Search Results (342)

Calcium carbonate (CaCO₃) has attracted considerable attention owing to its structural versatility and broad applications in materials science and geochemistry. In this study, we employed Density Functional Theory (DFT) simulations to systematically investigate the structural, elastic, and dynamic properties of trigonal CaCO₃ under hydrostatic pressures ranging from 0 to 1.2 GPa. The optimized lattice constants closely align with previous theoretical and experimental values, thereby confirming the reliability of the computational approach. Mechanical stability was validated across the entire pressure range, with elastic constants and moduli demonstrating gradual increases under compressive strain. Elastic anisotropy was rigorously quantified using universal anisotropy indices, three-dimensional surface visualizations, and directional projections of elastic moduli. These analyses revealed pronounced pressure-dependent anisotropy. Furthermore, optical properties, including refractive indices and dielectric functions, were analyzed to clarify pressure-induced variations in electromagnetic interactions. These findings offer valuable insights into the pressure behavior of CaCO₃, advancing its potential applications in advanced functional materials and geophysical research. Full article

In order to improve the inversion accuracy of electrical resistivity tomography (ERT) and overcome the limitations of traditional linear methods, this paper proposes an improved shuffled frog leaping algorithm (SFLA). First, an equilibrium grouping strategy is designed to balance the contribution weight of each subgroup to the global optimal solution, suppressing the local optimum traps caused by the dominance of high-quality groups. Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. Additionally, the root mean square error is reduced by 57%. In the engineering validation at the Baota Mountain mining area in Jurong, the improved SFLA inversion clearly reveals the undulating bedrock morphology. At a measuring point 55 m along the profile, the bedrock depth is 14.05 m (ZK3 verification value 12.0 m, error 17%), and at 96 m, the depth is 6.9 m (ZK2 verification value 6.7 m, error 3.0%). The characteristic of deeper bedrock to the south and shallower to the north is highly consistent with the terrain and drilling data (RMSE = 1.053). This algorithm provides reliable technical support for precise detection of complex geological structures using ERT. Full article

Due to the limited endurance of UAVs, especially in scenarios involving large areas and dense target nodes, it is challenging for multiple UAVs to complete diverse tasks while ensuring timely execution. Toward this, we propose a cross-platform system consisting of an aircraft carrier (AC) and multiple UAVs, which makes unified task planning for included heterogeneous platforms to maximize the efficiency of the entire combat system. The carrier-based UAV swarm mission planning problem is formulated to minimize completion time and resource utilization, taking into account large-scale targets, multi-type tasks, and multi-obstacle environments. Since the problem is complex, we design a decoupled framework to simplify the solution by decomposing it into two levels: upper-level AC path planning and bottom-level multi-UAV cooperative mission planning. At the upper level, a drop point determination method and a discrete genetic algorithm incorporating improved A* (DGAIIA) are proposed to plan the AC’s path in the presence of no-fly zones and radar threats. At the bottom level, an improved differential evolution algorithm with a market mechanism (IDEMM) is proposed to minimize task completion time and maximize UAV utilization. Specifically, a dual-switching search strategy and a neighborhood-first buying-and-selling mechanism are developed to improve the search efficiency of the IDEMM. Simulation results validate the effectiveness of both the DGAIIA and IDEMM. An animation of the simulation results is available at simulation section. Full article

Colorectal cancer (CRC) remains a predominant cause of global cancer-related mortality, highlighting the pressing demand for innovative therapeutic strategies. Natural polysaccharides have emerged as promising candidates in cancer research due to their multifaceted anticancer mechanisms and tumor-suppressive potential across diverse malignancies. In this study, we enzymatically extracted a polysaccharide, named ERPP, from Ruditapes philippinarum and comprehensively evaluated its anti-colorectal cancer activity. We conducted in vitro assays, including CCK-8 proliferation, clonogenic survival, scratch wound healing, and Annexin V-FITC/PI apoptosis staining, and the results demonstrated that ERPP significantly inhibited HT-29 cell proliferation, suppressed colony formation, impaired migratory capacity, and induced apoptosis. JC-1 fluorescence assays provided further evidence of mitochondrial membrane potential (MMP) depolarization, as manifested by a substantial reduction in the red/green fluorescence ratio (from 10.87 to 0.35). These antitumor effects were further validated in vivo using a zebrafish HT-29 xenograft model. Furthermore, ERPP treatment significantly attenuated tumor angiogenesis and downregulated the expression of the vascular endothelial growth factor A (Vegfaa) gene in the zebrafish xenograft model. Mechanistic investigations revealed that ERPP primarily activated the mitochondrial apoptosis pathway. RT-qPCR analysis showed an upregulation of the pro-apoptotic gene Bax and a downregulation of the anti-apoptotic gene Bcl-2, leading to cytochrome c (CYCS) release and caspase-3 (CASP-3) activation. Additionally, ERPP exhibited potent antioxidant capacity, achieving an 80.2% hydroxyl radical scavenging rate at 4 mg/mL. ERPP also decreased reactive oxygen species (ROS) levels within the tumor cells, thereby augmenting anticancer efficacy through its antioxidant activity. Collectively, these findings provide mechanistic insights into the properties of ERPP, underscoring its potential as a functional food component or adjuvant therapy for colorectal cancer management. Full article

This study aimed to investigate the underlying mechanisms by which dandelion extract inhibits the proliferation of breast cancer MDA-MB-231 cells. Dandelion root and leaf extracts were prepared using a heat reflux method and subjected to solvent gradient extraction to obtain fractions with different polarities. MTT assays revealed that the ethyl acetate fraction exhibited the strongest inhibitory effect on cell proliferation. LC-MS analysis identified 12 potential active compounds, including sesquiterpenes such as Isoalantolactone and Artemisinin, which showed significantly lower toxicity toward normal mammary epithelial MCF-10A cells compared to tumor cells (p < 0.01). Mechanistic studies demonstrated that the extract induced apoptosis in a dose-dependent manner, with an apoptosis rate as high as 85.04%, and significantly arrested the cell cycle at the S and G2/M phases. Label-free quantitative proteomics identified 137 differentially expressed proteins (|FC| > 2, p < 0.05). GO enrichment analysis indicated that these proteins were mainly involved in cell cycle regulation and apoptosis. KEGG pathway analysis revealed that the antitumor effects were primarily mediated through the regulation of PI3K-Akt (hsa04151), JAK-STAT (hsa04630), and PPAR (hsa03320) signaling pathways. Moreover, differential proteins such as PI3K, AKT1S1, SIRT6, JAK1, SCD, STAT3, CASP8, STAT2, STAT6, and PAK1 showed strong correlation with the core components of the EA-2 fraction of dandelion. Molecular docking results demonstrated that these active compounds exhibited strong binding affinities with key target proteins such as PI3K and JAK1 (binding energy < −5.0 kcal/mol). This study elucidates the multi-target, multi-pathway synergistic mechanisms by which dandelion extract inhibits breast cancer, providing a theoretical basis for the development of novel antitumor agents. Full article

This paper proposes an anti-disturbance model predictive fault-tolerance control strategy for open-circuit faults of five-phase flux intensifying fault-tolerant interior permanent magnet (FIFT-IPM) motors. This strategy is applicable to electric agricultural equipment that has an open winding failure. Due to the rich third-harmonic back electromotive force (EMF) content of five-phase FIFT-IPM motors, the existing model predictive current fault-tolerant control algorithms fail to effectively track fundamental and third-harmonic currents. This results in high harmonic distortion in the phase current. Hence, this paper innovatively proposes a multi-plane virtual vector model predictive fault-tolerant control strategy that can achieve rapid and effective control of both the fundamental and harmonic planes while ensuring good dynamic stability performance. Additionally, considering that electric agricultural equipment is usually in a multi-disturbance working environment, this paper introduces an adaptive gain sliding-mode disturbance observer. This observer estimates complex disturbances and feeds them back into the control system, which possesses good resistance to complex disturbances. Finally, the feasibility and effectiveness of the proposed control strategy are verified by experimental results. Full article

Lane detection is a key technology in automatic driving environment perception, and its accuracy directly affects vehicle positioning, path planning, and driving safety. In this study, an enhanced real-time model for lane detection based on an improved DeepLabV3+ architecture is proposed to address the challenges posed by complex dynamic backgrounds and blurred road boundaries in suburban road scenarios. To address the lack of feature correlation in the traditional Atrous Spatial Pyramid Pooling (ASPP) module of the DeepLabV3+ model, we propose an improved LC-DenseASPP module. First, inspired by DenseASPP, the number of dilated convolution layers is reduced from six to three by adopting a dense connection to enhance feature reuse, significantly reducing computational complexity. Second, the convolutional block attention module (CBAM) attention mechanism is embedded after the LC-DenseASPP dilated convolution operation. This effectively improves the model’s ability to focus on key features through the adaptive refinement of channel and spatial attention features. Finally, an image-pooling operation is introduced in the last layer of the LC-DenseASPP to further enhance the ability to capture global context information. DySample is introduced to replace bilinear upsampling in the decoder, ensuring model performance while reducing computational resource consumption. The experimental results show that the model achieves a good balance between segmentation accuracy and computational efficiency, with a mean intersection over union (mIoU) of 95.48% and an inference speed of 128 frames per second (FPS). Additionally, a new lane-detection dataset, SubLane, is constructed to fill the gap in the research field of lane detection in suburban road scenarios. Full article

Star sensors, as the most precise attitude measurement devices currently available, play a crucial role in spacecraft attitude estimation. However, traditional frame-based cameras tend to suffer from target blur and loss under high-dynamic maneuvers, which severely limit the applicability of conventional star sensors in complex space environments. In contrast, event cameras—drawing inspiration from biological vision—can capture brightness changes at ultrahigh speeds and output a series of asynchronous events, thereby demonstrating enormous potential for space detection applications. Based on this, this paper proposes an event data extraction method for weak, high-dynamic space targets to enhance the performance of event cameras in detecting space targets under high-dynamic maneuvers. In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. During the target extraction stage, we introduce the DBSCAN clustering algorithm to achieve the subpixel-level extraction of target centroids. Moreover, to address issues of target trajectory distortion and data discontinuity in certain ultrahigh-dynamic scenarios, we construct a camera motion model based on real-time motion data from an inertial measurement unit (IMU) and utilize it to effectively compensate for and correct the target’s trajectory. Finally, a ground-based simulation system is established to validate the applicability and superior performance of the proposed method in real-world scenarios. Full article

When lithium-ion batteries experience thermal runaway, a large amount of heat rapidly accumulates inside, causing the internal pressure to rise sharply. Once the pressure exceeds the battery’s safety valve design capacity, the valve activates and releases flammable gas. If ignited in a high-temperature environment, the escaping gas can cause a jet fire containing high-temperature substances. Effectively controlling the internal temperature of the jet fire, especially rapidly cooling the core area of the flame during the jet process, is important to prevent the spread of lithium-ion battery fires. Therefore, this work proposes a strategy of a synergistic effect using microcapsule fire extinguishing agents and fine water mist to achieve an external barrier and an internal attack. The microcapsule fire extinguishing agents are prepared by using melamine–urea–formaldehyde resin as the shell and 1,1,1,2,2,3,3,4,4-nonafluoro-4-methoxybutane (C₅H₃F₉O) and 1,1,2,2,3,3,4-heptafluorocyclopentane (C₅H₃F₇) as the composite core. During the process of lithium-ion battery thermal runaway, the microcapsule fire extinguishing agents can enter the inner area of the jet fire under the protection of the fine water mist. The microcapsule shell ruptures at 100 °C, releasing the highly effective composite fire suppressant core inside the jet fire. The fine water mist significantly blocks the transfer of thermal radiation, inhibiting the spread of the fire. Compared to the suppression with fine water mist only, the time required to reduce the battery temperature from the peak value to a low temperature is reduced by 66 s and the peak temperature of the high-temperature substances above the battery is reduced by 228.2 °C. The propagation of the thermal runaway is suppressed, and no thermal runaway of other batteries around the faulty unit will occur. This synergistic suppression strategy of fine water mist and microcapsule fire extinguishing agent (FWM@M) effectively reduces the adverse effects of jet fires on the propagation of thermal runaway (TR) of lithium-ion batteries, providing a new solution for efficiently extinguishing lithium-ion battery fires. Full article

The efficiency of coalbed methane (CBM) extraction is closely related to the drilling response of coal seams, which is significantly influenced by natural fracture development of coal seams. This work investigated 11 coal samples from the Baode, Xinyuan, and Huolinhe mines, employing quantitative fracture characterization, acoustic wave testing, drilling experiments, and cuttings analysis to systematically reveal the relationships and mechanisms between fracture parameters and coal drilling response characteristics. The result found that acoustic parameters (average wave velocity v and drilling surface wave velocity v₀) exhibit significant negative correlations with fracture line density (ρ₁) and area ratio (ρ₂) (|r| > 0.7), while the geological strength index (GSI) positively correlates with acoustic parameters, confirming their utility as indirect indicators of fracture development. Fracture area ratio (ρ₂) strongly correlates with drilling cuttings rate q (r = 0.82), whereas GSI negatively correlates with drilling rate w, indicating that highly fractured coal is more friable but structural stability constrains drilling efficiency, while fracture parameters show limited influence on drill cuttings quantity Q. Cuttings characteristics vary with fracture types and density. Type I coal (low-density coexisting exogenous fractures and cleats) produces cuttings dominated by fine particles with concentrated size distribution (average particle size d ≈ 0.52 mm, crushability index n = 0.46–0.61). Type II coal (exogenous-fracture-dominant) exhibits coarser particle sizes in cuttings (d ≈ 0.8 mm, n = 0.43–0.53). Type III coal (dense-cleat-dominant) drill cuttings are mainly coarse particles and are concentrated in distribution (d ≈ 1.53 mm, n = 0.72–0.98). Additionally, drilling response differences are governed by the coupling effects of vitrinite reflectance (R_o), density, and firmness coefficient (f), with Huolinhe coal being easier to drill due to its lower R_o, f, and density. This study elucidates the mechanism by which fracture development affects coal drilling response through multi-parameter correlation analysis, while also providing novel insights into the optimization of fracturing sweet spot selection for CBM development. Full article

Fruit quality testing plays a crucial role in the advancement of fruit industry, which is related to market competitiveness, consumer satisfaction and production process optimization. In recent years, nondestructive testing technology has become a research hotspot due to its outstanding advantages. In this paper, the principle, application, advantages and disadvantages of optical, acoustic, electromagnetics, dielectric properties research and electronic nose non-destructive testing technology in fruit quality testing are systematically reviewed. These technologies can detect a variety of chemical components of fruit, realize the assessment of maturity, damage degree, disease degree, and are suitable for orchard picking, quality grading, shelf life prediction and other fields. However, there are limitations to these techniques. The optical, acoustic and electronic nose technologies are susceptible to environmental factors, the electromagnetic technology has defects in the detection of complex molecules and fruit internal quality, and the dielectric characteristics are greatly affected by the shape and state of the sample surface. In the future, efforts should be made to enhance the implementation of non-destructive testing technology in the fruit industry through technology integration, optimization algorithm, cost reduction, and expansion of industrial chain application, so as to help the premium growth of the fruit industry. Full article

Deep neural network fusion approaches utilizing multimodal remote sensing are essential for crop mapping. However, challenges such as insufficient spatiotemporal feature extraction and ineffective fusion strategies still exist, leading to a decrease in mapping accuracy and robustness when these approaches are applied across spatial‒temporal regions. In this study, we propose a novel rice mapping approach based on dual-branch transformer fusion networks, named RDTFNet. Specifically, we implemented a dual-branch encoder that is based on two improved transformer architectures. One is a multiscale transformer block used to extract spatial–spectral features from a single-phase optical image, and the other is a Restormer block used to extract spatial–temporal features from time-series synthetic aperture radar (SAR) images. Both extracted features were then combined into a feature fusion module (FFM) to generate fully fused spatial–temporal–spectral (STS) features, which were finally fed into the decoder of the U-Net structure for rice mapping. The model’s performance was evaluated through experiments with the Sentinel-1 and Sentinel-2 datasets from the United States. Compared with conventional models, the RDTFNet model achieved the best performance, and the overall accuracy (OA), intersection over union (IoU), precision, recall and F1-score were 96.95%, 88.12%, 95.14%, 92.27% and 93.68%, respectively. The comparative results show that the OA, IoU, accuracy, recall and F1-score improved by 1.61%, 5.37%, 5.16%, 1.12% and 2.53%, respectively, over those of the baseline model, demonstrating its superior performance for rice mapping. Furthermore, in subsequent cross-regional and cross-temporal tests, RDTFNet outperformed other classical models, achieving improvements of 7.11% and 12.10% in F1-score, and 11.55% and 18.18% in IoU, respectively. These results further confirm the robustness of the proposed model. Therefore, the proposed RDTFNet model can effectively fuse STS features from multimodal images and exhibit strong generalization capabilities, providing valuable information for governments in agricultural management. Full article

This study presents a novel two-dimensional hyperchaotic map, referred to as the 2D exponent-logarithm-sine chaotic map (2D-ELSCM), which is intricately designed through the interplay of exponential, logarithmic, and sine functions. To comprehensively evaluate the chaotic performance of the 2D-ELSCM, several critical metrics are employed, including the largest Lyapunov exponent (LLE), permutation entropy (PE), sample entropy (SE), Kolmogorov entropy (KE), and the results of the 0–1 test, which yield values of 8.3175, 0.9998, 1.9826, 2.1117, and 0.9970, respectively. Furthermore, the 2D-ELSCM successfully passes the NIST randomness tests, collectively confirming its exceptional randomness and complexity. Building upon this robust chaotic map, we develop a distinctive chaotic image encryption scheme that employs an improved Knuth-Durstenfeld shuffle (IKDS) to rearrange pixel positions, effectively disrupting the correlation between adjacent pixels. Complementing this, we introduce a dynamic diffusion mechanism that integrates DNA encoding with the Zigzag transform, thereby promoting global pixel diffusion and enhancing encryption security. The initial conditions of the chaotic map are generated from the SHA-512 hash of the plaintext image in conjunction with an external key, which not only expands the key space but also significantly improves key sensitivity. Simulation results demonstrate that the proposed encryption scheme achieves correlation coefficients approaching 0 in the encrypted test images, with an average NPCR of 99.6090% and UACI of 33.4707%. These findings indicate a strong resistance to various attacks and showcase excellent encryption quality, thereby underscoring the scheme’s potential for secure image transmission and storage. Full article

In the era of global climate change, existing evidence indicates that dominant species play a crucial role in regulating grassland structure and function. However, what remains overlooked are the factors that regulate the growth of dominant species under climate change. Some studies have indicated that the future climate of the Inner Mongolia grasslands will specifically show a trend of warming and humidification. Hence, in 2013, we conducted a controlled warming and precipitation addition experiment in a temperate steppe in Inner Mongolia, China. Open-top chambers (OTCs) were used to simulate warming (by 1.5 °C) and rainfall (twice a month, 10% of the average precipitation between 1960 and 2011 of the same month each time) during the growing season. In 2023, the resource utilization efficiency, morphological characteristics, leaf anatomical structure, and population quantity characteristics of the dominant species (Leymus chinensis), and community species diversity were monitored under control (CK), warming (T), precipitation addition (P), and warming plus precipitation addition (TP) conditions. We found that the plant height of L. chinensis significantly increased under warming; its height was 41.97 cm under TP, 41.84 cm under T, 29.48 cm under P, and 28.88 cm under CK. We observed that L. chinensis primarily obtains more light by increasing leaf area and height under warming conditions. Environmental changes also alter the tissue structure of L. chinensis leaves, leading to a decrease in lignification after increasing the water content. In this study, warming significantly increased the L. chinensis leaf area but decreased the leaf carbon content. Warming and precipitation addition regulated the height of L. chinensis by affecting the leaf area, leaf–stem ratio, and distance of the bottom leaf from the ground. Our results provide reasonable predictions regarding the succession direction of the L. chinensis steppe under global climate change in the future. Full article