The research is focused on the evolution of the enterprises, in the field of specialized professional services, medium-period, enterprises that implemented projects financed within Regional Operational Program (ROP) during the 2007–2013 financial programming period. The analysis of the economic performance of the micro-enterprises corresponds to general objectives, but there can be outlined connections between these performances and other economic indicators that were not considered or followed through the financing program. The study case is focused on the development of micro-enterprises in the services area, in the Central Region, Romania (one of the eight development regions in Romania). The scientific approach for this article was based on a regressive statistical analysis. The analysis included the economic parameters for the enterprises selected, comparing the economic efficiency of these enterprises, during implementation with the economic efficiency after the implementation of the projects, during medium periods, including the sustainability period. The purpose of the research was to analyse the economic efficiency of the selected micro-enterprises, after finalizing the projects’ implementation. The authors intend to point out the need for a managerial instrument based on the economic efficiency of companies that are benefiting from non-reimbursable funds. This instrument should be taken into consideration in planning regional development at the national level, regarding the conditions and results expected. Although the authors used regressive statistical analysis the purpose was to prove that there is a need for additional managerial instruments when the financial allocations are being designed at the regional level. This study follows the interest of the authors in proving that the efficiency of non-reimbursable funds should be analysed distinctively on the activity sectors.

Nowadays investors are measuring the performances of a business organization not only based on their operating efficiency but also fulfilling their social responsibility. At least the investors need to know whether the activities of the business have any adverse impact on the society and environment. This study explores the accountability of the business from the social and environmental context. This empirical study tends to investigate the nature of the ownership structure that influences the environmental disclosure of a business entity. Based on the sample of fifty-five DSE-listed textile companies, this study used multiple regression to assess the causal relationship between the ownership structure and corporate environmental disclosure. Moreover, this cross-sectional study also considers the agency theory and stakeholder theory to explain the relationship between the ownership structure and environmental disclosure. The findings indicate that corporate environmental disclosure is positively influenced by foreign ownership and institutional ownership whereas director ownership and public ownership have no significant association with the environmental disclosure. These insightful results challenge conventional assumptions and highlight the need for a nuanced understanding of the factors that drive environmental reporting practices in the context of an emerging economy. The main contribution of this article lies in its provision of empirical evidence from an emerging economy, Bangladesh, which helps in understanding sustainable practices in a global context. Additionally, it aids in developing effective corporate governance policies and strategies tailored to similar emerging economies by recognizing the role of ownership structures in influencing environmental accountability. These findings further assist policymakers, managers, and other sustainability advocates in understanding how different ownership structures affect corporate environmental disclosure.

Falling is one of the most critical outcomes of loss of consciousness during triage in emergency department (ED). It is an important sign requires an immediate medical intervention. This paper presents a computer vision-based fall detection model in ED. In this study, we hypothesis that the proposed vision-based triage fall detection model provides accuracy equal to traditional triage system (TTS) conducted by the nursing team. Thus, to build the proposed model, we use MoveNet, a pose estimation model that can identify joints related to falls, consisting of 17 key points. To test the hypothesis, we conducted two experiments: In the deep learning (DL) model we used the complete feature consisting of 17 keypoints which was passed to the triage fall detection model and was built using Artificial Neural Network (ANN). In the second model we use dimensionality reduction Feature-Reduction for Fall model (FRF), Random Forest (RF) feature selection analysis to filter the key points triage fall classifier. We tested the performance of the two models using a dataset consisting of many images for real-world scenarios classified into two classes: Fall and Not fall. We split the dataset into 80% for training and 20% for validation. The models in these experiments were trained to obtain the results and compare them with the reference model. To test the effectiveness of the model, a t-test was performed to evaluate the null hypothesis for both experiments. The results show FRF outperforms DL model, and FRF has same accuracy of TTS.

This study aims to develop a robust prioritization model for municipal projects in the Holy Metropolitan Municipality (Makkah) to address the challenges of aligning short-term and long-term objectives. The research explores How multi-criteria decision-making (MCDM) techniques can prioritize municipal projects effectively while ensuring alignment with strategic goals and local needs. The methodology employs the analytic hierarchy process (AHP) and exploratory factor analysis (EFA) to ensure methodological rigor and data adequacy. Data were collected from key stakeholders, including municipal planners and community representatives, to enhance transparency and reliability. The model’s validity was assessed through latent factor analysis, confirming the relevance of identified criteria and factors. Results indicate that flood prevention projects are the highest priority (0.4246), followed by road projects (0.3532), park construction (0.1026), utility projects (0.0776), and digital transformation (0.0416). The study highlights that certain factors are critical for evaluating and prioritizing municipal projects. “Capacity and Demand” emerged as the most influential factor (0.5643), followed by “Strategic Alignment” (0.2013), “Project Interdependence” (0.1088), “Increasing Investment” (0.0950), and “Risk” (0.0306). These findings are significant as they offer a structured, data-driven approach to decision-making aligned with Saudi Vision 2030. The proposed model optimizes resource allocation and project selection, representing a pioneering effort to develop the first prioritization framework specifically tailored to Makkah’s unique municipal needs. Notably, this is the first study to establish a prioritization method specifically for Makkah’s municipal projects, providing valuable contributions to the field.

Protecting the environment and the Earth's natural resources is one of the most important tasks for modern societies, economies, and countries. Changes in the environment have made climate protection a key task of state policy implemented at the local, national, and international. They also have caused such negative social manifestations as environmental radicalism and terrorism. The purpose of this paper was to analyze the capacity of state institutions to prevent environmental terrorism and radicalism, particularly in the Russian context, by identifying and prioritizing key challenges and countermeasures. A mixed-methods approach was adopted, involving both qualitative and quantitative analyses. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 35 articles and reviews were selected to provide a foundation for understanding eco-terrorism trends. Additionally, an expert survey was conducted with 44 qualified participants to rank problems and recommended actions. The Kendall concordance coefficient was used to assess the consistency of expert opinions. The authors conclude that low environmental awareness and insufficient cooperation between state institutions and environmental organizations are the most significant challenges in preventing eco-terrorism. To adequately and competently prevent environmental terrorism and radicalism in society, the prevention system must be based on clear and thoughtful actions by state institutions.

The employees in academic sector had to face an abrupt change due to Covid-19 pandemic and transformation of education into online and remote learning. This has led to virtual work intensity as an aftermath that negatively influences employees’ job satisfaction. In addition, due to remote working conditions, the lines between work and life had been dimmed and thus, the current situation is important to be addressed for wellbeing of academic staff. This research specifically aims to examine impact of virtual work intensity on job satisfaction among university staff. Furthermore, mediating effect of organizational support and work-life balance on the aforementioned relationship are analyzed to better understand the underlying effects. Through PLS-SEM and using a questionnaire survey, a total of 183 data were collected from teachers and administrative staff of two universities. The results show that virtual work intensity can hinder job satisfaction, while organizational support and work-life balance can improve job satisfaction of academic employees. This is due to the fact that support, and balance act against work intensity that diminishes wellbeing of individuals. This implies the vital role of organizations (e.g., human resource department) in providing support for their staff, and creating an environment, where academic staff can have a better work-life balance, leading to higher rates of job satisfaction as an important factor for psychological wellbeing.