Designing a talents training model for cross-border e-commerce: a mixed approach of problem-based learning with social media

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Cross-border e-commerce has developed rapidly integrating the global economy. Research has presented some solutions for the challenges and barriers in cross-border e-commerce from the perspective of the enterprise. However, little is known about the requirements of cross-border e-commerce talents and how to train them. In this paper, we firstly conducted semi-structured interviews to acquire the requirements of cross-border e-commerce talents. Business and market knowledge, technical skills, analytical ability and business practical ability were found to be the four core requirements. Then, we integrated problem-based learning and social media to design a talents training model for cross-border e-commerce and did a program to evaluate effectiveness of the model. Finally, its effectiveness was evaluated from the four evaluation dimensions of attitude, perceived enjoyment, concentration and work intention. The talents training model was improved according to the suggestions

Two-person Graph Convolutional Network for Skeleton-based Human Interaction Recognition

Graph convolutional networks (GCNs) have been the predominant methods in skeleton-based human action recognition, including human-human interaction recognition. However, when dealing with interaction sequences, current GCN-based methods simply split the two-person skeleton into two discrete graphs and perform graph convolution separately as done for single-person action classification. Such operations ignore rich interactive information and hinder effective spatial inter-body relationship modeling. To overcome the above shortcoming, we introduce a novel unified two-person graph to represent inter-body and intra-body correlations between joints. Experiments show accuracy improvements in recognizing both interactions and individual actions when utilizing the proposed two-person graph topology. In addition, We design several graph labeling strategies to supervise the model to learn discriminant spatial-temporal interactive features. Finally, we propose a two-person graph convolutional network (2P-GCN). Our model achieves state-of-the-art results on four benchmarks of three interaction datasets: SBU, interaction subsets of NTU-RGB+D and NTU-RGB+D 120

CLEME2.0: Towards More Interpretable Evaluation by Disentangling Edits for Grammatical Error Correction

The paper focuses on improving the interpretability of Grammatical Error Correction (GEC) metrics, which receives little attention in previous studies. To bridge the gap, we propose CLEME2.0, a reference-based evaluation strategy that can describe four elementary dimensions of GEC systems, namely hit-correction, error-correction, under-correction, and over-correction. They collectively contribute to revealing the critical characteristics and locating drawbacks of GEC systems. Evaluating systems by Combining these dimensions leads to high human consistency over other reference-based and reference-less metrics. Extensive experiments on 2 human judgement datasets and 6 reference datasets demonstrate the effectiveness and robustness of our method. All the codes will be released after the peer review.Comment: 16 pages, 8 tables, 2 figures. Under revie

Analysis on the similarity and difference of the mechanism of Guizhi decoction and formula granules alleviating blood stasis syndrome via metabolomics

Objective To analyze the similarity and difference of the mechanism for Guizhi decoction and its formula granules alleviating blood stasis syndrome (BSS) in rats using proton neclear magnetic resonance spectroscopy (1H-NMR) metabolomics. Methods Firstly, the chemical constituents of Guizhi decoction and its formula granules were analyzed based on liquid chromatography-mass spectrometry (LC-MS) technology. Secondly, 28 SD female mice were randomly divided into control group, model group, decoction group and granule group. The model was constructed with ice water bath and subcutaneous injection of adrenaline. After the modeling was completed, 24 h urine of rats was collected and metabolomic analysis was performed to reveal the metabolic profile regulation mechanism of BSS rats improved by Guizhi decoction and formula granules from the metabolomic level. Results A total of 19 and 20 chemical constituents were identified in decoction and formula granules respectively, and 15 chemical constituents were identified together, 4 chemical constituents were identified in decoction but not in formula granules, and 5 chemical constituents were identified in formula granules but not in decoction. Compared with the model group, the index of whole blood viscosity was significantly regressed after drug intervention in the decoction group and the granule group, and the index of red blood cell aggregation was significantly regressed in the decoction group. The metabolomics results showed that 15 differential metabolites were screened in the decoction group compared with the model group, and that it could improve BSS by modulating four pathways: glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, histidine metabolism, and taurine and hypotaurine metabolism. Thirteen differential metabolites were screened in the granule group compared with the model group. Guizhi formula granules could alleviate BSS by regulating three pathways: glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism and histidine metabolism. Conclusion Both Guizhi decoction and formula granules can improve BSS by regressing disordered differential metabolites and metabolic pathways, which indicates that Guizhi formula granules have similar efficacy to the decoction

The influence of leaf anatomical traits on photosynthesis in Catimor type Arabica coffee

Leaf photosynthesis is largely determined by anatomical features. This study aimed to reveal the quantitative effects of the anatomical structure of Coffea arabica leaves on photosynthesis. Pearson’s correlation and path analysis were used to explore the correlation between leaf structure and photosynthesis. To calculate the comprehensive evaluation value of the correlation between leaf anatomical traits and photosynthetic parameters, the Criteria Importance Through Intercriteria Correlation (CRITIC) method was used to obtain the objective weight of each photosynthetic parameter. The study revealed that leaf anatomical traits were highly significant (p <0.01) and correlated with photosynthetic parameters, suggesting that anatomical traits greatly influenced photosynthesis in C. arabica leaf. Similarly, path coefficient analysis strongly showed direct and indirect correlation of photosynthetic capacity of stomatal conductance of the leaves of C. arabica. The results of the comprehensive evaluation also indicated that leaf thickness (LT) and stomatal density (d) were the anatomical characteristics most closely related to photosynthesis. In these results, understanding the effects of the anatomical structure of coffee leaves on photosynthesis, may provide useful information for coffee breeding programs and the management of coffee plantations to optimize photosynthetic capacity

Promoting the process of determining brain death through standardized training

ObjectiveThis study aims to explore the training mode for brain death determination to ensure the quality of subsequent brain death determination.MethodsA four-skill and four-step (FFT) training model was adopted, which included a clinical neurological examination, an electroencephalogram (EEG) examination, a short-latency somatosensory evoked potential (SLSEP) examination, and a transcranial Doppler (TCD) examination. Each skill is divided into four steps: multimedia theory teaching, bedside demonstration, one-on-one real or dummy simulation training, and assessment. The authors analyzed the training results of 1,577 professional and technical personnel who participated in the FFT training model from 2013 to 2020 (25 sessions), including error rate analysis of the written examination, knowledge gap analysis, and influencing factors analysis.ResultsThe total error rates for all four written examination topics were &lt; 5%, at 4.13% for SLSEP, 4.11% for EEG, 3.71% for TCD, and 3.65% for clinical evaluation. The knowledge gap analysis of the four-skill test papers suggested that the trainees had different knowledge gaps. Based on the univariate analysis and the multiple linear regression analysis, among the six factors, specialty categories, professional and technical titles, and hospital level were the independent influencing factors of answer errors (p &lt; 0.01).ConclusionThe FFT model is suitable for brain death (BD) determination training in China; however, the authors should pay attention to the professional characteristics of participants, strengthen the knowledge gap training, and strive to narrow the difference in training quality

Study on the mechanism of Danggui-Guizhi formula granules in the intervention of cold coagulation and blood stasis syndrome based on fecal metabolomics

Objective The mechanism of Danggui-Guizhi formula granules (DGK-GZK) in the intervention of cold coagulation and blood stasis syndrome (BSS) was studied based on 1H-NMR fecal metabolomics. Methods Eighteen SD female mice were randomly divided into three groups: control group, model group and DGK-GZK group. The effect of DGK-GZK on blood stasis was evaluated by weight changes and hemorheology indexes of rats. Meanwhile, fecal samples of rats in each group on the 14th day were collected for 1H-NMR metabolomics analysis, so as to elucidate the pathogenesis of BSS and the regulation mechanism of DGK-GZK in the intervention of BSS from the metabolic level. Results Compared with the model group, the weight loss of rats in the DGK-GZK group was slowed down after drug intervention, and the hemorheology was significantly reversed (P < 0.01). Fecal metabolomics results showed that the metabolic profile of the model group was significantly different from that of the control group on the 14th day, while the metabolic profile of the DGK-GZK group was separated from that of the model group and tended to be that of the control group. A total of fifteen biomarkers related to BSS were screened by multivariate statistical analysis, mainly involving pathways such as glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, butyric acid metabolism, as well as glyoxylic acid and dicarboxylic acid metabolism. DGK-GZK could significantly reverse these seven biomarkers: acetate, alanine, betaine, butyrate, leucine, propionate, and threonine (all P < 0.05), mainly regulating the disorders in pathways such as glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism, butyric acid metabolism, as well as glyoxylic acid and dicarboxylic acid metabolism. Conclusion BSS is a dynamic and slow-developing process, and the DGK-GZK can improve BSS by regulating various metabolites