Search Results (1,254)

Accurately predicting the ionosphere’s Total Electron Content (TEC) is significant for ensuring the regular operation of satellite navigation and communication systems and space weather prediction. To further improve the accuracy of TEC prediction, this paper proposes a TEC prediction model based on the grid-optimized Gate Recurrent Unit (GRU). This model has the following main features: (1) it uses statistical learning methods to interpolate the missing data of TEC observations; (2) it constructs a sliding time window by using the multi-dimensional time series features of two types of solar activity indices to support modeling; (3) It adopts grid search combined with optimization of network depth, time step length, and other hyperparameters to significantly enhance the model’s ability to extract the characteristics of the ionospheric 11-year cycle and seasonal variations. Taking the EGLIN station as an example, the proposed model is verified. The experimental results show that the root mean square error of the GRU model during the period from 2019 to 2020 was 0.78 TECU, which was significantly lower than those of the CCIR, URSI, and statistical machine learning models. Compared with the other three models, the RMSE error of the GRU model was reduced by 72.73%, 72.64%, and 57.38%, respectively. The above research verifies the advantages of the proposed model in predicting TEC and provides a new idea for ionospheric modeling. Full article

To investigate the evolution of the optothermal properties of lithium niobate with ion beam irradiation parameters, the thermal effect theory was analyzed, and ion beam irradiation technology was used to modify lithium niobate samples. The transmittance of lithium niobate crystals after ion beam irradiation and the relationship between their optothermal properties and transmittance were studied. The results show that the average surface optothermal signal of lithium niobate exhibits a significant dependence on ion beam parameters. When the ion beam voltage is 800 V, the ion beam current is 30 mA, and the irradiation time is 60 s, a distinct absorption peak is observed on the surface of lithium niobate, with an average surface optothermal signal of 5377.34 ppm, demonstrating potential for all-optical modulation. Full article

In this paper, a novel online detection system is designed to enhance accuracy and operational efficiency in the outbound logistics of automotive components after production. The system consists of a scanning portal system and an improved YOLOv12-based detection algorithm which captures images of automotive parts passing through the scanning portal in real time. By integrating deep learning, the system enables real-time monitoring and identification, thereby preventing misdetections and missed detections of automotive parts, in this way promoting intelligent automotive part recognition and detection. Our system introduces the A2C2f-SA module, which achieves an efficient feature attention mechanism while maintaining a lightweight design. Additionally, Dynamic Space-to-Depth (Dynamic S2D) is employed to improve convolution and replace the stride convolution and pooling layers in the baseline network, helping to mitigate the loss of fine-grained information and enhancing the network’s feature extraction capability. To improve real-time performance, a GFL-MBConv lightweight detection head is proposed. Furthermore, adaptive frequency-aware feature fusion (Adpfreqfusion) is hybridized at the end of the neck network to effectively enhance high-frequency information lost during downsampling, thereby improving the model’s detection accuracy for target objects in complex backgrounds. On-site tests demonstrate that the system achieves a comprehensive accuracy of 97.3% and an average vehicle detection time of 7.59 s, exhibiting not only high precision but also high detection efficiency. These results can make the proposed system highly valuable for applications in the automotive industry. Full article

Background/Objectives: Late embryogenesis abundant (LEA) proteins regulate stress responses and contribute significantly to plant stress tolerance. As a model species for stress resistance studies, foxtail millet (Setaria italica) lacks comprehensive characterization of its LEA gene family. This study aimed to comprehensively identify SiLEA genes in foxtail millet and elucidate their functional roles and tissue-specific expression patterns. Methods: Genome-wide identification of SiLEA genes was conducted, followed by phylogenetic reconstruction, cis-acting element analysis of promoters, synteny analysis, and expression profiling. Results: Ninety-four SiLEA genes were identified and classified into nine structurally distinct subfamilies, which are unevenly distributed across all nine chromosomes. Phylogenetic analysis showed closer clustering of SiLEA genes with sorghum and rice orthologs than with Arabidopsis thaliana AtLEA genes. Synteny analysis indicated the LEA gene family expansion through tandem and segmental duplication. Promoter cis-element analysis linked SiLEA genes to plant growth regulation, stress responses, and hormone signaling. Transcriptome analysis revealed tissue-specific expression patterns among SiLEA members, while RT-qPCR verified ABA-induced transcriptional regulation of SiLEA genes. Conclusions: This study identified 94 SiLEA genes grouped into nine subfamilies with distinct spatial expression profiles. ABA treatment notably upregulated SiASR-2, SiASR-5, and SiASR-6 in both shoots and roots. Full article

The Junggar Basin contains a large amount of coal resources and is an important coal production base in China. The coal seam in Zhundong coalfield has a large single-layer thickness and high content of inertinite, but large particle Fe-sulphide minerals are associated with coal seams in some mining areas. A series of economic and environmental problems caused by the combustion of large-grained Fe-sulphide minerals in coal have seriously affected the economic, clean and efficient utilization of coal. In this paper, the ultra-thick coal seam of the Xishanyao formation in the Yihua open-pit mine of the Zhundong coalfield is taken as the research object. Through the analysis of coal quality, X-ray fluorescence spectrometer test of major elements in coal, inductively coupled plasma mass spectrometry test of trace elements, SEM-Raman identification of Fe-sulphide minerals in coal and LA-MC-ICP-MS test of sulfur isotope of marcasite, the coal quality characteristics, main and trace element characteristics, macro and micro occurrence characteristics of Fe-sulphide minerals and sulfur isotope characteristics of marcasite in the ultra-thick coal seam of the Xishanyao formation are tested. On this basis, the occurrence state and genesis of large particle Fe-sulphide minerals in the ultra-thick coal seam of the Xishanyao formation are clarified. The main results and understandings are as follows: (1) the occurrence state of Fe-sulphide minerals in extremely thick coal seams is clarified. The Fe-sulphide minerals in the extremely thick coal seam are mainly marcasite, and concentrated in the YH-2, YH-3, YH-8, YH-9, YH-14, YH-15 and YH-16 horizons. Macroscopically, Fe-sulphide minerals mainly occur in three forms: thin film Fe-sulphide minerals, nodular Fe-sulphide minerals, and disseminated Fe-sulphide minerals. Microscopically, they mainly occur in four forms: flake, block, spearhead, and crack filling. (2) The difference in sulfur isotope of marcasite was discussed, and the formation period of marcasite was preliminarily divided. The overall variation range of the δ³⁴S value of marcasite is wide, and the extreme values are quite different. The polyflake marcasite was formed in the early stage of diagenesis and the δ³⁴S value was negative, while the fissure filling marcasite was formed in the late stage of diagenesis and the δ³⁴S value was positive. (3) The coal quality characteristics of the thick coal seam were analyzed. The organic components in the thick coal seam are mainly inertinite, and the inorganic components are mainly clay minerals and marcasite. (4) The difference between the element content in the thick coal seam of the Zhundong coalfield and the average element content of Chinese coal was compared. The major element oxides in the thick coal seam are mainly CaO and MgO, followed by SiO₂, Al₂O₃, Fe₂O₃ and Na₂O. Li, Ga, Ba, U and Th are enriched in trace elements. (5) The coal-accumulating environment characteristics of the extremely thick coal seam are revealed. The whole thick coal seam is formed in an acidic oxidation environment, and the horizon with Fe-sulphide minerals is in an acidic reduction environment. The acidic reduction environment is conducive to the formation of marcasite and is not conducive to the formation of pyrite. (6) There are many matrix vitrinite, inertinite content, clay content, and terrigenous debris in the extremely thick coal seam. The good supply of peat swamp, suitable reduction environment and pH value, as well as groundwater leaching and infiltration, together cause the occurrence of large-grained Fe-sulphide minerals in the extremely thick coal seam of the Xishanyao formation in the Zhundong coalfield. Full article

Biochar serves as an effective adsorbent for the heavy metal cadmium, with its performance significantly influenced by its physicochemical properties and various environmental features. Traditional machine learning models, though adept at managing complex multi-feature relationships, rely heavily on expertise in feature engineering and hyperparameter optimization. To address these issues, this study employs an automated machine learning (AutoML) approach, automating feature selection and model optimization, coupled with an intuitive online graphical user interface, enhancing accessibility and generalizability. Comparative analysis of four AutoML frameworks (TPOT, FLAML, AutoGluon, H₂O AutoML) demonstrated that H₂O AutoML achieved the highest prediction accuracy (R² = 0.918). Key features influencing adsorption performance were identified as initial cadmium concentration (23%), stirring rate (14.7%), and the biochar H/C ratio (9.7%). Additionally, the maximum adsorption capacity of the biochar was determined to be 105 mg/g. Optimal production conditions for biochar were determined to be a pyrolysis temperature of 570–800 °C, a residence time of ≥2 h, and a heating rate of 3–10 °C/min to achieve an H/C ratio of <0.2. An online graphical user interface was developed to facilitate user interaction with the model. This study not only provides practical guidelines for optimizing biochar but also introduces a novel approach to modeling using AutoML. Full article

The applicability of the in-situ pyrolysis of oil-rich coal is highly dependent on regional geological conditions. In this study, six major geological factors and 19 key parameters influencing the in-situ pyrolysis of oil-rich coal were systematically identified. An analytic hierarchy process incorporating index classification and quantification was employed in combination with the geological features of the Tiaohu mining area to establish a feasibility evaluation index system suitable for in-situ development in the study region. Among these factors, coal quality parameters (e.g., coal type, moisture content, volatile matter, ash yield), coal seam occurrence characteristics (e.g., seam thickness, burial depth, interburden frequency), and hydrogeological conditions (e.g., relative water inflow) primarily govern pyrolysis process stability. Surrounding rock properties (e.g., roof/floor lithology) and structural features (e.g., fault proximity) directly impact pyrolysis furnace sealing integrity, while environmental geological factors (e.g., hazardous element content in coal) determine environmental risk control effectiveness. Based on actual geological data from the Tiaohu mining area, the comprehensive weight of each index was determined. After calculation, the southwestern, central, and southeastern subregions of the mining area were identified as favorable zones for pyrolysis development. A constraint condition analysis was then conducted, accompanied by a one-vote veto index system, in which the thresholds were defined for coal seam thickness (≥1.5 m), burial depth (≥500 m), thickness variation coefficient (≤15%), fault proximity (≥200 m), tar yield (≥7%), high-pressure permeability (≥10 mD), and high-pressure porosity (≥15%). Following the exclusion of unqualified boreholes, three target zones for pyrolysis furnace deployment were ultimately selected. Full article

Civil engineering structures with damage, defects, or subsurface utilities create a high-contrast exploration environment. These anomalies of interest exhibit different electromagnetic properties from the surrounding medium, and ground-penetrating radar (GPR) has the potential to accurately locate and map their three-dimensional (3D) distributions. However, full-waveform inversion (FWI) for GPR data struggles to simultaneously reconstruct high-resolution 3D images of both permittivity and conductivity models. Considering the magnitude and sensitivity disparities of the model parameters in the inversion of GPR data, this study proposes a 3D dual-parameter FWI algorithm for GPR with a composite model constraint strategy. It balances the gradient updates of permittivity and conductivity models through performing total variation (TV) regularization and minimum support gradient (MSG) regularization on different parameters in the inversion process. Numerical experiments show that TV regularization can optimize permittivity reconstruction, while MSG regularization is more suitable for conductivity inversion. The TV+MSG composite model constraint strategy improves the accuracy and stability of dual-parameter inversion, providing a robust solution for the 3D imaging of subsurface anomalies with high-contrast features. These outcomes offer researchers theoretical insights and a valuable reference when investigating scenarios with high-contrast environments. Full article

This study investigates the roles of grapevine berry inner necrosis virus (GINV) and grapevine yellow speckle viroid 1 (GYSVd1) in regulating the soluble sugar and organic acid metabolism of grape berries and wine. The contents of soluble sugar and organic acid components and the activity and expression levels of critical enzymes of the soluble sugar acid metabolism pathway were measured in ‘Welschriesling’ grape berries and wine carrying the virus GINV, the viroid GYSVd1, and a mixed infection of both GINV and GYSVd1 (GINV + GYSVd1), respectively. The results show that the virus GINV and the viroid GYSVd1 decreased the soluble sugar and increased the organic acid in berries and wine. GINV decreased glucose content and increased malic acid content by regulating AI, NADP-IDH, PEPC, and NAD-MDH activity, as well as VvHT4, VvSWEET10, VvPEPC, and VvMDH expression levels. GYSVd1 decreased glucose content and increased malic acid content by regulating AI and CS activity and VvHT4, VvSWEET15, and VvPEPC expression. The results suggest that the viroid GYSVd1 negatively impacts berries and wine more than the virus GINV. Moreover, in the mixed infection with GINV + GYSVd1, the negative effects of GINV and GYSVd1 on soluble sugars do not seem to be observed. Full article

Plant-derived extracellular vesicles (PDEVs) are nanoscale, phospholipid bilayer-enclosed vesicles secreted by living cells through cytokinesis under physiological and pathological conditions. Owing to their high biocompatibility and stability, PDEVs have attracted considerable interest in regenerative medicine applications. They can exhibit the capacity to enhance cellular proliferation, migration, and multi-lineage differentiation through immunomodulation, anti-inflammation effects, antioxidative protection, and tissue regeneration mechanisms. Given their abundant availability, favorable safety profile, and low immunogenicity risks, PDEVs have been successfully employed in therapeutic interventions for skeletal muscle disorders, cardiovascular diseases, neurodegenerative conditions, and tissue regeneration applications. This review mainly provides a comprehensive overview of PDEVs, systematically examining their biological properties, standardized isolation and characterization methodologies, preservation techniques, and current applications in regenerative medicine. Furthermore, we critically discuss future research directions and clinical translation potential, aiming to facilitate the advancement of PDEV-based therapeutic strategies. Full article

Foundation pit pumping induces groundwater drawdown both inside and outside the pit, consequently causing surrounding land subsidence. Based on actual engineering cases, this study established a three-dimensional numerical model using ABAQUS software (version 6.14-4) to systematically investigate the temporal evolution of groundwater drawdown and land subsidence during pit pumping, while quantifying the relationship between drawdown and subsidence stabilization time under different parameters. The key findings are as follows: (1) land subsidence stabilization time (50 days) is governed by external phreatic layer response, reaching 2.3 times longer than isolated aquifer conditions (22 days); (2) medium-permeability strata (0.01–10 K_0,AdII) showed peak sensitivity to drawdown–subsidence coupling; (3) pumping from a confined aquifer extends the subsidence stabilization time by a factor of 1.1 compared to phreatic aquifer conditions. These findings provide valuable insights for the design and risk assessment of dewatering strategies in foundation pits within multi-aquifer systems. Full article

An optical power splitter (OPS) with arbitrary splitting ratios has attracted significant research interest for its broad applications in photonic integrated circuits. A series of OPSs with arbitrary splitting ratios based on silicon nitride (Si₃N₄) platforms are presented. The devices are designed with ultra-compact dimensions using three-dimensional finite-difference time-domain (3D FDTD) analysis and an inverse design algorithm. Within a 50 nm bandwidth (1525 nm to 1575 nm), we demonstrated a 1 × 2 OPS with splitting ratios of 1:1, 1:1.5, and 1:2; a 1 × 3 OPS with ratios of 1:2:1 and 2:1:2; and a 1 × 4 OPS with ratios of 1:1:1:1 and 2:1:2:1. The target splitting ratios are achieved by optimizing pixel distributions in the coupling region. The dimensions of the designed devices are 1.96 × 1.96 µm², 2.8 × 2.8 µm², and 2.8 × 4.2 µm², respectively. The designed devices achieve transmission efficiencies exceeding 90% and exhibit excellent power splitting ratios (PSRs). Full article

Background: Liver fibrosis, a consequence of various chronic liver diseases, is characterized by excessive accumulation of extracellular matrix (ECM), leading to impaired liver function and potentially progressing to cirrhosis or hepatocellular carcinoma. The molecular mechanisms underlying liver fibrosis are complex and not fully understood. In vivo experiments are essential for studying the molecular mechanisms of the disease. However, the diverse principles behind mouse modeling techniques for liver fibrosis can complicate the elucidation of specific fibrotic mechanisms. Methods: Five distinct liver fibrosis models were utilized: CONTROL, NASH (non-alcoholic steatohepatitis), BDL (bile duct ligation), TAA (thioacetamide), and CCl₄ (carbon tetrachloride). Patents for these drugs were reviewed using Patentscope^® and Worldwide Espacenet^®. ScRNA-seq was performed to analyze and compare the cellular and molecular differences in these models. Results: The analysis revealed that, particularly in the drug-induced fibrosis models, hepatic stellate cells (HSCs), Kupffer cells, and T-cell subsets exhibit distinct regulatory patterns and dynamic remodeling processes across different liver fibrosis models. These findings highlight the heterogeneity of immune responses and extracellular matrix (ECM) remodeling in various models, providing important insights into the complex mechanisms underlying liver fibrosis. Conclusions: The study enhances our understanding of liver fibrosis development and provides valuable insights for selecting the most representative animal models in future research. This comprehensive analysis underscores the importance of model-specific immune responses and ECM remodeling in liver fibrosis. Full article

The diffusion effect of river cooling is critical for mitigating the urban heat island effect in riverside areas and for establishing an urban cooling network. River cooling effect diffusion is influenced by the two-dimensional (2D) and three-dimensional (3D) urban morphology of surrounding areas. However, the characteristics of 2D/3D urban morphology that facilitate efficient river cooling effect diffusion remain unclear. This study establishes a technical framework to analyze river cooling effect diffusion resistance (RCDR) across different urban morphologies, using the Huangpu River waterside area in Shanghai as a case study. Seven urban morphology indicators, derived from both 2D and 3D dimensions, were developed to characterize the river cooling effect diffusion resistance. The relative contributions and marginal effects were analyzed using the Boosted Regression Tree (BRT) model. The study found that (1) river cooling effect diffusion was heterogeneous, with four typical patterns; (2) the Landscape Shape Index (LSI) and Blue-green Space Ratio (BGR) significantly impacted cooling effect diffusion; and (3) optimal cooling effect diffusion occurred when the blue-green space occupancy ratio exceeded 20% and building density ranged from 0.1 to 0.3. This study’s technical framework offers a new perspective on river cooling effect diffusion and heat island mitigation in riverside spaces, with significant practical value and potential for broader application. Full article

Compared to widely used near-infrared OCT (NIR-OCT) systems, visible light OCT (vis-OCT) is an emerging imaging modality that leverages visible light to achieve high-resolution, high-contrast imaging and enables detailed spectroscopic analysis of biological tissues. In this review, we provide an overview of the state-of-the-art technology development and biomedical applications of vis-OCT. We also discuss limitations and future perspectives for advancing vis-OCT. Full article