Label-Free, Sensitive, and Versatile Colorimetric Method for Molecule Detection via the G-Quadruplex-Based Signal Quenching Strategy.

Signal amplification strategies have emerged as a prominent tool in the field of improving the detection sensitivity of small extracellular vesicles (sEVs). It is important to highlight that the utilization of signal quenching strategies is not commonly implemented. A detection technique for sEVs was established based on the unwinding of G-quadruplex using Klenow fragment polymerase (KF), which served as an inspiration for this study. This system is characterized by its simplicity and lack of labeling, making it an efficient approach for signal quenching. In the presence of sEVs, the CD63 aptamer in the capture@sMBs complex binds with the CD63 protein on the surface of sEVs to release trigger sequences, which were employed as a primer to mediate the DNA polymerase/endonuclease-assisted signal recycling. The signal recycling process produces numerous single-stranded DNA sequences that can bind to the toehold section of the G-quadruplex. This leads to the rupture of the G-quadruplex structure and the subsequent deactivation of a DNAzyme generated by the G-quadruplex structure and hemin, thereby inhibiting its biological catalytic function. Consequently, the G-quadruplex structure would undergo a transformation to a duplex structure, leading to the emergence of a discernible differential signal that can be noticed in a majority of instances, even without the aid of magnification devices. The decrease in the prominent signal allows for the efficient analysis of target sEVs, which exhibit a notably low detection limit. In addition to the detection of sEVs, the approach has also been utilized for the investigation of miRNA-21. The approach demonstrates a high level of selectivity and robustness in its capacity to differentiate between target miRNA and base-mismatched miRNA as well as other miRNA families. This statement suggests that the assay holds significant promise for use in biochemical research and clinical diagnosis.

Decision model for binary safety management behavior in a supply chain under digital scenarios: A study based on differential game theory.

The purpose of this study is to expand and deepen research in the field of safety production, explore the role of enterprises as decision-making entities in safety production, analyze the role of different types of decision-making behaviors in the process of enterprise safety production, and provide certain theoretical guidance for multi-agent decision-making in safety production. By summarizing and comparing the existing dual system of supply chain safety management, this study proposes dividing supply chain safety management into the two categories of safety organization and safety research and development (safety R&D) in the context of digitalization. Differential equations are established to describe a two-level supply chain safety management problem including manufacturers and suppliers. The research results show that, compared with the Nash equilibrium, when there are strong manufacturers involved in safety management cooperation, the manufacturer's safety R&D subsidy to suppliers improves the total revenue of the supply chain. When the manufacturer's safety organization supervision efficiency is high, the Stackelberg equilibrium is lower. It is a Pareto improvement for the manufacturer to supervise the supplier's safety organization to the Nash equilibrium. In the case of dual safety cooperation in the supply chain, when there are strong manufacturers, R&D subsidies have a crowding out effect on the safety organization cooperation. Finally, based on the example analysis, relevant suggestions are put forward for supply chain safety management.

The influence of work safety information disclosure on performance of listed companies in high-risk industries: Evidence from Shenzhen stock Exchange.

The disclosure of work safety information of listed companies in high-risk industries is an important aspect of their social responsibility, and it is also an inevitable requirement to meet the right of stakeholders to know, which has a far-reaching impact on the development of enterprises. In order to clarify the impact mechanism of work safety information disclosure on enterprise performance of listed companies in high-risk industries. 222 listed companies in high-risk industries were taken as the research object, and the multiple regression analysis method was used to analyze the relationship between the level of work safety information disclosure of enterprises and their financial performance, safety performance and social reputation. The results show that the work safety information disclosure of listed companies in high-risk industries has a positive impact on corporate financial performance, safety performance and social reputation; unabsorbed slack resources have a positive U-shaped regulatory effect on work safety information disclosure and enterprise social reputation; The shareholding ratio of institutional investors has an inverted U-shaped regulatory effect on the positive relationship between work safety information disclosure and enterprise social reputation. This study has enriched the theoretical and practical exploration of research on work safety information disclosure. It can help improve the level of work safety information disclosure and safety management in enterprises, while guiding the sustainable development of occupational health and safety within these organizations.

Understand, track and develop enterprise workplace safety, and sustainability in the industrial park.

Industrial parks make great contributions to the local economy, society, and culture, but they have also encountered many problems, such as limited resources, the longevity of ecological restoration, and the contagion of safety accidents. As a socioeconomic and ecological composite system formed by the interaction of multiple stakeholders, the solutions to succeed in workplace sustainability in industrial parks are still not known. The purpose of this study is to explore how to integrate existing resources to achieve a win-win situation in industrial park safety and environmental protection issues. According to Actor-network Theory and a systematic search, this study identifies the relevant subjects from selected 24 studies and clarifies the interactions made by these subjects. In sum, this study concludes two main modes of developing workplace sustainability in the park from multiple actors' perspectives: self-regulation of inner park subjects and the driving force of exterior park subjects.

Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port.

As Chi na's shipping industry continues to develop, ship emissions have become a significant source of pollutants. Consequently, it has become imperative to comprehend accurately the nature and attributes of ship pollutant emissions and understand their causation and effect as a crucial aspect of pollution control and legislation. This paper employs high-precision automatic identification system (AIS) dynamic and static data, along with pollutant emission parameters, to estimate the pollutant emissions from a ship's main engine, auxiliary engine, and boiler using a dynamic approach. Additionally, the study considers the sailing state and trajectory of the vessel and analyzes the characteristics of ship carbon emissions. Taking Tianjin Port as an example, this study conducts a multi-dimensional analysis of pollutant emissions to gain insight into the causation and effect of pollutants based on the collected big AIS data. The results show that the pollutant emissions in this region are mainly concentrated in the vicinity of Tianjin Port land port area, Dagusha Channel, and the Main Shipping Channel of Tianjin Xingang Fairway. Carbon emissions peak in September and are lower in June and December. Through accurate analysis of pollutant emission sources and emission characteristics in the region, this paper establishes the regular relationship between pollutant emissions and possible influencing factors and provides data support for China to formulate accurate pollutant emission reduction policies and regulate ship construction technology and carbon trading.

Uncovering the behavioral determinants behind private car purchase intention during the new normal of COVID-19: An empirical investigation in China.

Based on the Protection Motivation Theory (PMT), the Psychological Reactance Theory (PRT), and the Theory of Planned Behavior (TPB), we revealed the psychological impact factors of individuals' private car purchase intentions during the new normal of COVID-19. Structural equation modeling (SEM) and Bayesian network (BN) were used to analyzed the car purchase decision-making mechanism. A questionnaire survey was conducted to collect empirical data from April 20th to May 26th of 2020 in China. We investigated 645 participants and analyzed the data. The SEM results showed that conditional value, pro-car-purchasing attitude, and perceived behavioral control, health value, and cost factors have significant direct effects on car purchase intention. According to BN's prediction of purchase intention, the probability of high purchase intention grew by 47.6%, 97.3% and 163.0%, respectively, with perceived behavioral control, pro-car-purchasing attitude, and conditional value shifting from "low" to "medium" and "high". This study provided a new perspective for researchers to explore the purchase intention of cars during the epidemic. Meanwhile, we could provide a reference for the government and enterprises to develop measures related to the automobile market."

A Spatial-Temporal Causal Convolution Network Framework for Accurate and Fine-Grained PM2.5 Concentration Prediction.

Accurate and fine-grained prediction of PM2.5 concentration is of great significance for air quality control and human physical and mental health. Traditional approaches, such as time series, recurrent neural networks (RNNs) or graph convolutional networks (GCNs), cannot effectively integrate spatial-temporal and meteorological factors and manage dynamic edge relationships among scattered monitoring stations. In this paper, a spatial-temporal causal convolution network framework, ST-CCN-PM2.5, is proposed. Both the spatial effects of multi-source air pollutants and meteorological factors are considered via spatial attention mechanism. Time-dependent features in causal convolution networks are extracted by stacked dilated convolution and time attention. All the hyper-parameters in ST-CCN-PM2.5 are tuned by Bayesian optimization. Haikou air monitoring station data are employed with a series of baselines (AR, MA, ARMA, ANN, SVR, GRU, LSTM and ST-GCN). Final results include the following points: (1) For a single station, the RMSE, MAE and R2 values of ST-CCN-PM2.5 decreased by 27.05%, 10.38% and 3.56% on average, respectively. (2) For all stations, ST-CCN-PM2.5 achieve the best performance in win-tie-loss experiments. The numbers of winning stations are 68, 63, and 64 out of 95 stations in RMSE (MSE), MAE, and R2, respectively. In addition, the mean MSE, RMSE and MAE of ST-CCN-PM2.5 are 4.94, 2.17 and 1.31, respectively, and the R2 value is 0.92. (3) Shapley analysis shows wind speed is the most influencing factor in fine-grained PM2.5 concentration prediction. The effects of CO and temperature on PM2.5 prediction are moderately significant. Friedman test under different resampling further confirms the advantage of ST-CCN-PM2.5. The ST-CCN-PM2.5 provides a promising direction for fine-grained PM2.5 prediction.

Study on Influencing Factors of Micro and Small Enterprises' Work Safety Behavior in Chinese High-Risk Industries.

Due to the limited work safety resources and the poor awareness of work safety from business owners with absolute decision-making power, safety accidents frequently occur in Chinese micro and small enterprises (MSEs) in high-risk industries. This study identifies the influencing factors of work safety behavior from MSEs, government safety supervision departments, and work safety service agencies. Based on the theory of planned behavior (TPB), the mechanism model of work safety behavior is built from the aspects of behavior attitude, subjective norms, behavior control cognition, past behaviors, and risk awareness of the enterprise. Based on the interview with nearly 600 MSEs in the east of China over 6 months, the results show that the work safety awareness of the business owner determines the work safety lever of the enterprise, and the work safety behavior of MSEs is a passive restraint behavior. Our findings provide a new perspective on the formation of MSEs' work safety behavior in high-risk industries.

Impact analysis of behavior of front-line managers on employee safety behavior by integrating interpretive structural modeling and Bayesian network.

Employee safety behavior is a basic element of enterprise work safety. The results of accident investigations and risk assessments in enterprises indicate that management factors are some of the most important factors that affect employee safety behavior. The purpose of this study is to explore the relationship between the behavior of front-line managers (FLMs) and employee safety behavior by integrating a qualitative method, i.e., the interpretive structural model (ISM), and a quantitative method, i.e., the Bayesian network (BN). The results of the BN analysis showed that safety incentives and safety communication were the best predictors of safety participation, while safety supervision and safety control were the best predictors of safety compliance. Moreover, the results revealed that an instantaneous improvement of safety communication, safety incentives, safety supervision and safety guidance was the most effective joint measure to reach a high-level of safety behavior of employees in the workplace.

Linking Safety-Specific Leader Reward and Punishment Omission to Safety Compliance Behavior: The Role of Distributive Justice and Role Ambiguity.

Background: Although positive safety leadership has attracted increasingly academic and practical attention due to its critical effects on followers' safety compliance behavior, far fewer steps have been taken to study the safety impact of laissez-faire leadership. Objective: This study examines the relationships between safety-specific leader reward and punishment omission (laissez-faire leadership) and followers' safety compliance, and the mediations of safety-specific distributive justice and role ambiguity. Methods: On a two-wave online survey of 307 workers from high-risk enterprises in China, these relationships were tested by structural equations modeling and bootstrapping procedures. Results: Findings show that safety-specific leader reward omission was negatively associated with followers' safety compliance through the mediating effects of safety-specific distributive justice and role ambiguity. Safety-specific leader punishment omission was also negatively associated with followers' safety compliance through the mediating effect of safety-specific role ambiguity, while safety-specific distributive justice was an insignificant mediator. Originality: The study addresses and closes more gaps by explaining how two contextualized laissez-faire leadership measures relate to followers' safety behaviors, following the contextualization and matching principles between predictors, mediators and criteria, and by revealing two mechanisms behind the detrimental effects of laissez-faire leadership on safety outcomes.

Safety-Specific Passive-Avoidant Leadership and Safety Compliance among Chinese Steel Workers: The Moderating Role of Safety Moral Belief and Organizational Size.

Despite the documented relationship between active-approaching leadership behaviors and workplace safety, few studies have addressed whether and when passive-avoidant leadership affects safety behavior. This study examined the relationship between two types of safety-specific passive-avoidant leadership, i.e., safety-specific leader reward omission (SLRO) and safety-specific leader punishment omission (SLPO), and safety compliance, as well as the moderating effects of an individual difference (safety moral belief) and an organizational difference (organizational size) in these relationships. These predictions were tested on a sample of 704 steel workers in China. The results showed that, although both SLRO and SLPO are negatively related to safety compliance, SLPO demonstrated a greater effect than SLRO. Moreover, we found that steel workers with high levels of safety moral belief were more resistant to the negative effects of SLRO and SLPO on safety compliance. Although steel workers in large enterprises were more resistant to the negative effects of SLPO than those in small enterprises, the SLRO-compliance relationship is not contingent upon organizational size. The current study enriched the safety leadership literature by demonstrating the detrimental and relative effects of two types of safety-specific passive-avoidant leadership on safety compliance and by identifying two boundary conditions that can buffer these relationships among steel workers.

The effect of perceived organizational support for safety and organizational commitment on employee safety behavior: a meta-analysis.

Recently, the significance of organizational support and commitment in workplace safety has gained much recognition. The improvement of individual safety behavior needs more convincing and effective evidence. This study constructed a comprehensive theoretical model and used meta-analysis to examine the relationships between perceived organizational support for safety, organizational commitment and employee safety behavior. Support was found for the study's hypothesis that both perceived organizational support for safety and organizational commitment have a positive association with employee safety behavior, with the latter demonstrating the stronger relationship. However, organizational commitment was not mediated by perceived organizational support for safety and employee safety behavior. Results show that the safety behavior of employees in general industries and developed regions is more vulnerable to perceived organizational support for safety and organizational commitment than that in high-risk industries and developing regions. The implications of the findings and suggestions for further research are discussed.

Driving Mechanism Model for the Supply Chain Work Safety Management Behavior of Core Enterprises-An Exploratory Research Based on Grounded Theory.

Guiding core enterprises to participate in supply chain work safety governance is an innovative mode of work safety control, which has an important impact on improving the work safety level of small and medium-sized enterprises in the supply chain. Through in-depth interviews, the grounded theory is adopted to explore the driving factors of work safety management behaviors of core enterprise. It is found that the work safety management behavior of the core enterprise is driven by both internal and external factors. External driving factors are the main category of institutional pressure composed of regulatory pressure, normative pressure, and cognitive pressure. Internal driving factors are divided into the main category of behavioral awareness and the behavioral capability of the core enterprises. The behavioral awareness is composed of responsibility sense, problem cognition and behavioral effect perception. The behavioral capability is composed of safety management strength and safety coordination capability. Institutional pressure, behavioral awareness, and behavioral capability all influence the work safety management behavior of core enterprise in supply chain significantly, but with different ways and paths. On this basis, the driving mechanism model of the above three main categories on the work safety management behavior in core enterprise supply chain is explored. The research can provide targeted policy ideas and implementation paths for the government to formulate effective guiding policies to promote the work safety management behavior of core enterprise.

Allosteric Probe-Initiated Wash-Free Method for Sensitive Extracellular Vesicle Detection through Dual Cycle-Assisted CRISPR-Cas12a.

Extracellular vesicles (EVs) are emerging as promising biomarkers for cancer diagnosis and therapy. Recognizing low-abundance EVs from clinical samples in an easy-to-operate way is highly desired but remains a challenge. Herein, we established an allosteric probe-initiated dual cycle amplification-assisted CRISPR-Cas12a (AID-Cas) platform for sensitive detection of EVs in a wash-free way. In AID-Cas, the allosteric probe can specifically recognize and bind with target EVs and thus initiate the following dual-cycle amplification. Subsequently, the amplified products were transcribed to generate numerous single-stranded RNAs, which could work as crRNA to trigger the trans-cleavage of CRISPR-Cas12a. Consequently, the proposed approach achieved a good linear response to extracted EVs in a concentration range from 102 to 106 particles/µL. Because of its high sensitivity, together with its wash-free convenience, the proposed strategy could have promising clinical potentials for early diagnosis of cancers.

Aptamer-Cholesterol-Mediated Proximity Ligation Assay for Accurate Identification of Exosomes.

Accurate identification of exosomes plays an essential role in facilitating disease diagnosis and therapies. Herein, we proposed an Aptamer-cholesterol-mediated Proximity Ligation Assay (AcmPLA) for accurate identification of exosomes in a dual-probe strategy, one aptamer probe for recognition of exosomal innate surface protein CD63 and another cholesterol probe for biolipid layer targeting. By integrating a proximity ligation of probes bound with exosomal biomarkers for specific recognition and a rolling circle amplification (RCA) strategy for signal amplification, we have successfully developed an exosomes-surface approach that can perform "AND" logic analysis of dual biomarkers, which not only could be used for exosomes quantification, but also for exosomes tracing. Besides RCA-initiated signal amplification, CD9 antibody-labeled magnetic beads were used to capture exosomes for isolation and secondary signal enrichment. Our approach can achieve specific exosomes isolation and accurate identification and thus could be exploited for broad applications in biological science, biomedical engineering, and personalized medicine.

Rapid and sensitive exosome detection with CRISPR/Cas12a.

Numerous studies have shown that exosomes are closely related to the pathogenesis of various diseases, especially cancers. Therefore, a rapid and sensitive method for exosome detection will be of great importance for the diagnosis and prognosis of diseases. We report here a method for exosome detection based on the CD63 aptamer and clustered regular interspaced short palindromic repeats (CRISPR)/Cas12a system. This method consists mainly of exosomal membrane protein recognition based on the CD63 aptamer and signal amplification based on CRISPR/Cas12a. The CD63 aptamer, as an easily adaptable nucleic acid strand, is responsible for the conversion of the amounts of exosomes into nucleic acid detection, whereas CRISPR/Cas12a is responsible for highly specific nucleic acid signal amplification. The detection range of the method was determined as 3 × 103-6 × 107 particles per microliter. Additionally, we successfully applied this method to detect exosomes in clinical samples from both healthy individuals and patients with lung cancer, and the results were highly consistent with those obtained by nanoparticle tracking analysis. In general, this method provides a highly sensitive and specific method for the detection of exosomes and offers an avenue toward future exosome-based diagnosis of diseases.

Effects of organizational safety on employees' proactivity safety behaviors and occupational health and safety management systems in Chinese high-risk small-scale enterprises.

Based on the characteristics of small-scale enterprises, the improvement of occupational health and safety management systems (OHS MS) needs an effective intervention. This study proposed a structural equation model and examined the relationships of perceived organization support for safety (POSS), person-organization safety fit (POSF) and proactivity safety behaviors with safety management, safety procedures and safety hazards identification. Data were collected from 503 employees of 105 Chinese high-risk small-scale enterprises over 6 months. The results showed that both POSS and POSF were positively related to improvement in safety management, safety procedures and safety hazards identification through proactivity safety behaviors. Our findings provide a new perspective on organizational safety for improving OHS MS for small-scale enterprises and extend the application of proactivity safety behaviors.

Agent-Based Modeling of Employee Protection-Oriented Safety Proactivity Behaviors at Small Scale Enterprises.

Although the safety production level at small scale enterprises is important for business success, critical safety interactions among the enterprises, its employees, the public, and the government have not been explained well in the literature. To address this gap, a bottom-up method of agent-based modeling is applied here that includes these key stakeholders. The study illustrates how employee protection-oriented safety proactivity behaviors, including whistleblowing and public exposure, can impact the safety production level at small scale enterprises, which are also watched by the public and regulated by the government. The results confirm that protection-oriented safety proactivity behaviors have a significant impact on the safety production levels at small enterprises through the interactions among multiple agents. The model results are validated using an employee questionnaire. The recommendation is for employees to encourage protection-oriented safety proactivity behaviors to improve safety production levels and for the public and the government to provide additional safety support.

Retracted: Rapid and effective sample cleanup based on graphene oxide-encapsulated core-shell magnetic microspheres for determination of fifteen trace environmental phenols in seafood by liquid chromatography-tandem mass spectrometry.

This article has been retracted at the request of the Editor after the corresponding author pointed the Editor to comments from an anonymous reader. The article reports electron micrographs of different preparations while showing identical images as used in previous publications by the same authors. The particles in Fig. 4C (SEM image of Fe3O4@SiO2) are identical to each other and the corresponding author confirmed that these have been copy-pasted. In addition, these particles have previously been communicated as different substances in Fig. 1B from Pan et al., J. Mater. Chem. A, 2015,3, 23042-23052 (DOI: 10.1039/C5TA05840F) and Fig. 3F from Pan et al., Anal. Methods, 2017,9, 5281-5292 (DOI: 10.1039/C7AY01444A). Furthermore, the curves in Fig. 7, especially the baseline, shows a remarkable similarity to Fig. 8 from Pan et al., J. Mater. Chem. A, 2015,3, 23042-23052 (DOI: 10.1039/C5TA05840F) and Fig. 5F from Pan et al., J. Mater. Chem. A, 2014,2, 15345-15356 (DOI: 10.1039/c4ta02600d). The manipulation of images and data in this way is a serious offense to the integrity of the scientific community and casts doubts on all the data, and accordingly also the conclusions based on that data, in this publication. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process. This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal).

Study on the Influence of Government Intervention on the Occupational Health and Safety (OHS) Services of Small- and Medium-Sized Enterprises (SMEs).

The OHS services of SMEs are still in their start-up stage in China. As such, there is an absence of mature market norms, which in turn makes it difficult to guarantee the quality of OHS services. The government, as the "night watchman" of the market, is supposed to not only involve itself in the regulation of OHS service quality, but also introduce and implement proper regulatory strategies. This paper employs a computational experiment approach to construct an experimental platform based on multiagent interactions. By simulating the OHS service transaction activities of SMEs, this paper takes the perspective of dynamic evolution. From this perspective, we probe into the optimal regulatory strategy covering the positive influence of government punishment, policy supports, and service quality ratings of the OHS services of SMEs. These strategies should be built on the foundation of proper punishment standard and intensity, proper support standard and intensity, and quality rating information disclosure.