Search Results (63,428)

Wireless Body Area Networks (WBANs) enable real-time health monitoring essential for timely clinical intervention, yet their performance is frequently hindered by sensor degradation, noise interference, and strict low-latency constraints in resource-limited environments. Conventional preprocessing approaches indiscriminately reprocess all incoming data, including uncorrupted samples, thereby increasing computational overhead, introducing latency, and potentially distorting valid physiological trends. This study introduces a unified real-time monitoring framework tailored for WBAN systems. The key contributions include: (1) an adaptively gated multi-stage preprocessing pipeline that selectively restores corrupted samples while preserving clean data, (2) an overlap-aware sliding-window mechanism enabling low-latency operation, and (3) a clinically informed risk assessment strategy for early-warning support. By avoiding unnecessary modification of intact signals, the framework maintains physiological integrity while substantially improving reconstruction and predictive reliability. Across multiple vital signs, the proposed approach achieves substantial reconstruction gains, with Mean Squared Error (MSE) reductions ranging from 53% to 67% under strong degradation conditions. An adaptive ARIMA-based forecasting layer captures short-term physiological dynamics with directional accuracies of approximately 65–70% for one-step (10 s) ahead prediction. Early-warning behavior is intentionally conservative, prioritizing false alarm suppression over aggressive alerting. Per-signal evaluation reveals high sensitivity for blood pressure signals, whereas glucose and certain high-variability modalities exhibit conservative sensitivity under modality-specific thresholds. Importantly, the aggregated multi-modal risk decision achieves strong overall system-level performance, with sensitivity and specificity of 0.89 and 0.92, respectively. Overall, the proposed framework establishes a robust, low-latency, and computationally efficient foundation for dependable physiological monitoring in WBAN environments, leveraging selective processing to optimize both resource utilization and clinical reliability. Full article

Automotive vision systems depend critically on front-view cameras, whose image quality frequently degrades under adverse conditions such as rain, fog, low illumination, and rapid motion. To address this challenge, we propose VMESR, a variable mamba-enhanced super-resolution network that integrates a selective state-space model into a lightweight super-resolution architecture. By serializing 2D feature maps and applying variable-depth mamba blocks, VMESR captures long-range dependencies with linear complexity. A multi-scale feature extractor, enhanced residual modules equipped with a convolutional block attention module, and dense fusion connections work together to improve the recovery of high-frequency details. Extensive experiments demonstrate that VMESR achieves competitive performance in both objective metrics and perceptual quality compared to state-of-the-art methods, while significantly reducing parameter counts and computational cost. VMESR provides a practical balance between efficiency and reconstructive accuracy, offering a deployable super-resolution solution for embedded automotive sensors and enhancing the robustness of autonomous driving perception pipelines. Full article

Biogas slurry is rich in nitrogen, phosphorus and bioactive substances, making it an effective material for restoring degraded grasslands. Against this background, we conducted a field experiment in Zhenglan Banner, Xilingol League, Inner Mongolia Autonomous Region, China, from 2024 to 2025, to study the short-term effects of biogas slurry fertilizer on vegetation characteristics and above- and belowground plant traits. The experiment comprised three treatments: a water control (CK), 50% diluted biogas slurry (BS_50%), and full-strength biogas slurry (BS_100%). All treatments were applied at a rate of 300 m³·ha⁻¹, with CK receiving an equivalent volume of water. The biogas slurry contained 0.11% nitrogen (N), 0.07% phosphorus (P₂O₅), and 0.09% potassium (K₂O). Results showed that, compared with the control, biogas slurry application increased plant height, coverage, and biomass by 8.04–54.00%, 5.48–17.76%, and 18.40–96.01% in the first year, respectively. Plant crude protein and crude fat also increased by 7.33–31.17% and 21.54–30.00%. In the second year, the increases were 26.41–50.22%, 6.16–20.55%, and 13.91–52.42% for plant height, coverage, and biomass and 4.46–28.27% and 14.24–19.89% for crude protein and crude fat, respectively. The carbon, nitrogen and isotope indices of leaves and roots also increased simultaneously. Biogas slurry application altered plant community composition, BS_50% transiently increased plant family richness, BS_100% exerted persistent inhibitory effects, and species diversity across all fertilization treatments showed a recovery trend in the second year. Principal component analysis and redundancy analysis showed that treatment groups were clearly separated in 2024 but overlapped substantially in 2025. Root δ¹³C and root δ¹⁵N were key indicators distinguishing vegetation community characteristics. The results of this study confirmed that the application of biogas slurry fertilizer could actively improve the vegetation recovery of degraded grasslands. It provided reference support for the resource utilization of biogas slurry fertilizer and the sustainable management of grassland ecosystems. Full article

The study first demonstrated that burdock fructooligosaccharide (BFO) could inhibit peel browning in green banana, with 0.5% BFO treatment showing the most significant suppression of peel browning during low-temperature storage (7 ± 1 °C). The results revealed that 0.5% BFO treatment effectively restrained the increase in electrolyte leakage and malondialdehyde (MDA) content and maintained cell membrane integrity. Furthermore, BFO treatment enhanced total phenolic content and antioxidant capacity, alleviated oxidative damage, and better preserved the external quality of banana peel. Simultaneously, BFO treatment markedly inhibited both the activities of chlorophyll-degrading enzymes and their relative gene expression levels in banana peel, thereby maintaining higher chlorophyll content. This research provided a new insight into the mechanism of inhibiting peel browning for low-temperature storage preservation of banana. Full article

Autonomous vehicle path-tracking and lateral stability depend critically on reliable steering actuator operation. However, steering systems are susceptible to bias faults from mechanical misalignment, friction, drivetrain asymmetry, and degradation. These faults distort commanded versus actual steering inputs, causing accumulated lateral and heading errors during high-speed driving. Actuator biases manifest as constant offsets, gradual drift, or intermittent activations, which complicate reliable diagnosis. This study presents an adaptive sliding mode observer-based active fault-tolerant control framework for real-time detection, estimation, and mitigation. An extended four-state lateral error model incorporating distance and heading errors captures the influence of steering bias on vehicle behavior and stability. Adaptive observer gain tuning addresses modeling uncertainties arising from speed variations, linearization residuals, and tire stiffness changes to ensure robust estimation under realistic driving conditions. The effectiveness of the proposed method is validated through high-speed double lane change simulations considering three representative bias scenarios: an initial constant bias, a gradually increasing drift bias, and an intermittent bias. Results demonstrate reliable bias estimation and significantly improved path-tracking accuracy compared to uncompensated cases. Operating without additional sensors, hardware redundancies, or controller switching, the framework is suitable for practical implementation in autonomous vehicle steering systems. Full article

Background: Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) has been implicated in vascular inflammation beyond its action on LDL-C degradation. We investigated whether PCSK9 may exacerbate proinflammatory signaling of M1 macrophages and if its neutralization with alirocumab could attenuate this effect and plaque progression by LDL-C independent mechanisms. Methods: ApoE⁻/⁻ mice were treated with alirocumab for 13 weeks, and aortic arches were isolated for atherosclerotic plaque characterization based on lesion size and lipid and macrophage infiltration. Plasma and splenic monocytes/macrophages were also assessed by flow cytometry, and PCSK9, the lipid profile, and inflammatory cytokines were measured by qPCR or Western blot. Cultured THP-1-derived M1 macrophages were stimulated with PCSK9 and evaluated for TLR4-NFκB-NLRP3 activation and cytokine production. In addition, soluble PCSK9, LDL-C, and proinflammatory factors were analyzed in 1190 patients with acute coronary syndrome (ACS). Results: Alirocumab reduced plaque lesion (0.42-fold; p < 0.05) and lipid (0.63-fold; p < 0.01) and macrophage (0.61-fold; p < 0.05) infiltration, mainly the M1 subtype (0.37-fold; p < 0.01), as well as TLR4, NLRP3 and caspase-1 expressions (0.49-fold, 0.51-fold and 0.51-fold, respectively; p < 0.05), without altering LDL-C. Also, it decreased proinflammatory cytokines but enhanced anti-inflammatory factors and M2 markers at the descending aorta. Alirocumab enriched circulating Ly6C^low monocytes (1.51-fold; p < 0.05) and splenic M2 macrophages (1.32-fold; p < 0.01), while reducing M1 (0.62-fold; p < 0.05). In cultured M1 macrophages, PCSK9 overexpressed proinflammatory cytokines (i.e., CXCL9, CXCL10, TNF-α, IL-1β, and IL-6), downregulated anti-inflammatory mediators (i.e., CCL17, TGM2, TGF-β1, and IL-10), and promoted NFκB-p65 nuclear translocation and NLRP3 and gasdermin-D activation. However, TLR4 inhibition or silencing blunted these effects. In patients with AC, there was a positive association between PCSK9 and hsCRP and FGF-23 plasma levels, independently of LDL-C. Conclusions: PCSK9 may be released in parallel to proinflammatory factors such as hsCRP and FGF-23 in patients with ACS, independently of LDL-C levels. PCSK9 may directly promote macrophage-driven inflammatory responses through the TLR4-NFκB-NLRP3 signaling, but its neutralization with alirocumab attenuated this inflammatory axis and limited atherosclerotic progression, supporting an anti-inflammatory benefit secondary to PCSK9 inhibition. Full article

Corn germ meal contains high-quality protein with the potential of producing bioactive peptides. This study aimed to improve the peptide yield and bioactivity of protein hydrolysates from corn germ meal via thermal-alkaline treatment and solid-state fermentation. Corn germ meal was subjected to thermal-alkaline treatment, and the processing conditions were screened. The material obtained under the optimal conditions was then used for solid-state fermentation. The optimal conditions for thermal-alkaline treatment were 100 meshes, a treatment temperature of 100 °C, an alkali concentration of 1.3%, a treatment duration of 30 min, and a water addition of 120%. The protein digestibility of corn germ meal under optimal conditions improved by 86.28%. The combined treatment of thermal-alkaline treatment and solid-state fermentation significantly altered the chemical composition and structural characteristics of corn germ meal, thereby influencing the solubility and hydrolyzability of its proteins. This approach effectively increased the protein yield (≤37.89%) and peptide yield in protein hydrolysates (≤26.01%) of corn germ meal, consequently enhancing the antioxidant activity and angiotensin I-converting enzyme (ACE) inhibitory activity of protein hydrolysates. Furthermore, the treatment altered amino acid composition in the meal material and effectively degraded anti-nutritional factors such as phytic acid and tannin and improved the comprehensive utilization of corn germ meal. Full article

Little research has examined how often biomedical trainees encounter mistreatment in a single day or how such momentary experiences may undermine engagement in training. To address this gap, we investigated the prevalence and short-term consequences of daily sexual harassment, racial mistreatment, and incivility among graduate students and post-doctoral fellows in U.S. biomedical programs. In Study 1, 404 National Institutes of Health-funded trainees completed a two-wave survey assessing mistreatment, mood, and program attitudes across two 24 h periods separated by 10 days. On either day, 36.9% of participants experienced or observed at least one mistreatment episode, with no differences by gender or underrepresented minority status. Day 1 mistreatment was significantly negatively associated with program attitudes 10 days later, suggesting short-term derailment effects. In Study 2, 21 participants responded to true accounts of peers’ mistreatment to describe their emotional reactions and expectations of mentors. Trainees reported anger, disgust, and betrayal, and emphasized the need for mentors to acknowledge these harms, intervene appropriately, and offer support. This study provides the first evidence of single-day mistreatment prevalence among biomedical health trainees and demonstrates that even brief exposures can degrade training program attitudes. Findings underscore the need for improved mentor training and institutional resources to protect and support trainees. Full article

The pedological component of geodiversity represents a fundamental—yet often overlooked—aspect of the abiotic environment with profound implications for ecosystem functioning and the provision of essential ecosystem services. It is shaped by the complex interplay of lithology, hydrological regimes, relief and its ruggedness, climate, human activity, and time; soil systems mediate crucial ecological processes across spatial and temporal scales. Understanding these interdependencies is critical for sustainable natural resource management and biodiversity conservation. Even more so, soils and the processes related to them become vital when measuring, evaluating, and protecting geodiversity since they can promote groundwater recharge, nutrient cycling, organic matter decomposition, carbon storage, biomass, and food production and habitat provision. Soils provide opportunities for recreation and geotourism, and can contribute to landscape aesthetics. Hence, they are a direct link between abiotic and biotic nature. Given increasing threats from erosion, degradation, pollution, and other changes, this review synthesizes and reviews current research on the pedological component of geodiversity and its connections to hydrological, relief, and other processes. From this perspective, it highlights the need for integrative strategies that safeguard soil functionality and ensure the long-term provision of ecosystem services. By performing that, it provides directions for further discussion and inclusion of soils and their diversity within geodiversity evaluations. Full article

Climate-induced natural hazards are increasingly disrupting metro operations in megacities, necessitating robust and generalizable frameworks for system-wide resilience. While current studies often treat infrastructure degradation, operational adjustment, and passenger flow redistribution as separate problems, this study proposes a resilience-oriented decision framework that couples these universal processes together to address diverse disruptive events. Taking extreme rainfall as a critical representative scenario, a multi-objective recovery optimization model is developed to jointly optimize repair resource cost and average section saturation. Resilience is quantified through the demand satisfaction ratio over the disruption–recovery process, ensuring the framework’s applicability across different hazard types. A case study of the Shanghai metro system under a real extreme rainfall event demonstrates the model’s efficacy in capturing complex system dynamics. Results show a clear Pareto trade-off between repair resource cost and average section saturation, while increasing service capacity on adjacent lines improves the Pareto frontier. Prioritizing repairs on lines with the fewest damaged sections effectively reduces network saturation by restoring corridor throughput. The resilience curve proves that higher repair resources not only shorten recovery time but also raise the minimum demand satisfaction ratio. These findings provide a scalable methodology for designing resilient metro recovery strategies under various climate-related disruptions globally. Full article

Addressing national goals for ecological conservation in the Yellow River Basin, this study focuses on its Henan segment (HYRB). We developed a VOR-SQ assessment framework by augmenting the classic Vitality–Organization–Resilience model with ecosystem services and an enhanced ecological quality indicator. Using multi-source remote sensing and statistical data, we examine the spatiotemporal evolution of ecosystem health in the HYRB from 2000 to 2020. The XGBoost-SHAP algorithm was applied to identify nonlinear drivers and threshold effects. Key findings indicate (1) a persistent “high west, low east” health gradient with an overall declining trend; western mountains remain healthy, while eastern plains, urban, and intensive agricultural areas show degradation. (2) Natural factors—evapotranspiration (ET), elevation, NDVI, and slope—dominate health dynamics, with critical thresholds (~1153 mm, ~457 m, ~0.76, ~10.5°, respectively) beyond which their impacts shift markedly. (3) Anthropogenic factors (GDP, population/road density) contribute less globally but cause strong local negative disturbances in plains. For instance, road density > 434 km/km² or population density > 159 persons/km² reverses their effects from positive to negative. Accordingly, we propose tailored strategies: western conservation, central farmland optimization, and eastern development control. By coupling the VOR-SQ framework with XGBoost-SHAP, this study offers a robust diagnostic tool for ecosystem health and adaptive governance in fragile socio-ecological systems. Full article

Deep-sea gear transmission systems encounter critical lubrication challenges arising from the synergistic coupling of extreme hydrostatic pressure and cryogenic temperatures. These environmental stressors induce exponential viscosity escalation in lubricants, precipitating severe fluidity degradation, elevated startup resistance, and lubrication starvation. Concurrently, seawater intrusion triggers lubricant emulsification, additive deactivation, and electrochemical corrosion at meshing interfaces, collectively escalating the risk of catastrophic lubrication failure and compromising long-term operational reliability. This study systematically elucidates the lubrication degradation mechanisms inherent to deep-sea environments and proposes targeted mitigation strategies. Through comprehensive characterization of deep-sea environmental parameters and their impact on lubricant rheological behavior, we critically evaluate the applicability and inherent limitations of conventional Thermal Elasto-Hydrodynamic Lubrication (TEHL) theory under extreme conditions. Our analysis reveals that established TEHL frameworks necessitate substantial modification to accurately capture pressure-viscosity-temperature coupling phenomena and seawater contamination kinetics. Meshing interface texturing, as an effective anti-friction and wear-mitigation strategy, is investigated to delineate its mechanistic pathways for enhancing lubricant film formation and tribological performance under starved lubrication regimes. Key findings demonstrate that optimized micro-texture architectures can effectively compensate for viscosity-induced fluidity deficits and attenuate the deleterious effects of seawater ingress. Critical knowledge gaps are identified, and future research trajectories are charted: (i) multiphysics coupling models integrating thermo-hydrodynamic, chemo-physical, and mechanical degradation processes; (ii) synergistic texture-coating design paradigms; (iii) high-pressure low-temperature experimental validation protocols; and (iv) engineering implementation frameworks for deep-sea gear transmission systems. This review establishes theoretical foundations and provides technical guidelines for robust lubrication design and long-term operational stability of deep-sea transmission equipment. Full article

Direction of Arrival (DOA) estimation faces significant performance degradation under low Signal-to-Noise Ratio (SNR) conditions, where traditional algorithms and deep learning models struggle due to corrupted spatial information and limited training data. To address these challenges, this paper introduces a novel two-stage framework that integrates a Generative Adversarial Network (GAN) for signal enhancement with a complex-valued Convolutional Neural Network (CNN) for DOA estimation. The proposed GAN incorporates an attention mechanism and a dedicated phase-consistent loss function to suppress noise while preserving spatial phase information critical for accurate direction finding. Enhanced signals are transformed into covariance matrices and processed by a complex-valued CNN designed to extract robust spatial features. Extensive experiments demonstrate that the proposed method achieves a DOA accuracy of 72.2% and a Root Mean Square Error (RMSE) of $3.9°$ at —10 dB SNR with 500 snapshots, substantially outperforming conventional and deep learning baselines. The framework also shows strong robustness to limited data, maintaining 93.8% accuracy with only 50 snapshots. The framework offers a practical solution for reliable DOA estimation in low-SNR and data-scarce environments. Full article

Transmission towers are continuously exposed to corrosive environments, and corrosion of their structural members can significantly reduce the overall load-carrying capacity and stability. In this study, four locally corroded angle steel specimens with single-side connections were fabricated using an electrochemical method. Eccentric compression tests were conducted on these four corroded specimens together with two uncorroded reference specimens. The failure modes, load–displacement curves, and load–strain responses of the corroded specimens were systematically analyzed. It was observed that the strain in the compression leg exceeded that in the free leg. A finite element model, validated against experimental results, was employed for a parametric study to investigate the effects of the spacing between two corrosion regions, their respective relative corrosion depths, and corrosion areas on the degradation rate of load-carrying capacity. Based on the observed influence patterns of these corrosion parameters, an assessment method for capacity degradation under a “dual corrosion region” configuration was developed, accounting for three scenarios: corrosion on the compression leg, the free leg, or both sides simultaneously. This method comprehensively captures realistic corrosion characteristics and demonstrates improved rationality and accuracy. Finally, a sensitivity analysis was performed using the proposed assessment approach, examining key parameters including section corrosion ratio, corrosion area, corrosion location, and slenderness ratio. The results indicate that, under the dual corrosion region condition, the section corrosion ratio is the most dominant factor influencing the capacity degradation rate. Full article

Dental hard tissues, through their remarkable resistance to degradation, represent one of the most durable biological materials available for postmortem investigation. The preparation of undecalcified or ground sections allows microscopic visualization of enamel, dentin and cementum structures, which can preserve chronological, physiological, or environmental information. This review provides a comprehensive overview of the forensic applications of dental hard tissue ground sections, focusing on methodological principles, interpretive potential and practical constraints. The literature in forensic odontology highlights their relevance for age estimation through tooth cementum annulation, identification of neonatal and accentuated stress lines, and the assessment of thermal or chemical alterations. While these methods have proven scientific validity in anthropology and histology, their forensic implementation remains limited by heterogeneity in protocols and interpretative subjectivity. Standardization of preparation techniques, digital imaging, and integration with complementary analyses such as micro-CT or SEM could enhance the reliability and medico-legal relevance of this classical but underused approach. Full article