Search Results (1,129)

Undergraduate design education faces a structural contradiction characterized by high cognitive load (CL) and relatively low innovation output. Meanwhile, existing generative AI tools predominantly emphasize the generation of visual outcomes, often overlooking the logical guidance mechanisms inherent in design thinking. This study proposes a Dual-Path teaching model integrating critical reconstruction behaviors to examine how AI enhances design thinking. It adopts structured interactions with the DeepSeek large language model, CL theory, and Structural Equation Modeling for analysis. Quantitative results indicate that AI-assisted paths significantly enhance design quality (72.43 vs. 65.60 in traditional paths). This improvement is attributed to a “direct effect + multiple mediators” model: specifically, AI reduced the mediating role of Extraneous Cognitive Load from 0.907 to 0.017, while simultaneously enhancing its investment in Germane Cognitive Load to support deep, innovative thinking. Theoretically, this study is among the first to integrate AI-driven critical reconstruction behaviors (e.g., iteration count, cross-domain terms) into CL theory, validating the “logical chain externalization → load optimization” mechanism in design education contexts. Practically, it provides actionable strategies for the digital transformation of design education, fostering interdisciplinary thinking and advancing a teaching paradigm where low-order cognition is outsourced to reinforce high-order creative thinking. Full article

Hong Kong faces critical construction challenges, including workforce aging, land shortages, and near-capacity waste disposal. Modular Integrated Construction (MiC) offers a promising solution. As Hong Kong has just recently adopted the MiC, quantitative studies that explore the actual performance differences between MiC projects and conventional on-site construction projects in Hong Kong are lacking. To fill this knowledge gap, this study utilizes an extended life cycle assessment–Life Cycle Performance Assessment to conduct on-site investigations and case studies on a MiC pilot residential project and a conventional on-site construction residential project in Hong Kong from multiple dimensions: cost, time, safety, and environment. The assessment indicators include five types of greenhouse gas emissions, cost performance, schedule performance, and safety-level index. This study found that the greenhouse gas emissions of the MiC project during the entire construction period were reduced by approximately 21.60% compared to traditional on-site construction projects. The most significant part of the greenhouse gas emissions of the two methods was the embodied emissions of construction materials, accounting for 83.11% and 87.17%. Compared with the conventional construction project, the factors that actively promote the reduction of greenhouse gas emissions in the MiC project are the embodied greenhouse gas emissions of building materials, the transportation of construction waste, and the resource consumption of equipment. In addition, there is no significant difference in the safety performance index of the two construction methods, but MiC projects have more efficient schedule performance management. Surprisingly, the cost control of MiC projects is not as good as that of conventional construction projects, which differs from existing research results in other regions. Full article

Molecular-mimetic nanocolloids (MMNCs) are promising for advanced materials, yet self-assembly fabrication faces challenges in purity and programmability. We report a total synthesis strategy for surfactant-mimetic nanocolloids (SMNCs), an amphiphilic MMNC subclass. SMNCs consist of a ~5 nm silica nanoparticle head and a bottlebrush polymer tail. Regioselective silica deposition on linear-block-brush polymers via the modified sol–gel method enables precise control. This strategy is versatile and can be adapted to synthesize other MMNCs with different components. It offers a more controlled alternative to self-assembly methods, advancing MMNC synthesis and enabling their broader use in emerging technologies. Full article

Hydraulic actions may compromise dam foundation stability. Helical anchors have been used in dam foundation reinforcement projects because of the advantages of large uplift and compression bearing capacity, fast installation, and convenient recovery. However, the research on the anchor plate, which plays a key role in the bearing performance of helical anchors, is insufficient at present. Based on the finite element model of helical anchor, this study reveals the failure mode and influencing factors of the anchor plate and establishes the theoretical model of deformation calculation. The results showed that the helical anchor plate had obvious bending deformation when the dam foundation reinforced with a helical anchor reached large deformation. The helical anchor plate can be simplified to a flat circular disk. The stress distribution of the closed flat disk and the open flat disk was consistent with that of the helical disk. The maximum deformation of the closed flat disk was slightly smaller than that of the helical disk (less than 6%), and the deformation of the open flat disk was consistent with that of the helical disk. The results fill the blank of the design basis of helical anchor plate and provide a reference basis for the engineering design. Full article

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article

Topographic slope is a key parameter for characterizing landscape geomorphology. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) offers high-resolution along-track slopes based on the ground profiles generated by dense signal photons. However, the across-track slopes are typically derived using the ground photon geolocations from the weak-beam and strong-beam pair, limiting the retrieval accuracy and losing valid results over rugged terrains. The goal of this study is to propose a new method to derive the across-track slope merely using single-track photon data of a strong beam based on the theoretical formula of the received signal pulse width. Based on the ICESat-2 photon data over the Walker Lake area, the specific purposes are to (1) extract the along-track slope and surface roughness from the signal photon data on the ground; (2) generate an elevation frequency histogram (EFH) and calculate its root mean square (RMS) width; and (3) derive the across-track slope from the RMS width of the EFH and evaluate the retrieval accuracy against the across-track slope from the ICESat-2 product and plane fitting method. The results show that the mean absolute error (MAE) obtained by our method is 11.45°, which is comparable to the ICESat-2 method (11.61°) and the plane fitting method (12.51°). Our method produces the least invalid data proportion of ~2.5%, significantly outperforming both the plane fitting method (10.29%) and the ICESat-2 method (32.32%). Specifically, when the reference across-track slope exceeds 30°, our method can consistently yield the optimal across-track slopes, where the absolute median, inter quartile range, and whisker range of the across-track slope residuals have reductions greater than 4.44°, 1.31°, and 0.10°, respectively. Overall, our method is well-suited for the across-track slope estimation over rugged terrains and can provide higher-precision, higher-resolution, and more valid across-track slopes. Full article

This study addresses the challenges of manual measurement bias and low robustness in detecting small, occluded targets in complex marine environments during real-time onboard sorting of Portunus trituberculatus. We propose YOLO-DFAM, an enhanced YOLOv11n-based model that replaces the global average pooling in the Focal Modulation module with a spatial–channel dual-attention mechanism and incorporates the ASF-YOLO cross-scale fusion strategy to improve feature representation across varying target sizes. These enhancements significantly boost detection, achieving an mAP@50 of 98.0% and precision of 94.6%, outperforming RetinaNet-CSL and Rotated Faster R-CNN by up to 6.3% while maintaining real-time inference at 180.3 FPS with only 7.2 GFLOPs. Unlike prior static-scene approaches, our unified framework integrates attention-guided detection, scale-adaptive tracking, and lightweight weight estimation for dynamic marine conditions. A ByteTrack-based tracking module with dynamic scale calibration, EMA filtering, and optical flow compensation ensures stable multi-frame tracking. Additionally, a region-specific allometric weight estimation model (R² = 0.9856) reduces dimensional errors by 85.7% and maintains prediction errors below 4.7% using only 12 spline-interpolated calibration sets. YOLO-DFAM provides an accurate, efficient solution for intelligent onboard fishery monitoring. Full article

Coxsackievirus B3 (CV-B3) infection causes inflammatory conditions such as viral myocarditis and meningitis, and incidence rates are rising annually. While children are more likely to be affected by severe manifestations, the molecular basis of this age-dependent susceptibility is poorly understood. In this study, we used young Balb/c mice at three developmental stages (7-, 14-, and 30-day-old mice) to investigate CV-B3 pathogenesis. Our findings revealed that 7-day-old mice exhibited substantial infection susceptibility and pathological severity compared to older mice. Critically, an age-dependent analysis showed a progressive decline in the expression of CV-B3-binding Coxsackievirus and Adenovirus Receptor (CAR) splice variants (CAR1 and CAR2) at both the transcriptional and translational levels as the mice matured from 7 to 30 days. These receptor isoforms demonstrated a direct correlation with viral replication efficiency in younger hosts. Concurrently, aging was associated with a rise in non-binding CAR variants (CAR3 and CAR4). During CV-B3 infection, the abundance of CAR1/CAR2 in young mice facilitated accelerated viral proliferation, coupled with the hyperactivation of the NLRP3 inflammasome and the expansion of IL-17-producing γδT cells (γδT17 cells). This cascade triggered excessive production of proinflammatory cytokines (IL-1β, IL-18, and IL-17), culminating in pronounced inflammatory infiltrates within cardiac and cerebral tissues. These findings establish NLRP3 inflammasome dysregulation as a critical determinant of CV-B3-induced tissue damage and provide novel insights into the heightened susceptibility to CV-B infection during early life and its associated severe disease rates. Full article

To develop solutions to the frequency instability and failure of silicon micromechanical resonant accelerometers, the state characteristics of micromechanical resonant accelerometers are investigated under temperature and vibration stresses. Through theoretical analysis and finite element simulation, the following is found: the Young’s modulus of silicon varies with temperature, causing a resonance frequency shift of −1.364 Hz/°C; the residual stress of temperature change affects the resonance frequency shift of the microstructure, causing it to be 5.43 Hz/MPa (tensile stress) and −5.25 Hz/MPa (compressive stress); thermal expansion triggers the failure of the bonding wire, and, in the range of 10 °C to 150 °C, the peak stress of the electrode/lead bond area increases from 83.2/85.6 MPa to 1.08/1.28 GPa. The failure mode under vibration stress is resonance structure fracture and interlayer peeling. An isolation frame design is proposed for the sensitive part of the microstructure, which reduces the frequency effects by 34% (tensile stress) and 15% (compressive stress) under temperature-variable residual stresses and the maximum value of the structural root mean square stresses by 69.7% (X-direction), 63.6% (Y-direction), and 71.3% (Z-direction) under vibrational stresses. Full article

In high-frequency surface wave radar (HFSWR) systems, the retrieval of the directional wave spectrum has remained challenging, especially in the case of echoes from long ranges with a low signal-to-noise ratio (SNR). Therefore, a quadratic programming algorithm based on the regularization technique is proposed with an empirical criterion for estimating the optimal regularization parameter, which minimizes the effect of noise to obtain more accurate inversion results. The reliability of the inversion method is preliminarily verified using simulated Doppler spectra under different wind speeds, wind directions, and SNRs. The directional wave spectra inverted from a radar network with two multiple-input multiple-output (MIMO) systems are basically consistent with those from the ERA5 data, while there is a limitation for the very concentrated directional distribution due to the truncated second order in the Fourier series. Further, in the field experiment during a storm that lasted three days, the wave parameters are calculated from the inverted directional spectra and compared with the ERA5 data. The results are shown to be in reasonable agreement at four typical locations in the core detection area. In addition, reasonable performance is also obtained under the condition of low SNRs, which further verifies the effectiveness of the proposed inversion algorithm. Full article

Household appliances constitute the second largest source of residential energy consumption in China, accounting for over 20% of the total and exhibiting a steady growth trend. Despite their substantial impact on energy demand and carbon emissions, a comprehensive analysis of the current status and future trends of household appliances in China is still lacking. This study employs the Long-Range Energy Alternatives Planning (LEAP) system to model energy consumption and carbon emissions for five major household appliances (air conditioners, refrigerators, washing machines, TVs, and water heaters) from 2022 to 2052. Three scenarios were analyzed: a Reference (REF) scenario (current trends), an Existing Policy Option (EPO) scenario (current energy-saving measures), and a Further Strengthening (FUR) scenario (enhanced efficiency measures). Key results show that by 2052, the EPO scenario achieves cumulative savings of 1074.8 billion kWh and reduces emissions by 580.7 million metric tons of CO₂ equivalent compared to REF. The FUR scenario yields substantially greater benefits, demonstrating the significant potential of strengthened policies. This analysis underscores the critical role of improving appliance energy efficiency and provides vital insights for policymakers and stakeholders aiming to reduce residential sector emissions. Full article

Objectives: There is a scarcity of studies on multisite infections (MSIs) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP). The primary objectives of this research were to determine the clinical characteristics of CRKP MSI, and the risk factors of infection and mortality. Methods: Patients with a CRKP bloodstream infection (BSI) were enrolled retrospectively between January 2017 and December 2021 in Xijing Hospital, China. The risk factors for CRKP MSI and mortality were evaluated. The demographic data, clinical and microbiological characteristics, therapy and outcomes were analyzed. Results: Among 101 patients, 74.3% (75/101) had a diagnosis of CRKP MSI, while 25.7% (26/101) of CRKP non-MSI. The overall case fatality rate was 42.6% (43/101). Multivariate analysis indicated that previous surgery (OR 3.971, 95% CI 1.504–10.480, p = 0.005) and ICU admission (OR 3.322, 95% CI 1.252–8.816, p = 0.016) were independent risk factors for CRKP MSI. ICU admission (OR 4.765, 95% CI 1.192–19.054, p = 0.027), a Pitt bacteremia score (PBS) > 4 (OR 3.820, 95% CI 1.218–11.983, p = 0.022) and thrombocytopenia (OR 8.650, 95% CI 2.573–29.007, p < 0.001) were independent risk factors for mortality due to CRKP MSI. Conclusions: Our findings confirmed that CRKP MSIs were associated with poorer outcomes. To improve prognosis, early screening of individuals at the highest risk is vital. Full article

In this investigation, a hierarchical FeCo-layered double hydroxide (FeCo-LDH) electrochemical membrane material was prepared by a simple in situ hydrothermal method. The prepared material formed a 3D honeycomb-structured FeCo-LDH-modified carbon felt (FeCo-LDH/CF) catalytic layer with uniform open pores on a CF substrate with excellent catalytic activity and was served as the cathode in a flow-through electro-Fenton (FTEF) reactor. The electrocatalyst demonstrated excellent treatment performance (99%) in phenol simulated wastewater (30 mg L⁻¹) under the optimized operating conditions (applied voltage = 3.5 V, pH = 6, influent flow rate = 15 mL min⁻¹) of the FTEF system. The high removal rate could be attributed to (i) the excellent electrocatalytic oxidation performance and low interfacial charge transfer resistance of the FeCo-LDH/CF electrode as the cathode, (ii) the ability of the synthesized FeCo-LDH to effectively promote the conversion of H₂O₂ to •OH under certain conditions, and (iii) the flow-through system improving the mass transfer efficiency. In addition, the degradation process of pollutants within the FTEF system was additionally illustrated by the •OH dominant ROS pathway based on free radical burst experiments and electron paramagnetic resonance tests. This study may provide new insights to explore reaction mechanisms in FTEF systems. Full article

Target detection is the key technology of the apple-picking robot. To overcome the limitations of existing apple target detection methods, including low recognition accuracy of multi-species apples in complex orchard environments and a complex network architecture that occupies large memory, a lightweight apple recognition model based on the improved YOLO11 model was proposed, named YOLO-WAS model. The model aims to achieve efficient and accurate automatic multi-species apple identification while reducing computational resource consumption and facilitating real-time applications on low-power devices. First, the study constructed a high-quality multi-species apple dataset and improved the complexity and diversity of the dataset through various data enhancement techniques. The YOLO-WAS model replaced the ordinary convolution module of YOLO11 with the Adown module proposed in YOLOv9, the backbone C3K2 module combined with Wavelet Transform Convolution (WTConv), and the spatial and channel synergistic attention module Self-Calibrated Spatial Attention (SCSA) combined with the C2PSA attention mechanism to form the C2PSA_SCSA module was also introduced. Through these improvements, the model not only ensured lightweight but also significantly improved performance. Experimental results show that the proposed YOLO-WAS model achieves a precision (P) of 0.958, a recall (R) of 0.921, and mean average precision at IoU threshold of 0.5 (mAP@50) of 0.970 and mean average precision from IoU threshold of 0.5 to 0.95 with step 0.05 (mAP@50:95) of 0.835. Compared to the baseline model, the YOLO-WAS exhibits reduced computational complexity, with the number of parameters and floating-point operations decreased by 22.8% and 20.6%, respectively. These results demonstrate that the model performs competitively in apple detection tasks and holds potential to meet real-time detection requirements in resource-constrained environments, thereby contributing to the advancement of automated orchard management. Full article

This study systematically investigates the impact of Cu²⁺ doping on the structural, magnetic, and magnetocaloric properties of Cu_xCo_1−xCr₂O₄ nanoparticles synthesized via a solution combustion method. Cu incorporation up to x = 20% induces a progressive structural transformation from a cubic spinel to a trigonal corundum phase, as confirmed by X-ray diffraction and Raman spectroscopy. The doping process also leads to increased particle size, improved crystallinity, and reduced agglomeration. Magnetic measurements reveal a transition from hard to soft ferrimagnetic behavior with increasing Cu content, accompanied by a notable rise in the Curie temperature from 97.7 K (x = 0) to 140.2 K (x = 20%). The magnetocaloric effect (MCE) is significantly enhanced at higher doping levels, with the 20% Cu-doped sample exhibiting a maximum magnetic entropy change (−ΔS_M) of 2.015 J/kg-K and a relative cooling power (RCP) of 58.87 J/kg under a 60 kOe field. Arrott plot analysis confirms that the magnetic phase transitions remain second-order in nature across all compositions. These results demonstrate that Cu doping is an effective strategy for tuning the magnetostructural response of CoCr₂O₄ nanoparticles, making them promising candidates for low-temperature magnetic refrigeration applications. Full article