Search Results (1,485)

Hard disk failure prediction is an important proactive maintenance method for storage systems. Recent years have seen significant progress in hard disk failure prediction using high-quality SMART datasets. However, in industrial applications, data loss often occurs during SMART data collection, transmission, and storage. Existing machine learning-based hard disk failure prediction models perform poorly on low-quality datasets. Therefore, this paper proposes a hard disk fault prediction technique based on low-quality datasets. Firstly, based on the original Backblaze dataset, we construct a low-quality dataset, Backblaze-, by simulating sector damage in actual scenarios and deleting 10% to 99% of the data. Time series features like the Absolute Sum of First Difference (ASFD) were introduced to amplify the differences between positive and negative samples and reduce the sensitivity of the model to SMART data loss. Considering the impact of different quality datasets on time window selection, we propose a time window selection formula that selects different time windows based on the proportion of data loss. It is found that the poorer the dataset quality, the longer the time window selection should be. The proposed model achieves a True Positive Rate (TPR) of 99.46%, AUC of 0.9971, and F1 score of 0.9871, with a False Positive Rate (FPR) under 0.04%, even with 80% data loss, maintaining performance close to that on the original dataset. Full article

To address traditional methods’ limitations in neglecting the interaction between random shock loads and progressive degradation, as well as failure correlations, this study proposes a dynamic reliability framework integrating Gamma processes, homogeneous Poisson processes (HPP), and mixed Copula functions. The framework develops a wind turbine gearbox reliability model under shock–degradation coupling while quantifying failure correlations. Gamma processes characterize continuous degradation, with parameters estimated from P-S-N curves. Based on stress–strength interference theory, random shocks within damage thresholds are integrated to form a coupled reliability model. A Gumbel–Clayton–Frank mixed Copula with a multi-layer nested algorithm quantifies failure correlations, with correlation parameters estimated via the RSS principle and genetic algorithms. Validation using a 2 MW gearbox’s planetary gear-stage system covers four scenarios: natural degradation, shock–degradation coupling, and both scenarios with failure correlations. The results show that compared to independent assumptions, the model accelerates reliability decline, increasing failure rates by >37%. Relative to natural degradation-only models, failure rates rise by >60%, validating the model’s effectiveness and alignment with real-world operational conditions. Full article

This study investigates the robustness of steel moment-resisting frames (MRFs) under column loss scenarios, both in undamaged and post-seismic conditions. In this context, robustness is defined as the ability of a damaged structure to prevent progressive collapse following an earthquake. A parametric investigation was conducted on 48 three-dimensional MRF configurations, varying key design and geometric parameters such as the number of storeys, span length, and design load combinations. Nonlinear dynamic analyses were performed using realistic ground motions and column loss scenarios defined by UFC guidelines. The effects of pre-existing seismic damage, façade claddings, and joint typologies were explicitly accounted for using validated component-based modelling approaches. The results indicate that long-span, low-rise frames are more vulnerable to collapse initiation due to higher plastic demands, while higher-rise frames benefit from load redistribution through their increased redundancy. In detail, long-span, low-rise frames experience roughly ten times higher displacement demands than their short-span counterparts, and post-seismic damage has limited influence, yielding rotational demands within 5–10% of the undamaged case. The Reserve Displacement Ductility (RDR) ranges from approximately 6.3 for low-rise, long-span frames to 21.5 for high-rise frames, highlighting the significant role of geometry in post-seismic robustness. The post-seismic damage was found to have a limited influence on the dynamic displacement and rotational demands, suggesting that the robustness of steel MRFs after a moderate earthquake is largely comparable to that of the initially undamaged structure. These findings support the development of more accurate design and retrofit provisions for seismic and multi-hazard scenarios. Full article

This study presents a comprehensive investigation of acoustic emission (AE) characteristics for condition monitoring of rolling bearings in passenger ropeway systems. Through controlled laboratory experiments and field validation across multiple operational ropeways, we establish an optimized AE-based diagnostic framework. Key findings demonstrate that resonant VS150-RIC sensors outperform broadband sensors in defect detection, showing greater energy response at characteristic frequencies for inner race defects. The RMS parameter emerges as a robust diagnostic indicator, with defective bearings exhibiting periodic peaks and higher mean RMS values. Field tests reveal progressive RMS escalation preceding visible damage, enabling predictive maintenance. Furthermore, we develop a novel Paligemma LLM model for automated wear detection using AE time-domain images. The research validates the AE technology’s superiority over conventional vibration methods for low-speed bearing monitoring, providing a scientifically grounded approach for safety-critical ropeway maintenance. Full article

Zebrafish (Danio rerio) combine accessible behavioral phenotypes with conserved neurochemical pathways and molecular features of vertebrate brain function, positioning them as a powerful model for investigating early neurodegenerative processes and screening neuroprotective strategies. In this context, integrated behavioral and proteomic analyses provide valuable insights into the initial pathophysiological events shared by conditions such as Parkinson’s disease and related disorders—including mitochondrial dysfunction, oxidative stress, and synaptic impairment—which emerge before overt neuronal loss and offer a crucial window to understand disease progression and evaluate therapeutic candidates prior to irreversible damage. To investigate this early window of dysfunction, zebrafish larvae were exposed to 500 μM 1-methyl-4-phenylpyridinium (MPP⁺) from 1 to 5 days post-fertilization and evaluated through integrated behavioral and label-free proteomic analyses. MPP⁺-treated larvae exhibited hypokinesia, characterized by significantly reduced total distance traveled, fewer movement bursts, prolonged immobility, and a near-complete absence of light-evoked responses—mirroring features of early Parkinsonian-like motor dysfunction. Label-free proteomic profiling revealed 40 differentially expressed proteins related to mitochondrial metabolism, redox regulation, proteasomal activity, and synaptic organization. Enrichment analysis indicated broad molecular alterations, including pathways such as mitochondrial translation and vesicle-mediated transport. A focused subset of Parkinsonism-related proteins—such as DJ-1 (PARK7), succinate dehydrogenase (SDHA), and multiple 26S proteasome subunits—exhibited coordinated dysregulation, as visualized through protein–protein interaction mapping. The upregulation of proteasome components and antioxidant proteins suggests an early-stage stress response, while the downregulation of mitochondrial enzymes and synaptic regulators reflects canonical PD-related neurodegeneration. Together, these findings provide a comprehensive functional and molecular characterization of MPP⁺-induced neurotoxicity in zebrafish larvae, supporting its use as a relevant in vivo system to investigate early-stage Parkinson’s disease mechanisms and shared neurodegenerative pathways, as well as for screening candidate therapeutics in a developmentally responsive context. Full article

Significant progress has been made in the low-temperature toughness and crack resistance of polypropylene fiber-reinforced composites. However, there is still a gap in the research on damage evolution under freeze–thaw cycles and complex stress ratios. To solve the problem of durability degradation of traditional rubble masonry in cold regions, this paper focuses on the study of polypropylene fiber-mortar-masonry blocks with different fiber contents. Using acoustic emission and digital image technology, the paper conducts a series of tests on the scaled-down polypropylene fiber-mortar-masonry structure, including uniaxial compressive tests, three-point bending tests, freeze–thaw cycle tests, and tests with different stress ratios. Based on the Kupfer criterion, a biaxial failure criterion for polypropylene fiber mortar-masonry stone (PPF-MMS) was established under different freeze–thaw cycles. A freeze–thaw damage evolution model was also developed under different stress ratios. The failure mechanism of PPF-MMS structures was analyzed using normalized average deviation (NAD), RA-AF, and other parameters. The results show that when the dosage of PPF is 0.9–1.1 kg/m³, it is the optimal content. The vertical stress shows a trend of increasing first and then decreasing with the increase in the stress ratio, and when α = 0.5, the degree of strength increase reaches the maximum. However, the freeze–thaw cycle has an adverse effect on the internal structure of the specimens. Under the same number of freeze–thaw cycles, the strength of the specimens without fiber addition decreases more rapidly than that with fiber addition. The NAD evolution rate exhibits significant fluctuations during the middle loading period and near the damage failure, which can be considered precursors to specimen cracking and failure. RA-AF results showed that the specimens mainly exhibited tensile failure, but the occurrence of tensile failure gradually decreased as the stress ratio increased. Full article

During the excavation of the underground cavern at the Baihetan hydropower station, significant time-dependent deformation of the surrounding rock was observed, posing a serious challenge to the long-term stability control of the caverns. In this study, numerical models of the layered excavation for typical monitoring sections in the main and auxiliary powerhouses on both banks of the Baihetan hydropower station were established using a viscoplastic damage model. The time-dependent deformation responses of the surrounding rock during the entire underground cavern excavation process were successfully simulated, and the deformation and failure mechanisms of the surrounding rock during layered excavation were analyzed in combination with field monitoring data. The results demonstrate that the maximum stress trajectories at the right-bank powerhouse under higher stress conditions exceeded those at the left-bank powerhouse by 6 MPa after the powerhouse excavation. A larger stress difference caused stress trajectories to move closer to the rock strength surface, therefore making creep failure more likely to occur in the right bank. Targeted reinforcement in high-disturbance zones of the right-bank powerhouse reduced the damage progression rate at borehole openings from 0.295 per month to 0.0015 per month, effectively suppressing abrupt deformations caused by cumulative damage. These findings provide a basis for optimizing the excavation design of deep underground caverns. Full article

Sanguisorba tenuifolia is a wild plant of the genus Sanguisorba officinalis. This study aimed to investigate the regulatory effect of the dichloromethane fraction of Sanguisorba tenuifolia on LPS-induced inflammatory responses in RAW264.7 cells, thereby providing a new scientific basis for the medicinal development of Sanguisorba tenuifolia. Initially, we used 75% ethanol to crudely extract the roots of Sanguisorba tenuifolia, followed by fractional extraction using dichloromethane (CH₂Cl₂), ethyl acetate (EtOAc), butanol (BuOH), and distilled water (DW) as solvents. By measuring the inhibitory effects of each fractionated extract on NO production, we determined that the SCE (Dichloromethane fraction of Sanguisorba tenuifolia) exhibited the most potent anti-inflammatory activity, leading to its progression to the next experimental stage. Subsequently, we evaluated the effects of SCE on cell viability and LPS-induced inflammatory cytokine secretion in RAW264.7 cells. A rat model of reflux esophagitis was also used to validate the in vivo anti-inflammatory effects of SCE. Additionally, we utilized UPLC/MS-MS to identify and analyze the active components of SCE. The results indicated that SCE could effectively inhibit LPS-induced cellular inflammation by modulating the p38/ERK/MAPK and NF-κB signaling pathways, and also reduced the damage of the esophageal mucosa in rats with reflux esophagitis. UPLC/MS-MS analysis of SCE identified 423 compounds, including 12 active ingredients such as triterpenoids, phenols, and steroids. This discovery not only provides scientific support for the potential of Sanguisorba tenuifolia as an anti-inflammatory agent but also lays the groundwork for the development of new therapeutics for the treatment of inflammatory diseases. Full article

Grain boundary weakening in high-temperature environments significantly influences the fatigue crack growth mechanisms of nickel-based superalloys, introducing challenges in accurately predicting fatigue life. In this study, a dislocation-density-based crystal plasticity phase-field (CP–PF) model is developed to simulate the fatigue crack growth behavior of the GH4169 alloy under both room and elevated temperatures. Grain boundaries are explicitly modeled, enabling the competition between transgranular and intergranular cracking to be accurately captured. The grain boundary separation energy and surface energy, calculated via molecular dynamics simulations, are employed as failure criteria for grain boundary and intragranular material points, respectively. The simulation results reveal that under oxygen-free conditions, fatigue crack propagation at both room and high temperatures is governed by sustained shear slip, with crack advancement hindered by grains exhibiting low Schmid factors. When grain boundary oxidation is introduced, increasing oxidation levels progressively degrade grain boundary strength and reduce overall fatigue resistance. Specifically, at room temperature, oxidation shortens the duration of crack arrest near grain boundaries. At elevated service temperatures, intensified grain boundary degradation facilitates a transition in crack growth mode from transgranular to intergranular, thereby accelerating crack propagation and exacerbating fatigue damage. Full article

Background/Objectives: A growing body of evidence is amassing in the literature suggesting a correlation between Alzheimer’s disease (AD) and thrombotic vascular complications, which led to the suggestive hypothesis that thrombosis may contribute to AD onset and progression by damaging the neurovasculature and reducing the cerebral blood flow. In turn, low cerebral blood flow is likely to contribute to neurodegeneration by reducing nutrient and oxygen supply and impairing toxic metabolite removal from the brain tissue. Methods: We searched the literature for studies in animal models of AD or patients diagnosed with the disease that reported circulating markers of platelet hyperactivity or hypercoagulation, or histological evidence of brain vascular thrombosis. Results: Platelet hyperactivity and hypercoagulability have been described in multiple animal models of AD, and histological evidence of neurovascular thrombosis has also been reported. Similarly, clinical studies on patients with AD showed circulating markers of platelet hyperactivity and hypercoagulation, or histological evidence of neurovascular thrombosis collected from post-mortem brain tissue samples. Conclusions: Taken together, a convincing picture is emerging that suggests a strong correlation between systemic or neurovascular thrombosis and AD. Nonetheless, a mechanistic role for haemostasis dysregulation and neurovascular damage in the onset or the progression of AD remains to be proven. Future research should focus on this important question in order to clarify the mechanisms underlying AD and identify a treatment for this disease. Full article

Accurate seismic performance assessment of flexure-shear critical reinforced concrete (RC) columns necessitates precise hysteresis modeling that captures their distinct cyclic characteristics—particularly pronounced strength degradation, stiffness deterioration, and pinching effects. However, existing hysteresis models for such circular RC columns fail to comprehensively characterize these coupled cyclic degradation mechanisms under repeated loading. This study develops a novel hysteresis model explicitly incorporating three key mechanisms: (1) directionally asymmetric strength degradation weighted by hysteretic energy, (2) cycle-dependent pinching governed by damage accumulation paths, and (3) amplitude-driven stiffness degradation decoupled from cycle count, calibrated and validated using 14 column tests from the Pacific Earthquake Engineering Research Center (PEER) structural performance database. Key findings reveal that significant strength degradation primarily manifests during initial loading cycles but subsequently stabilizes. Unloading stiffness degradation demonstrates negligible dependency on cycle number. Pinching effects progressively intensify with cyclic advancement. The model provides a physically rigorous framework for simulating seismic deterioration, significantly improving flexure-shear failure prediction accuracy, while parametric analysis confirms its potential adaptability beyond tested scenarios. However, applicability remains confined to specific parameter ranges with reliability decreasing near boundaries due to sparse data. Deliberate database expansion for edge cases is essential for broader generalization. Full article

Osteoarthritis (OA) is the most common chronic arthropathy worldwide. OA synovitis is a common feature that predicts the development and progression of symptoms and joint damage. Although the OA synovium is a target for novel therapies, the development of ex vivo models remains an area requiring further research. We aim to develop a 3D tissue explant culture model of human OA synovium that preserves the architecture and cellular heterogeneity of the original tissue in vitro. We derived tissue explant models from seven patients with OA and followed the culture for up to 10 days, assessing their morphology and cellular composition by immunohistochemistry (IHC) and flow cytometry, respectively. IHC analysis of explant cultures showed that tissue integrity and viability were maintained in our in vitro system. Furthermore, cellular heterogeneity was essentially unchanged when considering CD4⁺ T cells, CD8⁺ T cells, and myeloid fractions in our model. No significant variation was observed in the CD90⁺ and CD90^-CD55⁺ fractions, which also maintained an activated state as indicated by high levels of FAP expression. An ex vivo OA synovial tissue explant model can maintain pathological tissue integrity for 10 days in culture. This simple and reliable culture system may be useful for analyzing the pathogenesis of OA disease and for the development and testing of therapeutic drugs. Full article

Background: Herbal medicine represents a rich yet complex source of bioactive compounds, offering both therapeutic potential and toxicological risks. Methods: In this study, we systematically evaluated the biological effects of three traditional herbal extracts—Mentha longifolia, Scrophularia orientalis, and Echium biebersteinii—using Caenorhabditis elegans as an in vivo model. Results: All three extracts significantly reduced worm survival, induced larval arrest, and triggered a high incidence of males (HIM) phenotypes, indicative of mitotic failure and meiotic chromosome missegregation. Detailed analysis of germline architecture revealed extract-specific abnormalities, including nuclear disorganization, ectopic crescent-shaped nuclei, altered meiotic progression, and reduced bivalent formation. These defects were accompanied by activation of the DNA damage response, as evidenced by upregulation of checkpoint genes (atm-1, atl-1), increased pCHK-1 foci, and elevated germline apoptosis. LC-MS profiling identified 21 major compounds across the extracts, with four compounds—thymol, carvyl acetate, luteolin-7-O-rutinoside, and menthyl acetate—shared by all three herbs. Among them, thymol and carvyl acetate significantly upregulated DNA damage checkpoint genes and promoted apoptosis, whereas thymol and luteolin-7-O-rutinoside contributed to antioxidant activity. Notably, S. orientalis and E. biebersteinii shared 11 of 14 major constituents (79%), correlating with their similar phenotypic outcomes, while M. longifolia exhibited a more distinct chemical profile, possessing seven unique compounds. Conclusions: These findings highlight the complex biological effects of traditional herbal extracts, demonstrating that both beneficial and harmful outcomes can arise from specific phytochemicals within a mixture. By deconstructing these extracts into their active components, such as thymol, carvyl acetate, and luteolin-7-O-rutinoside, we gain critical insight into the mechanisms driving reproductive toxicity and antioxidant activity. This approach underscores the importance of component-level analysis for accurately assessing the therapeutic value and safety profile of medicinal plants, particularly those used in foods and dietary supplements. Full article

Air pollution is a known contributor to cancer risk, although its specific impact on endometrial cancer (EC) remains unclear. This study integrates network toxicology, transcriptomics, molecular docking, and machine learning to investigate pollutant–gene interactions in EC. We identify 83 air pollution-associated EC genes (APECGs), with TNF, ESR1, IL1B, NFKB1, and PTGS2 as the hub genes. A 13-gene RSF-SuperPC model, including CCNE1, SLC2A1, AHCY, and CDC25C, shows effective prognostic stratification. Molecular docking reveals strong binding between pollutants (e.g., benzene, toluene, and ethylbenzene) and key APECGs. The enrichment and SHAP analyses suggest that pollutant-driven EC progression involves DNA damage, metabolic reprogramming, epigenetic dysregulation, immune suppression, and inflammation. These findings reveal potential mechanisms linking air pollution to EC and support the development of biomarkers for high-exposure populations. Further experimental and epidemiological validation is needed to enable clinical translation. Full article

Ground subsidence is a significant geotechnical hazard in urban areas, leading to property damage, casualties, and broader societal issues. This study investigates the mechanisms of cavity formation and ground subsidence through laboratory model tests using Korean standard sand and marine clay under controlled conditions. A transparent soil box apparatus was fabricated to simulate sewer pipe damage, with model grounds prepared at various relative densities, groundwater levels, and fines contents. The progression of cavity formation and surface collapse was observed and quantitatively analyzed by measuring the time to cavity formation and ground subsidence, as well as the mass of discharged soil. Results indicate that lower relative density accelerates ground subsidence, whereas higher density increases cavity volume due to greater frictional resistance. Notably, as the fines content increased, a tendency was observed for ground subsidence to be increasingly suppressed, suggesting that cohesive clay particles can limit soil loss under seepage conditions. These findings provide valuable insights for selecting backfill materials and managing subsurface conditions to mitigate ground subsidence risks in urban infrastructure. Full article