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924 results on '"Liu, Hai-Yan"'

4. Estimation for recurrent events through conditional estimating equations

Author

Schiopu-Kratina, Ioana, Liu, Hai Yan, Alvo, Mayer, and Bergeron, Pierre-Jerome

Subjects
Statistics - Applications
Abstract

We present new estimators for the statistical analysis of the dependence of the mean gap time length between consecutive recurrent events, on a set of explanatory random variables and in the presence of right censoring. The dependence is expressed through regression-like and overdispersion parameters, estimated via conditional estimating equations. The mean and variance of the length of each gap time, conditioned on the observed history of prior events and other covariates, are known functions of parameters and covariates. Under certain conditions on censoring, we construct normalized estimating functions that are asymptotically unbiased and contain only observed data. We discuss the existence, consistency and asymptotic normality of a sequence of estimators of the parameters, which are roots of these estimating equations. Simulations suggest that our estimators could be used successfully with a relatively small sample size in a study of short duration.

Published
2021

22. A phase Ib/II study of pacritinib, an interleukin 1 receptor associated kinase 1 (IRAK1) inhibitor, in patients (pts) with solid tumors harboring the 1q21.3 copy number amplification (CNA).

Author

Lim, Joline Si Jing, Aau, Mei Yee, Yeong, Joe, Goh, Boon Cher, Yong, Wei Peng, Soo, Ross A., Wong, Andrea, Tan, David Shao Peng, Chee, Cheng Ean, Sundar, Raghav, Jeyasekharan, Anand Devaprasath, Wong, Calista, Chen, Polly Leilei, Liu, Hai Yan, Yu, Qiang, Tam, Wai Leong, and Lee, Soo-Chin

Published
2024
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29. Image Quality Predictor with Highly Efficient Fully Convolutional Neural Network

Author

Cao Yu-Dong, Liao Xin-Lin, and Liu Hai-Yan

Subjects
Electronic computers. Computer science, QA75.5-76.95
Abstract

A highly efficient deep fully convolutional neural network (DFCN) for image quality assessment (IQA) is designed in this paper. The DFCN consists of two branches, one scoring local patches and the other estimating the weights of local patches to enhance quality prediction. Then, the DFCN outputs quality score of the whole image with aggregate weighted average pooling. There are no fully connected layers in the DFCN, resulting in far fewer parameters. In addition, the network model utilizes multiscale images as inputs to enrich the extracted distortion information. Furthermore, the parameters of the model are optimized in two steps to reduce the requirement for computing power and the risk of overfitting. The parameters of the shared layers and the quality module are optimized firstly, and then, the parameters of the weight module are optimized with the designed loss function. The extensive experimental results show that the proposed DFCN outperforms other competing IQA methods and has strong generalization ability.

Published
2022
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39. Effect of corn straw leaves and pith on growth performance, nutrient apparent digestibility, serum biochemical indexes, and immune indexes of mutton sheep.

Author

LIU Hai-yan, LI Xue-long, WANG Yan-jing, WANG Xiu-fei, ZHANG Di, ZHAO Sheng-nan, and YANG Rui-hong

Subjects
*CORN as feed, *CORN straw, *FEED analysis, *SHEEP, *COMPLEMENT (Immunology), *IMMUNOGLOBULIN M, LEAF growth
Abstract

The experiment was conducted to study the effect of corn stalk leaves and pith on the growth performance, nutrient apparent digestibility, and serum biochemical indexes of mutton sheep. Thirty healthy ewes weighing (30.0 ± 3.0) kg were randomly divided into two groups according to the principle of similar body weight, with three replicates in each group and five ewes in each replicate. The sheep in the control group were fed a corn straw as the roughage, the sheep in the experimental group were fed corn stalk leaves and pith as the roughage, and the sheep in the experimental group and the control group were fed the same concentrate. The pre-trial period was 10 days and the formal trial period was 90 days. The results showed that compared with the control group, the average daily gain of the experimental group increased by 10.58%, the average daily dry matter intake increased by 1.01%, and the feed to gain ratio decreased by 8.66%. The apparent digestibility rates of dry matter, crude protein, crude fat, neutral detergent fiber, acid detergent fiber, calcium, and phosphorus in the experimental group were 6.52%, 8.69%, 9.43%, 8.17%, 8.43%, 5.87%, and 6.51% higher than those in the control group, respectively. Compared with the control group, the total protein content, globulin content, and alkaline phosphatase activity in the serum of sheep in the experimental group increased by 3.41%, 10.70%, and 12.42%, respectively, and the urea nitrogen content decreased by 5.00%. The concentrations of serum immunoglobulin A, immunoglobulin M, immunoglobulin G, complement C3, and complement C4 in the experimental group were 5.89%, 7.90%, 7.58%, 6.95%, and 2.66% higher than those in the control group, respectively. The experiment o indicates that compared with the whole corn stalk, corn stalk leaves and pith are a kind or high quality roughage herbivorous livestock. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Systematic Study on QCD Interactions of Heavy Mesons with $\rho$ Meson

Author

Li, Zuo-Hong, Liu, Wei, and Liu, Hai-Yan

Subjects
High Energy Physics - Phenomenology
Abstract

The strong interactions of the negative-parity heavy mesons with $\rho$ meson may be described consistently in the context of an effective lagrangian, which is invariant under isospin SU(2) transformation. Four coupling constants $g_{HH\rho}$, $f_{H^*H\rho}$, $g_{H^*H^*\rho}$ and $f_{H^*H^*\rho}$ enter the effective lagrangian, where $H$ $(H^*)$ denotes a pseudoscalar bottom or charm meson (the corresponding vector meson). Using QCD light cone sum rule (LCSR) method and, as inputs, the hadronic parameters updated recently, we give an estimate of $g_{H^*H^*\rho}$ and $f_{H^*H^*\rho}$, about which little was known before, and present an improved result for $g_{HH\rho}$ and $f_{H^*H\rho}$. Also, we examine the heavy quark asymptotic behavior of these nonperturbative quantities and assess the two low energy parameters $\beta$ and $\lambda$ of the corresponding effective chiral lagrangian., Comment: 16 pages, 1 eps figure, version to appear in PLB

Published
2007
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46. A method for synthesizing copper nanoclusters based on protein–polyacrylamide gel and its application

Author

Liu, Hai-Yan, Andoh, Vivian, Cao, Zheng, Tao, Cheng, Fan, Jun-Min, Lv, Xing-Ping, and Ma, Lin

Abstract

Copper nanoclusters (NCs) are increasingly favored by many researchers in the field of biochemistry. In this study, we have provided a method for the preparation of copper NCs based on a protein “turn-on” method, i.e. by immobilizing low-emissive copper nanoparticles (NPs) and proteins [human serum albumin (HSA), catalase, and lysozyme] together in polyacrylamide gel, high-fluorescent copper NCs can be achieved easily. The fluorescent color of HSA-mediated copper NCs is blue purple, the one of catalase-mediated copper NCs is pink yellow, and that of lysozyme-mediated copper NCs is orange red. The results show that the pore size of polyacrylamide gel, the ratio of protein to copper NPs and the modifiers of copper NPs have crucial effects on the yield of copper NCs. This method can also be used for the detection of the corresponding proteins, i.e. HSA, catalase, and lysozyme, based on the fluorescence of their respective copper NCs. The detection limits for the three proteins are all 0.02 mg mL−1, with a linear dynamic range from 0.02 to 2.00 mg mL−1(HSA), 0.02 to 1.00 mg mL−1(catalase), and 0.02 to 1.00 mg mL−1(lysozyme). This method is simple and of low cost, which can be used for the identification of three proteins easily via a “turn-on” mode, which may have potential in biochemical analytical field for the detection of proteins or even more complex substances.

Published
2024
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48. Supplemental Data from ARRB1-Promoted NOTCH1 Degradation Is Suppressed by OncomiR miR-223 in T-cell Acute Lymphoblastic Leukemia

Author

Shu, Yi, primary, Wang, Yi, primary, Lv, Wen-Qiong, primary, Peng, Dan-Yi, primary, Li, Juan, primary, Zhang, Hang, primary, Jiang, Guang-Jie, primary, Yang, Bi-Jie, primary, Liu, Shan, primary, Zhang, Jia, primary, Chen, Yan-Hua, primary, Tang, Shi, primary, Wan, Ke-Xing, primary, Yuan, Jun-Tao, primary, Guo, Wei, primary, Fu, Guo, primary, Qi, Xin-Kun, primary, Liu, Zhi-Dai, primary, Liu, Hai-Yan, primary, Yang, Chao, primary, Zhang, Ling-Huan, primary, Liu, Fang-Jie, primary, Yu, Jie, primary, Zhang, Peng-Hui, primary, Qu, Bin, primary, Zhao, Hui, primary, He, Tong-Chuan, primary, and Zou, Lin, primary

Published
2023
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49. Table S2 from ARRB1-Promoted NOTCH1 Degradation Is Suppressed by OncomiR miR-223 in T-cell Acute Lymphoblastic Leukemia

Author

Shu, Yi, primary, Wang, Yi, primary, Lv, Wen-Qiong, primary, Peng, Dan-Yi, primary, Li, Juan, primary, Zhang, Hang, primary, Jiang, Guang-Jie, primary, Yang, Bi-Jie, primary, Liu, Shan, primary, Zhang, Jia, primary, Chen, Yan-Hua, primary, Tang, Shi, primary, Wan, Ke-Xing, primary, Yuan, Jun-Tao, primary, Guo, Wei, primary, Fu, Guo, primary, Qi, Xin-Kun, primary, Liu, Zhi-Dai, primary, Liu, Hai-Yan, primary, Yang, Chao, primary, Zhang, Ling-Huan, primary, Liu, Fang-Jie, primary, Yu, Jie, primary, Zhang, Peng-Hui, primary, Qu, Bin, primary, Zhao, Hui, primary, He, Tong-Chuan, primary, and Zou, Lin, primary

Published
2023
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50. Data from ARRB1-Promoted NOTCH1 Degradation Is Suppressed by OncomiR miR-223 in T-cell Acute Lymphoblastic Leukemia

Author

Shu, Yi, primary, Wang, Yi, primary, Lv, Wen-Qiong, primary, Peng, Dan-Yi, primary, Li, Juan, primary, Zhang, Hang, primary, Jiang, Guang-Jie, primary, Yang, Bi-Jie, primary, Liu, Shan, primary, Zhang, Jia, primary, Chen, Yan-Hua, primary, Tang, Shi, primary, Wan, Ke-Xing, primary, Yuan, Jun-Tao, primary, Guo, Wei, primary, Fu, Guo, primary, Qi, Xin-Kun, primary, Liu, Zhi-Dai, primary, Liu, Hai-Yan, primary, Yang, Chao, primary, Zhang, Ling-Huan, primary, Liu, Fang-Jie, primary, Yu, Jie, primary, Zhang, Peng-Hui, primary, Qu, Bin, primary, Zhao, Hui, primary, He, Tong-Chuan, primary, and Zou, Lin, primary

Published
2023
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