Learning to Reweight for Graph Neural Network

Graph Neural Networks (GNNs) show promising results for graph tasks. However, existing GNNs' generalization ability will degrade when there exist distribution shifts between testing and training graph data. The cardinal impetus underlying the severe degeneration is that the GNNs are architected predicated upon the I.I.D assumptions. In such a setting, GNNs are inclined to leverage imperceptible statistical correlations subsisting in the training set to predict, albeit it is a spurious correlation. In this paper, we study the problem of the generalization ability of GNNs in Out-Of-Distribution (OOD) settings. To solve this problem, we propose the Learning to Reweight for Generalizable Graph Neural Network (L2R-GNN) to enhance the generalization ability for achieving satisfactory performance on unseen testing graphs that have different distributions with training graphs. We propose a novel nonlinear graph decorrelation method, which can substantially improve the out-of-distribution generalization ability and compares favorably to previous methods in restraining the over-reduced sample size. The variables of the graph representation are clustered based on the stability of the correlation, and the graph decorrelation method learns weights to remove correlations between the variables of different clusters rather than any two variables. Besides, we interpose an efficacious stochastic algorithm upon bi-level optimization for the L2R-GNN framework, which facilitates simultaneously learning the optimal weights and GNN parameters, and avoids the overfitting problem. Experimental results show that L2R-GNN greatly outperforms baselines on various graph prediction benchmarks under distribution shifts

Soil Physicochemical and Biological Properties of Paddy-Upland Rotation: A Review

Paddy-upland rotation is an unavoidable cropping system for Asia to meet the increasing demand for food. The reduction in grain yields has increased the research interest on the soil properties of rice-based cropping systems. Paddy-upland rotation fields are unique from other wetland or upland soils, because they are associated with frequent cycling between wetting and drying under anaerobic and aerobic conditions; such rotations affect the soil C and N cycles, make the chemical speciation and biological effectiveness of soil nutrient elements varied with seasons, increase the diversity of soil organisms, and make the soil physical properties more difficult to analyze. Consequently, maintaining or improving soil quality at a desirable level has become a complicated issue. Therefore, fully understanding the soil characteristics of paddy-upland rotation is necessary for the sustainable development of the system. In this paper, we offer helpful insight into the effect of rice-upland combinations on the soil chemical, physical, and biological properties, which could provide guidance for reasonable cultivation management measures and contribute to the improvement of soil quality and crop yield

Effects of Ginkgo biloba Extract on Inflammatory Mediators (SOD, MDA, TNF-α, NF-κBp65, IL-6) in TNBS-Induced Colitis in Rats

Inflammatory mediators play a criticial role in ulcerative colitis immune and inflammatory processes. The aim of the study was to investigate the effects of Ginkgo biloba extract on inflammatory mediators (SOD, MDA, TNF-α, NF-κBp65, IL-6) in TNBS-induced colitis in rats. Colitis in rats was induced by colonic administration with 2,4,6-trinitrobenzene sulfonic acid (TNBS, 150 mg/kg). EGB in doses of (50, 100, 200 mg/kg) was administered for 4 weeks to protect colitis. The results showed that EGB could significantly ameliorate macroscopic and histological damage, evidently elevate the activities of SOD and reduce the contents of MDA, inhibit the protein and mRNA expressions of TNF-α, NF-κBp65, and IL-6 in the colon tissues of experimental colitis in a dose-dependent manner compared with the model group. We concluded that the probable mechanisms of EGB ameliorated inflammatory injury in TNBS-induced colitis in rats by its modulation of inflammatory mediators and antioxidatio

Milestones in Autonomous Driving and Intelligent Vehicles Part \uppercase\expandafter{\romannumeral1}: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks and lack systematic summaries and research directions in the future. Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. This is the second part (Part \uppercase\expandafter{\romannumeral1} for this technical survey) to review the development of control, computing system design, communication, High Definition map (HD map), testing, and human behaviors in IVs. In addition, the third part (Part \uppercase\expandafter{\romannumeral2} for this technical survey) is to review the perception and planning sections. The objective of this paper is to involve all the sections of AD, summarize the latest technical milestones, and guide abecedarians to quickly understand the development of AD and IVs. Combining the SoS and Part \uppercase\expandafter{\romannumeral2}, we anticipate that this work will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future.Comment: 18 pages, 4 figures, 3 table

Milestones in autonomous driving and intelligent vehicles: survey of surveys

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose a Survey of Surveys (SoS) for total technologies of AD and IVs that reviews the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. To our knowledge, this article is the first SoS with milestones in AD and IVs, which constitutes our complete research work together with two other technical surveys. We anticipate that this article will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future

Online Detection of Action Start via Soft Computing for Smart City

International audienceSoft Computing are facing a rapid evolution thanks to the development of artificial intelligence especially the deep learning. With video surveillance technologies of Soft Computing such as image processing, computer vision and pattern recognition combined with Cloud Computing, the construction of smart cities could be maintained and greatly enhanced. In this article, we focus on the ODAS (Online Detection of Action Start) task in video understanding and analysis which is critical to the multimedia security in smart cities. We propose a novel model to tackle this problem and achieves state-of-the-art results on the benchmark THUMOS14 dataset

Fluid Inclusions and Stable Isotope Geochemistry of Gold Mineralization Associated with Fine-Grained Granite: A Case Study of the Xiawolong Gold Deposit, Jiaodong Peninsula, China

The Xiawolong gold deposit, located in the Muping–Rushan gold metallogenic belt (eastern Jiaodong Peninsula), is a newly discovered deposit that developed in the late Early Cretaceous as fine-grained granite. Gold mineralization, which mainly occurs in the middle of fresh fine-grained granite dikes, consists of stockwork-style and disseminated ores. They are characterized by middle-high-temperature mineral assemblages, such as molybdenite and magnetite, associated with gold-bearing pyrite. Four types of primary fluid inclusions, contained within the quartz grains from the gold-bearing disseminated and stockwork-style fine-grained granitic ores, were identified based on microthermometry and Raman spectroscopy. The types identified were type 1 aqueous inclusions with middle-high temperature (201 to 480 °C) and middle-low salinity of 0.18 to 17.00 wt.% NaCl equiv.; type 2 H2O–CO2 inclusions, which show middle-high temperatures (218 to 385 °C), middle-low salinities (1.23 to 13.26 wt.% equiv. NaCl), and variable XCO2 (0.031 to 0.044); type 3 daughter mineral-bearing inclusions with high temperature (416 to 446 °C) and relatively constant and high salinity (28.59 to 32.87 wt.% NaCl equiv.); and type 4 CO2 fluid inclusions, which possess a bulk density of 0.405 to 0.758 g/cm3 and a constant XCO2 (0.952 to 0.990) (according to the decreasing abundance of fluid inclusions). The δ18Owater range is between 3.4 and 5.9‰, and the range of the δD is from −97.1 to −77.4‰, which indicates that the ore-forming process is of a magmatic water origin. The δ34S values possess a narrow range between 4.5 and 9.3‰, indicating the source of the Mesozoic Kunyushan granitoids. The Pb isotopic compositions of pyrite show that the Mesozoic Kunyushan granitoids are the main lead source for pyrites. Types 1, 2, and 3 fluid inclusions coexist in the same view field of the quartz grain, which are suggested to occur as the result of fluid immiscibility because of the boiling of a single homogeneous NaCl-CaCl2-KCl-CO2-H2O system. The fluid immiscibility, rather the fluid mixing and wall-rock sulfidation, is the mechanism of gold precipitation in the Xiawolong deposit. Compared with both the “Linglong-type” and “Jiaojia-type” gold deposits in the Jiaodong Peninsula in terms of geological–petrographic evidence and all of the available geochemical data, it can be concluded the Xiawolong gold deposit is of magmatic hydrothermal origin, having a genetic relation to the fine-grained granite

Systems Pharmacology-Based Precision Therapy and Drug Combination Discovery for Breast Cancer

Breast cancer (BC) is a common disease and one of the main causes of death in females worldwide. In the omics era, researchers have used various high-throughput sequencing technologies to accumulate massive amounts of biomedical data and reveal an increasing number of disease-related mutations/genes. It is a major challenge to use these data effectively to find drugs that may protect human health. In this study, we combined the GeneRank algorithm and gene dependency network to propose a precision drug discovery strategy that can recommend drugs for individuals and screen existing drugs that could be used to treat different BC subtypes. We used this strategy to screen four BC subtype-specific drug combinations and verified the potential activity of combining gefitinib and irinotecan in triple-negative breast cancer (TNBC) through in vivo and in vitro experiments. The results of cell and animal experiments demonstrated that the combination of gefitinib and irinotecan can significantly inhibit the growth of TNBC tumour cells. The results also demonstrated that this systems pharmacology-based precision drug discovery strategy effectively identified important disease-related genes in individuals and special groups, which supports its efficiency, high reliability, and practical application value in drug discovery