Search Results (91,106)

With the increasingly frequent exploitation and transportation of offshore oil, the threat of oil spill accidents to the marine ecological environment has become increasingly serious. It is urgent to develop efficient and reliable oil film monitoring technology. Based on the marine radar oil spill data, an innovative OAT-NGN hybrid strategy segmentation algorithm was proposed. By integrating the local feature learning ability of a Neural Gas Network (NGN) and the global search strategy of the Oat optimization algorithm (OAT), the proposed method effectively meets the challenges of traditional oil film segmentation methods in complex sea conditions. Firstly, the raw data of marine radar were preprocessed by using co-frequency interference and speckle noise suppression. Then, the OAT algorithm guided the updating of neural weights in the NGN on a global scale for the exploration of a more optimal solution space during the optimization process. Finally, the oil spill segmentation results were projected to the polar coordinate system through post-processing technology. The experimental results showed that this method effectively balanced the problem of false detection and missing detection. Compared with existing methods, OAT-NGN shown stronger adaptability in complex scenarios. In order to improve the segmentation performance, its innovative dynamic weight adjustment mechanism and spatial constraint design provide a new technical path. Full article

The cable crane is the core hoisting equipment for high arch dam construction, and its hoisting trajectory is critical for both operational efficiency and safety. However, current trajectory planning does not adequately consider the underactuated characteristics of the cable crane. For instance, sudden stops or abrupt changes in direction can easily induce large swings of the bucket, causing safety risks and equipment wear. To address this issue, this paper developed a trajectory planning model for obstacle avoidance with smooth transitions in cable crane hoisting for arch dams and solved the high-dimensional optimization problem using a path–velocity decoupling strategy. First, a shortest path with geometrical conciseness and free collision was generated based on an improved A* algorithm to reduce the frequency of directional changes. Next, for different hoisting scenarios, segmented S-curve and polynomial velocity functions were proposed to ensure smooth velocity transitions. Then, an orthogonal experimental design was employed to generate a cluster of candidate trajectories that meet kinematic constraints, from which the optimal trajectory was selected using a multi-objective evaluation function. The results demonstrate that the motion trajectory planned using the proposed method is notably smoother. Compared with the traditional trapezoidal velocity method, it reduces the maximum swing amplitude of the bucket by 40.78% at a modest time cost. In real-time obstacle avoidance scenarios, the approach outperforms emergency-stop strategies, reducing the bucket’s maximum swing amplitude by 30.48%. This work will provide a reference for engineers to optimize the trajectory of large lifting equipment in construction fields such as high arch dams and bridges. Full article

This study investigated the anti-obesity effects of a homogenized, viscous vegetable (VV) mixture prepared from mucilaginous vegetables, with a focus on modulating hepatic lipid metabolism and gut microbiota composition in mice fed with a high-fat (HF) diet. The VV mixture was formulated by blending freeze-dried powders of ten mucilaginous vegetables, classified as moderately thick using a line-spread test and extremely thick according to the IDDSI framework in a 1:9 ratio (VV mixture: water, w/w). Six-week-old male C57BL/6 mice were fed control or HF diets, with or without 10% VV mixture for 8 weeks (n = 7 per group). The HF diet induced significant weight gain, adipose tissue accumulation, hepatic steatosis, and inflammation. The HF diet also significantly reduced hepatic ACO1, CPT1 mRNA expression, and α-diversity with distinct fecal microbiota profiles. On the other hand, VV mixture supplementation reduced serum TC, LDL-C levels and NAFLD scores. VV mixture supplementation also increased hepatic ACO1 and CPT1 mRNA expression, enhanced α-diversity, and enriched SCFA-producing bacteria, particularly the Lachnospiraceae NK4A136 group. In conclusion, the VV mixture attenuated HF diet-induced obesity, possibly through its high viscosity–mediated effects on hepatic fatty acid oxidation and gut microbiota modulation. Full article

This study presents the development of an innovative multifunctional cup holder designed to enhance safety, usability, and sustainability. Addressing common issues such as accidental spills, heat retention, and structural stability, the proposed design incorporates adjustable fixation and heating functionalities. The research applies a systematic design approach, applying the Theory of Inventive Problem Solving (TRIZ) methodology to resolve design contradictions and enhance product functionality. By integrating human factors considerations and universal design principles, the cup holder aims to improve user experience and accessibility. The design features a vacuum-based adjustable fixation system to prevent tipping, a controlled heating mechanism to maintain beverage temperature, and a shock-absorbing structure for enhanced durability. To evaluate whether the final design meets user expectations, a SERVQUAL questionnaire was used to collect user feedback, which was then analyzed using the Importance–Performance Analysis combined with the Kano model (IPA-Kano model). The results revealed an overall importance score of 4.347 and a satisfaction score of 3.943. Key strengths identified include reliable shock resistance, effective fixation, and ease of operation, while areas such as brand reputation and temperature control precision were found to require improvement due to their high importance but low performance. These insights confirm that the proposed design effectively enhances stability, thermal performance, and user convenience, while aligning with users’ expectations. By addressing critical functional and safety needs, this research advances the development of practical, user-centered innovations in everyday product design. Full article

The accurate detection of embedded parts and truss rebars in prefabricated concrete composite slabs before casting is essential in ensuring structural safety and reliability. However, traditional inspection methods are time-consuming and lack real-time monitoring capabilities, limiting their suitability for modern prefabrication workflows. To address these challenges, this study proposes MBAV, a lightweight object detection model for the quality inspection of prefabricated concrete composite slabs. A dedicated dataset was built to compensate for the absence of public data and to provide sufficient training samples. The proposed model integrates positional encoding into a lightweight architecture to enhance its ability to capture multiscale features in complex environments. Ablation and comparative experiments on the self-constructed dataset show that MBAV achieves an mAP₅₀ of 91% with a model size of only 5.7 MB—8% smaller than comparable models. These results demonstrate that MBAV is accurate and efficient, with its lightweight design showing strong potential for real-time quality inspection in prefabricated concrete production. Full article

Aim: This study was conducted to determine the feasibility, safety, and clinical outcomes of the vaginal natural-orifice transluminal endoscopic surgery (vNOTES) approach in gynecology for obese patients. Methods: PubMed, Cochrane Library, and Google Scholar were searched, from inception to April 2025. A systematic review was performed following the PRISMA guidelines. Studies assessing the use of vNOTES for gynecological procedures in obese women were included. The quality of included articles was evaluated according to the Newcastle–Ottawa Scale. Results: The search yielded three retrospective cohort studies, one cross-sectional, and ten case series. The patients in the vNOTES group (n = 99) had statistically significant shorter operative times, reduced hospitalization, lower postoperative pain scores, fewer perioperative complications, and improved quality of life when compared to the laparoscopy group (n = 84). A study compared obese women to non-obese women undergoing vNOTES and found that operative times were longer in the obese group. Conversion to laparoscopy or laparotomy occurred in fewer than 5% of cases, and intraoperative and postoperative complication rates were low across all studies. Conclusions: vNOTES appears to be safe and potentially superior to other minimally invasive techniques. The small sample size of the case series and the lack of a sufficient number of comparative studies limit the strength of the conclusions. Full article

Staphylococcus aureus is the primary pathogen responsible for mastitis in dairy cows and foodborne illnesses, posing a significant threat to public health and food safety. Here, we developed an enhanced sensor based on solid-phase separation using gold-magnetic nanoparticles (Au@Fe₃O₄) and signal amplification via dendritic DNA nanostructures. The substrate chain was specifically immobilized using thiol–gold coordination, and a three-dimensional dendritic structure was constructed through sequential hybridization of DNAzymes, L chains, and Y chains, resulting in a 2.8-fold increase in initial fluorescence intensity. Upon specific cleavage of the substrate chain at the rA site by S. aureus DNA, the complex dissociates, resulting in fluorescence intensity decay. The fluorescence intensity is negatively correlated with the concentration of Staphylococcus aureus. After optimization, the biosensor maintains a detection limit of 1 CFU/mL within 3 min, with a linear range extended to 1–10⁷ CFU/mL (R² = 0.998) and recovery rates of 85.6–102.1%, significantly enhancing resistance to matrix interference. This provides an innovative solution for rapid on-site detection of foodborne pathogens. Full article

With the accelerated commercialization of autonomous vehicles, new accident types and complex risk factors have emerged beyond the scope of existing traffic safety management systems. This study aims to contribute to sustainable safety by establishing a quantitative basis for early recognition and response to high-risk situations in urban traffic environments where autonomous and conventional vehicles coexist. To this end, high-risk factors were identified through a combination of literature meta-analysis, accident history and image analysis, autonomous driving video review, and expert seminars. For analytical structuring, the six-layer scenario framework from the PEGASUS project was redefined. Using the analytic hierarchy process (AHP), 28 high-risk factors were identified. A risk prediction model framework was then developed, incorporating observational indicators derived from expert rankings. These indicators were structured as input variables for both road segments and autonomous vehicles, enabling spatial risk assessment through agent-based strategies. This space–object integration-based prediction model supports the early detection of high-risk situations, the designation of high-enforcement zones, and the development of preventive safety systems, infrastructure improvements, and policy measures. Ultimately, the findings offer a pathway toward achieving sustainable safety in mixed traffic environments during the initial deployment phase of autonomous vehicles. Full article

The recording of minerals extracted from a deposit is crucial for effective planning, exploitation management, and compliance with legal requirements. It also enables improved workplace safety and the minimization of negative environmental impact. Automation in mining optimizes exploitation, transportation, and data management processes, resulting in better forecasting, more accurate resource calculations, and reduced operational costs. The usage of geographic information system tools facilitates data modeling and analysis, enhancing monitoring and mining exploitation management. This paper presents the classical approach to determining the volume of extracted minerals and proposes GIS-based tools for the automation of the volume calculation process. The automation of the process is presented both from a theoretical perspective, providing requirements and parameters for individual calculation procedures, and from a practical perspective, using the example of a typical open pit mine, where the procedure is implemented starting from field measurements, carrying out calculations, and ending with visualization and interpretation. The study highlights the benefits of automating the calculation procedure for the volume of extracted minerals, including task execution acceleration, increased efficiency, reduced calculation time, and minimized human error. This ultimately leads to more precise and consistent results. Full article

Background: Over the past two decades, the Copenhagen Psychosocial Questionnaire (COPSOQ) has been established as a valid instrument to measure psychosocial stress at work. Currently, the COPSOQ international network is responsible for monitoring and improving the COPSOQ. In 2019, a new questionnaire was published, and the Greek version is now being validated. The aim of the current study was to assess the reliability and validity of the psychometric properties of the Greek long version of the Copenhagen Psychosocial Questionnaire III (COPSOQ-III-GR). Methods: The measurement qualities of the Greek COPSOQ III have been explored in accordance with the usual requirements of a validation study, as defined by DIN EN ISO 10075-3. A sample of observations from 2189 participants surveyed with the COPSOQ in Greece was used to validate the current version with appropriate statistical analyses. Exploratory factor analysis was used to assess the statistical relationships for many scales. Results: With its 108 items and 40 scales, the Greek COPSOQ III includes all internationally validated psychosocial workplace factors that remain comparable (~72%) with the COPSOQ III German version content. In addition to the primary results, congruence with widely used theoretical approaches such as the demand–control (−support) model (DCM) or the job demands–resources model (JDR) is generally satisfactory. In summary, our validation study for the Greek COPSOQ III version showed adequate reliability and validity, which is in line with the findings of the COPSOQ III questionnaire from other European countries, and it is also compatible with the validation of the German COPSOQ III. Our regression analysis revealed that 34 psychosocial workplace factors (34 “context” scales) could adequately predict the scores of the satisfactory and health scales (6 “outcome” scales). The analysis also revealed the top five predictors (context variables) for each of the six “effect” scales (outcome variables). Conclusions: With the launch of COPSOQ III in Greece, current and new workplace psychosocial aspects could be explored, since COPSOQ III (GR) appears to be a valid and reliable instrument for enterprise research and risk assessment. Full article

Autonomous UAV navigation in unknown and complex environments remains a core challenge, especially under limited sensing and computing resources. While most methods rely on modular pipelines involving mapping, planning, and control, they often suffer from poor real-time performance, limited adaptability, and high dependency on accurate environment models. Moreover, many deep-learning-based solutions either use RGB images prone to visual noise or optimize only a single objective. In contrast, this paper proposes a unified, model-free vision-based DRL framework that directly maps onboard depth images and UAV state information to continuous navigation commands through a single convolutional policy network. This end-to-end architecture eliminates the need for explicit mapping and modular coordination, significantly improving responsiveness and robustness. A novel multi-objective reward function is designed to jointly optimize path efficiency, safety, and energy consumption, enabling adaptive flight behavior in unknown complex environments. The trained policy demonstrates generalization in diverse simulated scenarios and transfers effectively to real-world UAV flights. Experiments show that our approach achieves stable navigation and low latency. Full article

mRNA-LNP-based COVID-19 vaccines, namely Pfizer-BioNTech’s Comirnaty and Moderna’s Spikevax, were successfully deployed to help control the SARS-CoV-2 pandemic, and their updated formulations continue to be recommended, albeit only for high-risk populations. One widely discussed aspect of these vaccines is their uniquely broad spectrum and increased incidence of adverse events (AEs), collectively referred to as post-vaccination syndrome (PVS). Although the reported PVS rate is low, the high number of administered doses among healthy individuals has resulted in a substantial number of reported vaccine-related injuries. A prominent manifestation of PVS is multisystem inflammation, hypothesized to result from the systemic transfection of organ cells with genetic instructions for a toxin, the spike protein, delivered with lipid nanoparticles (LNPs). In this narrative review, we focus on endothelial cells in the microcirculatory networks of various organs as primary sites of transfection with mRNA-LNP and consequent PVS. We outline the anatomical variations in the microcirculation contributing to the individual variability of symptoms and examine the molecular and cellular responses to vaccine nanoparticle exposure at the endothelial cell level with a focus on the pathways of a sustained cascade of toxic and autoimmune processes. A deeper understanding of the mechanisms underlying mRNA-LNP-induced AEs and PVS at the organ and cellular levels is critical for improving the safety of future vaccines and other therapeutic applications of this groundbreaking technology. Full article

Lambda-cyhalothrin (LCY), a widely used pyrethroid insecticide, is toxic to bees—vital pollinators experiencing global declines; however, its molecular effects during early development remain poorly understood. We investigated the molecular mechanisms underlying chronic sublethal exposure to LCY in the larval and adult stages. Larvae were exposed to LCY (0.004 µg active ingredient/larva), with four groups examined: solvent-treated larvae group (SLG), solvent-treated adult group (SAG), LCY-treated larvae group (LLG), and LCY-treated adult group (LAG). We identified 1128 and 168 significantly altered genes in LLG vs. SLG and LAG vs. SAG, respectively, with 125 larval- and 25 adult-specific DEGs, indicating stage-dependent toxicity. LCY dysregulated processes such as cuticle formation, sulfur metabolism, oxidoreductase activity, and neuropeptide signaling in larvae, while adults exhibited altered redox balance, peptide receptor signaling, and monoamine transport. Neuroactive signaling disruptions were observed in both stages, with additional effects on motor function, amino acid metabolism, and glycolysis in larvae; whereas adults exhibited altered lipid biosynthesis and energy metabolism. Downregulated genes involved in chitin metabolism and antioxidant defenses in larvae suggested compromised exoskeletal integrity and increased vulnerability. Overall, our findings highlight the long-term molecular consequences of early-life exposure and emphasize the need for safer pesticide practices to protect pollinator health. Full article

Next-generation pilot suits are evolving into intelligent, adaptive platforms that integrate advanced polymeric materials, smart textiles, and on-body artificial intelligence. High-performance polymers have advanced in mechanical strength, thermal regulation, and environmental resilience, with fabrication methods like electrospinning, weaving, and 3D/4D printing enabling structural versatility and sensor integration. In particular, functional nanomaterials and hierarchical nanostructures contribute critical properties such as conductivity, flexibility, and responsiveness, forming the foundation for miniaturized sensing and integrated electronics. The integration of flexible fiber-based electronics such as biosensors, strain sensors, and energy systems enables real-time monitoring of physiological and environmental conditions. Coupled with on-body AI for multimodal data processing, autonomous decision-making, and adaptive feedback, these systems enhance pilot safety while reducing cognitive load during flight. This review places a special focus on system-level integration, where polymers and nanomaterials serve as both structural and functional components in wearable technologies. By highlighting the role of nanostructured and functional materials within intelligent textiles, we underline a potential shift toward active human–machine interfaces in aerospace applications. Future trends and advancements in self-healing materials, neuromorphic computing, and dynamic textile systems will further elevate the capabilities of intelligent pilot suits. This review discusses interdisciplinary strategies for developing pilot wearables capable of responding to real-time physiological and operational needs. Full article

Inspired by the interpretability of Kolmogorov–Arnold Networks (KANs), a novel Pixel-level Feature Selection (PFS) model based on KANs (PFSKANs) is proposed as a fundamentally distinct alternative from trainable Convolutional Neural Networks (CNNs) and transformers in the computer vision tasks. We modify the simplification techniques of KANs to detect key pixels with high contribution scores directly at the input image. Specifically, a trainable selection procedure is intuitively visualized and performed only once, since the obtained interpretable pixels can subsequently be identified and dimensionally standardized using the proposed mathematical approach. Experiments on the image classification tasks using the MNIST, Fashion-MNIST, CIFAR-10, and CIFAR-100 datasets demonstrate that PFSKANs achieve comparable performance to CNNs in terms of accuracy, parameter efficiency, and training time. Full article