Search Results (2,558)

The shear characteristics of the frozen soil–concrete interface are core parameters in frost heave resistance design in cold-region engineering, and the influence mechanism of interface roughness on these characteristics is not clear. In this study, the regulatory effect of different roughness levels (R-0 to R-4) on the interfacial freezing strength was quantitatively analyzed for the first time through direct shear tests, and the evolution characteristics of the contribution ratio of the ice cementation strength were revealed. The results show that the peak shear strength of the interface increases significantly with the roughness (when the normal stress is 400 kPa and the water content is 14%, the increase in R-4 is 47.7% compared with R-0); the ice cementation strength increases synchronously and its contribution ratio increases with the increase in roughness. Although the absolute value of the residual strength increase is small, the relative amplitude is larger (178.5% increase under the same working conditions). The peak cohesion increased significantly with the roughness (R-0 to R-4 increased by 268.6%), while the residual cohesion decreased. The peak and residual internal friction angle increased slightly with the roughness. The study clarifies the differential influence mechanism of roughness on the interface’s shear parameters and provides a key quantitative basis for the anti-frost heave design of engineering interfaces in cold regions. Full article

Detecting power transformer winding degradations at an early stage is very important for the safe operation of nuclear power plants. Most transformer failures are caused by insulation breakdown; the winding turn-to-turn short circuit fault is frequently encountered. Experience has shown that routine testing techniques, e.g., winding resistance, leakage inductance, and sweep frequency response analysis (SFRA), are not sensitive enough to identify minor turn-to-turn short defects. The SFRA technique is effective only if the fault is in such a condition that the flux distribution in the core is prominently distorted. This paper proposes the frequency domain reflectometry (FDR) technique for detecting and locating transformer winding defects. FDR measures the wave impedance and its change along the measured windings. The wire over a plane model is selected as the transmission line model for the transformer winding. The effectiveness is verified through lab experiments on a twist pair cable simulating the transformer winding and field testing on a real transformer. The FDR technique successfully identified and located the turn-to-turn short fault that was not detected by other testing techniques. Using FDR as a complementary tool for winding condition assessment will be beneficial. Full article

The resistivity imaging system is specifically designed for the precise measurement of resistivity distributions within drilled columnar core samples. Its coaxial symmetric configuration enables the non-destructive characterization of electrical properties, with broad applications in oil and gas exploration, reservoir evaluation, and geological research. By integrating a ring return electrode and full-circumference electrode arrays, the system can acquire core-scale resistivity data in conductive media environments. The self-developed imaging software employs advanced processing algorithms—including depth correction, amplitude normalization, and image enhancement—to transform raw resistivity measurements into high-resolution surface imaging maps. Experimental results demonstrate that the system can resolve features such as cracks with a minimum width of 0.5 mm and pores with a minimum inner diameter of 0.4 mm in granite core, providing a novel technical approach for the fine-scale characterization of core materials. Full article

Freshwater salinization, an escalating global environmental stressor, poses a significant threat to freshwater biodiversity, including fish communities. This study investigates the grass carp (Ctenopharyngodon idellus), a species with the highest aquaculture output in China, to elucidate the molecular underpinnings of its physiological adaptations to fluctuating salinity gradients. We used high-throughput mRNA sequencing and differential gene expression profiling to analyze transcriptional dynamics in intestinal and kidney tissues of grass carp exposed to heterogeneous salinity stressors. Concurrent serum biochemical analyses showed salinity stress significantly increased Na⁺, Cl⁻, and osmolarity, while decreasing lactate and glucose. Salinity stress exerted a profound impact on the global transcriptomic landscape of grass carp. A substantial number of co-regulated differentially expressed genes (DEGs) in kidney and intestinal tissues were enriched in immune and metabolic pathways. Specifically, genes associated with antigen processing and presentation (e.g., cd4-1, calr3b) and apoptosis (e.g., caspase17, pik3ca) exhibited upregulated expression, whereas genes involved in gluconeogenesis/glycolysis (e.g., hk2, pck2) were downregulated. KEGG pathway enrichment analyses revealed that metabolic and cellular structural pathways were predominantly enriched in intestinal tissues, while kidney tissues showed preferential enrichment of immune and apoptotic pathways. Rigorous validation of RNA-seq data via qPCR confirmed the robustness and cross-platform consistency of the findings. This study investigated the core transcriptional and physiological mechanisms regulating grass carp’s response to salinity stress, providing a theoretical foundation for research into grass carp’s resistance to salinity stress and the development of salt-tolerant varieties. Full article

Background/Objectives: Strengthening antimicrobial stewardship (AMS) programs is an invaluable intervention in the ongoing efforts to contain the threat of antimicrobial resistance (AMR), particularly in low-resource settings. This study evaluates the impact of the Telementoring, Education, and Advocacy Collaboration initiative for Health through Antimicrobial Stewardship (TEACH AMS), which uses the virtual Extension for Community Healthcare Outcomes (ECHO) learning model to enhance AMS capacity in Kenya, Ghana, and Malawi. Methods: A mixed-methods approach was used, which included attendance data collection, facility-level assessments, post-session and follow-up surveys, as well as focus group discussions. Results: Between September 2023 and February 2025, 77 virtual learning sessions were conducted, engaging 2445 unique participants from hospital-based AMS committees and health professionals across the three countries. Participants reported significant knowledge gain, and data showed facility improvements in two core AMS areas, including the implementation of multidisciplinary ward-based interventions/communications and enhanced monitoring of antibiotic resistance patterns. Along those lines, participants reported that the program assisted them in improving prescribing and culture-based treatments, and also evidence-informed antibiotic selection. The evidence of implementing ward-based interventions was further stressed in focus group discussions, as well as other strengthened practices like point-prevalence surveys, and development or revision of stewardship policies. Substantial improvements in microbiology services were also shared by participants, particularly in Malawi. Other practices mentioned were strengthened multidisciplinary communication, infection prevention efforts, and education of patients and the community. Conclusion: Our findings suggest that a virtual case-based learning educational intervention, providing structured and tailored AMS capacity building, can drive behavior change and strengthen healthcare systems in low resource settings. Future efforts should aim to scale up the engagements and sustain improvements to further strengthen AMS capacity. Full article

Background/Objectives: Enterococci, particularly Enterococcus faecalis and Enterococcus faecium, are Gram-positive cocci that can cause severe infections in hospitalized patients. The rise of vancomycin-resistant enterococci (VRE) and vancomycin-variable enterococci (VVE) poses significant challenges in healthcare settings due to their resistance to multiple antibiotics. Methods: We conducted a point prevalence survey (PPS) to assess the prevalence of VRE and VVE colonization in hospitalized patients. Rectal swabs were collected from 160 patients and analyzed using molecular assays (MAs) and culture. Whole-genome sequencing (WGS) and core-genome multilocus sequence typing (cgMLST) were performed to identify the genetic diversity. Results: Of the 160 rectal swabs collected, 54 (33.7%) tested positive for the vanA and/or vanB genes. Culture-based methods identified 47 positive samples (29.3%); of these, 44 isolates were identified as E. faecium and 3 as E. faecalis. Based on the resistance profiles, 35 isolates (74.5%) were classified as VRE, while 12 (25.5%) were classified as VVE. WGS and cgMLST analyses identified seven clusters of E. faecium, with sequence type (ST) 80 being the most prevalent. Various resistance genes and virulence factors were identified, and this study also highlighted intra- and inter-ward transmission of VRE strains. Conclusions: Our findings underscore the potential for virulence and resistance of both the VRE and VVE strains, and they highlight the importance of effective infection control measures to prevent their spread. VVE in particular should be carefully monitored as they often escape detection. Integrating molecular data with clinical information will hopefully enhance our ability to predict and prevent future VRE infections. Full article

Enhancing the wear resistance of structural steels used in demanding industrial applications is critical for extending components’ lifespan and ensuring mechanical reliability. In this study, we investigated the influence of flux-cored arc welding (FCAW) hardfacing on the tensile behavior of S355MC steel. Protective Fe-Cr-C alloy layers were deposited in one and two successive passes using automated FCAW, followed by tensile testing of specimens oriented at varying angles relative to the weld bead direction. The methodology integrated 3D scanning and digital image correlation to accurately capture geometric and deformation parameters. The experimental results revealed a consistent reduction in tensile strength and ductility in all the welded configurations compared to the base material. The application of the second weld layer further intensified this effect, while specimen orientation influenced the degree of mechanical degradation. Microstructural analysis confirmed carbide refinement and good adhesion, but also identified welding-induced defects and residual stresses as factors that contributed to performance loss. The findings highlight a clear trade-off between improved surface wear resistance and compromised structural properties, underscoring the importance of process optimization. Strategic selection of welding parameters and bead orientation is essential to balance functional durability with mechanical integrity in industrial applications. Full article

Electromagnetic and magnetic devices are increasingly prevalent in sectors such as transportation, industry, and renewable energy due to the ongoing electrification trend. These devices exhibit nonlinear behavior, particularly under signals rich in harmonics. They require precise and appropriate modeling for accurate sizing. Identifying model-specific parameters, which depend on frequency, is crucial. This article focuses on a specific frequency range where a circuit model with series resistance and inductance, along with a parallel resistance to account for iron losses (${\mathrm{R}}_{\mathrm{iron}}$), is applicable. While the determination of series elements is well documented, the determination of ${\mathrm{R}}_{\mathrm{iron}}$ remains complex and debated, with traditional methods neglecting operating conditions such as magnetic saturation. To address these limitations, an innovative experimental method is proposed, comprising two main steps: determining the complex impedance of the magnetic device and extracting ${\mathrm{R}}_{\mathrm{iron}}$ from the model. This method aims to provide a more precise and representative estimation of ${\mathrm{R}}_{\mathrm{iron}}$, improving the reliability and accuracy of electromagnetic and magnetic device simulations and designs. The obtained values of the iron loss equivalent resistance are different by at least 300% than those obtained by an impedance analyzer. The proposed method is expected to advance the understanding and modeling of losses in electromagnetic and magnetic devices, offering more robust tools for engineers and researchers in optimizing device performance and efficiency. Full article

Since the initial use of biological ion channels to detect single-stranded genomic base pair differences, label-free and highly sensitive resistive pulse sensing (RPS) with nanopores has made remarkable progress in single-molecule analysis. By monitoring transient ionic current disruptions caused by molecules translocating through a nanopore, this technology offers detailed insights into the structure, charge, and dynamics of the analytes. In this work, the RPS platforms based on biological, solid-state, and other sensing pores, detailing their latest research progress and applications, are reviewed. Their core capability is the high-precision characterization of tiny particles, ions, and nucleotides, which are widely used in biomedicine, clinical diagnosis, and environmental monitoring. However, current RPS methods involve bottlenecks, including limited sensitivity (weak signals from sub-nanometer targets with low SNR), complex sample interference (high false positives from ionic strength, etc.), and field consistency (solid-state channel drift, short-lived bio-pores failing POCT needs). To overcome this, bio-solid-state fusion channels, in-well reactors, deep learning models, and transfer learning provide various options. Evolving into an intelligent sensing ecosystem, RPS is expected to become a universal platform linking basic research, precision medicine, and on-site rapid detection. Full article

The estimation of the state of health (SOH) of lithium-ion batteries is a critical technology for enhancing battery lifespan and safety. When estimating SOH, it is essential to select representative features, commonly referred to as health indicators (HIs). Most existing studies primarily focus on HIs related to capacity degradation and internal resistance increase. However, due to the complexity of lithium-ion battery degradation mechanisms, the relationships between these mechanisms and health indicators remain insufficiently explored. This paper provides a comprehensive review of core methodologies for SOH estimation, with a particular emphasis on the classification and extraction of health indicators, direct measurement techniques, model-based and data-driven SOH estimation approaches, and emerging trends in battery management system applications. The findings indicate that capacity, internal resistance, and temperature-related indicators significantly impact SOH estimation accuracy, while machine learning models demonstrate advantages in multi-source data fusion. Future research should further explore composite health indicators and aging mechanisms of novel battery materials, and improve the interpretability of predictive models. This study offers theoretical support for the intelligent management and lifespan optimization of lithium-ion batteries. Full article

Insulin resistance (IR), a core component in the development of type 2 diabetes mellitus (T2DM), is increasingly recognized for its role in cardiovascular and pulmonary complications. This review explores the relationship between IR, right ventricular dysfunction (RVD), and decreased lung volume in patients with T2DM. Emerging evidence suggests that IR contributes to early structural and functional alterations in the right ventricle, independent of overt cardiovascular disease. The mechanisms involved include oxidative stress, inflammation, dyslipidemia, and obesity—factors commonly found in metabolic syndrome and T2DM. These pathophysiological changes compromise right ventricular contractility, leading to reduced pulmonary perfusion and respiratory capacity. RVD has been associated with chronic lung disease, pulmonary hypertension, and obstructive sleep apnea, all of which are prevalent in the diabetic population. As RVD progresses, it can result in impaired gas exchange, interstitial pulmonary edema, and exercise intolerance—highlighting the importance of early recognition and management. Therapeutic strategies should aim to improve insulin sensitivity and cardiac function through lifestyle interventions, pharmacological agents such as SGLT2 inhibitors and GLP-1/GIP analogs, and routine cardiac monitoring. These approaches may help slow the progression of RVD and its respiratory consequences. Considering the global burden of diabetes and obesity, and the growing incidence of related complications, further research is warranted to clarify the mechanisms linking IR, RVD, and respiratory dysfunction. Understanding this triad will be crucial for developing targeted interventions that improve outcomes and quality of life in affected patients. Full article

Fungal infections pose a significant yet under-recognised global health burden, affecting over one billion individuals annually and contributing to approximately 2.5 million direct deaths. The World Health Organisation (WHO) has recently reemphasised this issue through the publication of its Fungal Priority Pathogens List (FPPL) and its 2025 report evaluating current antifungal diagnostics and therapeutics. Among the most prevalent fungal pathogens is Trichophyton rubrum, an anthropophilic dermatophyte responsible for up to 70% of superficial fungal infections, including onychomycosis. The emergence of antifungal resistance further complicates management, necessitating the development of novel, effective, and sustainable treatment alternatives. Natural compounds are increasingly being explored for their antifungal potential due to their broad-spectrum activity and lower toxicity. Coconut oil has gained particular attention for its therapeutic properties attributed to medium-chain fatty acids (MCFAs), especially lauric acid. The aim of this study was to understand how innate and modified coconut oils can alter the rheological properties of Pluronic hydrogels while retaining antifungal activity for downstream application in treating fungal infections. Results identified hydrophobic interactions by FTIR and DSC between the hydrocarbon chains of the coconut triglycerides and the hydrophobic core of the Pluronic micelles, leading to gel stabilisation as identified by rheological analysis. Full article

The gut microbiota plays an essential role in the host’s metabolism. Its composition and structure depend on biological and environmental factors. This work was designed to identify the composition and structure of the wild and captive red grouper (Epinephelus morio) microbiota and make predictions regarding its metabolic functions. Our hypothesis stated that wild and captive individuals would share the most abundant taxonomic groups, forming a core microbiota, and individuals in captivity might have exclusive taxonomic groups. Metagenomic DNA was extracted from the intestinal contents of wild and captive individuals. The 16S rRNA gene was amplified and sequenced using Illumina pair-end technology. QIIME2 pipeline was used for sequence analysis and alpha and beta diversity assessment. PICRUSt was used to infer metabolic functions. Twenty-nine phyla were identified; the most abundant were Pseudomonadota, Bacillota, Fusobacteriota, and Actinomycetota. The dominant genera were Photobacterium, Vibrio, Cetobacterium, and Escherichia-Shigella. The metabolic prediction analysis suggested that the Epinephelus morio gut microbiota is related to food digestion, the immune system, antioxidant enzymes, antibiotic resistance, and vitamin B12 transport. We concluded that the microbiota of E. morio established in captivity is sensitive to environmental changes such as water pollution, which can cause a decrease in diversity. Full article

To ensure confidentiality and integrity in the era of quantum computing, most post-quantum cryptographic schemes are designed to achieve either encryption or digital signature functionalities separately. Although a few signcryption schemes exist that combine these operations into a single, more efficient process, they typically rely on complex vector, matrix, or polynomial-based structures. In this work, a novel post-quantum public-key encryption and signature (PQES) scheme based entirely on scalar integer operations is presented. The proposed scheme employs a simplified structure where the ciphertext, keys, and core cryptographic operations are defined over scalar integers modulo n, significantly reducing computational and memory overhead. By avoiding high-dimensional lattices or ring-based constructions, the PQES approach enhances implementability on constrained devices while maintaining strong security properties. The design is inspired by modified learning-with-errors (LWE) assumptions, adapted to scalar settings, making it suitable for post-quantum applications. Security and performance evaluations, achieving a signcryption time of 0.0007 s and an unsigncryption time of 0.0011 s, demonstrate that the scheme achieves a practical balance between efficiency and resistance to quantum attacks. Full article

Aramid fibre has become a critical material for individual soft body armour due to its lightweight nature and exceptional impact resistance. To investigate its energy absorption mechanism, quasi-static and dynamic tensile experiments were conducted on Kevlar^® 29 plain-woven fabric using a universal material testing machine and a Split Hopkinson Tensile Bar (SHTB) apparatus. Tensile mechanical responses were obtained under various strain rates. Fracture morphology was characterised using scanning electron microscopy (SEM) and ultra-depth three-dimensional microscopy, followed by an analysis of microstructural damage patterns. Considering the strain rate effect, a viscoelastic constitutive model was developed. The results indicate that the tensile mechanical properties of Kevlar^® 29 plain-woven fabric are strain-rate dependent. Tensile strength, elastic modulus, and toughness increase with strain rate, whereas fracture strain decreases. Under quasi-static loading, the fracture surface exhibits plastic flow, with slight axial splitting and tapered fibre ends, indicating ductile failure. In contrast, dynamic loading leads to pronounced axial splitting with reduced split depth, simultaneous rupture of fibre skin and core layers, and fibrillation phenomena, suggesting brittle fracture characteristics. The modified three-element viscoelastic constitutive model effectively captures the strain-rate effect and accurately describes the tensile behaviour of the plain-woven fabric across different strain rates. These findings provide valuable data support for research on ballistic mechanisms and the performance optimisation of protective materials. Full article