Search Results (21,606)

Background/Objectives: Measures of excess body fat are often more informative for predicting health risk than body mass index (BMI) alone. With obesity prevalence increasing among young adults, this study evaluated whether adding dominant handgrip strength improves prediction of body fat percentage (BF%) and BF%-defined obesity in a university population. Methods: Cross-sectional data from 895 students (401 women, 494 men; mean age 19.9 years; fall 2015–spring 2016) in Kentucky, USA were analyzed. BMI was calculated from self-reported height and weight. BF% was estimated using bioelectrical impedance analysis (BIA), and dominant handgrip strength was measured with a hydraulic hand grip dynamometer. Sex-specific linear and logistic regression models assessed associations among BMI, grip strength, relative grip strength, and BF%. Results: BMI was a strong predictor of BF% in linear models (R² = 0.74 in women; 0.68 in men). Grip strength alone was not associated with BF% but showed an inverse association when combined with BMI. For BF%-defined obesity, BMI remained the most influential predictor, with grip strength contributing additional predictive value. Among men, age significantly modified these relationships, with marked differences between those aged 18–19 years versus older participants. Conclusions: BMI strongly predicted BF% and BF%-based obesity in this cross-sectional study of a predominantly white young adult population. Incorporating handgrip strength modestly improved classification, particularly among women, suggesting that a functional measure like hand grip strength may enhance obesity screening and health communication in young adults. Full article

Objectives: We aimed to evaluate the reliability and validity of the Arabic version of the Chronic Heart Failure Health-Related Quality of Life Questionnaire (CHFQOLQ-20) among patients with heart failure in Jordan. Methods: A cross-sectional study was conducted among 399 adults with heart failure recruited from a tertiary hospital in Jordan (median age 68 years; 55.9% male). The CHFQOLQ-20 was translated using forward–backward procedures. Construct validity was examined using confirmatory factor analysis (CFA) and a multidimensional Partial Credit Model. Differential item functioning by sex and internal consistency were assessed. Results: CFA supported the original four-domain structure (physical, cognitive, mental, and general health), with all items showing significant factor loadings. Item-level analyses demonstrated acceptable model fit, ordered response thresholds, and minimal sex-related bias. Physical health scores were lower than other domains. Conclusions: The Arabic CHFQOLQ-20 is a valid, reliable, and multidimensional measure of HRQoL in patients with heart failure, supporting its use in clinical practice and research. Full article

To develop secure, fast, and interoperable smart substations, it is vital to understand the current situation and potential future directions of the technologies involved. This study presents the evolution and state of the art of the Generic Object Oriented Substation Event (GOOSE) communication protocol, defined by the International Electrotechnical Commission (IEC) 61850 standard. A Systematic Literature Review (SLR) was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. This included journal articles published from 2004 to 2025 and conference papers from 2020 to 2025, written in English within Engineering. Only studies primarily focusing on GOOSE, citing it at least ten times, and indexed in the Scopus, IEEE Xplore, and Web of Science databases were included. The quantitative analysis used SciMAT software, complemented by a qualitative analysis. Due to the bibliometric and thematic nature of this review, potential biases were considered at the review level rather than by applying a formal study-level risk-of-bias tool. The final analysis comprised 82 journal articles and 84 conference papers. The results offer a comprehensive mapping of GOOSE research evolution, identify nine main challenges and limitations from the last 22 years, and highlight current research directions. The literature reveals methodological heterogeneity, a predominance of simulation-based approaches, and limited large-scale empirical validation. Full article

Vector–matrix multiplication (VMM), implemented through multiply–accumulate (MAC) operations, represents the dominant computational primitive in many artificial intelligence (AI) workloads. When executed on conventional von Neumann architectures, VMM operations suffer from important energy consumption and latency due to the separation between memory and processing units. To overcome these limitations, crossbar arrays built from Resistive Random Access Memory (RRAM) cells have been proposed for accelerating VMM computations. In this work, we investigate the key optimization trade-offs associated with implementing RRAM-based neural networks for classification applications. A simple two-layer neural network is first defined and trained in software to generate the weight matrices and bias parameters. Next, three hardware implementation scenarios are evaluated depending on whether negative floating-point numbers are used: Positive Weights Only (PWO), Positive and Negative Weights Only (PNWO), and Positive and Negative Weights with Biases (PNWB). The different implementations are analyzed at the hardware level by examining classification accuracy, energy efficiency, latency, and area overhead. The study further incorporates important RRAM limitations, including restricted conductance range and device variability. Hardware results show that the PWO scenario offers the lowest energy consumption (189 fJ/MAC) and area overhead but results in the lowest accuracy. PNWO and PNWB significantly improve accuracy (+177% and +180%) but increase energy consumption (+63% and +87%) and area (×2 and ×2.1). Under variability effects, PWO achieves better accuracy (94.65%), followed by PNWO (93.11%) and PNWB (92.11%). Full article

Recent global events have slowed progress toward achieving the Sustainable Development Goals (SDGs), making robust sustainability reporting (SR) systems critical for monitoring and corrective actions. While research on the link between corporate sustainability performance (CSP) and corporate financial performance (CFP) is extensive, the specific role of sustainability reporting as a communication channel remains insufficiently explored. Therefore, the objective of this paper is to address this gap in the literature by assessing the relevance of sustainability reporting for modeling the relationship between CSP and CFP. In this study, a univariate meta-analysis based on a PRISMA screening framework was performed to assess the unidirectional relationship between SR and CFP, specifically investigating whether SR acts as a moderating or mediating factor in the CSP-CFP nexus. The analysis is limited to 19 high-quality articles published in top-tier accounting journals between 2014 and 2024 to minimize publication bias and ensure reliability. The meta-analysis reveals no statistically significant moderating effect of SR on CFP. Instead, the results confirm a significant mediating effect, particularly when considering the presence of sustainability reports rather than just their specific content. These findings suggest that SR serves as a vital catalyst for corporate communication, providing more positive effects in voluntary compared to mandatory disclosure settings. This paper has both theoretical and practical implications, which are mainly relevant to standard-setters for assessing the efforts of SR disclosure regulation, and is of fundamental importance to managers as it indicates that SR does not relate solely to the practice of conformity, but rather to essential channels of communication and value creation. Full article

Micro-public space (MPS) regeneration is typically evaluated at the point of delivery, yet long-term performance depends on whether everyday stewardship can be sustained thereafter. This study reframes neighbourhood social capital as a governance–environment signal reflecting coordination capacity and examines whether residents’ willingness to participate in post-regeneration co-management is primarily appraisal-driven (perceived value, attitude, and perceived behavioural control) or coordination-driven via a residual direct channel consistent with routine governance. A cross-sectional survey of adults residing within walkable catchments of five regenerated MPS sites in Nan’an District, Chongqing, China ($N=477$), was conducted. An integrated Stimulus–Organism–Response × TPB model was estimated using WLSMV with ordered categorical indicators; indirect effects were assessed via bias-corrected bootstrap confidence intervals. Coordination capacity was strongly associated with perceived value, participation attitude, and perceived behavioural control. In the joint model, only perceived value retained a statistically reliable positive association with stewardship willingness, whereas the incremental contributions of attitude and perceived behavioural control were negligible once the stimulus was included. A residual direct association from coordination capacity to willingness persisted beyond the appraisal block, supporting a direct-dominant interpretation; bootstrap analyses yielded no robust evidence for mediation (BCa 95% CIs crossed zero). These findings suggest that sustaining regenerated micro-spaces requires low-friction governance designs that minimise coordination costs, reinforce soft accountability, and render institutional responsiveness visible to residents. Full article

Objective: This umbrella review synthesizes and critically appraises the evidence on the efficacy and safety of tegoprazan-based versus proton pump inhibitor (PPI)-based regimens for Helicobacter pylori (H. pylori) eradication. Methods: This umbrella review was pre-registered in PROSPERO (CRD420251271120). Systematic reviews and meta-analyses published between 1 January 2018 and 10 December 2025 were identified through MEDLINE/PubMed, EMBASE, and the Cochrane Library. Reviews comparing tegoprazan-based and PPI-based eradication regimens in adult patients were included. Methodological quality was assessed using AMSTAR-2, risk of bias with ROBIS, and certainty of evidence with GRADE. Pooled relative risks (RRs) were calculated, with subgroup analyses by study design, treatment duration, and therapeutic regimen. Results: Eight systematic reviews and meta-analyses encompassing 17 primary studies and 12,714 participants were included. Tegoprazan-based regimens were associated with a statistically significant improvement in eradication efficacy compared with PPI-based therapies (RR = 1.019; 95% CI: 1.003–1.035; p = 0.021). In randomized controlled trials, the benefit was more pronounced (RR = 1.037; 95% CI: 1.015–1.061; p = 0.001), whereas no statistically significant benefit was observed in non-randomized studies (RR = 1.014; 95% CI: 0.991–1.037; p = 0.235). The efficacy advantage was mainly confined to quadruple therapy regimens (RR = 1.044; 95% CI: 1.002–1.088; p = 0.038). Tegoprazan-based regimens were associated with a lower incidence of overall adverse events compared with the PPI group (RR = 0.930; 95% CI: 0.885–0.976; p = 0.003). Conclusions: Tegoprazan-containing regimens were associated with a modest but statistically significant improvement in H. pylori eradication compared with PPI-containing regimens, particularly in randomized controlled trials and quadruple therapy regimens. Full article

Social Network Analysis (SNA) has been widely applied to risk identification research. However, two key constraints, namely rating bias and the subjectivity of threshold selection, undermine the reliability and reproducibility of analytical results. To address this di-lemma, this study aims to construct a standardized and robust analytical framework for SNA-based risk identification. The core research objectives are as follows: elucidate the differential impact mechanism of threshold variation on the macro-topological structure and micro-level node ranking of risk networks, examine the cross-threshold robustness of core risk node rankings, and delimit the effective threshold range for stable risk identification. Accordingly, to fulfill the above objectives, this study proposes a multi-threshold robustness inspection method based on individual rating patterns, and conducts systematic empirical analysis with industrial projects in the post-support period of reservoir resettlement as research cases. The results indicate that threshold variation exerts marked systematic effects on the macro-topological structure of risk networks, whereas the relative rankings of core risk nodes remain robust. The effective threshold range for risk identification in such projects is α ∈ [0.1,0.3]. This study provides a repeatable quality control framework for SNA-based risk identification, with favorable cross-domain transferability. Full article

Cardiovascular diseases are a growing public health challenge in Ethiopia, worsened by limited access to diagnostics, including ECG, and shortages of specialized expertise. AI-powered ECG offers potential to improve diagnostic accuracy, efficiency, and access in resource-limited settings, but its adoption is influenced by policy, regulatory, financing, and governance factors, which are not well understood in Ethiopia. This study explored these system-level determinants using qualitative methods from September to October 2025 across federal institutions, four regions, and five tertiary hospitals. Twenty-five stakeholders, including policymakers, regulators, digital health experts, and hospital leaders, were interviewed. Data were transcribed verbatim, coded inductively, and analyzed thematically. Six themes emerged: policy and governance, regulatory frameworks, financing and cost considerations, data governance and bias, integration barriers, and sustainability recommendations. Findings showed AI-powered ECG interpretation aligns with Ethiopia’s digital health and noncommunicable disease priorities, but the country lacks AI-specific health policies, clear regulations, and dedicated budgets. Financing is largely donor-dependent, data governance and algorithmic bias remain concerns, and infrastructure gaps and digital skill shortages limit readiness. Study participants recommended learning from prior digital health projects, coordinated scale-up, phased implementation, and continuous monitoring. Effective adoption will require context-specific policies, sustainable financing, robust regulation, strong data governance, and careful system integration to ensure equitable, responsible, and sustainable use. Full article

Background/Objectives: Influenza remains a primary cause of severe illness and death in adults over 60. In this group, immunosenescence and existing health conditions make infections more dangerous and traditional vaccines less effective. The MF59-adjuvanted vaccine was specifically designed to overcome these limitations by enhancing the body’s immune activation and antigen presentation. While the vaccine shows clear benefits, some recent concerns regarding vaccine safety have been raised without supporting scientific evidence. Therefore, this systematic review focuses on providing a comprehensive evaluation of its safety outcomes compared to standard vaccines. Methods: Following the PRISMA guidelines, a systematic review and meta-analysis were conducted; two researchers independently assessed the eligibility of the studies, and the risk of bias was assessed using RoB2 and ROBINS tools for randomized clinical trials and observational studies, respectively. Pooled risk estimates were calculated using a random-effects model. Results: Ten RCTs and three non-RCTs meeting the inclusion criteria were included. No significant differences were found for severe systemic outcomes: Guillain–Barré syndrome (RR 1.01, 95% CI 0.64–1.80) and encephalitis (RR 1.23, 95% CI 0.85–1.78). For other systemic adverse effects, there were no significant differences between adjuvanted and non-adjuvanted vaccines; only myalgia showed a small but significant increase with adjuvanted vaccines (RR 1.35, 95% CI 1.02–1.78) compared with non-adjuvanted vaccines. Conclusions: MF59-adjuvanted influenza vaccines have a favorable and well-characterized safety profile in adults aged 60 years and older. Adverse events are predominantly mild and transient, with no evidence of increased risk of serious or immune-mediated outcomes compared with non-adjuvanted vaccines. Full article

Spaceborne LiDAR systems, such as ICESat-2, provide critical data for global land cover and topography; however, their performance in rugged, vegetated landscapes requires rigorous local validation. This study evaluates the vertical accuracy of ICESat-2 ATL08 terrain height metrics in the complex Turkish Western Black Sea region, utilizing a reference dataset of high-precision terrestrial GNSS measurements. Following strict IQR-based outlier detection and photon density filtering, 1637 spatially matched segments were analyzed. The h_te_best_fit terrain height metric showed the best agreement with the terrestrial GNSS reference data, yielding an RMSE of 3.37 m and a mean bias of −0.42 m, indicating a slight underestimation of the terrain surface. The univariate analysis revealed a strong positive correlation between terrain slope and vertical error, indicating that slope is the prominent degradation factor contributing to pulse broadening. Additionally, dense forest cover was found to limit ground photon retrieval, leading to increased error margins, whereas nighttime acquisitions offered slightly improved precision. These findings suggest that while ATL08 is a valuable topographic source, slope-dependent corrections are essential for applications in mountainous environments. Full article

This study examines the historical and anticipated effects of climate change on essential hydroclimatic variables (temperature, precipitation, evapotranspiration, and soil moisture) in the Southeastern Anatolia Project (GAP) region of Türkiye, a semi-arid and agriculturally significant basin experiencing heightened water stress. The analysis employs a collection of CMIP6 Global Climate Models (GCM) and integrates three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), utilizing statistical bias correction methods such as Delta Change, Quantile Mapping (QM), and Empirical Quantile Mapping (EQM) to improve the regional accuracy of the projections. The ACCESS-CM2 model, validated with data from Türkiye’s Meteorological General Directorate (MGM), was chosen for comprehensive spatial mapping, utilizing Inverse Distance Weighting (IDW) interpolation across seven temporal intervals encompassing past, present, and future periods. The findings indicate a steady increase in temperature and evapotranspiration, especially under high-emission scenarios, with temperature rises above +4 °C and considerable water losses anticipated by century’s end. Soil moisture exhibits a declining tendency, particularly in the southern and eastern regions, signifying increasing drought susceptibility. Precipitation patterns demonstrate significant spatial variability and rising uncertainty, with relative error (RE%) values increasing under SSP5-8.5. Historical data from 1963 to 2022 corroborate these conclusions, indicating a progressive shift towards a warmer and drier regional climate. These observations highlight the importance of climate adaptation strategies and water management in the GAP region. The research provides decision-makers a high-resolution, bias-corrected hydroclimatic dataset. Full article

Background/Objectives: Stroke is a sudden neurological event caused by disrupted cerebral blood flow and represents a leading cause of acquired disability worldwide. Motor impairments and spasticity are among the most prevalent sequelae, significantly limiting functional independence and quality of life. Non-invasive electrotherapy has emerged as a complementary strategy in neurorehabilitation aimed at enhancing neuroplasticity and improving motor recovery. To systematically review current evidence regarding the effectiveness of non-invasive electrotherapy modalities in the rehabilitation of motor sequelae and spasticity following stroke, and to examine their theoretical and clinical rationale. Methods: A systematic literature review was conducted in accordance with PRISMA 2020 guidelines. The protocol was prospectively registered in the Open Science Framework (OSF). A comprehensive search was performed in Pubmed, Web of Science (WoS), and Scopus for studies published up to 14 November 2023, using the terms “Electric Stimulation Therapy” and “Stroke”. The methodological quality was assessed using the PEDro scale. The levels of evidence were classified according to the Oxford Centre for Evidence-Based Medicine criteria, and the risk of bias was evaluated using the Cochrane Risk of Bias tool (RoB 2). Results: Sixteen studies were included in the review. The analyzed interventions comprised neuromuscular electrical stimulation (NMES), transcutaneous electrical nerve stimulation (TENS), functional electrical stimulation (FES), neuromuscular electrical stimulation combined with transcranial magnetic stimulation (NMES + rTMS), transcranial direct current stimulation (tDCS), and afferent electrical stimulation (AES). Overall, the methodological quality of the included studies ranged from moderate to high, with PEDro scores between 6 and 9 out of 10. According to the Oxford Centre for Evidence-Based Medicine classification, most studies corresponded to level 1b evidence, while a smaller proportion were classified as level 2b. A risk of bias assessment using the Cochrane RoB 2 tool showed that the majority of the included studies presented a low risk of bias across most domains, although some concerns were identified in the domains of randomization and measurement in a limited number of trials. Across modalities, consistency within group improvement in motor function and spasticity was reported. However, between group comparisons with conventional rehabilitation were often inconsistent and did not consistently demonstrate superiority. The variability in stimulation parameters, intervention duration, and outcome measures further limited direct comparisons across studies. Conclusions: Non-invasive electrotherapy appears to be a safe and promising adjunct to conventional stroke rehabilitation. Nevertheless, further high-quality studies are required to clarify the underlying neurophysiological mechanisms and to establish standardized treatment protocols. Full article

This paper introduces a new family of distributions called exponentiated Harris-G. This new distribution is a weighted distribution of the well established exponentiated-G distributions. The model allows for easy derivation of statistical properties based on the exponentiated-G distribution. Several statistical properties for the new model were derived. The paper considered different parameter estimation techniques and the maximum likelihood estimation technique emerged as the best technique. This was evaluated via Monte Carlo simulation studies of the proposed family. Estimation techniques were ranked based on the lowest values of the root mean square error and average bias. The proposed model showed enhanced flexibility in data modeling when compared to some selected competing models. This was demonstrated through application of the special case to two real-world datasets. Full article

The ongoing substance use crisis in the United States involves a broad range of illicit and prescription drugs, including opioids, stimulants, sedatives, and various psychoactive and non-psychoactive compounds. Traditional surveillance methods rely on self-reported data, which could lead to bias and recall inconsistencies. Wastewater-based epidemiology has emerged as a powerful, non-invasive tool for monitoring community-level drug use, offering near real-time estimates and the potential to serve as an early warning system. However, challenges such as analyte degradation, wastewater variability, and matrix effects can affect data quality and comparability across regions. This study presents a standardized, practical workflow for multi-drug (n = 52) detection in wastewater, aiming to minimize analyte loss and improve reproducibility. Composite samples were collected from multiple U.S. cities, transported on ice, and extracted using solid-phase extraction. Extraction efficiencies were compared using Oasis Hydrophilic-Lipophilic-Balanced and Mixed-mode Cation-Exchange (MCX) cartridges, with the MCX sorbent providing complementary reversed-phase and cation-exchange interactions that enabled the retention of chemically diverse compounds across multiple drug classes. Analysis was performed with an Ultra-High-Performance Liquid Chromatography system coupled to a triple quadrupole mass spectrometer, in which the instrument parameters and critical methodological considerations, including sample handling, transport, column selection, and method validation, are detailed. This work contributes to the development of a robust, scalable protocol for multi-drug surveillance in wastewater, supporting timely, data-driven public health responses and informing national drug policy efforts. Full article