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This study aims to explore the dynamics involved in the non-medical use of tramadol among manual labourers in Nigeria.

Using the phenomenological approach, we conducted in-depth interviews with forty (40) manual labourers (age: 19–36 years). These participants were selected through purposive and snowball sampling techniques from two cities in Anambra state, Nigeria, and the data was analysed with thematic analysis.

The results revealed that most of the participants were introduced to tramadol use by their friends. They used tramadol for pain relief, euphoric feeling, energy for work and sexual performance. Unfortunately, most of them may have gradually become dependent on this drug to function well in life without knowing the possible medical and psychological implications.

The sample choice may limit the generalization of the findings; however, the study indicates a need to improve working condition, access to healthcare and awareness of the negative effects of non-medical use of tramadol.

Non-medical use of tramadol may have started as an attempt to help self in performing the daily routine. This action can jeopardize an individual’s mental health and, at the extreme state, hinder performance of daily routine. Friends and the quality of information they provide play a significant role in the onset of this action. The strong point is that many people who are involved in the non-medical use of tramadol are unaware of the possible risks. Improving working conditions and access to healthcare for chronic pain could help reduce these risks.

Unsupervised domain adaptation object detection not only mitigates model terrible performance resulting from domain gap, but also has the ability to apply knowledge trained on a definite domain to a distinct domain. However, aligning the whole feature may confuse the object and background information, making it challenging to extract discriminative features. This paper aims to propose an improved approach which is called intrinsic feature extraction domain adaptation (IFEDA) to extract discriminative features effectively.

IFEDA consists of the intrinsic feature extraction (IFE) module and object consistency constraint (OCC). The IFE module, designed on the instance level, mainly solves the issue of the difficult extraction of discriminative object features. Specifically, the discriminative region of the objects can be paid more attention to. Meanwhile, the OCC is deployed to determine whether category prediction in the target domain brings into correspondence with it in the source domain.

Experimental results demonstrate the validity of our approach and achieve good outcomes on challenging data sets.

Limitations to this research are that only one target domain is applied, and it may change the ability of model generalization when the problem of insufficient data sets or unseen domain appeared.

This paper solves the issue of critical information defects by tackling the difficulty of extracting discriminative features. And the categories in both domains are compelled to be consistent for better object detection.

Recently, the convolutional neural network (ConvNet) has a wide application in the classification of motor imagery EEG signals. However, the low signal-to-noise electroencephalogram (EEG) signals are collected under the interference of noises. However, the conventional ConvNet model cannot directly solve this problem. This study aims to discuss the aforementioned issues.

To solve this problem, this paper adopted a novel residual shrinkage block (RSB) to construct the ConvNet model (RSBConvNet). During the feature extraction from EEG signals, the proposed RSBConvNet prevented the noise component in EEG signals, and improved the classification accuracy of motor imagery. In the construction of RSBConvNet, the author applied the soft thresholding strategy to prevent the non-related motor imagery features in EEG signals. The soft thresholding was inserted into the residual block (RB), and the suitable threshold for the current EEG signals distribution can be learned by minimizing the loss function. Therefore, during the feature extraction of motor imagery, the proposed RSBConvNet de-noised the EEG signals and improved the discriminative of classification features.

Comparative experiments and ablation studies were done on two public benchmark datasets. Compared with conventional ConvNet models, the proposed RSBConvNet model has obvious improvements in motor imagery classification accuracy and Kappa coefficient. Ablation studies have also shown the de-noised abilities of the RSBConvNet model. Moreover, different parameters and computational methods of the RSBConvNet model have been tested on the classification of motor imagery.

Based on the experimental results, the RSBConvNet constructed in this paper has an excellent recognition accuracy of MI-BCI, which can be used for further applications for the online MI-BCI.

This study aims to examine the effect of regional discrimination on tourists’ unethical behavior intention and the mediating role of tourist anger. Furthermore, the study examines whether the impact of regional discrimination on tourist anger is moderated by tourist self-efficacy.

Three scenario experiments were conducted to test the research hypotheses.

The results indicated an indirect effect of regional discrimination on tourists’ unethical behavior intention via tourist anger. In addition, the findings showed that tourist self-efficacy would weaken the relationship between regional discrimination and tourist anger.

This study reveals tourists’ emotional and behavioral reactions to regional discrimination. Further research can examine the influence of regional discrimination from other theoretical lens and field experiments are encouraged.

This study enriches current knowledge on regional discrimination by developing an integral framework to explore tourists’ reactions toward regional discrimination.

This study aims to integrate conservation of resources theory discus the antecedents and consequences of cyberloafing as well as the boundary effect between cyberloafing and mental health.

The authors collected 431 valid questionnaires in four months. Each questionnaire was divided into two parts that had to be distributed. The interval between the first distribution and the second distribution was 15 days.

The research study revealed that employees’ Zhong-Yong thinking and cyberloafing promote mental health, and cyberloafing has a mediating effect. Mindfulness weakens the positive impact of cyberloafing on mental health.

The research study’s results break the stereotype that cyberloafing is not good for organizations. When managers allow employees to engage in cyberloafing at work, this is conducive to employees’ mental health, which can ensure the company’s sustainable development.

Existing empirical studies emphasize the role of customer preference measurement accuracy (CPMA) on customized product quality while neglecting the role of manufacturing flexibility. However, the rise of web-based technology has highlighted consumer-manufacturer interaction in mass customization (MC). This paper explores the relationships between CPMA, manufacturing flexibility, customer participation and customized product quality, inspired by module decomposition and integration theory.

The study carried out a questionnaire survey of 241 directors who are specifically responsible for MC in the apparel industry in China and tested hypotheses with structural equation modeling (SEM).

CPMA has a direct positive influence on customized product quality and an indirect positive effect through manufacturing flexibility. Also, customer participation after placing an order (CPAPO) has a negative moderating effect on the linkage between CPMA and manufacturing flexibility.

A more dynamic relationship between CPMA and MF can be explored in the future, and the findings can be tested in other industries with more abundant data.

Manufacturing flexibility should be improved along with CPMA in MC. Also, disruptions caused by customer participation in the post-design stage should be noticed. In this context, better consumer service in the early design stage may be one possible solution.

First, the essential but unexplored mediating role of manufacturing flexibility is identified, adding knowledge to the consumer–manufacturer interaction literature in MC production. Second, module decomposition and integration are applied to unify consumers and manufacturers into one empirical model, enriched theoretical research on modular theory. Third, this study opens new discussions on the moderating role of customer participation.

The purpose of this paper was to determine the profile of dairy product consumers in the organic market.

The study was based on a survey questionnaire developed by the author and administered to a total of 1,108 respondents. The statistical analysis (including descriptive statistics, the analysis of the discriminative function and the Chi2 test was performed with the use of Statistica 13.1 PL. The respondents’ gender was the factor behind the differences in how they behaved.

The consumers indicated the channels they rely upon to find information on organic dairy products; in addition to trusting the opinions of their family members and experts, they also use web platforms. Further, they specified their preferred locations for buying favorite products during the pandemic: specialized organic food shops, large distribution chains and online stores.

These outcomes will help in identifying target consumer segments and information channels for specific information and advertising messages. They also form an important resource for developing some potential strategies which the supply chain stakeholders could implement to promote organic consumption of dairy products.

This study identifies consumers’ preferred dairy products; motives for purchasing organic dairy products; barriers that consumers believe exist in the market; sources of knowledge about products purchased by consumers; and consumers’ preferred channels for purchasing organic dairy products. To the best of the author’s knowledge, this is the first study of dairy product consumers in the organic market in Poland.

This study investigated the effect of individual perceptions of innovation-oriented human resource system (IHRS) on individual innovative work behavior (IWB) and how this effect is realized.

The authors conducted an online questionnaire survey at three time points with 481 employees in three Chinese organizations. Structural equation modeling was used to test the hypothesized relationships among the variables.

Perceived IHRS was found to positively influence IWB, and this effect was sequentially mediated by individual perceptions of innovative culture and intrinsic motivation.

In order to elicit IWB, HR systems should be constructed around the strategic objective of innovation. Moreover, there should be a match between IHRS and innovative culture to trigger intrinsic motivation and ultimately IWB.

This study examines the effect of perceptions of IHRS on individuals' IWBs; Moreover, it integrates organizational culture and individual motivation and finds a chain mediating role of individual perceptions of innovative culture and intrinsic motivation in the relationship between IHRS and IWB.

This study examines the relationship between green intellectual capital (GIC) and competitive advantage (CA) and proposes the moderating role of corporate philanthropy types (cash, in-kind and both) during the COVID-19 pandemic. In particular, this study investigates the types of corporate philanthropy, strengthening the link between GIC and CA for Chinese listed firms during a pandemic.

Cross-sectional data were collected from 248 chief executive officers (CEOs) of Chinese firms listed on the Shanghai Stock Exchange through a structured questionnaire. Regression analysis was employed to test the proposed hypotheses.

The findings reveal that all types of GIC positively influence a firm's CA. Furthermore, all three types of philanthropy – cash, in-kind and both – moderate the relationship between GIC and CA. However, the intensity of moderation was higher in the case of in-kind philanthropy than in the other two types.

To the best of the authors' knowledge, this is the first empirical study to examine the relationship between GIC (considering its three components: human, structural and relational capital) and CA in China. The study finds different types of philanthropy as moderating variables to better explain the relationship between GIC and CA. Further, it contributes to a new line of research that aims to study philanthropic aspects connected to the GIC debate.

Based on the stimulus-organism-response theory, this research constructs the influence of the stimulus factors of the live-streaming shopping environment on consumers' psychological situation. It then produces the research model of impulsive purchase intention.

In this study, the online questionnaire survey method was used to survey users who participated in live-streaming shopping, and a total of 335 valid questionnaires were collected. Then SPSS and SmartPLS were used for data empirical evaluation and hypotheses test.

Research results show that demand, convenience, interactivity, and playfulness are positively stimulating consumers' perceived enjoyment. And their perceived enjoyment directly drives their intention of impulsive purchase.

The choice of the live streaming platform, the design of the interactive interface, and the design of the shopping process are all factors that the streamer must carefully consider. The results of this study can be used as a reference for the development of live-streaming shopping and provide the industry with an understanding of the main factors that affect users' live streaming and impulsive purchases to plan an effective live streaming platform and content.

“E-commerce live streaming” is regarded as the latest trend of e-commerce, and impulse buying is regarded as a key factor in the success of transactions. This research has developed factors that influence impulsive purchases after watching live streaming based on the SOR theory.