The patterns and prevention of injuries in college table tennis training

This paper conducts a detailed investigation and analysis of injuries among table tennis athletes from college sports academies, and preliminarily explores some general patterns of sports-related injuries that have occurred, summarizing some preventive measures and solutions

Research on power allocation of integrated VLPC based on deep reinforcement learning

A power allocation scheme for integrated visible light position and communication (VLPC) system based on deep reinforcement learning was proposed to achieve power allocation for communication positioning integration.First, the frame structure design of integrated VLPC was proposed.Then the channel state information could be estimated by using the positioning information, and the CRLB of the positioning error was derived.Furthermore, the internal coupling relationship between positioning accuracy and communication rate was clarified.On this basis, a dynamic power allocation scheme based on deep deterministic policy gradient was proposed.Simulation results show that the proposed scheme can simultaneously achieve high-precision positioning and high-speed communication

Comparison of detection methods and follow-up study on the tyrosine kinase inhibitors therapy in non-small cell lung cancer patients with ROS1 fusion rearrangement

BACKGROUND: The screening of ROS proto-oncogene 1, receptor tyrosine kinase(ROS1) fusion rearrangement might be potentially beneficial for an effective therapy against non-small cell lung cancer (NSCLC). However, the three main ROS1 rearrangement detection methods have limitations, and no routine protocol for the detection of ROS1 rearrangement in NSCLC is available. In this study, our aims were to compare immunohistochemistry (IHC), fluorescent in situ hybridization (FISH) and quantitative real-time polymerase chain reaction (qRT-PCR) in their ability to detect ROS1 rearrangement in NSCLC, and discuss the clinical characteristics and histopathology of the patients with ROS1 rearrangement. Moreover, the effects of tyrosine kinase inhibitors (TKIs) therapy on the patients with ROS1 rearrangement and advanced stage disease (III b–IV) were investigated. METHODS: Patients with a previously diagnosed NSCLC were recruited in this study from November 2013 to October 2015. IHC was performed using the D4D6 monoclonal antibody (mAb) in an automatic IHC instrument, while FISH and qRT-PCR were carried out to confirm the IHC results. FISH and qRT-PCR positive cases underwent direct sequencing. After detection, patients with advanced ROS1 rearranged NSCLC had received TKI therapy. RESULTS: Two hundred and thirty-eight patients were included in this study. ROS1 rearrangement was detected in 10 patients. The concordant rate of FISH and qRT-PCR results was 100 %, while in the FISH and IHC results high congruence was present when IHC showed a diffusely (≥60 % tumor cells) 2–3+ cytoplasmic reactivity pattern. Patients harboring ROS1 rearrangement were mostly young (8/10), females (7/10) and non-smokers (7/10) with adenocarcinoma (10/10) and acinar pattern. Most of their tumor were in intermediate grade (6/8). Among these 10 patients, three of them in stage IV with ROS1 rearrangement gained benefits from ROS1 TKI therapy. CONCLUSIONS: IHC, FISH and qRT-PCR can reliably detect ROS1 rearrangement in NSCLC, while IHC can be used as a preliminary screening tool. These results supported the efficacy of ROS1 TKI therapy in treating advanced NSCLC patients with ROS1 rearrangement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-016-2582-9) contains supplementary material, which is available to authorized users

Progress in the Remote Sensing Monitoring of the Ecological Environment in Mining Areas

Based on the results of an extensive literature research, we summarize the research progress of remote sensing monitoring in terms of identifying mining area boundaries and monitoring land use or land cover changes of mining areas. We also analyze the application of remote sensing in monitoring the biodiversity, landscape structure, vegetation change, soil environment, surface runoff conditions, and the atmospheric environment in mining areas and predict the prospects of remote sensing in monitoring the ecological environment in mining areas. Based on the results, the accurate classification of land use or land cover and the accurate extraction of environmental factors are the basis for remote sensing monitoring of the ecological environment in mining areas. In terms of the extraction of ecological factors, vegetation extraction is relatively advanced in contrast to the extraction of animal and microbial data. For the monitoring of environmental conditions of mining areas, sophisticated methods are available to identify pollution levels of vegetation and to accurately monitor soil quality. However, the methods for water and air pollution monitoring in mining areas still need to be improved. These limitations considerably impede the application of remote sensing monitoring in mining areas. The solving of these problems depends on the progress of multi-source remote sensing data and stereoscopic monitoring techniques.</jats:p