Search Results (8,198)

Accurate prediction of pedestrian movements is vital for autonomous driving, smart transportation, and human–computer interactions. To effectively anticipate pedestrian behavior, it is crucial to consider the potential spatio-temporal interactions among individuals. Traditional modeling approaches often depend on absolute position encoding to discern the positional relationships between pedestrians. Unfortunately, this method overlooks relative spatio-temporal relationships and fails to simulate ongoing interactions adequately. To overcome this challenge, we present a relative spatio-temporal encoding (RSTE) strategy that proficiently captures and analyzes this essential information. Furthermore, we design a multi-spatio-temporal graph (MSTG) modeling technique aimed at modeling and characterizing spatio-temporal interaction data across several individuals over time and space, with the goal of representing the movement patterns of pedestrians accurately. Additionally, an attention-based MSTT model has been developed, which utilizes an end-to-end approach for learning the structure of the MSTG. The findings indicate that an understanding of an individual’s preceding trajectory is crucial for forecasting the subsequent movements of other individuals. Evaluations using two challenging datasets reveal that the MSTT model markedly outperforms traditional trajectory-based modeling methods in predictive performance. Full article

Automated cherry harvesting presents a significant opportunity to overcome the high costs and inefficiencies of manual labor in modern agriculture. However, robotic harvesting in dense canopies requires sophisticated path planning to navigate cluttered branches and selectively pick target fruits. This paper introduces a complete robotic harvesting solution centered on a novel path-planning algorithm: the Multi-Strategy Integrated RRT for Continuous Harvesting Path (MSI-RRTCHP) algorithm. Our system first employs a machine vision system to identify and locate mature cherries, distinguishing them from unripe fruits, leaves, and branches, which are treated as obstacles. Based on this visual data, the MSI-RRTCHP algorithm generates an optimal picking trajectory. Its core innovation is a synergistic strategy that enables intelligent navigation by combining probability-guided exploration, goal-oriented sampling, and adaptive step size adjustments based on the obstacle’s density. To optimize the picking sequence for multiple targets, we introduce an enhanced traversal algorithm ($\sigma$-TSP) that accounts for obstacle interference. Field experiments demonstrate that our integrated system achieved a 90% picking success rate. Compared with established algorithms, the MSI-RRTCHP algorithm reduced the path length by up to 25.47% and the planning time by up to 39.06%. This work provides a practical and efficient framework for robotic cherry harvesting, showcasing a significant step toward intelligent agricultural automation. Full article

Multimodal knowledge graphs have recently been successfully applied to tasks such as those relating to information retrieval, question and answer, and recommender systems. In this study, we propose a dual-path fine-tuning mechanism technique with a low-rank adapter and an embedded cueing layer, aiming to improve the generalization and accuracy of the model in analogical reasoning tasks. The low-rank fine-tuning (LoRA) technique with rank-stable scaling factor is used to fine-tune the MKGformer model, and a cue-embedding layer is innovatively added to the input layer, which enables the model to better grasp the scale of the relationship between entities according to the dynamic cue vectors during the fine-tuning process and ensures that the model achieves the best results during training. The experimental results show that the R-MKG model improves several evaluation indexes by more than 20%, which is significantly better than the traditional DoRA and FA-LoRA methods. This research provides technical support for multimodal knowledge graph analogical reasoning. We hope that our work will bring benefits and inspire future research. Full article

Sodium p-perfluorous nonenoxybenzenesulfonate (OBS) has been proposed as a substitute for perfluorooctanesulfonic acid (PFOS), yet it has garnered increasing attention due to its environmental persistence and potential toxicity. Despite these concerns, the neurotoxic mechanisms of OBS remain unclear. This study investigates and compares the neurotoxic effects and mechanisms of OBS and PFOS in Caenorhabditis elegans. L4-stage worms were exposed to OBS (0.1–100 μM) or PFOS (100 μM) for 24 h. Neurobehavioral analysis showed that OBS exposure induced concentration-dependent neurobehavioral deficits, with 100 μM OBS significantly reducing pharyngeal pumping rate (29.8%), head swing frequency (23.4%), and body bending frequency (46.6%), surpassing the effects of PFOS. Both compounds decreased the fluorescence intensity of dopaminergic, glutamatergic, and γ-aminobutyric acid neurons and downregulated neurotransmitter-associated genes. They also increased ROS generation and inhibited antioxidant gene expression. Molecular docking revealed that OBS had a stronger binding affinity to p38 MAPK key protein (PMK-1) than PFOS. OBS and PFOS upregulated pmk-1 and skn-1, modulating oxidative stress and neuronal function. pmk-1 mutation differentially affected OBS-induced neurobehavioral changes and gene expression alterations. Our findings indicate that OBS exhibits stronger neurotoxicity than PFOS in Caenorhabditis elegans, mediated through the PMK-1 pathway. These results highlight the need for further investigation into the safety of OBS as a PFOS alternative. Full article

The histological integrity of the intestine depends on the tight and orderly arrangement of epithelial cells within the intestinal villi. Nodal, a transforming growth factor-β (TGF-β) family member, has been reported to promote epithelial cell proliferation. Collagen not only establishes physical connections between adjacent cells but also serves as an anchoring platform for cell adhesion and regeneration processes. Therefore, a 21-day feeding trial was conducted using RNA interference to investigate the role of the Nodal gene in regulating intestinal collagen synthesis and histological structure integrity in juvenile A. japonicus fed diets containing graded levels of vitamin E (VE) (0, 200, and 400 mg/kg). The results showed that the addition of 200 mg/kg VE significantly improved the growth rate, immune enzyme activities and related gene expression, as well as intestinal villus morphology. Additionally, the addition of 200 mg/kg VE upregulated the expression of Nodal, which activated the expression of collagen synthesis-related genes and promoted collagen deposition in the intestines of A. japonicus. After Nodal gene knockdown, A. japonicus presented a decreased growth rate, damage to the intestinal histological structure, and impaired collagen synthesis, with the most notable findings observed in A. japonicus fed diets without VE addition. However, these detrimental effects were eliminated to some extent by the addition of 200 mg/kg VE. These findings indicate that VE improves immune function and intestinal histological structure in A. japonicus through a Nodal-dependent pathway. Full article

Sea buckthorn is a vital woody oil species valued for its role in soil conservation and its bioactive seed oil, which is rich in unsaturated fatty acids and other compounds. However, low seed oil content and small seed size are the main bottlenecks restricting the development and utilization of sea buckthorn. In this study, we tested the seed oil content and seed size of 12 sea buckthorn cultivars and identified the key genes and transcription factors involved in seed development and lipid biosynthesis via the integration of UID RNA-seq (Unique Identifiers, UID), WGCNA (weighted gene co-expression network analysis) and qRT-PCR (quantitative real-time PCR) analysis. The results revealed five cultivars (CY02, CY11, CY201309, CY18, CY21) with significantly higher oil contents and five cultivars (CY10, CY201309, CY18, CY21, CY27) with significantly heavier seeds. A total of 10,873 genes were significantly differentially expressed between the S1 and S2 seed developmental stages of the 12 cultivars. WGCNA was used to identify five modules related to seed oil content and seed weight/size, and 417 candidate genes were screened from these modules. Among them, multiple hub genes and transcription factors were identified; for instance, ATP synthase, ATP synthase subunit D and Acyl carrier protein 1 were related to seed development; plastid–lipid-associated protein, acyltransferase-like protein, and glycerol-3-phosphate 2-O-acyltransferase 6 were involved in lipid biosynthesis; and transcription factors DOF1.2, BHLH137 and ERF4 were associated with seed enlargement and development. These findings provide crucial insights into the genetic regulation of seed traits in sea buckthorn, offering targets for future breeding efforts aimed at improving oil yield and quality. Full article

In UGC-based knowledge trading platforms, the abundance of personalized content often leads to varying quality levels. By incorporating embedded advertising, platforms can incentivize knowledge producers to produce high-quality content; however, the uncertainty in managing embedded advertisements increases the complexity of pricing knowledge products. This paper examines the impact of embedded advertising on the pricing of knowledge products, aims to maximize the profits of both knowledge producer and the platform. Based on Stackelberg game theory, two pricing decision models are developed under different advertising management modes: the platform-managed mode (where the platform determines the advertising intensity) and the advertiser-managed mode (where the advertiser determines the advertising intensity). The study analyzes the effects of UGC product quality, consumer sensitivity to advertising, and power structure on knowledge product pricing, and derives threshold conditions for optimal pricing. The results indicate that (1) When the quality of UGC knowledge product exceeds a certain threshold, platform-managed advertising becomes profitable. (2) Under the platform-managed mode, both the platform and knowledge producer can adopt price-increasing strategies to enhance profits. (3) Under the advertiser-managed mode, the platform can leverage differences in power structure to optimize revenue, while knowledge producer can actively enhance his pricing power to achieve mutual benefits with the platform. This study provides theoretical support and practical guidance for advertising cooperation mechanisms and pricing strategies for knowledge products in UGC-based knowledge trading platforms. Full article

Blood flow restriction training (BFRT) offers notable advantages, including simplicity and time efficiency. However, no meta-analysis has yet comprehensively evaluated its effects on glucose and lipid metabolism in overweight or obese adults. This meta-analysis examines the potential efficacy of BFRT in improving glycemic and lipid control in overweight/obese adults. The literature was searched in six databases, with the search period up to 31 March 2025. A total of eight randomized controlled trials involving 267 participants were identified. Data were analyzed using Stata 18.0 and RevMan 5.4 with random effects models. Outcomes included fasting blood glucose (FBG), homeostasis model assessment of insulin resistance (HOMA-IR), and lipid profiles, and risk of bias and publication bias (Egger’s test) were assessed. BFRT significantly reduced FBG (Hedges’ g = −1.13, 95% CI: −1.65 to −0.62, p < 0.01; I² = 66.34%) and HOMA-IR (Hedges’ g = −0.98, 95% CI: −1.35 to −0.61, p < 0.01; I² = 17.33%) compared with the controls. However, no significant changes were observed in lipid profiles. Our analysis demonstrates that BFRT exhibits the favorable effect of improving glucose metabolism in overweight/obese adults; however, current evidence does not support significant advantages of BFRT for lipid metabolism improvement. Full article

To reduce carbon emissions in the shipping industry, the energy management problem of the ship-integrated energy system (S-IES) is analyzed in this paper. Firstly, a marine environmental risk field model is constructed to quantify the degree of hazard when designing the sailing route. Meanwhile, an energy management model that considers both economic and environmental benefits is developed to enhance the penetration rate of renewable resources. Subsequently, a distributed energy management algorithm based on finite-time consensus theory is proposed to ensure a rapid and accurate response to load demand. Moreover, a mathematical analysis is provided to demonstrate the algorithm’s effectiveness. Finally, the sea area between Singapore Port (Singapore) and Penang Port (Malaysia) is chosen as the simulation environment. The experimental results demonstrate the effectiveness of energy management for the S-IES. Full article

Herein, we rationally designed a molecular catalytic filter for effective micropollutants decontamination via peroxymonosulfate (PMS) activation. Specifically, iron phthalocanine (FePc) molecules with defined Fe–N₄ coordination were immobilized onto carbon nanotubes (CNTs), forming a hybrid catalyst that integrated molecular precision with heterogeneous catalytic properties. The resulting CNT-FePc filter achieved a 98.4% removal efficiency for bisphenol A (10 ppm) in a single-pass operation system, significantly outperforming the CNT/PMS system without FePc (41.6%). Additionally, the CNT-FePc/PMS system demonstrated remarkable resistance to performance inhibition by common water matrix components. Unlike typical radical-dominated PMS activation processes, mechanistic investigations confirmed that the CNT-FePc/PMS system selectively promoted singlet oxygen (¹O₂) generation as the primary oxidative pathway. Density functional theory (DFT) calculations revealed that PMS exhibited stronger adsorption on FePc (−3.05 eV) compared to CNT (−2.86 eV), and that FePc effectively facilitated O–O bond elongation in PMS, thereby facilitating ¹O₂ generation. Additionally, seed germination assays indicated a significant reduction in the biotoxicity of the treated effluents. Overall, this work presents a catalyst design strategy that merges molecular-level coordination chemistry with practical flow-through configuration, enabling rapid, selective, and environmentally benign micropollutant removal. Full article

Microglia-mediated chronic neuroinflammation is a common pathological feature of Parkinson’s disease (PD). Strong evidence suggests that activated microglia can lesion neurons by releasing exosomes. However, the mechanisms of exosome release from activated microglia remain unclear. We recently revealed a key role of complement receptor 3 (CR3) in regulating microglial activation in the process of progressive neurodegeneration. This study aimed to investigate whether CR3 can regulate exosome release from activated microglia, as well as the underlying mechanisms. We found that LPS, an inducer of microglial M1 activation, induced exosome release from activated microglia. Inhibition of exosome synthesis suppressed LPS-induced microglial activation, gene expression of proinflammatory factors, and related neurotoxicity. Silencing or knocking out CR3 attenuated LPS-induced exosome release in microglia. NADPH oxidase (NOX2) was further identified as a downstream signal of CR3, mediating microglial exosome release and related neurotoxicity. CR3 silencing blocked LPS-induced NOX2 activation and superoxide production through inhibition of p47^phox phosphorylation and membrane translocation. Moreover, NOX2 activation elicited by PMA or supplementation of H₂O₂ recovered exosome release from CR3-silenced microglia. Subsequently, we demonstrated that the CR3-NOX2 axis regulates syntenin-1 to control microglial exosome release. Finally, we observed that the expression of CR3 was increased in the brain of LPS-treated mice, and genetic ablation of CR3 significantly reduced LPS-induced NOX2 activation, microglial M1 polarization, and exosome production in mice. Overall, our findings revealed a critical role of the CR3-NOX2 axis in controlling microglial exosome release and related neurotoxicity through syntenin-1, providing a novel target for the development of a therapeutic strategy for neuroinflammation-mediated neurodegeneration. Full article

The strong nonlinearity of shallow-water waves significantly affects the dynamic response of floating offshore wind turbines (FOWTs), introducing additional complexity in motion behavior. This study presents a series of 1:80-scale experiments conducted on a 5 MW FOWT at a 50 m water depth, under regular, irregular, and focused wave conditions. The tests were conducted under regular, irregular, and focused wave conditions. The results show that, under both regular and irregular wave conditions, the platform’s motion and mooring tension increased as the wave period became longer, indicating a greater energy transfer and stronger coupling effects at lower wave frequencies. Specifically, in irregular seas, mooring tension increased by 16% between moderate and high sea states, with pronounced surge–pitch coupling near the natural frequency. Under focused wave conditions, the platform experienced significant surge displacement due to the impact of large wave crests, followed by free-decay behavior. Meanwhile, the pitch amplitude increased by up to 27%, and mooring line tension rose by 16% as the wave steepness intensified. These findings provide valuable insights for the design and optimization of FOWTs in complex marine environments, particularly under extreme wave conditions. Additionally, they contribute to the refinement of relevant numerical simulation methods. Full article

Studying the impact of digital economy development on marine environmental quality has important theoretical and practical significance for achieving a win–win situation between high-quality economic development and high-level ecological environment protection. This article selects the marine environment of coastal provinces and cities in China from 2011 to 2022 as the research object and uses the entropy method to comprehensively evaluate the quality of marine environment and the level of digital economy. Also, we construct intermediary and threshold effect models to deeply explore the impact mechanism of digital economy development on marine environmental quality. We find that digital economy and marine environmental quality both show a wave-like rising trend, but the comprehensive level is relatively low. The development of the digital economy can effectively improve the level of marine environmental quality, and the digital economy promotes the improvement of marine environmental quality by improving the level of marine economy. The level of economic development and industrial scale has created a threshold effect in the process of promoting the development of marine environmental quality through the digital economy. Therefore, strengthening the digital governance of the marine environment and promoting the industrialization of marine ecology and the ecologicalization of marine industries will help promote the integrated development of the digital economy and marine environment. Full article

Rockfill particle gradation significantly influences mechanical performance in earth–rockfill dam construction, yet on-site screening is often time-consuming, labor-intensive, and structurally invasive. This study proposes a rapid and non-destructive detection method using mobile-based photography and an end-to-end image segmentation approach. An enhanced YOLOv8-seg model with an integrated dual-attention mechanism was pre-trained on laboratory images to accurately segment densely stacked particles. Transfer learning was then employed to retrain the model using a limited number of on-site images, achieving high segmentation accuracy. The proposed model attains a mAP50 of 97.8% (base dataset) and 96.1% (on-site dataset), enabling precise segmentation of adhered and overlapped particles with various sizes. A Minimum Area Rectangle algorithm was introduced to compute the gradation, closely matching the results from manual screening. This method significantly contributes to the automation of construction workflows, cutting labor costs, minimizing structural disruption, and ensuring reliable measurement quality in earth–rockfill dam projects. Full article

Multi-behavior sequential recommendation (MBSRec) is a form of sequential recommendation. It leverages users’ historical interaction behavior types to better predict their next actions. This approach fits real-world scenarios better than traditional models do. With the rise of the transformer model, attention mechanisms are widely used in recommendation algorithms. However, they suffer from low-pass filtering, and the simple learnable positional encodings in existing models offer limited performance gains. To address these problems, we introduce the context-aware multi-behavior sequential recommendation model (CAMBSRec). It separately encodes items and behavior types, replaces traditional positional encoding with context-similarity positional encoding, and applies the discrete Fourier transform to separate the high and low frequency components and enhance the high frequency components, countering the low-pass filtering effect. Experiments on three public datasets show that CAMBSRec performs better than five baseline models, demonstrating its advantages in terms of recommendation performance. Full article