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6,348 results on '"Deng, Chao"'

155. The Effect of Controlled Drainage and Nitrogen Fertilization on Growth, Nitrogen Uptake and Yield of Cotton

Author

WU Qian, WU Qixia, DENG Chao, LIU Kaiwen, QI Dongliang, and ZHU Jianqiang

Subjects
controlled drainage, nitrogen application, cotton yield, dry matter, water and nitrogen coupling, Agriculture (General), S1-972, Irrigation engineering. Reclamation of wasteland. Drainage, TC801-978
Abstract

【Objective】 Soil nitrogen and groundwater table are two abiotic factors affecting crop growth in the middle and low reaches of the Yangtze River in Southern China. This paper aims to investigate the combined impact of nitrogen fertilization and controlled drainage on growth, nitrogen uptake and yield of cotton. 【Method】 The variety Jinghua Mian 112 was used as the model plant, and the experiment consisted of two drainage treatments: conventional drainage (FKS) and controlled drainage (KS). Each irrigation had five nitrogen treatments: applying 0 (N0), 90 (N1), 180 (N2), 270 (N3) and 360 kg/hm2 (N4) of nitrogen. In each treatment, we measured the leaf SPAD at fertility stage, plant height and leaves at blooming stage, dry matter accumulation in different organs at maturity stage, as well as nitrogen uptake, and yield of the cotton. 【Result】 Compared with FKS, controlled drainage combined with a reduction in nitrogen application significantly increased leaf SPAD and plant height at flowering stage, dry matter accumulation and nitrogen uptake at maturity stage, boll numbers per plant, boll weight per boll and yield at maturity stage. Reducing nitrogen application without implementing controlled drainage reduced cotton yield, while under controlled drainage, reducing nitrogen application from N4 to N3 did not give rise to a noticeable reduction in cotton yield. KS+N3 increased the dry matter mass, nitrogen uptake per unit dry matter, and total nitrogen uptake in the bud and boll, significantly. 【Conclusion】 Reducing nitrogen application currently used by farmers by 25% combined with a controlled drainage is not only beneficial to cotton growth and promotes dry matter accumulation, but also increases nitrogen uptake and its subsequent allocation to reproductive organs, thereby increasing cotton yield.

Published
2023
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156. Efficacy and safety of glue mesh fixation for laparoscopic inguinal hernia: A meta-analysis of randomized controlled trials

Author

Nan Hu, Hong Xie, Deng-Chao Wang, Yue-Hua Lei, Jian Wei, Miao Yu, and Yue-Juan Li

Subjects
Glue, Inguinal hernia, Laparoscopic, Mesh fixation, Meta-analysis, Surgery, RD1-811
Abstract

It is still controversial whether glue can be used for mesh fixation in laparoscopic inguinal hernia repair. The aim of this meta-analysis was used to systematically evaluate the effectiveness and safety of glue mesh fixation in laparoscopic tension-free inguinal hernia repair. The PubMed database, EMBASE database and Cochrane Library were searched to collect published randomized controlled trials (RCTs) on laparoscopic tension-free inguinal hernia repair with glue mesh fixation. Sixteen RCTs and 2409 patients with inguinal hernia were included. The meta-analysis showed that compared with the mechanical mesh fixation group(MMFG), the glue mesh fixation group(GMFG) had significantly reduced incidences of chronic pain[relative risk (RR) = 0.40, 95% confidence interval (CI) (0.28,0.57), P

Published
2023
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158. Relative wealth concerns with partial information and heterogeneous priors

Author

Deng, Chao, Su, Xizhi, and Zhou, Chao

Subjects
Quantitative Finance - Portfolio Management
Abstract

We establish a Nash equilibrium in a market with $ N $ agents with the performance criteria of relative wealth level when the market return is unobservable. Each investor has a random prior belief on the return rate of the risky asset. The investors can be heterogeneous in both the mean and variance of the prior. By a separation result and a martingale argument, we show that the optimal investment strategy under a stochastic return rate model can be characterized by a fully-coupled linear FBSDE. Two sets of deep neural networks are used for the numerical computation to first find each investor's estimate of the mean return rate and then solve the FBSDEs. We establish the existence and uniqueness result for the class of FBSDEs with stochastic coefficients and solve the utility game under partial information using deep neural network function approximators. We demonstrate the efficiency and accuracy by a base-case comparison with the solution from the finite difference scheme in the linear case and apply the algorithm to the general case of nonlinear hidden variable process. Simulations of investment strategies show a herd effect that investors trade more aggressively under relativeness concerns. Statistical properties of the investment strategies and the portfolio performance, including the Sharpe ratios and the Variance Risk ratios (VRRs) are examed. We observe that the agent with the most accurate prior estimate is likely to lead the herd, and the effect of competition on heterogeneous agents varies more with market characteristics compared to the homogeneous case.

Published
2020

159. Hardware Impairments Aware Full-Duplex NOMA Networks Over Rician Fading Channels

Author

Deng, Chao, Liu, Meng, Li, Xingwang, and Liu, Yuanwei

Subjects
Computer Science - Information Theory
Abstract

A cooperative full duplex (FD) non-orthogonal multiple access (NOMA) scheme over Rician fading channels is considered. To be practical, imperfect successive interference cancellation (ipSIC) and residual hardware impairments (RHIs) at transceivers are taken into account. To evaluate the performance of the considered system, the analytical approximate expressions for the outage probability (OP) and the ergodic rate (ER) of the considered system are derived, and the asymptotic performance is also explored. Simulation results manifest that the FD cooperative NOMA can improve the ergodic sum rate (ESR) of the system compared to the half duplex (HD) mode.

Published
2020
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160. Smart Prediction of the Complaint Hotspot Problem in Mobile Network

Author

Zhu, Lin, Zhao, Juan, Wang, Yiting, Feng, Juanlan, Deng, Chao, Huang, Zhenning, and Li, Hui

Subjects
Computer Science - Networking and Internet Architecture
Abstract

In mobile network, a complaint hotspot problem often affects even thousands of users' service and leads to significant economic losses and bulk complaints. In this paper, we propose an approach to predict a customer complaint based on real-time user signalling data. Through analyzing the network and user sevice procedure, 30 key data fields related to user experience have been extracted in XDR data collected from the S1 interface. Furthermore, we augment these basic features with derived features for user experience evaluation, such as one-hot features, statistical features and differential features. Considering the problems of unbalanced data, we use LightGBM as our prediction model. LightGBM has strong generalization ability and was designed to handle unbalanced data. Experiments we conducted prove the effectiveness and efficiency of this proposal. This approach has been deployed for daily routine to locate the hot complaint problem scope as well as to report affected users and area.

Published
2020

171. Genome-wide association analyses identified novel susceptibility loci for pulmonary embolism among Han Chinese population

Author

Zhang, Zhu, Li, Haobo, Weng, Haoyi, Zhou, Geyu, Chen, Hong, Yang, Guoru, Zhang, Ping, Zhang, Xiangyan, Ji, Yingqun, Ying, Kejing, Liu, Bo, Xu, Qixia, Tang, Yongjun, Zhu, Guangfa, Liu, Zhihong, Xia, Shuyue, Yang, Xiaohong, Dong, Lixia, Zhu, Ling, Zeng, Mian, Yuan, Yadong, Yang, Yuanhua, Zhang, Nuofu, Xu, Xiaomao, Pang, Wenyi, Zhang, Meng, Zhang, Yu, Zhen, Kaiyuan, Wang, Dingyi, Lei, Jieping, Wu, Sinan, Shu, Shi, Zhang, Yunxia, Zhang, Shuai, Gao, Qian, Huang, Qiang, Deng, Chao, Fu, Xi, Chen, Gang, Duan, Wenxin, Wan, Jun, Xie, Wanmu, Zhang, Peng, Wang, Shengfeng, Yang, Peiran, Zuo, Xianbo, Zhai, Zhenguo, and Wang, Chen

Published
2023
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177. Your Favorite Gameplay Speaks Volumes About You: Predicting User Behavior and Hexad Type

Author

Hadi Mogavi, Reza, Deng, Chao, Hoffman, Jennifer, Haq, Ehsan-Ul, Gujar, Sujit, Bucchiarone, Antonio, Hui, Pan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Fang, Xiaowen, editor

Published
2023
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