Search Results (3,553)

To address the critical challenge of drilling fluid invasion in deep coalbed methane (CBM) reservoirs, this study provides novel insight into the micro-scale sealing mechanism and pore structure evolution by leveraging Low-Field Nuclear Magnetic Resonance (LF-NMR) as a quantitative probe. Unlike traditional macroscopic evaluations, we utilized dynamic NMR T₂ spectral analysis to decipher the synergistic behavior of a proposed “Bridging–Filling–Densifying” ternary sealing system, which integrates a nano-plugging agent, micro-fillers, and size-matched skeletal agents. The results demonstrate a significant improvement in sealing efficiency. The optimized hierarchical architecture reduced the NMR signal intensity of the invaded cores by over 99.8% under a differential pressure of 10 MPa, effectively eliminating fluid invasion channels. Crucially, the study reveals that while multi-scale particle size matching is the precondition for sealing, the mechanical rigidity of the skeletal particles is the determinant for maintaining filter cake integrity against high-pressure deformation. These findings elucidate the transition from a “macropore-dominated” structure to a “zero-detectable” sealed state, establishing a robust theoretical framework for designing non-damaging drilling fluids tailored to the complex geomechanics of deep CBM exploration. Full article

Under non-independent and identically distributed (Non-IID) conditions, significant variations exist in local model updates across clients and training phases during the collaborative modeling process of differential privacy federated learning (DP-FL). Fixed clipping thresholds and noise scales struggle to accommodate these diverse update differences, leading to mismatches between local update intensity and noise perturbations. This imbalance results in data privacy leaks and suboptimal model accuracy. To address this, we propose a differential privacy federated learning method based on adaptive clipping thresholds. During each communication round, the server adaptively estimates the global clipping threshold for that round using a quantile strategy based on the statistical distribution of client update norms. Simultaneously, clients adaptively adjust their noise scales according to the clipping threshold magnitude, enabling dynamic matching of clipping intensity and noise perturbation across training phases and clients. The novelty of this work lies in a quantile-driven, round-wise global clipping adaptation that synchronizes sensitivity bounding and noise calibration across heterogeneous clients, enabling improved privacy–utility behavior under a fixed privacy accountant. Using experimental results on the rail damage datasets, our proposed method slightly reduces the attacker’s MIA ROC-AUC by 0.0033 and 0.0080 compared with Fed-DPA and DP-FedAvg, respectively, indicating stronger privacy protection, while improving average accuracy by 1.55% and 3.35% and achieving faster, more stable convergence. We further validate its effectiveness on CIFAR-10 under non-IID partitions. Full article

This study discusses the thermal behavior of glass fiber-reinforced SiO₂-filled polymers in dry milling. Focus is put on the effects of the addition of SiO₂ particles on cutting-generated heat and the fresh-surface integrity of the composite. Cutting trials were developed using a Spinner U-620 5-axis CNC machine. Real-time temperature histories owing to the dry milling of both Glass/Epoxy and Glass/Polyester composites were recorded using thermocouples preinstalled within the composite specimen. SEM inspections were conducted to elucidate the prevailing failure mechanisms during the material removal process. The results showed that fiber orientation significantly dominated thermal responses. Cutting perpendicular to the fiber orientation results in a critical temperature, while the addition of SiO₂ particles effectively reduces the temperature overlaps and peak values, causing the temperature to drop. The addition of SiO₂ serves to keep the temperature sufficiently lower than the glass transition point of the matrix. However, increasing the feed rate from 50 mm/min to 150 mm/min reduced the overall temperature during cutting. Under similar cutting conditions, Glass/Polyester composites exhibited lower peak temperatures and heat quantities than Glass/Epoxy regardless of the feed rate and fiber orientation. Observations revealed that fiber orientation and matrix type strongly influence the intensity of the thermal and mechanical damages induced. These findings suggest that the addition of silicon dioxide can adjust the thermal balance in dry cutting and may improve the composite’s structural integrity significantly. Such a composite design promotes the heat control of sensitive parts in advanced engineering applications. Full article

Hurricanes have intensified and become more persistent under a changing climate, increasing the risk of infrastructure damage and property loss in coastal regions, threatening their sustainability. This study examines how hurricane intensity and persistence influence infrastructure loss, contributing to a more comprehensive understanding of climate-related risks. Using data from the National Oceanic and Atmospheric Administration (NOAA) Storm Events Database from 1996 to 2024, we develop a series of machine learning models to predict property losses based on storm characteristics and contextual vulnerability factors. Narrative-based text analysis and time-series feature engineering were applied to extract meteorological and temporal attributes, while regression and ensemble models were used for predictive evaluation. Results show that storm intensity alone explains only a small portion of loss variance, with persistence influencing damage primarily through rainfall and hydrological effects. The findings highlight that vulnerability, exposure, and cumulative risk dynamics are essential for accurate long-term prediction and for assessing infrastructure sustainability. Overall, the study demonstrates that combining machine learning techniques with climate and vulnerability data can inform future research on infrastructure sustainability. The quantified vulnerability-versus-intensity breakdown presented here can support post-disaster resource allocation, insurance risk modeling, and the prioritization of infrastructure maintenance in hurricane-prone regions. Full article

Background: Autophagy is a conserved intracellular degradation pathway essential for maintaining cellular homeostasis by recycling damaged organelles and proteins. Dysregulation of autophagy has been implicated in pregnancy-related complications such as preeclampsia and fetal growth restriction, underscoring its importance in maternal and fetal health. However, the autophagy status in the placental tissue of COVID-19-infected pregnant women remains unknown. Objective: To investigate autophagy activity in term placentas from pregnant women infected with COVID-19 compared to those from uninfected control pregnant women. Methods: In this prospective cross-sectional single-center study, 15 COVID-19-positive and 15 COVID-19-negative term pregnant women who delivered at Sultan Qaboos University Hospital between January 2020 and December 2022 were included. Immediately after delivery, the placental tissue samples were collected and assessed for autophagy activity using immunohistochemistry for LC3B and p62 markers, histopathological examination, and transmission electron microscopy. The proportion and intensity of LC3B and p62 staining were quantified. Statistical analysis was performed using the Mann–Whitney U test. Results: There was a significant reduction in p62 and LC3B expression in both the proportion and intensity in COVID-19 placentas compared to the control group. The proportion of p62 (p = 0.001) and LC3B (U = 46.000, p = 0.003) was significantly reduced in infected placentas. Similarly, intensity levels of both markers showed significant differences (p < 0.05), supporting the evidence of reduced LC3B/p62, suggesting autophagy modulation in COVID-19 patients’ placentas. Additionally, abnormal ultrastructural changes were observed in COVID-19–positive placentas, including mitochondrial injury, endoplasmic reticulum stress, microvillus loss, and basement membrane thickening. Conclusion: The study results from a limited sample size demonstrate a significantly altered autophagy flux in the placental tissues of term pregnant women with COVID-19 infection. These findings highlight the potential impact of COVID-19 infection on placental function and fetal development and underscore the need for further investigation into autophagy-modulating strategies to improve maternal–fetal health. Full article

In many densely populated towns and semi-urban areas, masonry buildings often stand close to busy roads, exposing them to blasts from improvised explosives or other localized sources. Such structures are rarely designed to resist sudden explosive forces, making severe damage or even progressive collapse likely. Even moderate-intensity blasts can weaken walls, endanger occupants, and cause significant property loss. Unlike reinforced concrete, masonry is highly susceptible to explosive impact. Therefore, understanding how these buildings behave under blast loads and developing affordable protection methods is crucial. Low-rise unreinforced masonry (URM) structures, usually up to about 13 m in height (roughly 2–4 stories), common in villages, semi-urban regions, and conflict-prone zones, are particularly at risk. In many areas, these poorly constructed buildings lack proper engineering design and are therefore highly vulnerable to blast damage. Non-load-bearing internal dividers and perimeter enclosures are especially prone to lateral displacement, which can initiate instability and, in severe cases, lead to overall structural failure. This research focuses on reducing catastrophic damage in URM walls when exposed to close-proximity blast forces using concrete-based protective coatings, both with and without embedded steel-welded wire mesh. The study references a previously tested laterally supported clay brick wall built with cement–sand mortar as the baseline model, with its behavior validated against experimental findings from existing literature. Two blast cases were considered corresponding to scaled stand-off distances of 2.19 m/kg^1/3 and 1.83 m/kg^1/3, representing moderate flexural-shear cracking and full structural failure, respectively. To replicate the observed behavior, a comprehensive 3D numerical simulation was developed using the ABAQUS/Explicit 2020 solver. The model’s predictions were benchmarked and verified through comparison with reported test data. While both blast intensities were used to confirm computational accuracy, the effectiveness of UHPC and UHPFRC protective coatings with and without embedded wire mesh was specifically evaluated under the more severe collapse scenario (Z = 1.83 m/kg^1/3). Results indicated that at a scaled distance of 1.83 m/kg^1/3, the uncoated URM wall could not withstand the blast because of poor tensile and bending capacity. In contrast, the UHPC- and UHPFRC-coatings provided improved confinement and better stress distribution. When welded wire mesh was embedded, crack control improved further, the interface bond strengthened, and a larger portion of blast energy was absorbed and dissipated. Full article

Background/Objectives: Acute radiotherapy-induced skin toxicity is a common complication in breast cancer treatment, with marked interindividual variability not fully explained by clinical factors. This study investigated the contribution of germline mutations in DNA repair and tumor suppressor genes to acute radiodermatitis in a homogeneous cohort treated with hypofractionated intensity-modulated radiotherapy with inverse planning, with adjustment for potential lifestyle confounders. Methods: Mutations were grouped into four functional categories: homologous recombination repair (HRR), Fanconi anemia (FA), DNA damage response (DDR), and tumor suppressor (TS) genes. Ordinal logistic regression models adjusted for clinical covariates evaluated pooled and functional category-specific mutation effects. Results: Overall, any mutation significantly increased the risk of higher-grade acute radiodermatitis (OR = 2.24, p = 0.003), an effect driven primarily by HRR and FA mutations, as exclusion of these mutations rendered the association non-significant (OR = 1.785, p = 0.064). Functional category-based analyses showed that HRR (OR = 2.60, p = 0.002) and FA (OR = 2.62, p = 0.002) mutations were the strongest predictors, reflecting overlapping roles in double-strand break and interstrand crosslink repair. DDR and TS mutations showed no significant effect. Conclusions: These results highlight the key role of high-fidelity DNA repair in normal tissue radiosensitivity and demonstrate that functional genetic stratification has diagnostic value as a pre-treatment predictive biomarker framework, enabling identification of patients at increased risk of acute skin toxicity and supporting personalized radiotherapy planning. Full article

Port areas are core hubs for national logistics and high-risk security zones that require constant vehicle access control. However, ensuring the reliability of automatic license plate recognition (ALPR) systems in port environments is severely challenged by complex image degradations, such as dense haze, low light, and motion blur. In this study, we propose a stage-wise degradation-aware restoration network (SDR-Net), which effectively addresses harsh port conditions by sequentially restoring photometric and structural degradations. Particularly, SDR-Net first secures visual cues lost to haze and low light through a photometric restoration module involving a dark-channel-prior-based dehazing and adaptive brightness adjustment. Next, a structural restoration module based on a generative adversarial network featuring edge-guided structural feature blocks and edge-aware refinement blocks is employed to precisely reconstruct character strokes and outlines damaged by motion blur, stably restoring license plate legibility even under complex degradation conditions. Experiments across various intensities of complex degradation demonstrate that SDR-Net maintains high character recognition accuracies of over 97.35% under mild motion blur and low-concentration haze conditions, indicating its superiority over state-of-the-art models. Notably, the performance gap between SDR-Net and comparison models widened as the degradation intensity increased, and SDR-Net achieved the highest multiscale structural similarity index scores across all intervals. Full article

This study elucidates the regulatory mechanisms of girdling on leaf senescence and fruit quality in ‘Jinyan’ kiwifruit, providing a theoretical basis for high-yield and high-quality cultivation. Ten-year-old vines were subjected to single (5 mm, 9 mm) and double (5 mm, 9 mm) girdling treatments at two distinct stages: peak flowering stage (Group A) and 10 days post-anthesis (Group B). Physiological markers, including reactive oxygen species (ROS) and antioxidant enzyme activities, were monitored at 10, 35, and 70 days post-treatment and integrated with fruit quality metrics using Principal Component Analysis (PCA). Physiologically, girdling induced a transient oxidative burst, characterized by increased ROS accumulation proportional to girdling intensity. This triggered a robust antioxidant defense response, where superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) activities peaked at 35 days, effectively mitigating oxidative damage (MDA) during the healing phase. Concurrently, metabolic substrates (soluble protein, starch, and sugar) were significantly enriched in leaves. Agronomically, all treatments enhanced fruit yield, single-fruit weight, and soluble solids content (SSC). Notably, double girdling treatments specifically promoted fruit elongation and dry matter accumulation. Comprehensive evaluation identified distinct optimal strategies: while moderate single girdling (A2) was superior during flowering, double girdling (B3, B4) proved most effective post-anthesis. Ultimately, double girdling performed 10 days post-anthesis emerged as the optimal regimen, effectively balancing source-sink relationships to maximize both physiological function and fruit quality. Full article

Influenza A virus (IAV) infection constitutes a major public health threat. Severe influenza virus infection can induce intense inflammatory responses and lung injury, leading to serious clinical symptoms or even death. The utility of current anti-influenza drugs is often limited by side effects and the emergence of drug-resistant strains. Based on the critical role of L-type voltage-gated calcium channels (L-VGCCs) in influenza virus replication, this study investigates the antiviral activity and mechanism of verapamil, a classic L-type calcium channel antagonist, against H1N1-UI182 virus. Verapamil, an L-type calcium channel blocker, is widely used in the treatment of cardiovascular diseases and has a well-established safety profile. Through molecular dynamics (MD) simulation and network pharmacology analysis, we predicted the stable binding mode of verapamil to the target protein (PDB id: 6JPA) and its potential multi-target network. In vitro, verapamil exhibited antiviral activity against H1N1-UI182 in MDCK cells, enhancing the survival rate of infected cells and reducing viral nucleoprotein (NP) expression. In a lethal H1N1-UI182 infection mouse model, verapamil treatment markedly improved survival rates, alleviated weight loss and lung pathological damage, exhibiting a dose-dependent protective effect. Lung tissue analysis showed that verapamil effectively reduced the lung index and viral load, suppressed the activation of the Nuclear factor kappa B (NF-κB) signaling pathway, and decreased the expression of key inflammatory factors, thereby mitigating the cytokine storm. A comparison of administration regimens indicated that pre-treatment yielded optimal efficacy, suggesting verapamil acts primarily during the early stage of the viral life cycle. This study systematically elucidates that verapamil exerts antiviral and immunomodulatory effects by regulating the NF-κB pathway. Network pharmacology analysis suggested the potential involvement of multiple targets and pathways, including EGFR, SRC, and phospholipase D signaling, providing hypotheses for future mechanistic investigation. This paper supports a drug repurposing strategy against drug-resistant influenza viruses and highlights its significant potential for clinical translation. Full article

Sliding contact wear at the pantograph–catenary interface directly impacts the current collection performance and power supply reliability of electrified railways. Addressing the challenges in multi-environmental wear studies—namely, fragmented modeling chains, inconsistent parameter calibrations, and prohibitive computational costs that hinder horizontal comparisons—this study develops an equivalent parameterized modeling framework tailored for engineering assessment. The framework encapsulates environmental effects as equivalent load increments and interface coefficient corrections, facilitating efficient multi-scenario parameter scanning within a 3D contact model. Findings reveal that environmental factors drive wear through a distinct “pressure-wear” nonlinear decoupling mechanism. In sandy environments, abrasive-mediated micro-cutting dominates, leading to a monotonic surge in wear depth as sand concentration increases, despite a buffered contact pressure response. In icing conditions, the synergy of low-temperature brittleness and geometric impact renders hotspot wear highly sensitive to temperature fluctuations. For salt spray conditions, the environmental impact is represented via equivalent corrections to the interfacial parameters; within this equivalent framework, the results suggest that salt spray intensity has a more pronounced effect on wear accumulation than humidity alone. This work reveals the divergence of dominant damage pathways across environments, offering a quantitative basis for the differentiated maintenance and remaining life estimation of pantograph–catenary systems in extreme climates. Full article

Achieving high morphological uniformity and mechanical strength is critical for the automation of watermelon grafting; yet, specific light protocols targeting these traits are lacking. This study employed LED lighting to regulate the morphological development of watermelon scion seedlings in a controlled plant factory environment. Using the watermelon cultivar ‘Heimeiling’ as the experimental material, three sequential experiments were conducted: (1) Under conditions of 95 μmol·m⁻²·s⁻¹ light intensity and a 12 h photoperiod, seven red/blue light ratios and a white light control were tested to identify the appropriate light quality. (2) Under the R3B1 light quality, gradients of the daily light integral (DLI) ranging from 2.88 to 17.28 mol·m⁻²·d⁻¹ were established by adjusting the light intensity and photoperiod to determine the optimal DLI. (3) Based on the above results, an orthogonal experiment was designed, with factors including the light quality (R7B1, R3B1, R1B1; where R7B1 represents 87.5% red light and 12.5% blue light), light intensity (120, 160, 200 μmol·m⁻²·s⁻¹), and photoperiod (16 h, 20 h, 24 h) to identify the optimal light environment combination for mechanical grafting. Results indicated that while monochromatic red light induced excessive elongation and suppressed metabolism, the R3B1 spectrum significantly enhanced the stem diameter, mechanical strength, and carbon–nitrogen accumulation while maintaining hormonal balance. Regarding the daily light integral (DLI), seedlings exhibited an optimal performance at 11.52 mol·m⁻²·d⁻¹. Lower DLI levels led to etiolation, whereas higher levels caused photoinhibition and PSII damage. Furthermore, orthogonal analysis revealed that light intensity was the dominant factor driving stem thickening and biomass accumulation, while light quality primarily regulated plant height. Consequently, a combination of R3B1 light quality, 200 μmol·m⁻²·s⁻¹ intensity, and a 20 h photoperiod was identified as the optimal strategy to satisfy the stringent morphological requirements for mechanical grafting. Full article

Background/Objectives: Proton therapy has emerged as an advanced radiotherapy modality due to its unique physical dose distribution and its distinct radiobiological properties. The finite range of protons in tissue enables highly conformal dose delivery with minimal exit dose, significantly reducing irradiation of surrounding normal tissues compared to photon-based radiotherapy. Beyond these physical advantages, proton beams exhibit a spatially varying linear energy transfer that increases toward the distal edge of the spread-out Bragg peak, leading to clustered and complex DNA damage that is more difficult for cancer cells to repair. Methods: This review integrates experimental, computational, and clinical evidence to examine how proton-induced DNA damage, relative biological effectiveness, oxygen effects, and non-targeted responses contribute to tumor control and normal tissue sparing. Results: Comparative analyses with photon intensity-modulated radiotherapy demonstrate consistent reductions in acute and late toxicities across multiple tumor sites, particularly in pediatric patients and in tumors located near critical organs. The review also discusses emerging technologies, including pencil beam scanning, image-guided and adaptive proton therapy, compact accelerator systems, and ultra-high dose rate FLASH proton therapy, which collectively aim to enhance treatment precision, biological effectiveness, and accessibility. Conclusions: Together, these developments support proton therapy as a rapidly evolving modality with significant potential to improve therapeutic outcomes in modern oncology. Full article

This research introduces a novel approach for seismic fragility assessment by employing a long short-term memory (LSTM) neural network to identify the most effective scalar and vector intensity measures (IMs). This approach enables the rapid and accurate plotting of vector fragility surfaces for shield tunnels embedded in layered soils and subjected to seismic actions. First, an extensive suite of two-dimensional, fully nonlinear soil–structure interaction analyses was executed to generate ground–motion–structure response pairs. These records were subsequently leveraged to train the LSTM network, which received free-field acceleration time histories and directly output critical engineering demand parameters along the tunnel lining. The developed framework significantly mitigates computational expenses while maintaining an acceptable level of fidelity relative to the reference finite element results. Consequently, it serves as an alternative to traditional time history evaluation techniques. Second, we conducted an IM screening process using the results of the LSTM predictions. On the basis of criteria such as relevance, efficiency, practicality, and professionalism, we benchmarked 17 scalar IM and 3 vector IM candidate schemes. The findings indicate that the peak ground velocity (PGV) serves as the most effective scalar IM, whereas the combination of peak ground acceleration (PGA) and PGV forms the optimal vector IM. Finally, probabilistic demand and capacity models are integrated within a fully analytical fragility formulation to derive both scalar and vector fragility estimates. Comparative evaluation reveals that vector IM based fragility surfaces markedly reduce epistemic uncertainty and furnish refined probabilistic descriptions of damage states (DSs) across the seismic demand space. Full article

Global climate change has increased the frequency and intensity of heat waves, posing a significant threat to livestock production. During heat exposure, the disruption of intestinal barrier integrity is a pivotal event in the pathogenesis of heat stress-induced intestinal injury. Endoplasmic reticulum (ER) stress and mitochondrial dysfunction are key consequences of heat stress at the cellular level. However, direct causal evidence linking ER stress to mitochondrial dysfunction in heat-stressed enterocytes remains limited. To investigate this, we used an integrated transcriptomic, metabolomic, and functional validation strategy to assess mitochondrial bioenergetics and cellular ultrastructure in porcine intestinal epithelial (IPEC-J2) cells under acute heat stress. Transcriptomic analysis revealed extensive reprogramming, highlighting the significant enrichment of pathways related to protein processing in the endoplasmic reticulum, apoptosis, and MAPK signaling. Untargeted metabolomics identified significant perturbations in amino acid and energy metabolism, as well as altered bile acid profiles. Functional assessments confirmed that heat stress severely impaired mitochondrial bioenergetics, as evidenced by reduced maximal respiration and ATP production, and induced ultrastructural damage to mitochondria. The pharmacological inhibition of ER stress by 4-phenylbutyric acid (4-PBA) significantly attenuated the mitochondrial bioenergetic impairment and ultrastructural damage, whereas ER stress induction recapitulated these defects. We demonstrate that heat stress induces profound transcriptional and metabolic remodeling characterized by ER stress activation, which critically mediates subsequent mitochondrial bioenergetic dysfunction and ultrastructural damage. Our findings suggest that targeting ER stress may represent a promising therapeutic strategy to ameliorate enterocyte mitochondrial dysfunction and mitigate heat stress-induced intestinal injury in livestock. Full article