Search Results (1,931)

Reliable perception in smoke-filled tunnels is essential for rescue robots, yet the temporal evolution of LiDAR degradation under realistic smoke conditions is not well quantified. This paper investigates the degradation of LiDAR data induced by environmental factors in a full-scale tunnel experiment involving three smoke scenarios, with real combustion smoke and theatrical smoke. To enable consistent comparison across experiments with different smoke dynamics, an RGB-based visibility reference is first used for temporal alignment across measurements. Based on this alignment, physically interpretable LiDAR indicators, such as intensity attenuation and range-dependent point density loss, are used to characterize smoke-induced changes in the LiDAR data. In addition, an established Deep semi-supervised anomaly detection (DeepSAD) model is employed to derive a continuous data-driven degradation score that indicates deviations from nominal LiDAR range image patterns. The learned score remains stable under clear-air conditions, despite geometric variations caused by object and sensor movement. During smoke exposure, the score increases in all smoke scenarios, although the temporal evolution differs between scenarios. The results show that the degradation score derived from DeepSAD provides a continuous data-driven description of changes in LiDAR range images under smoke exposure. Overall, the study presents an experimental analysis of LiDAR degradation using full-scale tunnel experiments with smoke, reporting physically interpretable LiDAR indicators and a continuous data-driven degradation score. Full article

The transfer of heavy metals (HMs) from industrial park soils to edible crops is strongly crop-specific; however, these differences have not been considered in probabilistic dietary health risk assessments. This study examined agricultural fields surrounding a high-altitude industrial park in southwestern China, where paired samples of surface soil, Chinese cabbage, and maize were collected and analyzed for Cd, Pb, Cr, Ni, Cu, Zn, Hg, and As. Spearman rank correlation and principal component analysis (PCA) were applied to identify elemental associations and probable sources; bioaccumulation factors (BAFs) were calculated to compare HM transfer and accumulation across the two crops; and Monte Carlo simulation was used to estimate probabilistic dietary health risks across age groups. The results showed that soil HMs in the study area displayed mixed-source characteristics, with marked enrichment of Pb, Cd, and Hg. After multiple comparison correction, only soil Ni showed a significant positive correlation with Ni in maize. Chinese cabbage had a relatively high accumulation capacity for Cd, whereas maize grains showed relatively limited transfer of most HMs, indicating pronounced crop-specific differences. Cd, Pb, Cr, Hg, and As concentrations in Chinese cabbage remained within permissible limits. For health risk, P95 hazard index (HI) values stayed below 1 across all age groups, indicating that non-carcinogenic risk was generally acceptable under the exposure scenarios evaluated; adults, however, carried higher estimated lifetime carcinogenic risk than other age groups. Sensitivity analysis revealed that As and Cd in Chinese cabbage were the dominant contributors to non-carcinogenic and carcinogenic risks, respectively, while the contribution of Cr to risk estimates was highly dependent on its speciation and toxicological parameter assumptions. By combining soil–crop monitoring, bioaccumulation analysis, and probabilistic risk assessment, this study characterizes crop-specific HM transfer patterns and identifies the principal drivers of health risk in industrially influenced agricultural systems, providing a scientific basis for risk-oriented monitoring, food safety management, and the long-term sustainable use of agricultural land in industrial–agricultural interface regions. Full article

Rule-defined rankings often transform continuous marks, discrete judgments, trimming rules, caps, truncation, and tie-breaking variables into a single official order. When ranking margins are small, a formally valid outcome may nevertheless be sensitive to marginal changes in the recorded decision state. This article presents Score Cloud Analysis as a rule-aware statistical sensitivity-reporting method for such systems. The method represents the official score as a deterministic function of recorded inputs and recomputes scores and ranks under finite perturbations, rather than relying on local linear approximations. It defines deterministic diagnostics, including directional Group A/Group C (A/C) decision exposures and their aggregate contested-point exposure, total sensitivity exposure, fragility-to-margin ratios, Score Cloud overlap, and single-call rank sensitivity, and separates these from scenario-conditional Monte Carlo Rank Cloud frequencies. The method is illustrated using a synthetic Wushu Taolu case study because that setting contains majority decisions, trimmed rater marks, discrete difficulty values, Head Judge adjustments, and tie-break rules. The synthetic experiment is an internal-consistency stress test, not an empirical validation and not an estimate of judging-error rates. A small sensitivity study varies perturbation scale and intra-athlete dependence to show which conclusions are scenario-specific. The method separates procedural validity from local rank robustness and is transferable to other reconstructable, rule-based, rater-mediated ranking systems. Full article

This study examined the microbial quality of air and surfaces in six elevators at a tertiary hospital in Greece in 2022. The results highlighted hospital elevators as potentially relevant environmental reservoirs of microbial contamination, with contact surfaces (buttons) exhibiting significantly higher microbial loads than the air. Strong seasonality was also documented; the elevated microbial burden observed during the October sampling period likely reflects seasonal fluctuations in occupant traffic and environmental factors, although direct traffic and microclimatic variables were not monitored. Presumptive Staphylococcus spp. strains dominated the air, while Gram-negative bacteria recovered on MacConkey agar prevailed on surfaces. Phenotypically resistant isolates were also detected, including isolates showing reduced susceptibility or resistance to clinically relevant antimicrobial agents, highlighting the potential value of incorporating AMR surveillance into environmental monitoring. The semi-quantitative environmental exposure assessment showed that, while air quality remained within acceptable limits, the surface-contact route via elevator buttons represented the largest estimated exposure component. Healthcare workers showed the highest estimated cumulative exposure because of the greater frequency of elevator use assumed in the exposure scenario. In conclusion, hospital elevators may act as environmental reservoirs of microbial contamination and potential exposure pathways within the hospital environment, highlighting the need for enhanced hygiene measures, systematic monitoring and the integration of antimicrobial resistance into exposure assessment. Full article

Large mineral flotation workshops in severe cold regions represent special industrial indoor environments characterized by the coexistence of limited ventilation and intense heat release. Such conditions generate pronounced spatial thermal stratification and localized heat accumulation within the workshop, leading to uneven worker thermal exposure and increased thermal discomfort and heat stress risk. However, conventional thermal comfort models were primarily developed for ordinary buildings with relatively stable thermal environments. Their applicability to large industrial workshops remains insufficiently validated. Nine representative monitoring points were arranged in the summer operating areas of the workshop, and thermal comfort surveys were conducted among 35 workers who had adapted to the local climate and working environment. The predicted mean vote (PMV) model was used as the baseline assessment framework, while an adaptive predicted mean vote (aPMV) model was further calibrated using field-based thermal sensation information. Monte Carlo simulation was employed to evaluate uncertainty propagation under field-data constraints, and Sobol sensitivity analysis was conducted to identify the dominant factors affecting thermal comfort predictions. The results demonstrated that the conventional PMV model exhibited a clear warm prediction bias under the investigated industrial conditions. After adaptive correction, the deviation from the field-based TSV was reduced by 82.93%, indicating improved agreement with workers’ actual thermal perception. Sensitivity analysis identified metabolic rate as the dominant contributor to aPMV output variance, with first-order and total-effect Sobol indices of 0.530 and 0.535. The proposed framework provides a scenario-specific approach for thermal comfort assessment in the investigated flotation workshop and offers preliminary methodological references for similar large-scale flotation workshops. Full article

The widespread use of neonicotinoids (NEOs) poses a significant risk to school-aged children. However, critical knowledge gaps remain regarding their comprehensive exposure profiles and associated health risks. This study assessed the co-exposure levels and non-carcinogenic risks of 16 NEOs (including both traditional and emerging compounds) in 184 school-aged children recruited from a typical rural and urban area of South China. The sum concentrations of 16 NEOs (∑₁₆NEOs) ranged from 0.648 to 227 μg/L (median: 8.99 μg/L). The predominant compounds were clothianidin (CLO, 1.93 μg/L), N-desmethyl-acetamiprid (N-dm-ACE, 1.64 μg/L), thiamethoxam (THM, 0.792 μg/L), and dinotefuran (DIN, 0.222 μg/L). To our knowledge, this is the first report of emerging NEOs—paichongding (IPP), sulfoxaflor (SUL), and flonicamid (FLO)—in children urine, with detection frequencies of 11.4%, 68.2%, and 53.4%, respectively. Significant rural–urban disparities in urinary concentrations were observed. The metabolite-to-parent ratios (e.g., N-dm-ACE/ACE, 5-OH-IMI/IMI, and THCP-AM/THCP) may serve as a useful biomarker for assessing human exposure to NEOs, as it provides valuable insight into the metabolic fate of the target compounds and aids in distinguishing exposure pathways. The median estimated daily intake (EDI) values for CLO, N-dm-ACE, THM, and ∑₁₂NEOs were 0.127, 0.117, 0.046, and 0.696 μg/kg-bw/day, respectively. Although the hazard quotient for individual compounds was below 1 for vast majority of school-aged children, cumulative exposure assessment indicated that 1.09% of participants had a hazard quotient exceeding 1 for both IMI_eq and ∑₁₂NEOs, suggesting potential health concerns under co-exposure scenarios. Using a multi-criteria Toxicological Priority Index (ToxPi) model, CLO, THM, thiacloprid-amid (THCP-AM), and N-dm-ACE were identified as the high-priority compounds requiring regulatory attention in children’s environmental health. This study provides the first comprehensive biomonitoring and ToxPi-based prioritization of both traditional and emerging NEOs in school-aged children in South China. The findings highlight the urgent need for continued monitoring, refined mixture risk assessment, and regulatory consideration of emerging substitutes and their metabolites, which are not adequately covered by current safety guidelines. Full article

Background: Global antibiotic consumption continues to rise across pediatric and adult populations, while the genotoxic consequences of host eukaryotic exposure remain less systematically characterized than the parallel problem of antimicrobial resistance. Several lines of evidence, from molecular cytogenetics, redox biology, and systems toxicology, now permit a more mechanistically resolved synthesis of antibiotic-induced genome stress than was previously possible, although a substantial fraction of this evidence is preclinical and warrants cautious clinical extrapolation. Scope: This narrative review evaluates the molecular mechanisms, cytogenetic biomarkers, and translational implications of antibiotic-induced genotoxicity, with a primary focus on six clinically prominent classes (fluoroquinolones, nitroimidazoles, aminoglycosides, macrolides, β-lactams, and tetracyclines) and a brief extension to glycopeptides and glycylcyclines. We organize the evidence around three convergent mechanistic axes rather than around individual drugs. Key findings: Accumulating evidence supports three intersecting off-target axes: (i) eukaryotic topoisomerase II interference, principally documented for fluoroquinolones; (ii) mitochondrial dysfunction, reflecting the evolutionary kinship between the mitoribosome and bacterial ribosomes; and (iii) inflammation-coupled redox stress, often amplified by microbiome perturbation. These pathways converge on a common spectrum of DNA lesions—including double-strand breaks, oxidatively modified bases, replication-fork stalling, and chromosomal mis-segregation) detected by complementary assays (CBMN-Cyt, comet, γH2AX, and oxidative and mitochondrial biomarkers). Pediatric, pregnant, geriatric, and oncology populations may represent biologically distinct susceptibility strata, although direct human evidence for several of these inferences remains limited. Limitations: Causal inference is constrained by infection as a confounder, frequent use of supratherapeutic in vitro concentrations, reliance on immortalized cell lines that may not recapitulate primary-cell repair capacity, inter-laboratory variability across cytogenetic assays, and a marked scarcity of pediatric and pregnancy biomonitoring data. Most existing positive signals derive from preclinical models; clinically validated long-term outcomes, particularly carcinogenic endpoints, remain inconsistently demonstrated for most antibiotic classes outside metronidazole. Conclusions: Antibiotic-induced genotoxicity appears to be a measurable and mechanistically tractable dimension of drug safety, though its clinical magnitude in real-world exposure scenarios requires further investigation. Integrating multi-omics, microphysiological systems, single-cell genotoxicology, and AI-assisted prediction may improve risk resolution, particularly in vulnerable populations. We argue that antimicrobial stewardship discussions should consider host genome integrity alongside resistance, while remaining mindful that the mechanistic case currently outpaces clinical-endpoint validation. Full article

Background: In patients with atrial fibrillation receiving long-term anticoagulation therapy with dabigatran etexilate (DABE), moxifloxacin (MFLX) is frequently coadministered to treat concurrent infections; however, the potential drug–drug interaction (DDI) between these agents remains unclear. Herein, we examined the underlying mechanism by which MFLX attenuates DABE pharmacokinetics in rats; subsequently, we elucidated the DDI in humans by establishing a physiologically based pharmacokinetic (PBPK) model based on these animal data. Methods: The 3- and 14-day effects of 40 mg/kg MFLX once daily and secondary bile acid (SBA)-containing dietary intervention on the pharmacokinetic profile of DABE and its active form, dabigatran (DAB), were examined in a rat model. Ileum tissues were harvested to measure the expression of P-glycoprotein (P-gp), pregnane X receptor (PXR), and peroxisome proliferator-activated receptor alpha (PPARα). In addition, we examined the effects of secondary bile acids (SBAs) on P-gp expression and quantified P-gp-mediated DABE efflux transport activity in Caco-2 cells. A PBPK model was used to predict the risk of DAB exposure under this DDI scenario and under combined high-risk conditions, including renal impairment and advanced age. Results: Treatment with MFLX for 3 and 14 days inhibited SBA-producing gut microbiota, thereby suppressing the conversion of primary bile acids to SBAs. Concurrently, a marked reduction in intestinal P-gp expression was observed, along with a significant enhancement of the oral bioavailability of DABE. These effects were reversed by SBA-containing diets. In vitro experiments using Caco-2 cells revealed that physiologically relevant concentrations of SBA significantly upregulated P-gp expression and function, whereas MFLX incubation alone showed no direct modulatory effect on these transporters or regulators. PBPK simulation results showed that in vivo exposure of DAB would increase by 41.7%, 104%, 251%, and 115% when coadministered with MFLX alone, with coexisting mild renal impairment, moderate renal impairment, and aging, respectively. Conclusions: MFLX increases DAB exposure by reducing SBA-regulated intestinal P-gp function. PBPK simulations suggest a low risk of DDI from MFLX coadministration alone; however, caution is warranted in patients with aging or renal impairment. Full article

Level 3 automated driving necessitates rapid driver reengagement following a takeover request, making human–machine interface design critical for safety. As a sensor-based in-vehicle interface, the augmented reality head-up display (AR-HUD) integrates real-time environmental sensing with visual information delivery, yet how different information presentation strategies influence driver visual attention during takeover remains underexplored. We examined the effects of presentation form (static/dynamic) and presentation timing (concurrent/progressive) using a 2 × 2 within-subject design. In the experiment, twenty-one licensed drivers viewed prerecorded automated driving takeover scenarios. Eye tracking measured mean fixation duration, mean saccade amplitude, time to first fixation, and fixation count, while ratings assessed usability, acceptance, and intention comprehension. Progressive presentation significantly reduced all eye-tracking measures and improved perceived usability ratings compared with concurrent presentation. This pattern indicates more concentrated and orderly gaze allocation and is consistent with lower visual-search and information-integration demands. However, the lower fixation count may partly reflect reduced information exposure. Static presentation reduced mean fixation duration but showed no consistent overall advantage on the remaining measures. Significant form-by-timing interactions showed that progressive presentation reduced saccade amplitude and time to first fixation and improved intention comprehension under static, but not dynamic, presentation. Among the four combinations, static-progressive presentation yielded the most favorable overall pattern. Overall, presentation timing affected more measured outcomes than presentation form. These findings provide preliminary evidence that presentation form and presentation timing shape gaze behavior and subjective evaluations of AR-HUD takeover displays. Full article

This paper presents a methodology to evaluate the entire process of thermal evolution and fracture failure within stay cables subjected to sheath fires. Computer software FDS 2021 and ABAQUS 2021 are applied to build a sequentially thermos–mechanics coupled method integrating thermal, structural, and fracture dynamic analyses in stay cables under sheath fire exposure conditions. Herein, three representative fire scenarios including full-circumferential, top-side, and bottom-side ignition are reconstructed. Further, 127 individual wires, accounting for interstitial cavity radiation and contact heat transfer, are utilized to perform analysis on sectional temperature in stay cables. The results indicate that the ignition mode dictates the cross-sectional temperature gradient, with localized ignitions inducing highly asymmetric thermal fields and pronounced internal bending moments. Elevated temperatures trigger a progressive load redistribution from the degraded fire-facing wires to cooler internal layers. Ultimately, abrupt global fracture occurs when the residual ultimate load-carrying capacity intersects with the actual applied tension, resulting in a fracture morphology that closely corresponds to the spatial thermal distribution. Furthermore, the structural capacity degradation exhibits three distinct time-dependent stages: a slow degradation stage, a sharp decline stage, and a recovery stage. Among the analyzed scenarios, full-circumferential ignition induces the most drastic overall capacity reduction, while bottom-side ignition poses a markedly greater rupture risk than top-side ignition. Full article

Coastal flood exposure indicators are increasingly needed to support climate adaptation and sustainable coastal planning in small island regions, yet regional-scale assessments that translate hydrodynamic simulations into spatially explicit exposure indicators remain limited across the Caribbean. This study develops a spatially explicit coastal flood exposure framework by integrating LISFLOOD-FP simulations with settlement dynamics, land-cover change, and population distribution data. Coastal inundation was simulated under baseline (1985–2014) and SSP5-8.5 (2015–2050) 100-year extreme sea-level conditions and overlaid with land-cover, settlement, and WorldPop data to assess land-cover, settlement, and population exposure across Caribbean island systems. The results show that SSP5-8.5 generally increases coastal inundation extent relative to the baseline, although the broad regional pattern remains similar. Large islands with extensive low-lying coastal plains show greater absolute inundation, whereas several smaller islands exhibit higher proportional exposure because of limited land area and concentrated coastal settlements. Wetlands constitute the largest share of exposed terrestrial land cover, while built-up land shows increasing exposure. These findings suggest that future coastal flood exposure in the Caribbean is shaped by both increasing hazard intensity and persistent human concentration in flood-prone coastal zones. Because the modelling framework does not explicitly represent wave setup/runup, compound flooding, or coastal defences, the results are interpreted as regional-scale screening indicators rather than locally calibrated flood-risk estimates. Full article

Brazil presents a distinctive convergence of continental-scale climatic diversity, extensive urbanization, large-scale biomass burning, rapid land-use change, persistent air-quality monitoring gaps, and deep social inequalities, producing highly heterogeneous and compound environmental health risks. In this context, treating air pollution and climate change as parallel environmental crises obscures their structural interconnections through shared emission sources, mutually reinforcing exposure pathways, and overlapping health and social consequences. In this narrative review, we critically synthesize scientific and institutional lines of evidence and argue that air pollution and climate risks can be more effectively addressed in Brazil through a single strategic agenda for science, public health, and governance. We first discuss why these challenges cannot be managed in isolation, emphasizing the effects of heat, drought, stagnation events, biomass burning, and extreme weather on pollutant formation, dispersion, and health burden. We then examine Brazil as a critical case where recent regulatory advances coexist with structural limitations in monitoring, data integration, and territorial coverage. Based on this diagnosis, we propose an integrated national agenda organized around five mutually reinforcing priorities: monitoring through hybrid networks; predictive science through climate-informed modeling and early warning; public health through the convergence of epidemiology, toxicology, and mechanistic research; equity-oriented research and action through the explicit incorporation of vulnerability, inequality, and climate justice; and policy appraisal through the assessment of disease burden, economic costs, mitigation co-benefits, and trade-offs. We further discuss the governance mechanisms needed to connect these priorities and translate evidence into coordinated action and adaptive public policies. We also argue that the Amazon should be approached not as an isolated ecological exception but as a central component of a broader Brazilian and Global South discussion on environmental health, land-use change, and climate justice. In this scenario, Brazil has the scientific capacity and regulatory momentum to become a reference in the integrated management of air pollution and climate risks, but this will depend on replacing fragmented approaches with a coordinated framework capable of linking exposure, mechanism, burden, inequality, and action. Full article

This research presents a comprehensive diagnosis of Ecuador’s electricity generation (2003–2024), focusing on structural vulnerabilities, fuel dependence, and Greenhouse Gas (GHG) emissions from electricity generation. The technological composition of the grid, including installed and effective capacity, as well as the share of fossil and organic fuels, is analyzed to construct a coherent analytical framework. GHGs (i.e., CO₂, CH₄, and N₂O) are estimated from fuel consumption in Non-Conventional Renewable Energy (NCRE) and Non-Renewable Energy (NRE), in accordance with the 2006 IPCC Guidelines. Conversion to CO₂ equivalent utilizes the AR5 GWP factors, in agreement with AR6. The results present annual series for each gas and their corresponding CO₂ equivalents, showing that NREs dominate the CO₂ profile, while NCREs contribute significantly to CH₄ and N₂O. Despite the expansion of installed capacity, a gap persists with effective capacity, reflecting the structural vulnerabilities of Ecuador’s electricity generation system, including exposure to hydrological variability (Kraftnōt, referring in this research to electricity shortages caused by reduced hydropower generation under adverse hydrological conditions), insufficient thermal backup, a high concentration of hydropower plants, fluctuating fossil fuel subsidies, and limited diversification. This manuscript provides a technical and quantitative basis using annual CO₂, CH₄, and N₂O values and their CO₂ equivalents to inform future decarbonization scenarios that strengthen NCRE integration within international climate commitments and a sustainable electricity transition. Full article

Future climate projections suggest an increase in heat-related mortality and a decrease in cold-related deaths under warming scenarios. Understanding the health impacts of extreme heat, and their implications for healthcare demand is essential for assessing the future burden of climate-related illnesses. In this study, we examined the relationship between extreme heat events and Emergency Department Visits (EDV) for heat-related illnesses (HRIs) across the United States from 2018 to 2025. Using data from the Centers for Disease Control and Prevention (CDC) Heat and Health Tracker and other relevant sources, we analyzed EDV rates standardized to 100,000 population. We aggregated daily into the 10 U.S. Health and Human Services (HHS) Regions. We used 0.5° × 0.5° gridded maximum daily temperature data (aggregated to HHS regions with proportional area weighting) and daily maximum heat index extracted from the CDC data portal (estimated using the US National Weather Service methodology and aggregated to HHS regions using total population weighting) to characterize seasonal patterns and regional variability. The association between peak heat events and EDV time series was explored using log-linear mixed-effects models, which accounted for seasonal trends, climate variables, and their regional variability. Random effects were used to capture regional heterogeneity in predictor-response relationships, accommodating variation in associations across regions. Model performance was evaluated using prediction error metrics and goodness-of-fit assessments. Maximum temperature and heat index were both significant predictors, with the heat index offering a slightly better fit. Associations were largely contemporaneous, with peak correlations at lag zero, underscoring the need for real-time response. EDV increased several days before peak environmental conditions, consistent with early exposure effects. While temperature-EDV relationships varied regionally, heat index associations were more stable. This work underscores the urgent need for regionally adaptive public health strategies in the face of intensifying climate extremes and outlines future directions for research and policy to strengthen health systems’ preparedness in a warming world. Full article

This paper studies a risk-averse stochastic unit commitment framework for an energy aggregator, operating a portfolio of conventional generators, renewable units, and battery energy storage in a network-constrained environment. Renewable generation and demand uncertainty are represented through a scenario-based extensive-form mixed-integer linear program. To avoid exposure to rare but high cost events, the model incorporates conditional value-at-risk as part of the objective function. The approach captures key market interactions, including day-ahead commitments, imbalance penalties, and power exchange with a neighboring network, while respecting generator constraints, storage dynamics, line flow limits, and bus voltage security. A comprehensive parametric study is conducted to quantify the influence of two risk parameters: the conditional value-at-risk confidence level $\alpha$ and the risk-aversion weight $\lambda$. Using a 300-scenario test set on a modified IEEE 9-bus system, the results show that risk-neutral scheduling exposes the aggregator to larger operational costs in extreme scenarios. Minor levels of risk aversion (0.1–0.5) reduce CVaR and tighten the distribution of costs. Increasing $\lambda$ further yields diminishing returns, while higher $\alpha$ values focus risk mitigation on the most severe outcomes. The results demonstrate how CVaR-based stochastic scheduling can support aggregator decision-making by quantifying downside risk under renewable uncertainty. Full article