.
Our upper bound holds in the classical, deterministic LOCAL model, while the
near-matching lower bound holds in the non-signaling model. This model,
introduced by Arfaoui and Fraigniaud in 2014, captures all models of
distributed graph algorithms that obey physical causality; this includes not
only classical deterministic LOCAL and randomized LOCAL but also quantum-LOCAL,
even with a pre-shared quantum state.
We also show that similar arguments can be used to prove that, e.g.,
3-coloring 2-dimensional grids or -coloring trees remain hard problems even
for the non-signaling model, and in particular do not admit any quantum
advantage. Our lower-bound arguments are purely graph-theoretic at heart; no
background on quantum information theory is needed to establish the proofs
Tree phylogenetic diversity structures multitrophic communities
1. Plant diversity begets diversity at other trophic levels. While species richness is
the most commonly used measure for plant diversity, the number of evolutionary
lineages (i.e. phylogenetic diversity) could theoretically have a stronger influence
on the community structure of co-occurring organisms. However, this prediction
has only rarely been tested in complex real-world ecosystems.
2. Using a comprehensive multitrophic dataset of arthropods and fungi from a
species-rich subtropical forest, we tested whether tree species richness or tree
phylogenetic diversity relates to the diversity and composition of organisms.
3. We show that tree phylogenetic diversity but not tree species richness determines
arthropod and fungi community composition across trophic levels and increases
the diversity of predatory arthropods but decreases herbivorous arthropod diver-
sity. The effect of tree phylogenetic diversity was not mediated by changed abun-
dances of associated organisms, indicating that evolutionarily more diverse plant
communities increase niche opportunities (resource diversity) but not necessarily
niche amplitudes (resource amount).
4. Our findings suggest that plant evolutionary relatedness structures multitrophic
communities in the studied species-rich forests and possibly other ecosystems
at large. As global change non-randomly threatens phylogenetically distinct plant
species, far-reaching consequences on associated communities are expected
Musculoskeletal simulation model generation from MRI datasets and motion capture data
International audienceToday computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from Magnetic Resonance Imaging (MRI) datasets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information and muscle-tendons actuators is finally used to create a subject-specific musculoskeletal model
Biotic interactions as mediators of context-dependent biodiversity-ecosystem functioning relationships
Biodiversity drives the maintenance and stability of ecosystem functioning as well as many of nature’s benefits to people, yet people cause substantial biodiversity change. Despite broad consensus about a positive relationship between biodiversity and ecosystem functioning (BEF), the underlying mechanisms and their context-dependencies are not well understood. This proposal, submitted to the European Research Council (ERC), aims at filling this knowledge gap by providing a novel conceptual framework for integrating biotic interactions across guilds of organisms, i.e. plants and mycorrhizal fungi, to explain the ecosystem consequences of biodiversity change. The overarching hypothesis is that EF increases when more tree species associate with functionally dissimilar mycorrhizal fungi. Taking a whole-ecosystem perspective, we propose to explore the role of tree-mycorrhiza interactions in driving BEF across environmental contexts and how this relates to nutrient dynamics. Given the significant role that mycorrhizae play in soil nutrient and water uptake, BEF relationships will be investigated under normal and drought conditions. Resulting ecosystem consequences will be explored by studying main energy channels and ecosystem multifunctionality using food web energy fluxes and by assessing carbon storage. Synthesising drivers of biotic interactions will allow us to understand context-dependent BEF relationships. This interdisciplinary and integrative project spans the whole gradient from local-scale process assessments to global relationships by building on unique experimental infrastructures like the MyDiv Experiment, iDiv Ecotron and the global network TreeDivNet, to link ecological mechanisms to reforestation initiatives. This innovative combination of basic scientific research with real-world interventions links trait-based community ecology, global change research and ecosystem ecology, pioneering a new generation of BEF research and represents a significant step towards implementing BEF theory for human needs
Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages
The NLP community has mainly focused on scaling Large Language Models (LLMs) vertically, i.e., making them better for about 100 languages. We instead scale LLMs horizontally: we create, through continued pretraining, Glot500-m, an LLM that covers 511 predominantly low-resource languages. An important part of this effort is to collect and clean Glot500-c, a corpus that covers these 511 languages and allows us to train Glot500-m. We evaluate Glot500-m on five diverse tasks across these languages. We observe large improvements for both high-resource and low-resource languages compared to an XLM-R baseline. Our analysis shows that no single factor explains the quality of multilingual LLM representations. Rather, a combination of factors determines quality including corpus size, script, “help” from related languages and the total capacity of the model. Our work addresses an important goal of NLP research: we should notlimit NLP to a small fraction of the world’s languages and instead strive to support as many languages as possible to bring the benefits of NLP technology to all languages and cultures. Code, data and models are available at https://github.com/cisnlp/Glot500
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