Fast All-Optical 10 Gb/s NRZ Wavelength Conversion and Power Limiting Function using Hybrid InP on SOI Nanocavity

International audienceA new optical switch is presented using InP/SOI hybrid photonic crystal nanocavity. Switching contrast of 11 dB with 20 mW peak power and recovery time of 14 ps are measured. NRZ wavelength conversion and power limiter are demonstrated at 10 Gb/s through system experiments with 6 and 1 mW peak power respectively

Dispersal syndromes in challenging environments: A cross‐species experiment

Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems. Keywords: context-dependent dispersal; dispersal strategy; distributed experiment; predation risk; resource limitatio

North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states

Simulation characteristics from eighteen global ocean–sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort

Mesenchymal Stromal Cells Improve Salivary Function and Reduce Lymphocytic Infiltrates in Mice with Sjögren's-Like Disease

Non-obese diabetic (NOD) mice develop Sjögren's-like disease (SS-like) with loss of saliva flow and increased lymphocytic infiltrates in salivary glands (SGs). There are recent reports using multipotent mesenchymal stromal cells (MSCs) as a therapeutic strategy for autoimmune diseases due to their anti-inflammatory and immunomodulatory capabilities. This paper proposed a combined immuno- and cell-based therapy consisting of: A) an injection of complete Freund's adjuvant (CFA) to eradicate autoreactive T lymphocytes, and B) transplantations of MSCs to reselect lymphocytes. The objective of this was to test the effectiveness of CD45(-)/TER119(-) cells (MSCs) in re-establishing salivary function and in reducing the number of lymphocytic infiltrates (foci) in SGs. The second objective was to study if the mechanisms underlying a decrease in inflammation (focus score) was due to CFA, MSCs, or CFA+MSCs combined.Donor MSCs were isolated from bones of male transgenic eGFP mice. Eight week-old female NOD mice received one of the following treatments: insulin, CFA, MSC, or CFA+MSC (combined therapy). Mice were followed for 14 weeks post-therapy. CD45(-)/TER119(-) cells demonstrated characteristics of MSCs as they were positive for Sca-1, CD106, CD105, CD73, CD29, CD44, negative for CD45, TER119, CD11b, had high number of CFU-F, and differentiated into osteocytes, chondrocytes and adipocytes. Both MSC and MSC+CFA groups prevented loss of saliva flow and reduced lymphocytic infiltrations in SGs. Moreover, the influx of T and B cells decreased in all foci in MSC and MSC+CFA groups, while the frequency of Foxp3(+) (T(reg)) cell was increased. MSC-therapy alone reduced inflammation (TNF-α, TGF-β), but the combination of MSC+CFA reduced inflammation and increased the regenerative potential of SGs (FGF-2, EGF).The combined use of MSC+CFA was effective in both preventing saliva secretion loss and reducing lymphocytic influx in salivary glands

Connecting Quorum Sensing, c-di-GMP, Pel Polysaccharide, and Biofilm Formation in Pseudomonas aeruginosa through Tyrosine Phosphatase TpbA (PA3885)

With the opportunistic pathogen Pseudomonas aeruginosa, quorum sensing based on homoserine lactones was found to influence biofilm formation. Here we discern a mechanism by which quorum sensing controls biofilm formation by screening 5850 transposon mutants of P. aeruginosa PA14 for altered biofilm formation. This screen identified the PA3885 mutant, which had 147-fold more biofilm than the wild-type strain. Loss of PA3885 decreased swimming, abolished swarming, and increased attachment, although this did not affect production of rhamnolipids. The PA3885 mutant also had a wrinkly colony phenotype, formed pronounced pellicles, had substantially more aggregation, and had 28-fold more exopolysaccharide production. Expression of PA3885 in trans reduced biofilm formation and abolished aggregation. Whole transcriptome analysis showed that loss of PA3885 activated expression of the pel locus, an operon that encodes for the synthesis of extracellular matrix polysaccharide. Genetic screening identified that loss of PelABDEG and the PA1120 protein (which contains a GGDEF-motif) suppressed the phenotypes of the PA3885 mutant, suggesting that the function of the PA3885 protein is to regulate 3,5-cyclic diguanylic acid (c-di-GMP) concentrations as a phosphatase since c-di-GMP enhances biofilm formation by activating PelD, and c-di-GMP inhibits swarming. Loss of PA3885 protein increased cellular c-di-GMP concentrations; hence, PA3885 protein is a negative regulator of c-di-GMP production. Purified PA3885 protein has phosphatase activity against phosphotyrosine peptides and is translocated to the periplasm. Las-mediated quorum sensing positively regulates expression of the PA3885 gene. These results show that the PA3885 protein responds to AHL signals and likely dephosphorylates PA1120, which leads to reduced c-di-GMP production. This inhibits matrix exopolysaccharide formation, which leads to reduced biofilm formation; hence, we provide a mechanism for quorum sensing control of biofilm formation through the pel locus and suggest PA3885 should be named TpbA for tyrosine phosphatase related to biofilm formation and PA1120 should be TpbB

Global Wheat Head Detection 2021: an improved dataset for benchmarking wheat head detection methods

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version

Phénotypage au champ des traits structurels du blé par imagerie RGB à résolution millimétrique

Genetic progress is one of the major leverage used to increase food production and satisfy the needs for the increasing human population under global change issues. Selecting or creating the optimal cultivar for a given location is quite challenging considering the very large spatial and temporal variability of the environmental conditions. Field phenotyping, i.e. the quantitative monitoring of crop state variables and canopy functioning, was recognized as the bottleneck to accelerate genetic progress and increase crop yield. This multidisciplinary study develops statistical and image processing methods to estimate the several structural traits of wheat to be applied to crop breeding. Further, this thesis was undertaken in the context of rapid hardware and software technological advancements illustrated by the increasing accessibility to UAV (Unmanned Aerial Vehicle) and UGV (Unmanned Ground Vehicle) platforms, the decreasing cost of processing units (GPUs, cloud computing) and the boom in the development of deep learning algorithms. This manuscript is divided into five chapters: The first chapter introduces the motivation behind the study as well as the current needs for high throughput phenotyping. A state of the art on phenotyping is also achieved by drawing attention to image processing methods and convolutional neural networks. The second chapter presents the development of methodologies for estimating the crop height. The feasibility of two main technologies and platforms were compared and proven: LiDAR mounted on a UGV and RGB (Red Green Blue) images acquired by a UAV. The next two chapters address the problem of estimating the density of wheat ears and stems from spatial high-resolution images. The results show the potential and limitations of deep learning for this application. Emphasis is also put on the study of the different possible acquisition configurations and the throughput of the method. The last chapter summarizes the pipelines developed and draws different perspectives of high throughput phenotyping to replace or supplement in-situ measurements as well as the improvement facilitated by the methods developed.Le progrès génétique est l'un des principaux leviers utilisés pour accroître la production alimentaire et nourrir la population humaine croissante dans un contexte de changement global. La sélection ou la création du cultivar optimal pour un endroit donné est très difficile compte tenu de la très grande variabilité spatiale et temporelle des conditions environnementales. Le phénotypage au champ, c'est-à-dire le suivi quantitatif des variables d'état des cultures et du fonctionnement du couvert, a été reconnu comme le goulot d'étranglement pour accélérer le progrès génétique. Dans cette thèse pluridisciplinaire, des méthodes statistiques et de traitement d’images sont développées afin d’estimer différents traits structuraux de cultures de blé pour application à l’amélioration variétale. Cette thèse a été entreprise au moment où la technologie progresse très rapidement, à la fois sur les aspects matériels et logiciels : accessibilité aux plates-formes de drones et de véhicules sans pilote, diminution du coût des unités de traitement graphique (GPU) explosion du développement des algorithmes d'apprentissage profond. Cette thèse s’articule en cinq chapitres : Le premier chapitre introduit les motivations de l’étude ainsi que les besoins actuel en matière de phénotypage haut débit. Un état de l’art sur le phénotypage est aussi présenté en attirant l’attention sur les méthodes de traitements d’images et de réseaux de neurones convolutifs. Le deuxième chapitre présente le développement de méthodologies permettant d’estimer la hauteur du couvert à partir d’observations par drone ou par robot roulant au sol. La faisabilité de deux principales technologies et plateformes ont été comparées et prouvées: le LiDAR porté par un véhicule au sol et des images RVB acquises par drone. Les deux chapitres suivants adressent le problème de l’estimation de la densité d’épis et de tiges de blé par images à haute résolution spatiale. Les résultats montrent le potentiel et les limites de l’apprentissage profond pour ces applications. L’accent est aussi mis sur l’étude des différentes configurations d’acquisitions possibles et le débit de la méthode. Le dernier chapitre revient sur les principaux résultats élaborés au cours de cette thèse et ouvre différentes perspectives pour le phénotypage haut-débit en remplacement ou complément des mesures manuelles classiquement réalisées par les sélectionneurs et propose des pistes pour améliorer les méthodes développées

Stochastic estimation of biogeochemical parameters from Globcolour ocean color satellite data in a North Atlantic 3D ocean coupled physical-biogeochemical model

Biogeochemical parameters remain a major source of uncertainty in coupled physical-biogeochemical models of the ocean. In a previous study (Doron et al., 2011), a stochastic estimation method was developed to estimate a subset of biogeochemical model parameters from surface phytoplankton observations. The concept was tested in the context of idealized twin experiments performed with a 1/4° resolution model of the North Atlantic ocean. The method was based on ensemble simulations describing the model response to parameter uncertainty. The statistical estimation process relies on nonlinear transformations of the estimated space to cope with the non-Gaussian behaviour of the resulting joint probability distribution of the model state variables and parameters. In the present study, the same method is applied to real ocean colour observations, as delivered by the sensors SeaWiFS, MERIS and MODIS embarked on the satellites OrbView-2, Envisat and Aqua respectively. The main outcome of the present experiments is a set of regionalised biogeochemical parameters. The benefit is quantitatively assessed with an objective norm of the misfits, which automatically adapts to the different ecological regions. The chlorophyll concentration simulated by the model with this set of optimally derived parameters is closer to the observations than the reference simulation using uniform values of the parameters. In addition, the interannual and seasonal robustness of the estimated parameters is tested by repeating the same analysis using ocean colour observations from several months and several years. The results show the overall consistency of the ensemble of estimated parameters, which are also compared to the results of an independent study