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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 To the best of the authors’ knowledge, this is a novel and unpublished endeavor.

Hoping to uncover the physical principles of the vibration of the functionally graded material (FGM) microplate, by which the authors can make contributions to the design and manufacturing process in factories like micro-electro-mechanical system (MEMS) and other industries.

The authors design a method by establishing a reasonable mathematical model of the physical microplate composed of a porous FGM.

The authors discover that the porosity, the distributions of porosity, the power law of the FGM and the length-to-thickness ratio all affect the natural frequency of the vibration of the microplate, but in different ways.

Originally proposed a model of the micro FGM plate considering the different distributions of the porosity and scale effect and analyzed the vibration frequency of it.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

Drawing on the conservation of resources theory, this study aims to identify the mediating effects of depersonalization and resilience on the relationship between customer incivility and organizational citizenship behavior (OCB). It further posits that these indirect effects vary depending on the caring climate and achievement orientation.

A field survey among 622 service employees (Study 1) and a three-wave field survey of 315 service employees and their managers (Study 2) from various service organizations were conducted.

This study confirms that depersonalization operates as a negative mediator in the relationship between customer incivility and OCB. Simultaneously, resilience emerges as a positive mediator, underscoring the contrasting pathways through which customer incivility affects OCB. Furthermore, a caring climate plays a pivotal role in mitigating the detrimental impact of depersonalization on OCB and weakening the positive impact of resilience on OCB. Additionally, this study identifies achievement orientation as a significant moderator between customer incivility and resilience.

This study advances theoretical foundations by investigating depersonalization and resilience as critical mediators in the intricate relationship between customer incivility and OCB. It goes beyond the conventional understanding of customer incivility’s impact by shedding light on the dual roles of a caring climate, demonstrating its potential to alleviate both positive and negative consequences of customer incivility. Moreover, its identification of achievement orientation as a moderator adds a novel dimension to the discourse, emphasizing the need for tailored strategies to harness employee resilience in the face of customer incivility.

The purpose of this paper is to assess the combined impact of the Industry 4.0 blockchain and industrial internet of things technology (IIoT) technologies on the development of supply chain linkages associated with power, benefits and risk reduction and the ultimate impact of the linkages on supply chain performance.

A structural model with blockchain and IIoT as antecedents to the supply chain power, benefits and risk reduction linkages and the linkages as antecedent to supply chain performance is theorized. Data collected from 303 US manufacturing managers are analyzed using a covariance-based structural equation modeling (CB/SEM) methodology.

The CB/SEM results indicate that blockchain technology does not directly impact implementation of the linkages. Rather, implementation of blockchain technology supports implementation of IIoT technology, which strengthens supply chain linkages, thereby improving supply chain performance.

To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence that Industry 4.0 technologies such as blockchain and IIoT strengthen linkages among supply chain partners related to power, benefits and risk reduction and that those stronger linkages lead to improved supply chain performance. It should be noted that this study is based on data from managers representing only one sector (manufacturing) and one country (USA). Replication based on data from other sectors and countries is needed to support generalization of the results.

Practitioners are provided with empirical evidence that the implementation of Industry 4.0 technologies such as blockchain and IIoT support supply chain management. These technologies facilitate data and information sharing among supply chain partners, enabling the integration and coordination of business processes throughout the entire supply chain.

The ultimate customers of supply chains benefit when supply chain partners work together efficiently and effectively. The implementation of blockchain and IIoT digital technologies lead to improve linkages among supply chain partners driving improvements in both efficiency and effectiveness, thus benefiting customers and society.

Industry 4.0 technologies are relatively new with the promise of improved supply chain performance. The efficacy of Industry 4.0 technologies as mechanisms to enhance information sharing is demonstrated based on the results of this study.

This study aims to investigate the association between board diversity and systematic risk. The theoretical framework used in this study is based on agency and resource dependency theories.

Using a panel data set of 788 firms listed in the Morgan Stanley Capital International (MSCI) Emerging Markets index from 2015 to 2020, the authors apply Panel-Corrected Standard Error estimation method to test the three proposed hypotheses and the two-stage least squares method is adopted for the endogenous test.

The results suggest that board-specific skills diversity (BSSD) and board independence (BIND) have a negative impact on systematic risk. On the other hand, board gender diversity does not affect systematic risk. The findings reinforce the relevance of board diversity for reducing systematic risk and offer valuable insights for policymakers and investors, suggesting that the presence of directors with specific skills and independent directors could reduce firms’ systematic risk.

The study extends the scope of agency and resource dependency theories by suggesting that the BSSD and BIND reduce agency costs and bring critical resources to the firm’s survival.

The findings support policymakers and managers in reducing systematic risk. In addition, the results demonstrate the importance of policies that encourage board diversity and BIND.

The study demonstrates how companies can reduce systematic risk through board diversity and BIND.

To the best of our knowledge, this is the first study to investigate the association between board diversity and systematic risk only in emerging markets.

This purpose of this study is to explore the impact of global trend of economic integration and interconnectedness which has drawn the attention of world economies and their implications on trade inflow. This trajectory has its impact, either positive/negative, on key macroeconomic indicators, to say the least on environmental sustainability, especially emerging economies. To this end, the need to explore the connection between foreign direct investment (FDI) inflow and energy consumption amidst the wave of economic globalisation is timely and pertinent for the case of Turkey.

This study seeks to explore the interaction between the outlined variables in a carbon-income framework for annual time series data from 1970 to 2016. A series of econometrics strategies was used consisting of unit root tests to examine the stationarity properties of the highlighted series. Subsequently, Pesaran’s Bounds testing technique is used to explore the long-run equilibrium relationship between the highlighted variables in conjunction with the Johansen cointegration test. For long-run regression coefficients, Pesaran’s autoregressive distributed lag and dynamic ordinary least squares methodology are used, and innovative accounting approaches are used to explore the responsiveness of each variable on another.

Empirical results validate the pollution haven hypothesis (PHH) in the long run for the case of Turkey. Thus suggesting that FDI inflow induced environmental degradation in Turkey. Additionally, this study observed that renewable energy, on the contrary, improves the quality of the environment. This study also affirms the presence of the environmental Kuznets curve phenomenon, indicating that Turkey, at its early stage of economic trajectory, emphasis is on economic growth rather than environmental quality. This suggests a need for more deliberate action(s) by the government administrators to pursue cleaner FDI inflow and energy technologies and strategies to foster a clean environment in Turkey and a cleaner ecosystem at large.

This study is unique in its choice of variables which is in line with the United Nations Sustainable Development Goals (SDGs) agenda to be achieved by 2030 and is very limited in the extant literature. From the economic perspective, the effect of the PHH is of interest especially to ascertain the extent the interplay among the variables has on the economy of Turkey. The empirical insights on PHH hypothesis have received less documentation in the extant literature especially for emerging economy like Turkey. Thus, this study seeks to revisit this theme for Turkey with aim to presents environmentally sustainable strategies without compromise for economic growth. Thus, this study seeks to revisit this theme.

The Purpose of this study is to prove the possibility of developing low cost mechanical anti – lock braking system (ABS) for the passenger’s safety.

The design methodology of the proposed newer mechanical ABS comprises of two units, namely, the braking unit and wheel lock prevention unit. The braking unit actuates the wheel stopping as and when the driver applies the brake, whereas the wheel lock prevention unit initiates wheel release to prevent locking and subsequent slip/skidding. The brake pedal with master cylinder assembly and double-arm cylinder forms the braking unit, brake pad cylinder, movable brake pad, solenoid valve and dynamo forms the wheel lock prevention unit. The dynamo coupled with the rotor energises/de-energises the solenoid values to direct airflow for applying brake and release it, which makes the system less energy-dependent.

The braking unit aids in vehicle stops, by locking the disc with the brake pad actuated by a double-arm cylinder. The dynamo energises the solenoid valve to activate the brake pad cylinder piston for applying the brake on the disc. Instantaneously, on applying the brake the dynamo de-energises the solenoid to divert the pneumatic flow for retracting the brake pad thereby minimizing the braking torque. The baking torque reduction revives the wheel rotating and prevents slip/skidding.

Mechanical ABS preventing wheel lock by torque reduction principle is a novel method that has not been evolved so far. The system was designed with repair/replacement of the parts and subcomponents to support higher affordability on safety grounds.

This study aims to explore whether digital platform capabilities (integration and reconstruction) affect technological innovation through knowledge bases in the dimensions of breadth and depth and the moderating role of organisational routines updating.

Hierarchical regression, mediation effect test macro and bootstrap were conducted to empirically analyse two waves of longitudinal survey data from 179 Chinese technology firms.

Results confirmed that knowledge bases (breadth and depth) mediated the effect of digital platform capabilities (integration and reconstruction) on technological innovation and that updating of organisational routines moderated the relationship between knowledge bases and technological innovation.

These findings offer guidance to firms that aim to achieve technological innovation and advantages, highlighting the importance of digital platform capabilities, knowledge bases and organisational routines updating.

Advancing from existing digital strategies and firm innovation literature, the authors provide a new perspective (knowledge bases) to respond to the information technology (IT) paradox and understand the role of digital platform capabilities in improving technological innovation.