Dynamic Dense Graph Convolutional Network for Skeleton-based Human Motion Prediction

Graph Convolutional Networks (GCN) which typically follows a neural message passing framework to model dependencies among skeletal joints has achieved high success in skeleton-based human motion prediction task. Nevertheless, how to construct a graph from a skeleton sequence and how to perform message passing on the graph are still open problems, which severely affect the performance of GCN. To solve both problems, this paper presents a Dynamic Dense Graph Convolutional Network (DD-GCN), which constructs a dense graph and implements an integrated dynamic message passing. More specifically, we construct a dense graph with 4D adjacency modeling as a comprehensive representation of motion sequence at different levels of abstraction. Based on the dense graph, we propose a dynamic message passing framework that learns dynamically from data to generate distinctive messages reflecting sample-specific relevance among nodes in the graph. Extensive experiments on benchmark Human 3.6M and CMU Mocap datasets verify the effectiveness of our DD-GCN which obviously outperforms state-of-the-art GCN-based methods, especially when using long-term and our proposed extremely long-term protocol

An Investigation of Time-Dependent Deformation Characteristics of Soft Dredger Fill

The creep characteristics of soft clays have been studied for decades. However, the lateral deformation of soils is not allowed during the commonly used one-dimensional consolidation tests, which cannot describe the real deformation features of soils in practice. On the other hand, the influence of drainage distance on the mechanical properties of soil is still controversial, classified as hypothesis A and hypothesis B. For a better understanding of deformation characteristics of soft clay, especially which in long-terms, a series of conventional oedometer tests as well as novel geometric confined consolidation tests was conducted on soft dredger fill. The results show that the secondary consolidation coefficient of the soil sample Cα would increase firstly, followed by a small decrease with the increase of consolidation pressure generally. Cα would decrease with the consolidation time and also be reduced by preloading. The strain at the completion of primary consolidation would increase with the drainage distance, but the Cα would be affected little. Both compression index Cc and Cα of soft clay would reduce after preconsolidation, in which two parameters show an approximate linear relationship. The creep coefficient of soft clay under the geometric confinement Cαε k is larger than that under the oedometer test Cαε. However, the trends of the relationship between the creep coefficient and loading are consistent regardless of the confinement conditions

Characterization of Escherichia coli strains isolated from geese by detection of integron-mediated antimicrobial resistance

ABSTRACT: Objectives: Current research shows that the resistance of Escherichia coli (E. coli) is mainly related to integron gene cassettes. To assess the resistance of E. coli of goose origin and the carriage of its integron genes in four farms in Heilongjiang Province, antibiotic resistance phenotypes and the presence of various types of integrons were investigated. Methods: In this study, test strains were sampled and isolated from the farms, and 109 test strains were tested for drug sensitivity of 15 different antimicrobial drugs by the Kb disc diffusion method. Polymerase chain reaction was used to detect E. coli in three types of integrase genes (intI1, intI2, and intI3) and for sequencing analysis of the class I integron gene cassette. Results: Susceptibility test results show that more than 70% of tested strains exhibit resistant phenotypes to ampicillin, amoxicillin, imipenem, tetracycline, and doxycycline. The detection rate of class I integrons was 68.91%, while class II integrons and class III integrons were not detected. The detection rate of class I integrin gene cassette was 7.42%. Sequence analysis showed that strains carried different integron gene cassettes: dfrA17-aadA5, dfrA1-aadA1, dfrA27-arr-3, and aminoglycoside 3′'-nucleotidyltransferase. Conclusions: Results suggest that the detection rate of class I integrons is highly correlated with their drug resistance. Class I integrons provide a valuable guide to studying the spread and the expression of resistance genes and thus finding effective measures to prevent bacterial resistance

Validating the Chinese Version of the Personal Accountability Measure for Assessing Teachers’ Perceptions and Experiences of Teacher Accountability in China

The study aims to validate the Chinese version of Personal Accountability Measure (PAM-Ch), which is used to assess the subjective aspect of teacher accountability, by surveying 1146 teachers enrolled in professional development courses offered by a public university in Beijing. The validation process involved two phases. First, the samples were randomly divided into three subgroups—for subgroup 1 (n = 390), exploratory factor analysis was computed; for subgroup 2 (n = 359), confirmatory factor analysis (CFA) was computed; and, for subgroup 3 (n = 381), a new CFA was performed for cross-validation. Second, Cronbach’s α, composite reliability (CR), average variance extracted (AVE), maximum shared variance (MSV), and average shared variance (ASV) were calculated for testing the reliability and validity. Throughout the process, three measurement models were tested for the adaptation of the PAM-Ch in this study. The results found that Model 2 was the best fit for the data, whose factor loadings ranged from 0.72–0.95 for internal accountability (factor 1) and 0.75–0.89 for external accountability (factor 2). The CRs of these two factors were 0.963 and 0.916, respectively, and the AVE values were 0.790 and 0.645, respectively, indicating that the PAM-Ch is a reliable and valid measure

Validating the Chinese Version of the Personal Accountability Measure for Assessing Teachers’ Perceptions and Experiences of Teacher Accountability in China

The study aims to validate the Chinese version of Personal Accountability Measure (PAM-Ch), which is used to assess the subjective aspect of teacher accountability, by surveying 1146 teachers enrolled in professional development courses offered by a public university in Beijing. The validation process involved two phases. First, the samples were randomly divided into three subgroups—for subgroup 1 (n = 390), exploratory factor analysis was computed; for subgroup 2 (n = 359), confirmatory factor analysis (CFA) was computed; and, for subgroup 3 (n = 381), a new CFA was performed for cross-validation. Second, Cronbach’s α, composite reliability (CR), average variance extracted (AVE), maximum shared variance (MSV), and average shared variance (ASV) were calculated for testing the reliability and validity. Throughout the process, three measurement models were tested for the adaptation of the PAM-Ch in this study. The results found that Model 2 was the best fit for the data, whose factor loadings ranged from 0.72–0.95 for internal accountability (factor 1) and 0.75–0.89 for external accountability (factor 2). The CRs of these two factors were 0.963 and 0.916, respectively, and the AVE values were 0.790 and 0.645, respectively, indicating that the PAM-Ch is a reliable and valid measure

Multiplayer Reach–Avoid Differential Games in 3D Space Inspired by Harris’ Hawks’ Cooperative Hunting Tactics

This paper investigates a multiplayer reach–avoid differential game in 3-dimensional (3D) space, which involves multiple pursuers, multiple evaders, and a designated target region. The evaders aim to reach the target region, while the pursuers attempt to guard the target region by capturing the evaders. This class of research holds significant practical value. However, the complexity of the problem escalates substantially with the growing number of players, rendering its solution extremely challenging. In this paper, the multiplayer game is divided into many subgames considering the cooperation among pursuers, reducing the computational burden, and obtaining numerically tractable strategies for players. First, the Apollonius sphere, a fundamental geometric tool for analyzing the 3D differential game, is formulated, and its properties are proved. Based on this, the optimal interception point for the pursuer to capture the evader is derived and the winning conditions for the pursuer and evader are established. Then, based on the Apollonius sphere, the optimal state feedback strategies of players are designed, and simultaneously, the optimal one-to-one pairings are obtained. Meanwhile, the Value function of the multiplayer reach–avoid differential game is explicitly given and is proved to satisfy Hamilton–Jacobi–Isaacs (HJI) equation. Moreover, the matching algorithm for the case with pursuers outnumbered evaders is provided through constructing a weighted bipartite graph, and the cooperative tactics for multiple pursuers are proposed, inspired by the Harris’ Hawks intelligent cooperative hunting tactics. Finally, numerical simulations are conducted to illustrate the effectiveness of the theoretical results for both cases where the number of adversary players is equal and unequal between the 2 groups