Context-aware explainable recommendations over knowledge graphs

Knowledge graphs contain rich semantic relationships related to items and incorporating such semantic relationships into recommender systems helps to explore the latent connections of items, thus improving the accuracy of prediction and enhancing the explainability of recommendations. However, such explainability is not adapted to users' contexts, which can significantly influence their preferences. In this work, we propose CA-KGCN (Context-Aware Knowledge Graph Convolutional Network), an end-to-end framework that can model users' preferences adapted to their contexts and can incorporate rich semantic relationships in the knowledge graph related to items. This framework captures users' attention to different factors: contexts and features of items. More specifically, the framework can model users' preferences adapted to their contexts and provide explanations adapted to the given context. Experiments on three real-world datasets show the effectiveness of our framework: modeling users' preferences adapted to their contexts and explaining the recommendations generated

Context-aware feature attribution through argumentation

Feature attribution is a fundamental task in both machine learning and data analysis, which involves determining the contribution of individual features or variables to a model's output. This process helps identify the most important features for predicting an outcome. The history of feature attribution methods can be traced back to General Additive Models (GAMs), which extend linear regression models by incorporating non-linear relationships between dependent and independent variables. In recent years, gradient-based methods and surrogate models have been applied to unravel complex Artificial Intelligence (AI) systems, but these methods have limitations. GAMs tend to achieve lower accuracy, gradient-based methods can be difficult to interpret, and surrogate models often suffer from stability and fidelity issues. Furthermore, most existing methods do not consider users' contexts, which can significantly influence their preferences. To address these limitations and advance the current state-of-the-art, we define a novel feature attribution framework called Context-Aware Feature Attribution Through Argumentation (CA-FATA). Our framework harnesses the power of argumentation by treating each feature as an argument that can either support, attack or neutralize a prediction. Additionally, CA-FATA formulates feature attribution as an argumentation procedure, and each computation has explicit semantics, which makes it inherently interpretable. CA-FATA also easily integrates side information, such as users' contexts, resulting in more accurate predictions

Constraint-based Recommender System for Crisis Management Simulations

In the context of the evacuation of populations, some citizens/volunteers may want and be able to participate in the evacuation of populations in difficulty by coming to lend a hand to emergency/evacuation vehicles with their own vehicles. One way of framing these impulses of solidarity would be to be able to list in real-time the citizens/volunteers available with their vehicles (land, sea, air, etc.), to be able to geolocate them according to the risk areas to be evacuated, and adding them to the evacuation/rescue vehicles. Because it is difficult to propose an effective real-time operational system on the field in a real crisis situation, in this work, we propose to add a module for recommending driver/vehicle pairs (with their specificities) to a system of crisis management simulation. To do that, we chose to model and develop an ontology-supported constraint-based recommender system for crisis management simulations

Caenorhabditis elegans RIG-I Homolog Mediates Antiviral RNA Interference Downstream of Dicer-Dependent Biogenesis of Viral Small Interfering RNAs.

Dicer enzymes process virus-specific double-stranded RNA (dsRNA) into small interfering RNAs (siRNAs) to initiate specific antiviral defense by related RNA interference (RNAi) pathways in plants, insects, nematodes, and mammals. Antiviral RNAi in Caenorhabditis elegans requires Dicer-related helicase 1 (DRH-1), not found in plants and insects but highly homologous to mammalian retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), intracellular viral RNA sensors that trigger innate immunity against RNA virus infection. However, it remains unclear if DRH-1 acts analogously to initiate antiviral RNAi in C. elegans Here, we performed a forward genetic screen to characterize antiviral RNAi in C. elegans Using a mapping-by-sequencing strategy, we uncovered four loss-of-function alleles of drh-1, three of which caused mutations in the helicase and C-terminal domains conserved in RLRs. Deep sequencing of small RNAs revealed an abundant population of Dicer-dependent virus-derived small interfering RNAs (vsiRNAs) in drh-1 single and double mutant animals after infection with Orsay virus, a positive-strand RNA virus. These findings provide further genetic evidence for the antiviral function of DRH-1 and illustrate that DRH-1 is not essential for the sensing and Dicer-mediated processing of the viral dsRNA replicative intermediates. Interestingly, vsiRNAs produced by drh-1 mutants were mapped overwhelmingly to the terminal regions of the viral genomic RNAs, in contrast to random distribution of vsiRNA hot spots when DRH-1 is functional. As RIG-I translocates on long dsRNA and DRH-1 exists in a complex with Dicer, we propose that DRH-1 facilitates the biogenesis of vsiRNAs in nematodes by catalyzing translocation of the Dicer complex on the viral long dsRNA precursors.IMPORTANCE The helicase and C-terminal domains of mammalian RLRs sense intracellular viral RNAs to initiate the interferon-regulated innate immunity against RNA virus infection. Both of the domains from human RIG-I can substitute for the corresponding domains of DRH-1 to mediate antiviral RNAi in C. elegans, suggesting an analogous role for DRH-1 as an intracellular dsRNA sensor to initiate antiviral RNAi. Here, we developed a forward genetic screen for the identification of host factors required for antiviral RNAi in C. elegans Characterization of four distinct drh-1 mutants obtained from the screen revealed that DRH-1 did not function to initiate antiviral RNAi. We show that DRH-1 acted in a downstream step to enhance Dicer-dependent biogenesis of viral siRNAs in C. elegans As mammals produce Dicer-dependent viral siRNAs to target RNA viruses, our findings suggest a possible role for mammalian RLRs and interferon signaling in the biogenesis of viral siRNAs

Bacillus spp. as potential probiotics: promoting piglet growth by improving intestinal health

The application of Bacillus spp. as probiotics in the swine industry, particularly for piglet production, has garnered significant attention in recent years. This review aimed to summarized the role and mechanisms of Bacillus spp. in promoting growth and maintaining gut health in piglets. Bacillus spp. can enhance intestinal barrier function by promoting the proliferation and repair of intestinal epithelial cells and increasing mucosal barrier integrity, thereby reducing the risk of pathogenic microbial invasion. Additionally, Bacillus spp. can activate the intestinal immune system of piglets, thereby enhancing the body’s resistance to diseases. Moreover, Bacillus spp. can optimize the gut microbial community structure, enhance the activity of beneficial bacteria such as Lactobacillus, and inhibit the growth of harmful bacteria such as Escherichia coli, ultimately promoting piglet growth performance and improving feed efficiency. Bacillus spp. has advantages as well as challenges as an animal probiotic, and safety evaluation should be conducted when using the newly isolated Bacillus spp. This review provides a scientific basis for the application of Bacillus spp. in modern piglet production, highlighting their potential in improving the efficiency of livestock production and animal welfare

Elastic Valley Spin Controlled Chiral Coupling in Topological Valley Phononic Crystals

Distinct from the phononic valley pseudo-spin, the real physical spin of elastic waves adds a novel tool-kit capable of envisaging the valley-spin physics of topological valley phononic crystals from a local viewpoint. Here, we report the observation of local elastic valley spin as well as the hidden elastic spin-valley locking mechanism overlooked before. We demonstrate that the selective one-way routing of valley phonon states along the topological interface can be reversed by imposing the elastic spin meta-source at different interface locations with opposite valley-spin correspondence. We unveil the physical mechanism of selective directionality as the elastic spin controlled chiral coupling of valley phonon states, through both analytical theory and experimental measurement of the opposite local elastic spin density at different interface locations for different transport directions. The elastic spin of valley topological edge phonons can be extended to other topological states and offers new tool to explore topological metamaterials.Comment: 5 pages, 3 figures, of main text + supplementary 10 figures. To be published in Phys. Rev. Let

Syst\`eme de recommandations bas\'e sur les contraintes pour les simulations de gestion de crise

In the context of the evacuation of populations, some citizens/volunteers may want and be able to participate in the evacuation of populations in difficulty by coming to lend a hand to emergency/evacuation vehicles with their own vehicles. One way of framing these impulses of solidarity would be to be able to list in real-time the citizens/volunteers available with their vehicles (land, sea, air, etc.), to be able to geolocate them according to the risk areas to be evacuated, and adding them to the evacuation/rescue vehicles. Because it is difficult to propose an effective real-time operational system on the field in a real crisis situation, in this work, we propose to add a module for recommending driver/vehicle pairs (with their specificities) to a system of crisis management simulation. To do that, we chose to model and develop an ontology-supported constraint-based recommender system for crisis management simulations.Comment: in French languag

Observation of Chern insulator in crystalline ABCA-tetralayer graphene with spin-orbit coupling

Degeneracies in multilayer graphene, including spin, valley, and layer degrees of freedom, are susceptible to Coulomb interactions and can result into rich broken-symmetry states. In this work, we report a ferromagnetic state in charge neutral ABCA-tetralayer graphene driven by proximity-induced spin-orbit coupling from adjacent WSe2. The ferromagnetic state is further identified as a Chern insulator with Chern number of 4, and its Hall resistance reaches 78% and 100% quantization of h/4e2 at zero and 0.4 tesla, respectively. Three broken-symmetry insulating states, layer-antiferromagnet, Chern insulator and layer-polarized insulator and their transitions can be continuously tuned by the vertical displacement field. Remarkably, the magnetic order of the Chern insulator can be switched by three knobs, including magnetic field, electrical doping, and vertical displacement field