Search Results (164)

To address multiple disturbance threats such as system anomalies and cyberattacks faced by power systems, an intelligent optimized secure filter method is developed in this paper for state estimation of power systems with the aid of the improved sparrow search algorithm–optimized unscented Kalman filter (ISSA-UKF). Firstly, the problem of insufficient robustness in noise modeling and parameter selection of the conventional unscented Kalman filter (UKF) is analyzed. Secondly, an intelligent optimization method is adopted to adaptively update the UKF’s process and measurement noise covariances in real time, and an ISSA-UKF fusion framework is constructed to improve the estimation accuracy and system response capability. Thirdly, an adaptive weight function based on disturbance observation differences is provided to strengthen the stability of the algorithm in response to abnormal measurements at edge nodes and dynamic system changes. Finally, simulation analysis under a typical power system model shows that compared with the conventional UKF method, the developed ISSA-UKF algorithm demonstrates significant improvements in estimation accuracy, robustness, and dynamic response performance and can effectively cope with non-ideal disturbances that may occur in power systems. Full article

To address the challenges associated with deep ground pressure control at the Sanshandao Gold Mine, a pre-controlled top-to-middle and deep-hole upper and lower-wall goaf subsequent filling mining method was proposed. Three distinct downward mining schemes were designed, the excavation procedure is systematically designed with 18 steps, and the temporal and spatial evolution characteristics of stress and displacement were analyzed using FLAC3D. The results revealed that stress concentration occurred during excavation steps 1–3. As excavation progressed to steps 4–9, the stress concentration area shifted primarily to the filling zones of partially excavated and filled sections. By steps 10–12, the stress concentration in these areas was alleviated. Upon completion of all excavation and filling steps, a small plastic zone was observed, accompanied by an alternating distribution of high and low stress within the backfill. Throughout the excavation process, vertical displacement ranged from 4.42 to 22.73 mm, while horizontal displacement ranged from 1.72 to 3.69 mm, indicating that vertical displacement had a more significant impact on stope stability than horizontal displacement. Furthermore, the fuzzy comprehensive evaluation method was applied to optimize the selection among the three schemes, with Scheme 2 identified as the optimal. Field industrial trials subsequently confirmed the technical rationality and practical applicability of Scheme 2 under actual mining conditions. Full article

Underwater image enhancement (UIE) technology plays a vital role in marine resource exploration, environmental monitoring, and underwater archaeology. However, due to the absorption and scattering of light in underwater environments, images often suffer from blurred details, color distortion, and low contrast, which seriously affect the usability of underwater images. To address the above limitations, a lightweight transformer-based model (LITM) is proposed for improving underwater degraded images. Firstly, our proposed method utilizes a lightweight RGB transformer enhancer (LRTE) that uses efficient channel attention blocks to capture local detail features in the RGB domain. Subsequently, a lightweight HSV transformer encoder (LHTE) is utilized to extract global brightness, color, and saturation from the hue–saturation–value (HSV) domain. Finally, we propose a multi-modal integration block (MMIB) to effectively fuse enhanced information from the RGB and HSV pathways, as well as the input image. Our proposed LITM method significantly outperforms state-of-the-art methods, achieving a peak signal-to-noise ratio (PSNR) of 26.70 and a structural similarity index (SSIM) of 0.9405 on the LSUI dataset. Furthermore, the designed method also exhibits good generality and adaptability on unpaired datasets. Full article

Housekeeping and colony defense behaviors are crucial for social aphids, as they help maintain a habitable living environment and enhance their ecological adaptability. However, over the past decades, numerous studies have focused on housekeeping and colony defense behaviors in species living in primary hosts, but little attention has been given to the secondary host stage. This constrains a deeper understanding of the altruistic behavior of social aphids, as well as the ecological and evolutionary significance of such behavior. We employed indoor video recordings to document and analyze the behaviors displayed by the soldiers of the sugarcane wooly aphid, C. lanigera, on secondary hosts. C. lanigera soldiers continuously patrol around the colony to detect potential threats. When encountering potential threats or obstacles, soldiers actively initiate cleaning behavior. The soldiers use their frontal horns to disengage the hardened honeydew, corpses, or honeydew simulants (rock sugar) that are attached to the surface of host plant leaves. Subsequently, they transport these materials away from the colony using their frontal horns or forelegs, either discarding or flicking them directly. When soldiers identify obstacles—such as predator eggshells—as natural enemies, they attack them with their frontal horns. Our findings contribute to a broader understanding of altruistic behavior in social aphids and the evolutionary success of their sociality. Full article

In biomass estimation based on size-related features, regression models are commonly used to predict fish mass. However, in real-world scenarios, fish are often partially occluded by others, resulting in missing or corrupted features. To address this issue, we propose a robust framework that integrates feature imputation with regression. Missing features are first reconstructed through imputation, followed by regression for biomass prediction. We evaluated various imputation and regression methods and found that the autoencoder achieved the best performance in imputation. Among regression models, SVR, Extra Trees, and MLP performed best in their respective categories. These three models, combined with the autoencoder, were selected to construct the final framework. Experimental results demonstrate that the proposed framework significantly improves performance. For instance, the RMSE of SVR, Extra Trees, and MLP decreased from 21.10 g, 2.49 g, and 18.40 g to 6.53 g, 1.95 g, and 5.09 g, respectively. Full article

Invasive bacteria have caused tremendous losses to global ecosystems and agricultural production, yet effective control measures remain elusive. Plant specialized metabolites are being investigated as an important source of antimicrobial active substances. And Ailanthus altissima is an abundant tree widespread throughout Northeast China. In this study, we identified 21 compounds from A. altissima leaves, including steroids, terpenes, phenolics, and coumarins. Two new steroidal compounds, ailanstigol A (1) and ailanstigol B (2), and one new coumarin (2′R,3′R)-7-(2′,3′,6′-trihydroxy-3′-methylhexyloxy)-6,8-dimethoxycoumarin (3) were isolated. Antibacterial screening revealed that compounds 1 and 2 exhibited inhibitory activity against two invasive bacteria, Xanthomonas oryzae pv. oryzae PXO 71A and PXO 86A and Pseudomonas syringae pv. maculicola ES4326. Further mechanistic screening unveiled that the steroidal compounds 1 and 2 may inhibit bacterial growth and reproduction by reducing cell viability, disrupting the cell membrane and increasing protein leakage, and inhibiting biofilm formation. In summary, our results enriched the known chemical diversity of A. altissima and provided a foundation for investigating the mechanisms by which steroidal compounds inhibit invasive bacterial growth. Full article

To address the challenges of data fragmentation, inconsistent standards, and weak interactivity in oil and gas field surface engineering, this study proposes an intelligent delivery system integrated with three-dimensional dynamic modeling. Utilizing a layered collaborative framework, the system combines optimization algorithms and anomaly detection methods during data processing to enhance the relevance and reliability of high-dimensional data. The model construction adopts a structured data architecture and dynamic governance strategies, supporting multi-project secure collaboration and full lifecycle data management. At the application level, it integrates three-dimensional visualization and semantic parsing capabilities to achieve interactive display and intelligent analysis of cross-modal data. Validated through practical engineering cases, the platform enables real-time linkage of equipment parameters, documentation, and three-dimensional models, significantly improving data integration efficiency and decision-making capabilities. This advancement drives the transformation of oil and gas field engineering toward intelligent and knowledge-driven practices. Full article

To address the issue of rockburst in deep return airways caused by thick, hard sandstone roofs in the Hulusu Coal Mine, this study proposes a deep borehole pressure relief technique based on hydraulic fracturing. The goal is to proactively weaken the hard roof structure and effectively mitigate rockburst hazards. The research integrates numerical modeling, theoretical analytics, and field application to systematically delve into the unstable mechanism of deep hard rock and determine the crack propagation patterns and optimal borehole parameters. Engineering validation was carried out at the 21,103 mining face. Results indicate that when the borehole inclination is 45°, the spacing is 15 m, the diameter is 65 mm, the borehole depth is 24 m over the coal pillar (CP) and 30 m on the operating face, the pressure relief effect is optimal. This configuration effectively forms a pressure relief zone in the roof, significantly reduces surrounding rock stress concentration, and enhances structural stability. Field monitoring shows that the roof energy is released stably through crack propagation, effectively reducing the risk of rockburst. The proposed technique provides theoretical and engineering support for rockburst prevention in deep hard rock mining conditions. Full article

A sufficient number of sensors installed in all structural components is a prerequisite for obtaining the full-field temporal–spatial displacement and is essential for large-scale structure health monitoring. In this paper, a novel lightweight vision-based temporal–spatial deflection measurement method is proposed to measure the full-field temporal–spatial displacement of slender structures. First, the geometric and mechanical properties of slender members are introduced as the priori information to vision-based measurement. Then, a slice template matching model is proposed by deploying a one-dimensional template matching model in every pixel column of each image frame, based on traditional digital image correlation (DIC) method. An indoor experiment was carried out to verify the proposed method, and experiment results show that measurement precision of STMM agrees well with the theory and the laser ranger, with a maximum measurement error of 0.03 pixels and the root-mean-square error (RMSE) of 0.052 mm, for transient beam deflection curve; with the correlation coefficient and coefficient of determination of 0.9994 and 0.9986, for dynamic deflection–time history curves at the middle-span point. Finally, further investigation reveals that brightness inconstancy is the source of STMM measurement error. Full article

Lolium perenne (Poaceae), a perennial forage, has high economic and nutritional value. It is often used as a replacement control for some invasive plants, as it has achieved good ecological and economic effects. However, its control effects, allelochemicals, allelopathic effects, release pathways, and contents are still unclear in the process of L. perenne replacement control of an invasive plant, Ageratina adenophora (Asteraceae). Therefore, it is necessary to reveal the mechanism of L. perenne replacement control of A. adenophora from the perspective of allelopathy. In this study, L. perenne could effectively inhibit the growth of A. adenophora in the competition assay. In addition, seven norsesquiterpenes (1–7) were isolated and identified from the whole plant of L. perenne, and most of the compounds exhibited potent allelopathic effects on the growth of A. adenophora and one model plant (Lactuca sativa, Asteraceae). Moreover, some active compounds were released into the environment through root secretion and rainwater leaching, and their contents were determined by UPLC-MS/MS (Ultra Performance Liquid Chromatography Tandem Mass Spectrometry). Our results elucidated the allelopathic mechanism of L. perenne’s replacement control, A. adenophora, and provided a theoretical basis for the development of norsesquiterpenes from L. perenne. Full article

To investigate the methane adsorption characteristics in different types of kerogen, microscopic models for three kerogen types—sapropelic (Type I), mixed (Type II), and humic (Type III)—were developed in this paper based on the paradigm diagram. Using Materials Studio 2020 software, a combination of molecular dynamics and Monte Carlo adsorption simulations was employed to examine the kerogen from the molecular structure to the cellular structure, with an analysis rooted in thermodynamic theory. The results indicated that the elemental composition of kerogen significantly influenced both the heat of adsorption and the adsorption position, with sulfur (S) having the greatest effect. Specifically, the C-S bond shifted the methane adsorption position horizontally by 0.861 Å and increased the adsorption energy by 1.418 kJ. Among the three types of kerogen crystals, a relationship was observed among the adsorption amount, limiting adsorption energy, and specific adsorption energy, with Type I < Type II < Type III. Additionally, the limiting adsorption energy was greater than the specific adsorption energy. The limiting adsorption energy of Type Ⅲ was only 28.436 kJ/mol, which indicates that methane is physically adsorbed in the kerogen. Regarding the diffusion coefficient, the value of 0.0464 Ų/Ps in the micropores of Type I kerogen was significantly higher than that in Types II and III, though it was much smaller than the diffusion coefficient observed in the macropores. Additionally, adsorption causes volumetric and effective pore volume expansion in kerogen crystals, which occurs in two phases: slow expansion and rapid expansion. Higher types of kerogen require a larger adsorption volume to reach the rapid expansion phase and expand more quickly. However, during the early stage of adsorption, the expansion rate is extremely low, and even a slight shrinkage may occur. Therefore, in shale gas extraction, it is crucial to design the extraction strategy based on the content and adsorption characteristics of the three kerogen types in order to enhance shale gas production and improve extraction efficiency. Full article

Amidst China’s rapid industrialization and deteriorating air quality, emerging evidence suggests a parallel decline in male reproductive health. However, large-scale assessments of pollution-semen quality associations remain scarce. This nationwide multicenter study investigated these relationships among 27,014 Chinese men using high-resolution satellite-derived exposure estimates (PM_2.5, PM₁₀, NO₂, O₃, CO, and SO₂) and generalized linear mixed models (GLMM), adjusting for key demographic confounders. A case-control study involving 5256 cases and 21758 controls used the exposure values of air pollutants 90 days prior to sperm collection for epidemiological exposure analysis reactions to obtain the association between sperm quality and air pollution. This study demonstrates significant associations between increased exposure to regional air pollutants and the risk of substandard semen quality in China. Key findings reveal NO₂’s potential reproductive toxicity, showing a 79.7% increased risk of semen volume abnormalities per 11.34 µg/m³ exposure (OR = 1.797, 95% CI: 1.402–2.302). Susceptibility disparities emerged, with 16.4-fold greater PM_2.5 sensitivity in obese individuals (OR = 1.121 vs. 1.007) and 133% higher PM₁₀ risk in urban residents (OR = 1.342 vs. 1.006). Strikingly, SO₂ exposure at 15% of the WHO 24 h average guideline (6.16 µg/m³) was associated with a 3.8% increase in abnormalities, indicating the challenge of the current safety thresholds. These findings highlight the need for policy reforms, including (1) incorporating reproductive health endpoints into air quality standards, (2) implementing antioxidant interventions for high-risk groups, and (3) strengthening traffic emission controls in urban planning. This study underscores the need for comprehensive strategies to mitigate the impact of air pollution on male reproductive health. Full article

Loquat (Eriobotrya japonica Lindl.) is one of the most important subtropical evergreen fruit trees. However, due to the lack of widely applicable genetic transformation platforms, the research about gene functional characterization and molecular mechanisms is largely confined. In this study, the efficient protocol of protoplast isolation (the enzyme solution composed of 2.4% macerozyme R-10, 4.8% cellulase RS, dissolved in a 0.6 M mannitol solution) and the method of protoplast purification (CPW solution containing 5% sucrose and 11% mannitol) have been achieved with protoplast yields of 12.6 × 10⁶/g·FW, reaching a viability rate of up to 91%. A protoplast transient gene expression system has been established with an efficiency of approximately 40% using GFP reporter gene. Using this reliable and efficient system, the protein localization characteristics of transcription factor EjDELLA, EjbHLH79, and marker gene OsPHT4 were also utilized for further analysis. To our knowledge, this is the first report on establishing an efficient system for protoplast isolation, purification, and transformation of loquat mesophyll. The system reported here will definitely promote rapid progress in breeding, genetic transformation, and molecular research. Full article

The accumulation of cadmium (Cd) and microplastics (MPs) can have major deleterious effects on the health of marine ecosystems and organisms, including the pearl oyster Pinctada fucata martensii. Here, we characterized the effects of Cd and MPs on key biochemical parameters of P. f. martensii via an experiment with various treatments. Pearl oysters were exposed to either only Cd (5 or 50 μg/L), only MPs (5 mg/L), or both Cd and MPs for 2 d, and this was followed by a 5-day recovery period. Measurements of the activities of lipase, amylase, protease, T-ATPase, catalase, glutathione peroxidase, acid phosphatase, and alkaline phosphatase enzymes, as well as the malondialdehyde content in the hepatopancreas, were made at various time points during the experiment. Metabolomics analysis of the gills was also performed. Significant interactions between time and treatment on lipase, protease, and catalase activities were observed. However, no significant effect of time–treatment interactions on amylase and T-ATPase activities was observed. Enzyme activities varied among groups both during the exposure period (6 to 48 h) and the recovery period. The malondialdehyde content was also increased throughout the experiment. Pathway analysis indicated that the purine metabolism, glycerophospholipid metabolism, nucleotide metabolism, arachidonic acid metabolism, neuroactive ligand–receptor interaction, and linoleic acid metabolism pathways were the most commonly affected under different treatments. The findings of our study revealed the differential effects of exposure time and treatment on enzyme activities and metabolites and their respective pathways. Our findings enhance our understanding of the biochemical responses of the pearl oyster P. f. martensii to environmental stressors, particularly Cd and MPs. Full article

Ambient air pollution has been associated with gestational diabetes mellitus (GDM); however, evidence regarding trimester-specific effects from China remains limited. This case–control study study analyzed data from pregnant women who delivered in Wuhan, China, between 2017 and 2022 (164 GDM cases and 731 controls), integrating geographic information, air quality measurements, and maternal characteristics. Using Inverse Distance Weighting interpolation and Generalized Linear Mixed Models (GLMM), we assessed associations between air pollutant exposure and GDM across different gestational periods. Results indicated that NO₂ demonstrated the strongest association with GDM compared to other pollutants. Specifically, increased NO₂ exposure was consistently associated with higher GDM risk throughout pregnancy. PM_2.5 exposure showed significant associations during early and mid-pregnancy, while SO₂ exposure was significantly associated with GDM risk exclusively in early pregnancy. Sensitivity analyses stratified by urban maternity status and maternal age revealed the stability of the study’s findings. These findings underscore the importance of reducing air pollution exposure during pregnancy and implementing targeted interventions for high-risk populations to prevent GDM development. Full article