In the last several decades, cardiovascular diseases (CVDs) have emerged as a major hazard to human life and health. Conventional formulations for the treatment of CVD are available, but they are far from ideal because of poor water solubility, limited biological activity, non-targeting, and drug resistance. With the advancement of nanotechnology, a novel drug delivery approach for the treatment of CVDs has emerged: nano-drug delivery systems (NDDSs). NDDSs have shown significant advantages in tackling the difficulties listed above. Cytotoxicity is a difficulty with the use of non-destructive DNA sequences. NDDS categories and targeted tactics were outlined, as well as current research advancements in the diagnosis and treatment of CVDs. It’s possible that gene therapy might be included into nano-carriers in the delivery of cardiovascular medications in the future. In addition, the evaluation addressed the drug’s safety.

Purpose: The study examines the mediating effect of self-emotion appraisal and other-emotion appraisal on psychological safety, individual resilience, and organizational commitment at the workplace. Design/methodology/approach: This study generated 140 survey responses from workers in diverse occupations and industries during the COVID-19 pandemic. A mixed-methods data analysis was conducted. Hierarchical regression analysis was employed to test the hypotheses, and process macroanalysis was used to generate the mediation analysis. Qualitative data analysis through thematic coding was adopted to interpret the respondents’ written opinions and narratives. Findings: The results revealed that self-emotion appraisal strongly correlates to resilience, but evaluation of self-emotion has no effect on organizational commitment. Other-emotion appraisal and psychological safety are not significant predictors of resilience at the workplace. Rather, psychological safety is a significant predictor of organizational commitment. The qualitative analysis generated from the respondents’ narratives provides deeper insight into the quantitative results. Additional data that emerged from the qualitative interpretation revealed other factors that are related to emotional appraisal, psychological safety, resilience, and organizational commitment. Practical implications: The findings shed light on the need to understand an individual’s emotional appraisal when instilling workplace resilience. Further, promoting psychological safety, such as by involving employees in the change process, managing fairness perception, and eliciting trust, enhances organizational commitment in the workplace. Integrating open communication, management intervention, and coaching programmes should form part of the employee engagement and development functions to help build organizational resilience and commitment. Originality/value: This research is an original contribution conducted during the global health crisis that led to abrupt changes in the workers’ lives and the workplaces in Singapore. Research implications: This present study demonstrated constructive findings on emotion regulations and perceived psychological safety associated with resilience and commitment amid the disruptive changes in work practices at the workplace. Further, the outcome of the study shows the mediating effect of self-emotional appraisal on psychological safety and resilience. The result draws parallels with past literature that showed that individuals who appraised their emotions tended to recalibrate and recognize their subjective behaviour and take actions to modify it. Social implications: Emotion regulation connotes employees’ emotion coping strategies, and research showed that emotion reappraisal produces a positive effect on workplace relationship quality. 

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.