Smoother than smooth: increasing the flow conveyance of an open-channel flow by using drag reduction methods

International audienceThe drag reduction method using polymer additives is a common strategy to minimize friction losses when carrying fluids (water, oil, or slurries) in pipes over long distances. Previous studies showed that the interactions between the polymer and turbulent structures of the flow tend to modify the streamwise velocity profile close to the walls by adding a so-called elastic sublayer between the classical viscous and log layers. The gain in linear head losses can reach up to 80% depending on the roughness of the walls and the concentration of polymers. The application of this technique to sewers and the subsequent gain in discharge capacity motivated this work to quantitatively measure the drag reduction in classical open-channel flows. Three measurement campaigns were performed in a dedicated long flume for several water discharges and several polymer concentrations: backwater curves over smooth and rough channel walls (including velocity and turbulent shear-stress profiles) and flows around emerging obstacles. The addition of polymers, even in limited concentrations, allowed a high friction decrease with the typical Darcy-Weisbach coefficient reduced by factors of 2 and 1.5, respectively, in smooth and rough walls configurations without obstacles, but without strong modifications of the nondimensional velocity profiles. In contrast, when adding emerging obstacles, the flow was unaffected by the inclusion of polymers, in agreement with the prediction of the literature. The drag reduction method by addition of small concentrations of polymers thus appears to be a promising technique to increase flow conveyance in open-channel flows

Optimizing contrastive learning for cortical folding pattern detection

The human cerebral cortex has many bumps and grooves called gyri and sulci. Even though there is a high inter-individual consistency for the main cortical folds, this is not the case when we examine the exact shapes and details of the folding patterns. Because of this complexity, characterizing the cortical folding variability and relating them to subjects' behavioral characteristics or pathologies is still an open scientific problem. Classical approaches include labeling a few specific patterns, either manually or semi-automatically, based on geometric distances, but the recent availability of MRI image datasets of tens of thousands of subjects makes modern deep-learning techniques particularly attractive. Here, we build a self-supervised deep-learning model to detect folding patterns in the cingulate region. We train a contrastive self-supervised model (SimCLR) on both Human Connectome Project (1101 subjects) and UKBioBank (21070 subjects) datasets with topological-based augmentations on the cortical skeletons, which are topological objects that capture the shape of the folds. We explore several backbone architectures (convolutional network, DenseNet, and PointNet) for the SimCLR. For evaluation and testing, we perform a linear classification task on a database manually labeled for the presence of the "double-parallel" folding pattern in the cingulate region, which is related to schizophrenia characteristics. The best model, giving a test AUC of 0.76, is a convolutional network with 6 layers, a 10-dimensional latent space, a linear projection head, and using the branch-clipping augmentation. This is the first time that a self-supervised deep learning model has been applied to cortical skeletons on such a large dataset and quantitatively evaluated. We can now envisage the next step: applying it to other brain regions to detect other biomarkers.Comment: 9 pages, 6 figures, 1 table, SPIE Imaging 202

Multiplication des canaux et valeur perçue de l’offre digitale dans la presse écrite : un effet de complémentarité ?

As many sectors, the newspaper industry has been impacted by digital channels. This has fostered the emergence of new ways of accessing information and contributed to the development of new types of contents. The latest academic and managerial reflections lead to assume the existence of a complementarity effect between contents as well as between channels. This research aims to verify this hypothesis with a survey conducted among 1028 readers of the French newspaper Le Monde. The results validate only, and under condi- tions, a complementary effect between channels

Connectivity-Based Parcellation of the Cortical Mantle Using q-Ball Diffusion Imaging

This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging. The parcellation is performed in two steps. First, the cortical mantle is split at a macroscopic level into 36 large gyri using a sulcus recognition system. Then, for each voxel of the cortex, a connection profile is computed using a probabilistic tractography framework. The tractography is performed from q fields using regularized particle trajectories. Fiber ODF are inferred from the q-balls using a sharpening process focusing the weight around the q-ball local maxima. A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds. During propagation, the particles father child particles in order to improve the sampling of the long fascicles. For each voxel, intersection of the particle trajectories with the gyri lead to a connectivity profile made up of only 36 connection strengths. These profiles are clustered on a gyrus by gyrus basis using a K-means approach including spatial regularization. The reproducibility of the results is studied for three subjects using spatial normalization

PLoS Biol

Microorganisms must make the right choice for nutrient consumption to adapt to their changing environment. As a consequence, bacteria and yeasts have developed regulatory mechanisms involving nutrient sensing and signaling, known as "catabolite repression," allowing redirection of cell metabolism to maximize the consumption of an energy-efficient carbon source. Here, we report a new mechanism named "metabolic contest" for regulating the use of carbon sources without nutrient sensing and signaling. Trypanosoma brucei is a unicellular eukaryote transmitted by tsetse flies and causing human African trypanosomiasis, or sleeping sickness. We showed that, in contrast to most microorganisms, the insect stages of this parasite developed a preference for glycerol over glucose, with glucose consumption beginning after the depletion of glycerol present in the medium. This "metabolic contest" depends on the combination of 3 conditions: (i) the sequestration of both metabolic pathways in the same subcellular compartment, here in the peroxisomal-related organelles named glycosomes; (ii) the competition for the same substrate, here ATP, with the first enzymatic step of the glycerol and glucose metabolic pathways both being ATP-dependent (glycerol kinase and hexokinase, respectively); and (iii) an unbalanced activity between the competing enzymes, here the glycerol kinase activity being approximately 80-fold higher than the hexokinase activity. As predicted by our model, an approximately 50-fold down-regulation of the GK expression abolished the preference for glycerol over glucose, with glucose and glycerol being metabolized concomitantly. In theory, a metabolic contest could be found in any organism provided that the 3 conditions listed above are met

PfAlbas constitute a new eukaryotic DNA/RNA-binding protein family in malaria parasites

In Plasmodium falciparum, perinuclear subtelomeric chromatin conveys monoallelic expression of virulence genes. However, proteins that directly bind to chromosome ends are poorly described. Here we identify a novel DNA/RNA-binding protein family that bears homology to the archaeal protein Alba (Acetylation lowers binding affinity). We isolated three of the four PfAlba paralogs as part of a molecular complex that is associated with the P. falciparum-specific TARE6 (Telomere-Associated Repetitive Elements 6) subtelomeric region and showed in electromobility shift assays (EMSAs) that the PfAlbas bind to TARE6 repeats. In early blood stages, the PfAlba proteins were enriched at the nuclear periphery and partially co-localized with PfSir2, a TARE6-associated histone deacetylase linked to the process of antigenic variation. The nuclear location changed at the onset of parasite proliferation (trophozoite-schizont), where the PfAlba proteins were also detectable in the cytoplasm in a punctate pattern. Using single-stranded RNA (ssRNA) probes in EMSAs, we found that PfAlbas bind to ssRNA, albeit with different binding preferences. We demonstrate for the first time in eukaryotes that Alba-like proteins bind to both DNA and RNA and that their intracellular location is developmentally regulated. Discovery of the PfAlbas may provide a link between the previously described subtelomeric non-coding RNA and the regulation of antigenic variation

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Prot

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Pro