Search Results (79,207)

The special back feeding energization process involves several stages, including tie-transformer energization, GIS-busbar energization, and no-load line energization. These operations can generate transient overvoltages and impose considerable stress on equipment insulation. To investigate the associated transient characteristics, field tests were conducted at a 500 kV GIS substation. Transient signals were recorded during tie-transformer energization and GIS-busbar switching, and the responses at different stages were analyzed. An electromagnetic transient model was subsequently developed in PSCAD/EMTDC and validated against the field measurements. The validated model was then used to investigate the key factors affecting no-load line energization through a GIS outgoing bay. The results show that tie-transformer energization is dominated by nonlinear core excitation. As the system operating state is progressively established, the transient responses during GIS-busbar and transmission line energization are governed mainly by network parameters and switching conditions. During no-load line energization, the closing phase angle and closing resistor condition are the dominant factors affecting switching overvoltage. Degradation of the closing resistor weakens transient suppression and increases the insulation stress on connected equipment. These findings provide a technical basis for evaluating energization transients and optimizing operating conditions during the commissioning of 500 kV GIS installations. Full article

Congenital fibrinogen disorders (CFDs) comprise quantitative deficiencies—afibrinogenemia and hypofibrinogenemia—and qualitative defects—dysfibrinogenemia and hypodysfibrinogenemia. This review is confined to the quantitative disorders, and the term quantitative CFDs is used throughout in preference to the wider umbrella term; qualitative defects are considered only insofar as they must be distinguished at the bench. Afibrinogenemia results from biallelic loss-of-function variants in FGA, FGB, or FGG, and is defined by fibrinogen activity below the analytical limit of detection with undetectable antigen; hypofibrinogenemia results from monoallelic variants and is defined by a proportionate reduction in activity and antigen. Several authoritative reviews of this field have appeared recently. The contribution intended here differs in emphasis. Rather than restate the stepwise diagnostic approach, we set out what actually goes wrong at the bench: the analytical variability among fibrinogen methods, the behavior of the Clauss assay near its limit of detection, and overestimation by prothrombin time-derived fibrinogen. We also address interference from anticoagulants and sample factors, the requirement for laboratory-specific reference intervals, the interpretation of discordant results, and the molecular workflow, including copy-number analysis and the handling of variants of uncertain significance. We also address a question that the descriptive literature largely leaves open: why patients carrying identical variants, sometimes within a single family, differ so markedly in phenotype. We propose a four-layer framework—cis-acting effects at the fibrinogen locus, hepatocyte proteostasis and endoplasmic reticulum quality control, trans-acting genetic modifiers, and acquired factors—and review the evidence supporting each. Population genomic data are reconsidered: current estimates derived from gnomAD suggest that predicted-deleterious fibrinogen genotypes are considerably more frequent than clinically ascertained disease, a discrepancy that reflects incomplete penetrance and the limits of in silico prediction rather than a hidden burden of undiagnosed severe disease. Management recommendations are presented with the strength of the supporting evidence made explicit. Fibrinogen concentrate is a first-line replacement. Widely accepted targets are a peak > 1.5 g/L before major surgery, and >1.0 g/L before minor procedures; >1.0 g/L postoperatively until hemostasis, and >0.5 g/L until wound healing; and a trough ≥ 1.0 g/L in pregnancy, rising to ≥1.5 g/L peripartum. All data are derived from expert consensus, registry data, and small interventional series rather than randomized trials, and are presented here as starting points for individualized care. Paradoxical thrombosis, its uncertain mechanism, and the possibility that replacement precipitates it are treated as an unresolved problem rather than a footnote. Full article

Aged pipeline networks face interacting operational, electrochemical, structural, and metallurgical degradation mechanisms that are often assessed independently, limiting diagnosis of system-wide failure propagation. This study develops an integrated, interpreTable fuzzy-logic framework to detect, quantify, and isolate failure scenarios in a 572 km pipeline network. The methodology combines 596 historical SCADA and SAP records, cathodic-protection and soil measurements from 907 evaluation points, 4651 ultrasonic-inspection anomalies, mechanical and metallographic characterization of API L X65 steel, and validated expert knowledge. Four Mamdani fuzzy inference systems were constructed to represent operational capacity, cathodic-protection performance, mechanical integrity, and metallurgical degradation. Their outputs were combined into a unified fault-signature matrix comprising 28 failure scenarios. Scenario FS-3 produced the broadest systemic response by activating all diagnostic residuals. Metallurgical scenarios FS-22 to FS-28 activated 61% of the matrix, showing their extensive influence on pipeline integrity. Structural scenarios FS-15 to FS-21 showed progressively broader signatures as wall deterioration increased. Meanwhile, FS-1, FS-2, FS-5, FS-6, and FS-7 remained localized and were more readily isolated. The proposed framework preserves diagnostic traceability through explicit input variables, fuzzy rules, and residual signatures. It provides an interpreTable basis for failure classification, diagnostic signature breadth, maintenance prioritization, and operator decision support. Its conclusions are limited to the analyzed network and require external validation before application to other pipeline systems. Full article

Conventional cast-in-place foundations can require substantial on-site work, motivating transportable precast alternatives for substation equipment. This study proposes a prestressed precast concrete isolated foundation (PPCIF), comprising a pedestal and stepped footing assembled with post-tensioned threaded bars. Component and connection design checks are combined with a three-dimensional finite-element model incorporating concrete damaged plasticity, discrete reinforcement, frictional contact, and soil–foundation interaction. Sixteen design cases cover four ground profiles and four prescribed load cases. The reported maximum settlement ranges from approximately 1.0 mm in the rock profile to 16.2 mm in the collapsible-loess parameter set. Local concrete compressive stress reaches 21.66 MPa, and tensile damage reaches 0.975 near the pedestal and ducts, identifying anchorage-region detailing as a priority for refinement. Prestressing supports compressive force transfer across the assembled interfaces, whose performance also depends on local relative movement. A supplementary J1 soil-mesh comparison gives loading-point settlement increments of 15.968, 15.174, and 16.104 mm at 895.6 kN. The combined results link ground-dependent settlement to local connection demand and provide a numerical basis for refining the modular foundation under the considered design loads. The findings constitute a preliminary parametric exploration under prescribed design actions and are intended to guide, rather than replace, experimental validation and project-specific design verification. Full article

This study focuses on modeling and experimental validation of drilling forces in low-frequency vibration-assisted bone drilling (LVAD), with explicit consideration of bone anisotropic effects. A mechanistic force model is established by integrating contributions from the main cutting edges and chisel edge, and a direction-dependent anisotropic coefficient is introduced to characterize the anisotropic shear strength of cortical bone. The influences of feed rate, spindle speed, drill diameter, vibration amplitude, frequency, and drilling orientation on drilling forces are analyzed theoretically and experimentally. Results show that drilling forces increase with feed rate and drill diameter and decrease with spindle speed and vibration amplitude. LVAD reduces drilling forces by up to 16.52% compared with conventional drilling. Perpendicular drilling produces lower forces than oblique drilling, and forces in the yz-plane are higher than those in the xz-plane due to bone anisotropy. The proposed model is well verified by experiments, providing a theoretical basis for parameter optimization in clinical bone drilling. Full article

Carbon fiber reinforced polymer (CFRP) is extensively employed in aerospace and advanced equipment industries for its outstanding mechanical performance and corrosion resistance. As conventional micro-drilling (CMD) easily induces excessive cutting force, accumulated heat, burrs and matrix thermal damage that degrade hole quality, this paper presents an experimental and theoretical investigation on the cutting force and thermal characteristics of CFRP in ultrasonic-assisted micro-drilling (UAMD). Combined with finite-element method (FEM) simulation and machining experiments, the machinability evolution law of CFRP under different machining methods and parameters is systematically explored. A self-developed high-frequency vibration spindle is adopted to improve the micro-hole machinability of CFRP materials. The paper systematically analyzes the cutting force, cutting heat, tool wear and other experimental results under CMD and UAMD with various machining parameters. To ensure the reliability of the research data, a corresponding finite-element model for CFRP micro-drilling was established and validated through experimental tests. The results demonstrate that UAMD can effectively improve the machining condition and suppress cutting force and cutting heat. Compared with the conventional CMD process, UAMD reduces the cutting force and cutting heat of CFRP micro-drilling by up to 16.3% and 19.6%, respectively. The high-frequency intermittent vibration effect of ultrasonic assistance facilitates heat dissipation, alleviates tool abrasion, and significantly extends tool service life. The proposed UAMD method effectively optimizes the cutting force and thermal characteristics in CFRP micro-drilling, providing a credible theoretical basis and technical reference for high-quality and high-precision micro-hole machining of CFRP materials. Full article

Machine learning technologies are increasingly being used in data analysis as potential tools for assessing natural resources. The goal of this study is to determine how successfully the recently released Time Series Modeller (MATLAB R2026a) predicts wind conditions in the Black Sea basin’s nearshore zones. Ten years of hourly ERA5 data (2016–2025) were considered, with the predicted parameters being related to wind speed (at 100 m height) and the corresponding wind direction. A number of deep learning models were evaluated, and the findings were presented using statistical metrics such as RMSE (Root Mean Squared Error), relative error, and the Weibull distribution. The ERA5 and anticipated wind speed showed fair agreement, with the exception of extremely low (<3 m/s) and high wind speeds (>18 m/s), which may have been inflated by the statistical indicator used. The wind dispersion was examined on a monthly and hourly basis. In terms of wind direction, it was discovered that deep learning models are unable to replicate wind conditions from the north sector; nevertheless, this appears to be an issue with models based on RMSE prediction. Full article

RGBT segmentation is a challenging task in the area of computer vision. Current advanced networks for RGBT segmentation focus on extracting deeper discriminative features from RGB and thermal images to provide richer semantic information for the fusion features to the decoder. However, excessively mining deeper semantic features only makes the model redundant. Simultaneously, lacking shallow spatial features leads to difficulties in guaranteeing accurate localization of targets. We believe that the features provided by images can be categorized into three types: edge, patch, and semantics. Only by synchronously taking into account the extraction of all three types of features can models achieve accurate classification on the basis of precise localization. Therefore, we propose Depth Adaption SegNet for RGB-T Segmentation (DASNet). According to the characteristics of the three types of features, we extract semantics, patch, and edge features from the deep, middle, and shallow stages respectively. We specifically design the cross-attention semantics module, patch activation module, and edge enhancement module to perform feature extraction. In addition, in order to efficiently fuse features from different categories, we design a deep-emphasis fusion module to fuse the output features of the modules. Compared to advanced methods, qualitative and quantitative experiments show that DASNet exhibits state-of-the-art performance on the CNN-based RGBT segmentation task. Full article

The construction sector faces environmental pressures from material use, waste, energy and carbon emissions. Building Information Modelling (BIM) and Design for Manufacture and Assembly (DfMA) can support environmental improvement through more integrated design, production and assembly. However, environmental benefits are often attributed to BIM-enabled DfMA without direct assessment, and it remains unclear which outcomes have been demonstrated and which mechanisms are associated with them. This study addresses this gap through a systematic literature review of 43 studies published between 2018 and 2026. Using an evidence-based management lens, the review examined BIM–DfMA integration, the environmental outcomes and mechanisms reported, and their evidential basis. Material efficiency and waste reduction were the most frequently reported outcomes and had the largest directly assessed evidence base, whereas carbon reduction, energy efficiency and circularity were less frequently assessed. Design optimisation, reduced rework, standardisation and reduced component variation were the most frequently identified mechanisms. The review proposes a conceptual framework showing that BIM–DfMA adoption alone does not establish environmental improvement and that environmental performance needs to be considered in relation to environmental criteria embedded in decisions, the material and construction system, and the lifecycle stages assessed. BIM–DfMA workflows should therefore include measurable environmental criteria, defined baselines and appropriate assessment boundaries to support consistent evaluation of environmental claims. Full article

Tubular injury induced by mitophagy or ferroptosis serves as a critical pathological basis for the progression of diabetic kidney disease (DKD). Mitophagy constitutes a critical process of mitigating tubular injury by eliminating damaged organelles to maintain cellular equilibrium and homeostasis. Ferroptosis, a form of programmed cell death characterized by lipid peroxidation, serves as a pivotal factor in the progression of DKD. While numerous studies have elucidated the complex relationship between mitophagy and ferroptosis, there is a scarcity of literature addressing the relationship between these two processes in the context of tubular damage in DKD. We reviewed recent literatures exploring the associations among mitophagy, ferroptosis, and renal tubular injury in DKD, and tried to summarize the complex crosstalk between ferroptosis and autophagy in DKD. We hope to offer some new ideas for the treatment of DKD. Full article

Conventional propagation of yam (Dioscorea spp.) is constrained by low multiplication rates, pathogen accumulation, and vulnerability of field-maintained germplasm to biotic and abiotic losses. However, most studies emphasize survival, whereas fewer evaluate accession-specific growth performance alongside water-extractable phenolic content and antioxidant responses under the same conservation conditions. This study integrated morphological, biochemical, and post-conservation regrowth assessments to evaluate eight Ghanaian yam accessions maintained for 24 weeks on hormone-free complete Murashige and Skoog medium. The experiment followed a completely randomized design with three biological replications. All accessions maintained 100% survival without contamination throughout conservation, although substantial accession-dependent differences occurred in vegetative performance. At week 24, UWR produced 5.5 shoots/plant, 14 leaves/plant, and reached 8.5 cm height, while NKURAKAU produced 4.5 shoots plant⁻¹ and reached 8.2 cm. In contrast, SO showed weaker growth, producing 2.8 shoots plant⁻¹, 6 leaves plant⁻¹, and 4.5 cm height. During four weeks of post-conservation recovery, NKURAKAU exhibited the strongest regrowth, producing 1.8 shoots plant⁻¹, 4.2 leaves plant⁻¹, and 5.0 cm high plantlets. Biochemical responses were also accession-specific. AMO exhibited the highest water-extractable TPC after 24 weeks of conservation (4.1 mg GAE/100 g dry weight), whereas UWR showed the lowest response (1.7 mg GAE/100 g dry weight). Conversely, SO and NKURAKAU exhibited comparatively strong DPPH radical-scavenging activity despite lower phenolic contents. No statistically detectable linear association between endpoint TPC and DPPH radical-scavenging activity was observed among the eight accessions (r = −0.24, p > 0.05). Exploratory hierarchical clustering of biochemical trait distinguished AMO as higher-TPC phenotype and SO/NKURAKAU as higher-DPPH phenotype. Overall, combining morphological traits, biochemical indicators, and post-conservation regrowth provides a more informative basis for accession-specific germplasm management than survival alone. NKURAKAU and UWR showed the most balanced performance, while AMO was notable for shoot multiplication and higher TPC. Full article

Previous studies of artificial intelligence (AI)-driven automation have mostly assessed entire occupations, providing limited evidence about differences among individual tasks. This study addresses this limitation by proposing an NLP-assisted task-level assessment framework for estimating the automation potential of journalistic work. Of the 30 task descriptions listed for the O*NET occupation “News Analysts, Reporters, and Journalists” (27-3023.00), 25 were retained following scope-based screening and grouped into ten composite tasks representing the focal news-production workflow. Each task was assessed across three dimensions—Verb Type, Social Dependence, and Skill Type—using NLP-assisted feature extraction and structured consensus-based evaluation. The resulting component scores were combined into a composite automation potential score ranging from 0 to 1. Editing visual content and filing stories obtained the highest estimated scores (0.97), followed by gathering background information and collecting media content (0.77). Arranging interviews (0.20), conducting interviews (0.23), and receiving assignments to develop story ideas (0.27) received the lowest estimated scores. The study contributes a transparent and interpretable proof-of-concept approach for operationalizing task-level automation potential across procedural, social, and skill-related dimensions. The resulting scores represent relative task-level estimates rather than observed rates or probabilities of workplace automation. With larger labeled task datasets, the three dimensions defined in this framework could provide a basis for supervised classification and subsequent predictive modeling of automation potential across broader task collections. Full article

Hawthorn (Crataegus spp.) is a wild fruit tree of considerable ecological, nutritional, and medicinal value, widely distributed throughout the Mediterranean region and other temperate areas. Its taxonomy is particularly complex due to high morphological variability and frequent synonymy, which complicates accurate species identification. In Algeria, Crataegus spp. are very common, exhibiting substantial variability, especially in the northern part of the country. Despite its broad distribution, information on the genetic diversity of Algerian hawthorn germplasm remains limited. Characterization of this diversity is essential to support the identification of valuable traits of interest and to provide suitable genetic resources for the effective valorization and conservation of the species. In this study, 205 samples of Algerian wild hawthorn were characterized through an integrated analysis based on morphological descriptors and SSR markers, separating the samples into two well-defined genetic groups corresponding to C. azarolus (CA) and C. monogyna (CM) species. High levels of allelic richness, heterozygosity, and private alleles revealed substantial genetic diversity within both species. Overall, the integration of morphological and molecular data will provide a valuable basis for the conservation and management of Algerian hawthorn genetic resources. Full article

Biological invasions driven by climate change and human activities pose a serious threat to biodiversity and ecosystem stability in global biodiversity hotspot regions. Lantana camara is a globally recognized aggressive invasive plant that has rapidly spread in southwest China and caused significant ecological risks. To clarify its potential geographic distribution, key driving factors, and future invasion dynamics under climate change, this study applied an MaxEnt model with feature-class optimization, integrating occurrence points, bioclimatic variables, topographic data, and the human footprint index to simulate habitat suitability in southwest China for the current period (1970–2000) and the future (2050s and 2070s) under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results show that the current high-suitability area for L. camara is 1.21 × 10⁴ km², mainly distributed in central Yunnan and the Chengdu Plain. Human activity (human footprint index, 52.3%) is the dominant driver, and the mean temperature of the coldest month (28.5%) is the primary natural limiting factor. Future suitable areas exhibit a remarkable scenario-dependent nonlinear response. By the 2070s, the high-suitability area expands most sharply under SSP2-4.5 (3.27 × 10⁴ km², an increase of about 170%), revealing that moderate warming facilitates northward expansion. Under SSP5-8.5, the high-suitability area contracts compared with the 2050s, indicating that extreme high temperatures restrain optimal habitats. Spatially, L. camara displays a “retreat south, advance north” pattern under high-emission scenarios, with its distribution centroid continuously shifting northeast, reflecting climate-driven niche changes. This study verifies that the invasion risk of L. camara does not rise linearly with climate warming. Moderate warming boosts its spread, whereas extreme warming reshapes its distribution, offering a scientific basis for risk assessment, early warning, and targeted control strategies against L. camara invasion in southwest China and worldwide. Full article

Identifying oocytes with high meiotic competence remains a major challenge for improving in vitro embryo production in South American camelids. Although Brilliant Cresyl Blue (BCB) staining has been used to distinguish alpaca oocytes with different meiotic and developmental competence, the biological and molecular feature associated with their meiotic competence remain poorly understood. This study characterized the transcriptomic profiles of immature alpaca (Vicugna pacos) oocytes classified as BCB-positive (BCB+) or BCB-negative (BCB−) using single-cell RNA sequencing. BCB+ oocytes exhibited a significantly larger ooplasm diameter, a higher proportion of condensed chromatin configurations, and higher in vitro maturation rates than BCB− oocytes. Transcriptomic analysis identified 2978 differentially expressed genes and revealed a clear separation between groups (PC1 = 64.8%). Differentially expressed genes with higher transcript abundance in BCB+ oocytes were enriched in DNA metabolism, cell cycle, oocyte meiosis, and proteasome pathways, whereas those with higher transcript abundance in BCB− oocytes were enriched in gene expression regulation, RNA metabolism, chromatin remodeling, and intracellular signaling. Protein–protein interaction (PPI) network analysis identified distinct hub genes in each group, including CDK1, CCNB2, MAD2L1, and AURKB in BCB+ oocytes and EP300, CREBBP, SMARCA4, and ARID1A in BCB− oocytes. These results provide the first single-cell transcriptomic characterization of BCB-classified alpaca oocytes and establish the molecular basis underlying the biological differences identified by BCB staining. Full article