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The purpose of this study was to evaluate the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on cardiovascular disease (CVD) risk factors in adults with overweight and obesity. Twenty-two articles were included by searching six databases, the total number of subjects was 620 in these articles. Outcomes were synthesised using a random-effects meta-analysis of the Standardized mean difference (SMD) in CVD risk factors. HIIT and MICT resulted in statistically significant reductions in Weight, BMI, fat%, total cholesterol(TC), and improvement in VO2max. Compared with MICT, subgroup of durations of HIIT training interval ≥2 min can significantly increase VO2max (SMD = 0.444, 95% CI:0.037~0.851,P = 0.032), subgroup of energy expenditure of HIIT equal to MICT can significantly increase VO2max (SMD = 0.399, 95% CI:0.106~0.692,P = 0.008). HIIT appears to provide similar benefits to MICT for improving body composition, VO2maxand TC, but HIIT spent less time than MICT by 9.7 min on one session. HIIT is superior to MICT in improving cardiopulmonary fitness when durations of HIIT training interval ≥2 min or energy expenditure of HIIT same as MICT. PROSPERO ID: CRD42016045835.

In order to solve the problems of difficult control, poor stability, and low control precision in complex autonomous non‐linear systems, and some sensors have non‐linear errors in special environments. Based on the PSO (Particle Swarm Optimization) algorithm, an PSO‐BP‐PID (Particle Swarm Optimization Back Propagation neural network PID) control method and a sensor error compensation algorithm based on BP (Back Propagation) neural network are designed for optimal temperature and humidity control and sensor error compensation in the autonomous greenhouse system. The error between the average temperature value and the target value after steady state is 0.5°C, and the error between the average humidity value and the target value is 1% RH. The results show that the control method can effectively compensate the non‐linear error of the sensor and improve the performance of the control system in a complex environment, which is suitable for the stable and control of actuators in autonomous systems. The error of temperature and humidity sensor is compensated by BP neural network; PSO (Particle Swarm Optimization) was used to optimize the BP‐PID parameters of the automatic greenhouse system. The error of temperature and humidity sensor is compensated by BP neural network; Particle Swarm Optimization (PSO) was used to optimize the BP‐PID parameters of the automatic greenhouse system.

This study analysed the relationship between the structured and unstructured activities of preschoolers and their mental and physical health, and also investigated the predicted changes in mental and physical health by reallocating activity time. This cross-sectional study was carried out with 324 preschoolers. Video recording and SOPARC activity observation system was used for the division of structured and unstructured activities. An accelerometer sensor was used to measure activity intensity. The SDQ psychological questionnaire was adopted to collect data on internalizing difficulties, externalizing difficulties, total difficulties and pro-social behaviours. Physical indices including body shape (height, weight, BMI), and physical fitness (upper and lower limb strength, flexibility, agility, and balance) were collected using Chinese toddler physical fitness measurement tools. Component data and isotemporal reallocation analyses were conducted using R Studio (Version 4.2). A total of 308 preschoolers (160 boys; aged 4.50 ± 0.93 years) were included in the data analysis. The activities composition, adjusted for sex, area, mental level (for mental indicators), or age (for physical indicators), was significantly correlated with various measurement indicators ( p  < 0.05). Specifically, structured (β=-0.87, p  < 0.05) and unstructured (β=-1.24, p  < 0.05) moderate-to-vigorous physical activity (MVPA) were significantly positive correlated with internalizing difficulties, while structured MVPA was significantly positively correlated with body shape (β = 2.17, p  < 0.05). Replacing structured light physical activity (LPA) with 10 min of structured MVPA has a positive effect on internalizing difficulties (SMD=-1.28, 95%CI: -2.30 to -0.27) and body shape (SMD = 1.76, 95%CI: 0.37 to 3.15). When the total replacement time reaches 25 min, the benefits become even more pronounced. Structured and unstructured MVPA are both beneficial to preschoolers’ mental and physical health, with the incorporation of MVPA for over 25 min in structured activities and supplementary unstructured MVPA yielding even greater benefits.

The air-suction precision seed-metering device is prone to the instability of the seed adsorption state, which arises from blockage of the suction hole and leads to uneven seeding. This paper analyzed and determined key structural parameters of the seed-metering plate, then established an adsorption mechanics model of the seed during the migration process and designed the key structure of the air-suction seed-metering device with the aim of improving the uniformity of high-speed direct seeding of vegetables. Furthermore, we used the DEM-CFD coupling method to analyze the influence of the law of seeds on the change of the flow field with different hole types. Results showed that the turbulent kinetic energy (202.65 m2∙s−2) and the coupling force to the seeds (0.029 N) of the B-type hole are the largest, which is the best fluid domain structure for the suction hole of the seed-metering plate. Moreover, we used Adams to analyze the meshing process between the knock-out wheel and the seed-metering plate, affirming the rationality of the knock-out wheel design. Finally, in order to improve the working efficiency of the seed-metering device, we performed one-factor and response surface experiments of seeding performance using the air-suction seed-metering device designed with the optimized structure as the experimental object. Analysis of the influence of weights across each factor on the experimental performance evaluation indicators revealed an optimal combination of seeding performance parameters in the air-suction seed-metering device, namely a seed-throwing angle of 13°, a working speed of 14.5 km/h, and negative pressure of 3.1 kPa. Results from verification experiments revealed the corresponding experimental indicators, namely qualified, multiple, and missing indexes of 95.9, 1.2%, and 2.9%, respectively.

Objective This study aims to elucidate the dose‒response relationship between 24-h activity behaviors and body fat percentage (BFP) in Chinese preschool children using a compositional isotemporal substitution model (ISM). Methods In a cross-sectional design, 881 children aged 3–6 from urban and rural areas of Jiangxi Province were sampled. Activity behaviors, including sedentary behavior (SB), low-intensity physical activity (LPA), and moderate- to high-intensity physical activity (MVPA), were measured using accelerometers. Sleep patterns were assessed through questionnaires, and BFP was determined by bioelectrical impedance analysis (BIA). The study employed compositional data analysis (CoDA) and ISM to estimate the impact of reallocating durations of different activity behaviors on BFP. Results Higher BFP was found in urban vs. rural children, decreasing with age. Overweight and obesity rates were 10.6% and 7.6%, respectively, above national averages. MVPA and LPA were negatively correlated with BFP, while SB was positively correlated. A 30-min MVPA reduction significantly increased zBFR, particularly in overweight children. Gender-specific nuances revealed that boys' MVPA negatively influenced zBFP ( β  = -0.155), P  < 0.05), while girls' SB positively impacted zBFP ( β  = 0.636, P  <  0.01 ). Isotemporal simulations emphasized amplified effects in overweight children, with boys' zBFR rising rapidly when MVPA was substituted and girls displaying a notable substitution effect between SB and LPA. Conclusion BFP is closely linked to 24-h activity behaviors, notably in overweight and obese preschoolers. ISM identified MVPA as a critical influencer, with a 30-min reduction substantially increasing BFP. Gender disparities were evident, implicating MVPA in boys and LPA and SB in girls.

Objective To investigate the “supercompensation” effect of preschoolers during the coronavirus disease 2019 lockdown by comparing the changes in physical activity (PA), psychological, and sleep indicators before and after the lockdown. Methods A total of 127 children (aged 3–6 years) were recruited. Before and after the lockdown, the children’s PA levels were measured using the ActiGraph GT3X + , and their psychological and sleep indicators were measured using the Strengths and Difficulties Questionnaire (SDQ) and Child Sleep Habit Questionnaire (CSHQ), respectively. Results Regarding PA, the children’s total physical activity, low-intensity physical activity, and medium-intensity physical activity (MVPA) were higher after the lockdown than before the lockdown, with significant differences in MVPA ( p  < 0.05). Regarding psychology, the children’s SDQ and multidimensional scores were better after the lockdown than before the lockdown, with a significant difference in SDQ scores ( p  < 0.05). Regarding sleep, the children’s CSHQ scores were better after the lockdown than before the lockdown, with a highly significant difference in CSHQ scores ( p  < 0.01). Conclusion After lockdown, children’s PA, psychological, and sleep effects were “supercompensated.” In particular, the PA of preschoolers before, during, and after the lockdown may show a “baseline-inhibition-supercompensation” process.

Purpose. To evaluate the relationships between objectively measured physical activity and physical fitness among preschool children. Methods. A total of 346 participants (201 boys and 145 girls) aged 3.5–5.5 years (M=4.5 yr, SD = 0.47) from Shanghai, China, completed physical fitness assessments, including triceps skinfold thickness (TSFT), grip strength, tennis throwing, sit and reach test, standing long jump, balance beam, 10mSRT, and 20mSRT. Physical activity was objectively measured by ActiGraphGT3X+ accelerometer. Multiple linear regression models were used to explore the cross-sectional associations between PA and physical fitness after adjusting for age, gender, BMI, and valid wearing time. Results. Positive associations were observed between stand long jump (p<.01), tennis throwing (p<.01), laps in 20mSRT (p<.01), and MVPA. However, TSFT (p<.05), time in 10mSRT (p<.01), and balance beam (p<.05) were negatively associated with MVPA. Furthermore, positive associations were found between stand long jump (p<.01), tennis throwing (p<.01), and MVPA only in boys. Negative associations were found between time on balance beam (p<.01) and MVPA only in girls. Conclusions. MVPA appears to be an effective and reliable predictor of preschoolers’ physical fitness. Boys’ body composition, muscular strength, explosive strength, agility, aerobic fitness, girls’ agility, aerobic fitness, and balance could improve as MVPA increases.

This article proposes a method for compiling the load spectra of reducers for hybrid electric vehicles. Selecting typical working conditions for real vehicle data collection, the load data under each typical working condition were divided into five categories according to the state of the power source and the data were preprocessed. The optimal sample loads for compiling load spectra were obtained based on a multi-criteria decision-making method, rainflow counting for optimal sample loads was performed according to different power source output patterns, non-parametric extrapolation was performed to obtain the full-life two-dimensional load spectrum after dimensionality reduction, and a full-life eight-level programmed load spectrum that could be used for bench tests was obtained. Using the programmed load spectrum and the extracted sample load as the load input, a fatigue life prediction simulation of the reducer gear of a hybrid electric vehicle was carried out. The reducer gear fatigue life from the programmed load spectrum was compared to the gear fatigue life under actual load. The fatigue life of the reducer gear when the programmed load spectrum was used as the input was 1.412 × 103. When the actual load was used as the input load, the fatigue life of the reducer gear was 1.933 × 103. The relative error between the two is only 26%, which is in the normal range. The results show that the programmed load spectrum is effective and reliable and that the load spectrum compilation method provides a basis for accurately evaluating the reliability of the hybrid electric vehicle reducer.

In order to precisely reproduce the precise seeding process of the population in the air-suction seed-metering device, it is necessary to execute accurate modeling of seed particles using the bonded-particle model, in combination with the discrete element method (DEM) and computational fluid dynamics (CFD). Through the repose angle, slope screening, rotating container, and particle sedimentation experiments, in this paper, the influence of the filling accuracy of the bonded-particle model on the flow behavior and mixing characteristics of the seed population was first explored based on EDEM software. The viability of the suggested modeling approach for pelleted vegetable seeds, as described in this study, was confirmed by comparing experimental and simulation outcomes. The surface roughness values obtained from the studies above were utilized to assess the accuracy of the bonded-particle model in filling. Additionally, a mathematical technique for determining the surface roughness was provided. Furthermore, an analysis of the multiple contacts in the bonded-particle model was also performed. The results indicated that the simulation results closely matched the experimental data when the number of sub-spheres in the bonded-particle model was equal to or more than 70, as measured by the standard deviation. In addition, the most optimal modeling scheme for the pelletized vegetable seed bonded-particles, based on the cost of coupling simulation, was found to be the bonded-particle surface roughness (BS) with a value of 0.1. Ultimately, a practical example was utilized to demonstrate the utilization of the pelleted vegetable seed bonded-particle model and the DEM-CFD coupling approach in analyzing the accuracy of the seeding process in the air-suction seed-metering device. This example will serve as a valuable reference point for future field studies.

Visual simultaneous localization and mapping (VSLAM) is a foundational technology that enables robots to achieve fully autonomous locomotion, exploration, inspection, and more within complex environments. Its applicability also extends significantly to agricultural settings. While numerous impressive VSLAM systems have emerged, a majority of them rely on static world assumptions. This reliance constrains their use in real dynamic scenarios and leads to increased instability when applied to agricultural contexts. To address the problem of detecting and eliminating slow dynamic objects in outdoor forest and tea garden agricultural scenarios, this paper presents a dynamic VSLAM innovation called MOLO-SLAM (mask ORB label optimization SLAM). MOLO-SLAM merges the ORBSLAM2 framework with the Mask-RCNN instance segmentation network, utilizing masks and bounding boxes to enhance the accuracy and cleanliness of 3D point clouds. Additionally, we used the BundleFusion reconstruction algorithm for 3D mesh model reconstruction. By comparing our algorithm with various dynamic VSLAM algorithms on the TUM and KITTI datasets, the results demonstrate significant improvements, with enhancements of up to 97.72%, 98.51%, and 28.07% relative to the original ORBSLAM2 on the three datasets. This showcases the outstanding advantages of our algorithm.