Efficient distributed representations beyond negative sampling

This article describes an efficient method to learn distributed representations, also known as embeddings. This is accomplished minimizing an objective function similar to the one introduced in the Word2Vec algorithm and later adopted in several works. The optimization computational bottleneck is the calculation of the softmax normalization constants for which a number of operations scaling quadratically with the sample size is required. This complexity is unsuited for large datasets and negative sampling is a popular workaround, allowing one to obtain distributed representations in linear time with respect to the sample size. Negative sampling consists, however, in a change of the loss function and hence solves a different optimization problem from the one originally proposed. Our contribution is to show that the sotfmax normalization constants can be estimated in linear time, allowing us to design an efficient optimization strategy to learn distributed representations. We test our approximation on two popular applications related to word and node embeddings. The results evidence competing performance in terms of accuracy with respect to negative sampling with a remarkably lower computational time

Leave no Place Behind: Improved Geolocation in Humanitarian Documents

Geographical location is a crucial element of humanitarian response, outlining vulnerable populations, ongoing events, and available resources. Latest developments in Natural Language Processing may help in extracting vital information from the deluge of reports and documents produced by the humanitarian sector. However, the performance and biases of existing state-of-the-art information extraction tools are unknown. In this work, we develop annotated resources to fine-tune the popular Named Entity Recognition (NER) tools Spacy and roBERTa to perform geotagging of humanitarian texts. We then propose a geocoding method FeatureRank which links the candidate locations to the GeoNames database. We find that not only does the humanitarian-domain data improves the performance of the classifiers (up to F1 = 0.92), but it also alleviates some of the bias of the existing tools, which erroneously favor locations in the Western countries. Thus, we conclude that more resources from non-Western documents are necessary to ensure that off-the-shelf NER systems are suitable for the deployment in the humanitarian sector

Effect of Ni(II), Cd(II) and Al(III) on human fibroblast bioenergetics, a preliminary comparative study

International audienceExposure to Ni, Cd or Al leads to different health issues depending on the dose and the exposure frequency. Their mechanism of action is poorly known, but as metals, they may have some points in common. The aim of this work was to compare the impact on cell bioenergetic of these metals using a common cell model: a normal human dermal fibroblast (NHDF) in primary culture. To study cell bioenergetics which ''concerns energy conservation and conversion processes in a living cell'' as defined by Demirel and Sandler, two technics are combined: oximetry and microcalorimetry. The heat flow measured by microcalorimetry reflects cell metabolism and more generally glucose catabolism (the only nutriment brought to the NHDF). Cell respiration is measured by oximetry and shows the impact on the mitochondria, the energy factory of the cell. Without incubation, Cd inhibits thermogenesis and cell respiration, Ni has no effect, and Al inhibits cell respiration but not thermogenesis. After 24 h of contact at 40 lM, NHDF died with Cd but seemed over-activated with Al and Ni (thermogenesis and cell respiration increased)

Optimizing quantum-enhanced Bayesian multiparameter estimation in noisy apparata

Achieving quantum-enhanced performances when measuring unknown quantities requires developing suitable methodologies for practical scenarios, that include noise and the availability of a limited amount of resources. Here, we report on the optimization of quantum-enhanced Bayesian multiparameter estimation in a scenario where a subset of the parameters describes unavoidable noise processes in an experimental photonic sensor. We explore how the optimization of the estimation changes depending on which parameters are either of interest or are treated as nuisance ones. Our results show that optimizing the multiparameter approach in noisy apparata represents a significant tool to fully exploit the potential of practical sensors operating beyond the standard quantum limit for broad resources range

Non-asymptotic Heisenberg scaling: experimental metrology for a wide resources range

Adopting quantum resources for parameter estimation discloses the possibility to realize quantum sensors operating at a sensitivity beyond the standard quantum limit. Such approach promises to reach the fundamental Heisenberg scaling as a function of the employed resources $N$ in the estimation process. Although previous experiments demonstrated precision scaling approaching Heisenberg-limited performances, reaching such regime for a wide range of $N$ remains hard to accomplish. Here, we show a method which suitably allocates the available resources reaching Heisenberg scaling without any prior information on the parameter. We demonstrate experimentally such an advantage in measuring a rotation angle. We quantitatively verify Heisenberg scaling for a considerable range of $N$ by using single-photon states with high-order orbital angular momentum, achieving an error reduction greater than $10$ dB below the standard quantum limit. Such results can be applied to different scenarios, opening the way to the optimization of resources in quantum sensing

Study of horizontal gene transfer in plant-parasitic plant-parasitic nematodes by mining of soil metagenomes

Les nématodes phytoparasites (NPP) sont parmi les plus importants ravageurs des cultures et menacent l'approvisionnement alimentaire mondial. Outre la nécessité de comprendre leur biologie pour développer de nouvelles stratégies de lutte, ces organismes sont fascinants en termes d'évolution génomique. Le parasitisme des plantes a évolué plusieurs fois indépendamment chez les nématodes selon des processus évolutifs convergents. Il semble que tous les NPP aient acquis des gènes bactériens et fongiques par transferts horizontaux de gènes (THG). Certains des gènes acquis horizontalement sont impliqués dans des fonctions parasitaires essentielles comme la dégradation des parois cellulaires des plantes ou l'assimilation des nutriments provenant des plantes. Cependant, plusieurs questions majeures restent encore en suspens concernant l'origine de ces gènes, leur distribution dans les génomes et la chronologie des événements d'acquisition. La plupart des NPP vivent dans le sol; nous pouvons donc supposer que ces gènes proviennent des micro-organismes du sol. Cependant, la sous-représentation de ces micro-organismes dans les librairies de séquences généralistes a probablement limité les précédentes analyses sur les THG. Pour pallier ce problème, nous avons constitué une bibliothèque de protéines provenant de plus de 6 800 métagénomes du sol disponibles publiquement. Un problème important dans les données métagénomiques concerne la qualité des données provenant des organismes eucaryotes due à l'utilisation d'outils dédiés aux génomes procaryotes. Afin de mieux représenter le pool de gènes présents dans les environnements naturels des NPP, nous avons identifié les contigs eucaryotes et re-prédit les gènes et protéines en utilisant un prédicteur de gènes eucaryotes.. Nous avons, ainsi, obtenu une librairie de protéines fiable et non redondante plus représentative de la biodiversité naturelle du sol.En utilisant cette librairie enrichie en protéines de sol, nous avons effectué une détection de THG sur 18 génomes de NPP du clade Tylenchina constituant un groupe très diversifié de modes de parasitisme. Après curation manuelle, la proportion de gènes acquis par transferts horizontaux avec confirmation phylogénétique est comprise entre 0.5 et 1,9% des gènes codant pour des protéines. Les THG dans les génomes de NPP proviennent principalement de bactéries. Nous avons également observé des THG provenant d'organismes eucaryotes tels que des champignons et pour la première fois des protistes et des plantes. Les taxa les plus représentés parmi les donneurs sont des espèces vivant dans le sol des clades bactériens Burkholderiaceae, Proteobacteria, Actinobacteria, Rhizobiales et fongiques (Dikary)a. L'utilisation de données métagénomiques a permis de préciser l'histoire des THG déjà décrits mais aussi d'identifier des centaines de nouveaux THG. Les prédictions fonctionnelles des THG nouvellement identifiées indiquent une large diversité de fonctions potentielles dont les implications biologiques pourront être plus précisément décrites dans le cadre d'expériences biochimiques. L'intégration de données environnementales dans notre librairie de référence a permis d'étendre la détection des THG et de compléter le catalogue des descendants des potentiels donneurs.Plant-parasitic nematodes (PPN) are among the most important crop pests and threaten the world's food production. Besides the need to understand their biology to develop new control strategies, they are fascinating organisms in terms of genomic evolution. Plant parasitism has evolved several times independently in nematodes with some convergent evolutionary processes. For instance, all studied PPN have acquired bacterial and fungal genes by horizontal gene transfers (HGT). Some of the acquired genes are involved in essential parasitic functions like plant cell wall degradation or processing nutrients from the plant. However, several major questions concerning their origin, evolutionary fate and distribution in the genomes and timing of acquisition events remain unsolved. Most PPN live in soil; thus, we hypothesised that these genes originated from soil-dwelling microorganisms. However, the underrepresentation of soil microorganisms in generalist sequence libraries has previously limited HGT analyses.To circumvent this problem, we built a protein library including more than 6,800 soil metagenomes from the Joint Genome Institute's IMG/M server. The first challenge was to make this massive dataset more accurate and suitable for HGT analysis in PPN genomes. An important issue in metagenomic data is the underrepresentation of eukaryotes and their annotation with prokaryotic tools. To better represent the pool of genes present in the natural environments of PPN, we identified eukaryotic contigs and re-predicted proteins using Augustus, a eukaryotic dedicated gene predictor. Moreover, we reduced the protein sequence redundancy and refined the taxonomic assignment. After all these steps, we obtained an improved and non-redundant database that was more representative of the soil's natural biodiversity. This soil protein library, two times larger than the classic library, contains mainly organisms genetically divergent than lab-cultured.Then, we performed an HGT detection on proteins from 18 plant-parasitic nematode genomes of the Tylenchina clade, constituting a highly diverse group of PPN phenotypes, against our library enriched with soil protein. After manual curation, the proportion of genes acquired by horizontal transfers with phylogenetic confirmation is between 0.5 to 1.9% to protein-coding genes originating from HGT in PPN genomes. Those genes mainly originate from bacteria, but we also observed HGT from eukaryotic kingdoms such as fungi, protists and plants. The most represented taxa in donors are soil-dwelling species of clades Burkholderiaceae, Proteobacteria, Actinobacteria, Rhizobiales and Dikarya. The usage of metagenomic data clarified the history of previously described HGTs but also identified hundreds of new HGTs. Functional analyses of the newly identified HGTs indicate a wide diversity of potential functions whose biological implications can be more precisely described in in-vitro experiments. Integrating environmental data in our reference library has allowed us to extend the detection of HGTs and to complete the catalog of potential donor offspring

Compared study of the cytogenotoxicity of cadmium, nickel and aluminium on normal human dermal fibroblast

Les métaux sont des éléments chimiques ubiquitaires, naturellement présents dans notre environnement et utilisés dans de nombreux secteurs d’activité tels que, l’aérospatial, la cosmétologie ou l’industrie pharmaceutique. De nombreux travaux montrent qu’ils sont susceptibles d’être à l’origine de diverses pathologies. Toutefois, la diversité et les modalités des études réalisées rendent difficiles la comparaison de leurs effets et mécanisme d’action. Dans ce contexte, ce travail concerne l’étude de la cyto-génotoxicité du cadmium, du nickel et de l’aluminium, sur un même modèle cellulaire, le fibroblaste cutané humain. Leur cytotoxicité est évaluée en étudiant leur effet sur la bioénergétique cellulaire par microcalorimétrie et, leur effet sur la viabilité cellulaire est mesuré par des techniques colorimétriques conventionnelles. Leur génotoxicité est déterminée par des techniques spécifiques que sont le test des comètes et des micronoyaux. De plus, une approche de leur interaction avec l’ADN est réalisée par microcalorimétrie. Les résultats montrent que la cytotoxicité du cadmium est supérieure à celle du nickel, elle-même supérieure à celle de l’aluminium. Seuls le cadmium et le nickel sont génotoxiques à pH7 principalement en induisant un effet aneugène. Leur interaction est de type électrostatique anti-coopérative avec les groupements phosphate de l’ADN. Si l’aluminium à pH7, n’exerce pas d’effet génotoxique, son interaction avec l’ADN à pH acide est comparable à celle du cadmium et du nickel. Ce résultat singulier lié à la valeur du pH suggère l’importance de la prise en compte de la spéciation des métaux pour l’étude de leurs effets aussi bien in vitro qu’in vivoMetals are ubiquitous chemical elements naturally present in our environment and used in many field, like aerospace, cosmetology or pharmaceutical industries. Many works show that metals are involved in diverse diseases. However, the way these studies are led, make the comparison of their effects and mechanism of action delicate. In this context, this work studies the cyto-genotoxicity of cadmium, nickel and aluminum on a single cellular model: normal human dermal fibroblasts. Cytotoxicity is first evaluated by the cell bioenergetics study thanks to microcalorimetry technics, and then the effect on cell viability is measured by conventional colorimetric techniques. Genotoxicity is evaluated by specific technics which are comet and micronuclei assays. Furthermore, thermodynamic properties of the interaction between metals and DNA are determined tanks to microcalorimetry measures. Results show that cadmium cytotoxicity is higher than nickel, itself higher than aluminum. Cadmium and nickel are the only ones genotoxic, they mostly induce aneugenic effects. They present an electrostatic anti-cooperative interaction with DNA phosphate groups. If, at pH 7, aluminum does not induce genotoxicity, his interaction is comparable to cadmium and nickel at acidic pH. This unusual result, related to pH value, highlights the importance of the speciation determination when metal effects are studied, as well in vitro as in viv