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Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

The existing literature has been mainly focused on local problems but without an overall framework for studying the top-level planning of intelligent construction from a systematic perspective. The purpose of this paper is to fill this gap.

This research adopts a deductive research approach.

This research proposes a reference architecture and related business scenario framework for intelligent construction based on the existing theory and industrial practice.

The main contribution of this research is to provide a useful reference to the Chinese government and industry for formulating digital transformation strategies, as well as suggests meaningful future research directions in the construction industry.

This paper aims to propose a novel control scheme and offer a control parameter optimizer to achieve better automatic carrier landing. Carrier landing is a challenging work because of the severe sea conditions, high demand for accuracy and non-linearity and maneuvering coupling of the aircraft. Consequently, the automatic carrier landing system raises the need for a control scheme that combines high robustness, rapidity and accuracy. In addition, to exploit the capability of the proposed control scheme and alleviate the difficulty of manual parameter tuning, a control parameter optimizer is constructed.

A novel reference model is constructed by considering the desired state and the actual state as constrained generalized relative motion, which works as a virtual terminal spring-damper system. An improved particle swarm optimization algorithm with dynamic boundary adjustment and Pareto set analysis is introduced to optimize the control parameters.

The control parameter optimizer makes it efficient and effective to obtain well-tuned control parameters. Furthermore, the proposed control scheme with the optimized parameters can achieve safe carrier landings under various severe sea conditions.

The proposed control scheme shows stronger robustness, accuracy and rapidity than sliding-mode control and Proportion-integration-differentiation (PID). Also, the small number and efficiency of control parameters make this paper realize the first simultaneous optimization of all control parameters in the field of flight control.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Different leadership styles are used to make innovations in organizations. So, a sound system of social exchanges has always been a need in this dynamic and technological world to challenge organizational problems. Drawing on the social exchange theory, this study aims to empirically investigate the mediating relationship of a set of social exchanges, e.g. leader-member exchange (L.M.X.), knowledge sharing behavior (K.S.B.) and voice behavior (V.B.), between transformational leadership (T.L) and innovative work behavior (I.W.B). Particularly, it explores the best social exchange behavior between T.L and I.W.B that plays a highly constructive role in the innovativeness of the hospitality industry in Pakistan.

The study targeted 403 frontline employees from hotels situated near Swat Valley, Pakistan. The study used a quantitative approach by using a convenient sampling technique. Structural equation modeling was run by using Smart partial least square 3.3.3 to test the proposed model.

The research supported that T.L significantly influenced I.W.B via a L.M.X., K.S.B. and V.B. T.L did not directly and significantly influence I.W.B so, there were full mediations between T.L and I.W.B. Specifically, knowledge-sharing behavior played a highly constructive role in innovativeness.

The study targeted frontline employees from one place, Swat valley; however, data collection from different tourist places may generalize the results based on social exchanges and innovative behavior. A dyadic interaction between top-level and middle-level management may closely trace the innovative ideas among the employees.

The study found knowledge sharing to be a highly effective mechanism that supports employee innovation more than a L.M.X. and V.B. As a result, the managers should establish a sound system of knowledge sharing, which means a knowledge economy so that employees innovativeness can be boosted and promoted.

The present study was the first study in the hotel industry of Pakistan that reveals a highly effective mediating mechanism: K.S.B., which exists with T.L to increase workers’ innovativeness highly.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。

This study aims to examine the effect of supervisor developmental feedback on employee silence behaviour by developing a moderated mediation model. The model focuses on the mediating role of role breadth self-efficacy and high activated positive affect underpinning the relationship between supervisor developmental feedback and employee silence behaviour, and the moderating role of interdependent self-construal.

The two-wave survey was conducted among 265 employees. Structural equation modelling was conducted to test the mediation and moderation mediation hypotheses.

Results indicated that high activated positive affect mediated the negative relationship between supervisor developmental feedback and employee silence behaviour. The authors also found that interdependent self-construal moderated the relationship between supervisor developmental feedback and role breadth self-efficacy, as well as the indirect effect of supervisor developmental feedback on employee silence behaviour via role breadth self-efficacy.

This empirical study provides preliminary evidence of the mediating role of breadth self-efficacy and high activated positive affect in the negative relationship between supervisor developmental feedback and employee silence behaviour. The moderated mediation results further show that the mediation of role breadth self-efficacy between supervisor developmental feedback is contingent on individual interdependent self-construal, such that the mediation effect is significant among individuals with high interdependent self-construal, but the mediation effect of high activated positive effect is independent of individual interdependent self-construal. The findings further extend boundary conditions (interdependent self-construal) that may constrain the effect of supervisor developmental feedback on role breadth self-efficacy and high activated positive affect. The research makes considerable contributions to the cognitive-affective personality system theory by specifying the cognitive and affective mechanisms between supervisor developmental feedback and employee silence behaviour, as well as the boundary conditions.

This paper aims to explore the quantile-specific short- and long-term effects of economic policy uncertainty (EPU) on the efficiency of the green bond market.

This study examines the long-term cointegration relationship and the short-term fluctuation relationship of EPU, WTI crude oil price (WTI) and European Union Allowances price (EUA) with the green bond market efficiency (GBE) using the quantile autoregressive distributed lag method. Additionally, the authors analyze the differences before and after the Covid-19 pandemic.

EPU has a significant positive impact on the GBE before the outbreak. However, during the crisis period, the impact of EPU and WTI was greatly weakened, whereas the impact of EUA was strengthened.

This paper demonstrates the dynamics of GBE and its influencing factors under different periods. The findings provide insights for market participants and policymakers to gain a clearer understanding of the green bond market.

This paper extends the study of green bonds by quantifying the GBE and elucidating the nonlinear relationship between efficiency and independent variables at different quantiles over different periods.

This paper aims to investigate the relationship between emotional labor and workplace violence based on the social exchange theory. Drawing on the social exchange theory, this paper aims to investigate the relationship between emotional labor and workplace violence. Specifically, the authors take a relational approach by introducing positive patient treatment as the mediator. The moderating role of organizational support in the relationship between emotional labor and workplace violence is also considered.

The data of this study encompasses 536 nurses from 10 university hospitals in Turkey. Hierarchical multiple regression analysis was conducted to test the proposed model.

The findings of this study support the negative effect of emotional labor on workplace violence and the mediating effect of patient-positive treatment. Moreover, when organizational support is low, the relationship between emotional labor and workplace violence is strong. In contrast, the effect is weak when organizational support is high.

The findings of this study suggest that health-care administrators should offer more training to nurses to help them manage their emotions while interacting with their patients. This leads to positive interpersonal relationships, which, in turn, lowers workplace violence. Moreover, health-care administrators should pay more attention to the buffering role of perceived organizational support for those subordinates with low emotional labor and higher workplace violence.

The study provides new insights into emotional labor’s influence on workplace violence and the moderating role of organizational support in the link between emotional labor and workplace violence. The paper also offers practical assistance to nurses in the health-care industry interested in building positive patient treatment and trust with their patients and minimizing workplace violence.

Multi-well hydrofracturing is an important technology to create new fractures and expand existing fractures to increase reservoir permeability. The propagation morphology of the fracture network is affected by the disturbance between the fractures initiation sequences and spacings between adjacent wells. However, it remains unclear how well spacing and initiation sequences lead to fracture propagation, deflection and connection.

In this study, the thermal-hydro-mechanical coupling effect in the hydrofracturing process was considered, to establish a finite element-discrete element model of multistage hydrofracturing in a horizontal well. Using typical cases, the unstable propagation of hydraulic fractures in multiple horizontal wells was investigated under varying well spacing and initiation sequences. Combined with the shear stress shadow caused by in situ stress disturbed by fracture tip propagation, the quantitative indexes of fracture propagation such as length, volume, displacement vector, deflection and unstable propagation behavior of the hydrofracturing fracture network were analyzed.

The results show that the shear stress disturbance caused by multiple hydraulic fractures is a significant factor in multi-well hydrofracturing. Reducing the spacing between multiple wells increases the stress shadow area and aggravates the mutual disturbance and deflection between the fractures. The quantitative analysis results show that a decrease of well spacing reduces the total length of hydraulic fractures but increases the total volume of the fracture; compared with sequential and simultaneous fracturing, alternate fracturing can effectively reduce stress shadow area, alleviate fracture disturbance and generate larger fracture propagation length and volume.

The numerical models and results of the unstable propagation and stress evolution of the hydraulic fracture network under thermal-hydro-mechanical coupling obtained in this study can provide useful guidance for the evaluation and design of rock mass fracture networks in deep unconventional oil and gas reservoirs.