Question Directed Graph Attention Network for Numerical Reasoning over Text

Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language understanding and arithmetic computation. To address this challenge, we propose a heterogeneous graph representation for the context of the passage and question needed for such reasoning, and design a question directed graph attention network to drive multi-step numerical reasoning over this context graph.Comment: Accepted at EMNLP 202

Function of TRP channels in monocytes/macrophages

The transient receptor potential channel (TRP channel) family is a kind of non- specific cation channel widely distributed in various tissues and organs of the human body, including the respiratory system, cardiovascular system, immune system, etc. It has been reported that various TRP channels are expressed in mammalian macrophages. TRP channels may be involved in various signaling pathways in the development of various systemic diseases through changes in intracellular concentrations of cations such as calcium and magnesium. These TRP channels may also intermingle with macrophage activation signals to jointly regulate the occurrence and development of diseases. Here, we summarize recent findings on the expression and function of TRP channels in macrophages and discuss their role as modulators of macrophage activation and function. As research on TRP channels in health and disease progresses, it is anticipated that positive or negative modulators of TRP channels for treating specific diseases may be promising therapeutic options for the prevention and/or treatment of disease

Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488–47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10−13), ALDH2/MYL2 (rs671, P = 3.40 × 10−11; rs12229654, P = 4.56 × 10−9), ITIH4 (rs2535633, P = 1.77 × 10−10) and NT5C2 (rs11191580, P = 3.83 × 10−8) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10−8) and an additional 14 at P < 1.0 × 10−3 with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity

ScaleNet - Improve CNNs through Recursively Rescaling Objects

Deep networks are often not scale-invariant hence their performance can vary wildly if recognizable objects are at an unseen scale occurring only at testing time. In this paper, we propose ScaleNet, which recursively predicts object scale in a deep learning framework. With an explicit objective to predict the scale of objects in images, ScaleNet enables pretrained deep learning models to identify objects in the scales that are not present in their training sets. By recursively calling ScaleNet, one can generalize to very large scale changes unseen in the training set. To demonstrate the robustness of our proposed framework, we conduct experiments with pretrained as well as fine-tuned classification and detection frameworks on MNIST, CIFAR-10, and MS COCO datasets and results reveal that our proposed framework significantly boosts the performances of deep networks

Overlapping community‐based particle swarm optimization algorithm for influence maximization in social networks

Abstract Influence maximization, whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network, has many applications such as goods advertising and rumour suppression. Among the existing influence maximization methods, the community‐based ones can achieve a good balance between effectiveness and efficiency. However, this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping node. In fact, many nodes in social networks are overlapping ones, which play more important role in influence spreading. To this end, an overlapping community‐based particle swarm optimization algorithm named OCPSO for influence maximization in social networks, which can make full use of overlapping nodes, non‐overlapping nodes, and their interactive information is proposed. Specifically, an overlapping community detection algorithm is used to obtain the information of overlapping community structures, based on which three novel evolutionary strategies, such as initialisation, mutation, and local search are designed in OCPSO for better finding influential nodes. Experimental results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts (e.g. CGA, CMA‐IM, CIM, CDH‐SHRINK, CNCG, and CFIN)

Root Distribution and Soil Properties of Gully Heads and Their Effects on Headcut Migration in the Mollisols Region of Northeast China

Previous studies have proved that root distribution along gully headwalls greatly alters soil properties and further affects the soil erodibility of gully heads. However, it is not clear whether the gully headcut migration is affected by root distribution and soil properties. Five representative gullies developed in different land uses were selected to clarify the variations of root distribution and soil properties and their effects on headcut migration in the rainy season (May to October 2021) in the Mollisols region of northeast China. Results showed that the 68.4%&ndash;93.3% of root mass density and 65.6&ndash;88.5% of root length density were concentrated in 0&ndash;30 cm soil layer of gully heads, and the roots of &lt;2.0 mm accounted for &gt;85%. The gullies developed in farmlands had relatively higher soil compactness, shear strength and aggregate stability, but lower organic matter (OMC), disintegration capacity and soil permeability than those developed in woodlands, unpaved roads in farmland and stable gully-beds. Changes in soil properties of gully heads were closely related to root density. The linear, areal, and volumetric migration rate of gully heads varied greatly and were 1.07&ndash;35.11 m yr&minus;1, 28.95&ndash;562.46 m2 yr&minus;1 and 56.82&ndash;6626.37 m3 yr&minus;1, respectively, with the average of 9.07 m yr&minus;1, 156.92 m2 yr&minus;1 and 1503.02 m3 yr&minus;1, respectively. The change in headcut migration rate was significantly affected by root density, soil properties and drainage area, of which soil texture, OMC, soil aggregate structure, and the drainage area were the critical factors influencing headcut migration in the Mollisols region of northeast China

Root Distribution and Soil Properties of Gully Heads and Their Effects on Headcut Migration in the Mollisols Region of Northeast China

Previous studies have proved that root distribution along gully headwalls greatly alters soil properties and further affects the soil erodibility of gully heads. However, it is not clear whether the gully headcut migration is affected by root distribution and soil properties. Five representative gullies developed in different land uses were selected to clarify the variations of root distribution and soil properties and their effects on headcut migration in the rainy season (May to October 2021) in the Mollisols region of northeast China. Results showed that the 68.4%–93.3% of root mass density and 65.6–88.5% of root length density were concentrated in 0–30 cm soil layer of gully heads, and the roots of 85%. The gullies developed in farmlands had relatively higher soil compactness, shear strength and aggregate stability, but lower organic matter (OMC), disintegration capacity and soil permeability than those developed in woodlands, unpaved roads in farmland and stable gully-beds. Changes in soil properties of gully heads were closely related to root density. The linear, areal, and volumetric migration rate of gully heads varied greatly and were 1.07–35.11 m yr−1, 28.95–562.46 m2 yr−1 and 56.82–6626.37 m3 yr−1, respectively, with the average of 9.07 m yr−1, 156.92 m2 yr−1 and 1503.02 m3 yr−1, respectively. The change in headcut migration rate was significantly affected by root density, soil properties and drainage area, of which soil texture, OMC, soil aggregate structure, and the drainage area were the critical factors influencing headcut migration in the Mollisols region of northeast China