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In recent decades, advancements in biosensors technology have made fluorescent biosensor pivotal for biomolecular recognition. This paper aims to provide an in-depth analysis of polymerase chain reaction (PCR) fluorescent biosensor detection technology for identifying Escherichia coli (E. coli), setting the stage for future developments in the field.

The review of literature on PCR fluorescent biosensor detection technology for E. coli over the past decades includes discussions on traditional biological fluorescent detection, quantitative PCR fluorescent detection and digital fluorescent detection technology.

Advancements in fluorescent biosensor technology enable precise measurement of fluorescent signals, and when integrated with microfluidic technology, produce compact, reagent-efficient digital sensor devices.

This paper provides a comprehensive review of recent fluorescent detection technology for pathogenic E. coli, assessing method efficiencies and offering insights to advance the field.

Celebrity endorsers are usually considered to bring positive effects to associated nodes, such as brands and corporations. However, limited evidence suggests that brands and corporations are equally responsible for affecting celebrities and their credibility. Drawing on associative network theory, this study explores the effects of brand credibility and corporate credibility on celebrity credibility, both directly and through the mediating and moderating effects of advertising credibility. The research addresses three main issues: (1) whether brand credibility, corporate credibility and advertising credibility have significant effects on celebrity credibility; (2) whether advertising credibility has a significant mediating effect on the effects of brand credibility and corporate credibility on celebrity credibility and (3) whether advertising credibility has a significant moderating effect on the effects of brand credibility and corporate credibility on celebrity credibility.

The study used a quantitative approach involving structural equation modelling. Data were collected from 675 participants from London and focussed on four leading international brands, corporations and celebrity endorsers.

The findings show that brand credibility and advertising credibility have positive direct effects on celebrity credibility; and that advertising credibility mediates the effects of both credibility constructs on celebrity credibility. Furthermore, moderating effects of advertising credibility are also found.

This study will help managers to understand the reverse effects, i.e. the effects of brand credibility and corporate credibility on celebrity credibility. They will be able to understand that a credible brand and corporation like a credible celebrity can also bring significant effects on the associated elements. This will help them to recruit celebrity endorsers who have historically earned their credibility from previous endorsements of credible brands and corporations. Further, these findings will help managers to understand that credibility of the brand and corporation can also affect the credibility of the associated advertising, resulting in having a significant effect on the credibility of the celebrity. This on the consumers’ side will enhance their preferences, attitudes and behaviours, while for the corporation, it will enhance their economic and commercial performance.

This is the first study in the literature, where a conceptual model based on the reverse effects of both credibility constructs on celebrity credibility is examined, directly and based on the moderating and mediating effects of advertising credibility. Hence, the contributions to the literature are threefold: first, the study examines the reverse effect of celebrity endorsement, whereby the credibility of a brand or corporation is transferred to a celebrity endorser; second, the study examines the mediating and moderating effects of advertising credibility on this reverse effect and finally, associative network theory is used to examine the importance of the model.

The main objective of this article is to visualize the structure and trends of pro-environmental behavior (PEB) between 1999 and 2023 through mapping and in-depth analysis. The aim is to analyze PEB, which has received considerable academic attention in recent years due to its key role in the conservation of the environment and the protection of local communities in tourist destinations. This paper provides an important summary of the recent research that has explored the role that tourists have in protecting the environment through PEB.

This study presents a visual analysis of 2005 scholarly articles between the years 1999 and 2023 related to PEB. Using the knowledge mapping based on VOSviewer it presents the current status of research, which includes the analysis of citation analysis, co-citation analysis, co-citation network and longitudinal analysis.

PEB is an emerging topic due to its relevance to protecting the environment in the context of travel. The citation and co-citation analysis show the relevance of the behavior of tourists with regard to protecting the environment. The co-word analysis highlights the current significance of research concerning green hotels and the destination image of environmentally responsible destinations.

This study sheds light on the current research progress of PEB in the context of tourism through a comprehensive analysis (citation, co-citation and co-word). In addition, we provide theories and factors that have been previously used to study PEB in the context of tourism. The findings contribute to a broad and diverse understanding of the concept of PEB, which can provide important insights for policymakers in formulating management strategies and policies aimed at reducing environmental impacts in destinations.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

In this chapter, we explore the dark side of the metaverse and the need for user protection. While the metaverse offers multiple opportunities it also poses significant risks for users, such as privacy concerns, addiction, harassment, and cyberbullying. First, we discuss the various threats that users may encounter such as online harassment, assaults, cyberbullying, hate speech, identity theft, and virtual property theft. As per the Center for Countering Digital Hate, an incident of violation occurs every seven minutes within VRChat, a popular virtual reality game. The level of misconduct in the metaverse can surpass the extent of internet harassment. Virtual reality gaming has been associated with various health issues like sleep deprivation, and insomnia as well as mental health concerns such as depression, anger, and anxiety. We examine how these issues may impact user’s physical and mental health. The sensors and devices used in the metaverse collect a vast amount of user biometric data and spatial data. Interactions between users and metaverse could be leaked. We examine different methods that improve user protection, including everyone from enhanced security protocols via the application of privacy-enhanced technology to several avatars, two-factor authentication, and user educational and awareness programs. Moreover, we explore how the newest technologies, like blockchain and artificial intelligence, play a role in making user safety more important. We finished the course with the study of the case of Second Life, the virtual reality gaming platform, and pointing out some of the problems that exist within it.

This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

This study aimed to observe the effect of workplace spirituality (WPS) on employee silence. In addition, the study investigated the mediating role of workplace incivility on the relationship of WPS with employee silence. We further explored the WPS–workplace incivility link by testing the dark triad as the moderator.

We collected time-lagged data from 403 employees in the Indian hospitality industry. Statistical Package for Social Sciences (SPSS) and Partial Least Squares - Structural Equation Modeling (PLS-SEM) were used to observe the linkages among the study variables.

The results revealed that WPS is associated negatively with employee silence. The dark triad moderated the association between WPS and workplace incivility. Workplace incivility significantly mediated the association between WPS and employee silence.

The study findings would help organizations in promoting WPS to alleviate the occurrences of uncivil behavior at work and comprehend the negative consequences of workplace incivility such as employee silence.

To the best of the author’s knowledge, this study is the first of its kind to explore the linkage between WPS and employee silence. The paper makes a significant contribution by analyzing the interactive effect of personal (dark triad), environmental (WPS) and behavioral (workplace incivility) factors on employee silence.

The phenomenon of nonposting behavior, known as lurking, has become increasingly prevalent on social networking sites (SNS). This study aims to understand why certain users are inclined to lurk on SNS by proposing a theoretical framework that integrates self-presentational concerns, SNS fatigue and social presence.

Building upon the theoretical framework, a moderated mediation model is established to illustrate the mechanisms of lurking on SNS. Survey data were collected from 616 SNS users through an online survey and analyzed using the SPSS macro PROCESS.

The findings show that self-presentational concerns have positive and direct effects on lurking. Moreover, the relationship between self-presentational concerns and lurking is partially mediated by SNS fatigue. Furthermore, both the direct effect and the mediating effect are moderated by social presence.

This study offers a novel theoretical perspective on lurking behavior by introducing a moderated mediation model. The findings reveal intricate mechanisms underlying this specific SNS usage behavior and its connections to both self-presentational concerns and SNS fatigue, thereby enriching the existing literature on user engagement and inactivity on SNS. Furthermore, this research highlights the pivotal role of social presence in moderating the effects of self-presentational concerns, offering new insights into the dynamics of online social interactions.

This study aimed to examine consumers’ impulse purchases of luxury products in the metaverse, specifically by exploring how consumers’ motivational and emotional experiences affect virtual luxury product purchases in the metaverse.

An online survey was administered to a total of 230 users of various metaverse platforms in China. The data were analysed using partial least squares structural equation modelling (PLS-SEM) disjoint two-stage approach.

The findings indicated that motivational experience (goal importance and goal interest) and positive emotion (fantasy, feeling and fun) have positive effects on impulse buying of luxury products in the metaverse, but none for negative emotions (loneliness and isolation).

This study indicated that understanding and leveraging consumers’ motivational experiences and positive emotions can drive their impulse buying behaviour of luxury products in the metaverse, hence providing virtual and brand retailers with a testbed for their products before they launch in the physical market.

This study enriches our comprehension of consumers’ metaverse luxury purchases by delving into the impacts of motivational and emotional experiences on impulse buying behaviours.

As the risk of uncertain quality of used products potentially hinders remanufacturing, this study aims to examine the impact of risk aversion under quality uncertainty of used products in a remanufacturing supply chain (RSC) consisting of a manufacturer and an independent remanufacturer.

We develop an RSC model where the manufacturer produces new products, outsources remanufacturing to the independent remanufacturer and sells both new and remanufactured products to end consumers. Using a manufacturer-led Stackelberg game framework, we derive the equilibrium solutions under risk-neutral and risk-averse scenarios. Additionally, we design a two-part tariff contract to achieve coordination.

We show that while risk aversion leads the manufacturer to raise the outsourcing fee, which in turn reduces both the remanufactured quantity and the collection rate of used products. Consequently, consumer surplus and social welfare decline, while environmental impacts rise. The proposed two-part tariff contract can improve the collection rate and social welfare. We also explore two extensions: an authorization remanufacturing scenario and a two-period scenario. We find that risk aversion has no impact on the selection of remanufacturing mode and the equilibria in the first period. Our findings provide timely managerial insights for RSC management.

One of the main risks deterring remanufacturing is the quality uncertainty of used products. However, the risk aversion arising from this uncertainty and its effects have rarely been studied within a game-theoretic framework. This paper fills this gap by analyzing the remanufacturer’s risk aversion under quality uncertainty and investigating its impacts.