Search Results (6,363)

Landslide susceptibility assessment acts as a core technical tool for geological disaster governance, ecological protection and long-term risk mitigation strategies. This modeling approach quantifies the possibility of slope-collapse events and delivers objective decision-making support for regional geologic environment supervision. To overcome the low computational efficiency and weak capacity of conventional evaluation frameworks to extract multi-level spatial grid rules, this paper takes Nanning City, the capital and largest city of the Guangxi Zhuang Autonomous Region in southern China, as the research object. Ten types of terrain and geological control factors combined with historical landslide inventory records are adopted to build a two-stage coupled evaluation framework integrating the information value method (IVM), a Bidirectional Temporal Convolutional Network (BiTCN) and Transformer, named IVM-BiTCN–Transformer. The hierarchical framework first adopts IVM to finish preliminary hazard grading and calculate factor contribution weights, then inputs classified grid samples into the BiTCN-Transformer module to realize local terrain feature and global factor fusion, which significantly lifts the overall identification precision. Ten widely adopted landslide evaluation algorithms are selected for contrast simulation, with multiple quantitative metrics adopted to judge model reliability. Experimental outcomes prove that the presented IVM-BiTCN–Transformer framework obtains superior hazard discrimination capacity, which can raise the precision and stability of landslide zoning and offer reliable technical support for targeted regional geological disaster prevention. Full article

Background and Objectives: Laryngeal cancer imposes substantial inpatient costs in middle-income health systems. We described recent trends in laryngeal cancer hospitalizations in Romania, estimated hospital expenditure, and modeled the impact of prevention scenarios to 2035. Methods: We conducted an ecological analysis of 20,056 discharges diagnosed as laryngeal cancer (ICD-10 C32.x) between 2019 and 2023. Each episode was assigned a mean unit cost of 1100 USD, with age- and residence-specific adjustments, and re-priced using EU (3900 USD) and US (30,000 USD) tariffs. We derived annual costs and projected 2035 expenditure under three prevention scenarios. Results: Annual discharges fell from 5408 in 2019 to 3151–3212 in 2020–2021, then rose to 4409 in 2023, while inpatient spending ranged from 3.47 to 5.95 million USD, reaching 4.85 million USD in 2023 (22,200 USD/100,000 population). Re-pricing 2023 activity at EU and US unit costs yielded counterfactual totals of 17.20 and 132.27 million USD. Older adults (≥65 years) generated 47.6% of discharges and 49.1% of spending in 2023, and urban residence increased the odds of age ≥65 by 48% (OR 1.48, 95% CI 1.40–1.57). Without new prevention, costs are projected to reach 12.60 million USD by 2035; a 30% smoking reduction and a combined package including radon mitigation and dysphonia screening would lower 2035 costs to 10.33 and 9.07 million USD. Conclusions: Demographic aging and sustained case volume will markedly increase hospital costs, while prevention scenarios are associated with lower projected inpatient expenditure. Full article

Allergic diseases are increasing globally, particularly among children, who are highly vulnerable due to critical windows of immune development. This review examines climate change as a key environmental determinant driving the rising burden of pediatric allergic diseases, including asthma, allergic rhinitis (AR), atopic dermatitis (AD), and food allergy (FA). Climate change influences disease risk through interconnected pathways, such as increased air pollution, altered aeroallergen patterns, and more frequent extreme weather events. Elevated carbon dioxide (CO₂) levels and rising temperatures prolong pollen seasons and enhance allergenicity, while pollutants such as ozone (O₃) and particulate matter (PM) exacerbate airway inflammation and immune dysregulation. Emerging evidence emphasizes the role of early-life exposure, particularly during prenatal and early postnatal periods, when environmental insults can induce long-term effects via epigenetic modifications and immune reprogramming. These mechanisms may increase susceptibility to allergic sensitization and subsequent disease development. Epidemiological studies consistently link exposure to air pollution, including PM_2.5 (PM with aerodynamic diameter < 2.5 μm) and nitrogen dioxide (NO₂), with increased risk of allergic diseases in children. Additionally, climate change-related events such as wildfires, sand and dust storms, and thunderstorms further elevate exposure to allergens and pollutants, contributing to acute exacerbations and disease progression. Climate change may also contribute to allergic diseases through microbiome dysbiosis, as altered environmental microbial exposures, biodiversity loss, air pollution, and antibiotic-associated microbial disruption may impair immune tolerance and promote allergic sensitization in children. Addressing this growing public health challenge requires integrated mitigation strategies to reduce greenhouse gas (GHG) emissions and improve air quality, alongside adaptive interventions to enhance resilience and reduce exposure. Understanding these mechanisms is essential for developing targeted prevention strategies and protecting child health in a changing climate. Full article

The scheduling of crude oil operations in marine refineries is a complex combinatorial problem, exacerbated by stochastic disruptions like vessel delays and port congestion. Traditional deterministic and expected-value approaches fail to mitigate high-impact tail events, causing severe demurrage and production bottlenecks. To address this, we propose a novel CVaR-Driven Reactive GRASP Simheuristic. This framework hybridizes GRASP with Monte Carlo simulation, embedding Conditional Value-at-Risk (CVaR) into the adaptive memory to actively steer the search away from catastrophic logistical gridlocks. Overcoming standard “unlimited port capacity” assumptions, the model endogenously calculates demurrage dynamics and introduces an automated Failure Taxonomy for explainable insights. Evaluated on a 30-day industrial case study, representing a standard short-term operational scheduling horizon, under baseline conditions and severe dynamic disruptions (vessel delays, unit maintenance), the diagnostic reveals that over 80% of scheduling failures stem from endogenous port congestion rather than internal dead-ends. Furthermore, a comprehensive ablation study mathematically validates the superiority of the CVaR-driven memory over standard expected-cost optimization in preventing catastrophic tail-risk scenarios. Results demonstrate that this CVaR-driven approach effectively absorbs stochastic shocks, prevents stockouts, and minimizes worst-case costs, generating highly robust schedules in under three minutes. Ultimately, it provides a robust, risk-aware Decision Support System (DSS) for supply chain and operations managers. Full article

Dementia is primarily characterized by cognitive dysfunction, which is one of the major causes of disability. As hearing loss has been identified as the largest modifiable risk factor for dementia, understanding the intrinsic relationship between the two is crucial for preventing and mitigating the progression of dementia. A body of research has demonstrated a close association between hearing loss and morphological changes in the brain; however, the underlying molecular mechanisms require further elucidation. This review synthesizes current evidence on tau protein, amyloid beta protein, glutamate, gamma-aminobutyric acid, reactive oxygen species, and brain-derived neurotrophic factor to clarify potential molecular pathways linking hearing loss with cognitive dysfunction and to identify candidate targets for future mechanistic and translational studies. Full article

Cadmium is a toxic heavy metal classified by the International Agency for Research on Cancer as a human carcinogen and recognized as an endocrine-disrupting chemical. The present study aimed to evaluate tissue-specific susceptibility to cadmium-induced oxidative damage to membrane lipids (lipid peroxidation, LPO) and to assess the antioxidative effects of melatonin in porcine tissue homogenates representing endocrine (the thyroid and the ovary) and non-endocrine (the liver, the kidney, and the brain) organs. Homogenates were incubated with cadmium chloride (CdCl₂; 2.5–1000 µM) without/with melatonin (0.1–5.0 mM). Lipid peroxidation was assessed spectrophotometrically by measuring malondialdehyde + 4-hydroxyalkenals (MDA + 4-HDA) levels. Cadmium significantly increased LPO in the liver (2.5–1000 μM) and in the kidney (25–1000 μM), whereas no prooxidative effect was observed in endocrine tissues or in the brain. Liver damage was mitigated by melatonin doses as low as 0.1 μM across the 250–1000 μM cadmium range, while protection in the kidney was limited to higher melatonin concentrations (2.5–5.0 mM) against damage induced by 100–1000 μM cadmium concentrations. The findings demonstrate pronounced tissue-specific differences in susceptibility to cadmium-induced oxidative stress and support the potential of melatonin as a preventive agent against heavy metal-induced oxidative stress, particularly in non-endocrine organs. Full article

Failure Mode and Effect Analysis (FMEA) is a widely applied preventive risk assessment approach to enhance product reliability and safety, yet its structural validity is frequently questioned. Existing improvement models generally overlook the interrelationships among failure modes and suffer from high uncertainty and instability in opinion aggregation, risk factor weight allocation, and Risk Priority Number (RPN) computation. To bridge these gaps, this study proposes an integrated decision-making model. First, the Decision Making and Trial Evaluation Laboratory (DEMATEL) method is employed to analyze interactions among failure modes, constructing an influential network diagram to identify critical items. Second, a Rough Dombi Aggregator is applied for opinion aggregation, minimizing data loss and handling uncertainties from experts’ diverse backgrounds. Third, the Full Consistency Method (FUCOM) is utilized to determine the relative weights of risk factors. Finally, four weighted aggregation methods are developed to calculate RPNs, mitigating the instability common in traditional methods. This vehicle power system case study, alongside model comparison and sensitivity analysis, demonstrates the model’s effectiveness and robustness. The results indicate that across 9 different weight fluctuation scenarios, the core high-risk item “FM₇: Generator coil burned out due to short circuit” consistently ranks 1st. This highlights the exceptional stability of the proposed model in overcoming evaluation fluctuations. Ultimately, this integrated framework not only enhances the accuracy and robustness of failure mode prioritization but also serves as a valuable practical reference for engineers formulating preventive maintenance strategies under limited resources. Full article

Deep decarbonization of high-temperature industrial furnaces and kilns is essential for reducing greenhouse gas emissions in energy-intensive sectors. Hydrogen and hydrogen-enriched fuels are promising alternatives to conventional fossil fuels; however, their integration is not a straightforward fuel replacement. Owing to hydrogen’s high laminar burning velocity, wide flammability limits, low volumetric heating value, and water-vapor-rich combustion products, hydrogen substitution can substantially alter flame stability, heat transfer pathways, pollutant formation, and material service behavior. This review systematically summarizes the key technologies and application progress of hydrogen-based fuel substitution in high-temperature industrial systems. First, the thermophysical and kinetic differences between hydrogen and hydrocarbon fuels are analyzed. Subsequently, core enabling technologies are discussed, including flashback prevention, low-NOx combustion control, thermal-flow-field regulation, heat transfer optimization, and material compatibility under high-temperature, water-vapor-rich atmospheres. Application progress in representative scenarios—including metallurgy, heat treatment, petrochemical-fired heaters, waste treatment, rotary kilns, and cremation furnaces—is reviewed to identify scenario-specific constraints. The review indicates that successful hydrogen substitution requires a transition from isolated burner optimization toward system-level integration of combustion control, heat transfer management, emission mitigation, and material adaptation. Future research should prioritize integrated furnace design, long-term material service assessment, multi-fuel operating strategies, and data-driven control frameworks. Full article

Complex percutaneous coronary intervention (PCI) represents a growing proportion of contemporary coronary revascularization, driven by aging populations, increasing comorbidity burden, and advances in interventional techniques. Complex PCI encompasses a spectrum of anatomically and procedurally challenging lesions, including left main disease, bifurcation lesions requiring two-stent strategies, chronic total occlusions, long stent lengths, severe calcification requiring atherectomy, and multivessel revascularization. Antithrombotic therapy, comprising antiplatelet and anticoagulant agents, is essential for preventing stent thrombosis and other ischemic events in both the early and long-term phases after PCI. While antithrombotic therapy mitigates ischemic risks associated with complex PCI, these patients frequently carry a high bleeding risk, thus making the choice of antithrombotic regimen challenging. Recent guideline recommendations emphasize balancing ischemic and bleeding risks rather than relying solely on procedural complexity. This review synthesizes contemporary evidence, guideline recommendations, and clinical considerations for antithrombotic therapy after complex PCI. Full article

The growing aging population is a primary driver of chronic, long-term health conditions. The rising prevalence of cognitive decline in older populations is a pressing public health issue due to its impact on health and social care and its emotional toll on family members. A lesser-known condition is sarcopenia—the age-related debilitating loss of skeletal muscle mass and function which leads to weakness and loss of mobility, quality of life and social independence. Neither health condition has a clear pharmacological treatment pathway. Diet and nutrition have therefore received the most attention for disease prevention. This review evaluates the research on the association between sarcopenia and cognitive decline and how both conditions may be linked to protein intake. While findings can be inconclusive or contradictory, a higher consumption of protein may protect against declines in physical and cognitive health, either acting separately or synergistically with exercise. The evidence supports the recommendation for a daily intake of protein higher than the current guideline of 0.8 g/kg/d for older people. Evidence suggests that healthy dietary patterns such as the Mediterranean diet appear to positively influence cognitive health in older people. Furthermore, the impact of specific high-protein foods, including egg, soy and dairy foods, on cognitive health has been reviewed, again with a suggestion that their consumption may mitigate against cognitive decline. Functional foods aimed at the aging population who wish to increase their protein intake and avert or delay the onset of these health conditions could play an important role in preventive nutrition, especially if they are formulated around the protein-rich foods which appear to positively impact cognitive health. Full article

While conventional theories posit that stronger institutions buffer economies against crises, the COVID-19 pandemic presents a puzzle: despite substantial variation in institutional capacity, the global economic contraction of 2020 was both severe and widespread. Motivated by this puzzle, we constructed a global panel dataset from 2014 to 2024 and employed two-way fixed-effect estimation with Driscoll–Kraay robust standard errors to examine the differential role of state capacity across COVID-19 crisis phases. The results confirm that the shock caused by the pandemic reduced GDP per capita growth across countries, with the Americas experiencing disproportionately deeper contractions and stronger rebounds relative to other regions. Most importantly, the findings reveal a temporal asymmetry in institutional effectiveness: our constructed composite resource-based measure of state capacity does not mitigate the initial economic contraction but exerts a positive, statistically significant effect on post-pandemic recovery. Unsurprisingly, model re-estimation with the conventional perception-based measure of state capacity fails to replicate this dynamic, underscoring the importance of measurement strategy in institutional research. These results challenge the assumption that institutions uniformly buffer shocks, demonstrating instead that state capacity is more consequential for recovery than crisis prevention. Full article

The aging of social infrastructure, intensively constructed during periods of rapid economic growth, is a pressing challenge facing modern society. Conventional infrastructure asset management has disproportionately emphasized a “managerial financial perspective,” aiming to maintain physical functions within limited budgets. However, the malfunction of road appurtenances such as tunnel lighting facilities induces severe traffic accidents and chronic congestion, resulting in public health risks for users (physical trauma, psychological stress, and the deterioration of Disability-Adjusted Life Years: DALYs) as well as massive socio-economic losses. The primary novelty of this study lies in bridging the gap between stochastic engineering deterioration models—specifically, discrete-time Markov chain models predicting physical degradation—and socio-economic stakeholder value chains. This study constructs a “Social Life Cycle Cost (LCC) Optimization Model” that directly incorporates these social losses and stakeholder risk disparities into the evaluation function, addressing the limitations of conventional financial-centric LCC models. By conducting robust uncertainty and global sensitivity analyses via large-scale Markov Chain Monte Carlo simulations (number of trials $N={10}^5$), we reveal that a corrective maintenance strategy inheres a critical “fat-tail risk” of stochastically incurring catastrophic social losses. Conversely, preventive intervention at State C minimizes the expected total cost with statistical significance ($p<0.001$) and drastically decouples engineering costs from social risks. This research provides quantitative evidence that early infrastructure intervention functions as an indispensable “social investment” for mitigating public health risks under the specific parameters of the proposed model. Full article

Expansive soils represent a critical challenge in geotechnical engineering due to their significant volumetric changes in response to moisture variations, which cause recurrent structural damage to foundations, pavements and infrastructure. The intensification of wet–dry cycles associated with climate change increases the likelihood of failures, reinforcing the need for more efficient and sustainable stabilization methods. Conventional techniques based on lime or salts present environmental and performance limitations when used independently. This study evaluates a combined approach using sodium chloride (NaCl) and lime sludge (LS), an abundant industrial by-product, to improve the behavior of expansive soils while simultaneously valorizing a difficult-to-manage waste material. Mixtures containing 3%, 6% and 9% NaCl and 5%, 10% and 15% LS were prepared. Atterberg limits, free swell, swelling pressure and infiltration tests were carried out to analyze the response of the treated soil. The results show significant reductions in plasticity and swelling potential: the liquid limit decreased by up to 35%, the plasticity index by up to 36% and the free swell by up to 65% for the optimal combination (9% NaCl + 15% LS). In addition, infiltration increased from 25 to 40 mm, indicating improved hydraulic behavior of the treated soil. The direct reuse of lime sludge prevented its disposal in landfills and reduced the environmental impact associated with its management. Overall, the findings demonstrate that the combination of NaCl and LS is an effective and economical alternative under short-term laboratory conditions, with potential for sustainable application subject to long-term validation for mitigating the swelling of expansive soils. Pilot-scale validation under extreme climatic conditions is recommended to advance toward its integration into resilient infrastructure projects. This approach offers a more efficient, cost-effective, and sustainable technical solution, distinguished by its dual action (chemical and recycling) and its contribution to waste valorization. Future research will focus on validating the method at the pilot scale and assessing its performance under extreme climatic conditions, consolidating its applicability in resilient infrastructure projects. Full article

Distributed-drive all-wheel steering (AWS) six-axle vehicles possess distinct advantages in power performance, maneuverability, and environmental adaptability. However, when navigating tight curves under sudden low-friction road conditions, their inherent long wheelbase and strong inter-axle coupling typically lead to compromised spatial maneuverability, trajectory decoupling between the vehicle nose and tail, and lateral dynamic instability. To resolve these critical issues, this paper proposes a geometry–dynamics coupled lateral control scheme with adaptive speed planning for six-axle vehicles under confined spatial and low-friction conditions by seamlessly fusing a dual-point preview mechanism with multi-mode steering mappings. First, a three-degree-of-freedom nonlinear vehicle dynamic model incorporating longitudinal, lateral, and yaw motions is constructed, alongside the formulation of extended Ackermann kinematic steering manifolds for three distinct modes: rear-axle steering, center steering, and crab steering. To rectify the kinematic under-constrained deficiency inherent in conventional single-point preview path-tracking architectures, a joint front-and-rear dual-point preview constraint mechanism is established. This framework permits the quantitative derivation of a spatial geometric reconstruction method for the instantaneous center of rotation (ICR), which algebraically maps the ideal ICR trajectory requirements onto the physical constraints of the selected steering modes. Consequently, complete geometric constraints on both the front and rear trajectories are achieved, enabling active compression of the vehicle’s turning radius. Furthermore, to handle sudden low-friction disturbances, road adhesion limits and vehicle lateral stability boundaries are explicitly incorporated to design a multi-scale adaptive preview distance dynamic scaling mechanism driven by dynamic safety margin corrections. By adaptively scaling the spatial constraint at the geometric layer, this mechanism proactively mitigates nonlinear tire sideslip force saturation via feedforward action, thereby preventing tracking divergence and catastrophic sideslip instability under physical adhesion limits. Co-simulations based on the high-fidelity TruckSim-Simulink platform demonstrate that, in standard curves, the proposed dual-point preview manifold fusion strategy reduces the minimum turning radius by 9.6–10.1% and shortens the cornering transit time by 7.5% compared with the traditional single-point preview mechanism. By actively constraining the front and rear trajectories, the trajectory decoupling between the vehicle nose and tail is effectively resolved. Under narrow-lane scenarios, the maximum lateral error is restricted within 0.78 m, representing a 37.6% reduction relative to the single-point preview, while the maximum steering angle of the front axle is compressed by approximately 18%, thereby significantly improving spatial passability and preventing intermediate body interference. Most notably, under low-friction surface disturbances, the dynamic-margin-corrected adaptive preview adjustment mechanism exhibits remarkable robustness, constraining the maximum lateral tracking error to within 0.68 m. The proposed geometry–dynamics coupled lateral control strategy successfully elevates the tight-curve maneuverability of heavy transport vehicles while concurrently reinforcing their lateral dynamic stability under limit combined spatial and adhesion constraints. Full article

The co-existence of event-driven critical traffic and time-driven periodic traffic inevitably exacerbates cross-layer network congestion in resource-constrained edge environments. Although hybrid protocol architectures integrating the Constrained Application Protocol (CoAP) at the edge and Quick UDP Internet Connections (QUIC) in the core network have emerged, existing gateways manage these protocols independently, failing to provide an organic congestion control mechanism. To overcome these limitations, this paper proposes an ultra-lightweight Edge Intelligence (EI)-assisted end-to-end (E2E) CoAP-QUIC cross-layer congestion control framework powered by Proximal Policy Optimization (PPO). The proposed scheme introduces an ultra-lightweight traffic classification mechanism that instantly distinguishes traffic classes by parsing the existing two-bit type field in the CoAP header, effectively bypassing the payload inspection overhead. On the basis of this, the PPO agent shapes its reward function in real time, actively shifting optimization weights between delay reduction and throughput optimization. This dual-action control directly mitigates congestion by dynamically tuning the QUIC congestion window and CoAP back-off timers to prevent edge buffer saturation. Extensive simulations using Network Simulator 3 (NS-3) demonstrate that the proposed framework significantly outperforms state-of-the-art baselines, bounding end-to-end latency for critical traffic under 100 ms and improving overall energy efficiency by 21.5% while achieving a 98.2% packet delivery ratio. Full article