Factors Influencing Consumer-Perceived Risk in E-Commerce Transactions in China

Over the last decade, electronic commerce has become one of the fastest growing markets in China and it is still growing at a dramatic speed. E-commerce introduces a convenient way for consumers to do shopping. During the online transaction processes, different types of risks are perceived by consumers due to the uncontrollable aspects of the Internet. The facets of perceived risk include social risk, financial risk, performance risk, psychological risk, privacy risk and time risk. This research examines the factors influencing consumer’s risk perception of online transactions, with a focus on trust, novelty and dread. The research model is the psychometric paradigm. Data from this study was collected through an online survey website. Sample was selected by non probability sampling method. The research has found that online vendor’s reputation, service quality, website’s usability and security are negatively related to consumer’s perceived risk, among which the most critical factor is reputation. These factors influence different facets of perceived risk respectively. In the future, both sellers’ efforts in building trust with consumers and advanced technologies are supposed to reduce consumer’s perceived risk in e-commerce transactions. Key words: perceived risk, e-commerce, trust, psychometric paradig

Fraud Dataset Benchmark and Applications

Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings. We note that, as compared to other well researched fields, fraud detection has unique challenges: high-class imbalance, diverse feature types, frequently changing fraud patterns, and adversarial nature of the problem. Due to these, the modeling approaches evaluated on datasets from other research fields may not work well for the fraud detection. In this paper, we introduce Fraud Dataset Benchmark (FDB), a compilation of publicly available datasets catered to fraud detection FDB comprises variety of fraud related tasks, ranging from identifying fraudulent card-not-present transactions, detecting bot attacks, classifying malicious URLs, estimating risk of loan default to content moderation. The Python based library for FDB provides a consistent API for data loading with standardized training and testing splits. We demonstrate several applications of FDB that are of broad interest for fraud detection, including feature engineering, comparison of supervised learning algorithms, label noise removal, class-imbalance treatment and semi-supervised learning. We hope that FDB provides a common playground for researchers and practitioners in the fraud detection domain to develop robust and customized machine learning techniques targeting various fraud use cases

Chronic jet lag alters gut microbiome and mycobiome and promotes the progression of MAFLD in HFHFD-fed mice

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common chronic liver disease worldwide. Circadian disruptors, such as chronic jet lag (CJ), may be new risk factors for MAFLD development. However, the roles of CJ on MAFLD are insufficiently understood, with mechanisms remaining elusive. Studies suggest a link between gut microbiome dysbiosis and MAFLD, but most of the studies are mainly focused on gut bacteria, ignoring other components of gut microbes, such as gut fungi (mycobiome), and few studies have addressed the rhythm of the gut fungi. This study explored the effects of CJ on MAFLD and its related microbiotic and mycobiotic mechanisms in mice fed a high fat and high fructose diet (HFHFD). Forty-eight C57BL6J male mice were divided into four groups: mice on a normal diet exposed to a normal circadian cycle (ND-NC), mice on a normal diet subjected to CJ (ND-CJ), mice on a HFHFD exposed to a normal circadian cycle (HFHFD-NC), and mice on a HFHFD subjected to CJ (HFHFD-CJ). After 16 weeks, the composition and rhythm of microbiota and mycobiome in colon contents were compared among groups. The results showed that CJ exacerbated hepatic steatohepatitis in the HFHFD-fed mice. Compared with HFHFD-NC mice, HFHFD-CJ mice had increases in Aspergillus, Blumeria and lower abundances of Akkermansia, Lactococcus, Prevotella, Clostridium, Bifidobacterium, Wickerhamomyces, and Saccharomycopsis genera. The fungi-bacterial interaction network became more complex after HFHFD and/or CJ interventions. The study revealed that CJ altered the composition and structure of the gut bacteria and fungi, disrupted the rhythmic oscillation of the gut microbiota and mycobiome, affected interactions among the gut microbiome, and promoted the progression of MAFLD in HFHFD mice

Probiotics fortify intestinal barrier function: a systematic review and meta-analysis of randomized trials

BackgroundProbiotics play a vital role in treating immune and inflammatory diseases by improving intestinal barrier function; however, a comprehensive evaluation is missing. The present study aimed to explore the impact of probiotics on the intestinal barrier and related immune function, inflammation, and microbiota composition. A systematic review and meta-analyses were conducted.MethodsFour major databases (PubMed, Science Citation Index Expanded, CENTRAL, and Embase) were thoroughly searched. Weighted mean differences were calculated for continuous outcomes with corresponding 95% confidence intervals (CIs), heterogeneity among studies was evaluated utilizing I2 statistic (Chi-Square test), and data were pooled using random effects meta-analyses.ResultsMeta-analysis of data from a total of 26 RCTs (n = 1891) indicated that probiotics significantly improved gut barrier function measured by levels of TER (MD, 5.27, 95% CI, 3.82 to 6.72, P < 0.00001), serum zonulin (SMD, -1.58, 95% CI, -2.49 to -0.66, P = 0.0007), endotoxin (SMD, -3.20, 95% CI, -5.41 to -0.98, P = 0.005), and LPS (SMD, -0.47, 95% CI, -0.85 to -0.09, P = 0.02). Furthermore, probiotic groups demonstrated better efficacy over control groups in reducing inflammatory factors, including CRP, TNF-α, and IL-6. Probiotics can also modulate the gut microbiota structure by boosting the enrichment of Bifidobacterium and Lactobacillus.ConclusionThe present work revealed that probiotics could improve intestinal barrier function, and alleviate inflammation and microbial dysbiosis. Further high-quality RCTs are warranted to achieve a more definitive conclusion.Clinical trial registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=281822, identifier CRD42021281822

Motivations of women who organized others for prostitution: Evidence from a female prison in China

This article discusses women’s involvement in sex work management – an offence defined under section 358 of the 1997 Chinese Criminal Law and one of the re-emerged areas of illegality following the economic reforms since 1978. It first provides the historical context, legislative background and relevant sections of the Chinese vice laws so as to help make sense of the data obtained. Then it discusses the methodological issues before presenting the empirical findings to explore the socio-demographic profile of the incarcerated female sex work organizers who participated in this study and their motivations for organizing others for prostitution. Based on empirical data, this article explores the impact of social conditions on female offenders in China’s reform era and also the effects of the anti-prostitution policy in the country. Moreover, through a Chinese case study, it makes contributions to broader scholarship on the sex trade regulation. It concludes with a couple of implications for policy and practice

The dynamic conformational landscape of the protein methyltransferase SETD8

Elucidating the conformational heterogeneity of proteins is essential for understanding protein function and developing exogenous ligands. With the rapid development of experimental and computational methods, it is of great interest to integrate these approaches to illuminate the conformational landscapes of target proteins. SETD8 is a protein lysine methyltransferase (PKMT), which functions in vivo via the methylation of histone and nonhistone targets. Utilizing covalent inhibitors and depleting native ligands to trap hidden conformational states, we obtained diverse X-ray structures of SETD8. These structures were used to seed distributed atomistic molecular dynamics simulations that generated a total of six milliseconds of trajectory data. Markov state models, built via an automated machine learning approach and corroborated experimentally, reveal how slow conformational motions and conformational states are relevant to catalysis. These findings provide molecular insight on enzymatic catalysis and allosteric mechanisms of a PKMT via its detailed conformational landscape