Search Results (531)

This study investigates premature fatigue failures in three EA1N steel axles from permanent magnet direct-drive locomotives during wheel-seat bending tests. Complete fracture occurred in one axle at 3 million cycles, and in the other two axles, cracks appeared and were observed through magnetic particle detection at 3.5 million and 1.6 million cycles, respectively. A comprehensive failure analysis was conducted through metallurgical examination, fractography, mechanical testing, residual stress measurement, and finite element analysis. The fractographic results revealed fractures consistently initiated at the wheel-seat to axle-body transition arc, exhibiting characteristic ratchet marks and beach patterns. The premature fracture mechanism was identified as a high-stress fatigue fracture. The residual stress measurements showed detrimental tensile stresses at the surface. Coupled with the operating stress, the stress on the axle exceeds fatigue strength, which accelerates the initiation and propagation of fatigue cracks. Based on these observations, the failure mechanism was identified, and preventive methods were proposed to reduce the risk of recurrence of the in-service axles. Full article

China has adopted extensive restoration practices to improve ecosystem function. The efficiency of these restoration efforts remains unclear, which may hinder the supply of ecosystem services (ESs). In this context, this study first employed InVEST models to clarify spatio-temporal changes in five key ESs. The static and dynamic efficiencies of ecosystem service production in 130 cities from 2015 to 2021 in the Yangtze River Economic Belt (YREB) were then measured using the Super-SBM-Malmquist model, with ESs considered as outputs. The results indicated that water conservation (WC), water purification (WP), and soil retention (SR) exhibited overall declining trends, decreasing by 28.32%, 3.22%, and 10.00%, respectively, while carbon storage (CS) and habitat quality (HQ) remained steady. More than 70% of studied cities exhibited static efficiency levels below 50%, which were attributed to inefficient utilization of labor, capital, and technology. Significant spatial heterogeneity was observed, with high-efficiency cities mainly located in mountainous areas and low-efficiency cities concentrated in flat regions. The downward trend in dynamic efficiency has been reversed from a 39.02% decline in 2015–2018 to a 38.31% increase in 2018–2021, despite being adversely affected by technological regression. Finally, several policy implications are proposed, including optimizing resource allocation, introducing advanced technology and setting the intercity cooperation and complementarity mechanisms. Full article

The Amazon Basin plays a crucial role in the global hydrological cycle, where seasonal and interannual variations in terrestrial water storage (TWS) are essential for understanding climate–hydrology coupling mechanisms. This study utilizes data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its follow-on mission (GRACE-FO, collectively referred to as GRACE) to investigate the spatiotemporal dynamics of hydrological mass changes in the Amazon Basin from 2002 to 2021. Results reveal pronounced spatial heterogeneity in the annual amplitude of TWS, exceeding 65 cm near the Amazon River and decreasing to less than 25 cm in peripheral mountainous regions. This distribution likely reflects the interplay between precipitation and topography. Vertical displacement measurements from the Global Navigation Satellite System (GNSS) show strong correlations with GRACE-derived hydrological load deformation (mean Pearson correlation coefficient = 0.72) and reduce its root mean square (RMS) by 35%. Furthermore, the study demonstrates that existing hydrological models, which neglect groundwater dynamics, underestimate hydrological load deformation. Principal component analysis (PCA) of the Amazon GNSS network demonstrates that the first principal component (PC) of GNSS vertical displacement aligns with abrupt interannual TWS fluctuations identified by GRACE during 2010–2011, 2011–2012, 2013–2014, 2015–2016, and 2020–2021. These fluctuations coincide with extreme precipitation events associated with the El Niño–Southern Oscillation (ENSO), confirming that ENSO modulates basin-scale interannual hydrological variability primarily through precipitation anomalies. This study provides new insights for predicting extreme hydrological events under climate warming and offers a methodological framework applicable to other critical global hydrological regions. Full article

An oat protein isolate is an ideal raw material for producing a wide range of plant-based products. However, oat protein exhibits weak functional properties, particularly in emulsification. Casein-based ingredients are commonly employed to enhance emulsifying properties as a general practice in the food industry. pH-shifting processing is a straightforward method to partially unfold protein structures. This study modified a mixture of an oat protein isolate (OPI) and casein by combining a pH adjustment (adjusting the pH of two solutions to 12, mixing them at a 3:7 ratio, and maintaining the pH at 12 for 2 h) with an atmospheric cold plasma (ACP) treatment to improve the emulsifying properties. The results demonstrated that the ACP treatment significantly enhanced the solubility of the OPI/casein mixtures, with a maximum solubility of 82.63 ± 0.33%, while the ζ-potential values were approximately −40 mV, indicating that all the samples were fairly stable. The plasma-induced increase in surface hydrophobicity supported greater protein adsorption and redistribution at the oil/water interface. After 3 min of treatment, the interfacial pressure peaked at 8.32 mN/m. Emulsions stabilized with the modified OPI/casein mixtures also exhibited a significant droplet size reduction upon extending the ACP treatment to 3 min, decreasing from 5.364 ± 0.034 μm to 3.075 ± 0.016 μm. The resulting enhanced uniformity in droplet size distribution signified the formation of a robust interfacial film. Moreover, the ACP treatment effectively enhanced the emulsifying activity of the OPI/casein mixtures, reaching (179.65 ± 1.96 m²/g). These findings highlight the potential application value of OPI/casein mixtures in liquid dairy products. In addition, dairy products based on oat protein are more conducive to sustainable development than traditional dairy products. Full article

Geographic object-based image analysis (GEOBIA) has demonstrated substantial utility in remote sensing tasks. However, its integration with deep learning remains largely confined to image-level classification. This is primarily due to the irregular shapes and fragmented boundaries of segmented objects, which limit its applicability in semantic segmentation. While convolutional neural networks (CNNs) excel at local feature extraction, they inherently struggle to capture long-range dependencies. In contrast, Transformer-based models are well suited for global context modeling but often lack fine-grained local detail. To overcome these limitations, we propose GOFENet (Geo-Object Feature Enhanced Network)—a hybrid semantic segmentation architecture that effectively fuses object-level priors into deep feature representations. GOFENet employs a dual-encoder design combining CNN and Swin Transformer architectures, enabling multi-scale feature fusion through skip connections to preserve both local and global semantics. An auxiliary branch incorporating cascaded atrous convolutions is introduced to inject information of segmented objects into the learning process. Furthermore, we develop a cross-channel selection module (CSM) for refined channel-wise attention, a feature enhancement module (FEM) to merge global and local representations, and a shallow–deep feature fusion module (SDFM) to integrate pixel- and object-level cues across scales. Experimental results on the GID and LoveDA datasets demonstrate that GOFENet achieves superior segmentation performance, with 66.02% mIoU and 51.92% mIoU, respectively. The model exhibits strong capability in delineating large-scale land cover features, producing sharper object boundaries and reducing classification noise, while preserving the integrity and discriminability of land cover categories. Full article

Background/Objectives: Chemically or genetically detoxified pertussis toxin (PTx) is a crucial antigen component of the acellular pertussis vaccine. Chemical detoxification using glutaraldehyde generally causes significant structural changes to the toxin. However, how these structural changes in PTx affect its antigenic properties remains unclear. Additionally, there is limited knowledge regarding how many alterations in antigenic properties impact immunogenicity. Methods: To investigate the impact of structural changes on antigenic properties, we developed a sandwich ELISA to quantify the neutralizing epitopes on PTx. Subsequently, we analyzed different PTx toxoid (PTd) preparations with the assay. Additionally, we assessed the immunogenicity of various acellular pertussis vaccine candidates containing these PTd preparations. Finally, the assay was applied to evaluate the consistency of commercial batches of PTx and PTd intermediates. Results: The assay demonstrated reasonable specificity, accuracy, and precision, and it was sensitive enough to quantify variations in neutralizing epitopes among different PTd samples that shared the same protein concentration. Importantly, we found a positive correlation between the number of neutralizing epitopes in detoxified PTx and its immunogenicity, indicating that the amount of neutralizing epitopes present determines the immunogenicity of glutaraldehyde-inactivated PTx. Moreover, commercial batches of PTx and PTd intermediates exhibited minor variations in neutralizing epitopes. Conclusions: These findings have significant implications for developing acellular pertussis vaccines as they highlight the importance of preserving the neutralizing epitopes of PTx during detoxification to ensure the vaccine’s effectiveness. This assay is also valuable for the quality control of PTd as it more accurately represents the actual antigenic changes of PTx. Full article

Background/Objectives: Sweet potato is a tropical and subtropical crop and its growth and yield are susceptible to low-temperature stress. However, the molecular mechanisms underlying the low temperature stress of sweetpotato are unknown. Methods: In this work, combined transcriptome and metabolism analysis was employed to investigate the low-temperature responses of two sweet potato cultivars, namely, the low-temperature-resistant cultivar “X33” and the low-temperature-sensitive cultivar “W7”. Results: The differentially expressed metabolites (DEMs) of X33 at different time stages clustered in five profiles, while they clustered in four profiles of W7 with significant differences. Differentially expressed genes (DEGs) in X33 and W7 at different time points clustered in five profiles. More DEGs exhibited continuous or persistent positive responses to low-temperature stress in X33 than in W7. There were 1918 continuously upregulated genes and 6410 persistent upregulated genes in X33, whereas 1781 and 5804 were found in W7, respectively. Core genes involved in Ca²⁺ signaling, MAPK cascades, the reactive oxygen species (ROS) signaling pathway, and transcription factor families (including bHLH, NAC, and WRKY) may play significant roles in response to low temperature in sweet potato. Thirty-one common differentially expressed metabolites (DEMs) were identified in the two cultivars in response to low temperature. The KEGG analysis of these common DEMs mainly belonged to isoquinoline alkaloid biosynthesis, phosphonate and phosphinate metabolism, flavonoid biosynthesis, cysteine and methionine metabolism, glycine, serine, and threonine metabolism, ABC transporters, and glycerophospholipid metabolism. Five DEMs with identified Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were selected for correlation analysis. KEGG enrichment analysis showed that the carbohydrate metabolism, phenylpropanoid metabolism, and glutathione metabolism pathways were significantly enriched and played vital roles in low-temperature resistance in sweet potato. Conclusions: These findings contribute to a deeper understanding of the molecular mechanisms underlying plant cold tolerance and offer targets for molecular breeding efforts to enhance low-temperature resistance. Full article

To investigate the relationship between the seeding performance of a novel pre-cut sugarcane planter designed by South China Agricultural University and operational settings, field seeding tests was conducted with the following protocol: First, the John Deere M1654 tractor’s forward velocity was calibrated, and the planter’s safe loading capacity was determined. Subsequently, eight experimental treatments (A–H) were designed to quantify the relationships between the three performance indicators: seeding density N, the seeding efficiency E and seeding uniformity (coefficient of variation, CV), and three key operational parameters: forward speed of planter v, the discharging sprocket rotational speed n, and the hopper outlet size w. Mathematical models (R20.979) between three key operational parameters with two performance indicators (N, E) was developed through analysis of variance (ANOVA) and regression analysis. The seeding rate per meter was confirmed to follow a Poisson distribution based on Kolmogorov–Smirnov (K–S) tests. When the CV was below 40%, the mean relative error remained within 3%. These findings provide a theoretical foundation for seeding performance prediction under field conditions. Full article

Fractures in marine sediments are critical zones for hydrate formation. The kinetics and morphological characteristics of hydrates within sandstone fractures are comprehensively investigated in this study by employing a high-pressure visualization reaction vessel to examine their formation, dissociation, and reformation processes. The results are presented below: (1) In 3 mm Type I fractures, the induction time is longer than that observed in the other two fracture widths. Hydrates predominantly form on the fracture walls and gradually expand toward both sides of the fracture. (2) Gas enters the fracture from multiple directions, causing the hydrate in Type X fractures to expand toward the center from all sides, which shortens the induction time and increases the quantity of hydrate formation. (3) An increase in fracture roughness promotes nucleation of the hydrate at surface protrusions but inhibits the total quantity of hydrate formation. (4) Hydrate dissociation typically propagates from the fracture wall into the interior, exhibiting a wavy surface morphology. Gas production is influenced by the fracture width, with the highest gas production observed in a 3 mm fracture. (5) Due to the memory effect, the hydrate induction time for reformation is significantly shorter, though the quantity of hydrate formed is lower than that of the first formation. This study aims to provide micro-level insights into the distribution of hydrates in sandstone fractures, thereby facilitating more efficient and safe extraction of hydrates from fractures. Full article

To develop new kiwifruit cultivars (Actinidia chinensis var. chinensis) with desirable traits, we conducted wild resource surveys in the Wudang Mountains region of China. Seven promising accessions were identified through preliminary screening, exhibiting fruit weights ranging from 50.46 g to 75.06 g and a soluble solids content (SSC) between 14.33% and 16.32%. The accession ‘WD-03-1’ stood out by meeting the dual selection criteria of fruit weight exceeding 70 g and a SSC above 15%. After a decade-long evaluation, this elite genotype was officially certified as a superior cultivar by the Hubei Provincial Variety Committee for Forestry in 2016, receiving the registered name ‘Wudang 1’. Distinguished as a rare green-fleshed variety in the A. chinensis var. chinensis, ‘Wudang 1’ produces uniform elliptical fruits (shape index of 1.34) with an average weight of 83.22 g. Its flesh combines sweet and tart flavors with exceptional nutritional parameters: 16.33% SSC, 15.28% dry matter, 12.10% soluble sugars, 1.24% titratable acidity, 132.10 mg/100 g vitamin C, and 7.77 mg/g amino acids. Comparative analysis with established cultivars ‘Jinnong’ and ‘Cuiyu’ revealed that ‘Wudang 1’ matures earlier and demonstrates superior performance in three key quality metrics (SSC, dry matter, and vitamin C). Further analysis of aromatic profiles during the prime consumption stage identified 41 volatile compounds, predominantly comprising aldehydes, esters, alcohols, and ketones, which collectively contribute to its distinctive fragrance. Full article

The quantitative assessment of Parkinson’s disease (PD) is critical for guiding diagnosis, treatment, and rehabilitation. Conventional clinical evaluations—heavily dependent on manual rating scales such as the Unified Parkinson’s Disease Rating Scale (UPDRS)—are time-consuming and prone to inter-rater variability. In this study, we propose a fully automated UPDRS gait-scoring framework. Our method combines (a) surface electromyography (EMG) signals and (b) inertial measurement unit (IMU) data into a single deep learning model. Our end-to-end network comprises three specialized branches—a diagnosis head, an evaluation head, and a balance head—whose outputs are integrated via a customized fusion-detection module to emulate the multidimensional assessments performed by clinicians. We validated our system on 21 PD patients and healthy controls performing a simple walking task while wearing a four-channel EMG array on the lower limbs and 2 shank-mounted IMUs. It achieved a mean classification accuracy of 92.8% across UPDRS levels 0–2. This approach requires minimal subject effort and sensor setup, significantly cutting clinician workload associated with traditional UPDRS evaluations while improving objectivity. The results demonstrate the potential of wearable sensor-driven deep learning methods to deliver rapid, reliable PD gait assessment in both clinical and home settings. Full article

The inherent intermittency and uncertainty of renewable energy generation pose significant challenges to the safe and stable operation of power grids, particularly when power demand does not match renewable energy supply, leading to issues such as wind and solar power curtailment. To effectively promote the consumption of renewable energy while leveraging electric vehicles (EVs) in virtual power plants (VPPs) as distributed energy storage resources, this paper proposes an ordered scheduling strategy for EVs in campus areas oriented towards renewable energy consumption. Firstly, to address the uncertainty of renewable energy output, this paper uses Conditional Generative Adversarial Network (CGAN) technology to generate a series of typical scenarios. Subsequently, a mathematical model for EV aggregation is established, treating the numerous dispersed EVs within the campus as a collectively controllable resource, laying the foundation for their ordered scheduling. Then, to maximize renewable energy consumption and optimize EV charging scheduling, an improved Particle Swarm Optimization (PSO) algorithm is adopted to solve the problem. Finally, case studies using a real-world testing system demonstrate the feasibility and effectiveness of the proposed method. By introducing a dynamic inertia weight adjustment mechanism and a multi-population cooperative search strategy, the algorithm’s convergence speed and global search capability in solving high-dimensional non-convex optimization problems are significantly improved. Compared with conventional algorithms, the computational efficiency can be increased by up to 54.7%, and economic benefits can be enhanced by 8.6%. Full article

The primary measurement involves detecting tiny (picometer-level) pathlength fluctuations between satellites using heterodyne laser interferometry for space-based gravitational wave detection. The interference of two laser beams with a MHz-level frequency difference produces a MHz beat-note, in which the gravitational wave signal is encoded in the phase of the beat-note. The phasemeter then performs micro-radian accuracy phase measurement and communication information demodulation for this beat-note. To mitigate the impact of phase modulation, existing solutions mostly alleviate it by reducing the modulation depth and optimizing the structure of the pseudo-random noise (PRN) codes. Since the phase modulation is not effectively separated from the phase of the beat-note phase measurement, it has a potential impact on the phase extraction of the micro-radian accuracy of the beat-note. To solve this problem, this paper analyzes the influence mechanism of phase modulation on beat-note phase measurement and proposes a method to separate the modulated phase based on complex rotation. The beat-note is processed by complex conjugate rotation, which can effectively eliminate the PRN modulated phase. Simulation and analysis results demonstrate that this method can significantly enhance the purity of the measured phase in the beat-note while maintaining the ranging and communication functions. Targeting the application of the micro-radian phasemeter in space-based gravitational wave detection, this study presents the reconstruction and separation method of the ranging and communication phase in beat-note, which also provides a new direction for the final selection of modulation depth in the future. Full article

As the primary electronic payload of laser interferometry system for space gravitational wave detection, the core function of the phasemeter is ultra-high precision phase measurement. According to the principle of laser heterodyne interferometry and the requirement of 1 pm ranging accuracy of the phasemeter, the phase measurement noise should reach 2π μrad/Hz^1/2@(0.1 mHz–1 Hz). The heterodyne interference signal first passes through the quadrant photoelectric detector (QPD) to achieve photoelectric conversion, then passes through the analog-to-digital converter (ADC) to achieve analog and digital conversion, and finally passes through the digital phase-locked loop (DPLL) for phase locking. The sampling timing jitter of the heterodyne interference signal caused by the ADC is the main noise affecting the phase measurement performance and must be suppressed. This paper proposes a sampling timing jitter noise suppression system (STJNSS), which can set system parameters for high-frequency signals used for inter-satellite clock noise transmission, the system clock of the phasemeter, and the pilot frequency for suppressing ADC sampling timing jitter noise, meeting the needs of the current major space gravitational wave detection plans. The experimental results after the integration of SJNSS and the phase meter show that the phase measurement noise of the heterodyne interferometer signal reaches 2π μrad/Hz^1/2@(0.1 mHz–1 Hz), which meets the requirements of space gravitational wave missions. Full article