Search Results (61,652)

Background: Gastrointestinal (GI) cancers remain a major global health concern, where timely and accurate interpretation of endoscopic findings plays a decisive role in patient outcomes. In recent years, deep learning–based decision support systems have shown considerable potential in assisting GI diagnosis; however, their broader adoption is often limited by patient privacy regulations, uneven data availability, and the fragmented nature of clinical data across institutions. Federated learning (FL) offers a practical solution by enabling collaborative model training while keeping patient data local to each hospital. Methods: Vision Transformers (ViTs) are particularly well suited for endoscopic image analysis due to their ability to capture long-range contextual information. Nevertheless, their high computational and communication costs pose a significant challenge in federated settings, especially when data distributions vary across clients. To address this issue, we propose a privacy-preserving federated framework that combines ViTs with a Clinical-Entropy Guided Quantum Evolutionary Algorithm (CEQEA) for adaptive token pruning. The CEQEA leverages the diagnostic diversity of each client’s local dataset to guide population initialization, evolutionary updates, and mutation strength, allowing the pruning strategy to adapt naturally to different clinical profiles. Results: The proposed framework was evaluated on curated upper- and lower-GI tract subsets of the HyperKVASIR dataset under realistic non-IID federated conditions. On the final test sets, the model achieved a mean micro-averaged accuracy of 92.33% for lower-GI classification and 90.19% for upper-GI classification, while maintaining high specificity across all diagnostic classes. At the same time, the adaptive pruning strategy reduced the number of tokens processed by approximately 40% and decreased the number of required federated communication rounds by 33% compared to ViT-based federated baselines. Conclusions: Overall, these results indicate that entropy-aware, quantum-inspired evolutionary optimization can effectively balance diagnostic performance and efficiency, making transformer-based models more practical for privacy-preserving, multi-institutional gastrointestinal endoscopy. Full article

Promoting the agricultural recycling of biogas slurry (BS) is crucial for sustainable development, yet its long-term ecological impacts remain unclear. Through a multi-year field trial in a sugarcane system, this study examined the effects of BS application (0, 3, and 6 years) on the soil properties, bacterial communities, and functional genes for C, N, P, and S cycling. The results revealed distinct two-phase patterns of changes in soil properties, microbial communities, and functional genes. Short-term (3-year) application induced a “disturbance” phase, characterized by significant acidification (pH decreased by 17.91%), a surge in nitrate-N (increased by 757.27%), and a transient decline in bacterial richness. Long-term (6-year) application drove a “functional restructuring” phase, reversing acidification and significantly increasing soil organic matter (29.05%) and total nitrogen (TN) (20.81%). Bacterial richness recovered, and community composition distinctively restructured. Functional gene analysis revealed shifts in gene abundance that transitioned from high abundance in the short term to a new balance favoring processes like N fixation. Co-occurrence network analysis indicated that this functional shift was associated with core microbial modules (e.g., Firmicutes) and changes in soil pH and SOM. This study suggests that, although short-term application causes significant adjustments, sustained and appropriate BS application can ultimately enhance soil fertility and promote a functionally reorganized state by reshaping microbial interaction networks. It presents a microbial ecological basis for the safe and sustainable use of BS in circular agriculture. Full article

Large-scale composite equipment manufacturing imposes stringent requirements on the lean management of multi-specification fiber prepreg sheet storage, while existing optimization methods suffer from poor process adaptability, insufficient multi-objective collaborative optimization capability, and low space utilization of static layouts. This study constructs a symmetric optimization framework for multi-objective composite sheet storage to address these critical bottlenecks. Specifically, the multi-dimensional process value of fiber sheets is quantified, and the layered storage optimization problem is transformed into a 0–1 knapsack problem with symmetric constraints. An improved Dynamic Programming–Backtracking (DP-BT) material selection algorithm and an adaptive dynamic programming iterative space optimization algorithm are proposed to achieve a symmetric balance of inter-layer space utilization and global optimization. Experimental validation with actual production data of 17 fiber sheet types verifies that the proposed method enables space optimization for specified layer counts to maximize average space utilization, with the rate rising from 79.4% (initial 4-layer layout) to 95.7% (3-layer) and 99.9% (2-layer), and a peak single-layer utilization of 100%. This framework achieves favorable optimization performance in the target production scenario and provides a referenceable symmetric optimization approach for the lean storage management of similar fiber sheet storage scenarios in composite manufacturing. Full article

In this study, NH₂-MgO was employed as a crosslinking agent to covalently link boron nitride (BN) and silicon carbide whiskers (SiC_w) via an amidation reaction, yielding the BN-MgO-SiC_w hybrid filler. The BN-MgO-SiC_w/PBz composites were fabricated using a ball-milling-assisted solution mixing method combined with hot-press molding, and their comprehensive properties were systematically evaluated. The results demonstrate that the BN-MgO-SiC_w/PBz composite exhibits excellent thermal conductivity, favorable dielectric properties, superior thermal stability, and outstanding mechanical performance. At a filler loading of 50 wt%, the composite achieved a thermal conductivity of 1.41 W/mK, which is substantially higher than that of the KH560-BN/PBz composite (0.91 W/mK) and approximately 5.2 times that of the neat PBz matrix. The dielectric constant (ε) and dielectric loss (tan δ) of the BN-MgO-SiC_w/PBz composite were 6.81 and 0.013, respectively, remaining at relatively low levels. The thermal degradation temperature at 30% weight loss (T₃₀) and the heat resistance index temperature (T_HRI) reached 572 °C and 244 °C, respectively, both higher than those of the KH560-BN/PBz composite at the same filler loading (511 °C and 224 °C). The tensile strength and flexural strength of the BN-MgO-SiC_w/PBz composite were 50.0 MPa and 72.3 MPa, respectively, exceeding those of the KH560-BN/PBz composite (39.4 MPa and 56.2 MPa) while remaining slightly below those of the neat PBz matrix. Collectively, these findings indicate that the BN-MgO-SiC_w/PBz composite holds great promise as a novel material with well-balanced comprehensive properties, making it a strong candidate for applications in fields such as electronic packaging. Full article

Inadvertent perioperative hypothermia increases susceptibility to surgical site infection (SSI) through impaired immune function, reduced oxidative killing, and altered collagen deposition. We performed a narrative review of recent clinical and translational studies evaluating active thermal management for SSI prevention, with emphasis on forced-air warming (FAW) and conductive systems, and on high-risk settings (prolonged surgery, elevated BMI, and pediatric patients). Across studies, active warming more reliably maintains intraoperative normothermia than passive insulation; however, evidence for a consistent reduction in SSI rates is strongest in vulnerable cohorts and lengthy procedures and remains heterogeneous across specialties. FAW demonstrates high warming efficiency, yet its use in implant-based operations continues to be debated because of potential airflow disruption and bacterial mobilization concerns. The literature increasingly supports precision approaches, including pre-warming protocols, improved perioperative temperature monitoring, and predictive models to identify patients at greatest risk of hypothermia. In conclusion, effective SSI prevention requires procedure- and patient-specific thermal strategies, selecting devices that balance warming performance with sterility considerations while integrating perioperative risk stratification and real-time monitoring. Full article

Background: Neuropathic pain remains a major unmet clinical challenge. Growing evidence identifies sigma receptors (σRs) as pivotal intracellular modulators of maladaptive stress signaling, positioning them as promising non-opioid targets for chronic pain management. Notably, despite the pleiotropic nature of σRs in regulating diverse cellular pathways—which might theoretically suggest a high risk of off-target effects—current selective antagonists have demonstrated remarkable safety and tolerability profiles. Sigma-1 and sigma-2 receptors (σ1R and σ2R) are molecularly and functionally distinct proteins that regulate neuronal excitability, proteostasis, and neuroimmune communication, all mechanisms that characterize neuronal excitability and cellular stress adaptation. σ1R acts as a ligand-operated molecular chaperone at the mitochondria-associated endoplasmic reticulum membrane. Extensive preclinical data demonstrate that σ1R antagonism attenuates peripheral and central sensitization, suppresses neuroinflammation, and restores opioid analgesic efficacy. These findings are supported by the advanced clinical candidate E-52862, which has shown efficacy and a favorable safety profile in neuropathic pain conditions. σ2R, identified as transmembrane protein 97 (σ2R/TMEM97), functions as a regulator of cholesterol trafficking, lysosomal integrity, and integrated stress response (ISR). σ2R modulation alleviates neuropathic pain by restoring proteostatic balance and reducing ISR-driven neuronal vulnerability rather than directly suppressing excitability. Emerging σ2R ligands such as FEM-1689, UKH-1114, and CM-398 provide compelling proof-of-concept for durable, disease-modifying analgesia. Methods: A structured literature search was conducted using PubMed, Scopus, and Web of Science to identify studies published within the last decade describing σ1R and σ2R/TMEM97 biology, ligand development, and their preclinical or clinical evaluation in neuropathic pain. Reference lists were manually screened to ensure comprehensive coverage. Conclusions: This review synthesizes pharmacology, ligand development, and translational evidence supporting σRs as next-generation targets for neuropathic pain therapy, highlighting convergent roles of σ1R and σ2R in pain chronification and outlining future directions for structure-guided therapeutic strategies. Full article

Italy and the surrounding seas are recognised as one of the European hotspots for tornadoes and waterspouts. In recent years, the town of Rosignano Solvay (on the Northern Tyrrhenian coast) experienced repeated waterspouts affecting the same areas, raising local concern about the possible influence of heated wastewater discharged into the sea by a nearby industrial site. We reconstruct the mesoscale meteorological conditions of four intense waterspouts near Rosignano Solvay using a limited-area weather model at a high-to-very-high resolution (inner domain grid spacing of 500 m; sensitivity tests at 100 m). At the reported event times, the intensity of key mesoscale precursors (low-level wind shear, 1 km storm-relative helicity, maximum updraft intensity, and lifting condensation level) is consistent with the values typically associated with EF1 (or stronger) tornadoes and waterspouts. The model systematically predicts the peak of instability indices 2–3 h earlier than the reported event times. For one case study, we conduct two sea surface temperature sensitivity experiments to assess the potential atmospheric impact of heated wastewater discharge (temperature increases of +1.5 K and +5 K over a 10 km² area). The resulting changes in instability indices are marginal, with differences of at most 3% relative to the control run. A simple mass-balance estimate for the modified sea patch suggests that, given the reported discharge rates, a plausible impact of the warm water released from the industrial site could lead to an increase in the local sea surface temperature of approximately +0.7 °C over two months. We conclude that synoptic and mesoscale conditions primarily govern waterspout initiation in this region, while the direct effect of the small warm coastal plume from the industrial discharge appears to be minor. Full article

Long-span bridges are critical components of transportation infrastructure because they promote efficient connectivity between agricultural production centers, tourist destinations, and major urban areas. To construct these structures, the balanced cantilever method is widely used; however, the lack of rigid longitudinal connections between the pylons and the deck often allows for large displacement demands during seismic activities. Fluid viscous dampers (FVDs) are employed to mitigate these effects. This study investigates the impact of using FVDs at the abutments of the Hisgaura cable-stayed bridge located on the Curos-Malaga corridor in the department of Santander, Colombia. A nonlinear response history analysis was conducted using seismic records from crustal sources, scaled to the local seismic hazard, and performed in SAP2000©. The results indicate that the presence of FVDs does not adversely affect the axial forces in the stay cables under the Extreme Event Limit State I. Furthermore, demand reductions were observed at the pylon closest to the abutment (Pylon 4). Under critical seismic records, reductions of up to 81.95% in relative deck-pylon displacement, 62.17% in bending moment, and 58.46% in base shear were achieved. These findings demonstrate an improved global structural behavior under severe seismic loading conditions. Full article

Rapid urbanization-induced extreme rainstorms severely disrupt social functions. Previous research often focused on “de-densification” strategies, which are difficult to adapt to high-density Sponge City Stormwater Management Units (SMUs) that carry core development functions. This study uses Shenzhen as a case study, utilizing Keep movement big data as a “social sensor” for system function perception and introducing the Socio-Ecological-Technological Systems (SETS) theory to construct a “recovery (RCN)–resistance (MI)” binary assessment framework. Through systematic clustering and hierarchical regression models, the driving mechanisms of blue landscape patterns, topography, road networks, and the built environment on social behavioral resilience are systematically parsed. The results show: (1) Road network morphology dominates resistance, while multi-dimensional elements collaborate for recovery. Resistance (MI) is primarily dominated by macro road network detour resistance (TPD2000, β = 0.956), while recovery depends on the synergistic support of blue space interspersion (Blue_IJI), topography, and micro-circulation road networks. (2) Green infrastructure fails in the model due to efficiency bottlenecks, empirical evidence of weakened regulation caused by green space fragmentation in ultra-high-density environments. (3) Low-density, eco-centric built environments provide dual synergistic gains for resilience. Based on this, a “Bidirectional Socio-Ecological Resilience Needs Pyramid” model is constructed, identifying four governance types such as the “Synergistic Balanced Type”. This study provides a quantitative basis for the transition from administrative control to precise morphological governance in high-density cities. Full article

With the rapid advancement of information technology, the energy consumption of data centers has become a critical issue. Accurate cooling load prediction is essential for optimizing cooling system operations and improving energy efficiency. However, conventional models often struggle to capture the complex nonlinearities and multi-variable coupling effects inherent in data centers. To address the limitations of existing models in terms of training efficiency and generalization performance, this study proposes a cooling load prediction model that integrates the light gradient boosting machine (LightGBM) algorithm with Bayesian optimization. The model was validated using data generated from an EnergyPlus simulation of a representative medium-scale data center. Comparative analysis demonstrates that the proposed model surpasses naive benchmarks (T-1, T-24, and T-168) and other machine learning models (SVR, XGBoost, and LSTM), achieving superior performance with a Root Mean Squared Error (RMSE) of 4.3234 kW, R² of 0.9999, and Mean Absolute Percentage Error (MAPE) of 0.07%. A noise robustness analysis further reveals that the model maintains excellent performance under realistic uncertainties, achieving an R² above 0.99 and an RPD exceeding 12 even at high noise levels (SNR = 20 dB). The total runtime and Relative Prediction Deviation (RPD) were 33.45 s and 86.2685, respectively, indicating an excellent balance between computational efficiency and robust predictive reliability. The key contribution of this research is the effective integration of LightGBM and Bayesian optimization to provide a highly accurate and efficient tool for data center cooling load prediction. This approach offers a scientific foundation for the intelligent control of cooling systems and energy efficiency optimization in data centers, with direct practical implications for building energy management. Full article

In this work, the effect of partial to complete Al substitution of Si on the microstructure, retained austenite (RA) stability, and mechanical properties of cold-rolled TRIP-aided steels was investigated. Four experimental TRIP-aided steels (Fe-0.2C-1.5Mn-1.5/1.0/0.5/0Si-0/0.5/1.0/1.5Al-0.025Nb, wt.%) were designed. The results indicate that replacing Si with Al significantly increases the volume fraction of soft polygonal ferrite (from 52% to 73%) and decreases that of bainite. Although the volume fraction of RA decreases (from 15.6% to 12.4%), its average carbon content and, consequently, its mechanical stability are enhanced, which suppresses the strain-induced martensitic transformation. In terms of mechanical properties, the substitution leads to a monotonic decrease in both yield strength (from 573 MPa to 536 MPa) and ultimate tensile strength (UTS) (from 839 MPa to 648 MPa), primarily due to reduced solid-solution strengthening, coarsened ferrite grains, and a weakened TRIP effect. Conversely, the total elongation (TEL) increases from 28.3% to 32.4%, attributed to the higher fraction of ductile ferrite. Consequently, the product of tensile strength and total elongation (PSE) exhibits a slight decline. The 1.5Si-TRIP steel exhibited the most balanced mechanical properties, achieving the highest PSE of 23.7 GPa·%. Full article

Background: Traditional functional mobility assessments often fail to detect subclinical postural decline in active aging populations. This study introduces the Head–Sternum Dissociation Index as a novel digital biomarker to identify latent sensorimotor deficits before macroscopic balance failure occurs. Methods: Ninety-four participants (Young, Middle-Aged Civil, Middle-Aged Dancers, and Older Adults) performed instrumented limits of stability tasks, specifically functional and lateral reach tests, utilizing a three-sensor inertial measurement unit configuration. Postural strategies were quantified via the Head–Sternum Dissociation Index and the peak ratio of corrective micro-movements, validating the sensor output against a gold-standard force platform. Results: A significant kinematic breakpoint in postural control was identified at age 55 (p < 0.001). However, Middle-Aged Civilians exhibited early kinematic divergence despite maintaining normal Timed Up and Go test performance. Receiver operating characteristic analysis revealed distinct, sex-specific physiological limits: aging males predominantly adopted a rigid “Stiffness” strategy (peak ratio ≤ 1.15, head–sternum dissociation threshold > 0.63°), while females utilized a broader, more permissive “Continuous” strategy (head–sternum dissociation threshold > 0.31°). Notably, recreational rhythmic training (dance) completely neutralized this age-related decay, with middle-aged dancers maintaining highly efficient, youthful stabilization profiles (Cohen’s d = 2.20). Conclusions: The Head–Sternum Dissociation Index, combined with relative corrective frequency, successfully phenotypes early sensorimotor erosion. These findings advocate for the integration of sex-specific kinematic screening into primary care, allowing clinicians to prescribe targeted interventions well before clinical fall risk manifests. Full article

Polycystic ovary syndrome (PCOS) is associated with reproductive, metabolic, and inflammatory disturbances. Alterations in T-cell subpopulations—particularly increased T helper 17 cells (Th17) and decreased regulatory T cells (Treg)—have been reported in PCOS; however, data on normoandrogenic phenotype D remain limited. Hypoxia-inducible factor 1α (HIF-1α), a key regulator of hypoxic response, also influences immune and metabolic processes and may affect the Treg/Th17 balance. To assess Treg and Th17 abundance, HIF-1α expression within these cells, and their ratios in women with phenotype D PCOS compared with healthy controls. The study included 49 women with phenotype D PCOS and 40 controls comparable in terms of age and BMI. Anthropometric, hormonal, metabolic, and inflammatory parameters were evaluated. Peripheral T-cell subsets and intracellular HIF-1α expression were analyzed by multiparameter flow cytometry. Absolute numbers of Treg and Th17 cells did not differ between groups. However, PCOS patients showed significantly higher Treg/Th17 and HIF-1α-positive Treg/HIF-1α-positive Th17 ratios. HIF-1α-positive Treg cells correlated positively with adiposity and insulin resistance markers; however, after False Discovery Rate (FDR) correction, correlations no longer remained statistically significant. Despite normoandrogenemia, PCOS patients exhibited higher hs-CRP levels. Phenotype D PCOS is characterized by altered immune cell ratios rather than absolute T-cell differences, suggesting distinct immunological features and persistent low-grade inflammation. Full article

Utilizing multi-source meteorological data for lightning identification is crucial for monitoring severe convective weather. However, several key challenges persist in this field: dimensional imbalance and modal competition among multi-source heterogeneous data, model training bias caused by the extreme sparsity of lightning samples, and an imbalance between false alarms and missed detections resulting from complex background noise. To address these challenges, this paper proposes a lightning identification network guided by physical priors and constrained by supervision. First, to tackle the issue of modal competition in fusing satellite (high-dimensional) and radar (low-dimensional) data, a physical prior-guided asymmetric radar information enhancement mechanism is introduced. This mechanism uses radar physical features as contextual guidance to selectively enhance the latent weak radar signatures. Second, at the architectural level, a multi-source multi-scale feature fusion module and a weighted sliding window–multilayer perceptron (MLP) enhanced decoding unit are constructed. The former achieves the coupling of multi-scale physical features at a 2 km grid scale through cross-level semantic alignment, building a highly consistent feature field that effectively improves the model’s ability to detect lightning signals. The latter leverages adaptive receptive fields and the nonlinear modeling capability of MLPs to effectively smooth spatially discrete noise, ensuring spatial continuity in the reconstructed results. Finally, to address the model bias caused by severe class imbalance between positive and negative samples—resulting from the extreme sparsity of lightning events—an asymmetrically weighted BCE-DICE loss function is designed. Its “asymmetric” characteristic is implemented by assigning different penalty weights to false-positive and false-negative predictions. This loss function balances pixel-level accuracy and inter-class equilibrium while imposing high-weight penalties on false-positive predictions, achieving synergistic optimization of feature enhancement and directional suppression. Experimental results show that the proposed method effectively increases the hit rate while substantially reducing the false alarm rate, enabling efficient utilization of multi-source data and high-precision identification of lightning strike areas. Full article

In this article, we introduce and investigate a novel class of graphs that are called Power Congruence Graph PCGs, which are defined over the vertex set V$=\{0,1,2,\dots ,n-1\}$ where two vertices $a,b\in V$ are adjacent if $a^k\equiv b^k(modm)$ for some modulus $m\in M_p$, where $M_p=\{p,p^2,\dots ,p^t\mid p^t<n\}$. We thoroughly characterize the structural features of these graphs, establishing that each PCG decomposes into a union of $d+1$ complete components, where $d={\displaystyle \frac{p-1}{gcd(k,p-1)}}$. The component sizes are explicitly given for n, p, and k. This decomposition highlights symmetry patterns in the component arrangement, emphasizing connectedness and structural balance. We derive key graph-theoretic metrics such as degree distribution, size, chromatic number, clique number and domination number. We also compute the adjacency and Laplacian matrices, as well as their spectra and associated graph energies to better understand the structural similarities and differences among PCGs with different exponents and prime moduli. This paper offers a systematic framework for comprehending power congruence based graph constructs, integrating number theory with structural and spectral graph theory and illustrating the natural symmetry that underpins these combinatorial structures. Full article