Search Results (63,948)

Existing macroscopic finite element models for electron beam welding (EBW) typically assume isotropic material behavior, often failing to accurately predict residual stresses induced by strong crystallographic textures. To address this limitation, this study established a sequential dual-scale coupled numerical model bridging micro-texture to macro-mechanics by combining the crystal plasticity finite element method (CPFEM) with thermal-elastic-plastic theory. Representative volume elements (RVEs) incorporating α and β dual-phase characteristics were constructed based on electron backscatter diffraction (EBSD) data from the TA15 weld cross-section. Through simulated tensile and shear calculations on the RVEs, homogenized orthotropic stiffness matrices and Hill yield constitutive parameters were derived and mapped onto the macroscopic model. Simulation results indicate that the proposed model maintains the prediction error for molten pool morphology within 16.3%, while effectively correcting the stress overestimation inherent in isotropic models. Specifically, it adjusts the peak longitudinal residual stress at the weld center from 800 MPa to approximately 350 MPa, significantly reducing the anomalous “M-shaped” stress distribution. By successfully capturing shear stress components, this work provides a high-fidelity computational approach for predicting complex stress states in welded joints, offering critical insights for structural integrity assessment. Full article

Industrial heritage embodies the complex interplay between historical continuity, technological development, and social spatial transformation. However, existing assessment methods often rely on qualitative judgments or fragmented criteria, limiting their ability to systematically evaluate the reuse potential in the context of heterogeneous heritage. To overcome this limitation, this study constructs an empirical evaluation framework that defines heritage value through quantifiable indicators and examines how different value dimensions affect reuse potential. Based on a dataset of 124 industrial heritage sites located on saline–alkali soil along the coast of Jiangsu Province, this study integrates multiple data sources such as archival records, field surveys, spatial data, and questionnaire surveys to construct a multidimensional indicator system. This system quantifies and analyzes four value dimensions: historical, architectural, technological, and socio-cultural, and employs machine learning methods for analysis. The study utilizes a Random Forest model to examine the relative impact of each dimension and assess their comprehensive explanatory power in classifying the potential for heritage reuse. The performance of the model is evaluated through cross-validation, yielding robust results (accuracy = 0.833, macro F1 = 0.812). A five-fold cross-validation is conducted to train a Random Forest classifier. The model achieves an accuracy of 0.833, a macro F1 score of 0.812, and an AUC of 0.871, outperforming the baseline classifier and validating the reliability of the analytical framework. The research findings indicate that the impact of architectural integrity and technical characteristics on reuse potential significantly outweighs symbolic or perceptual attributes, unveiling structural biases present in traditional heritage assessment practices. This study transcends descriptive assessments by empirically examining the operational modes of different value dimensions within a unified analytical framework, offering empirical insights into the mechanisms influencing the reuse of industrial heritage. The proposed framework provides a reproducible and transparent approach to support heritage conservation and adaptive reuse strategies in industrial transformation areas. Full article

This paper proposes a Bayesian estimation method for spatial lagged panel quantile models. The proposed model simultaneously considers spatial lag effects of the dependent variable and the quantile regression framework, enabling effective capture of spatial dependence and conditional distribution heterogeneity. The research constructs a Bayesian estimation framework based on the asymmetric Laplace distribution by decomposing the random disturbance term into a combination of normal and exponential distributions, successfully developing a probabilistic model with both thick tail robustness and computational efficiency. On this basis, the study derives the full conditional posterior probability distributions of model parameters and designs a hybrid Markov Chain Monte Carlo (MCMC) sampling algorithm integrating Gibbs sampling and Metropolis–Hastings algorithm for parameter estimation. Numerical simulation experiments demonstrate that, compared with traditional estimation methods, the proposed Bayesian estimation approach exhibits superior estimation accuracy and robustness across different quantiles, with particularly pronounced advantages in small sample and heavy-tailed distribution scenarios. This methodology provides a more reliable theoretical tool for analyzing panel data with spatial dependencies. This method can not only accurately quantify the spatial spillover effect, but also identify the different effects of the same influencing factor at different emission levels, which provides a strong methodological support for formulating differentiated and precise emission reduction policies. Full article

Social networks are now integral to corporate strategy and daily social life. They enable the rapid and extensive dissemination of information, proving highly effective for promoting hotel marketing content. Consequently, they facilitate interaction and engagement between hotels and their customers, serving both advertising and evaluation purposes. This study aims to analyse the use of the Facebook social network by luxury wine hotels located in countries associated with the Mediterranean Diet. An analytical model examining the variables of content, interactivity, and visibility was employed. A total of 17 luxury hotel pages were analysed, with data collected using the Karma Fanpage platform, an online tool for social media analysis and monitoring. The findings indicate that the majority of profile posts were photographs, and that this format generated the highest number of user reactions. It is recommended that hotels publish more photographic content to foster greater engagement and conduct further analysis of the specific types of posts that elicit the most reactions. Full article

Producing high-quality analytical reports for the environmental domain is typically time-consuming and requires significant human expertise. This paper describes MeteoChat, a semi-automatic framework for efficiently generating specialized environmental reports from heterogeneous environmental data. MeteoChat utilizes a Large Language Model (LLM) fine-tuned and integrated with Retrieval-Augmented Generation (RAG). The system’s core is its plug-and-play philosophy, which separates analytical reasoning from the data source and the report’s intended audience. The fine-tuning phase uses data-agnostic, parameterized question–context–answer triples defined by an environmental expert to teach the LLM domain-specific analytical logic and audience-appropriate communication styles. Subsequently, the RAG phase integrates the model with actual datasets, which are processed via an Extract–Transform–Load (ETL) workflow to generate statistical summaries. This architectural separation ensures that the same reporting engine can operate on different sources, such as meteorological time series, satellite imagery, or geographical data, without additional training. Users interact with the system via a web-based conversational interface, where responses are tailored for either technical experts (using explicit calculations and tables) or the general public (using simplified, narrative language). MeteoChat has been tested with real data extracted from the micrometeorological network of ARPA Lazio. Full article

Background: The valorization of sustainable feed ingredients such fermented de-oiled rice bran meal (FDRBM) is crucial; however, the molecular mechanisms driving its benefits remain unclear. This study addresses this gap by investigating FDRBM as a dietary substitute for maize in rabbits to determine its effects on meat quality and underlying gut–liver axis communication. Methods: In an eight-week trial, New Zealand White rabbits were assigned to a control diet or the basal diet with a 20% substitution of either unfermented de-oiled rice bran (UFDRBM) or FDRBM. Post-trial, the researchers analyzed carcass traits, meat quality, and nutritional composition. A multi-omics approach integrates gene expression data from the ileum and muscle with liver metabolomics to model coordinated biological responses. Results: Although growth performance was similar, the FDRBM diet significantly improved meat quality by enhancing water-holding capacity and increasing essential amino acids (p < 0.05). Mechanistically, these improvements were associated with the upregulation of genes associated with oxidative muscle fiber (Tnnc1) and lipid metabolism. Analysis of the gut–liver axis revealed that FDRBM enhanced ileum antioxidant capacity, which coincided with profound reprogramming of liver metabolism (p < 0.01 *), identifying C17-sphinganine as a differential metabolite. Conclusion: This study provides novel insights into the mode of action of FDRBM, suggesting that it enhances rabbit meat quality in part by modulating metabolic gene expression and is associated with coordinated molecular changes across the gut–liver axis. Full article

Cytoplasmic male sterility (CMS) provides a natural model for studying nuclear–cytoplasmic interactions, although the details of nuclear–cytoplasmic communication remain poorly understood. In this study, transcriptomic and metabolomic data were integrated to elucidate the molecular and metabolic regulatory networks underlying stamen developmental defects in the tobacco CMS K326 (Nicotiana tabacum). Disrupted energy metabolism, auxin pathways, and floral development gene expression were identified in CMS K326. Metabolites such as glucose-6-phosphate, fructose-6-phosphate, and oxalosuccinic acid decreased, while an accumulation of succinate was observed and auxin IAA was deficient. Our study revealed that disrupted nuclear–cytoplasmic interactions in CMS K326 are associated with concurrent disruptions in early auxin homeostasis and energy metabolism, which collectively lead to the disturbance of the stamen development program. This study provides multiomics-level evidence for understanding stamen identity defects in CMS. Full article

Efficient sorting of resin-based CFRP composites is critical for optimizing composite recycling streams. In this work, a methodology integrating Laser-Induced Breakdown Spectroscopy (LIBS) with Machine Learning (ML)-enhanced classification models to achieve accurate material discrimination is presented. LIBS is employed to identify the chemical composition of individual compounds, producing spectrograms that are subsequently processed to group chemically similar materials based on Epoxy resin (Bisphenol-A). The grouped datasets that contain 4000 peaks and 665 features were sampled to standardize feature dimensionality and cleaned to remove noise. A statistical analysis is then conducted to select the most informative features, followed by dimensionality reduction using Linear Discriminant Analysis (LDA). Finally, classification is performed using a Support Vector Classification (SVC) model, fine-tuned to the processed data to maximize accuracy. With a 5-fold cross validation (CV), the average nested accuracy score is 0.8317 ± 0.0212. This integrated approach demonstrates the potential for advancing automated sorting technologies in composite recycling applications. Full article

We develop a PDE and boundary integral framework for quaternion-valued fields on product domains $\Omega \subset \mathbb{H}\times \mathbb{H}$ governed by the mixed left/right Cauchy–Fueter system We identify the natural compatibility condition and prove local solvability with quantitative $H^1$ estimates, as well as global weak solvability on admissible products $U_x\times U_y$. Motivated by these estimates, we introduce domains of hyperholomorphy and hyper-conjugates for data that are harmonic in each factor (${\Delta }_{x}u={\Delta }_{y}u=0$), and we establish Carleman-type quantitative unique continuation tools (boundary blow-up, three-balls, and doubling), including a propagation-of-smallness principle across the two factors. On the potential-theoretic side, we construct a double boundary integral representation for biregular fields with kernel $K(\xi ,\eta ;x,y)=E(\xi -x)E(y-\eta )$, establish mapping and jump relations for the associated layer potentials on Lipschitz boundaries, and obtain a Fredholm boundary integral equation for the boundary density in the smooth admissible regime. Finally, we prove a constructive Runge approximation theorem on admissible products and outline a practical discretization workflow consistent with the analysis. Full article

Anterior cruciate ligament (ACL) reconstruction is a common orthopedic procedure, but graft failure remains a significant complication, particularly in young and active individuals. Understanding the multifactorial etiology of failure and optimizing revision strategies are crucial for improving outcomes. A structured narrative review of the literature was conducted, including studies published from January 2000 to May 2024. Databases searched included PubMed/MEDLINE, Embase, and Google Scholar. Eligible studies addressed definitions, etiology, classification, and surgical management of ACL reconstruction failure. Data were synthesized qualitatively, integrating evidence on technical, biological, and traumatic causes, as well as neuromuscular and psychosocial factors influencing functional outcomes. ACL reconstruction failure is primarily caused by technical errors, particularly tunnel malposition (60–70% of cases), followed by traumatic (15–25%) and biological (10–15%) mechanisms. Failure timing provides diagnostic clues: early (<3 months) failures often relate to fixation or infection, mid-term (3–12 months) to technical errors, and late (>12 months) to trauma or degeneration. Revision strategies include individualized graft selection, anatomical tunnel placement, repair of associated lesions, and consideration of biomechanical abnormalities. Overall success rates of revision procedures average 70–75%, with lower outcomes in adolescents and high-demand athletes. Emerging techniques, including lateral extra-articular tenodesis and biologic augmentation, may enhance revision outcomes, although long-term evidence remains limited. ACL reconstruction failure is a multifactorial event requiring thorough preoperative assessment, precise surgical planning, and individualized management. Addressing technical, biological, and neuromuscular factors, alongside patient-specific considerations, is essential to optimize functional outcomes and reduce failure rates. Future research should focus on standardized reporting, multicenter prospective studies, and advanced surgical planning tools to further improve revision success. Full article

This study analyzed the hydroclimatic functioning of the Lake Fitri basin (Chad) by combining rainfall records, in situ hydrological observations, water balance analysis, and spatial remote sensing data. Results show a strong Sahelian climatic control, with rainfall concentrated in a short-wet season (July–September) and potential evapotranspiration largely exceeding precipitation. Batha River flows are highly seasonal, generating short flood pulses that drive lake level fluctuations and aquifer recharge. Water balance estimates indicate that recharge is limited and episodic (approximately 70–120 mm in 2020), representing only 14–24% of annual rainfall, occurring almost exclusively during extreme rainfall events. Compared with Lake Chad, Lake Fitri is more directly sensitive to local rainfall variability, reflecting its dependence on a single tributary. Overall, the findings underline the fragility of this hydrosystem and the need for reinforced monitoring and integrated management to ensure sustainable water resources under increasing climatic variability. This work constitutes the initial reference for the hydroclimatic characterization of Lake Fitri, thanks to a methodology combining in situ and satellite data. Full article

In response to growing energy demands and climate pressure in hot regions, this study presents an integrated techno-economic and environmental assessment of building envelope retrofit strategies aimed at facilitating the transition of existing buildings toward Nearly Zero-Energy Building (NZEB) targets. Three advanced retrofit solutions—radiative coatings (RC), glazing-integrated photovoltaic (GIPV) systems, and solar green roofs—are evaluated using a validated building performance simulation framework across four representative climatic zones in Egypt. The results demonstrate that radiative coatings provide the most favorable economic performance, achieving return on investment (ROI) values between 12.37% and 21.72% and payback periods ranging from 3.5 to 6.2 years. Solar green roofs and GIPV systems deliver substantial reductions in annual electricity consumption and operational CO₂ emissions, with their performance strongly influenced by climatic conditions and cooling demand intensity. Solar green roofs achieve ROI values of 5.15–6.54% with payback periods of 11.7–14.9 years, while GIPV systems yield ROI values of 4.0–5.24% and payback periods between 14.6 and 17.1 years. Overall, the findings indicate that climate-adapted envelope retrofit strategies can significantly enhance building energy performance while providing measurable economic and environmental benefits. This study offers a robust, data-driven basis for retrofit prioritization and policy formulation in hot regions. Full article

Spaceborne infrared ship detection holds critical strategic significance in both military and civilian domains. As a crucial data source for ship detection, infrared remote sensing imagery offers the advantages of all-weather detection and strong anti-interference capability. However, existing methods often overlook the detailed features of small ships and fail to effectively suppress interference, leading to missed detections and false alarms in complex backgrounds. To tackle this issue, this study proposes a hierarchical frequency- and spatial-feature attention network (HFS-Net) for fast and accurate ship detection in spaceborne infrared images. The main motivation is to aggregate frequency-spatial information for improved feature extraction, while devising novel hybrid attention-based structures to facilitate interaction among semantic information. Specifically, we design an adaptive frequency-spatial feature attention (AFSA) module to enrich the feature representation. In particular, AFSA integrates information from spatial and frequency domains and introduces channel attention to adaptively extract important features and edge details of ship targets. In addition, we propose an attention-based component-wise feature interaction (ACFI) module that combines multi-head self-attention to capture long-range feature dependencies and component-wise feature aggregation to further enhance the interaction of high-level semantic information. Extensive experiments demonstrate that HFS-Net achieves higher detection accuracy than several representative detectors in maritime infrared scenes with small ships and complex backgrounds, while maintaining real-time efficiency and moderate computational complexity. Full article

Twin wildfires burned over 9500 ha in Seferihisar, İzmir, western Türkiye, on 29—30 June 2025 under extreme fire weather conditions. This study reconstructs the spatiotemporal progression of the fires and examines the drivers of contrasting behaviors and burn severity. Multi-source datasets—Sentinel-2 imagery, VIIRS/MODIS thermal detections, MTG images and thermal detections, aerial photos, and ground data—were integrated to delineate progression polygons and compute rate of spread (ROS), fuel consumption (FC), and fire-line intensity (FI). Kuyucak fire showed rapid early growth, burning 3554 ha in 2.5 h (mean ROS of 5.0 km h⁻¹; mean FI of 37,789 kW m⁻¹), driven by strong northeasterly winds of 40–50 km h⁻¹, steep terrain, dense Pinus brutia fuels, and very low dead fine-fuel moisture (<6%). Kavakdere fire advanced more slowly (mean ROS of 1.6 km h⁻¹) across open grassland and cropland, yielding lower FC and FI. Synoptic analysis revealed a strong pressure-gradient-induced northeasterly wind regime linked to a mid-tropospheric geopotential height dipole between Central Europe and the Eastern Mediterranean, while WRF simulations indicated a dry boundary layer and enhanced low-level winds during peak spread. Sentinel-2 dNBR burn severity mapping showed substantial spatial variability tied to fuel and topography contrasts. Findings demonstrate how twin ignitions under similar weather conditions can produce divergent outcomes, underscoring the need for terrain- and fuel-aware strategies during extreme Mediterranean fire outbreaks. Full article

Familial partial lipodystrophy type 3 (FPLD3) is a rare autosomal dominant disorder caused by mutations in peroxisome proliferator-activated receptor gamma(PPARG), which encodes the key adipogenic transcription factor peroxisome proliferator-activated receptor gamma(PPARγ). Clinical diagnosis is challenging due to phenotypic overlap with common metabolic syndromes. We identified a novel PPARG variant in a Chinese family and performed comprehensive functional characterization to elucidate its pathogenic mechanism. The proband, a 15-year-old boy presenting with atypical fat distribution, severe insulin resistance, hypertriglyceridemia, and pancreatitis, underwent clinical evaluation and whole-exome sequencing. The identified variant was confirmed by Sanger sequencing. Its functional impact was assessed through in silico modeling, luciferase reporter assays, protein stability analysis (cycloheximide chase), and evaluation of mitochondrial function (JC-1 staining) and adipocyte gene expression in cellular models. A heterozygous PPARG c.634C>T (p.Arg212Trp, R212W) variant was identified and segregated with the phenotype. Functional studies revealed that the R212W mutant exhibits a partial loss of transcriptional activity (~40% of wild-type) while retaining ligand sensitivity. Crucially, we demonstrated that the mutant protein has significantly reduced stability due to accelerated degradation. In adipocyte models, R212W expression led to impaired mitochondrial membrane potential, depleted cellular ATP levels, and downregulated expression of key metabolic genes (glucose transporter 4[GLUT4], adiponectin[ADIPOQ], fatty acid binding protein 4[FABP4], lipoprotein lipase[LPL], perilipin 1[PLIN1]). These functional deficits were partially rescued by treatment with the PPARγ agonist rosiglitazone. We report a novel pathogenic PPARG R212W variant associated with FPLD3. Our data extend beyond a simple loss-of-function model by establishing a multi-faceted pathogenic mechanism involving protein destabilization, mitochondrial dysfunction, and cellular bioenergetic failure. The partial rescue by rosiglitazone suggests a potential therapeutic avenue. This study underscores the importance of integrating clinical phenotyping with deep functional analysis to diagnose and understand rare monogenic lipodystrophies. Full article