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In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

Personal influence is one of the most powerful strategies to influence publics’ behaviours. Yet, there is scant attention on how personal influence is leveraged for different public relations purposes in different cultural contexts. This study empirically investigates the presence and use of personal influence among Italian public relations professionals.

A survey was conducted through a self-administrated, web-based questionnaire and was developed from earlier studies investigating personal influence in public relations literature. Survey participants included public relations professionals across public, non-profit and private sectors.

The findings empirically show the presence and regular use of personal influence by professionals from all sectors to cultivate interpersonal relationships. Personal influence is considered a personal resource and used to leverage own influencing power. The findings also document four major manifestations of personal influence, which were named: relational closeness strategy, engagement strategy, expertise strategy and added value strategy.

This study enhances our understanding of personal influence in a specific cultural context and offers strategic insights for international professionals seeking to leverage influence in the socio-political environment of Italy. It also offers elements to improve public relations education and training.

The study offers some preliminary understandings of how Italian professionals leverage their personal influence in their daily public relations activities contributing with empirical evidence to the body of knowledge in public relations.

This ethnographic revisit of a general hospital aims to critically explore and describe the mechanisms of corporate culture change and how institutional excellence is facilitated and constrained by everyday management practices between 1996/1997 and 2014/2015.

A five-month field study of day-to-day life in the hospital's nursing division was conducted by means of an ethnographic revisit, using participant-observation, semi-structured interviews, free conversations and documentary material.

Using labour process analysis with ethnographic data from a general hospital, the corporate culture is represented as faceted, complex and sophisticated, lending little support to the managerial claims that if corporate objectives are realised, they are achieved through some combination of shared values, beliefs and managerial practices. The findings tend to support the critical view in labour process writing that modern managerial initiatives lead to tightened corporate control, advanced employee subjection and extensive effort intensification. The findings demonstrate the way in which the nursing employees enthusiastically embrace many aspects of the managerial message and yet, at the same time, still remain suspicious and distance themselves from it through misbehaviour and adaptation, and, in some cases, use the rhetoric against management for their own ends.

What are the implications for clinical and managerial practitioners? The recommendations are to (1) develop managerial practitioners who are capable of managing change combined with the professional autonomy of clinical practitioners, (2) take care to practise what you preach in clinical and managerial reality, as commitment, consent, compliance and difference of opinion are signs of a healthy corporate culture and (3) consider the implications between social structures and human actions with different work behaviours on different levels involved.

This ethnographic revisit considers data from a labour process analysis of corporate culture change in a general hospital and revisits the ways in which contradictory expectations and pressures are experienced by nursing employees and management practitioners spread 17 years apart.

The purpose of this paper is to apply the conjugate gradient (CG) method, together with the adjoint operator (AO) to the pulsating heat pipe problem, including some quite interesting experimental results. The CG method, together with the AO, was able to estimate the unknown functions more efficiently than the other techniques presented in this paper. The estimation of local heat transfer coefficients, rather than the global ones, in pulsating heat pipes is a relatively new subject and presenting a robust, efficient and self-regularized inverse tool to estimate it, supported also by some experimental results, is the main purpose of this paper. To also increase the visibility and the general use of the paper to the heat transfer community, the authors include, as supplemental material, all numerical and experimental data used in this paper.

The approach was established on the solution of the inverse heat conduction problem in the wall by using as starting data the temperature measurements on the outer surface. The procedure is based on the CG method with AO. The here proposed approach was first verified adopting synthetic data and then it was validated with real cases regarding pulsating heat pipes.

An original fast methodology to estimate local convective heat flux is proposed. The procedure has been validated both numerically and experimentally. The procedure has been compared to other classical methods presenting some peculiar benefits.

The approach is suitable for pulsating heat pipes performance evaluation because these devices present a local heat flux distribution characterized by an important variation both in time and in space as a result of the complex flow patterns that are generated in this type of devices.

The procedure here proposed shows these benefits: it affords a general model of the heat conduction problem that is effortlessly customized for the particular case, it can be applied also to large datasets and it presents reduced computational expense.

This study aimed to estimate the economic benefits of PM2.5 emission abatement by Red Pine, Pinus Koraiensis and Quercus, using a metering model analyzing the amount of PM2.5 absorption in Korea.

To estimate the economic effects of PM2.5 adsorptions by trees, the frequency of hospital visits resulting from respiratory and circulatory diseases was estimated using a Probit model based on the data from National Health and Nutrition Survey.

The results show that Quercus and Pinus Koraiensis absorb and eliminate the largest amount of PM2.5. Reducing 1 ton of PM2.5 emission through the planting of trees leads to lower incidences of respiratory and circulatory diseases equivalent to the amount of 95 million won. When the trees planted are 2-year-old Red Pine, Pinus Koraiensis and Quercus, the resulting economic benefits of the PM2.5 abatement would amount to 481 million won, 173 million won and 1,027 million won, respectively. If the trees are 80 years old, the economic benefits are estimated to be 73 billion won for Red Pine, 103 billion won for Pinus Koraiensis and 38 billion won for Quercus.

One limitation of this study is that the weight of PM2.5 adsorbed by each leaf area entirely depended on the experimental results from a prior study and the values are likely to be different from those actually absorbed in natural surroundings. In addition, because of the lack of data from a domestic survey on the surface of leaf area or the reload flow rate of PM2.5, this study referred to data from foreign research. Unfortunately, this specific data may not reflect climatic and terrain characteristics specific to the target country. We used the annual wind speed to calculate the reload flow rate and elimination volume; however, the figures could be more accurate with hourly or daily climate variations. When estimating the health benefits of changes in PM2.5 emissions on respiratory and circulatory diseases, more segmented access to patients' hospital visits and hospital admissions are desirable. Finally, the study focused on the three major tree species of Korea, however, a more detailed study of PM2.5 reduction by various tree types is needed in the future.

This paper quantitatively assessed the amount of PM2.5 adsorption by each of the three tree species. Then, the economic benefits were calculated in terms of how much money would be saved on hospital visits thanks to the reduced PM2.5 levels and lower incidences of respiratory and circulatory system diseases. The net contribution of this study was to prove the trees' function of reducing PM2.5 as it relates to human health. We focused on the most common trees in Korea and compared them to provide new information on the species.

In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study.

It can be seen that support vector machine (SVM) is used with particle swarm optimization (PSO) where PSO is used as a fast and accurate classification to search the problem-solving space and finally the results are compared with the neural network performance.

Based on the result, the authors can say that both new models are trustworthy in 6 days, however, SVM-PSO is better than basic research. The hit rate of SVM-PSO is 77.5%, but the hit rate of neural networks (basic research) is 74.2.

In this research, two approaches (raw-based and signal-based) have been developed to generate input data for the model: raw-based and signal-based. For comparison, the hit rate is considered the percentage of correct predictions for 16 days.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

The media has even been very critical of some East Asian countries’ use of digital contact-tracing to control Covid-19. For example, South Korea has been criticised for its use of privacy-infringing digital contact-tracing. However, whether their type of digital contact-tracing was unnecessarily harmful to the human rights of Korean citizens is open for debate. The purpose of this paper is to examine this criticism to see if Korea’s digital contact-tracing is ethically justifiable.

This paper will evaluate Korea’s digital contact-tracing through the lens of the four human rights principles to determine if their response is ethically justifiable. These four principles were originally outlined in the European Court of Human Rights, namely, necessary, proportional, scientifically valid and time-bounded (European Court of Human Rights 1950).

The paper will propose that while the use of Korea’s digital contact-tracing was scientifically valid and proportionate (albeit, in need for improvements), it meets the necessity requirement, but is too vague to meet the time-boundedness requirement.

The Covid-19 pandemic has proven to be one of the worst threats to human health and the global economy in the past century. There have been many different strategies to tackle the pandemic, from somewhat laissez-faire approaches, herd immunity, to strict draconian measures. Analysis of the approaches taken in the response to the pandemic is of high scientific value and this paper is one of the first to critically engage with one of these methods – digital contact-tracing in South Korea.

Building on conservation of resources theory and unfolding theory of turnover, this paper aims to propose a model of the effects of despotic leadership on employees’ job satisfaction and turnover intention in the hospitality industry. In this model, the authors theorize psychological distress to play an intervening role among the aforesaid linkages.

The data were collected in three-waves from 212 employees working in Palestinian restaurants. A covariance-based matrix in structural equation modeling was used to verify the proposed linkages in the study. A marker variable was used to control the common method bias.

The results showed that despotic leadership has a direct negative effect on job satisfaction and a positive indirect effect on turnover intentions. Besides, psychological distress showed to play significant mediating effects among the aforementioned relationships.

This study gives insights to the hospitality industry on how despotic leadership can be destructive and lead to negative consequences.

This study is unique, as it is the first study conducted on despotic leadership in a hospitality setting. The study responded to scholarly calls made to enrich the literature pertaining to despotic leadership and its outcomes.

There is a lack of clarity about what constitutes Science, Technology, Engineering, Arts and Mathematics (STEAM) education and what the arts contribute. In this paper the authors discuss a distinct model, theorised from a five-year study of a particular, innovative STEAM education project (The Imagineerium), and developed by the researchers through working with primary school teachers in England within a second project (Teach-Make). The paper examines how teachers implemented this model, the Trowsdale art-making model for education (the TAME), and reflected on its value and positive impact on their planning and pedagogy.

The paper draws on two studies: firstly, a five-year, mixed methods, participative study of The Imagineerium and secondly a participative and collaborative qualitative study of Teach-Make.

Study of The Imagineerium showed strong positive educational outcomes for pupils and an appetite from teachers to translate the approach to the classroom. The Teach-Make project showed that with a clear curriculum model (the TAME) and professional development to improve teachers' planning and active pedagogical skills, they could design and deliver “imagineerium-like” schemes of work in their classrooms. Teachers reported a positive impact on both their own approach to supporting learning, as well as pupil progression and enjoyment.

The paper argues that the TAME, a consolidation of research evidence from The Imagineerium and developed through Teach-Make, offers both a distinctive and effective model for STEAM and broader education, one that is accessible to, valued by and manageable for teachers.