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Limb motion capture is essential in human motion-recognition, motor-function assessment and dexterous human-robot interaction for assistive robots. Due to highly dynamic nature of limb activities, conventional inertial methods of limb motion capture suffer from serious drift and instability problems. Here, a motion capture method with integral-free velocity detection is proposed and a wearable device is developed by incorporating micro tri-axis flow sensors with micro tri-axis inertial sensors. The device allows accurate measurement of three-dimensional motion velocity, acceleration, and attitude angle of human limbs in daily activities, strenuous, and prolonged exercises. Additionally, we verify an intra-limb coordination relationship exists between thigh and shank in human walking and running, and establish a neural network model for it. Using the intra-limb coordination model, dynamic motion capture of human lower limbs including thigh and shank is tactfully implemented by a single shank-worn device, which simplifies the capture device and reduces cost. Experiments in strenuous activities and long-time running validate excellent performance and robustness of the wearable device in dynamic motion recognition and reconstruction of human limbs. Current wearable motion capture technologies are unable to accurately detect dynamic motion of human limbs due to drift and instability problems. Here, the authors report a wearable motion capture device combining tri-axis velocity sensor and inertial sensors for accurate 3D limb motion capture.

Fine particulate matter (PM2.5) is a severe air pollution problem in China. Observations of PM2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC). The data show a general 30 %–50 % decrease in annual mean PM2.5 across China over the 2013–2018 period, averaging at −5.2 µg m−3 a−1. Trends in the five megacity cluster regions targeted by the government for air quality control are -9.3±1.8 µg m−3 a−1 (±95 % confidence interval) for Beijing–Tianjin–Hebei, -6.1±1.1 µg m−3 a−1 for the Yangtze River Delta, -2.7±0.8 µg m−3 a−1 for the Pearl River Delta, -6.7±1.3 µg m−3 a−1 for the Sichuan Basin, and -6.5±2.5 µg m−3 a−1 for the Fenwei Plain (Xi'an). Concurrent 2013–2018 observations of sulfur dioxide (SO2) and carbon monoxide (CO) show that the declines in PM2.5 are qualitatively consistent with drastic controls of emissions from coal combustion. However, there is also a large meteorologically driven interannual variability in PM2.5 that complicates trend attribution. We used a stepwise multiple linear regression (MLR) model to quantify this meteorological contribution to the PM2.5 trends across China. The MLR model correlates the 10 d PM2.5 anomalies to wind speed, precipitation, relative humidity, temperature, and 850 hPa meridional wind velocity (V850). The meteorology-corrected PM2.5 trends after removal of the MLR meteorological contribution can be viewed as being driven by trends in anthropogenic emissions. The mean PM2.5 decrease across China is −4.6 µg m−3 a−1 in the meteorology-corrected data, 12 % weaker than in the original data, meaning that 12 % of the PM2.5 decrease in the original data is attributable to meteorology. The trends in the meteorology-corrected data for the five megacity clusters are -8.0±1.1 µg m−3 a−1 for Beijing–Tianjin–Hebei (14 % weaker than in the original data), -6.3±0.9 µg m−3 a−1 for the Yangtze River Delta (3 % stronger), -2.2±0.5 µg m−3 a−1 for the Pearl River Delta (19 % weaker), -4.9±0.9 µg m−3 a−1 for the Sichuan Basin (27 % weaker), and -5.0±1.9 µg m−3 a−1 for the Fenwei Plain (Xi'an; 23 % weaker); 2015–2017 observations of flattening PM2.5 in the Pearl River Delta and increases in the Fenwei Plain can be attributed to meteorology rather than to relaxation of emission controls.

Energy‐autonomous wearable human activity monitoring is imperative for daily healthcare, benefiting from long‐term sustainable uses. Herein, a fully self‐powered wearable system, enabling real‐time monitoring and assessments of human multimodal health parameters including knee joint movement, metabolic energy, locomotion speed, and skin temperature, which are fully self‐powered by highly‐efficient flexible thermoelectric generators (f‐TEGs) is proposed and developed. The wearable system is composed of f‐TEGs, fabric strain sensors, ultra‐low‐power edge computing, and Bluetooth. The f‐TEGs worn on the leg not only harvest energy from body heat and supply power sustainably for the whole monitoring system, but also serve as zero‐power motion sensors to detect limb movement and skin temperature. The fabric strain sensor made by printing PEDOT: PSS on pre‐stretched nylon fiber‐wrapped rubber band enables high‐fidelity and ultralow‐power measurements on highly‐dynamic knee movements. Edge computing is elaborately designed to estimate multimodal health parameters including time‐varying metabolic energy in real‐time, which are wirelessly transmitted via Bluetooth. The whole monitoring system is operated automatically and intelligently, works sustainably in both static and dynamic states, and is fully self‐powered by the f‐TEGs. A fully self‐powered wearable system is developed for monitoring knee joint movement, skin temperature, locomotion speed, and metabolic energy, which is entirely powered by highly‐efficient flexible thermoelectric generators (f‐TEGs). The wearable system integrates f‐TEGs, fabric strain sensor, edge computing, and Bluetooth, which works sustainably in both static and dynamic states, enabling real‐time monitoring and assessment of human motion and health.

While research on physical exercise has predominantly focused on rational decision-making behaviors related to health benefits, comparatively less attention has been paid to achievement emotion and its role in promoting physical exercise. Building upon dual-system theory (DST), this study examines whether achievement emotion mediates between social support and physical exercise, integrating expected value and information processing theories. It also explores how this mediation effect depends on sports motivation and feedback literacy. A questionnaire survey was conducted among 534 college students (281 male, 253 female). Data were analysed using hierarchical regression procedures in terms of moderated mediation. The results show that achievement emotion partially mediates the relationship between social support and physical exercise. Specifically, the interaction of social support × sports motivation indicates that the strength of the relationship between social support and achievement emotion increases linearly with higher levels of sports motivation; similarly, the interaction of social support × feedback literacy indicates that the strength of the relationship between social support and physical exercise also increases linearly through feedback literacy level. Finally, the interaction of achievement emotion × feedback literacy indicates that the strength of the relationship between achievement emotion and physical exercise increases linearly through feedback literacy level. These findings suggest that attention should be paid to achievement emotion, sports motivation, and feedback literacy when designing social support interventions to promote physical exercise. This research provides a theoretical reference for improving levels of physical exercise among college students.

Overactive bladder (OAB) is a common condition that significantly affects quality of life. Magnesium deficiency may influence muscle and nerve functions, potentially contributing to bladder dysfunction. This study aimed to examine whether magnesium depletion is associated with OAB symptoms among U.S. adults. We analyzed data from 28,621 participants aged 20–80 years in the National Health and Nutrition Examination Survey (NHANES) 2005–2018. OAB symptoms were assessed using a standardized questionnaire, and magnesium depletion was evaluated using a magnesium depletion score (MgDS). Logistic regression models adjusted for demographic, lifestyle, and clinical factors were employed to explore the association. Higher MgDS was significantly associated with an increased risk of OAB. In the fully adjusted model, each one-point increase in MgDS was linked to 9% higher odds of OAB (OR = 1.09, 95% CI 1.03–1.15, p  = 0.002). Compared to the low MgDS group, individuals in the middle MgDS group had 17% higher odds of OAB (OR = 1.17, 95% CI 1.03–1.33, p  = 0.02), while those in the high MgDS group had 20% higher odds (OR = 1.20, 95% CI 1.05–1.38, p  = 0.01). Subgroup analyses indicated that this association was particularly pronounced in females, non-smokers, middle-aged adults (40–60 years), and individuals with obesity (BMI ≥ 30 kg/m 2 ). Our findings suggest that magnesium depletion is associated with increased OAB risk in U.S. adults; however, due to the cross-sectional nature of this study, causality cannot be inferred and further prospective studies are needed.

Carbonaceous aerosols significantly affect global radiative forcing and climate through absorption and the scattering of sunlight. Black carbon (BC) and brown carbon (BrC) are light-absorbing carbonaceous aerosols. The direct radiative effect (DRE) of BrC is uncertain. A recent study suggests that BrC absorption is comparable to BC in the upper troposphere over biomass burning regions and that the resulting radiative heating tends to stabilize the atmosphere. Yet current climate models do not include proper physical and chemical treatments of BrC. In this study, we derived a BrC global biomass burning emission inventory on the basis of the Global Fire Emissions Database version 4 (GFED4), developed a module to simulate the light absorption of BrC in the Community Atmosphere Model version 5 (CAM5) of the Community Earth System Model (CESM), and investigated the photobleaching effect and convective transport of BrC on the basis of Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry Project (DC3) measurements. The model simulations of BC were also evaluated using HIAPER (High-Performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) measurements. We found that globally BrC is a significant absorber, the DRE of which is 0.10 W m−2, more than 25 % of BC DRE (+0.39 W m−2). Most significantly, model results indicated that BrC atmospheric heating in the tropical mid and upper troposphere is larger than that of BC. The source of tropical BrC is mainly from wildfires, which are more prevalent in the tropical regions than higher latitudes and release much more BrC relative to BC than industrial sources. While BC atmospheric heating is skewed towards the northern mid-latitude lower atmosphere, BrC heating is more centered in the tropical free troposphere. A possible mechanism for the enhanced convective transport of BrC is that hydrophobic high molecular weight BrC becomes a larger fraction of the BrC and less easily activated in a cloud as the aerosol ages. The contribution of BrC heating to the Hadley circulation and latitudinal expansion of the tropics is likely comparable to BC heating.

Since its first confirmed case at the end of 2019, COVID-19 has become a global pandemic in three months with more than 1.4 million confirmed cases worldwide, as of early April 2020. Quantifying the changes of pollutant emissions due to COVID-19 and associated governmental control measures is crucial to understand its impacts on economy, air pollution, and society. We used the WRF-GC model and the tropospheric NO2 column observations retrieved by the TROPOMI instrument to derive the top-down NOx emission change estimation between the three periods: P1 (January 1st to January 22nd, 2020), P2 (January 23rd, Wuhan lockdown, to February 9th, 2020), and P3 (February 10th, back-to-work day, to March 12th, 2020). We found that NOx emissions in East China averaged during P2 decreased by 50% compared to those averaged during P1. The NOx emissions averaged during P3 increased by 26% compared to those during P2. Most provinces in East China gradually regained some of their NOx emissions after February 10, the official back-to-work day, but NOx emissions in most provinces have not yet to return to their previous levels in early January. NOx emissions in Wuhan, the first epicenter of COVID-19, had no sign of emission recovering by March 12. A few provinces, such as Zhejiang and Shanxi, have recovered fast, with their averaged NOx emissions during P3 almost back to pre-lockdown levels.

Magnetic rings are widely used in automotive, home appliances, and consumer electronics. Due to the materials used, processing techniques, and other factors, there will be top cracks, internal cracks, adhesion, and other defects on individual magnetic rings during the manufacturing process. To find such defects, the most sophisticated YOLOv5 target identification algorithm is frequently utilized. However, it has problems such as high computation, sluggish detection, and a large model size. This work suggests an enhanced lightweight YOLOv5 (MR-YOLO) approach for the identification of magnetic ring surface defects to address these issues. To decrease the floating-point operation (FLOP) in the feature channel fusion process and enhance the performance of feature expression, the YOLOv5 neck network was added to the Mobilenetv3 module. To improve the robustness of the algorithm, a Mosaic data enhancement technique was applied. Moreover, in order to increase the network’s interest in minor defects, the SE attention module is inserted into the backbone network to replace the SPPF module with substantially more calculations. Finally, to further increase the new network’s accuracy and training speed, we substituted the original CIoU-Ioss for SIoU-Loss. According to the test, the FLOP and Params of the modified network model decreased by 59.4% and 47.9%, respectively; the reasoning speed increased by 16.6%, the model’s size decreased by 48.1%, and the mAP only lost by 0.3%. The effectiveness and superiority of this method are proved by an analysis and comparison of examples.

As the rotating speed of aviation gears becomes higher and higher, the influence of windage resistance on jet streamline must be considered in lubrication system design. To provide theoretical guidance for nozzle layout, an analytical model to calculate the windage impingement depth of gears is proposed. To obtain the best oil jet lubrication effect, the multi-objective optimization design method of oil jet streamline layout parameters with the largest impingement depth and the smallest impingement depth difference between two gears was proposed. CFD simulation analysis of flow field around gears are conducted to study the influence of jet nozzle layout parameters on the oil distribution and oil pressure. The results show that: the modulus and transmission ratio mainly affect the value range of oil jet streamline offset, and the correlation is positive. With the increase of inclination angle and initial offset, the impingement depth of the two gears is negatively correlated. The optimized oil jet streamline layout parameters of the case in the article are S  = 0.53 mm, β  = 4.6°, and the impingement depth difference between the two wheels of the gear pair after optimization is reduced by more than 50.3%. Calculation results are consistent with CFD, which validates the effectiveness and accuracy of the model. This research provides a design theory and method for the selection of oil lubrication parameters for aviation high-speed and heavy-load aviation gears.

The concentration of fine particulate matter (PM 2.5 ) across China has decreased by 30–50% over the period 2013–2018 due to stringent emission controls. However, the nitrate component of PM 2.5 has not responded effectively to decreasing emissions of nitrogen oxides and has actually increased during winter haze pollution events in the North China Plain. Here, we show that the GEOS-Chem atmospheric chemistry model successfully simulates the nitrate concentrations and trends. We find that winter mean nitrate would have increased over 2013–2018 were it not for favourable meteorology. The principal cause of this nitrate increase is weaker deposition. The fraction of total inorganic nitrate as particulate nitrate instead of gaseous nitric acid over the North China Plain in winter increased from 90% in 2013 to 98% in 2017, as emissions of nitrogen oxides and sulfur dioxide decreased while ammonia emissions remained high. This small increase in the particulate fraction greatly slows down deposition of total inorganic nitrate and hence drives the particulate nitrate increase. Our results suggest that decreasing ammonia emissions would decrease particulate nitrate by driving faster deposition of total inorganic nitrate. Decreasing nitrogen oxide emissions is less effective because it drives faster oxidation of nitrogen oxides and slower deposition of total inorganic nitrate. Reduction of ammonia emissions may be effective in reducing the nitrate component of fine particulate matter air pollution across the North China Plain, according to the simulation of nitrate trends using the GEOS-Chem atmospheric chemistry model.