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"National Strength "
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Prediction of Macroscopic Compressive Mechanical Properties for 2.5D Woven Composites Based on Artificial Neural Network
The complex modeling and computational cost are unavoidable in analysis of finite element models (FEMs) when mechanical properties of woven composite materials are predicted. To overcome the drawbacks of FEMs, two different artificial neural network models (ANNMs) based on quasi-static axial compression experimental data of 2.5D woven composite plates (2.5DWCPs) are constructed: (1) The direct strength prediction model (DSPM) is a non-destructive way to predict strength, which is meaningful in engineering; (2) The indirect strength prediction model (ISPM) is based on stress–strain curves, which firstly proposes a simplified data processing method including the state variables (SVs). The SVs are introduced to modify the experimental stress–strain curves, which not only reduces training data size but also significantly improves prediction accuracy. Then, the performance of the DSPM and the ISPM has been evaluated by numerical examples. The results indicate that the DSPM has simple and direct expressions of input parameters (IPs) and output parameters (OPs), which makes it easier to construct and train ANNMs. The ISPM not only utilizes sufficient training data from experiments but also performs well in predicting stress–strain curve and failure strain. In short, two proposed ANNMs have ability to fast and accurately predict compression strength, which are more suitable for engineering than FEMs. To reduce experimental costs, the DSPM is proposed to produce reasonable results. If a lot of experimental data are prepared, the ISPM can produce more accurate results.
Journal Article
Characterization of the natural enemy community attacking cotton aphid in the bt cotton ecosystem in northern china
Planting Bt cotton in China since 1997 has led to important changes in the natural enemy communities occurring in cotton, however their specific effect on suppressing the cotton aphids (being notorious in conventional cotton ecosystem) has not been fully documented yet. We observed strong evidence for top-down control of the aphid population, e.g. the control efficiency of natural enemies on cotton aphid increased significantly in open field cages compared to exclusion cages, accounted for 60.2, 87.2 and 76.7% in 2011, 2012 and 2013 season, respectively. The cotton aphid populations peaked in early June to late July (early and middle growth stages) in open field cotton survey from 2011 to 2013. The population densities of cotton aphids and natural enemies were highest on middle growth stage while lowest densities were recorded on late stage for aphids and on early plant stage for natural enemies. Aphid parasitoids (Trioxys spp., Aphidius gifuensis), coccinellids and spiders were key natural enemies of cotton aphid. Briefly, natural enemies can suppress aphid population increase from early to middle plant growth stages by providing biocontrol services in Chinese Bt cotton.
Journal Article
Developing endurance
\"This book from the NSCA's Sport Performance Series is a resource for endurance coaches, athletes, strength and conditioning specialists, and other sport-related specialists to learn fundamental physiological principles of endurance, assessment and training techniques that target muscular endurance while also promoting overall physical fitness, as well as how to properly design individualized endurance training programs in order to minimize the risk of injury while maximizing competitive performance and enjoyment of their sport\"-- Provided by publisher.
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