Search Results (230)

The detection of coils in reservoir areas is part of the environmental perception technology of unmanned cranes. In order to improve the perception ability of unmanned cranes to include environmental information in reservoir areas, a method of automatic detection of coils based on two-dimensional LiDAR dynamic scanning is proposed, which realizes the detection of the position and attitude of coils in reservoir areas. This algorithm realizes map reconstruction of 3D point cloud by fusing LiDAR point cloud data and the motion position information of intelligent cranes. Additionally, a processing method based on histogram statistical analysis and 3D normal curvature estimation is proposed to solve the problem of over-segmentation and under-segmentation in 3D point cloud segmentation. Finally, for segmented point cloud clusters, coil models are fitted by the RANSAC method to identify their position and attitude. The accuracy, recall, and F1 score of the detection model are all higher than 0.91, indicating that the model has a good recognition effect. Full article

This study integrated non-targeted metabolomics and transcriptomics to investigate dynamic changes in Antheraea pernyi pupae across five developmental stages. Metabolomic analysis identified 1246 metabolites, primarily organic acids, lipids, heterocyclic compounds, and oxygen-containing organics. Principal component analysis revealed stage-specific metabolic profiles: amino acid derivatives (pyruvate, proline, lysine) declined, while pyrimidines (cytidine, uridine, β-alanine) and monosaccharides (glucose, mannose) increased. 18β-glycyrrhetinic and ursolic acids accumulated significantly in the middle and late stages. Transcriptomic analysis identified 7230 differentially expressed genes (DEGs), with 366, 1705, and 5159 significantly differentially expressed genes in the T1, T3, and T5 comparison groups, respectively. KEGG enrichment highlighted ABC transporters, amino acid/pyrimidine metabolism, and tyrosine pathways as developmentally critical, with aminoacyl-tRNA biosynthesis upregulated in later phases. Integrated multi-omics analysis revealed coordinated shifts in metabolites and genes across developmental phases, reflecting dynamic nutrient remodeling during pupal maturation. This study systematically delineates the molecular transitions driving pupal development in Antheraea pernyi pupae, uncovering conserved pathway interactions and mechanistic insights into nutrient metabolism. These findings provide a scientific foundation for leveraging pupal resources in functional food innovation and bioactive compound discovery for pharmaceutical applications. Full article

Natural gas storage is an effective solution to address the energy supply–demand imbalance, and underground gas storage (UGS) is a primary method for storing natural gas. The overarching goal of this study is to monitor and analyze surface deformation at the Hutubi underground gas storage facility in Xinjiang, China, which is the largest gas storage facility in the country. This research aims to ensure the stable and efficient operation of the facility through long-term monitoring, using remote sensing data and advanced modeling techniques. The study employs the SBAS-InSAR method, leveraging Synthetic Aperture Radar (SAR) data from the TerraSAR and Sentinel-1 sensors to observe displacement time series from 2013 to 2024. The data is processed through wavelet transformation for denoising, followed by the application of a Gray Wolf Optimization (GWO) algorithm combined with Variational Mode Decomposition (VMD) to decompose both surface deformation and gas pressure data. The key focus is the development of a high-precision predictive model using a Gated Recurrent Unit (GRU) network, referred to as GWO-VMD-GRU, to accurately predict surface deformation. The results show periodic surface uplift and subsidence at the facility, with a notable net uplift. During the period from August 2013 to March 2015, the maximum uplift rate was 6 mm/year, while from January 2015 to December 2024, it increased to 12 mm/year. The surface deformation correlates with gas injection and extraction periods, indicating periodic variations. The accuracy of the InSAR-derived displacement data is validated through high-precision GNSS data. The GWO-VMD-GRU model demonstrates strong predictive performance with a coefficient of determination (R²) greater than 0.98 for the gas well test points. This study provides a valuable reference for the future safe operation and management of underground gas storage facilities, demonstrating significant contributions to both scientific understanding and practical applications in underground gas storage management. Full article

Model updating is a challenging task with regard to maintaining the performance of non-destructive detection models while using hyperspectral imaging techniques for detecting the internal quality of fresh fruits like blueberries. Different sample batches and differences in hyperspectral image acquisition environments may lead to a significant decline in the performance of hyperspectral detection models. This study investigated the transferability of a hyperspectral model for the quantitating soluble solid content of blueberries across different batches for two harvest years. Hyperspectral images and SSC values of blueberries were collected from two batches, including 364 samples from 2024 and 175 samples from 2025. The differences between SSC measurements and spectral data across these two batches were analyzed. Based on the sample dataset of the year 2024, a high-performance quantitative model for detecting SSC values was established by combining it with partial least squares regression (PLSR) and competitive adaptive reweighted sampling (CARS). This high-performance model could achieve a high determination coefficient (${\mathrm{R}}_{\mathrm{P}}^2$) of 0.8965 and a low root mean square error of prediction (RMSEP) of 0.3707 °Brix. Using the sample dataset for the year 2025, the hyperspectral model was updated by the semi-supervised parameter-free calibration enhancement (SS-PFCE) algorithm. The updated model performed better than those established using individual datasets from 2024 and 2025, and obtained an ${\mathrm{R}}_{\mathrm{P}}^2$ of 0.8347 and an RMSEP of 0.4930 °Brix. This indicates that the calibration transfer strategy is superior in improving hyperspectral model performance. This study demonstrated that the SS-PFCE algorithm, as a calibration transfer strategy, could effectively improve the transferability of the established model for detecting the SSC of blueberries across different sample batches. Full article

Background: This study intended to fully assess the predictive efficiency of different clinical laboratory parameters for the mortality risk in severe fever with thrombocytopenia syndrome (SFTS). Methods: We systematically searched the Web of Science, PubMed, Cochrane Library, and Embase up to 13 December 2024 for studies on the association of laboratory parameters with SFTS mortality. Two investigators were independently responsible for the study screening and data extraction, and they assessed the study quality using the Newcastle–Ottawa Scale (NOS). Stata17.0 was adopted for the meta-analyses. Results: We finally included 33 observational studies involving 9502 participants (1799 deaths and 7703 survivors). The results showed that increases in the viral load (odds ratio (OR) 1.93, 95% confidence interval (CI) 1.56–2.38), neutrophil-to-lymphocyte ratio (hazard ratio (HR) 1.31, 95% CI 1.13–1.51), neutrophil percentage (HR 1.02, 95% CI 1.01–1.03), white blood cells (HR 1.06, 95% CI 1.01–1.11), activated partial thromboplastin time (OR 1.07, 95% CI 1.04–1.09), prothrombin time (OR 1.31, 95% CI 1.03–1.65), creatine kinase-myocardial band (OR 1.01, 95% CI 1.01–1.02), and procalcitonin (HR 1.27, 95% CI 1.10–1.47) greatly increased the SFTS mortality, while decreases in the lymphocyte percentage (HR 0.96, 95% CI 0.94–0.98), platelets (HR 0.98, 95% CI 0.97–0.99), and albumin (HR 0.91, 95% CI 0.86–0.96) also greatly increased the SFTS mortality; the results were all statistically significant (p < 0.05). Conclusion: Abnormalities of laboratory parameters (e.g., viral load, blood routine, coagulation, multi-organ dysfunction, and inflammation indicators) are good predictors of SFTS mortality, which can provide valuable references in clinical practice. Full article

Research based on the theory of embodied cognition has revealed that the vertical position of target information in space influences individuals’ construal level, which in turn affects their ethical decision-making. However, previous studies have shown inconsistent effects of construal level on ethical decision-making, which may be moderated by factors such as the manipulation methods of construal level and the salience of trade-offs. This study examines how manipulating the vertical position (high/low) of target information in space—thereby altering perceived spatial distance—impacts ethical decision-making through the lens of embodied cognition, using eye-tracking technology. Experiment 1 isolated the effect of target verticality, while Experiment 2 introduced trade-off salience as an additional factor. Eye-tracking metrics in Experiment 1 revealed that lower target positions significantly increased late-stage cognitive processing difficulty. Experiment 2 demonstrated an interaction between target position and trade-off salience in ethical decision-making. These findings suggest that spatial positioning influences cognitive processing via construal level, with its effects on ethical decision-making moderated by trade-off cues. In summary, this study reveals the significant influence of trade-off salience as a contextual cue in individuals’ ethical decision-making while also providing an embodied cognition perspective to inform decision behavior in human–computer interaction contexts. Full article

To successfully prepare cellulose hydrogels through a dissolution–regeneration process, 60 wt% LiBr aqueous solution was used as a green solvent. Carboxyl groups were precisely introduced onto the surface of the cellulose hydrogels through a TEMPO-mediated oxidation reaction, while the three-dimensional network structure and open pore morphology were completely retained. This modification strategy significantly enhanced the loading capacity of the hydrogels with copper nanoparticles (Cu NPs). The experimental results show that the LiBr aqueous solution can efficiently dissolve cellulose, and the TEMPO oxidation introduces carboxyl groups without destroying the stability of the hydrogels. Cu NPs are uniformly dispersed and highly loaded on the surface of the hydrogel because of the anchoring effect of the carboxyl groups. Cu NP-loaded hydrogels exhibit excellent catalytic activity in the NaBH₄ reduction of 4-nitrophenol (4-NP). Cu NP-loaded hydrogels maintain their complete structure and good catalytic performance after five consecutive cycles. Moreover, Cu NP-loaded hydrogels demonstrate high efficiency in degrading organic dyes such as methyl orange and Congo red. This study successfully developed efficient, low-cost, and environmentally friendly Cu NP-loaded hydrogel catalysts through the synergistic effect of LiBr green solvent and TEMPO oxidation modification, providing a feasible alternative to noble metal catalysts. Full article

Stroke-induced hand dysfunction substantially impairs patients’ quality of life, creating an urgent need for portable, adaptive rehabilitation devices. This study introduces a smart rehabilitation glove actuated by shape-memory alloy (SMA) wires, leveraging their high power-to-weight ratio, controllable strain recovery, and reversible phase transformation to overcome the limitations of conventional motor-driven or pneumatic gloves. The glove incorporates SMA-based actuation units achieving 50 mm contraction (5% strain) within 7 s, enabling finger flexion to ~34° for personalized rehabilitation protocols. A mobile application provides wireless regulation of SMA actuation modes and facilitates real-time telemedicine consultations. The prototype demonstrates an ultra-lightweight, compact design enabled by SMA’s intrinsic properties, offering a promising solution for home-based post-stroke rehabilitation. This work establishes the transformative potential of SMAs in wearable biomedical technologies. Full article

At present, the fitting process of deep groove ball bearings has the problems of low manual production efficiency and poor performance of fitted bearings. For the automatic bearing fitting production line, there are some problems, such as a low success rate of fitting and easy interruption of the production process. In this article, two grouping methods, the equidistant grouping method and the equal probability grouping method, are proposed. We establish a dimensional deviation distribution model by measuring the dimensional deviation of deep groove ball bearing components. Using the bearing component dimensional deviation distribution model, we carry out the equidistant grouping method and the equal probability grouping method to fit the bearing component. And the influence of the traditional bearing fitting method and the two grouping methods on the success rate of deep groove ball bearing fitting is compared and analyzed. This research found that the traditional bearing fitting method is easy to fall into local optimization, and too many unmatched components which have a larger dimensional deviation lead to the interruption of the fitting process. The success rate of the traditional fitting method is lower than grouping methods. For the two grouping methods, the equal probability grouping method can ensure that the probability of each group of components entering the automatic production line is the same. Compared with the equidistant grouping method, it is easier to make it possible to fit the bearing component. The equal probability grouping method is recommended. Full article

With the intensification of human activities, the water resource environment in the karst mountainous area of central Shandong has undergone significant changes, directly manifested in the cessation of karst spring flows and the occurrence of karst collapses within the spring basin in the Laiwu Basin. To support the scientific development and management of karst water, this study utilizes comprehensive analysis and deuterium-oxygen isotope test data from surveys and sampling of 20 typical karst springs conducted between 2016 and 2018. By integrating mathematical statistics, correlation analysis, and ion component ratio methods, the study analyzes the genesis, hydrochemical ion component sources, and controlling factors of typical karst springs in the Laiwu Basin. The results indicate that the genesis of karst springs in the Laiwu Basin is controlled by three factors: faults, rock masses, and lithology, and can be classified into four types: water resistance controlled by lithology, by faults, by basement, and by rock mass. The karst springs are generally weakly alkaline freshwater, with the main ion components being HCO₃⁻ and Ca²⁺, accounting for approximately 55.02% and 71.52% of the anion and cation components, respectively; about 50% of the sampling points have a hydrochemical type of HCO₃·SO₄-Ca·Mg. Stable isotope (δ¹⁸O and δD) results show that atmospheric precipitation is the primary recharge source for karst springs in the Laiwu Basin. There are varying degrees of evaporative fractionation and water–rock interaction during the groundwater flow process, resulting in significantly higher deuterium excess (d-excess) in the sampling points on the southern side of the basin compared to the northern side, indicating clear differentiation. The hydrochemical composition of the karst groundwater system is predominantly governed by water–rock interactions during flow processes and anthropogenic influences. Carbonate dissolution (primarily calcite) serves as the principal source of HCO₃⁻, SO₄²⁻, Ca²⁺, and Mg²⁺, while evaporite dissolution and reverse cation exchange contribute to the slight enrichment of Ca²⁺ and Mg²⁺ alongside depletion of Na⁺ and K⁺ in spring waters. Saturation indices (SI) reveal that spring waters are saturated with respect to gypsum, aragonite, calcite, and dolomite, but undersaturated for halite. The mixing of urban domestic sewage, agricultural planting activities, and the use of manure also contributes to the formation of Cl⁻ and NO₃⁻ ions in karst springs. Full article

As the global food crisis worsens, enhancing crop yields on saline–alkali soils has become a critical measure for ensuring global food security. Wheat (Triticum aestivum L.), one of the world’s most important staple crops, is particularly sensitive to phosphorus availability, making appropriate phosphorus fertilization a key and manageable strategy to optimize yield. Although many studies have explored phosphorus fertilization strategies, most have focused on non-saline soils or generalized conditions, leaving a critical gap in understanding how phosphorus application affects wheat yield, soil nutrient dynamics, and nutrient uptake efficiency under saline–alkali stress. Therefore, further investigation is required to establish phosphorus management practices specifically adapted to saline–alkali environments for sustainable wheat production. To address this gap, the experiment was designed with varying phosphorus fertilizer application rates based on P₂O₅ content (0, 60 kg/hm², 120 kg/hm², 180 kg/hm², and 240 kg/hm²), considering only the externally applied phosphorus without accounting for the inherent phosphorus content of the soil. The results indicated that as the phosphorus application rate increased, the wheat yield first increased and then decreased. The highest yield (6355 kg·hm⁻²) was achieved when the phosphorus application rate reached 120 kg/hm², with an increase of 47.2–63.5% compared to the control (no fertilizer). Similarly, biomass, thousand-grain weight, and the absorption of nitrogen, phosphorus, and potassium in both straw and grains exhibited the same increasing-then-decreasing trend. Mechanistic analysis revealed that phosphorus fertilization enhanced soil alkali–hydrolyzable nitrogen, available phosphorus, and available potassium, thereby promoting nutrient uptake and ultimately improving grain yield. The innovations of this study lie in its focus on phosphorus management specifically under saline–alkali soil conditions, its integration of soil nutrient changes and plant physiological responses, and its identification of the optimal phosphorus application threshold for balancing yield improvement and nutrient efficiency. These findings provide a scientific basis for refining phosphorus fertilization strategies to sustainably boost wheat productivity in saline–alkali environments. Full article

In the cotton fields in Xinjiang, residual film is present in the soil for a long period of time, leading to a decrease in the tensile strength of the residual film and increasing the difficulty of recycling. Existing technologies for residual film recovery focus on mechanical properties and ignore the dragging and tearing of residual film by cotton stubble. The effect of cotton straw–root stubble on residual film recovery can only be better determined by appropriate machine operating parameters, which are essential to improving residual film recovery. Through analyses of the pickup device, key parameters were identified, and a model was built by combining the FEM and SPH algorithms to simulate the interaction of nail teeth, residual film, soil and root stubble. The simulation revealed the force change law of residual film in root stubble-containing soil and the influence of root stubble. By simulating the changes in the characteristics of the residual film during the process, the optimum operating parameters for the nail teeth were determined: a forward speed of 1849.57 mm/s, a rotational speed of 5.5 r/s and a soil penetration angle of 30°. Under these optimized conditions, the maximum shear strain, pickup height (maximum deformation) and average peak stress of the residual film were 1293, 363.81 mm and 3.42 MPa, respectively. Subsequently, field trials were conducted to verify the change in the impact of the nail teeth at the optimized speed on the recovery of residual film in plots containing root stubble. The results demonstrated that when the root stubble height was 5–8 cm, the residual film averaged a recovery rate of 89.59%, with a dragging rate of only 4.10% at crossings. In contrast, 8–14 cm stubble plots showed an 82.86% average recovery and an 11.91% dragging rate. In plots with a root stubble height of 5–8 cm, compared with plots with a root stubble height of 8–14 cm, the recovery rate increased by 6.73%, and the dragging rate of residual film on root stubble decreased by 7.81%. The percentage of entangled residual film out of the total unrecovered film was 30.10% lower in the 5–8 cm stubble plots than in the 8–14 cm stubble plots. It was confirmed that the effect of cotton root stubble on residual film recovery could be reduced under appropriate machine operating parameters. This provides strong support and a theoretical and practical basis for future research on the correlation between root stubble and residual film and how to improve the residual film recovery rate. Full article

This study delves into the ecological implications of diverse fishery patterns on aquatic ecosystems, centering on environmental parameters, species richness, and nutrient dynamics. Using the ecological fishery management model of Yangming Lake as a case, it evaluates its influence on water quality improvement, species diversity promotion, and ecosystem stability maintenance. From 2018 to 2022, the Shannon–Wiener index in Yangming Lake increased by 17.34%, and water quality significantly improved, with phytoplankton biomass decreasing by 95.5%, total nitrogen content dropping by 33.69%, and permanganate index declining by 30.75%. Although ecological fisheries demonstrate certain effectiveness in tackling invasive species, further in-depth research is needed. This study emphasizes the importance of striking a balance between fishery development and ecological protection, in line with the United Nations Food and Agriculture Organization’s “blue transformation” strategy. Our findings offer valuable insights for sustainable fisheries development and highlight the necessity of customized management strategies to protect biodiversity and ecosystem resilience. Future research will focus on exploring the long-term ecological effects of ecological fisheries and the role of native carnivorous fish in controlling invasive species. Full article

This study presents a novel method for altering the surface properties of carbon fiber (CF) to improve the bonding strength at its interface with norbornene–polyimide (PI-NA) resin. Cobaltous sulfide (CoS) nanosheets were successfully synthesized on the CF surface using a solvothermal method combined with a chemical sulfidation process. The modification increased the specific surface area and surface roughness of the CFs, enhancing the interfacial mechanical lock-in effect between the fibers and the resin. This facilitated effective load transfer between the resin and the fibers, thereby significantly improving the interfacial strength of CF-reinforced polymers (CFRPs). The experimental findings showed that after solvothermal treatment with a precursor solution of 0.006 g/mL for 4.5 h, vertical CoS nanosheets were successfully grown on the CF surface. The interlaminar shear strength (ILSS) and interfacial shear strength (IFSS) of the modified CF reached 60.03 MPa and 83.27 MPa, respectively, representing increases of 19.49% and 27.01% compared to untreated fiber composites. This research demonstrates that this method is simple to apply and promising in terms of industrial scalability. Full article