Search Results (263)

This review presents a comprehensive synthesis of recent advances in the tensile performance of adhesively bonded joints, focusing on applied aspects and modeling developments rather than providing a full theoretical analysis. Although many studies have addressed individual joint types or modeling techniques, an integrated review that compares joint configurations, modeling strategies, and performance optimization methods under tensile loading remains lacking. This work addresses that gap by examining the mechanical behavior of key joint types, namely, single-lap, single-strap, and double-strap joints, and highlighting their differences in stress distribution, failure mechanisms, and structural efficiency. Modeling and simulation approaches, including cohesive zone modeling, extended finite element methods, and virtual crack closure techniques, are assessed for their predictive accuracy and applicability to various joint geometries. This review also covers material and geometric enhancements, such as adherend tapering, fillets, notching, bi-adhesives, functionally graded bondlines, and nano-enhanced adhesives. These strategies are evaluated in terms of their ability to reduce stress concentrations and improve damage tolerance. Failure modes, adhesive and adherend defects, and delamination risks are also discussed. Finally, comparative insights into different joint configurations illustrate how geometry and adhesive selection influence strength, energy absorption, and weight efficiency. This review provides design-oriented guidance for optimizing bonded joints in aerospace, automotive, and structural engineering applications. Full article

Accurate and timely forecasting of cross-regional tourist flows is essential for sustainable destination management, yet existing models struggle with sparse data, complex spatiotemporal interactions, and limited interpretability. This paper presents SE-TFF, a multi-scale tourism-flow forecasting framework that couples a Squeeze-and-Excitation (SE) network with reinforcement-driven optimization to adaptively re-weight environmental, economic, and social features. A benchmark dataset of 17.8 million records from 64 countries and 743 cities (2016–2024) is compiled from the Open Travel Data repository in github (OPTD) for training and validation. SE-TFF introduces (i) a multi-channel SE module for fine-grained feature selection under heterogeneous conditions, (ii) a Top-K attention filter to preserve salient context in highly sparse matrices, and (iii) a Double-DQN layer that dynamically balances prediction objectives. Experimental results show SE-TFF attains 56.5% MAE and 65.6% RMSE reductions over the best baseline (ARIMAX) at 20% sparsity, with 0.92 × 10³ average MAE across multi-task outputs. SHAP analysis ranks climate anomalies, tourism revenue, and employment as dominant predictors. These gains demonstrate SE-TFF’s ability to deliver real-time, interpretable forecasts for data-limited destinations. Future work will incorporate real-time social media signals and larger multimodal datasets to enhance generalizability. Full article

Plant diseases significantly undermine agricultural productivity. This study introduces an improved YOLOv10n model named WD-YOLO (Weighted and Double-scale YOLO), an advanced architecture for efficient plant disease detection. The PlantDoc dataset was initially enhanced using data augmentation techniques. Subsequently, we developed the DSConv module—a novel convolutional structure employing double-scale weighted convolutions that dynamically adjust to different scale perceptions and optimize attention allocation. This module replaces the conventional Conv module in YOLOv10. Furthermore, the WTConcat module was introduced, dynamically merging weighted concatenation with a channel attention mechanism to replace the Concat module in YOLOv10. The training of WD-YOLO incorporated knowledge distillation techniques using YOLOv10l as a teacher model to refine and compress the architectural learning. Empirical results reveal that WD-YOLO achieved an mAP50 of 65.4%, outperforming YOLOv10n by 9.1% without data augmentation and YOLOv10l by 2.3%, despite having significantly fewer parameters (9.3 times less than YOLOv10l), demonstrating substantial gains in detection efficiency and model compactness. Full article

Background: Optimal nutrition and training regimens are essential for athletes to maximize performance and recovery. Probiotic supplementation, through the modulation of the gut microbiota, and omega-3 fatty acids, known for their anti-inflammatory properties, may enhance physiological adaptations when combined with targeted training. This study evaluated the effects of probiotics and omega-3 supplementation, alongside ultra-short race pace training (USRPT), on performance metrics in competitive sprint swimmers. Methods: In this double-blind, placebo-controlled study, 60 male sprint swimmers (age: 19.2 ± 3.6 years; height: 182.2 ± 5.2 cm; weight: 81.6 ± 4.4 kg) with a minimum of five years of training experience, were randomly assigned to six groups (n = 10 per group): (1) Control (CON), (2) USRPT only, (3) Placebo + USRPT (PLA + USRPT), (4) Probiotics + USRPT (PRO + USRPT), (5) Omega-3 + USRPT (OMEGA + USRPT), and (6) Probiotics + Omega-3 + USRPT (PRO + OMEGA + USRPT). Over the eight-week intervention, the participants in PRO + USRPT consumed one multi-strain probiotic capsule daily (4.5 × 10¹¹ CFU) and a placebo capsule. Those in OMEGA + USRPT ingested 1000 mg of fish oil after lunch (500 mg EPA and 180 mg DHA per capsule) paired with a placebo capsule. The combined supplementation group (PRO + OMEGA + USRPT) received both probiotic and omega-3 capsules. The PLA + USRPT group consumed two starch capsules daily. The USRPT protocol was implemented across all the training groups, where the swimmers performed 17 sets of 25 m and 12.5 m sprints based on weekly recorded race times. Performance assessments included pre- and post-test measurements of sprint times (50 m and 100 m freestyle), vertical jump tests (both in water and on dry land), and other strength and endurance metrics (reaction time, agility T-test, sprint index, fatigue index, and velocity). Results: The combined intervention of probiotics and omega-3 with USRPT produced the greatest improvements in performance. The PRO + OMEGA + USRPT group reduced 50 m freestyle time by 1.92% (p = 0.002, pEta² = 0.286) and 100 m freestyle time by 2.48% (p = 0.041, pEta² = 0.229), demonstrating significant Time × Group interactions consistent with a synergistic effect. Additionally, the sprint index improved (pEta² = 0.139, p = 0.013) and reaction time decreased (pEta² = 0.241, p = 0.009) in the combined group, indicating enhanced anaerobic capacity and neuromuscular responsiveness compared to single interventions. Conclusions: This study suggests that combining probiotics and omega-3 supplementation with USRPT leads to synergistic improvements in sprint swimming performance, enhancing anaerobic power and recovery beyond what is achieved with individual interventions. This integrated approach may provide a practical strategy for competitive swimmers seeking to optimize their performance. Future studies should incorporate mechanistic markers, longer intervention durations, and diverse athlete populations to clarify further and extend these findings. Full article

In advanced structural applications—aerospace and automotive—fiber-laminated composite (FRP) materials are increasingly used for their superior strength-to-weight ratios, making the reliability of their mechanical joints a critical concern. Mechanically fastened joints play a major role in ensuring the structural stability of FRP Composite structures; however, accurately predicting their failure behavior remains a major challenge due to the anisotropic and heterogeneous nature of composite materials. This paper presents a progressive damage modeling approach to investigate the failure modes and joint strength of mechanically fastened carbon fiber-laminated (CFRP) composite joints. A 3D constitutive model based on continuum damage mechanics was developed and implemented within a three-dimensional finite element framework. The joint model comprises a composite plate, a steel plate, a steel washer, and steel bolts, capturing realistic assembly behavior. Both single- and double-lap joint configurations, featuring single and double bolts, were analyzed under tensile loading. The influence of clamping force on joint strength was also investigated. Model predictions were validated against existing experimental results, showing a good correlation. It was observed that double-lap joints exhibit nearly twice the strength of single-lap joints and can retain up to 85% of the strength of a plate with a hole. Furthermore, double-lap configurations support higher clamping forces, enhancing frictional resistance at the interface and load transfer efficiency. However, the clamping force must be optimized, as excessive values can induce premature damage in the composite before external loading. The stiffness of double-bolt double-lap (3DD) joints was found to be approximately three times that of single-bolt single-lap (3DS) joints, primarily due to reduced rotational flexibility. These findings provide useful insights into the design and optimization of composite bolted joints under tensile loading. Full article

The evolutionary patterns and influencing factors of the coupling coordination among multiple functions of cultivated land serve as an important basis for emphasizing the value of cultivated land utilization and promoting coordinated regional development. The entropy weight TOPSIS model, coupling coordination degree (CCD) model, spatial autocorrelation analysis, and Geodetector were employed in this study along with panel data from 125 cities in the Yangtze River Economic Belt (YREB) for 2010, 2015, 2020, and 2022. Three key aspects in the region were investigated: the spatiotemporal evolution of cultivated land functions, characteristics of coupling coordination, and their underlying influencing factors. The results show the following: (1) The functions of cultivated land for food production, social support, and ecological maintenance are within the ranges of [0.023, 0.460], [0.071, 0.451], and [0.134, 0.836], respectively. The grain production function (GPF) shows a continuous increase, the social carrying function (SCF) first decreases and then increases, and the ecological maintenance function (EMF) first increases and then decreases. Spatially, these functions exhibit non-equilibrium characteristics: the grain production function is higher in the central and eastern regions and lower in the western region; the social support function is higher in the eastern and western regions and lower in the central region; and the ecological maintenance function is higher in the central and eastern regions and lower in the western region. (2) The coupling coordination degree of multiple functions of cultivated land is within the range of [0.158, 0.907], forming a spatial pattern where the eastern region takes the lead, the central region is rising, and the western region is catching up. (3) Moran’s I index increased from 0.376 in 2010 to 0.437 in 2022, indicating that the spatial agglomeration of the cultivated land multifunctionality coupling coordination degree has been continuously strengthening over time. (4) The spatial evolution of the coupling coordination of cultivated land multifunctionality is mainly influenced by the average elevation and average slope. However, the explanatory power of socioeconomic factors is continuously increasing. Interaction detection reveals characteristics of nonlinear enhancement or double-factor enhancement. The research results enrich the study of cultivated land multifunctionality and provide a decision-making basis for implementing the differentiated management of cultivated land resources and promoting mutual enhancement among different functions of cultivated land. Full article

Vehicle collisions with street lighting poles generate extremely high impact forces, often resulting in serious injuries or fatalities. Therefore, enhancing the structural resilience of pole bases is a critical engineering objective. This study investigates a comprehensive dynamic analysis conducted with respect to base material behavior and energy absorption of GFRP lighting pole structures under impact loads. A finite element (FE) model of a 5 m-tall tapered GFRP pole with a steel base sleeve, base plate, and anchor bolts was developed. A 500 kg drop-weight impact at 400 mm above the base simulated vehicle collision conditions. The model was validated against experimental data, accurately reproducing the observed failure mode and peak force within 6%. Parametric analyses explored variations in pole diameter, wall thickness, base plate size and thickness, sleeve height, and anchor configuration. Results revealed that geometric parameters—particularly wall thickness and base plate dimensions—had the most significant influence on energy absorption. Doubling the wall thickness reduced normalized energy absorption by approximately 76%, while increases in base plate size and thickness reduced it by 35% and 26%, respectively. Material strength and anchor bolt configuration showed minimal impact. These findings underscore the importance of optimizing pole geometry to enhance crashworthiness. Controlled structural deformation improves energy dissipation, making geometry-focused design strategies more effective than simply increasing material strength. This work provides a foundation for designing safer roadside poles and highlights areas for further exploration in base configurations and connection systems. Full article

UAV-based small target detection is crucial in environmental monitoring, circuit detection, and related applications. However, UAV images often face challenges such as significant scale variation, dense small targets, high inter-class similarity, and intra-class diversity, which can lead to missed detections, thus reducing performance. To solve these problems, this study proposes a lightweight and high-precision model UAV-YOLO based on YOLOv8s. Firstly, a double separation convolution (DSC) module is designed to replace the Bottleneck structure in the C2f module with deep separable convolution and point-by-point convolution fusion, which can reduce the model parameters and calculation complexity while enhancing feature expression. Secondly, a new SPPL module is proposed, which combines spatial pyramid pooling rapid fusion (SPPF) with long-distance dependency modeling (LSKA) to improve the robustness of the model to multi-scale targets through cross-level feature association. Then, DyHead is used to replace the original detector head, and the discrimination ability of small targets in complex background is enhanced by adaptive weight allocation and cross-scale feature optimization fusion. Finally, the WIPIoU loss function is proposed, which integrates the advantages of Wise-IoU, MPDIoU and Inner-IoU, and incorporates the geometric center of bounding box, aspect ratio and overlap degree into a unified measure to improve the localization accuracy of small targets and accelerate the convergence. The experimental results on the VisDrone2019 dataset showed that compared to YOLOv8s, UAV-YOLO achieved an 8.9% improvement in the recall of mAP@0.5 and 6.8%, while the parameters and calculations were reduced by 23.4% and 40.7%, respectively. Additional evaluations of the DIOR, RSOD, and NWPU VHR-10 datasets demonstrate the generalization capability of the model. Full article

Background/Objectives: Despite extensive research on caffeine’s (CAF’s) ergogenic effects, evidence regarding its impact on anaerobic performance in female athletes remains limited and inconclusive. The aim of this study was to investigate the acute effects of 6 mg/kg⁻¹ caffeine on anaerobic performance, functional strength, agility, and ball speed in female soccer players. Methods: A randomized, double-blind, placebo-controlled crossover design was employed. Thirteen moderately trained female soccer players (age: 21.08 ± 1.11 years; height: 161.69 ± 6.30 cm; weight: 59.69 ± 10.52 kg; body mass index (BMI): 22.77 ± 3.50 kg/m²; training age: 7.77 ± 1.16 years; habitual caffeine intake: 319 ± 160 mg/day) completed two experimental trials (caffeine vs. placebo (PLA)), separated by at least 48 h. Testing sessions included performance assessments in vertical jump (VJ), running-based anaerobic sprint test (RAST), bilateral leg strength (LS), handgrip strength (HS), single hop for distance (SH), medial rotation (90°) hop for distance (MRH), change of direction (COD), and ball speed. Rating of perceived exertion (RPE) was also recorded. Results: CAF ingestion significantly improved minimum (p = 0.011; d = 0.35) and average power (p = 0.007; d = 0.29) during RAST. A significant increase was also observed in SHR (single leg hop for distance right) performance (p = 0.045; d = 0.44). No significant differences were found in VJ, COD, ball speed, LS, HS, SHL, MRHR, or MRHL (p > 0.05). RPE showed a moderate effect size (d = 0.65) favoring the CAF condition, though not statistically significant (p = 0.110). Conclusions: In conclusion, acute CAF intake at a dose of 6 mg/kg⁻¹ may enhance anaerobic capacity and lower-limb functional strength in female soccer players, with no significant effects on jump height, agility, or upper-body strength. Full article

This study evaluated the effects of fermented banana agro-waste silage (BAWS) in finishing diets for KHAPS pigs (Duroc × MeiShan hybrid). BAWS was produced via 30 days of anaerobic fermentation of disqualified banana fruit, pseudostem, and wheat bran, doubling crude protein content and generating short-chain fatty acids, as indicated by a satisfactory Flieg’s score. Thirty-six pigs were assigned to control (0%), 5%, or 10% BAWS diets formulated to meet NRC nutritional guidelines. Over a 70-day period, BAWS inclusion caused no detrimental effects on growth performance, carcass traits, or meat quality; a transient decline in early-stage weight gain and feed efficiency occurred in the 10% group, while BAWS-fed pigs demonstrated reduced backfat thickness and increased lean area. Fore gut microbiome analysis revealed reduced Lactobacillus and elevated Clostridium sensu stricto 1, Terrisporobacter, Streptococcus, and Prevotella, suggesting enhanced fiber and carbohydrate fermentation capacity. Predictive COG (clusters of orthologous groups)-based functional profiling showed increased abundance of proteins associated with carbohydrate transport (COG2814, COG0561, COG0765) and stress-response regulation (COG2207). These results support BAWS as a sustainable feed ingredient that maintains production performance and promotes fore gut microbial adaptation, with implications for microbiota-informed nutrition and stress resilience in swine. Full article

Polyurethane (PU) is widely employed in the biomedical field. As application scenarios become increasingly complex, it is essential to modify PU to meet diverse requirements. Additionally, the degradation of PU is closely linked to the sustainability of its function, with degradation products having a direct impact on adjacent tissues. In this study, a novel PU containing double bonds in its main chain was developed. We investigated the influence of various ratios of soft segment composition on the degradation performance of PU, maintaining a fixed ratio of soft to hard segments and utilizing specific synthesis methods. The structure and molecular weight of the PU were analyzed using FTIR, NMR, and GPC techniques. The results of physical and chemical performance tests indicated that an increase in polycaprolactone diol (PCL diol) content within the soft segment enhanced the mechanical properties, hydrophobicity, and degradation performance of the PU. A further assessment of the degradation toxicity of PU was carried out using zebrafish as a model organism. The findings indicated that the degradation solution of PU exhibited slight toxicity to zebrafish embryonic development over prolonged degradation periods. However, it also significantly enhanced the hatching of zebrafish embryos. In summary, the novel PU developed in this study demonstrates favorable biocompatibility, and the approach of introducing reaction sites or modifying the composition of its soft segments within the molecular structure offers a promising and effective strategy to address specific application requirements. Full article

(1) Background: Lima beans (Phaseolus lunatus L.) are underutilized legumes rich in nutrients; however, they are limited by the presence of antinutritional content. In this study, we evaluated the effects of a low-cost germination treatment on the nutritional composition, antinutrient content, and digestibility of whole lima beans. (2) Methods: unlike previous studies focused on common legumes or isolated proteins, this work adopted a whole-seed approach and integrated multiple parameters to provide a comprehensive evaluation. (3) Results: The total polyphenol and flavonoid contents increased significantly, by 215.57 mg GAE/g and 71.84 mg RE/g, respectively, at 72 h of germination (p < 0.05). Antioxidant activity nearly doubled compared to raw beans, while the tannins and phytic acid content decreased significantly (p < 0.05). SDS-PAGE showed that germination enhanced digestibility by breaking down high-molecular-weight proteins into smaller fragments (15–30 kDa). Notably, samples germinated for 12–48 h showed higher digestibility after 2–3 h of limited proteolysis. (4) Conclusions: these findings indicate that germination effectively reduces antinutritional factors and improves digestibility, making processed lima beans a promising nutrient-dense ingredient for food formulations. Full article

This study systematically investigated two ecotypes of Ulva prolifera, the dominant species responsible for green tides in the Yellow Sea, classified as Subtype I (strain I08-1) and Subtype II (strain QD-7). Both subtypes produce positively phototactic biflagellate gametes with oval/pear-shaped morphology but exhibit distinct cellular dimensions. Subtype I gametes demonstrated significantly larger cell sizes, with long and short axes measuring 6.55 μm and 4.62 μm, respectively, compared to Subtype II’s dimensions of 6.46 μm (long axis) and 3.03 μm (short axis). Developmental analysis revealed striking morphological divergence at the 6-day germling stage: Subtype I attained an average length of 1301.14 μm, more than doubling Subtype II’s 562.25 μm. Superior growth kinetics were observed in Subtype I, exhibiting enhanced specific growth rates (SGRs) across multiple parameters—main stem length (8.58% vs. 3.55%), primary branch elongation (19.17% vs. 12.59%), main stem width expansion (17.29% vs. 5.00%), and biomass accumulation (41.90% vs. 40.96% fresh weight). Chlorophyll quantification confirmed significantly higher pigment content in Subtype I. Pre-co-culture photosynthetic profiling demonstrated Subtype I’s superior quantum efficiency (α = 0.077 vs. 0.045) with marked differences in regulated energy dissipation (YNPQ) and non-photochemical quenching (NPQ). Post-co-culture physiological adaptation was evident in Subtype II, showing significant elevation of non-regulated energy dissipation quantum yield (YNO) and eventual surpassing of maximum electron transport rate (ETRmax) compared to Subtype I. These findings establish that U. prolifera employs robust photoprotective and thermal adaptation strategies under natural photothermal conditions. Crucially, YNO-based analysis revealed Subtype II’s enhanced high-light protection mechanisms and superior adaptability to intense irradiance environments. This research elucidates ecotype-specific environmental adaptation mechanisms in U. prolifera, providing critical insights for optimizing green tide mitigation strategies and advancing ecological understanding of algal bloom dynamics. Full article

Noise reduction is essential in analyzing electrochemical impedance spectroscopy (EIS) data for accurate parameter identification of models of electrochemical sources and interfaces. EIS is widely used to study the behavior of electrochemical systems as it provides information about the processes occurring at electrode surfaces. However, measurement noise can severely compromise the accuracy of parameter identification and the interpretation of EIS data. This paper presents methods for parameter identification of Randles (also known as R-RC or 2R-1C) equivalent electrical circuits and noise reduction in EIS data using recursive filtering. EIS data obtained at the estimated characteristic frequency is processed with three equations in the closed form for the parameter estimation of series resistance, charge transfer resistance, and double-layer capacitance. The proposed recursive filter enhances estimation accuracy in the presence of random noise. Filtering is embedded in the estimation procedure, while the optimal value of the recursive filter weighting factor is self-tuned based on the proposed search method. The distinguished feature is that the proposed method can process EIS data and perform estimation with filtering without any input from the user. Synthetic datasets and experimentally obtained impedance data of lithium-ion batteries were successfully processed using PC-based and microcontroller-based systems. Full article

Grain yield establishment is a complex progress and the genetic basis of one of the most important yield components, 100-kernel weight, remains largely unknown. Here, we employed a double haploid (DH) population containing 477 lines which was developed from a cross of two maize elite inbred lines, PHBA6 and Chang7-2, to identify quantitative trait loci (QTL) that related to 100-kernel weight. The phenotypes of the DH population were acquired over three years in two different locations, while the DH lines were genotyped by next-generation sequencing technology of massively parallel 3ʹ end RNA sequencing (MP3RNA-seq). Eventually, 28,874 SNPs from 436 DH lines were preserved after SNP calling and filtering and a genetic map with a length of 837 cM was constructed. Then, single environment QTL analysis was performed using the R/qtl program, and it was found that a total of 17 QTLs related to 100-kernel weight were identified and distributed across the whole genome except chromosomes 5 and 6. The total phenotypic variation explained by QTLs detected in three different environments (BJ2016, BJ2107, and HN2018) was 22.2%, 32.9%, and 51.38%, respectively. Among these QTLs, three of them were identified across different environments as environmentally stable QTLs and explained more than 10% of the phenotypic variance each. Together, the results provided in this study preliminarily revealed the genetic basis of 100-kernel weight and will enhance molecular breeding for key agronomic kernel-related traits in maize. Full article