Search Results (2,308)

Accurate and efficient next-event prediction in wind-turbine maintenance processes (WTMPs) is crucial for proactive resource planning and early fault detection. However, existing deep-learning-based prediction approaches often encounter performance challenges during the training phase, particularly when dealing with large-scale datasets. To address this challenge, this paper proposes a Sampling-based Next-event Prediction (SaNeP) approach for WTMPs. More specifically, a novel event log sampling technique is proposed to extract a representative sample from the original WTMP training log by quantifying the importance of individual traces. The trace prefixes of the sampled logs are then encoded using one-hot encoding and fed into six deep-learning models designed for next-event prediction. To demonstrate the effectiveness and applicability of the proposed approach, a real-life WTMP event log collected from the HuangYi wind farm in Hebei Province, China, is used to evaluate the prediction performance of various sampling techniques and ratios across six predictive models. Experimental results demonstrate that, at a 30% sampling ratio, SaNeP combined with the LSTM model achieves a 3.631-fold improvement in prediction efficiency and a 6.896% increase in prediction accuracy compared to other techniques. Full article

The Xiaobaihegou fluorite deposit is located in the southwest of the Altyn-Tagh Orogen, NW China. However, the provenance, thermodynamic properties, and enrichment mechanisms of the ore-forming fluids in this deposit remain unclear. Fluorite mineralization primarily occurs in the vicinity of the contact zone between the granite and the wall rocks. The zircon U-Pb age of the alkali-feldspar granite in the Xiaobaihegou fluorite deposit is 482.3 ± 4.1 Ma. The ore-hosting lithologies are mainly calcareous rock series of the Altyn Group. The ore bodies are controlled by NE-trending faults and consist primarily of veined, brecciated, massive, and banded ores. The ore mineral assemblage is primarily composed of calcite and fluorite. The rare earth element (REE) patterns of fluorite and calcite in the Xiaobaihegou deposit exhibit right-dipping LREE enrichment with distinct negative Eu anomalies, which closely resemble those of the alkali-feldspar granite. This similarity suggests that the REE distribution patterns of fluorite and calcite were likely inherited from the pluton. The ore-forming process can be divided into an early stage and a late stage. The massive ores formed in the early stage contain mainly gas-rich two-phase fluid inclusions and CO₂-bearing three-phase inclusions, with homogenization temperatures ranging from 235 °C to 426 °C and salinities from 28.59% to 42.40% NaCl equivalent. In the late stage, brecciated and stockwork ores were formed. They host liquid-rich two-phase and gas-rich two-phase fluid inclusions, with homogenization temperatures ranging from 129 °C to 350 °C and salinities from 0.88% to 21.61% NaCl equivalent. The results of hydrogen and oxygen isotope studies indicate that the ore-forming fluids were derived from a mixture of magmatic–hydrothermal and meteoric water. Fluorite precipitation in the early stage was mainly due to the mixing of magmatic–hydrothermal solution and meteoric water, as well as a water–rock reaction. In the late stage, fluid mixing further occurred, resulting in a decrease in temperature and the formation of brecciated and stockwork ores. The ⁸⁷Sr/⁸⁶Sr and ¹⁴³Nd/¹⁴⁴Nd ratios of fluorite from the deposit range from 0.71033 to 0.71272 and 0.511946 to 0.512073, respectively, indicating that the ore-forming material originates from the crust. Based on the ore-forming characteristics, it is proposed that Ca may be primarily leached from the strata formation, while F may predominantly originate from magmatic–hydrothermal solutions. The formation of fluorite deposits is closely related to the transition of the Central Altyn-Tagh Block and Qaidam Block from a compressional orogenic environment to an extensional tectonic environment. Full article

Three-dimensional trench electrode silicon detectors play an important role in particle physics research, nuclear radiation detection, and other fields. A novel polysilicon-fill-strengthened etch-through 3D trench electrode detector is proposed to address the shortcomings of traditional 3D trench electrode silicon detectors; for example, the distribution of non-uniform electric fields, asymmetric electric potential, and dead zone. The physical properties of the detector have been extensively and systematically studied. This study simulated the electric field, potential, electron concentration distribution, complete depletion voltage, leakage current, capacitance, transient current induced by incident particles, and weighting field distribution of the detector. It also systematically studied and analyzed the electrical characteristics of the detector. Compared to traditional 3D trench electrode silicon detectors, this new detector adopts a manufacturing process of double-side etching technology and double-side filling technology, which results in a more sensitive detector volume and higher electric field uniformity. In addition, the size of the detector unit is 120 µm × 120 µm × 340 µm; the structure has a small fully depleted voltage, reaching a fully depleted state at around 1.4 V, with a saturation leakage current of approximately $4.8\times {10}^{-10}\mathrm{A}$, and a geometric capacitance of about 99 fF. Full article

Smart structures with topological configurations that integrate perception and actuation have complex geometric features. The simplification of these features can lead to deviations in dynamic characteristics, making it difficult to establish an accurate dynamic model. Uncertainties, such as material nonlinearity, hysteresis in elastic deformation, and external disturbances, affect the trajectory tracking accuracy of the smart structure’s actuation function. This paper proposes a modeling method that combines finite element unit bodies and orthogonal characteristic mode reduction to construct an accurate dynamic model of the smart structure and design an adaptive backstepping controller. Nonlinear dynamic equations are derived through a finite element analysis of the structure, and the orthogonal characteristic mode reduction method is employed to reduce computational complexity while ensuring model accuracy. An adaptive backstepping controller is designed to mitigate model uncertainties and achieve precise trajectory tracking control. Simulation and experimental results demonstrate that the proposed method can effectively handle the nonlinearity and modeling errors of smart structures, achieving high-precision trajectory tracking and verifying the accuracy of the dynamic model as well as the robustness of the controller. Full article

Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. The impressive superpixel generation approaches can improve the efficiency of the subsequent classification task and restrain the influence of the speckle noise to an extent. Most of the classical PolSAR superpixel generation approaches use the features extracted manually and even only consider the pseudocolor images. They do not make full use of polarimetric information and do not necessarily lead to good enough superpixels. The deep learning methods can extract effective deep features but they are difficult to combine with superpixel generation to achieve true end-to-end training. Addressing the above issues, this study proposes an end-to-end fully convolutional superpixel generation network for PolSAR images. It integrates the extraction of polarization information features and the generation of PolSAR superpixels into one step. PolSAR superpixels can be generated based on deep polarization feature extraction and need no traditional clustering process. Both the performance and efficiency of generations of PolSAR superpixels can be enhanced effectively. The experimental results on various PolSAR datasets show that the proposed method can achieve impressive superpixel segmentation by fitting the real boundaries of different types of ground objects effectively and efficiently. It can achieve excellent classification performance by connecting a very simple classification network, which is helpful to improve the efficiency of the subsequent PolSAR image classification tasks. Full article

Sulfur fumigation (SF), acid dipping (HCl treatment, HAT), and their combination (SF+HAT) are common methods for long-term preservation and color protection of litchi. However, their effects on the metabolic profile of the litchi pericarp have not been investigated. SF resulted in a yellowish-green pericarp by up-regulating lightness (L*), b*, C*, and h° but down-regulating total anthocyanin content (TAC) and a*, while HAT resulted in a reddish coloration by up-regulating a*, b*, and C* but down-regulating L*, h°, and TAC. SF+HAT recovered reddish color with similar L*, C* to SF but a*, b*, h°, and TAC between SF and HAT. Differential accumulated metabolites (DAMs) detected in HAT (vs. control) were more than those in SF (vs. control), but similar to those in SF+HAT (vs. control). SF specifically down-regulated the content of cyanidin-3-O-rutinoside, sinapinaldehyde, salicylic acid, and tyrosol, but up-regulated 6 flavonoids (luteolin, kaempferol-3-O-(6″-malonyl)galactoside, hesperetin-7-O-glucoside, etc.). Five pathways (biosynthesis of phenylpropanoids, flavonoid biosynthesis, biosynthesis of secondary metabolites, glutathione metabolism, and cysteine and methionine metabolism) were commonly enriched among the three treatments, which significantly up-regulated sulfur-containing metabolites (mainly glutathione, methionine, and homocystine) and down-regulated substrates for browning (mainly procyanidin B2, C1, and coniferyl alcohol). These results provide metabolic evidence for the effect of three treatments on coloration and storability of litchi. Full article

FeAl intermetallic compounds exhibit high application potential in high-voltage transmission lines to withstand external forces such as powerlines’ own gravity and wind force. The ordered crystal structure in FeAl intermetallic compounds endows materials with high strength, but the remarkable brittleness at room temperature restricts engineering applications. This contradiction is essentially closely related to the deformation mechanism at the nanoscale. Here, we performed molecular dynamics simulations to reveal anomalous grain size effects and deformation mechanisms in nanocrystalline FeAl intermetallic material. Models with grain sizes ranging from 6.2 to 17.4 nm were systematically investigated under uniaxial tensile stress. The study uncovers a distinctive inverse Hall-Petch relationship governing flow stress within the nanoscale regime. This behavior stems from high-density grain boundaries promoting dislocation annihilation over pile-up. Crucially, the material exhibits anomalous ductility at ultra-high strain rates due to stress-induced phase transformation dominating the plastic deformation. The nascent FCC phase accommodates strain through enhanced slip systems and inherent low stacking fault energy with the increasing phase fraction paralleling the stress plateau. Nanoconfinement suppresses the propagation of macroscopic defects while simultaneously suppressing room-temperature brittle fracture and inhibiting the rapid phase transformation pathways at extreme strain rates. These findings provide new theoretical foundations for designing high-strength and high-toughness intermetallic nanocompounds. Full article

Variable-thrust liquid rocket engines are essential for precision landing in deep-space exploration, reusable launch vehicle recovery, high-accuracy orbital maneuvers, and emergency obstacle evasions of space drones. However, with the increasingly complex space missions, challenges remain with the development of different technical schemes. In view of these issues, this paper systematically reviews the technology’s evolution through mechanical throttling, electromechanical precision regulation, and commercial space-driven deep throttling. Then, the development of key variable thrust technologies for liquid rocket engines is summarized from the perspective of thrust regulation and control strategy. For instance, thrust regulation requires synergistic flow control devices and adjustable pintle injectors to dynamically match flow rates with injection pressure drops, ensuring combustion stability across wide thrust ranges—particularly under extreme conditions during space drones’ high-maneuver orbital adjustments—though pintle injector optimization for such scenarios remains challenging. System control must address strong multivariable coupling, response delays, and high-disturbance environments, as well as bottlenecks in sensor reliability and nonlinear modeling. Furthermore, prospects are made in response to the research progress, and breakthroughs are required in cryogenic wide-range flow regulation for liquid oxygen-methane propellants, combustion stability during deep throttling, and AI-based intelligent control to support space drones’ autonomous orbital transfer, rapid reusability, and on-demand trajectory correction in complex deep-space missions. Full article

Deep space Color Remote Sensing Images (DCRSIs) are of great significance in reconstructing the three-dimensional appearance of celestial bodies. Among them, deep space color restoration, as a means to ensure the authenticity of deep space image colors, has significant research value. The existing deep space color restoration methods have gradually evolved into a joint restoration mode that integrates color images and spectrometers to overcome the limitations of on-orbit calibration plates; however, there is limited research on theoretical models for this type of method. Therefore, this article begins with the physical process of deep space color imaging, gradually establishes a color imaging spectral model, and proposes a new color restoration method for the color restoration of Mars remote sensing images. The experiment verifies that our proposed method can significantly reduce color deviation, achieving an average of 8.43 CIE DE 2000 color deviation units, a decrease of 2.63 (23.78%) compared to the least squares method. The color deviation decreased by 21.47 (71.81%) compared to before restoration. Hence, our method can improve the accuracy of color restoration of DCRSIs in space orbit. Full article

Glutamate dehydrogenase (GDH) is ubiquitous in organisms and crucial for amino acid metabolism, energy production, and redox balance. The gdhA and gudB genes encoding GDH were identified in Bacillus altitudinis AS19 and shown to be regulated by iron. However, their functions remain unclear. In this study, gdhA and gudB were analyzed using bioinformatics tools, such as MEGA, Expasy, and SWISS-MODEL, expressed with a prokaryotic expression system, and the induction conditions were optimized to increase the yield of soluble proteins. Phylogenetic analysis revealed that GDH is evolutionarily conserved within the genus Bacillus. GdhA and GudB were identified as hydrophobic proteins, not secreted or membrane proteins. Their structures were primarily composed of irregular coils and α-helices. SWISS-MODEL predicts GdhA to be an NADP-specific GDH, whereas GudB is an NAD-specific GDH. SDS-PAGE analysis showed that GdhA was expressed as a soluble protein after induction with 0.2 mmol/L IPTG at 24 °C for 16 h. GudB was expressed as a soluble protein after induction with 0.1 mmol/L IPTG at 16 °C for 12 h. The proteins were confirmed by Western blot and mass spectrometry. The enzyme activity of recombinant GdhA was 62.7 U/mg with NADPH as the coenzyme. This study provides a foundation for uncovering the functions of two GDHs of B. altitudinis AS19. Full article

Adapting Large Language Models (LLMs) to specialized domains like geriatric care remains a significant challenge due to the limited availability of domain-specific data and the difficulty of achieving efficient yet effective fine-tuning. Current methods often fail to effectively harness domain-specific causal insights, which are crucial for understanding and solving complex problems in low-resource domains.To address these challenges, we propose Causality-Aware, Parameter-Efficient Learning (CPEL), a novel framework that leverages domain-specific causal relationships to guide a multi-layer, parameter-efficient fine-tuning process for more effective domain adaptation. By embedding causal reasoning into the model’s adaptation pipeline, CPEL enables efficient specialization in the target domain while maintaining strong task-specific performance. Specifically, the Causal Prompt Generator of CPEL extracts and applies domain-specific causal structures, generating adaptive prompts that effectively guide the model’s learning process. Complementing this, the MPEFT module employs a dual-adapter mechanism to balance domain-level adaptation with downstream task optimization. This cohesive design ensures that CPEL achieves resource efficiency while capturing domain knowledge in a structured and interpretable manner. Based on this framework, we delved into its application in the field of geriatric care and trained a specialized large language model (Geriatric Care LLaMA) tailored for the aged-care domain, leveraging its capacity to efficiently integrate domain expertise. Experimental results from question-answering tasks demonstrate that CPEL improves ROUGE scores by 9–14% compared to mainstream LLMs and outperforms frontier models by 1–2 points in auto-scoring tasks. In summary, CPEL demonstrates robust generalization and cross-domain adaptability, highlighting its scalability and effectiveness as a transformative solution for domain adaptation in specialized, resource-constrained fields. Full article

Hemolin has been identified as a crucial immune gene in insect immune defense. The silkworm is susceptible to infections by pathogenic microorganisms when reared on artificial diets. In this study, through comparative analysis of the expression patterns of BmHemolin in silkworms fed on mulberry leaves and artificial diets, we found that the expression of BmHemolin was significantly upregulated in silkworms reared on artificial diets, and this upregulation was highly likely induced by pathogenic microorganisms. Further interaction analysis revealed that BmHemolin could bind to pathogenic microorganisms and form aggregates. Meanwhile, BmHemolin enhanced the melanization and aggregation of hemocytes. Subsequent in vitro antibacterial experiments showed that BmHemolin had the ability to inhibit the growth of Escherichia coli. In vivo clearance experiments demonstrated that BmHemolin facilitated the clearance of pathogens in the body. Moreover, CRISPR/Cas9-mediated knockout of the BmHemolin gene led to the downregulation of antimicrobial peptides and phagocytosis-related factors, while an excess of BmHemolin could enhance the expression of these genes, thereby improving the silkworm’s immune resistance to Enterococcus mundtii and increasing survival rates. In summary, our research demonstrates that BmHemolin played a pivotal role in both humoral and cellular immunity in the silkworm, thereby defending against pathogen invasion. Full article

This study aimed to explore the effects of dietary supplementation with soy isoflavones (SI) in the later stages of pregnancy on the antioxidant capacity of sows and intestinal health of newborn piglets. Forty sows with similar body weights and parity (average of 1–2 parity) were randomly divided into two groups (n = 20): the control group and SI group (dose: 100 mg/kg of feed). Feeding was started on day 85 of gestation and continued until farrowing. SI supplementation significantly increased the antioxidant levels in the serum of the sows and newborn piglets, placental tissue, and the intestinal tract of the piglets. This observation was indicated by a decreased activity of the oxidative stress marker malondialdehyde (MDA); increased activity of antioxidant enzymes such as superoxide dismutase, glutathione peroxidase, and catalase; and enhanced total antioxidant capacity. The organ indices of the intestine and liver and the villus height/crypt depth of the jejunum of newborn piglets significantly increased. SI supplementation activated the Nrf2 signaling pathway in the jejunum of neonatal piglets and the expression of placental antioxidant proteins, and it downregulated the expression of the Bax and Caspase 3 apoptotic proteins in the placenta and neonatal piglets. Intestinal and placental barrier integrity was strengthened. For example, ZO-1, Occludin, and Claudin 1 exhibited elevated expression. In conclusion, dietary supplementation with SI enhanced the antioxidant capacity of sows and piglets and improved the health of the placenta and intestinal tract of newborn piglets. Full article

The accurate monitoring of waterbird abundance and their habitat preferences is essential for effective ecological management and conservation planning in aquatic ecosystems. This study explores the efficacy of unmanned aerial vehicle (UAV)-based high-resolution orthomosaics for waterbird monitoring and mapping along the Lieve Canal, Belgium. We systematically classified habitats into residential, industrial, riparian tree, and herbaceous vegetation zones, examining their influence on the spatial distribution of three focal waterbird species: Eurasian coot (Fulica atra), common moorhen (Gallinula chloropus), and wild duck (Anas platyrhynchos). Herbaceous vegetation zones consistently supported the highest waterbird densities, attributed to abundant nesting substrates and minimal human disturbance. UAV-based waterbird counts correlated strongly with ground-based surveys (R² = 0.668), though species-specific detectability varied significantly due to morphological visibility and ecological behaviors. Detection accuracy was highest for coots, intermediate for ducks, and lowest for moorhens, highlighting the crucial role of image resolution ground sampling distance (GSD) in aerial monitoring. Operational challenges, including image occlusion and habitat complexity, underline the need for tailored survey protocols and advanced sensing techniques. Our findings demonstrate that UAV imagery provides a reliable and scalable method for monitoring waterbird habitats, offering critical insights for biodiversity conservation and sustainable management practices in aquatic landscapes. Full article

The modern Chinese architectural heritage combines sturdy Western materials with delicate Chinese styling, mainly adopting brick-timber structural systems that are highly vulnerable to fire damage. The study assesses the fire spread characteristics of the First Faculty House, a 20th-century architectural heritage located at a university in China. The assessment is carried out by analyzing building materials, structural configuration, and fire load. By using FDS (Fire Dynamics Simulator (PyroSim version 2022)) and SketchUp software (version 2023) for architectural reconstruction and fire spread simulation, explores preventive measures to reduce fire risks. The result show that the total fire load of the building amounts to 1,976,246 MJ. After ignition, flashover occurs at 700 s, accompanied by a sharp increase in the heat release rate (HRR). The peak ceiling temperature reaches 750 °C. The roof trusses have critical structural weaknesses when approaching flashover conditions, indicating a high potential for collapse. Three targeted fire protection strategies are proposed in line with the heritage conservation principle of minimal visual and functional intervention: fire sprinkler systems, fire retardant coating, and fire barrier. Simulations of different strategies demonstrate their effectiveness in mitigating fire spread in elongated architectural heritages with enclosed ceiling-level ignition points. The efficacy hierarchy follows: fire sprinkler system > fire retardant coating > fire barrier. Additionally, because of chimney effect, for fire sources located above the ceiling and other hidden locations need to be warned in a timely manner to prevent the thermal plume from invading other sides of the ceiling through the access hole. This research can serve as a reference framework for other Modern Chinese Architectural Heritage to develop appropriate fire mitigation strategies and to provide a methodology for sustainable development of the Chinese architectural heritage. Full article