The Influence of Intermediate Intensity Intermittent Cycle Training on College Students’ Fitness

Australia F45 functional training is a high-intensity intermittent cycle training method, integrating life, interest, competitiveness and cooperation together. The purpose of this study was to examine the effect of this training method on college students’ physical quality. 30 Participants from a university in southwest of China were recruited and were divided into two groups. The control group used traditional training methods while the experimental group used indirect circular training method, moderate intensity (pulse control at an average of 140-160 times / min), with the cooperation of music training. The corresponding fitness was tested before and 6 weeks after the experiment. Before and after the experiment, the scores of 50m, standing long jump, pull up / sit up, sitting forward, 800m / 1000m were tested respectively. The content of classroom training was composed of the auxiliary training contents of the five qualities: high leg lifting, small step running, frog jump, upright jump, push-up, flat support, standing forward and so on. The fitness of the students in the control group and the experimental group was improved, and the improvement of the experimental group was more obvious, especially the standing long jump, sit ups and long-distance running. It is suggested that college students accept the medium intensity intermittent cycle training method, which can improve the physical quality of college students

Research on Postgraduates’ Physical Exercise Behavior and Motivation

In China, graduate students are facing heavy pressure from study, work and life. In order to change this situation, many colleges and universities have set up PE elective courses, but the proportion of elective courses is generally low, and the health status of students has not been fundamentally improved. The purpose of this study is to investigate the current situation and motivation of Postgraduates\u27 physical exercise, and explore ways to attract more postgraduates to participate in physical exercise and promote their health. The study mainly adopts the methods of experiment and questionnaire. Two classes of students who chose PE elective courses are selected as the experimental objects. Students in Experimental class were given motivation stimulation, while another class were not. Sports stimulation includes combing family health history, inculcating the role through cases, monitoring students\u27 physique, etc. The two classes had same exercise time (once a week, 90 minutes each time), same exercise method (intermittent cycle training for 16 weeks). In addition, this study uses Professor Chen Shanping\u27s sports motivation scale to conduct a questionnaire survey on the graduate students participating in the experiment. Pearson analysis method in SPSS software was conducted to analyze the correlation between sports motivation and sports behavior. The students in the experimental class exercise better after class than those in the control class. Girls\u27 physical and social motivation of physical exercise is much higher than boys, while boys\u27 ability and motivation of physical exercise are significantly higher than boys. Different physical exercise motives have significant effects on physical exercise methods and physical exercise frequency. It is concluded that motivation stimulation is conducive to the formation of exercise behavior and there is a positive correlation between physical exercise motivation and physical exercise behavior

Votetrust: Leveraging friend invitation graph to defend against social network sybils

Online social networks (OSNs) suffer from the creation of fake accounts that introduce fake product reviews, malware and spam. Existing defenses focus on using the social graph structure to isolate fakes. However, our work shows that Sybils could befriend a large number of real users, invalidating the assumption behind social-graph-based detection. In this paper, we present VoteTrust, a scalable defense system that further leverages user-level activities. VoteTrust models the friend invitation interactions among users as a directed, signed graph, and uses two key mechanisms to detect Sybils over the graph: a voting-based Sybil detection to find Sybils that users vote to reject, and a Sybil community detection to find other colluding Sybils around identified Sybils. Through evaluating on Renren social network, we show that VoteTrust is able to prevent Sybils from generating many unsolicited friend requests. We also deploy VoteTrust in Renen, and our real experience demonstrates that VoteTrust can detect large-scale collusion among Sybils

Influence of temperature on the transmission performance of track circuit in high-speed railway

In order to explore the influence of temperature on track circuit, a mathematical simulation model of track circuit is established. Then, the influence mechanism of temperature on the key equipment of track circuit is analysed. Finally, the influence on the receiver voltage and the locomotive signal current are computed based on the simulation model

Spatio-Temporal Patterns and Impacts of Sediment Variations in Downstream of the Three Gorges Dam on the Yangtze River, China

Spanning the Yangtze River of China, the Three Gorges Dam (TGD) has received considerable concern worldwide with its potential impacts on the downstream side of the dam. This work investigated the spatio-temporal variations of suspended sediment concentration (SSC) at the downstream section of Yichang-to-Chenglingji from 2002 to 2015. A random forest model was developed to estimate SSC using MODIS ground reflectance products, and the spatio-temporal distributions of SSC were retrieved with this model to investigate the characteristics of water-silt variation. Our results revealed that, relatively, SSC before 2003 was evenly distributed in the downstream Yangtze River, while this spatial distribution pattern changed ce 2003 when the dam started storing water. Temporally, the SSC demonstrated a W-shaped curve of seasonal variation as one peak occurred in September and two troughs in March and November, and showed a significantly decreasing trend after three-stage impoundment. After official operation of the TGD in 2009, the SSC was reduced by over 40% than before 2003. Spatially, the most significant changes occurred in the upper Jingjiang section, where the SSC dropped by 45%. During all stages of impoundment, the water impoundment to 135 m in 2003 had the most significant impact on suspended sediment. The decreased SSC has led to emerging risks of bank failure, aggravated erosion of water front and aggressive down-cutting erosion along the downstream of the dam, as well as other ecological and environmental issues that require urgent attention by the government

EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Mixture-of-experts (MoE) is becoming popular due to its success in improving the model quality, especially in Transformers. By routing tokens with a sparse gate to a few experts (i.e., a small pieces of the full model), MoE can easily increase the model parameters to a very large scale while keeping the computation cost in a constant level. Most existing works just initialize some random experts, set a fixed gating strategy (e.g., Top-k), and train the model from scratch in an ad-hoc way. We identify that these MoE models are suffering from the immature experts and unstable sparse gate, which are harmful to the convergence performance. In this paper, we propose an efficient end-to-end MoE training framework called EvoMoE. EvoMoE starts from training one single expert and gradually evolves into a large and sparse MoE structure. EvoMoE mainly contains two phases: the expert-diversify phase to train the base expert for a while and spawn multiple diverse experts from it, and the gate-sparsify phase to learn an adaptive sparse gate and activate a dynamic number of experts. EvoMoE naturally decouples the joint learning of both the experts and the sparse gate and focuses on learning the basic knowledge with a single expert at the early training stage. Then it diversifies the experts and continues to train the MoE with a novel Dense-to-Sparse gate (DTS-Gate). Specifically, instead of using a permanent sparse gate, DTS-Gate begins as a dense gate that routes tokens to all experts, then gradually and adaptively becomes sparser while routes to fewer experts. Evaluations are conducted on three popular models and tasks, including RoBERTa for masked language modeling task, GPT for language modeling task and Transformer for machine translation task. The results show that EvoMoE outperforms existing baselines, including Switch, BASE Layer, Hash Layer and StableMoE

Recurrent LRP1-SNRNP25 and KCNMB4-CCND3 fusion genes promote tumor cell motility in human osteosarcoma

Background The identification of fusion genes such as SYT-SSX1/SSX2, PAX3-FOXO1, TPM3/TPM4-ALK and EWS-FLI1 in human sarcomas has provided important insight into the diagnosis and targeted therapy of sarcomas. No recurrent fusion has been reported in human osteosarcoma. Methods Transcriptome sequencing was used to characterize the gene fusions and mutations in 11 human osteosarcomas. Results Nine of 11 samples were found to harbor genetic inactivating alterations in the TP53 pathway. Two recurrent fusion genes associated with the 12q locus, LRP1-SNRNP25 and KCNMB4-CCND3, were identified and validated by RT-PCR, Sanger sequencing and fluorescence in situ hybridization, and were found to be osteosarcoma specific in a validation cohort of 240 other sarcomas. Expression of LRP1-SNRNP25 fusion gene promoted SAOS-2 osteosarcoma cell migration and invasion. Expression of KCNMB4-CCND3 fusion gene promoted SAOS-2 cell migration. Conclusions Our study represents the first whole transcriptome analysis of untreated human osteosarcoma. Our discovery of two osteosarcoma specific fusion genes associated with osteosarcoma cellular motility highlights the heterogeneity of osteosarcoma and provides opportunities for new treatment modalities.BioMed Central open acces