A Research Survey of Electronic Commerce Innovation: Evidence from the Literature

The development of technology has ignited many innovations in business management, especially in the electronic commerce area. The essential example, that is, online stores and online shopping, is a critical evolution and innovation from traditional brick-and-mortar stores to clicks and mortar. Following previous research (Van Oorschot et al.), this present study adopted bibliometric and keyword analysis to review the main characteristics of electronic commerce innovations. Focused on the academic sources, the research data used in this study were searched for and collected from the Web of Science (WoS), a renowned academic database which covers the most influential research journals in electronic commerce. Based on a combination of several keywords related to “innovation” and “electronic commerce,” the keyword search in the WoS was conducted in May 2019. As a result, a total of 334 research articles related to electronic commerce innovations were collected. Derived from the bibliometric analysis, some keywords that were seldom used in the earlier decade (2000-2009), but which rapidly grew in use in the recent decade (2010-2018) were found, including m-commerce, platforms, social commerce, online review, and co-creation. In addition, the top 10 influential articles listed in each of the two decades were identified. The results show some of the research trajectories in EC innovations. In the first decade (2000-2009), the top 10 papers focused on traditional IT adoption, such as self-service technology, enterprise resource planning systems, and the adoption of general attitude-intention theories such as the technology acceptance model. In the recent decade (2010-2018), researchers have shown more diverse interest in innovative EC applications, such as RFID applications, cloud computing, crowdsourcing, etc. Accompanying these EC innovation contexts, in addition to general attitude-intention theories, more theories such as signaling theory, have been adopted

Prognostic value of vitamin D in patients with pneumonia: A systematic review and meta-analysis

Purpose: To investigate the prognostic role of vitamin D in pneumonia patients  through meta-analysis.Methods: PubMed and Embase were systematically searched for relevant studies that assessed the impact of vitamin D on the risk of adverse outcomes among patients with pneumonia. Risk ratios (RR) with 95 % confidence intervals (95 % CI) were pooled using meta-analysis. Q-test and I2 statistics were used to evaluate between-study heterogeneity.Results: Six studies were finally included in the meta-analysis. The results of meta-analysis of these studies indicated that low vitamin D status was associated with higher risk of mortality among pneumonia patients (RR = 2.59, 95 % CI = 1.32-5.08; p = 0.005). Results from meta-analysis of studies with adjusted estimates suggest that low vitamin D status was independently associated with higher risk of mortality among pneumonia patients (RR = 3.15, 95 % CI 1.54-6.44, p = 0.002). There was no significant risk of bias in the meta-analysis.Conclusion: This study demonstrates that low vitamin D level is associated with a higher risk of adverse outcomes in patients with pneumonia.Keywords: Pneumonia, Vitamin D, Prognosis, Meta-analysis, Systematic revie

Factors Predicting Emotional Cue-Responding Behaviors of Nurses in Taiwan: An Observational Study

Objective Responding to emotional cues is an essential element of therapeutic communication. The purpose of this study is to examine nurses' competence of responding to emotional cues (CRE) and related factors while interacting with standardized patients with cancer. Methods This is an exploratory and predictive correlational study. A convenience sample of registered nurses who have passed the probationary period in southern Taiwan was recruited to participate in 15-minute videotaped interviews with standardized patients. The Medical Interview Aural Rating Scale was used to describe standardized patients' emotional cues and to measure nurses' CRE. The State-Trait Anxiety Inventory was used to evaluate nurses' anxiety level before the conversation. We used descriptive statistics to describe the data and stepwise regression to examine the predictors of nurses' CRE. Results A total of 110 nurses participated in the study. Regardless of the emotional cue level, participants predominately responded to cues with inappropriate distancing strategies. Prior formal communication training, practice unit, length of nursing practice, and educational level together explain 36.3% variances of the nurses' CRE. Conclusions This study is the first to explore factors related to Taiwanese nurses' CRE. Compared to nurses in other countries, Taiwanese nurses tended to respond to patients' emotional cues with more inappropriate strategies. We also identified significant predictors of CRE that show the importance of communication training. Future research and education programs are needed to enhance nurses' CRE and to advocate for emotion-focused communication

A novel endurance prediction method of series connected lithium-ion batteries based on the voltage change rate and iterative calculation.

High-power lithium-ion battery packs are widely used in large and medium-sized unmanned aerial vehicles and other fields, but there is a safety hazard problem with the application that needs to be solved. The generation mechanism and prevention measurement research is carried out on the battery management system for the unmanned aerial vehicles and the lithium-ion battery state monitoring. According to the group equivalent modeling demand of the battery packs, a new idea of compound equivalent circuit modeling is proposed and the model constructed to realize the accurate description of the working characteristics. In order to realize the high-precision state prediction, the improved unscented Kalman feedback correction mechanism is introduced, in which the simplified particle transforming is introduced and the voltage change rate is calculated to construct a new endurance prediction model. Considering the influence of the consistency difference between battery cells, a novel equilibrium state evaluation idea is applied, the calculation results of which are embedded in the equivalent modeling and iterative calculation to improve the prediction accuracy. The model parameters are identified by the Hybrid Pulse Power Characteristic test, in which the conclusion is that the mean value of the ohm internal resistance is 20.68mΩ. The average internal resistance is 1.36mΩ, and the mean capacitance value is 47747.9F. The state of charge prediction error is less than 2%, which provides a feasible way for the equivalent modeling, battery management system design and practical application of pack working lithium-ion batteries

Five Classification of Mammography Images Based on Deep Cooperation Convolutional Neural Network

Mammography is currently the preferred imaging method for breast cancer screening. Masses and calcification are the main positive signs of mammography. Due to the variable appearance of masses and calcification, a significant number of breast cancer cases are missed or misdiagnosed if it is only depended on the radiologists’ subjective judgement. At present, most of the studies are based on the classical Convolutional Neural Networks (CNN), which uses the transfer learning to classify the benign and malignant masses in the mammography images. However, the CNN is designed for natural images which are substantially different from medical images. Therefore, we propose a Deep Cooperation CNN (DCCNN) to classify mammography images of a data set into five categories including benign calcification, benign mass, malignant calcification, malignant mass and normal breast. The data set consists of 695 normal cases from DDSM, 753 calcification cases and 891 mass cases from CBIS-DDSM. Finally, DCCNN achieves 91% accuracy and 0.98 AUC on the test set, whose performance is superior to VGG16, GoogLeNet and InceptionV3 models. Therefore, DCCNN can aid radiologists to make more accurate judgments, greatly reducing the rate of missed and misdiagnosis

Two new lignan-iridoid glucoside diesters from the leaves of Vaccinium bracteatum and their relative and absolute configuration determination by DFT NMR and TDDFT-ECD calculation

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The Gastrointestinal-Brain-Microbiota Axis: A Promising Therapeutic Target for Ischemic Stroke

Ischemic stroke is a highly complex systemic disease characterized by intricate interactions between the brain and gastrointestinal tract. While our current understanding of these interactions primarily stems from experimental models, their relevance to human stroke outcomes is of considerable interest. After stroke, bidirectional communication between the brain and gastrointestinal tract initiates changes in the gastrointestinal microenvironment. These changes involve the activation of gastrointestinal immunity, disruption of the gastrointestinal barrier, and alterations in gastrointestinal microbiota. Importantly, experimental evidence suggests that these alterations facilitate the migration of gastrointestinal immune cells and cytokines across the damaged blood-brain barrier, ultimately infiltrating the ischemic brain. Although the characterization of these phenomena in humans is still limited, recognizing the significance of the brain-gastrointestinal crosstalk after stroke offers potential avenues for therapeutic intervention. By targeting the mutually reinforcing processes between the brain and gastrointestinal tract, it may be possible to improve the prognosis of ischemic stroke. Further investigation is warranted to elucidate the clinical relevance and translational potential of these findings

Heritable and Lineage-Specific Gene Knockdown in Zebrafish Embryo

BACKGROUND: Reduced expression of developmentally important genes and tumor suppressors due to haploinsufficiency or epigenetic suppression has been shown to contribute to the pathogenesis of various malignancies. However, methodology that allows spatio-temporally knockdown of gene expression in various model organisms such as zebrafish has not been well established, which largely limits the potential of zebrafish as a vertebrate model of human malignant disorders. PRINCIPAL FINDING: Here, we report that multiple copies of small hairpin RNA (shRNA) are expressed from a single transcript that mimics the natural microRNA-30e precursor (mir-shRNA). The mir-shRNA, when microinjected into zebrafish embryos, induced an efficient knockdown of two developmentally essential genes chordin and alpha-catenin in a dose-controllable fashion. Furthermore, we designed a novel cassette vector to simultaneously express an intronic mir-shRNA and a chimeric red fluorescent protein driven by lineage-specific promoter, which efficiently reduced the expression of a chromosomally integrated reporter gene and an endogenously expressed gata-1 gene in the developing erythroid progenitors and hemangioblasts, respectively. SIGNIFICANCE: This methodology provides an invaluable tool to knockdown developmental important genes in a tissue-specific manner or to establish animal models, in which the gene dosage is critically important in the pathogenesis of human disorders. The strategy should be also applicable to other model organisms

Experimental asymmetric plug-and-play measurement-device-independent quantum key distribution

Measurement-device-independent quantum key distribution (MDI-QKD) is immune to all security loopholes on detection. Previous experiments on MDI-QKD required spatially separated signal lasers and complicated stabilization systems. In this paper, we perform a proof-of-principle experimental demonstration of plug-and-play MDI-QKD over an asymmetric channel setting with a single signal laser in which the whole system is automatically stabilized in spectrum, polarization, arrival time, and phase reference. Both the signal laser and the single-photon detectors are in the possession of a common server. A passive timing-calibration technique is applied to ensure the precise and stable overlap of signal pulses. The results pave the way for the realization of a quantum network in which the users only need the encoding devices.National Natural Science Foundation (China) (Grants 11304391, 11674397 and 61671455)Natural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship

Mindfulness-based cognitive therapy v. group psychoeducation for people with generalised anxiety disorder: randomised controlled trial

Background: Research suggests that an 8-week mindfulness-based cognitive therapy (MBCT) course may be effective for generalised anxiety disorder (GAD). Aims: To compare changes in anxiety levels among participants with GAD randomly assigned to MBCT, cognitive–behavioural therapy-based psychoeducation and usual care. Method: In total, 182 participants with GAD were recruited (trial registration number: CUHK_CCT00267) and assigned to the three groups and followed for 5 months after baseline assessment with the two intervention groups followed for an additional 6 months. Primary outcomes were anxiety and worry levels. Results: Linear mixed models demonstrated significant group × time interaction (F(4,148) = 5.10, P = 0.001) effects for decreased anxiety for both the intervention groups relative to usual care. Significant group × time interaction effects were observed for worry and depressive symptoms and mental health-related quality of life for the psychoeducation group only. Conclusions: These results suggest that both of the interventions appear to be superior to usual care for the reduction of anxiety symptoms