The Effects Of Consumer Perceived Value On Purchase Intention In E-Commerce Platform: A Time-Limited Promotion Perspective

In order to stimulate consumption, most e-commercial giants of China conduct sales promotions centered on “price war”, thus impeding the healthy development of e-commercial enterprises to some degree. Under this condition, it’s every e-commercial enterprise’s top priority to understand the perceived dimension of the central value of the customers’ purchase intention and thus reposition their marketing direction. Therefore, centered on the customers’ purchase intention, this paper structures a four-dimension (i.e., price, functional, emotional and social) model of the perceived value; and, in the meantime, considering the time-limit characteristic of the promotion, as a moderator variable, time pressure is used in the model to conduct the empirical analysis. According to the study, among the dimensions of the perceived value, only the price value and emotional value have a significantly positive influence on the customers’ purchase intention, and the influence by emotional value is bigger than the other. In different time pressure, the influence on purchase intention by perceived value makes significant difference. When there is difference in product category, the time pressure adjustment makes big difference too

Stock Forecasting using Neural Network with Graphs

Due to the complex characteristic in the stock market, it is always a challenge and interesting topic to predict stock price. With the development of neural network models, deep learning has become a popular way to solve the stock prediction problem. Many of the current studies focus on how the stock own historical information which will affect the stock price in the future. Although the individual historical features are essential, the stock price is also affected by the other stocks. To capture such internal relations and influence, we propose to join stock graphs with the neural network model. The reason we choose to use graphs is that the connected graph structure can compress such relation between stocks. We investigate different graph construction methods so that we can describe the stock relation in a comprehensive way. Although graph convolutional network(GCN) has already been proved effective in the prediction of stock movement, it only considers one single graph. Here, we build a combination model based on the GCN that the model can deal with multiple graph features. Apart from GCN, we also applied the transformer-based model to learn the correlation between the stocks. Transformer is a popular model for natural language processing and the implementation in stock prediction is focus on dealing with the public mood. In our research, we applied the stock graph as a mask to attention layer so that the transformer can have prior knowledge. Our experiment applies the stock data from the New York stock exchange. We propose our model using graphs outperforms the recurrent neural network or other methods which do not take the graph structure into account. In the experiment, we investigate how various type of graphs influence the prediction result. The results show that the combination of multiple graphs effectively improves accuracy. But it does not outperform the general GCN model due to the quality of our constructed graphs. Furthermore, we introduced three graph construction methods and examined their impacts on stock prediction problem. The result indicates that the correlation graph is the optimal choice among them. Both multi-graph GCN and transformer with graph mask outperform the LSTM model. Besides, pure transformer+LSTM also produces a better result than the LSTM model. The result reveals our assumption that the internal relation provides sufficient improvements for the stock prediction problem

AU-Supervised Convolutional Vision Transformers for Synthetic Facial Expression Recognition

The paper describes our proposed methodology for the six basic expression classification track of Affective Behavior Analysis in-the-wild (ABAW) Competition 2022. In Learing from Synthetic Data(LSD) task, facial expression recognition (FER) methods aim to learn the representation of expression from the artificially generated data and generalise to real data. Because of the ambiguous of the synthetic data and the objectivity of the facial Action Unit (AU), we resort to the AU information for performance boosting, and make contributions as follows. First, to adapt the model to synthetic scenarios, we use the knowledge from pre-trained large-scale face recognition data. Second, we propose a conceptually-new framework, termed as AU-Supervised Convolutional Vision Transformers (AU-CVT), which clearly improves the performance of FER by jointly training auxiliary datasets with AU or pseudo AU labels. Our AU-CVT achieved F1 score as $0.6863$, accuracy as $0.7433$ on the validation set. The source code of our work is publicly available online: https://github.com/msy1412/ABAW

Dupilumab for the treatment of prurigo nodularis: A systematic review

BackgroundConventional treatment techniques have limited efficacy and more side effects in the treatment of prurigo nodularis. The better alternative treatment option for better outcomes of the disease is dupilumab.ObjectiveThe objective of this study was to systematically review dupilumab-related treatment outcomes in prurigo nodularis.MethodsSeveral databases like Embase, PubMed, Web of Science, and Cochrane library were searched for data acquisition on October 8, 2022. Based on Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, 24 publications were included in this study.ResultsAfter 4,12,16 and more than 16 weeks of dupilumab treatment, 8.3% (n=5/60), 34.4% (n=11/32), 3.6% (n=2/56), and 45.3% (n=29/64) of patients had complete remission, respectively. In addition, 85.0% (n=51/60), 59.4% (n=19/32), 83.9% (n=47/56), and 43.8% (n=28/64) had partial remission, respectively. Moreover, 6.7% (n=4/60), 6.3% (n=2/32), 12.5% (n=7/56), and 10.9% (n=7/64) showed no remission, respectively, and significant reduction of numeric rating scale itch intensity (from 9.0 to 4.9, 2.1, 2.8, 0.9) was attained. There were no serious adverse events observed during treatment, but the most common event observed was conjunctivitis (12.6%, n=15/119).ConclusionsDupilumab has definite effectiveness and safety in prurigo nodularis treatment.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier (CRD42022365802)

E-Service Quality Model of B2C Online Shopping Platform Based on User’S Perspective

In recent year, B2C has gradually become the main driving force of the network shopping market development, many B2C online shopping platform weakens the differences in product and price, which intensify the competition on e-service quality among B2C online shopping platform. Therefore, this paper discusses the composition of electronic service quality model of B2C online shopping platform from the user’s perspective, combining with the analysis of literature and the trading process. And the e-service quality model, which has carried on the empirical test, determined the evaluation index of e-service quality evaluation for B2C e-commerce platform. The results of this study show that e-service quality evaluation model of B2C online shopping platform is composed of seven dimensions and twenty-nine measurement items

E17110 promotes reverse cholesterol transport with liver X receptor β agonist activity in vitro

AbstractLiver X receptor (LXR) plays an important role in reverse cholesterol transport (RCT), and activation of LXR could reduce atherosclerosis. In the present study we used a cell-based screening method to identify new potential LXRβ agonists. A novel benzofuran-2-carboxylate derivative was identified with LXRβ agonist activity: E17110 showed a significant activation effect on LXRβ with an EC50 value of 0.72μmol/L. E17110 also increased the expression of ATP-binding cassette transporter A1 (ABCA1) and G1 (ABCG1) in RAW264.7 macrophages. Moreover, E17110 significantly reduced cellular lipid accumulation and promoted cholesterol efflux in RAW264.7 macrophages. Interestingly, we found that the key amino acids in the LXRβ ligand-binding domain had distinct interactions with E17110 as compared to TO901317. These results suggest that E17110 was identified as a novel compound with LXRβ agonist activity in vitro via screening, and could be developed as a potential anti-atherosclerotic lead compound

Perceptions of the benefits of the basic medical insurance system among the insured: a mixed methods research of a northern city in China

BackgroundThe perceptions of the benefits of the basic medical insurance system among the insured not only reflect the system's performance but also the public's basic medical insurance policy literacy, valuable information for countries that have entered the stage of deepening reform. This study aims to examine the factors that affect the perceptions of the benefits of the basic medical insurance system in China, diagnose the key problems, and propose corresponding measures for improvement.MethodsA mixed method design was used. Data for the quantitative study were obtained from a cross-sectional questionnaire survey (n = 1,045) of residents of Harbin who had enrolled for basic medical insurance system. A quota sampling method was further adopted. A multivariate logistic regression model was then employed to identify the factors influencing the perceptions of the benefits of the basic medical insurance system, followed by semi-structured interviews with 30 conveniently selected key informants. Interpretative phenomenological analysis was used to analyze the interview data.ResultsApproximately 44% of insured persons reported low perceptions of benefits. The logistic regression model showed that low perceptions of the benefits of the basic medical insurance system was positively correlated with the experience of daily drug purchases (OR = 1.967), perceptions of recognition with basic medical insurance system (OR = 1.948), perceptions of the financial burden of participation costs (OR = 1.887), perceptions of the convenience of using basic medical insurance for medical treatment (OR = 1.770), perceptions of the financial burden of daily drug purchases costs (OR = 1.721), perceptions of the financial burden of hospitalization costs (OR = 1.570), and type of basic medical insurance system (OR = 1.456). The results of the qualitative analysis showed that the key problem areas of perceptions of the benefits of the basic medical insurance system were: (I) system design of basic medical insurance; (II) intuitive cognition of the insured; (III) rational cognition of the insured; and (IV) the system environment.ConclusionsImproving the perceptions of the benefits of the basic medical insurance system of the insured requires joint efforts in improving system design and implementation, exploring effective publicity methods of basic medical insurance system information, supporting public policy literacy, and promoting the health system environment

A Novel Small Molecule Which Increases Osteoprotegerin Expression and Protects Against Ovariectomy-Related Bone Loss in Rats

The ratio of osteoprotegerin (OPG) to the receptor activator of NF-κB ligand (RANKL) is a key determinant in the regulation of bone metabolism. The study was performed to screen novel anti-osteoporotic drugs regulating OPG/RANKL ratio and evaluate their effect on bone metabolism. According to the screening results and in vitro results, we found a small molecule, E09241, significantly increased the ratio of OPG/RANKL by mainly increasing OPG expression. Our in vitro studies showed that E09241 increased the alkaline phosphatase (ALP) activity of mouse osteoblasts, promoted mineralization, and increased the expression of osteogenic differentiation-related genes. In addition, we observed that E09241 inhibited RANKL-induced osteoclast differentiation and reduced the expression of osteoclast differentiation-related proteins nuclear factor of activated T cells c1 (NFATc1) and matrix metalloproteinase 9 (MMP-9). More importantly, E09241 exerted therapeutic protection against bone loss in ovariectomized rats in vivo. This protective effect was confirmed to be achieved by inhibiting bone resorption and promoting bone formation in vivo. Mechanistically, E09241 regulates OPG expression through canonical Wnt/β-catenin signaling. Our findings suggest that E09241 is a promising small-molecule compound for treating osteoporosis with a dual effect on osteoblasts and osteoclasts