Search Results (3,954)

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

Wound care in military and combat environments poses distinct challenges that set it apart from conventional medical practice in civilian settings. The nature of injuries sustained on the battlefield—often complex, contaminated, and involving extensive tissue damage—combined with limited access to immediate medical intervention, significantly increases the risk of infection, delayed healing, and adverse outcomes. Traditional wound dressings frequently prove inadequate under such extreme conditions, as they have not been designed to address the specific physiological and logistical constraints present during armed conflicts. This review provides a comprehensive overview of recent progress in the development of advanced wound dressings tailored for use in military scenarios. Special attention has been given to multifunctional dressings that go beyond basic wound coverage by incorporating biologically active macromolecules such as collagen, chitosan, thrombin, alginate, therapeutic peptides, and growth factors. These compounds contribute to properties including moisture balance control, exudate absorption, microbial entrapment, and protection against secondary infection. This review highlights the critical role of advanced wound dressings in improving medical outcomes for injured military personnel. The potential of these technologies to reduce complications, enhance healing rates, and ultimately save lives underscores their growing importance in modern battlefield medicine. Full article

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by inattention, hyperactivity, and impulsivity, frequently observed in juvenile offenders. This systematic review explores the interplay between ADHD and juvenile delinquency, focusing on behavioural, psychological, and social dimensions. Following the PRISMA guidelines, a systematic literature review was conducted using EBSCO Discovery Service, Science Direct, PubMed, and snowballing techniques. Studies meeting specific inclusion criteria, including juvenile offenders diagnosed with ADHD and comparisons to non-offender or non-ADHD control groups, were analysed. The methodological quality of studies was assessed using the Joanna Briggs Institute appraisal tools. A total of 21 studies were included, highlighting significant associations between ADHD and juvenile delinquency. ADHD symptoms, especially impulsivity and emotional dysregulation, were linked to an earlier onset of offending and higher rates of property crimes. Comorbidities such as conduct disorder, substance use disorder, and depression exacerbated these behaviours. Sociodemographic factors like low education levels and adverse family environments were also critical modifiers. Early intervention and tailored treatment approaches were emphasised to address these challenges. The findings underscore the need for early diagnosis, individualised treatment, and integrative rehabilitation programmes within the juvenile justice system to mitigate long-term risks and promote social inclusion. Full article

In this paper, the accuracy of basic and advanced spiral inductor models for gallium nitride (GaN) integrated inductors is evaluated. Specifically, the experimental measurements of geometrically scaled circular spiral inductors, fabricated in a radio frequency (RF) GaN-on silicon technology, are exploited to estimate the errors of two lumped geometrically scalable models, i.e., a simple π-model with seven components and an advanced model with thirteen components. The comparison is performed by using either the standard performance parameters, such as inductance (L), quality factor (Q-factor), and self-resonance frequency (SRF), or the two-port scattering parameters (S-parameters). The comparison reveals that despite a higher complexity, the developed advanced model achieves a significant reduction in SRF percentage errors in a wide range of geometrical parameters, while enabling an accurate estimation of two-port S-parameters. Indeed, the correct evaluation of both SRF and two-port S-parameters is crucial to exploit the model in an actual circuit design environment by properly setting the inductor geometrical parameters to optimize RF performance. Full article

This paper introduces a theoretical large-scale radio channel model for the downlink in cellular systems, aimed at estimating variations in received signal power at the user terminal as a function of device mobility. This enables applications such as direction-of-arrival (DoA) estimation, estimating power at subsequent points based on received power, and detection of coverage anomalies. The model is validated using real-world measurements from urban and suburban environments, achieving a maximum estimation error of 7.6%. In contrast to conventional models like Okumura–Hata, COST-231, Third Generation Partnership Project (3GPP) stochastic models, or ray-tracing techniques, which estimate average power under static conditions, the proposed model captures power fluctuations induced by terminal movement, a factor often neglected. Although advanced techniques such as wave-domain processing with intelligent metasurfaces can also estimate DoA, this model provides a simpler, geometry-driven approach based on empirical traces. While it does not incorporate infrastructure-specific characteristics or inter-cell interference, it remains a practical solution for scenarios with limited information or computational resources. Full article

The extended operation of high-speed railways has led to an increased incidence of tunnel lining defects, with falling debris posing a significant safety threat. Within tunnels, single-train passage and trains-crossing events constitute the most frequent operational scenarios, both generating extreme aerodynamic environments that alter debris trajectories from free fall. To systematically investigate the aerodynamic differences and underlying mechanisms governing falling debris behavior under these two distinct conditions, a three-dimensional computational fluid dynamics (CFD) model (debris–air–tunnel–train) was developed using an improved delayed detached eddy simulation (IDDES) turbulence model. Comparative analyses focused on the translational and rotational motions as well as the aerodynamic load coefficients of the debris in both single-train and trains-crossing scenarios. The mechanisms driving the changes in debris aerodynamic behavior are elucidated. Findings reveal that under single-train operation, falling debris travels a greater distance compared with trains-crossing conditions. Specifically, at train speeds ranging from 250–350 km/h, the average flight distances of falling debris in the X and Z directions under single-train conditions surpass those under trains crossing conditions by 10.3 and 5.5 times, respectively. At a train speed of 300 km/h, the impulse of C_Fx and C_Fz under single-train conditions is 8.6 and 4.5 times greater than under trains-crossing conditions, consequently leading to the observed reduction in flight distance. Under the conditions of trains crossing, the falling debris is situated between the two trains, and although the wind speed is low, the flow field exhibits instability. This is the primary factor contributing to the reduced flight distance of the falling debris. However, it also leads to more pronounced trajectory deviations and increased speed fluctuations under intersection conditions. The relative velocity (CRV) on the falling debris surface is diminished, resulting in smaller-scale vortex structures that are more numerous. Consequently, the aerodynamic load coefficient is reduced, while the fluctuation range experiences an increase. Full article

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

Urban air pollution remains a significant environmental and public health issue, especially in European coastal cities such as Klaipėda. However, there is still a lack of local-scale knowledge on how land use structure influences pollutant distribution, highlighting the need to address this gap. This study addresses this by examining the spatial distribution of nitrogen dioxide (NO₂) concentrations in Klaipėda’s seaport city and several inland and coastal resort towns in Lithuania. The research specifically asks how different land cover types and demographic factors affect NO₂ variability and population exposure risk. Data were collected using passive sampling methods and analyzed within a GIS environment. The results revealed clear air quality differences between industrial/port zones and greener resort areas, confirmed by statistically significant associations between land cover types and pollutant levels. Based on these findings, a Land Use Pollution Pressure index (LUPP) and its population-weighted variant (PLUPP) were developed to capture demographic sensitivity. These indices provide a practical decision-support tool for sustainable urban planning, enabling the assessment of pollution risks and the forecasting of air quality changes under different land use scenarios, while contributing to local climate adaptation and urban environmental governance. Full article

Single-atom catalysts (SACs) have emerged as highly promising catalytic materials for the hydrogen evolution reaction (HER), attributed to their maximal atomic utilization efficiency and unique electronic configurations. Many structure parameters can influence the catalytic performance of SACs for HER, and the intrinsic advantages of SACs for HER still need to be summarized. This review systematically summarizes recent advances in SACs for HER. It discusses various types of SACs (including those based on Pt, Co, Ru, Ni, Cu, and other metals) applied in HER, and elaborates the critical factors influencing catalytic performance—specifically, the supports, coordination environments, and synergistic effects of these SACs. Furthermore, current research challenges and future perspectives in this rapidly developing field are also outlined. Full article

Plant functional traits serve as vital tools for understanding vegetation adaptation mechanisms in changing environments. As the primary organs for nutrient acquisition from soil, fine roots are highly sensitive to environmental variations. However, current research on fine-root adaptation strategies predominantly focuses on tropical, subtropical, and temperate forests, leaving a significant gap in comprehensive knowledge regarding fine-root responses in rocky-desertification habitats. This study investigates the fine roots of Pseudotsuga sinensis across varying degrees of rocky desertification (mild, moderate, severe, and extremely severe). By analyzing fine-root morphological and nutrient traits, we aim to elucidate the trait differences and correlations under different desertification intensities. The results indicate that root dry matter content increases significantly with escalating desertification severity. Fine roots in mild and extremely severe desertification exhibit notably higher root C, K, and Mg concentrations compared to those in moderate and severe desertification, while root Ca concentration shows an inverse trend. Our correlation analyses reveal a highly significant positive relationship between specific root length and specific root area, whereas root dry matter content demonstrates a significant negative correlation with elemental concentrations. The principal component analysis (PCA) further indicates that the trait associations adopted by the forest in mild- and extremely severe-desertification environments are different from those in moderate- and severe-desertification environments. This study did not account for soil nutrient dynamics, microbial diversity, or enzymatic activity—key factors influencing fine-root adaptation. Future research should integrate root traits with soil properties to holistically assess resource strategies in rocky-desertification ecosystems. This study can serve as a theoretical reference for research on root characteristics and adaptation strategies of plants in rocky-desertification habitats. Full article

The interleukin-20 (IL-20) cytokine subfamily, a subset of the IL-10 superfamily, includes IL-19, IL-20, IL-22, IL-24, and IL-26. Recently, their involvement in cancer biology has gained attention, particularly due to their impact on the tumor microenvironment (TME). Notably, IL-20 subfamily cytokines can exert both pro-tumorigenic and anti-tumorigenic effects, depending on the context. For example, IL-22 promotes tumor growth by enhancing cancer cell proliferation and protecting against apoptosis, whereas IL-24 demonstrates anti-tumor activity by inducing cancer cell death and inhibiting metastasis. Additionally, these cytokines influence macrophage polarization—an essential factor in the immune landscape of tumors—thereby modulating the inflammatory environment and immune evasion strategies. Understanding the dual role of IL-20 subfamily cytokines within the TME and their interactions with cancer cell hallmarks presents a promising avenue for therapeutic development. Interleukin-20 receptor antagonists are being researched for their role in cancer therapy, since they potentially inhibit tumor growth and progression. This review explores the relationship between IL-20 cytokines and key cancer-related processes, including growth and proliferative advantages, angiogenesis, invasion, metastasis, and TME support. Further research is necessary to unravel the specific mechanisms underlying their contributions to tumor progression and to determine their potential for targeted therapeutic strategies. Full article

Background: Emotional safety is increasingly recognized as crucial for high-quality patient care, encompassing a patient’s sense of security, courteous treatment, being heard, and a peaceful environment. Purpose: The purpose of this study was to explore the perceptions of patients and providers (doctors and nurses) regarding emotional harm and safety in relation to hospitalized patients. Methods: We conducted a qualitative study in public-sector teaching hospitals in Peshawar, Pakistan. Data were collected after we obtained informed consent using individual interviews with 15 providers, namely, doctors (n = 7) and nurses (n = 8), and five focus group discussions (FGDs) with 25 hospitalized patients. Data from both the interviews and FGDs were analyzed using Braun and Clarke’s six-phase approach to thematic analysis. Results: The key themes revealed by the providers’ perspectives were factors contributing to emotional harm, staff-related factors, coping mechanisms and solutions, and the impact of prior experiences and involvement. The main themes that emerged from the patients’ perspectives were anxiety upon admission, the impact of communication, emotional stress due to treatment delays, systemic/bureaucratic challenges, financial burden, a lack of emotional support, and post-hospitalization concerns. The consistent perspectives shared by both patients and providers included the impact of systemic factors, communication issues, the role of staff attitude/behavior, financial concerns, and the influence of prior experiences. Conclusions: This study highlights the complex interplay of systemic, staff-related, and patient-specific factors. It suggests a need to improve communication, staff support, administrative processes, financial counseling, emotional support integration, and discharge planning to minimize harm and create a patient-centered environment. Full article

Background and Objectives: Emotional intelligence (EI) plays a critical role in safeguarding the emotional and psychological well-being of healthcare workers, acting as a buffer against burnout, and influencing the quality of patient care. Despite its significance, there remains a need to understand how EI levels correlate with burnout and what factors predict burnout in high-stress healthcare environments. This study, conducted at King Khaled Hospital in Al-Majmaah, Saudi Arabia, aims to assess the EI levels of healthcare staff, to determine the relationship between EI and burnout, and to identify key predictors of burnout to inform targeted interventions for improving workforce resilience and patient outcomes. Materials and Methods: Both self-reporting and standardized tests were integrated using cross-sectional surveys to evaluate the EI of each participant and the burnout they experience by averaging the rating of a 30-item questionnaire, allowing comparison of the interaction between EI, burnout, and work factors. Results: A significantly moderate level of EI was identified, while a high level of well-being was associated with a low level of burnout, and a high level of emotionality was associated with a high level of burnout. Results indicated that high job demands, call rotation, or casual work, and insufficient staff support were organizational correlates of burnout. Conclusions: Improving EI with a focus on the well-being sub-dimension may prevent burnout, and, for that, the interventions must be specific at both personal and organizational levels. Full article

The influence of social media personalities has grown significantly, especially among youth audiences who spend substantial time on platforms like TikTok. The emergence and popularity of different types of social media influencers accelerated during the COVID-19 pandemic in many countries, including South Africa. In turn, this period also saw a surge in youth audiences following these influencers. This rapid growth of influencer followings among young people is largely driven by specific types of content that resonate with them, thus encouraging continued engagement. However, the benefits that these young followers gain from engaging with various influencers and the factors driving their preferences for specific influencers remain underexplored, particularly within the context of South African students within higher education. Therefore, this study explores the types of social media influencers most followed by university students at a South African University and investigates the key factors that drive their preferences. A structured online questionnaire was distributed, gathering both multiple-choice and open-ended responses from students. The data were analyzed using categorical frequency counts and thematic analysis. The data highlight how students actively turn to influencers as emotional anchors, role models, and sources of practical guidance. Their engagement reflects a deep need for connection, inspiration, and identity formation in a challenging academic and social environment. These patterns show that influencer content is not just entertainment but plays a critical developmental role. Understanding these motivations helps educators, policymakers, and brands to align better with youth values. The significance of these results lies in how influencer content is now coming in to fill the emotional, cultural, and educational gaps left by traditional systems among the young South African university students in this modern era. Full article

Brachycephalic head shape in dogs has been associated with behavioural traits that may enhance their appeal as companion animals, contributing to their popularity. However, it remains unclear whether these behavioural differences are directly linked to head shape or are mediated by factors such as body size, demographics, and dog-keeping practices. Drawing on two large-scale owner surveys (N = 5613) and cephalic index estimates for 90 breeds, we investigated the relationship between head shape and eight behavioural variables (four personality traits and four behavioural problems), while controlling for 20 demographic and dog-keeping characteristics, as well as body size. Our results show that behavioural differences among head shapes are only partly attributable to head shape itself; some are explained by confounding variables. Specifically, brachycephalic dogs appeared predisposed to positive behaviours (e.g., calmness, fewer behavioural problems), but these traits were often obscured by their small body size and low training experience. These findings highlight the complex interplay between morphology, behaviour, and environment, and emphasize the role of training and management in supporting the behavioural well-being of popular brachycephalic breeds. This has important implications for owners, breeders, and welfare professionals aiming to align aesthetic preferences with behavioural and welfare outcomes. Full article