TPGNN: Learning High-order Information in Dynamic Graphs via Temporal Propagation

Temporal graph is an abstraction for modeling dynamic systems that consist of evolving interaction elements. In this paper, we aim to solve an important yet neglected problem -- how to learn information from high-order neighbors in temporal graphs? -- to enhance the informativeness and discriminativeness for the learned node representations. We argue that when learning high-order information from temporal graphs, we encounter two challenges, i.e., computational inefficiency and over-smoothing, that cannot be solved by conventional techniques applied on static graphs. To remedy these deficiencies, we propose a temporal propagation-based graph neural network, namely TPGNN. To be specific, the model consists of two distinct components, i.e., propagator and node-wise encoder. The propagator is leveraged to propagate messages from the anchor node to its temporal neighbors within $k$-hop, and then simultaneously update the state of neighborhoods, which enables efficient computation, especially for a deep model. In addition, to prevent over-smoothing, the model compels the messages from $n$-hop neighbors to update the $n$-hop memory vector preserved on the anchor. The node-wise encoder adopts transformer architecture to learn node representations by explicitly learning the importance of memory vectors preserved on the node itself, that is, implicitly modeling the importance of messages from neighbors at different layers, thus mitigating the over-smoothing. Since the encoding process will not query temporal neighbors, we can dramatically save time consumption in inference. Extensive experiments on temporal link prediction and node classification demonstrate the superiority of TPGNN over state-of-the-art baselines in efficiency and robustness.Comment: Under revie

A Traffic State Detection Tool for Freeway Video Surveillance System

AbstractTraffic state is one of the most important traffic flow parameters to both the traffic management center and the traveler. It's difficult to extract traffic data using surveillance cameras because of the wider field, panning and zooming of the surveillance cameras. To leverage the existing surveillance camera infrastructure, a surveillance video based traffic state detection system is proposed. The proposed system can estimate traffic flow speed and road space occupancy, and recognize three typical traffic states (congested, slow, and smooth). Experimental results show that the system had good adaptation and high accuracy in daytime

Effectiveness and safety of Compound Danshen injection as treatment for pregnancy-induced hypertension: A metaanalysis

Purpose: To systematically evaluate the effectiveness and safety of Compound Danshen injection in patients with pregnancy-induced hypertension (PIH).Methods: PubMed, Embase, Cochrane Library, Chinese biomedical literature database (CBM), VIP (xiAn), China National Knowledge Infrastructure (CNKI) and Wan Fang databases were searched up to March 20, 2018, for all randomized controlled trials (RCTs) on the use of Compound Danshen injection in patients with PIH. Data were extracted from included studies after assessing the quality of literature. Revman 5.3 software was used for statistical analysis．Results: A total of 18 RCTs involving 1735 patients were included. The results of meta-analysis indicated that the study group was superior to the control group in clinical effectiveness (RR = 1.15, 95 % CI: 1.02 - 1.30); intrauterine fetal distress (RR = 0.26, 95 % CI: 0.09 - 0.70); cesarean section (RR = 0.72, 95 % CI: 0.58 - 0.90), and neonatal asphyxia (RR = 0.23, 95 % CI: 0.11 - 0.48). There were no statistical differences in fetal heart rate abnormalities (RR = 0.58, 95 %, CI: 0.33 - 1.02, p > 0.05) and postpartum hemorrhage (RR = 0.86, 95 % CI: 0.53 - 1.42) between the two groups.Conclusion: Treatment of PIH with Compound Danshen injection (alone or in combination) is superior to the use of conventional western medical treatment in safety and effectiveness. However, higher quality clinical studies are needed to confirm these results because most trials included in this study were of low quality.Keywords: Pregnancy-induced hypertension (PIH), Compound Danshen injection, Meta-analysi

Laying Bare: Agamben, Chandler, and The Responsibility to Protect

This paper demonstrates the hidden similarities between Raymond Chandler’s prototypical noir The Big Sleep, and the United Nations Responsibility to Protect (R2P) document. By taking up the work of philosopher Giorgio Agamben, this paper shows that the bare life produces the form of protection embodied by Philip Marlowe in Chandler’s novel and by the United Nations Security Council in R2P. Agamben’s theorizing of the extra-legal status of the sovereign pertains to both texts, in which the protector exists outside of the law. Philip Marlowe, tasked with preventing the distribution of pornographic images, commits breaking-and-entering, withholding evidence, and murder. Analogously, R2P advocates for the Security Council’s ability to trespass laws that safeguard national sovereignty in order to prevent “bare” atrocities against human life. As Agamben demonstrates, the extra-legal position of the protector is made possible by “stripping bare” human life. This paper also gestures towards limitations of Agamben’s thought by indicating, through a comparison of these two texts, that bare life produces states of exception as the object of protection rather than punishment

Duet: efficient and scalable hybriD neUral rElation undersTanding

Learned cardinality estimation methods have achieved high precision compared to traditional methods. Among learned methods, query-driven approaches face the data and workload drift problem for a long time. Although both query-driven and hybrid methods are proposed to avoid this problem, even the state-of-the-art of them suffer from high training and estimation costs, limited scalability, instability, and long-tailed distribution problem on high cardinality and high-dimensional tables, which seriously affects the practical application of learned cardinality estimators. In this paper, we prove that most of these problems are directly caused by the widely used progressive sampling. We solve this problem by introducing predicates information into the autoregressive model and propose Duet, a stable, efficient, and scalable hybrid method to estimate cardinality directly without sampling or any non-differentiable process, which can not only reduces the inference complexity from O(n) to O(1) compared to Naru and UAE but also achieve higher accuracy on high cardinality and high-dimensional tables. Experimental results show that Duet can achieve all the design goals above and be much more practical and even has a lower inference cost on CPU than that of most learned methods on GPU

Risky multi-criteria group decision making on green capacity investment projects based on supply chain

Green capacity investment projects have rapidly emerged involving suppliers, customers, and manufacturing organizations in supply chain systems with environmental challenges. This paper focuses on and identifies both primary strategic and operational elements that will aid managers in evaluating and making risky multi-criteria decisions on green capacity investment projects. We propose a cloud prospect value consensus process consisting of feedback and adjustment mechanisms that provide modification instructions to the corresponding decision makers for a decision matrix based on the cloud model and prospect theory, which considers psychological behavior, disagreements between decision makers, and the ambiguity of linguistic variable assessment across multi-criteria risks. The new model increases the efficiency and accuracy of decision making. To verify the feasibility and validity of the Cloud Prospect Value Consensus Degree based on the Feedback adjustment mechanism, its performance is compared with three state-of-the-art multi-criteria group decision-making methods

Inhibitory effects of cassiae semen extract on the formation of 2-amino-1-methyl-6-phenylimidazo [4,5-b] pyridine (PhIP) in model system

Introduction2-Amino-1-methyl-6-phenylimidazole [4,5-b] pyridine (PhIP), a heterocyclic amine (HAA), is found in meat products heated at high temperatures. However, PhIP is a mutagenic and potential carcinogenic compound. Cassiae semen, a type of medicine and food homology plant, is abundant in China and has been less applied for inhibiting heterocyclic amines.MethodsTo investigate the inhibitory effect of cassiae semen extract on PhIP formation within a model system and elucidate the inhibitory mechanism, an ultrasonic-assisted method with 70% ethanol was used to obtain cassiae semen extract, which was added to a model system (0.6 mmol of phenylalanine: creatinine, 1:1). PhIP was analyzed by LC–MS to determine inhibitory effect. The byproducts of the system and the mechanism of PhIP inhibition were verified by adding the extract to a model mixture of phenylacetaldehyde, phenylacetaldehyde and creatinine.ResultsThe results indicated that PhIP production decreased as the concentration of cassiae semen extract increased, and the highest inhibition rate was 91.9%. Byproduct (E), with a mass–charge ratio of m/z 199.9, was detected in the phenylalanine and creatinine model system but was not detected in the other systems. The cassiae semen extract may have reacted with phenylalanine to produce byproduct (E), which prevented the degradation of phenylalanine by the Strecker reaction to produce phenylacetaldehyde.DiscussionCassiae semen extract consumed phenylalanine, which is the precursor for PhIP, thus inhibiting the formation of phenylacetaldehyde and ultimately inhibiting PhIP formation. The main objective of this study was to elucidate the mechanism by which cassiae semen inhibit PhIP formation and establish a theoretical and scientific foundation for practical control measures

Experimental research on influence of multi-level loading on axial compression behavior of concrete-filled circular steel tubular short columns

In order to study the mechanical properties of early-age concrete-filled steel tube (CFST) under continuous construction process, an experimental investigation on six concrete-filled circular steel tubular short columns under multi-level loading was carried out. The influence of multi-level loading with different initial stress degrees, loading time intervals and loading levels on the deformation progression was analyzed. The bearing capacity of the columns was then tested at 28 days after the multi-level loading. The results show that creep deformation of the concrete-filled steel tubes under multi-level loading is significant and cannot be neglected. The deformation of the columns is significantly affected by the applied loading scheme. An increase of the initial stress degrees and increment of loading levels, or a reduction of loading time interval will all result in an increase of the deformation of the columns. However, the multi-level loading process has only small impact on the bearing capacity of the CFST short columns after 28 days

An integrated software for virus community sequencing data analysis

BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet.RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition "virus OTU" and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes.CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications.</p

Insight into the AP2/ERF transcription factor superfamily in sesame and expression profiling of DREB subfamily under drought stress

Background. Sesame is an important oilseed crop mainly grown in inclement areas with high temperatures and frequent drought. Thus, drought constitutes one of the major constraints of its production. The AP2/ERF is a large family of transcription factors known to play significant roles in various plant processes including biotic and abiotic stress responses. Despite their importance, little is known about sesame AP2/ERF genes. This constitutes a limitation for drought-tolerance candidate genes discovery and breeding for tolerance to water deficit. Results. One hundred thirty-two AP2/ERF genes were identified in the sesame genome. Based on the number of domains, conserved motifs, genes structure and phylogenetic analysis including 5 relatives species, they were classified into 24 AP2, 41 DREB, 61 ERF, 4 RAV and 2 Soloist. The number of sesame AP2/ERF genes was relatively few compared to that of other relatives, probably due to gene loss in ERF and DREB subfamilies during evolutionary process. In general, the AP2/ERF genes were expressed differently in different tissues but exhibited the highest expression levels in the root. Mostly all DREB genes were responsive to drought stress. Regulation by drought is not specific to one DREB group but depends on the genes and the group A6 and A1 appeared to be more actively expressed to cope with drought. Conclusions. This study provides insights into the classification, evolution and basic functional analysis of AP2/ERF genes in sesame which revealed their putative involvement in multiple tissue-/developmental stages. Out of 20 genes which were significantly up- /down-regulated under drought stress, the gene AP2si16 may be considered as potential candidate gene for further functional validation as well for utilization in sesame improvement programs for drought stress tolerance. (Résumé d'auteur