Search Results (471)

To address the environmental risks associated with large-scale stockpiling of red mud (RM) and coal gangue (CG) and the demand for their high-value utilization, this study proposes a ternary concrete system incorporating RM, fly ash (FA), and CG aggregate. The effects of RM content, FA content, CG aggregate replacement rate, and water-to-binder ratio on workability, mechanical properties, and frost resistance durability were systematically investigated through orthogonal experiments, with the underlying micro-mechanisms revealed by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results indicate that workability is predominantly governed by the water-to-binder ratio, while the micro-aggregate effect of FA significantly enhances fluidity. Mechanical properties are most significantly influenced by RM content; under a 20% CG aggregate replacement rate and a 0.45 water-to-binder ratio, an optimal compressive strength was achieved with a low content combination of RM and FA. Frost resistance deteriorated markedly with increasing RM and FA content, with the high-content group approaching the failure threshold after only 25 freeze–thaw cycles, occurring 50 and 125 cycles earlier than the medium- and low-content groups, respectively. Macro-micro results indicate a synergistic threshold at 20% red mud and 45% fly ash, yielding a compressive strength of 24.96 MPa. This value exceeds the 24.87 MPa of the 10% red mud + 45% fly ash group and the 21.90 MPa of the 10% red mud + 55% fly ash group. Microstructurally, this group also exhibits superior C-S-H gel uniformity and narrower crack widths compared to the others. Excessive incorporation of red mud and fly ash leads to agglomeration of unhydrated particles and increased porosity, aligning with the observed macroscopic strength degradation. This research identifies and quantifies the synergistic threshold governing RFCTSWC performance evolution, providing theoretical support for engineering applications of solid waste concrete. Full article

In order to meet the high-precision location requirements of the corneal Placido ring edge in corneal topographic reconstruction, this paper proposes a sub-pixel edge detection algorithm based on multi-scale and multi-position enhanced Mexican Hat Wavelet Transform and improved Zernike moment. Firstly, the image undergoes preliminary processing using a multi-scale and multi-position enhanced Mexican Hat Wavelet Transform function. Subsequently, the preliminary edge information extracted is relocated based on the Zernike moments of a 9 × 9 template. Finally, two improved adaptive edge threshold algorithms are employed to determine the actual sub-pixel edge points of the image, thereby realizing sub-pixel edge detection for corneal Placido ring images. Through comparison and analysis of edge extraction results from real human eye images obtained using the algorithm proposed in this paper and those from other existing algorithms, it is observed that the average sub-pixel edge error of other algorithms is 0.286 pixels, whereas the proposed algorithm achieves an average error of only 0.094 pixels. Furthermore, the proposed algorithm demonstrates strong robustness against noise. Full article

In the practical physical structure of the electromagnetic inerter–spring–damper (EM–ISD) suspension, parasitic damping inevitably coexists with the mechanical inerter effect. To investigate the intrinsic influence of this parasitic effect on the suspension system’s performance, this study first establishes a quarter-vehicle dynamic model that incorporates parasitic damping, based on the actual configuration of the EM–ISD suspension. Subsequently, the particle swarm optimization (PSO) algorithm is employed to optimize the key suspension parameters, with the objective of enhancing its comprehensive performance. The optimized parameters are then utilized to systematically analyze the dynamic characteristics of the suspension under the influence of parasitic damping. The results indicate that, compared to an ideal model that neglects parasitic damping, an increase in the parasitic damping coefficient leads to a deterioration in the root mean square (RMS) value of body acceleration, while concurrently reducing the RMS values of the suspension working space and dynamic tire load. However, by incorporating parasitic damping into the design considerations during the optimization phase, its adverse impact on ride comfort can be effectively mitigated. Compared with a traditional passive suspension, the optimized EM–ISD suspension, which accounts for parasitic damping, demonstrates superior performance. Specifically, the RMS values of body acceleration and suspension working space are significantly reduced by 11.1% and 17.6%, respectively, thereby effectively improving the vehicle’s ride comfort and handling stability. Full article

As global climate change accelerates, the urban heat island (UHI) phenomenon has become increasingly pronounced, posing significant challenges to urban energy balance, atmospheric processes, and public health. This study used the Weather Research and Forecasting (WRF) model to dynamically downscale two CMIP6 scenarios—moderate forcing (SSP245) and high forcing (SSP585)—focusing on Zhengzhou, a rapidly urbanizing city in central China. High-resolution simulations captured fine-scale intra-urban temperature patterns and analyze the spatial and seasonal variations in UHI intensity in 2030 and 2060. The results demonstrated significant seasonal variations in UHI effects in Zhengzhou for both 2030 and 2060 under SSP245 and SSP585 scenarios, with the most pronounced warming in summer. Notably, under the SSP245 scenario, elevated autumn temperatures in suburban areas reduced the urban–rural temperature gradient, while intensified rural cooling during winter enhanced the UHI effect. These findings underscore the importance of integrating high-resolution climate modeling into urban planning and developing targeted adaptation strategies based on future UHI patterns to address climate challenges. Full article

Water source identification and dynamic assessment are critical for mining safety, particularly in mines governed by complex geological structures. The hydrochemical mixing model demonstrates a natural advantage for early warning of water intrusion compared to geophysical monitoring techniques. This study discusses core issues related to the mixing model, including the conceptual framework, selection of end-members, and choice of tracers, and formulates principles for general applicability. In this study, three sources were identified using the conceptual model and hydrochemical analysis: water in F7 (main fault), shallow fracture water, and river water. A correlation analysis and variability analysis were applied to determine the tracers, and the ¹⁸O, D, Cl, B, and Li were determined. The end-members of the three sources are time-dependent in July and September, especially the shallow fracture water’s end-members. The dynamics of the mixing ratios of the three sources suggest that river water contributes only to the inrush (1–4%), with this being especially low in September, as the increasing hydraulic gradient from south to north prevents recharge. The water in F7 accounts for at least 70% of the inrush water. Shallow fracture water accounts for the rest and increases slightly in September as the precipitation increases in mining-disturbed areas. Finally, this work makes the later water control work more targeted. Full article

Nonlinear characteristics are essential for neuromorphic devices to process high-dimensional and unstructured data. However, enabling a device to realize a nonlinear response under the same stimulation condition is challenging as this involves two opposing processes: simultaneous charge accumulation and recombination. In this study, a hybrid transistor based on a mixed-halide perovskite was fabricated to achieve dynamic nonlinear changes in synaptic plasticity. The utilization of a light-induced mixed-bandgap structure within the mixed perovskite film has been demonstrated to increase the recombination paths of photogenerated carriers of the hybrid film, thereby promoting the formation of nonlinear signals in the device. The constructed heterojunction optoelectronic synaptic transistor, formed by combining a mixed-halide perovskite with a p-type semiconductor, generates dynamic nonlinear decay responses under 400 nm light pulses with an intensity as low as 0.02 mW/cm². Furthermore, it has been demonstrated that nonlinear photocurrent growth can be achieved under 650 nm light pulses. It is important to note that this novel nonlinear response is characterized by its dynamism. These improvements provide a novel method for expanding the modulation capability of optoelectronic synaptic devices for synaptic plasticity. Full article

Gravity and gravity gradient data serve as fundamental inputs for geophysical resource exploration and geological structure analysis. However, traditional denoising methods—including wavelet transforms, moving averages, and low-pass filtering—exhibit signal loss and limited adaptability under complex, non-stationary noise conditions. To address these challenges, this study proposes an improved U-Net deep learning framework that integrates multi-scale feature extraction and attention mechanisms. Furthermore, a Laplace consistency constraint is introduced into the loss function to enhance denoising performance and physical interpretability. Notably, the datasets used in this study are generated by the authors, involving simulations of subsurface prism distributions with realistic density perturbations (±20% of typical rock densities) and the addition of controlled Gaussian noise (5%, 10%, 15%, and 30%) to simulate field-like conditions, ensuring the diversity and physical relevance of training samples. Experimental validation on these synthetic datasets and real field datasets demonstrates the superiority of the proposed method over conventional techniques. For noise levels of 5%, 10%, 15%, and 30% in test sets, the improved U-Net achieves Peak Signal-to-Noise Ratios (PSNR) of 59.13 dB, 52.03 dB, 48.62 dB, and 48.81 dB, respectively, outperforming wavelet transforms, moving averages, and low-pass filtering by 10–30 dB. In multi-component gravity gradient denoising, our method excels in detail preservation and noise suppression, improving Structural Similarity Index (SSIM) by 15–25%. Field data tests further confirm enhanced identification of key geological anomalies and overall data quality improvement. In summary, the improved U-Net not only delivers quantitative advancements in gravity data denoising but also provides a novel approach for high-precision geophysical data preprocessing. Full article

The accurate mapping of crop planting patterns is vital for sustainable agriculture and food security, particularly in regions with complex cropping systems and limited cloud-free observations. This research focuses on the Jianghan Plain in southern China, where diverse planting structures and persistent cloud cover make consistent monitoring challenging. We integrated multi-temporal Sentinel-2 and Landsat-8 imagery from 2017 to 2021 on the Google Earth Engine platform and applied a sample migration strategy to construct multi-year training data. A random forest classifier was used to identify nine major planting patterns at a 10 m resolution. The classification achieved an average overall accuracy of 88.3%, with annual Kappa coefficients ranging from 0.81 to 0.88. A spatial analysis revealed that single rice was the dominant pattern, covering more than 60% of the area. Temporal variations in cropping patterns were categorized into four frequency levels (0, 1, 2, and 3 changes), with more dynamic transitions concentrated in the central-western and northern subregions. A multiscale geographically weighted regression (MGWR) model revealed that economic and production-related factors had strong positive associations with crop planting patterns, while natural factors showed relatively weaker explanatory power. This research presents a scalable method for mapping fine-resolution crop patterns in complex agroecosystems, providing quantitative support for regional land-use optimization and the development of agricultural policies. Full article

Electrospun nanofiber-based triboelectric nanogenerators (TENGs) have emerged as a highly promising class of self-powered sensors for a broad range of applications, particularly in intelligent sensing technologies. By combining the advantages of electrospinning and triboelectric nanogenerators, these sensors offer superior characteristics such as high sensitivity, mechanical flexibility, lightweight structure, and biocompatibility, enabling their integration into wearable electronics and biomedical interfaces. This review presents a comprehensive overview of recent progress in electrospun nanofiber-based TENGs, covering their working principles, operating modes, and material composition. Both pure polymer and composite nanofibers are discussed, along with various electrospinning techniques that enable control over morphology and performance at the nanoscale. We explore their practical implementations in both contact-type and non-contact-type sensing, such as human–machine interaction, physiological signal monitoring, gesture recognition, and voice detection. These applications demonstrate the potential of TENGs to enable intelligent, low-power, and real-time sensing systems. Furthermore, this paper points out critical challenges and future directions, including durability under long-term operation, scalable and cost-effective fabrication, and seamless integration with wireless communication and artificial intelligence technologies. With ongoing advancements in nanomaterials, fabrication techniques, and system-level integration, electrospun nanofiber-based TENGs are expected to play a pivotal role in shaping the next generation of self-powered, intelligent sensing platforms across diverse fields such as healthcare, environmental monitoring, robotics, and smart wearable systems. Full article

Polysaccharides isolated from Radix Cyathula officinalis Kuan (RCP) are key bioactive components with immunomodulatory, antioxidant, and anti-inflammatory effects. Their efficacy varies according to their geographic origin and processing methods. However, the systemic anti-aging mechanisms and antioxidant efficacy of RCP have not yet been comprehensively characterized. This study investigated the antioxidant and anti-aging effects of RCP in vitro and in vivo using a Caenorhabditis elegans heat stress model, comparing rRCP (RCP from raw samples) and wRCP (RCP from wine-processed samples) from key production areas. Among these, the RCP collected from the Zhonggang region exhibited the strongest antioxidant activity. Both rRCP and wRCP enhanced worms’ oxidative stress resistance, reduced their ROS levels, increased their antioxidant enzyme activities, prolonged their lifespan, and improved their reproductive capacity under thermal stress. Notably, the wRCP exhibited more pronounced benefits. Additionally, 16S rRNA sequencing revealed that RCP altered the gut microbiota’s composition by increasing its microbial diversity, enriching beneficial bacteria like Bacillus, and decreasing potential pathogens such as Escherichia and Citricoccus. The treatment also led to an increased abundance of Firmicutes and a slight reduction in Bacteroidetes. Collectively, these findings suggest that RCP, particularly wRCP, holds promise as a therapeutic agent for combating oxidative stress and promoting longevity, in part by modulating the gut microbiome. Full article

To address the challenge of physically realizing fractional-order electrical networks, this study proposes an implementation method for a mechatronic inerter–spring–damper (ISD) suspension based on a fractional-order biquadratic transfer function. Building upon a previously established model of a mechatronic ISD suspension, the influence of parameter perturbations on the suspension’s dynamic performance characteristics was systematically investigated. Positive real synthesis was employed to determine the optimal five-element passive network structure for the fractional-order biquadratic electrical network. Subsequently, the Oustaloup filter approximation algorithm was utilized to realize the integer-order equivalents of the fractional-order electrical components, and the approximation effectiveness was analyzed through frequency-domain and time-domain simulations. Bench testing validated the effectiveness of the proposed method: under random road excitation at 20 m/s, the root mean square (RMS) values of the vehicle body acceleration, suspension working space, and dynamic tire load were reduced by 7.86%, 17.45%, and 2.26%, respectively, in comparison with those of the traditional passive suspension. This research provides both theoretical foundations and practical engineering solutions for implementing fractional-order transfer functions in vehicle suspensions, establishing a novel technical pathway for comprehensively enhancing suspension performance. Full article

As mine mining extends to greater depths, the challenge of heat damage in high-temperature and high-humidity deep mines has emerged as a significant obstacle to the safe mining of deep mines. This paper reviews the causes of mine heat damage, evaluates heat damage mechanisms, and explores deep mine cooling technologies. Traditional deep mine cooling technologies employ mechanical refrigeration to cool air. While these technologies can mitigate heat damage, they are associated with issues including high energy consumption, insufficient dehumidification, and significant cold loss. To address the high energy consumption and fully utilize geothermal resources, heat pump technology and combined cooling, heating, and power technology are employed to recover waste heat from deep mines, thereby achieving efficient mine cooling and energy utilization. To enhance the effectiveness of air dehumidification, the integration of deep dehumidification with mine cooling technology addresses the high humidity ratio in mine working faces. To enhance the refrigeration capacity of the system, liquid-phase-change refrigeration technology is employed to boost the refrigeration capacity. For the future development of deep mine cooling technology, this paper identifies four key directions: the integration of diverse technologies, collaboration cooling and geothermal mining, deep dehumidification and cooling, and intelligent control. Full article

Yeast cells are passively exposed to ethanol stress during alcoholic fermentation, ultimately impairing cell viability and reducing fermentation efficiency. Arginine, a versatile amino acid, plays a crucial role in regulating cellular responses to various stresses. This study aimed to explore the underlying mechanism by which arginine protects Wickerhamomyces anomalus against ethanol stress. The effects of arginine supplementation (5 mM) under ethanol stress (9% v/v) on cell survival, reactive oxygen species (ROS) production, cellular and mitochondrial membrane integrity, and nitric oxide synthesis were investigated using fluorescent staining methods. Furthermore, differentially expressed genes (DEGs) and metabolites (DEMs) were identified through transcriptomics and metabolomics analyses. The results demonstrated that exogenous arginine enhanced cell survival, reduced ROS levels, maintained cellular and mitochondrial membrane integrity, stimulated nitric oxide production, and modulated gene expression and metabolic pathways involved in pyruvate metabolism, yeast meiosis, fatty acid degradation, glycerophospholipid metabolism, and the biosynthesis of various secondary metabolites. These findings provide intriguing insights into the mechanistic role of arginine in enhancing the tolerance of W. anomalus to ethanol stress, and broaden its application in the fermentation industry for alcoholic beverages. Full article

In industrial production, high-power microwaves are commonly used for heating and drying processes; however, their application in measurement is relatively limited. This paper presents a power measurement system to enhance the use of microwave measurements in industry and improve the efficiency of microwave drying for PET particles. Operating at 2.45 GHz, the system integrates four-port power measurements based on the multilayer perceptron (MLP). By introducing residual connectivity, the residual network is determined to detect the height of PET particles. Experimental results show that this system can perform rapid measurements without needing a vector network analyzer (VNA), significantly improving the efficiency of microwave energy utilization in the early drying stages. Furthermore, the system offers practical and cost-efficient predictions for low-loss particulate materials. This power measurement strategy holds promising application potential in future industrial production. Full article

Umami is a fundamental taste sensation, often described as a delicious and pleasant flavor perception. To enhance or complement the original flavor and meet the tastes of diverse regions, umami dipeptides have been extensively utilized in global food manufacturing. Currently, the application and purification techniques of dipeptides are relatively mature, while their umami mechanisms and molecular modification are both scarce. In this work, the 3D structure of the umami dipeptide target T1R1/T1R3 was first obtained through sequence alignment and homology modeling, then followed by the successful construction of a database containing 400 samples of dipeptides. Subsequently, the complex models of T1R1/T1R3, respectively, with DG (Asp-Gly) and EK (Glu-Lys) (i.e., T1R1_DG/T1R3, T1R1/T1R3_DG, T1R1_EK/T1R3, and T1R1/T1R3_EK) were obtained via molecular docking and virtual screening. Finally, based on comparative molecular dynamics (MD) simulation trajectories, the binding free energy was calculated to investigate receptor–ligand recognition and conformational changes, providing some implications for potential modifications of umami dipeptides. T1R1 tends to bind relatively small umami dipeptides, whereas T1R3 does the opposite, both of which favor the recognition of acidic and hydrophilic dipeptides. By comparing strategies such as hydroxyl introduction and chain length alteration, electrostatic effects may be more important than non-polar effects in molecular design. This work not only explores the recognition mechanism of umami dipeptides with the receptor T1R1/T1R3 showing certain theoretical significance, but also provides feasible suggestions for dipeptide screening and modification having certain application value. Full article