Search Results (43,320)

To address the challenges in UAV remote sensing imagery, such as small object size, dense occlusion and complex background interference, this paper proposes an enhanced small object detection algorithm based on an improved YOLOv13 model for drone applications in complex weather environments. First, an enhanced feature fusion attention network (EFFA-Net) is designed in the preprocessing stage to reduce image degradation and suppress the interference caused by smoke and haze. Then, in the backbone, a swish-gated convolution (SwiGLUConv) module is designed to adaptively expand the receptive field and enhance multi-scale feature extraction, which strengthens the representation of small targets while maintaining efficient computation. Furthermore, a locally enhanced multi-scale context fusion (LF-MSCF) module is integrated into the feature fusion neck of YOLO, combining multi-head self-attention, channel attention, and spatial attention to suppress background noise and redundant responses, thereby improving detection accuracy. Extensive experiments on the VisDrone-DET2019 dataset, UAVDT dataset, and HazyDet dataset demonstrate that the proposed algorithm outperforms other mainstream methods, showcasing excellent detection accuracy and robustness in complex UAV aerial scenarios. Full article

Accurate prediction of hard disk drive (HDD) health states is critical for enabling proactive data maintenance and ensuring data reliability in large-scale data centers. However, conventional models often suffer from semantic entanglement among heterogeneous SMART attributes and from the masking of incipient failure signatures by stochastic noise. To address these challenges, we propose SDGR-Net, a spatiotemporally decoupled learning framework designed to model the complex degradation dynamics of HDDs. SDGR-Net introduces three synergistic innovations: (1) a spatiotemporally decoupled dual-branch encoder that disentangles longitudinal temporal evolution from cross-variable correlations via parameter-isolated branches, thereby reducing representational interference; (2) a parsimonious dual-view temporal extraction mechanism that captures early-stage anomalies through forward–reverse sequence concatenation, enabling high-fidelity preservation of non-stationary pre-failure patterns; and (3) a cross-branch dynamic gated residual fusion module that functions as an adaptive information bottleneck to emphasize failure-critical features while suppressing redundant noise. Extensive experiments conducted on three heterogeneous HDD datasets, ST4000DM000, HUH721212ALN604, and MG07ACA14TA, demonstrate that SDGR-Net consistently outperforms six state-of-the-art baselines. In particular, SDGR-Net achieves a peak fault detection rate (FDR) of 0.9898 and a 69.6% relative reduction in false alarm rate (FAR) under high-reliability operating conditions. These results, corroborated by comprehensive ablation studies, indicate that SDGR-Net effectively balances detection sensitivity and operational robustness, offering a practical solution for intelligent HDD health monitoring. Full article

The dynamics of power converters are highly influenced by uncertainties, nonlinearities, and external disturbances. Thus, high-performance, extremely resilient, and robust control strategies are necessary for their control. For the robust operation of power converters, this article presents an adaptive and finite-time convergent active disturbance rejection control (ADRC) framework inspired by Professor Han’s seminal paper. Based on ADRC’s philosophy, this article proposes a control scheme that integrates adaptiveness and finite-time convergence in both the extended state observer and the control law. The proposed framework ensures quick disturbance estimation and its rejection, thus ensuring that the required response is tracked successfully. The controllers for different power converters, such as buck converters, boost converters, and single-phase inverters, are designed to ensure the desired dynamics, including low settling times and zero-percent overshoots. The controllers are implemented in the discrete-time domain using forward differences. Simscape simulation experiments on buck converters, boost converters, and single-phase inverters demonstrate that the responses are achieved with finite settling time with no overshoots. Thus, such control strategies are highly crucial for mission-critical power applications. Full article

To investigate the deterioration law of the mechanical properties of PVA-fiber-reinforced rubber concrete under the combined action of high-temperature and salt erosion, physical index tests, dynamic mechanical property experiments, and microstructural morphology observations were carried out on specimens subjected to different temperatures (ambient temperature, 100 °C, 300 °C) and various solution attacks (water, 5% NaCl, 5% Na₂SO₄, and 5% NaCl + 5% Na₂SO₄ mixture). The results show that, after exposure to 300 °C, the PVA fibers melt and the rubber pyrolyzes, since this temperature exceeds their melting points. A residual pore network is formed inside the matrix, and the damage degree of ultrasonic pulse velocity is about 2.3 times that of the 100 °C group. Although salt solution and its crystallization products can physically fill the pores and cause a partial recovery of pulse velocity, this change is mainly due to the alteration of the pore medium and does not represent a substantial restoration of the microstructure. The effects of different salt solutions on dynamic mechanical properties vary significantly: Sulfate erosion improves the dynamic performance significantly at ambient temperature by forming gypsum and ettringite to fill pores, but this strengthening effect disappears after 300 °C. Sodium chloride attack generates Friedel’s salt and consumes C₃A, leading to general strength deterioration. In composite salt erosion, the competitive and synergistic effects of Cl⁻ and SO₄²⁻ destabilize erosion products and weaken interfacial bonding, resulting in consistent decreases in dynamic compressive strength and elastic modulus under all temperatures and impact pressures. The strength reduction reaches 66.2% after 300 °C. Microscopic analysis confirms that composite salt erosion leads to the dissolution of ettringite and loose structure, which verifies the synergistic deterioration law of macroscopic properties. This study systematically reveals the damage evolution mechanism of PVA-fiber-reinforced rubber concrete under the coupled action of high-temperature and salt erosion, and provides a theoretical basis for the dynamic bearing capacity evaluation and durability design of concrete structures in such coupled environments. Full article

The integration of appropriate tillage practices with straw returning can effectively mitigate soil degradation in Northeast China. However, limited research has explored the impacts of different tillage practices combined with varying straw incorporation depths on the structure and diversity of soil microbial communities. In 2016, a field experiment was initiated using a two-factor split-plot design, featuring six treatments: two tillage depths of 10 cm (D10) and 30 cm (D30) combined with three straw management practices—straw mixing incorporation (SM), straw deep burial (SB), and straw removal (SR). Soil samples collected in 2019 were analyzed for multiple soil properties and microbial indices. Results indicated that both straw returning and tillage depth significantly influenced soil organic carbon (SOC), soil total nitrogen (STN), total phosphorus (TP), and total potassium (TK), with the D30 treatment combined with straw returning optimizing soil nutrient contents most effectively. Under straw returning, D10 significantly increased urease activity in the 0–10 cm soil layer, whereas D30 enhanced this enzyme activity in the 10–30 cm soil layer, while β-glucosidase activity was less responsive to tillage depth. For the D10 treatment with straw returning, acid phosphatase activity was markedly higher than that in the straw removal treatment, whereas N-acetyl-β-D-glucosaminidase activity exhibited the opposite trend. Straw-returning methods had no significant effects on the bacterial and fungal Chao1 indices, while the Shannon index was positively correlated with key soil properties. Redundancy analysis (RDA) of microbial community composition at the phylum level and soil environmental factors revealed that soil nutrients in the 0–10 cm soil layer were positively correlated with Actinobacteriota, Ascomycota, and Basidiomycota, whereas the explanatory power of soil nutrients for microbial community variation decreased in the 10–30 cm soil layer. Our results highlight that tillage depth and straw returning can regulate soil microbial community composition and enhance soil nutrient cycling, thereby providing a theoretical basis for optimizing the combined application mode of tillage and straw-returning practices in Northeast China. Full article

This study investigated the enhancement mechanisms and optimal mix proportion of basalt fiber (BF) in concrete for ship lock galleries. It focused on improving crack resistance, freeze–thaw resistance, impermeability, and abrasion–erosion resistance under complex hydraulic environments. Single-factor tests first determined the reasonable parameter ranges, which were subsequently used in a three-factor, four-level orthogonal experiment to analyze the effects of the water-to-binder ratio, fiber content, and fiber length on concrete’s mechanical properties. Range analysis of the orthogonal experiment indicated that the water-to-binder ratio was the most dominant factor (R = 57.4), followed by fiber content. Based on this, further durability tests were conducted, including ring restraint cracking, impermeability, freeze–thaw resistance, and abrasion–erosion resistance. Multi-objective optimization was performed using full factorial experiments and a comprehensive performance evaluation system. The final optimal mix proportion was determined as: a water-to-binder ratio of 0.35, a fiber content of 0.2%, and a fiber length of 12 mm. With this mix, the concrete’s ring cracking time was extended by 69.9%, the relative dynamic elastic modulus retention reached 73.0% after 100 freeze–thaw cycles, the relative permeability coefficient was 1.04 × 10⁻⁶ cm/h, and the abrasion–erosion resistance strength increased to 7.05 h·m²/kg, which achieved an optimal synergy among the mechanical properties, key durability indicators, and their workability. Mechanism analysis revealed that BF formed a three-dimensional, randomly distributed fiber network that comprehensively enhanced concrete performance through multi-scale mechanisms, including bridging, pore refinement, and energy dissipation. This research has provided systematic experimental evidence and mix proportion support for the durability design and engineering application of BF concrete in ship lock galleries. Full article

Challenge-based learning (CBL) is a student-centered approach engaging learners in complex, open-ended problems. While such openness can foster deeper learning and creativity, it also demands high self-direction. Teachers must therefore provide sufficient scaffolding without undermining CBL’s authenticity. This study examines how secondary education teachers design and enact scaffolding in sustainability-oriented CBL projects, and how students experience this support. A multiple-case study of three projects distinguished soft scaffolding (adaptive, just-in-time support) from hard scaffolding (predefined tools and structures). Data included teacher interviews (n = 3), student focus groups (n = 18), and classroom observations. Findings showed the scaffolding type and function depended on project open-endedness, teacher readiness, and alignment with project focus. In the most open-ended project, the teacher mainly used soft scaffolding to guide thinking and decision-making, whereas more structured projects relied on hard scaffolds for procedural support. Students’ experiences varied: some thrived under autonomy, developing ownership and engagement, while others needed more explicit guidance. These results suggest that scaffolds should align with project goals, be explicit in their contribution to progress, match students’ readiness for self-directed learning, be enacted by teachers comfortable in a coaching role, and include affective support to help students manage frustration and uncertainty. Full article

This study examines the relationships between technology readiness, Augmented Reality Consumer Experience Scale (ARCES), and purchase intention in digital retail environments. Unlike prior augmented reality studies that primarily focus on technology adoption or isolated experiential effects, this study integrates technology readiness, multidimensional AR-based consumer experience, and purchase intention within a single correlational framework. Data were collected from 385 university students using a correlational research design. The factor structure of the adapted measurement scale was assessed through exploratory and confirmatory factor analyses, and the relationships among the variables were examined using correlation analysis. The findings indicate significant positive relationships: technology readiness is positively associated with AR-based consumer experience, and AR-based consumer experience is positively associated with purchase intention. From a sustainability-oriented perspective, these findings suggest that AR-enabled retail experiences may support more informed and reflective pre-purchase evaluation processes in digital environments. Full article

Sonchus oleraceus L., a member of the Asteraceae family native to Eurasia, is a herbaceous plant whose young stems and leaves are consumed globally as a medicinal and edible wild vegetable; it is rich in flavonoids and exhibits various pharmacological activities, including anti-inflammatory and anti-tumor effects. This study optimized the extraction process of flavonoids from Xinjiang S. oleraceus using response surface methodology and evaluated the anti-inflammatory activity of luteoloside in vitro. Based on single-factor experiments and Box–Behnken design, the effects of ethanol concentration, extraction time, solid-to-liquid ratio, and extraction temperature on flavonoid yield were investigated. The optimal extraction conditions were determined as ethanol concentration 62%, extraction time 30 min, solid-to-liquid ratio 1:91 g/mL, and extraction temperature 64 °C, with a flavonoid yield of 21.64 mg/g. After purification via polyamide column chromatography, the luteoloside content was determined by HPLC to be 44.06 μg/g. Cytotoxicity assays revealed that a luteoloside concentration of 100 μmol/L reduced the viability of Oryctolagus cuniculus colon epithelial cells to approximately 80%. ELISA results demonstrated that luteoloside significantly inhibited the release of pro-inflammatory factors, including TNF-α, while promoting the expression of the anti-inflammatory factor IL-10. These findings indicate that luteoloside effectively alleviates LPS-induced cellular inflammation. Full article

Lead cake forms from dust as a result of the gas cleaning process during copper smelting. The objective of this study was to develop equipment and technology for a continuous hydrometallurgical method for extracting osmium from the lead cake. In this method, leaching is carried out using an aqueous solution of hydrogen peroxide and sulfuric acid. During the leaching, rhenium is converted into an acidic solution from which rhenium can be easily extracted into a marketable product. Osmium is predominantly converted into a solution, the processing of which, including the extraction of osmium into a marketable product, will be published later. A unit for leaching osmium–rhenium-containing cake with continuous loading for leaching, continuous feeding of leaching solutions, and continuous discharge of the leaching slurry was created. Using the simplex experimental design method, the dependence of osmium recovery on the consumption rates of hydrogen peroxide and sulfuric acid and the leaching duration was studied. Near-optimal leaching conditions were as follows: 68–70 mL of 30% hydrogen peroxide and 7 mL of concentrated sulfuric acid per 100 g of cake, 55 min of leaching, and a specific column throughput of 100 g of cake per 55 min. Nine experiments achieved 96.5% osmium recovery. Full article

Acoustic microactuation technology has emerged as an effective approach for fabrication of micro- and nanoscale objects, enabling precise processing and shaping control of microscale materials by efficiently transmitting ultrasonic vibration energy and focusing energy locally. In this work, the proposed platform is regarded as an acoustically driven micromachine, in which ultrasonic excitation acts as the primary microactuation mechanism. Micrometer-scale copper wires are widely used in microelectronics and precision manufacturing. However, their small dimensions and low rigidity make fixation and forming particularly challenging. To achieve controllable forming of fine copper wires, this study introduces an ultrasonic vibration energy-focusing principle and investigates an ultrasonic post-processing method tailored for such materials, with the aim of enhancing processing stability and forming accuracy. An ultrasonic processing experimental platform for copper wires was established, and multiple micro-tool designs—including glass fiber, 304 stainless steel wire with support, and elastic hard 304 stainless steel—were evaluated. Single-point and continuous processing experiments were conducted by varying micro-tool materials and support configurations, and the influence of feed speed on processing width and depth was systematically analyzed. The results indicate that a hard 304 stainless steel micro-tool supported by a hard plastic ring provides the best overall performance. Feed speed has a significant effect on processing depth, with a maximum average depth of approximately 0.95 μm achieved at a feed speed of 1 mm/min. These findings demonstrate the feasibility of ultrasonic processing for the effective forming of fine copper wires and confirm that appropriate micro-tool design and feed speed are critical for achieving stable and reliable processing results. The proposed system employs an ultrasonically actuated micro-tool to perform post-processing on micrometer-scale copper wires. The ultrasonic vibration serves as a microactuation mechanism that enhances local deformation and material response during micro-machining. Full article

This study explores how demystifying Earth Observation (EO) through co-creation pathways and local language can enhance flood resilience and environmental governance in African informal cities. Using case studies from Maiduguri and Hadejia, Nigeria, the research employed a transdisciplinary mixed-methods design combining rapid evidence assessment, surveys, participatory workshops (n = 50 stakeholders) integrating simplified Sentinel-1/2 demonstrations, indigenous knowledge mapping, and pre-/post-engagement surveys on EO familiarity. Non-expert participants were trained to interpret satellite data using local language, linking distant teleconnections with local flood experiences. The findings revealed significant gains in EO literacy and improvements in interpretive confidence, gender-inclusive participation, and policy engagement. Localizing the curriculum enabled participants to translate technical EO concepts into locally meaningful narratives, fostering cognitive empowerment and practical application in flood preparedness and advocacy. The study demonstrates that data democratization is not only a matter of open access but also of open understanding. It advances a conceptual model linking Demystification, Literacy, Empowerment, Co-Production and Resilience, positioning EO as a social technology that bridges scientific and indigenous knowledge systems. The findings contribute to debates on decolonizing environmental science and propose a potential participatory framework for integrating EO into community-based adaptation, legal accountability, and policy reform across Africa’s rapidly urbanizing landscapes. Full article

The present study investigates simple cubic lattice structures fabricated through an FDM-based three-dimensional (3D) printing method using wood–polylactic acid (wood–PLA) bio-composite filament and develops a data-driven framework to predict their mechanical response. The design of experiments (DOE) was developed using a response surface methodology (RSM) based on a central composite design (CCD) that was implemented in Design-Expert software (Version 13). During fabrication, four different manufacturing parameters—the layer height, the printing speed, the nozzle temperature, and the infill density—were considered. The compressive strength and compressive modulus were evaluated experimentally, and the corresponding stress–strain responses were examined. The results reveal that the layer height is the most influential parameter, where lower layer heights (0.06–0.1 mm) significantly improve both the compressive strength and the modulus due to enhanced interlayer bonding and reduced void formation. The printing speed and the nozzle temperature also play critical roles, where lower printing speeds (≈40 mm/s) and moderate nozzle temperatures (≈195–205 °C) promote more uniform material deposition and improved interlayer bonding, while higher speeds (≥60 mm/s) and excessive temperatures (≈225 °C) lead to reduced bonding quality and a deterioration in mechanical performance. In contrast, the infill density exhibited a non-monotonic influence, where intermediate levels (around 70%) provided an improved performance under combinations of the low layer height (≈0.1 mm), the low printing speed (≈40 mm/s), and the moderate nozzle temperature (≈195–215 °C), suggesting an interaction-driven effect rather than a purely density-dependent trend. To complement the experimental findings, a machine learning model based on eXtreme Gradient Boosting (XGBoost) was developed using 12,000 data points that were derived from stress–strain curves. The model successfully predicted continuous mechanical responses with errors in the range of 2–8% for unseen specimens, suggesting its capability to capture the relationship between printing parameters and mechanical behavior within the studied design space. Overall, the study highlights that the mechanical properties of wood–PLA lattice structures can be effectively tailored by choosing an appropriate printing parameter control and demonstrates the feasibility of using machine learning to estimate mechanical performance without additional physical testing within the defined parameter domain. Full article

The rapid global wild boar (Sus scrofa) population growth, coupled with increasing agricultural crop damage and disease transmission, suggests that current management and control strategies remain inadequate. Therefore, an international systematic review using the Web of Science database (WoS; Clarivate Analytics, Philadepphia, PA, USA), including a quantitative synthesis (119 studies up to 11 November 2025, containing 181 experiments) of population reduction methods was conducted, with an emphasis on evaluating their effectiveness, selectivity, and animal welfare aspects relating to wild boar and feral pigs. The results demonstrate a significant increase in research interest for population control methods in recent years. The highest average effectiveness was observed for aerial shooting (56.2% of the population per month), followed by poison baiting (27.6%) and trapping (6.0%). Aerial shooting appeared highly selective in the reviewed contexts; however, together with poison baiting, it is generally not permitted under current European conditions. Trapping (6.0%) and individual hunting (3.9%) offer moderate effectiveness but are highly context-dependent. From a welfare perspective, the analysis indicated that no significant difference in effectiveness was detected between studies that included welfare or stress assessment and those that did not, indicating that consideration of animal welfare does not reduce control efficiency. The study concluded that the analysis did not identify a single universally applicable solution that combines animal welfare considerations with high effectiveness, highlighting a significant research gap. This underscores the urgent need for an effective and publicly acceptable method of reducing wild boar populations, or for the development of strategies that appropriately integrate multiple approaches. However, the interpretation of results is limited by heterogeneity in study design and variability in reported data. Full article

Traditional Post-Occupancy Evaluation (POE) is static and incompatible with dynamic systems like Digital Twins, creating a digital gap in managing health-oriented urban environments, especially in Urban Underground Spaces (UUS). This paper bridges this gap with a deep learning framework that automates the continuous prediction of human physiological arousal. We created a novel multimodal dataset from in situ experiments, synchronizing first-person video, environmental data, and Galvanic Skin Response (GSR) as a real-time physiological arousal proxy. Our dual-branch spatial–temporal model fuses these data streams to predict GSR with high accuracy (Pearson’s r = 0.72), effectively mapping objective environmental inputs to continuous human physiological dynamics. This framework provides an automated, human-centric analysis engine for urban planning, design validation, and real-time building management. It establishes a foundational ‘human dynamics layer’ for urban Digital Twins, evolving them into predictive tools for simulating human-environment interactions and embedding physiological perception into intelligent urban systems. Full article