Search Results (3,769)

This study examines the joining characteristics of Cu foil stacks to lead tabs using green-laser welding in the main-welding step of a sequential welding process for lithium-ion pouch cells. The influence of lap configuration, line and wobble seam strategies, and process parameters was systematically investigated in terms of bead morphology, mechanical performance, metallurgical characteristics, and electrical resistance. Under the present line-welding parameter window (2.0 kW, 100–200 mm/s), humping, pinholes, and porosity were observed, particularly in the upper lead-tab configuration, which is attributed to melt-pool/keyhole instability under the applied conditions. Wobble welding effectively suppressed these defects in the foil-stack configuration by promoting stable melt flow and efficient bubble expulsion. Mechanical tests revealed that the wobble-based seam strategy achieved a maximum tensile–shear load of approximately 1.28 kN at a wobble amplitude of 0.8 mm. Fracture analysis confirmed a transition from seam-type interfacial failure in line welding to ductile tearing in the heat-affected zone with wobble welding. In electrical performance, wobble welding reduced resistance to as low as 45 µΩ at a wobble amplitude of 1.2 mm, while line welding yielded higher and scattered values. These results should be interpreted as the combined outcome of the wobble-based seam strategy (beam oscillation together with overlapped stitch welding at a lower travel speed) under the present processing windows. A strictly matched A/B comparison at identical linear energy density and seam layout will be investigated in future work to isolate the effect of oscillation. Full article

This study investigated the influence of drying techniques such as convection hot-air drying, vacuum drying, and freeze drying with slow and flash pre-freezing on the total phenolic content and the profile of dominant phenolic compounds in cultivated blueberry (Vaccinium corymbosum L.). Although fresh blueberries exhibited higher total phenolic content (1350.85 mg GAE/100 g), total flavonol glycosides (66.20 mg/100 g), and total anthocyanins (218.23 mg/100 g) compared with dried samples, freeze-dried samples, particularly those subjected to flash pre-freezing, retained higher contents of these components in the dried material compared to other drying techniques. This could be attributed to the microstructural preservation of plant tissue during freeze drying. Furthermore, the study demonstrated that subsequent milling of freeze-dried samples, whether using a knife mill or a ball mill, also affects the availability of bioactive compounds in freeze-dried blueberry powders. The combination of flash pre-freezing followed by ball milling yielded the highest availability of bioactive components in the processed blueberry powder. Full article

Anaerobic digestion (AD) of ensiled orange peel waste (OPW) offers a promising pathway for the valorisation of citrus-processing residues and the generation of renewable energy. This study evaluated the impact of two carbon-based materials, biochar and granular activated carbon (GAC), on methane yield and process stability using Biochemical Methane Potential (BMP) tests. The experimental setup consisted of two consecutive cycles, the second of which was designed to examine microbial acclimation by reusing both the digestate (as the inoculum) and the previously added carbon materials. Ensiled OPW exhibited a methane yield of 578 ± 59 mL_CH4/g_VS during the initial cycle, confirming its high biodegradability. The addition of biochar and GAC resulted in comparable yields (approximately 520–560 mL_CH4/g_VS) and did not enhance the ultimate methane potential; however, both additives proved fully compatible with the process. In the subsequent cycle, a marked increase in methane production was observed, with OPW reaching approximately 730 mL_CH4/g_VS, primarily attributed to improved microbial adaptation. Kinetic analysis revealed moderate enhancements in degradation rates, which were more pronounced when higher biochar dosages were used. Overall, ensiled OPW emerges as a highly suitable substrate for AD. At the same time, biochar and GAC did not adversely affect the AD process under the tested conditions; however, their potential benefits have yet to be fully demonstrated and warrant further investigation, particularly under continuous reactor operating conditions. Full article

The classification of ship targets in remote sensing images holds significant application value in fields such as marine monitoring and national defence. Although existing research has yielded considerable achievements in ship classification, current methods struggle to distinguish highly similar ship categories for fine-grained classification tasks due to a lack of targeted design. Specifically, they exhibit the following shortcomings: limited ability to extract locally discriminative features; inadequate fusion of features at high and low levels of representation granularity; and sensitivity of model performance to background noise. To address this issue, this paper proposes a fine-grained classification framework for ship targets in remote sensing images based on Multi-Granularity Attention Network (MA-Net), specifically designed to tackle the aforementioned three major challenges encountered in fine-grained classification tasks for ship targets in remote sensing. This framework first performs multi-level feature extraction through a backbone network, subsequently introducing an Adaptive Local Feature Attention (ALFA) module. This module employs dynamic overlapping region segmentation techniques to assist the network in learning spatial structural combinations, thereby optimising the representation of local features. Secondly, a Dynamic Multi-Granularity Feature Fusion (DMGFF) module is designed to dynamically fuse feature maps of varying representational granularities and select key attribute features. Finally, a Feature-Based Data Augmentation (FBDA) method is developed to effectively highlight target detail features, thereby enhancing feature expression capabilities. On the public FGSC-23 and FGSCR-42 datasets, MA-Net attains top-performing accuracies of 93.12% and 98.40%, surpassing the previous best methods and establishing a new state of the art for fine-grained classification of ship targets in remote sensing images. Full article

Targeting the thinly bedded and strongly heterogeneous tight sandstone gas reservoirs of the Shaximiao Formation in the Yingshan area of the Sichuan Basin, this study establishes an integrated workflow that combines high-fidelity 3D seismic processing with quantitative interpretation to address key challenges such as insufficient resolution of conventional seismic data under complex near-surface conditions and difficulty in depicting sand-body geometries. On the processing side, a 2D-3D integrated amplitude-preserving high-resolution strategy is applied. In contrast to conventional workflows that treat 2D and 3D datasets independently and often sacrifice true-amplitude characteristics during static correction and noise suppression, the proposed approach unifies first-break picking and static-correction parameters across 2D and 3D data while preserving relative amplitude fidelity. Techniques such as true-surface velocity modeling, coherent-noise suppression, and wavelet compression are introduced. As a result, the effective frequency bandwidth of the newly processed data is broadened by approximately 10–16 Hz relative to the legacy dataset, and the imaging of small faults and narrow river-channel boundaries is significantly enhanced. On the interpretation side, ten sublayers within the first member of the Shaximiao Formation are correlated with high precision, yielding the identification of 41 fourth-order local structural units and 122 stratigraphic traps. Through seismic forward modeling and attribute optimization, a set of sensitive attributes suitable for thin-sandstone detection is established. These attributes enable fine-scale characterization of sand-body distributions within the shallow-water delta system, where fluvial control is pronounced, leading to the identification of 364 multi-phase superimposed channels. Based on attribute fusion, rock-physics-constrained inversion, and integrated hydrocarbon-indicator analysis, 147 favorable “sweet spots” are predicted, and six well locations are proposed. The study builds a reservoir-forming model of “deep hydrocarbon generation–upward migration, fault-controlled charging, structural trapping, and microfacies-controlled enrichment,” achieving high-fidelity imaging and quantitative prediction of tight sandstone reservoirs in the Shaximiao Formation. The results provide robust technical support for favorable-zone evaluation and subsequent exploration deployment in the Yingshan area. Full article

Granite residual soil (GRS) is highly susceptible to water-induced softening, posing significant risks of slope instability and collapse. Conventional impermeable grouting often exacerbates these hazards by blocking groundwater drainage. This study investigates the efficacy of a permeable water-reactive polyurethane (PWPU) in stabilizing GRS, aiming to resolve the conflict between mechanical reinforcement and hydraulic conductivity. Uniaxial compression tests were conducted on specimens with varying initial water contents (5%, 10%, and 15%) and PWPU contents (5%, 10%, and 15%). To reveal the multi-scale failure mechanism, synchronous acoustic emission (AE) monitoring and digital image correlation (DIC) were employed, complemented by scanning electron microscopy (SEM) for microstructural characterization. Results indicate that PWPU treatment significantly enhances soil ductility, shifting the failure mode from brittle fracturing to strain-hardening, particularly at higher moisture levels where failure strains exceeded 30%. This enhancement is attributed to the formation of a flexible polymer network that acts as a micro-reinforcement system to restrict particle sliding and dissipate strain energy. An optimal PWPU content of 10% yielded a maximum compressive strength of 4.5 MPa, while failure strain increased linearly with polymer dosage. SEM analysis confirmed the formation of a porous, reticulated polymer network that effectively bonds soil particles while preserving permeability. The synchronous monitoring quantitatively bridged the gap between internal micro-crack evolution and macroscopic strain localization, with AE analysis revealing that tensile cracking accounted for 79.17% to 96.35% of the total failure events. Full article

The microevolutionary pathways and molecular mechanisms by which the important pathogen Vibrio parahaemolyticus acquires resistance in the aquatic environment under continuous selective pressure from quinolone antibiotic residues are still unknown. Here, the study successfully simulated the long-term pressure of antibiotic residues in aquaculture by susceptible V. parahaemolyticus (VPD14) which was isolated from seafood, to a 30-day in vitro induction with sublethal concentrations of levofloxacin, which yielded the mutants (VPD14M). A phenotypic analysis revealed that VPD14M exhibited resistance to ampicillin, levofloxacin and ciprofloxacin, compared to VPD14. These changes were accompanied by adaptations, including a decreased growth rate and an enhanced biofilm formation capacity. Whole-Genome Sequencing identified that the acquired resistance was primarily attributable to key point mutations in three Quinolone Resistance-Determining Regions (QRDRs). Specifically, a G → T substitution at nucleotide position 248 in the gyrA gene, leading to a serine-to-isoleucine substitution at the 83rd amino acid position (Ser83Ile) of the DNA gyrase subunit A; a C → T substitution at position 254 in the parC gene, resulting in a serine-to-phenylalanine substitution at position 85 (Ser85Phe) of the topoisomerase IV subunit A; and a C → T substitution at position 2242 in the gyrB gene, causing a proline-to-serine substitution at position 748 (Pro748Ser) of the DNA gyrase subunit B. Collectively, the study demonstrated that sublethal antibiotic levels rapidly drive quinolone resistance in V. parahaemolyticus, and the specific mutations identified offer critical support for resistance monitoring and seafood safety alerts. Full article

Accurate precipitation mapping is essential for effective disaster management; however, individual radar, satellite, and numerical weather prediction products often struggle in the topographically complex terrain of South Korea. This study proposes a high-resolution (~500 m) daily precipitation fusion framework that integrates Korea Meteorological Administration (KMA) radar, Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), and Local Data Assimilation and Prediction System (LDAPS) data. The framework employs a Random Forest model augmented with a monthly Empirical Cumulative Distribution Function (ECDF) correction. Auxiliary predictors are incorporated to enhance physical interpretability and stability, including terrain attributes to represent orographic effects, land-cover information to account for surface-related modulation of precipitation, and seasonal cyclic signals to capture regime-dependent variability. These predictors complement dynamic precipitation inputs and enable the model to effectively capture nonlinear spatiotemporal patterns, resulting in improved performance relative to individual radar, IMERG, and LDAPS products. Evaluation against Automated Synoptic Observing System (ASOS) observations yielded a correlation coefficient of 0.935 and a mean absolute error of 3.304 mm day⁻¹ in a Leave-One-Year-Out (LOYO) validation for 2024. Regional analyses further indicate substantial performance gains in complex mountainous areas, including the Yeongdong–Yeongseo region, where the proposed framework markedly reduces estimation errors under challenging winter conditions. Overall, the results demonstrate the potential of the proposed fusion framework to provide robust, high-resolution precipitation estimates in regions characterized by strong topographic and seasonal heterogeneity, supporting applications related to hazard analysis and hydrometeorological assessment. Full article

Ecolabelling has emerged as a key instrument to communicate environmental performance to consumers, particularly in the agri-food sector where resource use and ecological pressures are highly interlinked. Conventional Life Cycle Assessment (LCA)-based ecolabels often suffer from methodological discretion, lack of territorial specificity, and limited consumer trust. This study investigates how the Water–Energy–Food–Ecosystem (WEFE) Nexus could be integrated into LCA-based ecolabelling, with a specific focus on pasta production as a representative case in the food industry. Indicators were collected from recent literature on LCA and Nexus applications, selected for simplicity and clear attribution to one WEFE dimension, and then evaluated by experts from COST Action CA20138 (NexusNet) through a two round Delphi protocol. The process yielded 23 indicators distributed across the four dimensions, which were subsequently compared with six Environmental Product Declarations to assess data availability and compatibility. The results suggest that many indicators can be computed with standard LCA inventories, while the Nexus perspective adds value by capturing multidimensional impacts and regional resource pressures. Further refinement and empirical testing are expected to enhance the framework’s applicability, but the findings already indicate that incorporating WEFE-based indicators into pasta ecolabelling could represent a promising pathway to improve analytical depth and consumer relevance, aligning circular economy principles with corporate assessment practices. Full article

Table grapes are among the main fruit crops cultivated in Brazil, supported by cultivar diversity, technological advances, and adaptation to diverse edaphoclimatic conditions. Rootstock selection is critical in viticulture, influencing phenology, yield, and fruit quality. This study evaluated yield- and fruit-related production parameters, cluster characteristics, and biochemical composition of ‘BRS Núbia’ table grape grafted onto different rootstocks. The experiment was conducted at the Experimental Farm of the Faculty of Agricultural Sciences (UNESP), São Manuel, São Paulo, Brazil, using a randomized block design in a split-plot scheme (three rootstocks × three seasons) with seven replicates. Rootstocks included ‘IAC 572 Jales’, ‘IAC 766 Campinas’, and ‘Paulsen 1103’, while subplots corresponded to the first three production seasons after grafting. Evaluated variables comprised bud fruitfulness, yield, productivity, physical attributes of clusters, berries, and rachises, and in 2022, berry biochemical traits, including total phenolics, flavonoids, anthocyanins, and antioxidant activity. Rootstocks did not significantly affect bud fruitfulness or yield-related parameters. In contrast, production season markedly influenced vine performance, with the third (2023) season showing higher cluster and berry mass and size. Regarding fruit composition, vines grafted onto ‘Paulsen 1103’ and ‘IAC 766 Campinas’ showed greater accumulation of total phenolics and anthocyanins than those grafted onto ‘IAC 572 Jales’, overall. Full article

The study examines the mechanical strength of sulfur–biochar composites (SBCs), an underexplored area with potential for developing robust materials. Sulfur production, primarily from specialized extraction and waste generation in petroleum refining, yields about 70 million tons annually, necessitating efficient waste management. SBCs were produced using waste-derived biochar and elemental sulfur at varying sulfur contents (60–80%) and employing two fabrication methods: a muffle furnace and an electric burner. The mechanical performance of the composites was evaluated through strength and displacement measurements, with particular emphasis on the influence of processing method and sulfur content. The results demonstrate that both sulfur content and fabrication method significantly affect the mechanical behavior of SBCs. An increase in sulfur content led to a systematic improvement in ultimate strength for all samples. However, composites produced using the electric burner exhibited markedly higher ultimate forces and lower displacements compared to those fabricated in the muffle furnace, indicating superior strength and reduced brittleness. The enhanced performance is attributed to improved sulfur distribution and more effective infiltration of liquid sulfur into the porous biochar structure. These findings confirm the synergistic effect of combining sulfur with biochar and highlight the critical role of processing conditions in developing mechanically robust sulfur–biochar composites suitable for sustainable material applications. Full article

The Tibetan Plateau (TP) has experienced pronounced climate change over recent decades, yet the coupled interactions and trade-offs between vegetation dynamics and water yield (WY) remain insufficiently quantified. In this study, we employed the Lund–Potsdam–Jena (LPJ) model to simulate the spatiotemporal evolution of net primary productivity (NPP) and WY across the TP from 1981 to 2060, and applied the Geodetector method to identify the dominant drivers of vegetation dynamics. The results showed that: (1) during 1981–2020, both NPP and WY generally increased across the TP but exhibited distinct spatial patterns, with NPP showing more widespread and pronounced increases than WY; (2) sensitivity experiments revealed that a 2 °C warming substantially increased NPP (+48.79%) but suppressed WY (−17.96%), whereas a 25% increase in precipitation resulted in only a modest rise in NPP (+5.72%) but a sharp increase in WY (+46.72%); (3) the driving factor analysis showed that precipitation, temperature, and WY were the primary controls on NPP, while interaction analysis revealed that their combined effects explained NPP variability more effectively than individual factors; (4) under the Shared Socioeconomic Pathways (SSPs), vegetation–water interactions were projected to shift, with continued greening intensifying water depletion in arid regions, while humid regions were more capable of meeting increased water demand. These findings enhance understanding of vegetation–water coupling across the TP and provide a scientific basis for evaluating future ecohydrological risks under climate change. Full article

Surface roughness is a quality-critical attribute in industrial zinc phosphating, directly affecting sealing performance, coating uniformity, dimensional tolerances, and first-pass production yield in automotive pretreatment lines. While the chemical mechanisms of phosphate coating formation are well understood, the translation of this knowledge into statistically defensible, production-scale prioritization of bath chemistry control levers under real manufacturing constraints remains limited, particularly with respect to surface roughness stability and its environmental implications. This study investigates surface roughness control in a fully operational industrial zinc phosphating line by systematically evaluating the effects of pickling acid chemistry (H₂SO₄ versus H₃PO₄), dissolved ferrous iron (Fe²⁺) levels in pickling and phosphating baths, and nitrate accelerator dosage. A Taguchi L16 (2⁴) experimental design was implemented under real manufacturing constraints. Surface roughness (Rz) was measured in accordance with ISO 4287 and analyzed using a general linear model supported by partial effect size estimation (ηp²) and bootstrap confidence intervals. This approach enables statistically robust ranking of dominant and secondary control parameters, rather than qualitative trend confirmation alone. The robustness of statistically identified trends was independently verified using paired measurements from 25 production components, while scanning electron microscopy provided qualitative mechanistic support. The results demonstrate that pickling acid chemistry and nitrate accelerator dosage are the dominant control parameters governing surface roughness stability, whereas Fe²⁺ concentration does not act as a primary independent driver within the defined Fe²⁺ concentration ranges investigated in this study, but contributes through interaction-dependent mechanisms. Phosphoric acid pickling combined with nitrate acceleration consistently yields lower and more stable roughness values. In addition, roughness-related nonconformities were translated into product carbon footprint outcomes using an ISO 14067–aligned, gate-to-gate framework with Monte Carlo uncertainty analysis, explicitly quantifying the carbon footprint penalties associated with quality-driven rework and external return logistics under industrial production conditions. Full article

The efficiency of organic solar cells is constantly improving thanks to more advanced materials. Electron donor polymers, such as PM6 and its derivatives, as well as non-fullerene acceptors (NFAs) Y6 and ITIC and their derivatives, have become the standard materials for organic solar cell studies. To broaden the absorption range of solar cells, so-called ternary organic solar cells have been developed, which add a third material to the active layer. In this work, two chromophores based on the derivatives of the Janus-dione (s-indacene-1,3,5,7(2H,6H)-tetraone) central acceptor fragment, namely TIIC-1 and TIIC-2, were synthesized. Materials were characterized using theoretical and experimental methods, including UV-Vis absorption measurements, cyclic voltammetry, photoemission yield spectroscopy, and photoconductivity. The materials were incorporated as ternary components in PM6:Y7 bulk heterojunction solar cells. The power conversion efficiency (PCE) of PM6:Y7:TIIC-1 ternary solar cells was improved compared to binary PM6:Y7 reference cells. The PCE increased from 11.9% in binary blends to 12.5% in ternary cells. This increase is attributed to the cascade-like energy level arrangement, which facilitates charge transfer in the photoactive layer. Full article

In the field of construction engineering, utilizing information technology to empower and upgrade traditional construction methods has become an inevitable trend. Intelligent construction sites aim to enhance project management, quality, and safety levels through three layers—digitalization, networking, and intelligentization—by leveraging advanced information technologies such as Building Information Modeling (BIM), the Internet of Things (IoT), intelligent equipment, and big data. To promote the application of intelligent construction site technology, this paper takes intelligent construction sites as the research object, with the analysis of application benefits as the primary research focus. It systematically examines the definition and connotation of intelligent construction sites, reviews the current research status of intelligent construction sites and benefit evaluation theory, and proposes an intelligent construction site application benefit system across five dimensions: economy, product, organization, management, and strategy. Existing benefit assessment studies predominantly adopt single-dimension evaluation approaches, lacking integrated frameworks that combine quantitative and qualitative analysis. Return on Investment (ROI) and Analytic Hierarchy Process (AHP) analysis models are employed to calculate and evaluate the direct and indirect benefits, respectively. Validation was conducted through an actual project, and the results demonstrate that the application of intelligent construction sites yields an ROI of 102.7% based on discounted cash flow analysis (8% social discount rate), with an expert scoring of 9.42 for indirect benefits. The analysis models indicate positive benefits associated with intelligent construction site implementation. While direct causal attribution requires controlled comparison, the observed improvements are consistent with theoretical expectations and industry benchmarks for intelligent construction site adoption. This study verifies the availability of the evaluation system through its application to an actual project. It is hoped that this research will provide a reference for decision-making regarding the application and promotion of intelligent construction sites. Full article