Search Results (117)

The plant Synsepalum dulcificum is notable for its considerable edible and medicinal value, with a longstanding history as a folk remedy for diabetes. Its chemical constituents are rich and structurally diverse. However, there is limited information regarding the metabolic basis of these characteristics, and the biological activities and mechanisms underlying its blood glucose-lowering effects remain incompletely understood. In this study, we conducted a widely targeted metabolomics analysis of the stems, leaves, and fruits of S. dulcificum using UPLC-ESI-MS/MS to compare the differences in metabolite profiles among these three tissue types. Our analysis identified a total of 2544 secondary metabolites, primarily consisting of flavonoids and triterpenes, categorized into thirteen distinct compound classes. We selected differential metabolites through multivariate statistical analysis, revealing significant differences among the metabolite profiles of the three tissue types, with flavonoids being the most abundant compounds. Furthermore, we investigated the anti-diabetic mechanisms and potential pharmacological components of S. dulcificum utilizing network pharmacology and molecular docking techniques. Finally, the α-glucosidase inhibitory activity of the potential active components was evaluated using in vitro experiments. These findings establish a foundation for the future application of S. dulcificum in the prevention and treatment of diabetes. Full article

Pear buds exhibit inherent dormancy, during which carbohydrates play a pivotal role in dormancy release and germination. In this study, Pyrus pyrifolia ‘Cuiguan’ was employed as the experimental material to investigate the molecular mechanisms underlying flower bud dormancy release. The results revealed that the dynamic balance between starch and soluble sugar is critical for promoting dormancy release and germination in P. pyrifolia ‘Cuiguan’ flower buds. Through transcriptomic and proteomic profiling, a total of 4035 differentially expressed genes (DEGs) and 1596 differentially expressed proteins (DEPs) were identified, which were predominantly associated with carbohydrate metabolism, particularly sugar metabolism pathways. Their changes were coordinately regulated at both transcriptional and translational levels. Key structural genes involved in maltose and sucrose biosynthesis, including BAM (LOC103949270), AAM (LOC125479337, LOC103940334, and LOC103941903), SPS (LOC125475683), and INV (LOC125478747), were significantly upregulated during the germination stage, facilitating flower bud sprouting. Integrated multi-omic analysis demonstrated that starch–sugar interconversion may govern dormancy release and sustained bud growth by modulating sugar metabolism-related genes and proteins. These findings provide novel insights into the molecular mechanisms of carbohydrate biosynthesis and associated protein regulation during dormancy release and development of P. pyrifolia ‘Cuiguan’ under natural conditions. Full article

Metabolic syndrome has emerged as a significant global public health concern worldwide, characterized by a cluster of interrelated risk factors such as hypertension, hyperlipidemia, hyperglycemia, and abdominal obesity. In recent years, functional foods containing bioactive phytochemicals have attracted considerable scientific interest as potential therapeutic approaches for metabolic syndrome management. Xanthones, a class of naturally occurring tricyclic phenolic compounds abundant in various fruits and medicinal plants, demonstrate diverse biological activities relevant to metabolic health. This comprehensive review examines the dietary sources of xanthones, their bioactivity, and their promising role as functional food components for mitigating metabolic syndrome. The underlying mechanisms of action include modulation of lipid metabolism, improvement of insulin signaling pathways, potent anti-inflammatory and antioxidant effects, and modulation of glucose metabolism. Additionally, we discuss the stability and processing considerations of xanthones in food products. These findings highlight the development of xanthone-enriched functional foods and nutraceuticals as dietary interventions for metabolic syndrome prevention and management. This review comprehensively covers all relevant studies published up to the present without time restrictions. Full article

In this paper, the aerodynamic performance of an improved hybrid vertical-axis wind turbine is investigated, and the performance of the hybrid turbine at high tip–speed ratios is significantly enhanced by adding a spoiler at the end of the inner rotor. The improved design increases the average torque coefficient by 7.4% and the peak power coefficient by 32.4%, which effectively solves the problem of power loss due to the negative torque of the inner rotor in the conventional hybrid turbine at high TSR; the spoiler improves the performance of the outer rotor in the wake region by optimizing the airflow distribution, reducing the counter-pressure differential, lowering the inner rotor drag and at the same time attenuating the wake turbulence intensity. The study verifies the validity of the design through 2D CFD simulation, and provides a new idea for the optimization of hybrid wind turbines, which is especially suitable for low wind speed and complex terrain environments, and is of great significance for the promotion of renewable energy technology development. Full article

Intelligent operation and maintenance of urban rail transit systems is essential for improving train safety and efficiency. This study focuses on reducing time, physical effort, and safety risks in deploying intelligent metro inspection robots. This study introduces a design approach for an undercarriage robot simulation system and an offline teaching method. Gazebo and Isaac Sim are combined in this study. Gazebo is used for lightweight simulation in model development and algorithm testing. Isaac Sim is used for high-fidelity rendering and robust simulation in complex large-scale scenarios. This combined approach addresses critical aspects of system development. The research proposes environment data collection and processing methods for metro inspection scenarios. It also provides solutions for hole problems in point cloud mesh models and approaches for robot modeling and sensor configuration. Additionally, it involves developing a target vector labeling platform. Using these elements, an offline teaching system for undercarriage inspection robots has been designed with simulation tools. Offline teaching is unrestricted by on-site space and time. It reduces physical demands and boosts robot teaching efficiency. Experimental results indicate that it takes about 30 s to program a single manipulator motion offline. In contrast, manual on-site teaching takes about 5 min. This represents a significant efficiency improvement. While offline teaching results have some errors, high success rates can still be achieved through error correction. Despite challenges in modeling accuracy and sensor data precision, the simulation system and offline teaching approach decrease metro vehicle operation risks and enhance robot deployment efficiency. They offer a novel solution for intelligent rail transit operation and maintenance. Future research will focus on high-quality environmental point cloud data collection and processing, high-precision model development, and enhancing and expanding simulation system functionality. Full article

Autonomous underwater vehicle inspection in 3D environments presents significant challenges in spatial mapping for obstacle avoidance and motion control. Current solutions rely on either 2D forward-looking sonar or expensive 3D sonar systems. To address these limitations, this study proposes a cost-effective 3D reconstruction method using an oscillatory forward-looking sonar with a pan-tilt mechanism that extends perception from a 2D plane to a 75-degree spatial range. Additionally, a polar coordinate-based frontier extraction method for sequential sonar images is introduced that captures more complete contour frontiers. Through bridge pier scanning validation, the system shows a maximum measurement error of 0.203 m. Furthermore, the method is integrated with the Ego-Planner path planning algorithm and nonlinear Model Predictive Control (MPC) algorithm, creating a comprehensive underwater 3D perception, planning, and control system. Gazebo simulations confirm that generated 3D point clouds effectively support the Ego-Planner method. Under localisation errors of 0 m, 0.25 m, and 0.5 m, obstacle avoidance success rates are 100%, 60%, and 30%, respectively, demonstrating the method’s potential for autonomous operations in complex underwater environments. Full article

With increasing concerns over climate change and air pollution, sustainable transportation has become a critical component of modern city planning. Bike-sharing systems have emerged as an eco-friendly alternative to motorized transport, contributing to energy conservation and emission reduction. To elaborate on bike-sharing’s contribution to urban sustainable development, this study conducts a quantitative analysis of its environmental benefits through a case study of the Bluebikes program in the Boston area, using a longitudinal dataset of 20.07 million bike trips from January 2015 to December 2024, with data between January 2020 and December 2021 excluded. A combination of Scheiner’s model and Multinomial Logit model was adopted to evaluate the substitution of Bluebikes trips, an optimized Seasonal Autoregressive Integrated Moving Average (SARIMA) model was employed to predict future usage, while energy savings were calculated by estimating reductions in gasoline and diesel consumption. The findings reveal that during the analyzed period, Bluebikes trips saved 2616.44 tons of oil equivalent and reduced CO₂ and NO_X emissions by 7614.96 and 16.43 tons, respectively. Furthermore, based on the historical trends, it is forecasted that the Bluebikes program will annually save an average of 723.66 tons of oil equivalent and decrease CO₂ and NO_X emissions by 2422.65 and 4.52 tons between 2025 and 2027. The results highlight the substantial environmental impact of Bluebikes and support policies that encourage their usage. Full article

Major public health events pose a huge challenge to the sustainable improvement of city dwellers’ ecological well-being, hindering the achievement of urban ecological construction goals. In the context of resilient city and all-aged friendly city construction, age factor is given special consideration in urban green space management to meet the heterogeneous demands and preferences of city dwellers for urban ecological benefit. However, young, middle-age and elderly city dwellers’ utilization of urban green spaces during different periods of pandemic are poorly known. Meanwhile, insufficient discussion on the differences in ecological well-being contributions of different types of urban green spaces has led to difficulties in effectively connecting urban green space management planning with the city dwellers’ demands for ecological well-being. To help fill this gap, this study utilizes field study data on urban ecological construction and urban landscape and greening in Beijing from 2019 to 2023 to analyze the evolution and differences in utilization behaviors of urban green space among different age group city dwellers. Furthermore, this study applies the ordinary least square regression model (OLS) to explore the differences in the impact of various types of urban green space on the ecological well-being of city dwellers. The results revealed significant age effects in the utilization of urban green space during 2019–2023. It outlines the increased time spent in urban green space by younger city dwellers. In addition, the results demonstrated that the utilization behavior of park green space has a significant positive impact on the ecological well-being level of city dwellers, and the impact of utilization behavior on the ecological well-being level of city dwellers varies depending on the type of green space. Compared with community green space, the impact of park green space utilization behavior on the ecological well-being level of city dwellers is more significant. The conclusion from the main urban area of this Beijing case study contributes to the international discussion on urban green space management and urban green resilience governance in metropolitan areas worldwide as they add additional insights on the change and difference in the utilization behavior of urban green spaces, particularly looking at elderly, middle-aged and young city dwellers as well as the importance of a timely response to the heterogeneity preference of city dwellers’ ecological well-being demand. Full article

Cycling significantly contributes to improving metro accessibility; however, the quality of bicycle environments surrounding metro stations remains insufficiently studied. This study develops a criteria–indicators assessment framework that incorporates both objective characteristics of bicycle infrastructure and subjective perceptions of bicycle access to metro stations. The framework consists of four primary criteria—accessibility, convenience, safety, and comfort—along with eighteen sub-level indicators. Taking central Tianjin as the study area, the study evaluated the cycling environment quality around eight representative metro stations by employing information entropy and the analytic hierarchy process, with cosine similarity used to compare the outcomes against human–machine adversarial scoring result to ensure analytical robustness. The findings reveal substantial disparities in cycling infrastructure, with safety and accessibility exhibiting higher scores than convenience and comfort. Additionally, cycling environment quality is higher around comprehensive and public-service stations compared to residential stations, while commercial stations exhibit the lowest quality. The study underscores the necessity of expanding protected bike lanes, enhancing route directness, and improving parking and wayfinding facilities to promote cycling as an effective first- and last-mile metro access mode. Full article

Compared with traditional immunoassay methods, microfluidic immunoassay restricts the immune response in confined microchannels, significantly reducing sample consumption and improving reaction efficiency, making it worthy of widespread application. This paper proposes an exciting multi-frequency electrothermal flow (MET) technique by applying combined standing-wave and traveling-wave voltage signals with different oscillation frequencies to a three-period quadra-phase discrete electrode array, achieving rapid immunoreaction on functionalized electrode surfaces within straight microchannels, by virtue of horizontal pumping streamlines and transverse stirring vortices induced by nonlinear electrothermal convection. Under the approximation of a small temperature rise, a linear model describing the phenomenon of MET is derived. Although the time-averaged electrothermal volume force is a simple superposition of the electrostatic body force components at the two frequencies, the electro-thermal-flow field undergoes strong mutual coupling through the dual-component time-averaged Joule heat source term, further enhancing the intensity of Maxwell–Wagner smeared structural polarization and leading to mutual influence between the standing-wave electrothermal (SWET) and traveling-wave electrothermal (TWET) effects. Through thorough numerical simulation, the optimal working frequencies for SWET and TWET are determined, and the resulting synthetic MET flow field is directly utilized for microfluidic immunoassay. MET significantly promotes the binding kinetics on functionalized electrode surface by simultaneous global electrokinetic transport along channel length direction and local chaotic stirring of antigen samples near the reaction site, compared to the situation without flow activation. The MET investigated herein satisfies the requirements for early, rapid, and precise immunoassay of test samples on-site, showing great application prospects in remote areas with limited resources. Full article

Metallic thin-walled porous tubes have been widely applied in energy absorption fields due to their unique mechanical properties. Inspired by foam-filled structures, liquid crystal elastomers as a new category of metamaterials were filled in metallic thin-walled porous tubes to obtain a novel composite energy-absorbing structure that can improve energy-absorbing capabilities. By means of experiments and numerical simulations, this paper investigated deformation modes and the energy-absorbing performance of metallic thin-walled porous tubes filled with liquid crystal elastomers under dynamic crush. Moreover, the effects of geometric parameters on deformation modes and the energy-absorbing performance of the metallic thin-walled porous tubes filled with liquid crystal elastomers were analyzed. The results show that liquid crystal elastomers can enhance energy-absorbing capabilities under dynamic crush and geometric parameters can affect deformation modes, further affecting the energy-absorbing performance of metallic thin-walled porous tubes filled with liquid crystal elastomers. Full article

Balance assessment is crucial for health monitoring and rehabilitation evaluation of neurological diseases like Parkinson’s disease (PD) and stroke. The Berg Balance Scale (BBS) is a widely used clinical tool for balance evaluation. However, its dependence on trained therapists for subjective, time-consuming assessments limits its scalability. Current researchers have proposed several automated assessment systems. However, they suffer from difficulty in use in clinical settings and the need for feature engineering. The rapid advancement of wearable inertial measurement units (IMUs) provides an objective tool for motion analysis that is suitable for use in clinical environments. Thus, to address the limitations of manual scoring and complexities of capturing gait features, we proposed an automated BBS assessment system using an attention-based deep learning algorithm with IMU data, integrating convolutional neural networks (CNNs) for spatial feature extraction, bidirectional long short-term memory (Bi-LSTM) networks for temporal modeling, and attention mechanisms to emphasize informative features. Validated with 20 healthy subjects (young and elderly) and 20 patients (PD and stroke), the system achieved a mean absolute error (MAE) of 1.1627 and root mean squared error (RMSE) of 1.5333. Requiring only 5 min of walking data, this approach provided an efficient, objective solution for balance assessment to assist healthcare physicians as well as patients in their own health monitoring. The key limitations included: a limited generalizability to severely impaired patients who were unable to walk independently, and the inability to predict the score of individual tasks. Full article

In this study, a quantitative profiling method for detecting free fatty acids in crude lanolin based on the Quality by Design (QbD) concept was developed. High-performance liquid chromatography (HPLC) equipped with a charged aerosol detector (CAD) and a Proshell 120 EC C18 column was employed for the separation of crude lanolin components. Initially, the analytical target profile and critical method attributes were defined. Potential critical method parameters, including column temperature, flow rate, isocratic run time, gradient end organic phase ratio, and gradient time, were identified using fishbone diagrams and single-factor experiments. The definitive screening design (DSD) was then utilized to screen and optimize these parameters. Stepwise regression was applied to establish quantitative models between the critical method attributes and the method parameters. Subsequently, the method operable design region (MODR) was calculated and was successfully verified. The analytical conditions established were configured with 0.1% formic acid in water and 0.1% formic acid in acetonitrile serving as the mobile phases. The flow rate was set at 0.8 mL/min, and the column temperature was maintained at 35 °C with the evaporation tube temperature also set at 35 °C. An injection volume of 10 μL was used for each analysis. The gradient elution conditions were as follows: from 0 to 30 min, 75% of solvent B was used, and from 30 to 60 min, the proportion of solvent B was increased from 75% to 79%. Ten components, including 12-hydroxystearic acid, 2-hexyldecanoic acid, and palmitic acid, were identified by mass spectrometry, and seven common peaks were found in the fingerprints. The contents of palmitic acid, oleic acid, and stearic acid in the crude lanolin were quantitatively determined. Both the fingerprint and quantitative analysis methods were validated. The method was applied to analyze 15 batches of crude lanolin from different sources. The new established quantitative profiling method for free fatty acids can be potentially used for industrial applications to enhance the quality control of crude lanolin. Full article

An enhanced chaotic particle swarm optimization fuzzy PID is introduced to address the hydraulic wind turbine grid-connected speed control conditions. In the enhanced algorithm, a Circle chaotic mapping is combined with particle swarm optimization (PSO) to prevent PSO from becoming trapped in local optima. Moreover, a linear inertia weight reduction strategy is integrated to harmonize the algorithm’s capacity for expansive exploration and meticulous exploitation. Then, the enhanced algorithm is utilized to adjust and perfect the configuration variables within the fuzzy PID system. Based on the optimization, speed characteristics of the variable motor are analyzed. Simulation results show that when the swash plate angle factor varies within a specific range, the variable motor speed is only related to the quantitative pump speed. When the input speed of the quantitative pump changes in a step from 400 to 500 r/min, the enhanced CPSO fuzzy PID control approach reduces ascension time by 40% and 76%, and settling time by 80% and 76%, compared to the fuzzy PID and PSO fuzzy PID control approaches, respectively. When the input speed changes in a step from 500 to 600 r/min, the approach reduces ascension time by 25% and 72%, and settling time by 80% and 72%, respectively. When the input speed varies within a range of 400–500 r/min, the approach reduces ascension time by 37.5% and 80%, and settling time by 83% and 80%, respectively. And the enhanced CPSO fuzzy PID speed-control system exhibits no overshoot. Therefore, the enhanced CPSO fuzzy PID algorithm enhances the quantitative pump-motor system’s stability and rapidity, meeting hydraulic wind turbine grid-connected speed-control needs. Full article

As one of the largest gene families in plants, the Leucine-Rich Repeat Receptor-Like Kinase (LRR-RLK) genes are involved in important biological processes, such as plant growth and development and response to bio-/abiotic stresses. The rubber tree (Hevea brasiliensis Müll. Arg.) is the primary commercial source of natural rubber globally. In this study, 274 LRR-RLK genes were comprehensively identified and classified into 21 subclades of the rubber tree genome. Members belonging to the same subclade exhibited comparable gene structures and possessed conserved protein motifs. Gene duplication analysis detected 35 tandem duplication genes and 81 segmental duplication genes. Cis-element analysis of HbLRR-RLK promoters identified light, hormone, stress, and development-related cis-elements. Tissue-specific expression profiling revealed that 73% (200/274) of HbLRR-RLKs were expressed in at least one of seven analyzed tissues. Protein–protein interaction (PPI) network identified 584 potential interactions among the HbLRR-RLKs. Additionally, subcellular localization analysis suggested that HbPSKR2 (HbLRR-RLK174) is a plasma membrane-localized receptor, and the gene could restore the short-root phenotype of the atpskr mutant in Arabidopsis. These results provide a comprehensive structure to facilitate analysis of the evolution and functional diversification of LRR-RLKs in the rubber tree. Full article