BIOMECHANICAL ANALYSIS OF RIGHT SIDEDSTRIDE IN JAVELIN DELIVERY

The purpose of this study was to analyze the technique of javelin delivery using a rightsided stride. This study provided important data for more accurate analysis of the technique of javelin throwing with the right-sided delivery stride. The performance of 10 Chinese elite javelin throwers were filmed and then, some relevant parameters were analyzed. Based on these measurements, it was found that the right foot turns outward when contacting the ground, while the right knee is slightly flexed in the delivery stride. However the strength of the right leg depends on extension of right hip rather than that of right knee

How do emerging multinationals configure political connections across institutional contexts?

Forming informal ties with political agents is viewed as a viable strategy for multinational enterprises seeking to enter emerging countries. Less is known about the conditions under which political connection is most helpful for firms dealing with cross-border institutional distance. We discuss the distinctive mechanisms through which emerging multinationals may benefit from both home and host political connections. Based on the strategy tripod perspective, we postulate that the importance of different types of connections depends on the overall configurations of a firm’s resources and industry characteristics, and these may change with institutional distance. Our analysis of a sample of Chinese high-tech manufacturing firms yields new insights into political connections, institutional distance and the strategy tripod perspective

A Classification Method of Point Clouds of Transmission Line Corridor Based on Improved Random Forest and Multi-Scale Features

Classification of airborne laser scanning (ALS) point clouds of power lines is of great importance to their reconstruction. However, it is still a difficult task to efficiently and accurately classify the ground, vegetation, power lines and power pylons from ALS point clouds. Therefore, in this paper, a method is proposed to improve the accuracy and efficiency of the classification of point clouds of transmission lines, which is based on improved Random Forest and multi-scale features. The point clouds are filtered by the optimized progressive TIN densification filtering algorithm, then the elevations of the filtered point cloud are normalized. The features of the point cloud at different scales are calculated according to the basic features of the point cloud and the characteristics of transmission lines. The Relief F and Sequential Backward Selection algorithm are used to select the best subset of features to estimate the parameters of the learning model, then an Improved Random Forest classification model is built to classify the point clouds. The proposed method is verified by using three different samples from the study area and the results show that, compared with the methods based on Support Vector Machines, AdaBoost or Random Forest, our method can reduce feature redundancy and has higher classification accuracy and efficiency

A Classification Method of Point Clouds of Transmission Line Corridor Based on Improved Random Forest and Multi-Scale Features

Classification of airborne laser scanning (ALS) point clouds of power lines is of great importance to their reconstruction. However, it is still a difficult task to efficiently and accurately classify the ground, vegetation, power lines and power pylons from ALS point clouds. Therefore, in this paper, a method is proposed to improve the accuracy and efficiency of the classification of point clouds of transmission lines, which is based on improved Random Forest and multi-scale features. The point clouds are filtered by the optimized progressive TIN densification filtering algorithm, then the elevations of the filtered point cloud are normalized. The features of the point cloud at different scales are calculated according to the basic features of the point cloud and the characteristics of transmission lines. The Relief F and Sequential Backward Selection algorithm are used to select the best subset of features to estimate the parameters of the learning model, then an Improved Random Forest classification model is built to classify the point clouds. The proposed method is verified by using three different samples from the study area and the results show that, compared with the methods based on Support Vector Machines, AdaBoost or Random Forest, our method can reduce feature redundancy and has higher classification accuracy and efficiency

Prevalence of Pneumoconiosis in Hubei, China from 2008 to 2013

We have investigated newly reported pneumoconiosis cases in the province of Hubei, China from 2008 to 2013, to identify the major problems and challenges, and explore possible solutions for its prevention and control. We analyzed the data on new cases of pneumoconiosis from annual reports, including case distributions, patient ages, exposure duration, disease stages, and enterprise types. A total of 3665 new pneumoconiosis cases were reported between 2008 and 2013 in Hubei Province. Coal workers’ pneumoconiosis and silicosis, which accounted for 97.19% of the total, were the most common types. The duration of exposure of 33.32% cases was less than 10 years. Most of the new pneumoconiosis cases worked in industries that produced coal, nonferrous metal, or building materials. About 42.46% of pneumoconiosis cases were from small and medium-sized enterprises. The proportion of cases with combined pneumoconiosis and tuberculosis was 6.6%, and the incidence of tuberculosis was highest in workers with silicosis. The current situation of pneumoconiosis in China is serious. Lack of attention to occupational health, inefficient surveillance, and weak occupational health services may have contributed to the increased new pneumoconiosis cases

Interprovincial Joint Prevention and Control of Open Straw Burning in Northeast China: Implications for Atmospheric Environment Management

Large-scale open burning of straw residues causes seasonal and severe atmospheric pollution in Northeast China. Previous studies focused on the causes or assessment of atmospheric pollution in a single city. However, studies conducted on the interaction range, degree and policy control of pollutant transport on a large scale are still to be performed. In this study, we propose combined control of straw burning by dividing region the straw burning in Northeast China in recent 20 years, determining the transport routes between main cities, and analyzing the interaction characteristics of straw burning under different scenarios. The fire point data suggest that the most intense straw burning years in Northeast China in the past 20 years occurred in the range from 2014 to 2017, mainly after the autumn harvest (October–November) and before spring cultivation (March–April). The burning areas were concentrated in the belt of Shenyang-Changchun-Harbin, the border of the three provinces and Eastern-Inner Mongolia, and the surrounding area of Hegang and Jiamusi City. The lower number of fire points before 2013 indicates that high-intensity burning has not always been the case, while the sharp decline after 2018 is mainly due to scientific control of straw burning and increased comprehensive utilization of straw. Compared with S2, the PM2.5 concentrations increased by 6.2% in S3 and 18.7% in S4, indicating that burning in three or four provinces at the same time will significantly increase air pollution and exert a regional transmission effect. Straw burning in Northeast China is divided into six main regions based on correlation analysis and satellite fire monitoring. Under typical S3, the case analysis results indicate that there is regional transmission interaction between different cities and provinces, focusing on multi-province border cities, and it is affected by Northwest long airflow, and Southeast and Northeast short airflow. These results provide scientific and technological support for implementing the joint prevention and control plan for straw incineration in Northeast China

Emotional literacy and mental health in the early years

Includes bibliographical referencesSIGLEAvailable from British Library Document Supply Centre- DSC:m03/21842 / BLDSC - British Library Document Supply CentreGBUnited Kingdo