KINEMATIC ANALYSIS OF ELITE MALE TENNIS PLAYER'S STEP MOVEMENT FOR RETURN OF SERVICE

A three-dimensional camera analytic method was used to make kinematic analysis on three players' step movement for return of service in finals and semi-finals of the ATP Champions Tour. The movements were broke down to three stages (preparation stage, skip step stage, stroke stage) for analyzing the kinetic parameters. Then the kinematic characteristics of elite tennis player’s step movement for return of service were derived, to serve as reference for skill training and tennis matches. It was found that: in the preparation stage, Sampres, Aynaoui and Moya have an average horizontal angle between the feet of 12.1deg., 2.2deg., 45.6deg.respectively. In the stroke stage, the travel distances of Sampras and Moya were found to be greatly differed (0.892m and 0.667m respectively), and move faster (2.23m/s and 1.96m/s respectively)

COMPARATIVE KINEMATIC ANALYSIS OF ENQVIST AND MOYA’S TENNIS SERVE TECHNOLOGY

Serving occupies a more important role in the modern tennis. The tennis serve of two players, Thomas Enqvist and Carles Moya, were filmed in the semifinals of Chengdu Open-ATP Champions Tour and analysed with three-dimensional video analysis. The serve was divided into three stages as follows: throwing ball rising racket stage, backward swing stage, forward swing hitting stage. It is found that: in the first stage, the maximum value of shoulder-hip level projection angle of Enqvist and Moya are 18.5° and 28.7° respectively. In the second stage, Enqvist and Moya’s extension range of left knee joint were 55.1° and 34.6°.Their e angular velocity were 182.6°/s and 170.4°/s. In the third stage, Enqvist and Moya’s hitting height were 2.23m and 2.15m, Hitting height and body height ratio were 1.18 and 1.13, there are significant differences

Analysis of Multi-Element Blended Course Teaching and Learning Mode Based on Student-Centered Concept under the Perspective of “Internet+”

The integration of Internet and education has changed students’ learning environment and affected their learning behavior, which poses a greater challenge to the traditional teaching mode. Through the SWOT analysis of the “student centered” multi-element blended teaching mode in the era of “Internet + education”, it is concluded that the adaptability of learners themselves and the mismatch between teachers’ educational ideas and this teaching model delay the development of education to a certain extent. Some suggestions are put forward, such as strengthening the supervision and guidance, implementing the teaching and learning model scientifically, improving teachers’ ideology and comprehensive quality, and making full use of the characteristics of Internet opening, sharing and collaboration to construct the public service system and platform of national educational resources

A336C/A336T/T337C variations in HBV core gene and spontaneous hepatitis B e antigen loss in chronic hepatitis B patients

<p>Abstract</p> <p>Background</p> <p>A336C/A336T/T337C variations in HBV core gene were demonstrated to relate to the decreases in serum HBV DNA levels and HBV replication in chronic hepatitis B patients. Usually the drastic decrease in serum HBV DNA levels correlates with spontaneous HBeAg loss during the course of chronic HBV infection. The aim of the present study was to investigate whether there was correlation between A336C/A336T/T337C variations and spontaneous HBeAg loss</p> <p>Methodology/Principal Findings</p> <p>A modified PCR-RFLP assay and ELISA were adopted to determine A336C/A336T/T337C variations and serum HBeAg levels in chronic hepatitis B patients without any antiviral therapy, respectively, whereas G1896A variation and HBV genotype were detected using Taqman-PCR assay. RFLP pattern C, E, G, C/G mixture and a new pattern C' were found in this study. A336C/A336T/T337C variations occurred in 40/166(24.1%) chronic hepatitis B patients. Chi-square test showed that C336/T336/C337 variants was more frequent in chronic hepatitis B patients with A1896 variants than those with the wild type G1896 (χ2 = 4.7, P = 0.03), and moreover, patients with C336/T336/C337 variants had a significantly lower HBeAg-positive percentage than those with the wild type A336/T337. Binary logistic regression identified genotype B (OR = 4.1, 95%CI = 1.8-9.2, P = 0.001), the presence of C336/T336/C337 variants (OR = 3.2, 95%CI = 1.2-8.5, P = 0.02) and A1896 variants (OR = 7.8, 95%CI = 3.3-18.5, P < 0.001) as independent factors associated with spontaneous HBeAg loss.</p> <p>Conclusion/Significance</p> <p>A336C/A336T/T337C were naturally occurring polymorphisms in HBV core gene, and moreover, the presence of C336/T336/C337 variants was first demonstrated to be an independent factor associating with spontaneous HBeAg loss in chronic hepatitis B patients.</p

Data Files: Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

This data supports the research project Bi-objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity and a final report published on NITC’s website. Dataset collected through multiple sources and organized into different formats including CSV format, JSON format, shapefile and code repository. Context: The research project develops a bi-objective model that aims to help transit agencies to optimally deploy BEB while considering both capital investment and environmental equity. The unique spatio-temporal characteristic of BEB system, charging limitations (on-route and in-depot charging), and operational constraints are also considered and incorporated into the model

Enantioselective Organocatalytic Four-Atom Ring Expansion of Cyclobutanones: Synthesis of Benzazocinones

International audienceAn enantioselective Michael addition-four-atom ring expansion cascade reaction involving cyclobutanones activated by a N-aryl secondary amide group and ortho-amino nitrostyrenes has been developed for the preparation of functionalized eight-membered benzolactams using bifunc-tional aminocatalysts. Taking advantage of the secondary amide activating group, the eight-membered cyclic products could be further rearranged into their six-membered isomers having a glutarimide core under base catalysis conditions without erosion of optical purity, featuring an overall ring expansion-ring contraction strategy

Enabling Decision-Making in Battery Electric Bus Deployment through Interactive Visualization

The transit industry is rapidly transitioning to battery-electric fleets because of the direct environmental and financial benefits they could offer, such as zero emissions, less noise, and lower maintenance costs. Yet the unique spatiotemporal characteristics associated with transit system charging requirements, as well as various objectives when prioritizing the fleet electrification, requires the system operators and/or decision-makers to fully understand the status of the transit system and energy/power system in order to make informed deployment decisions. A recently completed NITC project, No. 1222 titled An Electric Bus Deployment Framework for Improved Air Quality and Transit Operational Efficiency, developed a bi-objective spatiotemporal optimization model for the strategic deployment of the Battery Electric Bus (BEB) to minimize the cost of purchasing BEBs, on-route and in-depot charging stations, and to maximize environmental equity for disadvantaged populations. As agencies such as the Utah Transit Authority (UTA) adopt the model and results, they desire to have a tool that could enable detailed spatiotemporal monitoring of components for the BEB system (e.g., locations of BEBs, the state-of-charge of batteries, charging station energy consumption at each specific timestamp), so that the integration of BEBs into the power/grid system as well as its operating condition could be better understood. To this end, this Translate Research to Practice grant will support the development of a visualization tool that allows transit operators/planners as well as decision-makers to explore the interdependency of the BEB transit system and energy infrastructure in both spatial and temporal dimensions with high resolution. The tool will be built on the scenario-based optimization modeling effort in NITC Project No. 1222, and allow agencies to make phase-wise (short-, mid-, or long-term) decisions based on investment resources and strategic goals. This project will also develop a guidebook to provide step-by-step guidance on data compilation for BEB analysis, model input, model implementation, and results interpretation. It will further detail how the developed visualization tool is structured and designed to ensure results exploration across transit operation and energy consumption. Both the guidebook and the tool will be directly useful to practitioners to easily implement our optimization model for their own transit network, and allow them to build interactive visualizations to assist with decision-making

Cloud-Magnetic Resonance Imaging System: In the Era of 6G and Artificial Intelligence

Magnetic Resonance Imaging (MRI) plays an important role in medical diagnosis, generating petabytes of image data annually in large hospitals. This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure. Additionally, local data processing demands substantial manpower and hardware investments. Data isolation across different healthcare institutions hinders cross-institutional collaboration in clinics and research. In this work, we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing, 6G bandwidth, edge computing, federated learning, and blockchain technology. This system is called Cloud-MRI, aiming at solving the problems of MRI data storage security, transmission speed, AI algorithm maintenance, hardware upgrading, and collaborative work. The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data (ISMRMRD) format. Then, the data are uploaded to the cloud or edge nodes for fast image reconstruction, neural network training, and automatic analysis. Then, the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services. The Cloud-MRI system will save the raw imaging data, reduce the risk of data loss, facilitate inter-institutional medical collaboration, and finally improve diagnostic accuracy and work efficiency.Comment: 4pages, 5figures, letter

SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation

High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. Firstly, these algorithms tend to focus on local information, neglecting non-local information between different pixel patches. Secondly, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Thirdly, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a Superpixel High-Resolution SAR Imaging Network (SPHR-SAR-Net) for rapid despeckling in high-resolution SAR mode. Based on the concept of superpixel techniques, we initially combine non-convex and non-local total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the Alternating Direction Method of Multipliers (ADMM) algorithm and unfold it into a Deep Unfolded Network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the Deep Unfolded Network is compatible with high-resolution imaging modes such as spotlight, staring spotlight, and sliding spotlight. In this paper, we demonstrate the superiority of SPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that SPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results