Search Results (18,057)

Background: Reducing salt in bread is considered a straightforward, cost-effective public health intervention and is implemented in several countries, either voluntarily or through legislation. A Memorandum of Understanding (MoU) was signed in Greece in 2016, setting a voluntary maximum salt content of 1.2% in artisanal bread. This study aimed to evaluate the effectiveness of the MoU and assessed the potential impact of reducing salt in bread on overall salt intake, using the MoU target and the relevant WHO global sodium benchmark. Methods: Artisanal bread samples (n = 253) randomly collected from different parts of Greece in 2024 were analyzed for salt content and compared with samples collected in 2012 (n = 220). Salt intake from bread was estimated using data from the Hellenic National Nutrition and Health Survey (HNNHS), and modeling scenarios were conducted. Results: The MoU and related voluntary awareness activities were ineffective as a strategy to reduce salt in bread. The mean salt content in bread in 2024 was 1.41 (0.30)%, representing a 6.8% increase compared to 1.32 (0.31)% in 2012. Only 19.4% of samples in 2024 contained ≤1.2% salt, compared to 31.8% in 2012. Full MoU compliance would enable an additional 3.1% of Greek bread consumers, currently exceeding 5 g in their daily salt intake from foods alone, to reduce their intake to below 5 g. This would rise to 6.2% if the WHO sodium benchmark was implemented. Conclusions: A mandatory salt limit, aligned with the WHO global benchmark, is urgently needed to support national reformulation strategies. This work can contribute to European and international discussions on food reformulation. Full article

This paper reviews and analyzes three types of vertical-axis wind rotors: the classic Savonius, spiral Savonius, and Darrieus designs. Using numerical modeling methods, including computational fluid dynamics (CFD), their aerodynamic characteristics, power output, and efficiency under different operating conditions are examined. Key parameters such as lift, drag, torque, and power coefficient are compared to identify the strengths and weaknesses of each rotor. Results highlight that the Darrieus rotor demonstrates the highest efficiency at higher wind speeds due to lift-based operation, while the spiral Savonius offers improved stability, smoother torque characteristics, and adaptability in turbulent or low-wind environments. The classic Savonius, though less efficient, remains simple, cost-effective, and suitable for small-scale urban applications where reliability is prioritized over high performance. In addition, the study outlines the importance of blade geometry, tip speed ratio, and advanced materials in enhancing rotor durability and efficiency. The integration of modern optimization approaches, such as CFD-based design improvements and machine learning techniques, is emphasized as a promising pathway for developing more reliable and sustainable vertical-axis wind turbines. Although the primary analysis relies on numerical simulations, the observed performance trends are consistent with findings reported in experimental studies, indicating that the results are practically meaningful for design screening, technology selection, and siting decisions. Unlike prior studies that analyze Savonius and Darrieus rotors in isolation or under heterogeneous setups, this work (i) establishes a harmonized, fully specified CFD configuration (common domain, BCs, turbulence/near-wall treatment, time-stepping) enabling like-for-like comparison; (ii) couples the transient aerodynamic loads p(θ,t) into a dynamic FEA + fatigue pipeline (rainflow + Miner with mean-stress correction), going beyond static loading proxies; (iii) quantifies a prototype-stage materials choice rationale (aluminum) with a validated migration path to orthotropic composites; and (iv) reports reproducible wake/torque metrics that are cross-checked against mature models (DMST/actuator-cylinder), providing design-ready envelopes for small/medium VAWTs. Overall, the work provides recommendations for selecting rotor types under different wind conditions and operational scenarios to maximize energy conversion performance and long-term reliability. Full article

The paper focuses on exploring ways to achieve sustainability in the manufacturing process through targeted optimization and ergonomic improvements of the work environment. The introductory section emphasizes the importance of sustainability from the perspectives of worker well-being, occupational safety, and efficient resource utilization. The paper presents a digital approach to workstation design with an emphasis on sustainability, which includes the creation of a 3D model of the assembly station using SolidWorks (v.2017) and Jack software (v.8.3), where the work movements of a virtual mannequin with realistic parameters are simulated. The analytical section is dedicated to evaluating workstation ergonomics using the RULA (Rapid Upper Limb Assessment), SSP (Static Strength Prediction), OWAS (Ovako Working Posture Analysis), and Lower Back Analysis methods, with the aim of identifying operations that reduce the sustainability of the work process due to excessive physical strain. Badly designed operations have a negative impact on sustainability in the meaning of physical workload strain (social dimension), low effectivity and quality (economic dimension), and higher resource (material, energy, transport, etc.) usage (environmental dimension). All these dimensions can be measured and expressed by number, but this paper focuses on workload only. Based on the results, specific measures were proposed with a focus on sustainability—raising the working height of pallets, optimizing the positioning of tools, and adjusting work movements. Repeated analyses after the implementation of these changes confirmed not only a reduction in physical strain and increased safety but also the enhancement of the sustainability of the working environment and processes. The results of the article clearly demonstrate that digital simulation and ergonomic design, oriented toward sustainability, are of crucial importance for the long-term efficiency and sustainable development of manufacturing organizations. The novelty of the work is in contribution to empirical validation on the role of digital twins, virtual ergonomics, and human factors in Industry 5.0 contexts, where the synergy between technological efficiency and human-centric sustainability is increasingly emphasized. The proposed approach represents a practical model for further initiatives aimed at improving the sustainability of assembly workstations. Full article

Eight diffusion couples were fabricated to systematically investigate the composition-dependent interdiffusion behavior in hcp Dy-Y, Dy-Nd, Sm-Nd, and Sm-Tb binary alloys. The interdiffusion coefficients were determined at two representative temperatures using the Sauer–Freise method based on concentration–distance profiles measured by electron probe microanalysis (EPMA). These experimentally obtained diffusivities, together with available thermodynamic data, were subsequently employed to assess the atomic mobilities of each system by means of the CALTPP (CALculation of Thermo Physical Properties) program within the CALPHAD (CALculation of PHAse Diagrams) framework. The optimized mobility parameters provide a reliable description of the diffusion behavior in all investigated alloys. This reliability is confirmed by the close agreement between the calculated and experimentally measured interdiffusion coefficients, as well as by the strong consistency between the model-predicted and experimental concentration profiles. The present work thus establishes the first set of critically evaluated atomic mobility parameters for these hcp rare-earth binary systems. These results fill an important gap in the kinetic database of rare-earth alloys and lay a robust foundation for future multi-component CALPHAD-based simulations, thereby supporting the design and optimization of advanced rare-earth permanent magnets with improved coercivity and thermal stability. Full article

Recent work on theological reflection on the phenomenon of human grief has called for an apophatic posture, one that resists speaking positively about what grief is, what grief does, or where it is situated with respect to the economy of God’s works. Grief, on this account, is viewed as inaccessible to theological inquiry and illogical in nature. This essay references recent work in psychological science to offer “theological fragments” on the nature of grief with the respect to the generational self’s journey in the “time of weeping.” In so doing, it argues that an integration of theological and psychological science provides a framework for describing grief in a way that resists the temptation to ascribe positive meaning or value to it in the reconciling work of God. Full article

Research on surfaces generated by curves plays a central role in linking differential geometry with physical applications, especially following Hasimoto’s transformation and the development of Hasimoto-inspired surface models. In this work, we introduce a new class of such surfaces, referred to as RM Hasimoto surfaces, constructed by employing the rotation-minimizing (RM) Darboux frame along both timelike and spacelike curves in Minkowski 3-space ${\mathbb{E}}_1^3$. In contrast to the classical Hasimoto surfaces defined via the Frenet or standard Darboux frames, the RM approach eliminates torsional difficulties and reduces redundant rotational effects. This leads to more straightforward expressions for the first and second fundamental forms, as well as for the Gaussian and mean curvatures, and facilitates a clear classification of key parameter curves. Furthermore, we establish the associated evolution equations, analyze the resulting geometric invariants, and present explicit examples based on timelike and spacelike generating curves. The findings show that adopting the RM Darboux frame provides greater transparency in Lorentzian surface geometry, yielding sharper characterizations and offering new perspectives on relativistic vortex filaments, magnetic field structures, and soliton behavior. Thus, the RM framework opens a promising direction for both theoretical studies and practical applications of surface geometry in Minkowski space. Full article

This study focuses on the experiences of female Paralympic athletes in Brazil through the lens of feminist disability studies. It is a qualitative study, grounded in the voices of disabled women, positioning them as the foundation of knowledge within a post-structuralist epistemological framework. The research involved in-depth interviews with four Brazilian Female Paralympians, conducted using a predefined interview guide, and the data were analyzed using thematic content analysis. The athletes were between 25 and 34 years of age and had experience competing in international competitions. From their narratives, two distinct yet interconnected categories emerge: (1) Being a disabled woman and (2) Like sportswomen. Disabled women have shown that they navigate an ableist and sexist society as disabled women within the context of sport; at the same time, they embody an empowered and inspirational identity as sportswomen. By exploring these perspectives, this study highlights the need to challenge and redefine societal perceptions and expectations surrounding disability. It provides insights into the experiences and agency of female Paralympic athletes. Full article

This study quantified mercury (Hg) levels in the body hair of domestic and wild animals in four Brazilian states, Paraná, Mato Grosso do Sul, Goiás, and Minas Gerais, by analyzing 169 samples from sows, piglets, free-range pigs, and wild animals. The highest mean Hg concentration (274.93 ± 48.14 µg/kg) was found in wild animals in the Pantanal (MSSilvestre, Mato Grosso do Sul), followed by Minas Gerais (245.09 ± 40.27 µg/kg) and Paraná (193.0 ± 42.45 µg/kg). Levels at the GO, MGM, MSLiv, and PRV sites were significantly lower (p ≤ 0.05), according to the Scott–Knott test. Statistical analysis using ANOVA indicated significant variation in Hg levels between locations (F = 2.36; p ≤ 0.05), with homogeneity of variance (Levene’s test, p = 0.1772). Animals raised in confinement had lower levels than wild animals, which, due to extensive movement and contact with diverse environments, exhibited greater bioaccumulation. Lactating sows showed greater sensitivity than piglets, demonstrating an effect of animal category on metal absorption. The main sources of mercury are anthropogenic activities, such as mining and industrial processes, responsible for the environmental release of the metal. Although the detected levels do not pose an immediate risk to animal health or meat quality, they highlight the need for continuous monitoring, given mercury’s ability to bioaccumulate and affect ecosystems and food security. This work contributes to the understanding of environmental exposure to mercury in Brazil, reinforcing the urgency of effective mitigation strategies to preserve biodiversity and public health. Full article

(1) Background/Purpose: Our research focuses on stakeholders’ attitudes in the Slovak SME sector, which we assessed through a questionnaire. The ability to evolve and adapt continuously is critical for micro-enterprises in competitive markets. (2) Study Design/Methodology/Approach: The primary objective of our research is to gain a comprehensive understanding of the new work organization processes in SMEs operating in a rapidly changing economic environment. Our research employed a single-sample cross-sectional sampling method, wherein respondents completed a questionnaire within a defined time frame. The primary data collection was carried out using a questionnaire containing closed questions. The research assesses the opinions of the respondents regarding the problem under study over a given period of time. The survey was conducted online. (3) Findings: 31% of the companies surveyed considered that introducing new work organization processes would make the company more adaptable to the changing economic environment. Only one-third considered involving employees in the processes the most important means to achieve this. Higher employee satisfaction is reported as a positive by 24% of companies. However, only a quarter of them believe the best way to achieve this is to involve employees in processes. For micro-enterprises, limited resources and smaller staff prioritize effective communication, and gaps can cause significant difficulties. Regarding the sample examined, among the hypotheses based on the literature background, we were only able to accept hypothesis H3 with modifications, which states that the biggest challenge for micro-companies in the industrial sector in a competitive market is understanding new technologies when improving employee skills. (4) Originality/Value: The research shows that micro-enterprises are particularly sensitive to the challenges associated with new technologies, which can be important information for designing training programs and developing support strategies for enterprises. Full article

Simulation is widely used in healthcare, with VR simulation replacing physical scenarios with virtual ones. Participants observe based on predefined learning objectives and reflect on them during debriefing sessions. De-escalation is recommended as the first-line response to potential aggression in mental healthcare. Staff in secure mental health units frequently face aggression, and training may enhance de-escalation skills. The study aimed to explore staff experiences with VR simulation as a supplement to physical simulation for de-escalation and examine differences between those with and without prior physical simulation experience. The study involved 58 frontline staff in a Norwegian high security secure mental health department. Twelve simulations were conducted, followed by a post-simulation questionnaire. Data was analyzed using thematic analysis and appropriate statistical analyses. Departmental and data protection approvals were obtained, and participation was based on informed consent. Two themes emerged: (1) enhances situational understanding, and (2) lack of training for action readiness. Participants rated the simulation highly on most questions and perceived VR simulation as a valuable supplement to physical simulation. Those without prior simulation experience were more satisfied with the VR scenario (mean difference = 0.421, 2-sided 95%CI = 0.036–0.807, t = 2.188, p = 0.033), learned more from the VR simulation (mean difference = 0.725, 2-sided 95%CI = 0.045–1.406, t = 2.136, p = 0.037), experienced VR scenario which was more applicable to clinical work (mean difference = 0.645, 2-sided 95% CI = 0.161–1.128, t = 2.674, p = 0.010), and reflected that the VR simulation increased their experienced safety (mean difference = 1.133. 95%CI = 0.478–1.788, t = 3.468, p = 0.001). Greater benefits were yielded from the VR simulation for those without prior simulation experience than those with previous experience. Further studies are recommended. Full article

Background: Dementia refers to a spectrum of clinical conditions characterized by impairments in memory, language, and cognitive function. Alzheimer’s Disease (AD) is the most common cause of dementia and it accounted for 60–70% of the estimated 57 million cases worldwide as of 2021. The exact pathology of this neurodegenerative condition is not fully understood. While it is currently incurable, progression to more critical stages can be slowed, and early diagnosis is crucial to alleviate and manage some of its symptoms. Contemporary diagnostic practices hinder early detection due to the high costs and inaccessibility of advanced neuroimaging tools and specialists, particularly for populations with resource-constrained clinical settings. Methods: This paper addresses this challenge by developing and evaluating computationally efficient lightweight deep learning models, MobileNetV2 and EfficientNetV2B0, for early AD detection from 2D slices sourced from standard structural magnetic resonance imaging (MRI). Results: For the challenging multi-class task of distinguishing between Cognitively Normal (CN), Early Mild Cognitive Impairment (EMCI), and Late Mild Cognitive Impairment (LMCI), our best model, EfficientNetV2B0, achieved 88.0% mean accuracy across a 5-fold stratified cross-validation (std = 1.0%). To enhance clinical interpretability and build trust, we integrated explainability methods, Grad-CAM++ and Guided Grad-CAM++, to visualize the anatomical basis for the models’ predictions. Conclusions: This work delivers an accessible and interpretable neuroimaging tool to support early AD diagnosis and extend expert-level capabilities to routine clinical practice. Full article

Piecewise modeling of power amplifiers (PAs) typically involves assembling different polynomials to capture nonlinear behavior across different operating regions. However, recombining these sub-models can introduce discontinuities at segment boundaries, degrading prediction accuracy and potentially impacting digital predistortion (DPD) performance. This work addresses this issue by introducing a statistical framework to detect discontinuities through localized variations in the conditional mean and variance of amplitude and phase responses. Using the Vector-Switched Generalized Memory Polynomial (VS-GMP) as a case study, we propose a low-complexity post-processing smoothing technique based on a raised cosine weighting function applied at model transition regions. Unlike structural approaches, the method requires no retraining and integrates seamlessly into existing workflows as a post-processing tool. Experimental validation across two PA architectures (Doherty and Single-Stage) and multiple 5G/LTE signals (20–200 MHz bandwidth, up to 11 dB PAPR, including carrier aggregation) demonstrates consistent improvements: up to a 3 dB NMSE reduction and notable spectral error suppression. Full article

Building on advances in promptable segmentation models, this work introduces a framework that integrates Large Vision-Language Model (LVLM) bounding box priors with prototype-based region of interest (ROI) selection to improve zero-shot medical image segmentation. Unlike prior methods such as SaLIP, which often misidentify regions due to reliance on text–image CLIP similarity, the proposed approach leverages visual prototypes to mitigate language bias and enhance ROI ranking, resulting in more accurate segmentation. Bounding box estimation is further strengthened through systematic prompt engineering to optimize LVLM performance across diverse datasets and imaging modalities. Evaluation was conducted on three publicly available benchmark datasets—CC359 (brain MRI), HC18 (fetal head ultrasound), and CXRMAL (chest X-ray)—without any task-specific fine-tuning. The proposed method achieved substantial improvements over prior approaches. On CC359, it reached a Dice score of 0.95 ± 0.06 and a mean Intersection-over-Union (mIoU) of 0.91 ± 0.10. On HC18, it attained a Dice score of 0.82 ± 0.20 and mIoU of 0.74 ± 0.22. On CXRMAL, the model achieved a Dice score of 0.90 ± 0.08 and mIoU of 0.83 ± 0.12. These standard deviations reflect variability across test images within each dataset, indicating the robustness of the proposed zero-shot framework. These results demonstrate that integrating LVLM-derived bounding box priors with prototype-based selection substantially advances zero-shot medical image segmentation. Full article

Circadian rhythm disruptions from shiftwork impact sleep quality and work performance, yet validated tools to assess circadian preferences in Arabic-speaking populations are scarce. This study aimed to translate and validate the 11-item Circadian Type Inventory (CTI-11) into Arabic (CTI-11A), evaluate its psychometric properties, and explore latent circadian profiles in relation to sleep quality. A cross-sectional survey in Bahrain involved 468 Arabic-speaking adults recruited via social media. The CTI-11A, assessing Languid/Vigorous (LV) and Flexible/Rigid (FR) subscales, and the Jenkins Sleep Scale (JSS) were administered. Confirmatory factor analysis (CFA), reliability tests, and latent class analysis (LCA) were conducted. Participants (mean age: 36.18 ± 10.35) showed CTI-11A total scores of 35.40 ± 6.61 and JSS scores of 5.76 ± 3.48. CFA confirmed the two-factor structure (RMSEA = 0.06, SRMR = 0.05, CFI = 0.93, TLI = 0.91), with Cronbach’s α of 0.72 (total CTI-11A). Test–retest reliability was high (ICC = 0.91). CTI-11A correlated moderately with JSS (r = 0.40, p < 0.001), with stronger FR-JSS (r = 0.36) than LV-JSS (r = 0.25) associations. LCA identified two classes (Class 1: 52%, vigorous/flexible; Class 2: 48%, languid/rigid), with Class 2 showing poorer sleep quality. The CTI-11A is a reliable and valid tool for assessing circadian preferences in Arabic-speaking populations, with distinct circadian profiles linked to sleep quality. While flexible/vigorous profiles associated with better sleep, languid/rigid profiles indicate higher sleep disturbance risk, informing targeted shiftwork interventions. Further refinement of the factor structure and broader regional validation are needed. Full article

Wearable, rectifiable aerosol photometers (WRAPs), instruments with combined nephelometer and on-board filter-based sampling capabilities, generally show strong correlations with reference instruments across a range of ambient and household PM_2.5 concentrations. However, limited data exist on their performance when challenged by mixed aerosol exposures, such as those found in dusty occupational environments. Understanding how these instruments perform across a spectrum of environments is critical, as they are increasingly used in human health studies, including those in which concurrent PM_2.5 and coarse dust exposures occur simultaneously. The authors collected co-located, ~24 h. breathing zone gravimetric and nephelometer PM_2.5 measures using the MicroPEM v3.2A (RTI International) and the UPAS v2.1 PLUS (Access Sensor Technologies). Samples were collected from adult brick workers (n = 93) in Nepal during work and non-work activities. Median gravimetric/arithmetic mean (AM) PM_2.5 concentrations for the MicroPEM and UPAS were 207.06 (interquartile range [IQR]: 216.24) and 737.74 (IQR: 1399.98) µg/m³, respectively (p < 0.0001), with a concordance correlation coefficient (CCC) of 0.26. The median stabilized inverse probability-weighted nephelometer PM_2.5 concentrations, after gravimetric correction, for the MicroPEM and UPAS were 169.16 (IQR: 204.98) and 594.08 (IQR: 1001.00) µg/m³, respectively (p-value < 0.0001), with a CCC of 0.31. Digital microscope photos and electron micrographs of filters confirmed large particle breakthrough for both instruments. A possible explanation is that the miniaturized pre-separators were overwhelmed by high dust exposures. This study was unique in that it evaluated personal PM_2.5 monitors in a high dust occupational environment using both gravimetric and nephelometer-based measures. Our findings suggest that WRAPs may substantially overestimate personal PM_2.5 exposures in environments with concurrently high PM_2.5 and coarse dust levels, likely due to large particle breakthrough. This overestimation may obscure associations between exposures and health outcomes. For personal PM_2.5 monitoring in dusty environments, the authors recommend traditional pump and cyclone or impaction-based sampling methods in the interim while miniaturized pre-separators for WRAPs are designed and validated for use in high dust environments. Full article