Search Results (1,210)

This article presents an ontology-driven Digital Twin (DT) for hotel front-desk operations that fuses two real-time data streams: (i) physiological and activity signals from wrist-worn wearables assigned to staff, and (ii) 3D people-positioning and occupancy events captured by reception-area cameras using a proprietary implementation of Optical Camera Communication (OCC). Building on a previously proposed front-desk ontology, the semantic model is extended with positional events, zone semantics, and wearable-derived workload indices to estimate queue state, staff workload, and service demand in real time. A vendor-agnostic, property-based REST API specifies the DT interface in terms of observable properties, including authentication and authorization, idempotent ingestion, timestamp conventions, version negotiation, integrity protection for signed webhooks, rate limiting and backoff, pagination and filtering, and privacy-preserving identifiers, enabling any compliant backend to implement the specification. The proposed layered architecture connects ingestion, spatial reasoning, and decision services to dashboards and key performance indicators (KPIs). This article details the positioning pipeline (calibration, normalized 3D coordinates, zone mapping, and confidence handling), the wearable workload pipeline, and an evaluation protocol covering localization error, zone classification, queue-length estimation, and workload accuracy. The results indicate that a spatially aware, ontology-based DT can support more balanced staff allocation and improved guest experience while remaining technology-agnostic and privacy-conscious. Full article

Background: Sleep deprivation may contribute to increased abdominal adiposity. Although weekend catch-up sleep is associated with various health outcomes, its role in abdominal adiposity remains unclear, particularly among female fixed-shift workers. Therefore, this study aimed to explore the association of workday sleep deprivation and weekend catch-up sleep with abdominal adiposity indicators in Brazilian female fixed-shift workers. Methods: A cross-sectional study was conducted on 450 female fixed-shift workers aged ≥ 18 years from a large industrial group in Southern Brazil. Abdominal adiposity indicators linked to cardiovascular risk were assessed: waist circumference (WC ≥ 88 cm), waist-to-height ratio (WHtR > 0.5), weight-to-waist index (WWI ≥ 11), conicity index (C-Index ≥ 1.27), and WC & Body Mass Index (combined WC ≥ 88 cm and BMI ≥ 30 kg/m²). Workday sleep deprivation was defined as <6 h (h) of sleep on workdays, and weekend catch-up sleep (absolute difference between weekend and workday sleep duration) was defined as >2 h longer sleep on weekends vs. workdays. Associations were estimated using a Poisson regression with robust variance adjusted for demographic, socioeconomic, behavioral, reproductive, and occupational confounders. Results: The mean age was 34.9 ± 9.9 years. The prevalence rates of abdominal adiposity were 45.3% for WC, 47.6% for WHtR, 26.2% for WWI and C-Index, and 28.7% for WC&BMI. Workday sleep deprivation and weekend catch-up sleep were reported by 27.1% and 43.3% of the participants, respectively. After adjustment for confounders, workday sleep deprivation was consistently associated with higher abdominal adiposity: Prevalence Ratio (PR) = 1.37 (95% CI: 1.10–1.69) for WC; 1.25 (95% CI: 1.02–1.53) for WHtR; 1.48 (95% CI: 1.07–2.04) for WWI; 1.43 (95% CI: 1.03–1.99) for C-Index, and 1.59 (95% CI: 1.17–2.16) for WC&BMI. Longer weekend catch-up sleep was positively associated with WHtR (PR = 1.24; 95% CI: 1.03–1.49) and WC&BMI (PR = 1.39; 95% CI: 1.04–1.85). Conclusions: Workday sleep deprivation was consistently linked to increased abdominal adiposity, whereas associations with longer weekend catch-up sleep were less consistent. These findings underscore the potential metabolic risk of insufficient sleep among female shift workers. Full article

Work-related musculoskeletal disorders (MSDs) remain a global occupational health priority, with recognized limitations in current point-in-time assessment methodologies. This research extends prior computer vision ergonomic assessment approaches by implementing biological proprioceptive feedback principles into a continuous, real-time monitoring system. Unlike traditional periodic ergonomic evaluation methods such as “Rapid Upper Limb Assessment” (RULA), our bio-inspired system translates natural proprioceptive mechanisms—which enable continuous postural monitoring through spinal feedback loops operating at 50–150 ms latencies—into automated assessment technology. The system integrates (1) markerless 3D pose estimation via MediaPipe Holistic (33 anatomical landmarks at 30 FPS), (2) depth validation via Orbbec Femto Mega RGB-D camera (640 × 576 resolution, Time-of-Flight sensor), and (3) proprioceptive-inspired alert architecture. Experimental validation with 40 adult participants (age 18–25, n = 26 female, n = 14 male) performing standardized load-lifting tasks (6 kg) demonstrated that 62.5% exhibited critical postural risk (RULA ≥ 5) during dynamic movement versus 7.5% at static rest, with McNemar test $p<0.001$ (Cohen’s $h=1.22$, 95% CI: 0.91–0.97). The system achieved 95% Pearson correlation between risk elevation and alert activation, with response latency of $42.1\pm 8.3$ ms. This work demonstrates technical feasibility for continuous occupational monitoring. However, long-term prospective studies are required to establish whether continuous real-time feedback reduces workplace injury incidence. The biomimetic design framework provides a systematic foundation for translating biological feedback principles into occupational health technology. Full article

Mid-sized Philippine cities commonly rely on fixed-time traffic signal plans that cannot respond to short-term, demand-driven surges, resulting in measurable idle time at stop lines, increased delay, and unnecessary emissions, while adaptive signal control has demonstrated performance benefits, many existing solutions depend on centralized infrastructure and high-bandwidth connectivity, limiting their applicability for resource-constrained local government units (LGUs). This study reports a field deployment of TrafficEZ, a lightweight edge AI signal controller that reallocates green splits locally using traffic-density approximations derived from cabinet-mounted cameras. The controller follows a macroscopic, cycle-level control abstraction consistent with Transportation System Models (TSMs) and does not rely on stationary flow–density–speed (fundamental diagram) assumptions. The system estimates queued demand and discharge efficiency on-device and updates green time each cycle without altering cycle length, intergreen intervals, or pedestrian safety timings. A quasi-experimental pre–post evaluation was conducted at three signalized intersections in El Salvador City using an existing 125 s, three-phase fixed-time plan as the baseline. Observed field results show average per-vehicle delay reductions of 18–32%, with reclaimed effective green translating into approximately 50–200 additional vehicles per hour served at the busiest approaches. Box-occupancy durations shortened, indicating reduced spillback risk, while conservative idle-time estimates imply corresponding CO₂ savings during peak periods. Because all decisions run locally within the signal cabinet, operation remained robust during backhaul interruptions and supported incremental, intersection-by-intersection deployment; per-cycle actions were logged to support auditability and governance reporting. These findings demonstrate that density-driven edge AI can deliver practical mobility, reliability, and sustainability gains for LGUs while supporting evidence-based governance and performance reporting. Full article

Water wastage management (WWM) in deep-level mines remains a critical challenge, as wastage increases operational costs and threatens sustainability. This study presents a systematic state-of-the-art review of WWM in deep-level mines. Relevant literature was critically assessed to establish current practices, identify limitations, and explore emerging solutions. Five principal approaches were identified: leak detection and repair, pressure control with fixed schedules, network optimisation, accountability measures, and smart management. While each provides benefits, significant challenges persist. Particularly, current pressure control techniques, essential for limiting leakage, rely on static demand profiles that cannot accommodate the stochastic nature of service water demand, often resulting in over- or under-supply. Smart management systems, which have proven effective for managing stochastic utilities in other industries, present a promising alternative. Enabling technologies such as sensors, automated valves, and tracking systems are already widely deployed in mining, underscoring the technical feasibility of such systems. However, no studies have yet examined their development for WWM in deep-level mines. This study recommends a framework for smart water management tailored to mining conditions and highlights three opportunities: developing real-time demand approximation methods, leveraging occupancy data for demand estimation, and integrating these models with mine water supply control infrastructure for implementation and evaluation. Full article

Accurate broiler weight estimation in commercial farms is hindered by noisy scale data and multi-broiler occupancy. To address this challenge, we propose a KDE-based framework enhanced with systematic preprocessing, including coefficient of variation (CV), relative change (ROC), and absolute change (AC). In this study, kernel density estimation (KDE) is employed not as a predictive model, but as a distributional tool to robustly extract representative flock weight from noisy, high-frequency scale measurements under commercial farm conditions. In the absence of physical ground-truth, our evaluation focused on the framework’s ability to consistently detect the single, representative peak in the KDE distribution. Weekly thresholds were empirically optimized for the preprocessing filters. Results show that the combined ROC + AC method consistently produced unimodal peak distributions and improved the Peak Detection Rate (PDR) from 91.2% (raw data) to 97.9%. Single-Entity Filtering, assisted by cameras, further mitigated density distortions caused by prolonged occupancy, while CV-only and ROC-only filtering yielded less stable representative values. These findings demonstrate that rigorous preprocessing is essential for reliable KDE-based weight estimation under real-world farm conditions. The proposed framework not only improves data quality and stabilizes distributions but also provides a practical foundation for real-time monitoring and AI-driven precision livestock farming models. Full article

Background: Prostate cancer in the Middle East and North Africa (MENA) region is shaped by a complex interplay of behavioral and environmental risk factors, yet comprehensive estimates of preventable cases remain scarce. To address this gap, we estimated population-attributable fractions (PAFs) for a range of modifiable exposures among men aged 50 years and older and assessed potential reductions in incidence under feasible intervention scenarios. Methods: Regional prevalence data were combined with relative risks from meta-analyses to compute closed-form PAFs for tobacco smoking, obesity, physical inactivity, high dairy and calcium intake, heavy alcohol use, drinking water nitrates, trihalomethanes, arsenic, lead, selenium status, ambient PM_2.5 and NO₂, and occupational diesel exhaust, covering an estimated 47 million men. Estimates were validated using a synthetic cohort simulation of 100,000 individuals, with uncertainty quantified through Monte Carlo sampling. Results: Results showed that drinking water nitrate exposure accounted for the largest single fraction (17.4%), followed by tobacco smoking (9.5%), physical inactivity (6.7%), and trihalomethane exposure (5.0%), while other exposures contributed smaller but meaningful shares. Joint elimination of all exposures projected a 45.5% reduction in incidence, and simultaneous feasible reductions in four targeted exposures yielded a combined potential impact fraction of 12.1%. Conclusions: These findings suggest that integrated water quality management, tobacco control, lifestyle interventions, and targeted environmental surveillance should be prioritized to reduce prostate cancer burden in the MENA region. However, estimates of drinking-water nitrate exposure rely on limited evidence from a single case–control study with a relatively small sample size, and should therefore be considered exploratory and primarily hypothesis-generating. Full article

Accessible and comfortable public transportation is a cornerstone of sustainable and inclusive urban mobility. However, there is a knowledge gap in how interior layout influences riders’ comfort perception under constant occupancy conditions. We conducted a pilot laboratory experiment in Valparaíso, Chile using a full-scale urban bus mock-up. Twenty-five participants each experienced four seating scenarios (yielding 100 total observations per outcome) that varied seat pitch (20, 30, 45 cm) and seat orientation (forward-facing vs. side-facing). Cumulative link mixed models were used to estimate seat pitch and orientation effects on the comfort outcomes, with participant-specific random intercepts. Increased seat pitch dramatically improved comfort ratings (e.g., virtually no participants felt comfortable at 20 cm, whereas nearly all did at 45 cm). Side-facing bench seating (longitudinal orientation) yielded significantly higher comfort, legroom, and ease-of-movement ratings than the forward-facing configuration at ~30 cm pitch (p < 0.001). Within the tested mock-up conditions, the results suggest that seat pitch is a major driver of perceived comfort and in-vehicle usability, and that a side-facing bench layout (tested at ~30 cm spacing) can improve perceived spaciousness relative to forward-facing seating. Because this is a small, non-probability pilot sample and a partial factorial design, these findings should be considered preliminary design sensitivities that warrant validation in larger, in-service studies before informing fleet-wide standards. Full article

Workers’ exposure to silica dust is a global occupational and public health concern and is particularly prevalent in Southern Africa, mainly because of inadequate dust control measures. It is worsened by the high prevalence of HIV/AIDS, which exacerbates tuberculosis and other occupational lung diseases. The prevalence of silicosis in the region ranges from 9 to 51%; however, silica dust exposure levels and controls, especially in the informal mining sector, particularly in artisanal small-scale mines (ASMs), leave much to be desired. This is important because silicosis is incurable and can only be eliminated by preventing worker exposure. Additionally, several studies have indicated inadequate occupational health and safety policies, weak inspection systems, inadequate monitoring and control technologies, and inadequate occupational health and hygiene skills. Furthermore, there is a near-absence of silica dust analysis laboratories in southern Africa, except in South Africa. This protocol aims to systematically evaluate the effectiveness of respirable dust and respirable crystalline silica dust exposure evaluation and control methodology for the mining industry. The study will entail testing the effectiveness of current dust control measures for controlling microscale particles using various exposure dose metrics, such as mass, number, and lung surface area concentrations. This will be achieved using a portable Fourier transform infrared spectroscope (FTIR) (Nanozen Industries Inc., Burnaby, BC, Canada), the Nanozen DustCount, which measures both the mass and particle size distribution. The surface area concentration will be analysed by inputting the particle size distribution (PSD) results into the Multiple-Path Particle Dosimetry Model (MPPD) to estimate the retained and cleared doses. The MPPD will help us understand the sub-micron dust deposition and the reduction rate using the controls. To the best of our knowledge, the proposed approach has never been used elsewhere or in our settings. The proposed approach will reduce dependence on highly skilled individuals, reduce the turnaround sampling and analysis time, and provide a reference for regional harmonised occupational exposure limit (OEL) guidelines as a guiding document on how to meet occupational health, safety and environment (OHSE) requirements in ASM settings. Therefore, the outcome of this study will influence policy reforms and protect hundreds of thousands of employees currently working without any form of exposure prevention or protection. Full article

Airborne micro- and nanoplastic particles (MNPs) are increasingly recognized as a potential occupational exposure hazard, yet substance-specific workplace data remain limited. This study quantified airborne MNP concentrations during polyester microfiber production using a correlative SEM–Raman approach that enabled chemical identification and size-resolved particle characterization. The aerosol mixture at the workplace was dominated by sub-micrometer particles, with PET—handled onsite—representing the main process-related MNP type, and black tire rubber (BTR) forming a substantial background contribution. Across both sampling periods, total MNP particle number concentrations ranged between 6.2 × 10⁵ and 1.2 × 10⁶ particles/m³, indicating consistently high particle counts. In contrast, estimated MNP-related mass concentrations were much lower, with PM₁₀ levels of 12–15 µg/m³ and PM_2.5 levels of 1.3–1.6 µg/m³, remaining well below applicable occupational exposure limits and near or below 8 h-equivalent WHO guideline values. Comparison with earlier workplace and indoor studies suggests that previously reported concentrations were likely underestimated due to sampling strategies with low efficiency for small particles. Moreover, real-time optical measurements substantially underestimated particle number and mass in this study, reflecting their limited suitability for aerosols dominated by small or dark particles. Overall, the data show that workplace MNP exposure at the investigated site is driven primarily by very small particles present in high numbers but low mass. The findings underscore the need for substance-specific, size-resolved analytical approaches to adequately assess airborne MNP exposure and to support future development of MNP-relevant occupational health guidelines. Full article

Invasive alien species pose a major threat to global biodiversity, especially within Europe. Understanding their spatial and temporal dynamics is essential for effective management planning and implementation. The ring-necked parakeet (Psittacula krameri, hereafter RNP) has been established in Greece for over four decades, yet its invasion dynamics remain unstudied despite pilling evidence of ecological impacts. During 2024 and 2025, we conducted repeated transect surveys across 99 1 km² grid squares within the urban complex of Thessaloniki to assess environmental factors influencing occupancy and abundance, and to estimate RNP population trends. Dynamic occupancy and N-mixture models revealed that both the presence and abundance of RNP were positively associated with the proportion of dense urban fabric and urban green areas. The proportion of occupied sites increased by more than 10% between survey years (2024–2025), while the estimated population growth rate for this interval was 1.64, signaling a substantial short-term increase. Our findings provide the first detailed evidence of an established and growing RNP population within the urban complex of Thessaloniki, Greece. Continued monitoring and research on ecological impacts are essential, while any management actions should be developed with public engagement to ensure social acceptance and long-term effectiveness. Full article

Evaluating energy self-sufficiency in the residential sector is crucial for decarbonization. However, the discrepancy between design-stage estimates and actual measurements (the performance gap) poses a significant challenge. While the primary cause of this gap lies in uncertainties stemming from occupant behavior and weather conditions, no medium-term probabilistic forecasting framework for the energy self-sufficiency rate (ESSR) incorporating these factors has been established. To address this issue, this study proposes a probabilistic forecasting framework that integrates a pre-trained time-series foundation model called Chronos with Monte Carlo simulation. Validation using real data from 39 households demonstrates that the proposed method can achieve prediction accuracy superior to baseline models. Furthermore, the derived probability distributions of ESSR quantify fluctuation risks across households and seasons, highlighting the limitations of conventional uniform evaluation models. Full article

Exposure to plant protection products (pesticides) is common among agricultural workers and may represent an underrecognized cause of mucocutaneous disease. We conducted a descriptive cross-sectional survey in agricultural communities in southern Thailand (August–November 2025) to estimate the prevalence, clinical characteristics, and dermatology-specific quality-of-life impact of pesticide-attributed symptoms. Agricultural workers with pesticide use or exposure within the preceding 12 months were recruited via convenience sampling; participants provided consent and completed standardized interviewer-administered questionnaires assessing demographics, pesticide exposure history and application practices, personal protective equipment (PPE) use, self-reported cutaneous and mucosal symptoms (ocular and oral/nasal), and the Dermatology Life Quality Index (DLQI). Of the 354 eligible individuals, 228 participated in the study, and 226 were included in the analyses. The median age was 54 years (interquartile range [IQR], 15), and 82.7% were male. Overall, 14.6% reported pesticide-attributed cutaneous symptoms, 5.3% reported ocular mucosal symptoms, and 0.4% reported oral/nasal mucosal symptoms. Cutaneous manifestations were predominantly symptoms occurring after exposure, with pruritic, erythematous eruptions affecting the arms and hands that typically resolved within 1–7 days after cessation of exposure. Among symptomatic participants, the median DLQI was 0.5 (IQR 3.0); however, DLQI scores were significantly higher among participants who reported pesticide-attributed cutaneous symptoms (p < 0.001) and ocular symptoms (p < 0.001). These findings suggest that pesticide-associated mucocutaneous effects are generally mild yet clinically meaningful, underscoring the need to strengthen PPE training, risk communication, and occupational health surveillance in agricultural settings. Full article

Background and Objectives: The growing number of patients seeking medical care in the internal medicine departments over the past decades has been accompanied by an increase in the bed occupancy rate. This is associated with a heavier work burden among the professional staff members, which may lead to a lower quality of care. Therefore, this study aimed to evaluate the association between the bed occupancy rate and staff compliance with hand hygiene regulations. Materials and Methods: This ecological study included 9 internal medicine departments (~300 beds) in a single medical center between 01/2017 and 12/2019. Routine hand hygiene performance was evaluated randomly, and the association between the bed occupancy rate and the staff’s compliance with the hospital regulations was studied. Univariate and multivariable analyses were performed by the generalized estimating equation model. Results: The study included 12,736 episodes that warranted hand hygiene practices (“opportunities”). The overall hand hygiene performance rate was 78.3% (physicians 76.2%, nurses 80.7%, and healthcare assistants 76.9%). There was an approximately 2% decline in staff compliance for each 10% increase in bed occupancy rate (adjusted IRR 0.98, 95%CI 0.97–0.99, p < 0.001). Stratification by staff members showed a significant decline in routine hand hygiene practices among physicians (adjusted IRR 0.97, 95%CI 0.95–0.99, p < 0.001) and healthcare assistants (adjusted IRR 0.97, 95%CI 0.96–0.99, p < 0.001) but not among nurses (adjusted IRR 0.99, 95%CI 0.98–1.01, p = 0.392). Conclusions: An increase in bed occupancy rate is associated with a decrease in the hospital staff’s compliance with hand hygiene and therefore may lead to a lower quality of care. Full article

Understanding how carnivores coexist is central to ecological theory and conservation. Coexistence among sympatric species arises through niche partitioning across spatial, temporal, and trophic dimensions, yet these mechanisms remain poorly explored in Central African forests where leopards (Panthera pardus) and African golden cats (Caracal aurata) act as dominant and subordinate carnivores. Using camera trap data and molecular scat analyses from two sites in northern Congo, we provided the first robust leopard density estimates for the region (i.e., semideciduous forests in Central Africa) and assessed coexistence mechanisms between the two felids across spatial, temporal, and trophic axes. Spatially explicit capture–recapture models revealed comparable leopard densities across sites (5–6 individuals/100 km²), exceeding the regional average for Central and East Africa. Spatiotemporal occupancy models indicated spatial and temporal overlap, with no evidence of predictive or reactive temporal avoidance, though fine-scale co-occurrence declined near linear forest features (i.e., main rivers and roads) where both species’ marginal occupancy was highest. Conversely, dietary analyses showed trophic segregation: leopards consumed medium- to large-sized ungulates (>20 kg), whereas golden cats relied on smaller prey (≤5 kg), identifying trophic partitioning as the main axis facilitating coexistence in this prey-rich system. Maintaining prey diversity and minimizing disturbance are key to sustaining both species and their coexistence mechanisms. Such multidimensional approaches are essential to understand intraguild interactions and anticipate community shifts under increasing pressure. Full article