Search Results (19,255)

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative porcelain sheathing system for cold-formed steel (CFS) shear walls. Porcelain has no veins thus it offers integrated and reliable strength unlike granite. Four full-scale CFS shear walls incorporating screwed porcelain sheathing (SPS) were tested under combined cyclic lateral and constant gravity loading. The experimental program investigated key seismic characteristics, including lateral stiffness and strength, deformation capacity, failure modes, and energy dissipation, to calculate the system response modification factor (R). The test results showed that configurations with horizontal sheathing, double mid-studs, and three blocking rows improved performance, achieving up to 21.1 kN lateral resistance and 2.5% drift capacity. The average R-factor was 4.2, which exceeds the current design code values (AISI S213: R = 3; AS/NZS 4600: R = 2), suggesting the enhanced seismic resilience of the SPS-CFS system. This study also proposes design improvements to reduce the risk of brittle failure and enhance inelastic behavior. In addition, the results inform discussions on permissible building heights and contribute to the advancement of CFS design codes for seismic regions. Full article

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

Background/Objectives: Despite legal frameworks acknowledging the need to protect the rights of female prisoners, penitentiary systems often neglect gender-specific needs, particularly for foreign women. Among them, Muslim women face distinct challenges linked to cultural and religious practices, which are frequently unmet in prison contexts. This review aims to explore the academic literature on the experiences of Muslim women in detention. Methods: A systematic review was conducted using three major bibliographic databases—Scopus, PubMed, and Web of Science—covering the period from 2010 to 2024. Inclusion criteria focused on peer-reviewed studies examining the condition of Muslim women in prison. Of the initial pool, only four articles met the criteria and were included in the final analysis. Results: The review reveals a marked scarcity of research on Muslim women in prison at both national and international levels. This gap may be due to their limited representation or cultural factors that hinder open discourse. The selected studies highlight key issues, including restricted access to services, limited ability to practice religion, and language and cultural barriers. These challenges contribute to increased psychological vulnerability, which is often underestimated in prison settings. Conclusions: There is an urgent need for targeted research and culturally competent training for prison staff to adequately support Muslim women in detention. Greater academic and institutional attention is essential to develop inclusive policies that consider the intersection of gender, religion, and migration, particularly in the post-release reintegration process. Full article

Background and Objectives: There is a global rise of public interest in integrative medicine. The principles of integrative medicine combining conventional medicine with evidence-based complementary therapies have been implemented in many medical areas, including plastic surgery, to improve patient’s outcome. The aim of the present study was to systematically analyze the application and use of additional non-pharmacological interventions (NPIs) of patients of a German department of plastic surgery. Materials and Methods: The present real-world data study utilized data from the Network Oncology registry between 2016 and 2021. Patients included in this study were at the age of 18 or above, stayed at the department of plastic surgery and received at least one plastic surgical procedure. Adjusted multivariable logistic regression analyses were performed to detect associations between the acceptance of NPIs and predicting factors such as age, gender, year of admission, or length of hospital stay. Results: In total, 265 patients were enrolled in the study between January 2016 and December 2021 with a median age of 65 years (IQR: 52–80) and a male/female ratio of 0.77. Most of the patients received reconstructive surgery (90.19%), followed by hand surgery (5.68%) and aesthetic surgery (2.64%). In total, 42.5% of the enrolled patients accepted and applied NPIs. Physiotherapy, rhythmical embrocations, and compresses were the most often administered NPIs. Conclusions: This exploratory analysis provides a descriptive overview of the application and acceptance of NPIs in plastic surgery patients within a German integrative care setting. While NPIs appear to be well accepted by a subset of patients, further prospective studies are needed to evaluate their impact on clinical outcomes such as postoperative recovery, pain management, patient-reported quality of life, and overall satisfaction with care. Full article

Detecting previously unseen anomalies in sensor data is a challenging problem for artificial intelligence when sensor-specific and deployment-specific characteristics of the time series need to be learned from a short calibration period. From the application point of view, this challenge becomes increasingly important because many applications are gravitating towards utilising low-cost sensors for Internet of Things deployments. While these sensors offer cost-effectiveness and customisation, their data quality does not match that of their high-end counterparts. To improve sensor data quality while addressing the challenges of anomaly detection in Internet of Things applications, we present an anomaly detection framework that learns a normality model of sensor data. The framework models the typical behaviour of individual sensors, which is crucial for the reliable detection of sensor data anomalies, especially when dealing with sensors observing significantly different signal characteristics. Our framework learns sensor-specific normality models from a small set of anomaly-free training data while employing an unsupervised feature engineering approach to select statistically significant features. The selected features are subsequently used to train a Local Outlier Factor anomaly detection model, which adaptively determines the boundary separating normal data from anomalies. The proposed anomaly detection framework is evaluated on three real-world public environmental monitoring datasets with heterogeneous sensor readings. The sensor-specific normality models are learned from extremely short calibration periods (as short as the first 3 days or 10% of the total recorded data) and outperform four other state-of-the-art anomaly detection approaches with respect to F1-score (between 5.4% and 9.3% better) and Matthews correlation coefficient (between 4.0% and 7.6% better). Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

HIV infection and hypertensive disorders of pregnancy (HDP), particularly preeclampsia (PE) with severe features, are leading causes of maternal mortality worldwide. This study investigates the role of asymmetric dimethylarginine (ADMA) and prostacyclin (PGI2) concentrations in endothelial impairment in normotensive pregnant versus PE women within an HIV endemic setting in KwaZulu-Natal Province, South Africa. The study population (n = 84) was grouped according to pregnancy type, i.e., normotensive (n = 42) and PE (n = 42), and further stratified by HIV status. Clinical factors were maternal age, weight, blood pressure (both systolic and diastolic) levels, and gestational age. Plasma concentrations of ADMA and PGI2 were measured using the enzyme-linked immunoassay (ELISA). Differences in outcomes were analyzed using the Mann–Whitney U and Kruskal–Wallis test together with Dunn’s multiple-comparison post hoc test. The non-parametric data were presented as medians and interquartile ranges. Gravidity, gestational age, and systolic and diastolic blood pressures were significantly different across the study groups where p < 0.05 was deemed significant. Furthermore, the concentration of ADMA was significantly elevated in PE HIV-positive vs. PE HIV-negative (p = 0.0174) groups. PGI2 did not show a significant difference in PE compared to normotensive pregnancies (p = 0.8826) but was significantly different across all groups (p = 0.0212). An increase in plasma ADMA levels was observed in the preeclampsia HIV-negative group compared to the normotensive HIV-negative group. This is linked to the role played by ADMA in endothelial impairment, a characteristic of PE development. PGI2 levels were decreased in PE compared to the normotensive group regardless of HIV status. These findings draw attention to the importance of endothelial indicators in pathogenesis and possibly early prediction of PE development. 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

Effective water infrastructure planning and management is key to sustainable water supply globally. This research assesses water infrastructure planning and management in Gauteng, South Africa, amid growing challenges from rapid urbanisation, high water demand, climate change, and resource scarcity. These challenges threaten the achievement of Sustainable Development Goals 6 and 11; hence, an integrated approach is required for water sustainability. The study responds to a gap in the literature, which often treats planning and management separately, by adopting an integrated, multi-institutional approach across the water value chain. A mixed-methods triangulation strategy was employed for data collection whereby surveys provided quantitative data, while two sets of structured interviews were conducted: the first round to determine causal relationships among the critical success factors and the second round to validate the proposed framework. The findings reveal a misalignment between infrastructure planning and implementation, contributing to infrastructure backlogs and a short- to medium-term focus. Infrastructure management is further constrained by inadequate system redundancy, leading to ineffective maintenance. External factors such as delayed adoption of 4IR technologies, lack of climate resilient strategies, and fragmented institutional coordination exacerbate these issues. Using Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis, the study identified Strategic Alignment and a Value-Driven Approach as the most influential critical success factors in water asset management. The research concludes by proposing an integrated water infrastructure and planning framework that supports sustainable water supply. Full article

Wireless sensor networks (WSNs) have attracted significant attention due to their widespread applications in various fields such as environmental monitoring, agriculture, intelligent transportation, and healthcare. In these networks, the power cost of a sensor node is closely related to the radius of its coverage area, following a nonlinear relationship where power increases as the coverage radius grows according to an attenuation factor. This means that increasing the coverage radius of a sensor leads to a corresponding increase in its power cost. Consequently, minimizing the total power cost of the network while all clients are served has become a crucial research topic. The power cover problem focuses on adjusting the power levels of sensors to serve all clients while minimizing the total power cost. This survey focuses on the power cover problem and its related variants in WSNs. Specifically, it introduces nonlinear integer programming formulations for the power cover problem and its related variants, all within the specified sensor setting. It also provides a comprehensive overview of the power cover problem and its variants under both specified and unspecified sensor settings, summarizes existing results and approximation algorithms, and outlines potential directions for future research. Full article

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

Air pollution is linked to childhood mortality and morbidity in low- and middle-income countries globally. There is growing evidence linking air pollution to asthma and other respiratory diseases in children. Studies have shown that children are likely to experience asthma due to their narrow airways and their heightened sensitivity to environmental irritants. This study aims to investigate the relationship between ambient air pollution and respiratory diseases in children under the age of 5. The study will be conducted in the informal township of Alexandra, north of Johannesburg, South Africa. A quantitative approach will be used in this cross-sectional analytical study. Data will be collected using different tools that include a questionnaire to determine the prevalence of asthma and respiratory disease and potential risk factors. While environmental air pollution will be measured using Radiello passive samplers and Gillian pumps. Data will be analyzed using the latest version of the STATANow/MP 19.5 software. Furthermore, health risk assessment will be conducted for lifetime non-carcinogenic and carcinogenic risk estimation following the USEPA framework. The study will identify environmental triggers that exacerbate asthma and other respiratory conditions in other similar community settings and will contribute to the body of knowledge in public health. Ethical approval was obtained from the Research Ethics Committee, Faculty of Health Sciences at the University of Johannesburg. Full article

Background: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. While most diagnoses occur in outpatient settings, a subset of cases are incidentally identified during emergency department (ED) visits. The clinical characteristics and treatment decisions of these patients, particularly in relation to social background factors such as living situation and access to primary care, remain poorly understood. Methods: We conducted a retrospective study of patients diagnosed with malignancies in the ED of a single institution between April 2018 and December 2021. Patients diagnosed with lung cancer within 60 days of an ED visit were included. Data on demographics, disease status, treatment decisions, and background factors—including whether patients lived alone or had a primary care physician (PCP)—were extracted and analyzed. Results: Among 32,108 patients who visited the ED, 148 were diagnosed with malignancy within 60 days; 23 had lung cancer. Of these, 69.6% had metastatic disease at diagnosis, and 60.9% received active treatment (surgery or chemotherapy). No significant associations were observed between the extent of disease and either living arrangement or PCP status. However, the presence of a PCP was significantly associated with the selection of best supportive care (p = 0.023). No significant difference in treatment decisions was observed based on age (cutoff: 75 years). Conclusions: Although social background factors such as living alone were not significantly associated with cancer stage or treatment choice, the presence of a primary care physician was associated with a higher likelihood of best supportive care being selected. This may indicate that patients with an established PCP have more clearly defined care goals at the end of life. These findings suggest that primary care access may play a role in shaping end-of-life care preferences, highlighting the importance of personalized approaches in acute oncology care. Full article

Background/Objectives: Antibiotic use is common among hospitalized pediatric patients. However, inappropriate use, including excessive use of Watch antibiotics, can contribute to antimicrobial resistance, adverse events, and increased healthcare costs. Consequently, there is a need to continually assess their usage among this vulnerable population. This was the objective behind this study. Methods: The medical records of all pediatric patients (under 12 years) admitted and treated with antibiotics at a Ghanaian Teaching Hospital between January 2022 and March 2022 were extracted from the hospital’s electronic database. The prevalence and appropriateness of antibiotic use were based on antibiotic choices compared with current guidelines. Influencing factors were also assessed. Results: Of the 410 admitted patients, 319 (77.80%) received at least one antibiotic. The majority (68.65%; n = 219/319) were between 0 and 2 years, and males (54.55%; n = 174/319). Ceftriaxone was the most commonly prescribed antibiotic (20.69%; n = 66/319), and most of the systemic antibiotics used belonged to the WHO Access and Watch groups, including a combination of Access and Watch groups (42.90%; n = 136/319). Neonatal sepsis (24.14%; n = 77/319) and pneumonia (14.42%; n = 46/319) were the most common diagnoses treated with antibiotics. Antibiotic appropriateness was 42.32% (n = 135/319). Multivariate analysis revealed ceftriaxone prescriptions (aOR = 0.12; CI = 0.02–0.95; p-value = 0.044) and surgical prophylaxis (aOR = 0.07; CI = 0.01–0.42; p-value = 0.004) were associated with reduced antibiotic appropriateness, while a pneumonia diagnosis appreciably increased this (aOR = 15.38; CI = 3.30–71.62; p-value < 0.001). Conclusions: There was high and suboptimal usage of antibiotics among hospitalized pediatric patients in this leading hospital. Antibiotic appropriateness was influenced by antibiotic type, diagnosis, and surgical prophylaxis. Targeted interventions, including education, are needed to improve antibiotic utilization in this setting in Ghana and, subsequently, in ambulatory care. Full article

To achieve the goals of productivity and sustainability across diverse livestock systems, reproductive factors play a pivotal role. Historically, reproductive research has primarily focused on females, as they are responsible for maintaining pregnancy and delivering offspring following oocyte fertilization. However, since the early 2000s, the biological significance of sperm RNAs has been increasingly recognized in various livestock species. These RNAs contribute both genetically and epigenetically at the time of fertilization and during early embryonic development. Multiple types of sperm RNA have been identified in bovine, porcine, ovine, buffalo, and caprine spermatozoa. Notably, transcriptomic profiling has shown potential to differentiate between high- and low-fertility males, even when conventional semen quality values appear normal in both groups. This opens the possibility for more accurate identification of highly fertile sires. Nevertheless, a definitive marker or set of markers has yet to be established, likely due to the transcriptome’s sensitivity to environmental conditions and to the variability in evaluation methodologies. Therefore, global scientific efforts should aim to establish standardized, robust protocols, as sperm RNA represents a promising avenue for enhancing the sustainability of animal production systems. Full article