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The study aims to investigate the relationship between transformational, transactional leadership and employee retention with the mediating effect of employee engagement.

Using judgemental sampling, data were collected from 650 employees serving at different levels in the pharmaceutical industry of Bangladesh. Structural equation modeling was employed to test the hypothesized relationships using AMOS.

The study found that transformational and transactional leadership significantly impact employee retention. The direct effects of transformational leadership (TFL) on employee engagement were found to be significant, while transactional leadership (TSL) has no significant direct influence on employee engagement. The output of the mediation analysis revealed that employee engagement significantly mediates the relationship between TFL and employee retention, whereas it showed an insignificant relationship between TSL and employee retention.

Based on the findings and the literature support, it can be postulated that an appropriate leadership style, especially TFL, that drives employee engagement can influence employees to stay with the organization longer. The study recommends that managers and leaders comprehend the importance of leadership and its appropriateness to retain valued employees by ensuring high workplace engagement.

The study would provide a unique insight into TFL and TSL practices and their impact on the pharmaceutical industry’s employee retention. This study also extends the research on employee engagement as a mediator between TFL and TSL and employee retention.

Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

This paper aims to present a novel numerical technique for solving the incompressible multiphase mixture model.

The multiphase mixture model contains a set of momentum and continuity equations for the mixture phase, a second phase continuity equation and the algebraic equation for the relative velocity. For solving continuity equation for the second phase and advection term of momentum, an improved approach fine grid advection-multiphase mixture flow (FGA-MMF) is developed. In the FGA-MMF method, the continuity equation for the second phase is solved with higher-order schemes in a two times finer grid. To solve the advection term of the momentum equation, the advection fluxes of the volume fraction in the continuity equation for the second phase are used.

This approach has been used in various tests to simulate unsteady flow problems. Comparison between numerical results and experimental data demonstrates a satisfactory performance. Numerical examples show that this approach increases the accuracy and stability of the solution and decreases non-monotonic results.

The solver for the multi-phase mixture model can only be adopted to solve the incompressible fluid flow.

The paper developed an innovative solution (FGA-MMF) to find multi-phase flow field value in the multi-phase mixture model. Advantages of the FGA-MMF technique are the ability to accurately determine the phases interpenetrating, decreasing the numerical diffusion of the interface and preventing instability and non-monotonicity in solution of large density variation problems.

The increasing prevalence of coronavirus disease (COVID-19) is a global crisis that leads to physical and psychological outcomes for health-care workers, so this study aims to investigate the mental health outcomes (including general health, generalized anxiety disorder and posttraumatic stress disorder) in health-care workers in Rafsanjan, Iran.

By using convenience sampling, this cross-sectional study was conducted on 332 health-care workers working in public hospitals in southern Iran. Data collection lasted from March to April 2020. General Health Questionnaire (GHQ-28), Generalized Anxiety Disorder 7-item (GAD-7) and Impact of Event Scale were used to collect data. The data were then analyzed by using SPSS 25 and descriptive and inferential statistics (chi-square and multivariate logistic regression).

In total 45.5% of the participants had psychological disorder according to GHQ. In addition, 25.3% of the participants had GAD and 31.6% had posttraumatic stress disorder (PTSD). The results using multivariate logistic regression showed that only income was significantly associated with psychological disorders (95% confidence interval for odds ratio: 1.32–6.45, P = 0.008).

According to the results, the incidence of GAD and PTSD was high among health-care workers. Therefore, it is recommended that the psychological skills of health-care workers be strengthened through counseling and training programs.

This paper provides a novel analysis of mental health in health-care workers in Iran.

This paper aims to investigate the relationship between corporate governance (CG) and corporate social responsibility (CSR) disclosure in a sample of 64 companies listed on the Tehran Stock Exchange.

This study opts for a descriptive-correlational method. To measure the extent of CSR disclosure and CG variables, companies’ annual reports and websites during 2014-2015 are content analyzed by applying a 64-item checklist. Boards’ size, age, tenure and independence, CEO duality, audit committee (AC) composition and ownership concentration are considered as CG variables. To ascertain the CG–CSR disclosure relationship, multivariate linear regression analysis is incorporated.

Based on the results, audit committee composition, board tenure and ownership concentration positively influence CSR disclosure level with ownership concentration as the most influential variable, that is, in companies with majority shareholders ownership, managers tend to disclose more CSR information.

Only annual reports and company websites are analyzed. Researchers are encouraged to apply other methods such as interview and to consider other variables, such as board diversity, proportion of female members and the extent of shareholders activities, to measure CG.

This paper provides implications at the policy level to identify governance mechanisms to increase CSR awareness of heavy-pollution industries in developing countries.

Studies rarely examined CSR reporting in Iran, particularly among heavy-pollution companies. Besides, the paper highlights the role of majority shareholders and non-executive AC members in CSR disclosure.

The readymade garments (RMG) industry acts as one of the foremost vital catalysts for financial as well as social advancement of Bangladesh. Due to the harsh impact of COVID-19, RMG sector has been confronting a never-seen-before phenomenon. Since the supply chain has seriously been influenced, concern raises among industry and policymakers on how to support against disturbances resulting from pandemics. Accordingly, this research aims to explore the vulnerability and capability factors of RMG sector in Bangladesh, their relationship and how these variables affect supply chain resilience.

A qualitative research design has been employed. In the first stage, content analysis has been performed. Since COVID-19 is a new experience, newspapers were the source to become acquainted with the vulnerability and capability factors following the guidelines provided by Pettit et al. (2010). In the second stage, in-depth interviews with key informants were conducted to investigate the relationship among the variables and how these factors may influence supply chain resilience.

This study identifies fourteen capability factors and their sub-factors of RMG industry in Bangladesh in order to improve the resilience capacity against the vulnerabilities in the context of COVID-19 pandemic.

This research is based on the setting of particular industry in Bangladesh, where respondents are immersed in a unique culture. Special care is required to generalize the results to other segments and phenomena.

The framework recognizes the balanced and unbalanced strength with the capability's components and find the relation between capabilities and vulnerabilities within the fashion industry. By creating the resilience network with the four conceivable positions, companies can find themselves with their capability's components and natural vulnerabilities.

This study investigates diverse components of capability figure against vulnerabilities to create the supply chain resilience. This paper, moreover, develops with four conceivable positions with their capabilities against existing vulnerabilities which brings timely contribution considering the context of COVID-19.

The present research is trying to construct the network of relationships between different department of an organization during the design and development of car engine. Analyzing the structure of the network, finding the patterns of collaborations, and determining the important departments are the main purposes of the present research.

Improving relationships during a project life is an effective way to enhance employee performance in project-oriented organizations. This paper examines the collaborative relationships between internal project stakeholders through social network analysis (SNA) in a project for the design and development of car engine. In the first step of the research, the network of internal stakeholders was studied based on collaboration in the common activities performed by the resources. Then, the network of correspondences between internal stakeholders was studied. Finally, the two networks were integrated into a single network.

In the integrated network, the “fuel and combustion department” had the largest degree centrality (i.e. highest collaboration with others). The “integration department” was found to have the highest closeness centrality (i.e. more rapid access to other nodes). Furthermore, the “procurement department” had the highest betweenness centrality (i.e. the most strategic department). Our results revealed the potential capabilities of SNA method for the project management in the vehicle industry.

The obtained results of the present research show us the value of applying SNA methods and concepts to analyze the inter-organizational network of the Project Stakeholders relationship.

Repetitive transcranial magnetic stimulation (rTMS) is a well-established treatment with efficacy for several psychiatric disorders and has yielded promising yet mixed data showing reductions in craving for substance use. Patients with substance use disorders and comorbid depression may encounter obstacles to receiving rTMS in outpatient settings for treatment of depression. In turn, implementation of rTMS in residential substance use programs would greatly benefit those with comorbid treatment resistant depression. This paper aims to provide recommendations for implementing rTMS within residential substance use treatment centers.

Using PubMed, the authors conducted a narrative review of manuscripts using various combinations of the following search terms: rTMS, depression, substance use and substance use disorder. The authors read manuscripts for their methodology, outcomes and adverse events to synthesize their results, which correspond to their recommendations for patient selection, safely implementing rTMS in residential substance use facilities and optimal rTMS protocols to start with.

Advantages of this approach include increased compliance, monitoring and access to care. Recommendations to safely incorporate rTMS in residential substance use disorder treatment centers revolve around selection of patients eligible for rTMS, allowing for sufficient time to elapse prior to commencing rTMS, monitoring for signs of recent substance use or withdrawal and using rTMS protocols compatible with the therapeutic programming of a treatment center.

This paper details the challenges and benefits of implementing rTMS for patients with dual diagnosis and provides recommendations to safely do so. To the best of the authors’ knowledge, this is a novel and unpublished endeavor.

Eyewitness testimony can determine the outcome of criminal investigations. The cognitive interview (CI) has been widely used to collect informative and accurate accounts. However, face-to-face interviews have been restricted during the current pandemic, raising the need for using video-conferencing. The authors tested whether virtual interviews could produce elaborate accounts from eyewitnesses and if the CI superiority effect against a structured interview (SI) could be fully replicated online.

The authors used a 2 × 2 factorial design with interview condition (CI vs SI) and environment (face-to-face vs virtual) manipulated between-subjects. A total of 88 participants were randomly assigned to one of the four conditions. Participants watched a mock robbery and were interviewed 48 h later using either the SI or the CI. Both interviews contained the same structure and interview phases but only the CI included its key cognitive mnemonics/ instructions. Both sessions were either face-to-face or online.

Participants interviewed with the CI recalled more information than participants interviewed with the SI, regardless of the interview environment. Both environments produced a comparable amount of recall. Report accuracy was high for all groups.

This can be crucial to inform police practices and research in this field by suggesting investigative interviews can be conducted virtually in situations such as the current pandemic or when time and resources do not allow for face-to-face interviewing.

To the best of the authors’ knowledge, this is the first study showing that the CI superiority effect can be replicated online and that a fully remote CI can produce elaborate accounts.

The purpose of this paper is to develop a system dynamics approach based on Susceptible, Exposed, Infected, Recovered (SEIR) model to investigate the coronavirus pandemic and the impact of therapeutic and preventive interventions on epidemic disaster.

To model the behavior of COVID-19 disease, a system dynamics model is developed in this paper based on SEIR model. In the proposed model, the impact of people's behavior, contact reduction, isolation of the sick people as well as public quarantine on the spread of diseases is analyzed. In this model, data collected by the Iran Ministry of Health have been used for modeling and verification of the results.

The results show that besides the intervening policies, early application of them is also of utmost priority and makes a significant difference in the result of the system. Also, if the number of patients with extreme conditions passes available hospital intensive care capacity, the death rate increases dramatically. Intervening policies play an important role in reducing the rate of infection, death and consequently control of pandemic. Also, results show that if proposed policies do not work before the violation of the hospital capacity, the best policy is to increase the hospital’s capacity by adding appropriate equipment.

The authors also had some limitations in the study including the lack of access to precise data regarding the epidemic of coronavirus, as well as accurate statistics of death rate and cases in the onset of the virus due to the lack of diagnostic kits in Iran. These parameters are still part of the problem and can negatively influence the effectiveness of intervening policies introduced in this paper.

The contribution of this paper includes the development of SEIR model by adding more policymaking details and considering the constraint of the hospital and public health capacity in the rate of coronavirus infection and death within a system dynamics modeling framework.