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This paper aims to investigate patterns in UK stock returns related to downside risk, with particular focus on stock returns during financial crises.

First, stocks are sorted into five quintile portfolios based on the relevant beta values (classic beta, downside beta and upside beta, calculated by the moving window approach). Second, patterns of portfolio returns are examined during various sub-periods. Finally, predictive powers of beta and downside beta are examined.

The downside risk is observed to have a significant positive impact on contemporaneous stock returns and a negative impact on future returns in general. In contrast, an inverse relationship between risk and return is observed when stocks are sorted by beta, contrary to the classic literature. UK stock returns exhibit clear time sensitivity, especially during financial crises.

This paper focuses on the impact of the downside risk on UK stock returns, assessed via a comprehensive sub-period analysis. This paper fills the gap in the existing literature, in which very few studies examine the time sensitivity in relation to the downside risk and the risk-return anomaly in the UK stock market using a long sample period.

Traditional nondestructive failure localization techniques are increasingly difficult to meet the requirements of high density and integration of system in package (SIP) devices in terms of resolution and accuracy. Time domain reflection (TDR) is recognized as a novel positioning analysis technology gradually being used in the electronics industry because of the good compatibility, high accuracy and high efficiency. However, there are limited reports focus on the application of TDR technology to SiP devices.

In this study, the authors used the TDR technique to locate the failure of SiP devices, and the results showed that the TDR technique can accurately locate the cracking of internal solder joints of SiP devices.

The measured transmission rate of electromagnetic wave signal was 9.56 × 107 m/s in the experimental SiP devices. In addition, the TDR technique successfully located the failure point, which was mainly caused by the cracking of the solder joint at the edge of the SiP device after 1,500 thermal cycles.

TDR technology is creatively applied to SiP device failure location, and quantitative analysis is realized.

The aim of this study is to explore students' expectations and perceived effectiveness of computer-assisted review tools, and the differences in reliability and validity between human evaluation and automatic evaluation, to find a way to improve students' English writing ability.

Based on the expectancy disconfirmation theory (EDT) and Intelligent Computer-Assisted Language Learning (ICALL) theory, an experiment is conducted through the observation method, semistructured interview method and questionnaire survey method. In the experiment, respondents were asked to write and submit four essays on three online automated essay evaluation (AEE) systems in total, one essay every two weeks. Also, two teacher raters were invited to score the first and last papers of each student. The respondents' feedbacks were investigated to confirm the effectiveness of the AEE system; the evaluation results of the AEE systems and teachers were compared; descriptive statistics was used to analyze the experimental data.

The experiment revealed that the respondents held high expectations for the computer-assisted evaluation tools, and the effectiveness of computer scoring feedback on students was higher than that of teacher scoring feedback. Moreover, at the end of the writing project, the students' independent learning ability and English writing ability were significantly improved. Besides, there was a positive correlation between students' initial expectations of computer-assisted learning tools and the final evaluation of learning results.

The innovation lies in the use of observation methods, questionnaire survey methods, data analysis, and other methods for the experiment, and the combination of deep learning theory, EDT and descriptive statistics, which has particular reference value for future works.

The purpose of this paper is to explore that relational capability plays a mediator role in the relationship between focal enterprises' control on knowledge transfer risks in R&D network.

The paper reviews the related literature from which it proposes a theoretical hypothesis and conceptual framework which is tested empirically adopting regression methodology by mathematical statistics software.

The results reveal that focal enterprises' control (core technological capability and network position) have a positive effect on knowledge transfer risks without the mediation of relational capability. Moreover, relational capability mediates the positive relationship between core technological capability and knowledge transfer risks.

The cross-sectional data of this research has difficult in testing causality between the variables, and future research should take account of the potential factors that can impact on knowledge transfer risks.

The results provide more valuable information to managers in alleviating knowledge transfer risks in R&D networks. For one thing, the study indicates how focal firms' control (core technological capability and network position) can be taken advantage of improving R&D efficiency and reducing the knowledge transfer risks. For another, the results emphasize that relational capability plays an important role in interacting with cooperative enterprises in the process of R&D activities.

Few studies present a theoretical discussion on focal firms control as the important determinants of knowledge transfer risks especially in the R&D network. Moreover it expands the related risk management theory by relational capability that mediates the relationship between focal firms control and knowledge transfer risks.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.