Search Results (20,771)

This study proposes a lightweight domain-assisted deep learning framework for binary human presence detection using ultra-wideband (UWB) radar. The proposed methodology processes raw UWB radar signals through statistically screened, physics-grounded signal features including Fast Fourier Transform (FFT)-based frequency-domain statistics and Hilbert Transform (HT)-derived envelope statistics which are selected via a per-subject Cohen’s d screening step and stacked as auxiliary input channels alongside the raw signal for a lightweight two-dimensional convolutional neural network (2D-CNN). A cross-subject evaluation protocol (train-on-one-subject, test-on-the-other) is adopted to assess generalization across individuals rather than relying on a pooled, sample-level split. Among the candidate features, a Frequency Standard Deviation (FSTD) is shown to match or exceed the performance of every multi-feature combination tested, indicating that targeted feature selection is more consequential than input fusion for this task. To further improve deployment efficiency, post-training INT8 quantization is applied, reducing the model to approximately 23 KB while preserving classification performance for quantization-robust configurations. Hardware-in-the-loop benchmarking on the STEdgeAI platform indicates on-device inference times ranging from approximately 0.88 ms on AI-enabled STM32N6 hardware to 117–130 ms on STM32H7-class microcontrollers; these figures reflect model inference only and exclude radar acquisition and preprocessing time. Experiments are conducted on a two-subject (one male, one female) indoor dataset; the reported cross-subject results are presented as a relative comparison across feature and quantization configurations rather than as an estimate of population-level generalization. The findings nonetheless illustrate the feasibility of combining principled feature selection with quantization-aware, hardware-validated deployment on embedded artificial intelligence (AI) platforms. Full article

Pepper suffers from bacterial leaf spot and yellow leaf curl, which substantially reduce crop yield and fruit quality. Traditional manual diagnosis suffers from delayed response, subjective bias and heavy labor consumption, while existing intelligent detection pipelines lack standardized preprocessing workflows, quantitative feature screening and systematic model comparison. To fill these research gaps, we built a pepper leaf dataset with 1260 samples (healthy, bacterial spot, yellow leaf curl). Three segmentation algorithms (Lab b-channel, RGB super-green, Otsu-ACWE) were quantitatively assessed to select the optimal preprocessing scheme. We extracted 32 fused visual features (27 RGB/HSV/Lab color moments + five gray-level co-occurrence matrix (GLCM) texture metrics) and adopted a random-forest classifier to eliminate seven low-contribution redundant features, retaining 25 discriminative variables. Three representative models, namely convolutional neural network (CNN), logistic regression (LR), and genetic-algorithm-optimized back-propagation neural network (GA-BP), were constructed for parallel comparison via 20 independent repeated trials, with accuracy, precision, recall, F1-score and area under the receiver operating characteristic curve (AUC) as evaluation indicators. The results verified that Lab b-channel segmentation achieved superior background separation and intact lesion edge retention. CNN yielded the best performance, with an average test accuracy of 97.67% and an average AUC of 0.999, accompanied by minimal metric standard deviations and outstanding stability. LR exhibits low computational cost and fast training, which is promising for applications with limited computing resources. In contrast, GA-BP shows weak nonlinear fitting ability and severe prediction fluctuations, making it unsuitable for high-precision diagnosis. This study proposes a standardized experimental framework to offer theoretical guidance and algorithmic references for intelligent vegetable leaf disease identification. All experiments were conducted on a dataset collected under standardized indoor single-illumination conditions; therefore, the conclusions of this study are only applicable to such controlled scenarios. Full article

Curved bridges subjected to strong ground motions have shown high seismic vulnerability in many countries. Several published studies analyze curved-bridge failures, focusing on collapses observed after severe earthquakes, which are frequently linked to loss of seating length. Other studies assess seismic fragility based on expected pier damage, and most published work uses numerical models derived from existing bridge portfolios that do not include specific real bridges. Many studies also aim to correlate the dynamic properties of existing bridges, estimated from ambient vibration measurements, with those of numerical models. The approaches mentioned above estimate the expected seismic response for specific bridge types that may not accurately represent real structures, and examine the most common failure mechanisms. Unlike these studies, the current research provides valuable and novel insights into the expected behavior of curved viaducts designed in accordance with modern standards and regulations. It shows that, in these cases, the most frequently reported failure in the literature, loss of seating length, is less likely than other failure mechanisms. The results apply to a real curved bridge whose numerical model was previously calibrated using ambient vibration measurements. Another distinctive feature is the assessment of reliability indices for a real structure, evaluating the values that current regulations would expect to observe during infrequent seismic events. Uncertainties in site amplification are reduced because a nearby seismic station is available. Nonlinear analyses were performed using two sets of seismic records from interplate and intraplate earthquake sources, scaled to match the expected seismic intensity at the bridge site, to assess damage progression in the bridge under both design and infrequent earthquake intensities. The study also emphasizes the significant effects of the selected ground-motion population and the frequency content of interplate and intraplate earthquakes on bridge seismic performance. Unlike the failure mechanism most commonly observed in curved bridges during high-intensity seismic events, which involves loss of superstructure seating length, this case study of a curved bridge designed under modern seismic regulations shows failure when shear demands exceed the bridge piers’ shear capacity. Full article

The development of low-altitude passenger transport and emerging short-haul air services has made inter-county short-distance routes an important subject for regional aviation market research and preliminary planning. However, piloted eVTOL and low-altitude short-haul passenger services remain at an early stage, lacking continuous and stable historical operational data for supervised modelling. Moreover, unobserved county-level routes cannot be simply regarded as having no market potential. This study formulates county-level candidate route identification as a large-scale priority ranking problem under sparse proxy labels and develops a multi-relational graph ranking framework. The framework integrates county attributes, mobility, transport impedance, high-speed rail substitution conditions, and estimated air travel time variables through multiple relational graphs, and employs an MR-GAT ranking model to learn relative priorities among candidate routes using a pairwise ranking objective. Observed civil aviation route labels and flight frequencies are used as primary supervision signals, while airport catchment weak labels are introduced for auxiliary analysis. Experiments conducted over 240,350 county-level candidate ODs show that, across ten random seeds, the MR-GAT model achieves a mean internal Top-1000 recall of 16.33%, compared with 7.55% for XGBoost and 2.00% for the gravity-based heuristic. Paired bootstrap analysis further supports the higher internal top-ranked retrieval performance of MR-GAT over XGBoost. Ten-seed relational ablation shows relatively small differences among individual relation-removal variants, indicating that no single relational graph dominates the ranking performance under the current evaluation setting. Sensitivity analysis further shows that the resulting ranking is highly robust to uniform additions of up to 90 min to the estimated air travel time. Analysis of the resulting candidate set indicates that high-ranking ODs are typically associated with stronger inter-county interactions, higher ground-transport impedance, and limited direct high-speed rail connectivity. The framework therefore provides an analytical screening tool for reducing a large candidate space to a smaller set of links for subsequent market and operational feasibility assessment. Full article

Understanding the cognitive architectures that enable learners to process feedback and self-regulate is fundamental to fostering intelligent second language (L2) learning, particularly as AI-based pedagogies become prevalent. Direct written corrective feedback, while common in beginner L2 writing, often triggers only surface-level processing. This study investigates whether written languaging (WL), a metacognitive activity where learners explain language problems in writing, can deepen feedback processing, thereby activating a more robust cognitive architecture for error correction. Using a within-subjects crossover design with 15 beginner Chinese-as-a-second-language (CSL) learners from a UK secondary school, we compared the immediate and transfer effects of direct feedback with WL versus direct feedback only. Results showed that the WL condition significantly reduced errors per 100 characters (Z = −2.556, p = .011, r = 0.66), with 86.7% of participants showing improvement, indicating enhanced cognitive regulation at the local level. However, the effect was hierarchical, with no significant impact on clause-level accuracy. General Certificate of Secondary Education (GCSE) writing scores improved significantly from pre-to-post-test (Z = −3.342, p = .001, r = 0.89), demonstrating transfer to subsequent performance. Qualitative analyses revealed that learners’ attention focused predominantly on characters (48.4%) and vocabulary (29.8%), with engagement moderated by proficiency and motivation. This study provides empirical evidence for a cognitive architecture of feedback processing, wherein WL functions as a metacognitive amplifier. This architecture is operationalised as a three-stage processing sequence noticing, hypothesis-testing, and metalinguistic reflection, with writing accuracy and WL texts serving as observable proxies for the underlying cognitive processes. Specifically, our findings reveal that WL’s facilitative effects are hierarchical, strongest at the level of local error reduction and not yet extending to clause-level syntactic accuracy, and are moderated by individual differences in proficiency and motivation. These empirical insights offer a cognitive-psychological foundation that could inform the future design of adaptive feedback systems; however, as this study did not involve any AI system, these implications are theoretical and await empirical validation in AI-mediated learning environments. Full article

Flow-passing components such as volutes and fixed guide vanes operating in high-velocity liquid flows with high sediment concentrations are subjected to long-term cavitation erosion and sand-particle abrasion, which cause substantial economic losses. To reduce the manufacturing and maintenance costs of mechanical equipment serving such environments, laser cladding was employed to fabricate Fe₄₅Cr₂₅Ni₂₀Ti₅Mo₅ multi-principal-element alloy coatings on Q235 steel substrate, and the effect of laser power on the microstructure and properties of the coatings was systematically investigated. On the basis of preliminary investigations, the present work elaborately analyzes the wear resistance and cavitation-erosion resistance of coatings fabricated under laser powers of 1000 W, 1200 W and 1400 W. The results reveal that the coating hardness gradually decreases from a maximum value of 485.67 HV_0.2 to 363.15 HV_0.2 with increasing laser power. When the laser power is 1200 W, the coating prepared under this laser power maintains a good balance between hardness and microstructural integrity. Under identical friction-and-wear test conditions, its wear rate reaches only 3.15 × 10⁻⁵ mm³/(N·m), which is reduced by 19.64%, 27.92% and 39.19% compared with the coatings produced at 1000 W, 1400 W and bare Q235 steel, respectively. After a 20h cavitation-erosion test, the mass loss of this coating is merely 2.56 mg, representing reductions of 72.88%, 81.5% and 96.91% relative to the 1000 W coating, 1400 W coating and Q235 steel substrate. The coating fabricated at 1200 W exhibits outstanding wear resistance and cavitation-erosion resistance. The results indicate that, under the experimental conditions of this study, the wear resistance and cavitation-erosion resistance of the coating can be effectively optimized by adjusting the laser power. Full article

Vanilla planifolia curing is a critical process for developing vanillin and other aroma compounds; however, conventional thermal scalding (CTS) used during the killing stage may reduce the enzymatic activity required for phenolic compound formation during subsequent curing stages. This study evaluated the effect of high hydrostatic pressure (HHP) as a non-thermal killing method. Green vanilla pods were subjected to HHP treatments at 20–600 MPa for either 5 s or 5 min and compared with CTS. Moisture content, β-glucosidase and phenylalanine ammonia-lyase activities, total phenolic content, glucovanillin, vanillin, and antioxidant capacity were monitored throughout 20 sweating–drying cycles. Initial moisture content was 92%, but after 20 curing cycles, most HHP and CTS treatments reached final contents of 19.7–27.8%, except 20 MPa/5 min, which retained 60.4%, indicating delayed dehydration. Selected HHP treatments produced up to a fivefold higher initial apparent β-glucosidase activity than scalding and maintained higher activity during some early curing cycles, promoting glucovanillin conversion to vanillin. PAL activity increased immediately after the killing treatments, reaching 32.43 µmol min⁻¹ kg⁻¹ db for CTS and comparable values in specific HHP treatments (20 MPa/5 s, 50 MPa/5 s, and 100 MPa/5 min), demonstrating that PAL activity is affected by the pressure treatments. Selected HHP treatments also exhibited significantly higher TPC and antioxidant capacity than CTS samples at specific curing stages. Furthermore, an inverse relationship between glucovanillin depletion and vanillin formation was observed, resulting in greater vanillin accumulation and lower losses during curing. These findings indicate that HHP is a promising non-thermal alternative to conventional scalding for improving vanilla bean quality and potentially shortening the curing process. Full article

Drought events are expected to induce both immediate and delayed effects on tree functioning, yet the persistence and dynamics of these legacy effects remain poorly understood. In an experimental set-up, European beech (Fagus sylvatica L.) saplings were subjected to two consecutive water-withholding treatments during the 2022 growing season, resulting in five drought-severity categories. We monitored these categories over the following three years to assess drought legacy effects on phenology and growth. In the first post-drought year, bud burst proceeded more slowly in all drought categories, with the plants exposed to severe summer drought displaying the longest duration. Minor differences between drought categories and control plants were observed in timing of autumn leaf senescence in the first post-drought year and in the following bud burst, suggesting recovery in these phenological responses. Unexpectedly, differences re-emerged in autumn leaf senescence in the second post-drought year, when all drought categories displayed delayed senescence. This differentiation persisted into the following spring, with delayed bud burst in the severe spring- and summer-drought categories. The severe spring-drought categories maintained delayed senescence in the third post-drought year. Diameter and height growth were strongly reduced in the first year following drought. Although growth differences largely disappeared in the second post-drought year, the severe summer-drought categories exhibited enhanced diameter growth in the third year, indicating compensatory growth. Together, these results demonstrate that drought legacy effects in F. sylvatica are dynamically expressed over multiple years, and that such temporal variability complicates predictions of long-term forest responses to increasingly frequent episodic drought events under climate change. Full article

Understanding how visual structure shapes attentional allocation is central to models of perceptual processing. Less is known about how formal properties like harmony and complexity shape exploration independent of salience or semantic content. This study examined how controlled structural variations relate to attention, facial engagement, and subjective judgment using eye-tracking and webcam-based facial coding. Participants ($N=40$) viewed stimuli derived from a common geometric base, manipulated into three conditions: high harmony (symmetrical, low complexity), high complexity (asymmetrical, disorganized), and structured complexity (high complexity with underlying order). Eye movements and facial expressions were recorded during free viewing. Metrics included time to first fixation, fixation duration, number of fixations, scanpath entropy, spatial dispersion, and facial-coding indices (neutral, happy, and surprise expression, and the ambient/focal coefficient K). None of the eye-tracking or facial-coding metrics differed significantly across conditions; given that the study was powered to detect only medium-to-large effects, this indicates no detectable difference under the present webcam-based, brief-exposure design rather than evidence that visual structure has no effect on attention. Subjective complexity ratings differed robustly across conditions, surviving correction for multiple comparisons: unexpectedly, the high-complexity condition was rated as less complex than the harmony and structured-complexity conditions, indicating the intended manipulation did not translate into perceived complexity as designed. A nominally significant difference in pleasantness ratings did not survive this correction. Using repeated-measures correlation to account for the non-independence of within-participant observations, scanpath entropy showed a nominal negative association with pleasantness that did not survive correction for multiple comparisons, and the coefficient K showed a weaker and partly inconsistent pattern of association with independent oculomotor indices than initial uncorrected analyses suggested. These findings indicate that, in the present study, formal visual structure shaped subjective complexity judgments more robustly than it shaped overt attentional or facial-affective engagement, a pattern consistent with—though not conclusive proof of—a broader dissociation between evaluative and attentional responses reported in face perception and developmental aesthetics research. Beyond this substantive finding, we report in detail how accounting for repeated-measures non-independence and applying an explicit multiplicity strategy changed our statistical conclusions, offering a worked methodological example for similarly structured webcam-based eye-tracking and facial-coding studies. Full article

Reliable characterization of freeze–thaw-induced structural change is essential for evaluating compacted soils used in cold-region engineering, where repeated freezing and thawing can alter both surface integrity and internal pore structure. This study combines digital imaging, quantitative crack analysis, and X-ray computed tomography to characterize structural changes in compacted expansive soil subjected to 0, 1, 4, 7, and 10 freeze–thaw cycles. Specimens with initial water contents of 18% and 25% were observed during freezing and after thawing, while the post-thaw three-dimensional pore structure of the 18% specimen was reconstructed from CT images. The 18% surface specimen exhibited no continuous crack network despite evident internal pore restructuring, whereas the 25% specimen showed pronounced crack opening during freezing and partial closure after thawing. With increasing cycles, the crack pattern evolved from a dominant wide crack to a branched network of narrower cracks and then became less continuous. CT-resolvable porosity increased from 23.0% initially to 26.7% after four cycles and then remained nearly stable, whereas connected porosity increased to 25.4% after ten cycles. These complementary observations indicate that post-thaw surface appearance alone may underestimate freeze–thaw-induced structural disturbance and highlight the importance of moisture condition and early-cycle evolution in cold-region engineering. Full article

Objectives: To establish an animal model for investigating the impact of female reproductive hormones on perioperative blood loss during cranio-maxillofacial surgery. Methods: Forty female Sprague-Dawley rats were sequentially allocated into five groups (n = 8 each): one sham-operated group (SHAM) receiving vehicle and four ovariectomized groups (OVX) receiving either the vehicle, 17β-estradiol, progesterone, or follicle-stimulating hormone-β. Successful ovariectomy was verified by monitoring body mass and measuring terminal serum hormone concentrations. Following a 13-day hormonal regimen, all subjects underwent a standardized surgical procedure to induce mandibular hemorrhage. Perioperative blood loss was quantified gravimetrically until complete hemostasis. Results: In the primary analysis, total blood loss differed among the four OVX groups (p = 0.038), with lower blood loss observed in the 17β-estradiol-treated OVX rats (OVX+E) compared to the vehicle-treated OVX controls (p = 0.0495), though sensitivity analyses indicated that this finding should be interpreted with caution. Conclusions: Within the limitations of this study, 17β-estradiol treatment was associated with lower perioperative blood loss in ovariectomized female rats following surgically induced mandibular hemorrhage. This finding suggests that estradiol exposure may influence perioperative bleeding and highlights the need for confirmation in larger, adequately powered studies to further investigate the potential role of estradiol in the preoperative risk assessment of female patients undergoing cranio-maxillofacial procedures. Full article

Rural teachers often face work overload arising from demanding teaching responsibilities and extensive non-teaching duties, which may be closely associated with their subjective well-being. However, prior research has largely adopted a single-effect perspective, paying insufficient attention to the potentially competing mechanisms linking work overload to well-being. Drawing on cognitive appraisal theory of stress, this study develops a moderated parallel mediation model to examine the dual pathways through which work overload is associated with rural teachers’ subjective well-being. Survey data were collected from 639 rural primary and secondary school teachers across 12 provincial-level regions in western China. The proposed model was tested using confirmatory factor analysis, hierarchical regression, and bootstrapping. The results indicate that work overload is positively associated with subjective well-being through job crafting, but negatively associated with subjective well-being through emotional exhaustion. Self-efficacy strengthens the positive association between work overload and job crafting while weakening the positive relationship between work overload and emotional exhaustion. Moreover, self-efficacy moderates both indirect associations, amplifying the beneficial pathway through job crafting and attenuating the detrimental pathway through emotional exhaustion. These findings reveal two distinct mechanisms linking work overload to rural teachers’ subjective well-being and extend research on occupational stress by identifying self-efficacy as an important boundary condition. The study also provides practical implications for educational authorities seeking to optimize workload arrangements and develop targeted support and incentive mechanisms for rural teachers. Full article

During service, conformal load-bearing antennas (CLBAs) are subjected to the coupled effects of aerodynamic and aerothermal loads. The resulting geometric distortion of the array surface, deflection of element pointing, and temperature drift of the material electromagnetic parameters lead to the degradation of radar cross-section (RCS) characteristics. To overcome the limitation of existing scattering models in uniformly describing the aforementioned multi-physics coupling effects, this paper proposes a comprehensive electromechanical–thermal coupled modeling method for the scattering field of CLBAs. This method establishes a complete mapping from flight conditions to the array RCS by incorporating geometric corrections for element-level pointing deflection and bending deformation, material corrections accounting for the temperature-dependent antenna efficiency, and phase corrections induced by aerodynamic displacements. Verification using a 9 × 9 cylindrical conformal array shows that, within a scanning range of ±30°, the model calculations agree with HFSS full-wave simulations with an absolute error of less than 1 dB, and the broadside RCS is reduced by 14.97 dB compared with that of a planar array. Furthermore, a BP neural network surrogate model is constructed to achieve accurate prediction of the array physical fields. Analyses across the Mach regime of 0.20–0.65 Ma indicate that structural deformation is the dominant cause of RCS distortion, with the trailing-edge array experiencing a rapid nonlinear increase in RCS peak increment, reaching up to 7 dB at 0.65 Ma. The proposed model provides an effective theoretical tool for the rapid evaluation of stealth performance for conformal antennas operating in complex environments. Full article

Background: Insufficient physical activity has become a significant public health problem. Currently, physical education classes alone are insufficient to meet the physical activity levels recommended by the World Health Organization. Physically Active Learning (PAL), as a novel curriculum, promotes physical activity by teaching new knowledge in various school subjects. Objective: To systematically evaluate the effects of PAL interventions on primary school students’ physical fitness, physical activity, and sedentary behavior, characterize the key features of PAL interventions, identify research gaps, and provide evidence-based recommendations for practice. Methods: Following the PRISMA guidelines, four electronic databases—Web of Science, ProQuest, Ebsco, and Embase—were searched, and English-language controlled intervention studies that met the PICOS eligibility criteria were included. Two researchers independently screened the literature and extracted and cross-checked the data. Results: This study included 17 studies from 8 countries published between 2009 and 2025. These studies involved primary school students aged 6 to 12. PAL most consistently increased MVPA (moderate-to-vigorous physical activity) or number of steps during the targeted academic lesson, whereas effects on whole-school-day, daily, or weekly physical activity were inconsistent. Lesson-level sedentary behaviour generally decreased or was replaced by walking, standing, or sit-to-stand transitions, but effects on whole-day sedentary time were mixed. Physical fitness interventions yielded varied outcomes, demonstrating significant improvements in upper body strength and explosive muscle strength and endurance, while showing inconsistent effects on aerobic capacity, and no significant changes in BMI or agility indicators. Conclusions: Our findings indicate that PAL has the potential to improve students’ physical activity levels in the classroom. However, its effects on physical fitness indicators remained equivocal across evaluated outcomes. PAL should be considered part of a broader school strategy to promote physical activity rather than as a standalone approach. To maximize health benefits, stronger integration of PAL with active recess, active commuting, and structured physical education is recommended. Full article

Graphene has emerged as a revolutionary two-dimensional (2D) nanomaterial, profoundly altering the fields of materials science and mechanical engineering. Driven by its superior mechanical, electrical, and thermal properties, including a Young’s modulus of approximately 1 TPa, high electrical conductivity, and high thermal conductivity, researchers have extensively explored its potential as a reinforcing filler in various composites. The thin composite steel/graphene-reinforced polymer/steel sandwich structure proposed in this study can be applied in the development of precision electromechanical devices due to its advantages of high dimensional stability, high rigidity in a confined space, light weight, and ability to reduce micro-vibrations. This study evaluates the effect of adding graphene to the alkyd-based polymer core layer on the mechanical properties and fracture mechanisms of a sandwich system with a total measured thickness of 0.35 ± 0.01 mm. Through small punch tests (SPTs) with controlled die and punch geometry coefficients, the local load-bearing behavior of the material was investigated in detail. Experimental results show that the dispersion of graphene enhances the flexural stiffness of the core layer, thereby improving the flexural stiffness of the entire structure and increasing the maximum load by 12.6% (from 0.79 ± 0.03 kN to 0.89 ± 0.04 kN). However, this structure exhibits a clear mechanical trade-off as the fracture strain decreases from 1.80 ± 0.08 mm to 1.50 ± 0.09 mm, resulting in a slight 6.1% decrease in approximated energy absorption capacity. Morphological observations at the fracture groove suggest a shift in the fracture mechanism from macroscopic ductile tearing with large plastic deformation to localized abrupt brittle shear plug, accompanied by instantaneous elastic energy release and delamination. These findings indicate that the graphene-reinforced sandwich structure is suitable for thin-film applications requiring high static rigidity, but careful consideration is needed in environments subject to dynamic impact. Full article