Search Results (1,388)

As the workforce adapts to evolving professional demands, working conditions simultaneously become increasingly stressful, competitive, and challenging, making it essential to examine the determinants of job performance among highly educated workers. This study investigates the influence of psychological capital, work–life balance, rewards, and incentives, and work commitment on job performance among higher education professionals, with particular attention to gender differences. A survey was administered to 661 university-educated workers, and the data was analyzed using covariance-based structural equation modeling (CB-SEM). Results demonstrate that psychological capital, work–life balance, and rewards and incentives positively influence job performance across both genders. However, the mediating effect of work commitment between rewards and incentives, work–life balance, and job performance was confirmed only among women. Work–life balance emerged as the primary factor influencing psychological capital, surpassing the impact of rewards and incentives. The findings reveal significant gender differences in professional commitment patterns, suggesting that women workers exhibit stronger emotional connections between organizational support mechanisms and performance outcomes. Practical implications emphasize the need for organizations to prioritize work–life balance strategies as foundational elements of human resource management, while implementing comprehensive reviews of gender equality policies to ensure equitable workplace experiences. This research contributes valuable insights for developing targeted interventions that optimize professional performance while addressing gender-specific workplace dynamics in emerging economies. Full article

Hybrid AC/DC microgrids have emerged as a promising solution for integrating diverse renewable energy sources, enhancing efficiency, and strengthening resilience in modern power systems. However, existing control schemes exhibit critical shortcomings that limit their practical effectiveness. Traditional linear controllers, designed around nominal operating points, often fail to maintain stability under large load and generation fluctuations. Optimization-based methods are highly sensitive to model inaccuracies and parameter uncertainties, reducing their reliability in dynamic environments. Intelligent approaches, such as fuzzy logic and ML-based controllers, provide adaptability but suffer from high computational demands, limited interpretability, and challenges in real-time deployment. These limitations highlight the need for robust control strategies that can guarantee reliable operation despite disturbances, uncertainties, and varying operating conditions. Numerical performance indices demonstrate that the reviewed robust control strategies outperform conventional linear, optimization-based, and intelligent controllers in terms of system stability, voltage and current regulation, and dynamic response. This paper provides a comprehensive review of recent robust control strategies for hybrid AC/DC microgrids, systematically categorizing classical model-based, intelligent, and adaptive approaches. Key research gaps are identified, including the lack of unified benchmarking, limited experimental validation, and challenges in integrating decentralized frameworks. Unlike prior surveys that broadly cover microgrid types, this work focuses exclusively on hybrid AC/DC systems, emphasizing hierarchical control architectures and outlining future directions for scalable and certifiable robust controllers. Also, comparative results demonstrate that state of the art robust controllers—including H∞-based, sliding mode, and hybrid intelligent controllers—can achieve performance improvements for metrics such as voltage overshoot, frequency settling time, and THD compared to conventional PID and droop controllers. By synthesizing recent advancements and identifying critical research gaps, this work lays the groundwork for developing robust control strategies capable of ensuring stability and adaptability in future hybrid AC/DC microgrids. Full article

Air pollution from fine particulate matter (PM2.5) is a recurring crisis in Northern Thailand, largely driven by seasonal biomass burning. This study investigates how socioeconomic and individual characteristics shape labor allocation during high-exposure periods. Using survey data from 400 individuals across eight provinces in April–May 2024, we applied a logit model to estimate the probability of reducing work hours. Results show heterogeneous and non-linear patterns of avoidance. The probability of work reduction rose across higher income strata but peaked in the third stratum before declining in the fourth, reflecting the trade-off between avoidance and the opportunity cost of foregone earnings. Education exhibited a strong awareness effect, with each additional year increasing avoidance behavior. Outdoor workers and individuals with respiratory conditions were most likely to reduce work, indicating rational prioritization under greater exposure risks. Together, these findings demonstrate environmental inequality: lower-income and less-educated groups remain disproportionately exposed due to limited coping capacity. The regional context of Northern Thailand further amplifies these vulnerabilities. Policy interventions should prioritize protective measures for vulnerable groups while promoting long-term alternatives to biomass burning. By highlighting nuanced behavioral responses, this study extends evidence on environmental inequality in developing-country contexts. Full article

Background/Objectives: Human resources for health remain one of the key factors ensuring the effectiveness and accessibility of the healthcare system. Many countries face a shortage of physicians due to the migration of healthcare professionals and career changes, making it crucial to understand the underlying causes of these processes. The aim of this study was to assess the intentions to emigrate among Lithuanian medical students, residents, and practicing physicians, as well as to identify the main reasons for migration and plans regarding employment in the medical profession. Methods: The study was conducted using an anonymous, author-designed questionnaire survey, in which 1367 respondents participated. Results: The results indicate that 50.91% of students, 39.70% of residents, and 36.81% of physicians plan to emigrate or do not intend to work in the medical profession at all. The main reasons specified for emigration were higher salaries, better living conditions, and greater professional opportunities. The primary reasons for leaving the medical profession included low salary, physical and psychological strain, and administrative burden (among physicians), also the perception that the profession is not suitable for them (among students and residents). Conclusions: These findings are important for shaping human resource policies and strategies in the Lithuanian healthcare system and may also be valuable for policymakers in other countries facing similar challenges. Full article

Background/Objectives: This study is part of an exploratory mixed-methods project investigating how companies and their employees in Germany dealt with adapted working conditions during the COVID-19 pandemic. Here, we identify predictive factors for employees’ attitudes towards the suitability of work-related technical, organisational, and personal SARS-CoV-2 infection control measures. Methods: In July 2021, when there was little evidence to suggest that the risk of work-related exposure to SARS-CoV-2 differed between occupations and workplaces, a standardised online and an optional paper-and-pencil survey were distributed across seven companies in southern Germany. Multivariate linear regression was used for analysis. Results: A total of 821 employees participated (average response rate: 24.5%). Most of the respondents (93%) worked in large companies, in the production industry (82%), with most of them having office jobs (82%). Around 29% reported doing most of their office work remotely during the pandemic. The perceived suitability of workplace infection control measures was rated quite high, with an overall mean score of 4.11 (SD 0.60) out of a possible 5. Workplace characteristics related to the COVID-19 pandemic as well as individual perception of SARS-CoV2 and COVID-19 in general were the most prominent predictors of attitudes towards the suitability of work-related SARS-CoV-2 infection control. For example, a higher COVID-19-specific reactance was negatively associated with attitudes towards technical (ß = −0.16), organisational (ß = −0.14), and personal (ß = −0.17) infection control measures (all p-values < 0.001). Furthermore, a higher rating of the employer’s commitment to occupational safety and health related to SARS-CoV-2, a higher individual disease perception, and a higher individual COVID-19-specific resilience had a positive association with attitudes towards the suitability of infection control measures. Finally, professional activity as well as company affiliation had statistically significant associations with employees’ attitudes towards the suitability of infection control measures. Conclusions: The results provide insight into factors relevant to pandemic prevention and control. In particular, our findings highlight the potential to implement organisational measures alongside compulsory technical occupational health measures. This could inform the development of pandemic preparedness strategies that prioritise adherence to established occupational infection control measures. Full article

Background: The European Doctoral Conference in Nursing Science provides a unique platform for doctoral students in nursing and health sciences to present their research in a supportive environment. Celebrating its 20th anniversary, the 2024 conference embraced the motto “looking back and looking forward,” offering an opportunity to reflect on the development of nursing science and future challenges. Results: Held at the Medical University of Graz, Austria, the conference hosted 90 participants from 13 countries. It featured two keynote lectures, three workshops, 48 presentations, and a science slam. Abstract submissions underwent peer review to ensure the quality of presentations. The presentations highlighted key challenges and opportunities across nursing practice, healthcare work environments, education and digitalization in nursing, and health perspectives. Topics included, for example, workforce retention, artificial intelligence in nursing practice, leadership in error management, and culturally sensitive care. The keynotes emphasized the importance of patient and public involvement in research and the benefits of survey data in nursing science. Workshops imparted knowledge and skills regarding funding acquisition, guideline development, and effective research presentation. A science slam introduced innovative and creative ways to present research. Conclusions: The conference showcased the evolving landscape of nursing science, emphasizing the importance of evidence-based practice, supportive working conditions, and constructive collaboration. It demonstrated the enthusiasm and readiness of a new generation of researchers to advance nursing science in a rapidly changing healthcare environment. Full article

Underwater wireless communication (UWC) is an emerging technology crucial for automating marine industries, such as offshore aquaculture and energy production, and military applications. It is a key part of the 6G vision of creating a hyperconnected world for extending connectivity to the underwater environment. Of the three main practicable UWC technologies (acoustic, optical, and radiofrequency), acoustic methods are best for far-reaching links, while optical is best for high-bandwidth communication. Recently, utilizing reconfigurable intelligent surfaces (RISs) has become a hot topic in terrestrial applications, underscoring significant benefits for extending coverage, providing connectivity to blind spots, wireless power transmission, and more. However, the potential for further research works in underwater RIS is vast. Here, for the first time, we conduct an extensive survey of state-of-the-art of RIS and metasurfaces with a focus on underwater applications. Within a holistic perspective, this survey systematically evaluates acoustic, optical, and hybrid RIS, showing that environment-aware channel switching and joint communication architectures could deliver holistic gains over single-domain RIS in the distance–bandwidth trade-off, congestion mitigation, security, and energy efficiency. Additional focus is placed on the current challenges from research and realization perspectives. We discuss recent advances and suggest design considerations for coupling hybrid RIS with optical energy and piezoelectric acoustic energy harvesting, which along with distributed relaying, could realize self-sustainable underwater networks that are highly reliable, long-range, and high throughput. The most impactful future directions seem to be in applying RIS for enhancing underwater links in inhomogeneous environments and overcoming time-varying effects, realizing RIS hardware suitable for the underwater conditions, and achieving simultaneous transmission and reflection (STAR-RIS), and, particularly, in optical links—integrating the latest developments in metasurfaces. Full article

This study interrogates whether Augmented Reality (AR) enhances vocabulary and content acquisition within Content and Language Integrated Learning (CLIL), situating the question in the broader debate on how immersive, multimodal technologies shape achievement and engagement. This study’s novelty lies in its direct AR-versus-print comparison in a real CLIL classroom using markerless, smartphone-based technology. Using a mixed-methods, classroom-based experiment, we drew on a convenience sample of 129 secondary students (ages 16–18), assigning them to an AR intervention (n = 64) or a print-based control (n = 65). Both cohorts received parallel instruction covering identical objectives and materials; vocabulary attainment was gauged using matched pretest and post-test measures, while engagement, attitudes, and perceived usefulness were captured through paired pre- and post-surveys and open-ended prompts. Quantitative analyses compared change scores across conditions and were complemented by qualitative summaries of learner comments. Results indicate that exposure to AR exerted a positive influence on learners’ engagement and supported learning processes, with perceptible shifts in students’ views of AR between baseline and post-intervention; nevertheless, effects were heterogeneous across instruments, items, and subgroups, suggesting that benefits accrued in a targeted rather than uniform fashion. Compared to the print-based group, students using AR demonstrated greater gains on visually supported vocabulary and content items, while other items showed no significant differences between groups. We conclude that AR constitutes a promising pedagogical resource for CLIL, capable of scaffolding vocabulary/content development and motivating participation, while the observed variability underscores the need for principled, context-sensitive integration. Future work should specify boundary conditions—such as task type, prior proficiency, cognitive load, and technology familiarity—and employ robust mixed-methods designs to determine for whom, and under which instructional circumstances, AR yields the greatest and most sustainable gains. Full article

The emergence of 6G wireless systems marks a paradigm shift toward intelligent, context-aware networks that can adapt in real-time to their environment. Within this landscape, Sensing-Assisted Communication (SAC) emerges as a key enabler, integrating perception into the communication control loop to enhance reliability, beamforming accuracy, and system responsiveness. Unlike prior surveys that treat SAC as a subfunction of Integrated Sensing and Communication (ISAC), this work offers the first dedicated review of SAC in Millimeter-Wave (mmWave) and Sub-Terahertz (Sub-THz) systems, where directional links and channel variability present core challenges. SAC encompasses a diverse set of methods that enable wireless systems to dynamically adapt to environmental changes and channel conditions in real time. Recent studies demonstrate up to 80% reduction in beam training overhead and significant gains in latency and mobility resilience. Applications include predictive beamforming, blockage mitigation, and low-latency Unmanned Aerial Vehicle (UAV) and vehicular communication. This review unifies the SAC landscape and outlines future directions in standardization, Artificial Intelligence (AI) integration, and cooperative sensing for next-generation wireless networks. Full article

This study investigates slope stability in an open-pit mining area by integrating engineering geological surveys, field investigations, and laboratory rock mechanics tests. A coordinated multimethod analysis was carried out using finite element-based numerical simulations from both two-dimensional and three-dimensional perspectives. The integrated approach revealed deformation patterns across the slopes and established a multiscale analytical framework. The results indicate that the slope failure modes primarily include circular and compound types, with existing step slopes showing a potential risk of wedge failure. While the designed slope meets safety requirements under three working conditions overall, the strongly weathered layer in profile XL3 requires a slope angle reduction from 38° to 37° to comply with standards. Three-dimensional simulations identify the main deformations in the middle-lower sections of the western area and zones B and C, with faults located at the core of the deformation zone. Rainfall and blasting vibrations significantly increase surface tensile stress, accelerating deformation. Although wedges in profiles XL1 and XL4 remain generally stable, coupled blasting–rainfall effects may still induce potential collapse in fractured areas, necessitating preventive measures such as concrete support and bolt support, along with real-time monitoring to dynamically optimize reinforcement strategies for precise risk control. Full article

Background: Postpartum depression is a common mental health condition that can occur up to one year after childbirth. Recent studies have increasingly used machine learning techniques to predict its occurrence; however, few have comprehensively explored the use of electronic health record data, particularly in tertiary care settings where such data can be fragmented. Methods: We analyzed electronic health record data from 12,284 women who delivered at The Birth Center at Atrium Health Wake Forest Baptist Medical Center, excluding those with missing data or no prenatal or postpartum visits. To define the target variable, we examined different combinations of depression screening tools (Edinburgh Postnatal Depression Scale and Patient Health Questionnaire-9), along with diagnosis codes specific to postpartum depression. We then trained a random forest classification model to predict postpartum depression. Results: The model achieved an area under the receiver operating characteristic curve of 0.733 ± 0.008, which is comparable to previous studies. Adding socioeconomic features from census tract data did not improve predictive performance, underscoring the importance of individual-level data. Incorporating national survey data, such as the Pregnancy Risk Assessment Monitoring System, also did not improve performance due to limited overlap in data features. Interestingly, model performance was slightly lower among Hispanic patients (area under the curve = 0.713 ± 0.040), although this difference was not statistically significant (p = 0.17), likely due to the small sample size. A similar, but statistically significant trend was observed in the larger national survey dataset (area under the curve = 0.699 ± 0.019 for Hispanic patients versus 0.735 ± 0.010 for White patients, p < 0.01). Conclusions: While our model demonstrates moderate predictive capability, further validation and prospective testing are needed before clinical implementation. This work also identified an optimal approach for digital phenotyping postpartum depression in electronic health record data and highlighted key gaps in data quality and completeness. These findings emphasize the importance of robust data when developing predictive models for real-world clinical use. Full article

In recent decades there has been a deterioration of wetlands with severe implications for human health, particularly through its effects on food, water, and climate security. Thus, there is an increasing interest in addressing the adverse effects of wetland degradation, particularly in relation to public health. Despite the necessity to comprehend the economic value associated with wetland degradation, there is still a paucity of research on the subject in many areas of the world, such as Latin American countries. The objective of this work is to determine the economic impacts of wetland degradation through its health impacts on local communities to achieve sustainable wetland management. To this end, a contingent valuation method has been applied selecting Lake Cuitzeo (Mexico) as an emblematic case study where there is a process of ecological degradation that has a negative impact on both the well-being and health of the population. Based on contingent valuation surveys of the population, respondents were directly asked to express their willingness to accept (WTA) by considering changes in well-being resulting from the loss of a benefit or their willingness to pay (WTP) for the improvement of goods/services. The findings indicated a willingness to accept economic compensation of 47.86 USD/household/month for health-related damages and a willingness to pay 2.77 USD/household/month for the environmental management measures to improve lake conditions. In addition, a multivariate analysis was carried out to determine the influence of socio-economic and environmental factors on the economic valuation exercise. The results can serve as a guide for policymakers in the implementation of socially accepted measures to solve the environmental and public health problems in degraded water bodies. Full article

This article is devoted to the crucial actual problem of the restoration of lands disturbed by the mining industry. It has been determined that before the reclamation of disturbed lands, it is essential to conduct an environmental impact assessment. The main objective of the research is to find and study the most optimal methods for reducing the technogenic impact of the mining industry on the environment by restoring disturbed areas. The object of the study was a mining enterprise in the Karaganda region. The Karaganda region was chosen for the study due to being the one with the most mining industry. After the extraction of mineral resources, the territories of the region became the most vulnerable and required the clearest solution for land restoration, taking into account the physical and geographical conditions. The work includes a statistical analysis of historical data on the state of disturbed territories of the Karaganda region, and laboratory and field studies. The comprehensive study revealed a clear need to restore disturbed lands. This will prevent further degradation of land resources and will make it possible to use them for new agricultural purposes. For the first time, studies were conducted for various soils, including technogenic soils, typical for areas where mining enterprises are located. For the first time, a reclamation algorithm has been developed for a mining enterprise in the Karaganda region, taking into account engineering and geological surveys. Full article

The increasing prevalence of private-sector work among doctors raises questions about its impact on their health and wellbeing. While private practice may offer autonomy and financial benefits, it presents unique psychosocial risks that are less understood. This study investigates the relationship between private-sector work, psychosocial working conditions, and burnout among doctors, and examines whether access to health and wellbeing resources changes these relationships. A cross-sectional survey with 509 doctors from 16 countries working either exclusively or partially in private practice assessed psychosocial risk factors (e.g., work demands, financial pressures, support, job control), and burnout, alongside access to and use of wellbeing resources. Results showed that more time in private practice was associated with higher work and financial demands, bullying, and burnout. Although access to health and wellbeing resources was initially linked to lower burnout, this relationship was not significant when psychosocial risk factors were accounted for. These findings suggest that support mechanisms are often reactive and insufficient in mitigating the impact of systemic demands. The study highlights the need for private healthcare employers to recognise their role in developing healthy work environments, and for organisational-level interventions to address the root causes of poor health and wellbeing among doctors in this sector. Full article

Environmental sound and animal vocalizations provide non-invasive information for welfare assessment in livestock systems. This systematic review surveys their application in beef and dairy cattle, poultry, and swine, with a focus on environmental noise, vocalizations and the characterization of acoustic sources. Searches in Scopus and Web of Science followed PRISMA guidance and the PICO framework. After applying strict criteria that required peer-reviewed experimental studies in English, quantifiable acoustic data, and clear descriptions of measurement procedures, the review included 36 studies. Four approaches recur: vocalizations as welfare indicators; characterization of acoustic sources; combined analyses of vocalizations and sources; and evaluation of animal responses to acoustic stimuli. Recent work reports advances in recording equipment, signal processing, and precision livestock tools. Important challenges remain, including heterogeneous acoustic metrics, limited physiological validation, and difficulties applying models under commercial conditions. Overall, the evidence supports sound as a candidate for real-time monitoring and highlights the need for accessible, standardized methods. The findings provide a basis for future research and practical applications in welfare assessment. Full article