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7 results on '"Qiang Tuo"'

1. The effect of dietary supplementation of Lycium barbarum leaves on the growth performance, organ indexes and intestinal microflora of rats

Author

Yindi Guo, Jie Liu, Qiang Tuo, Dongtao Zhang, Metha Wanapat, and Guosheng Xin

Subjects
Lycium barbarum leaves, Lycium barbarum polysaccharides, microbiota, functional feed, organ weight, Veterinary medicine, SF600-1100
Abstract

This study was conducted to investigate both fruit and different levels of leaf supplementation on the growth performance, organ indices and intestinal microflora of rats. Twenty-five healthy male Sprague–Dawley rats were randomly divided into five groups. The rats in the control (NC) and positive control (PC) groups were fed by gavage a basal diet and a basal diet with 4 g/kg of L. barbarum fruit homogenate, respectively. The test (LD, MD, and HD) groups were fed basal diets with additional 2, 4, and 8 g/kg of L. barbarum leaf homogenate, respectively. The feeding period was 35 d. The result revealed that the rats in the LD group had the highest average weight gain (p

Published
2024
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3. Research on Music Signal Processing Based on a Blind Source Separation Algorithm

Author

Xiaoming Zhao, Qiang Tuo, Ruosi Guo, and Tengteng Kong

Subjects
General Computer Science, Electrical and Electronic Engineering
Abstract

The isolation of mixed music signals is beneficial to the extraction and identification of music signal features and to enhance music signal quality. This paper briefly introduced the mathematical model for separating blind source from mixed music signals and the traditional Independent Component Analysis (ICA) algorithm. The separation algorithm was optimized by the complex neural network. The traditional and optimized ICA algorithms were simulated in MATLAB software. It was found that the time-domain waveform of the signal isolated by the improved ICA-based separation algorithm was closer to the source signal. The similarity coefficient matrix, signal-to-interference ratio, performance index, and iteration time of the improved ICA-based algorithm was 62.3, 0.0011, and 0.87 s, respectively, which were all superior to the traditional ICA algorithm. The novelty of this paper is setting the initial iterative matrix of the ICA algorithm with the complex neural network.

Published
2022

5. Enhancement of osteogenesis using a novel porous hydroxyapatite scaffold in vivo and vitro

Author

Guo Huang, Jinyu Li, Zhenghui Chen, Jia Wu, Kun Tian, Qingwei Wang, Taotao Xu, Qiang Tuo, Jie Weng, Xinrong Lv, Xiaohua Ren, and Yandong Mu

Subjects
0301 basic medicine, Scaffold, Materials science, Biocompatibility, Process Chemistry and Technology, Mesenchymal stem cell, 02 engineering and technology, 021001 nanoscience & nanotechnology, Bone morphogenetic protein 2, In vitro, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Cell biology, 03 medical and health sciences, 030104 developmental biology, Vasculogenesis, In vivo, Materials Chemistry, Ceramics and Composites, 0210 nano-technology, Protein adsorption
Abstract

The repair of large maxillofacial bony defects using regular scaffolds is restricted by the osteogenic effect. It was postulated that a novel porous hydroxyapatite (HA) scaffolds with a 25–30 µm groove structure (HAG) may counter this limitation. In this study we evaluated the biocompatibility of HAG scaffolds both in vitro and in vivo in beagle dogs by investigating the enhancement of scaffolds bioactivity and osteogenesis. Compared with a regular HA scaffolds, the HAG scaffolds significantly promoted human placenta-derived mesenchymal stem cell (hPMSC) osteogenic differentiation and the maturation of osteoblasts. This is achieved by increasing protein adsorption, as well as promoting directed growth and expression of osteogenic genes in vitro. The compressive strength of HAG scaffolds was significantly greater than HA in both dorsal muscle and the mandibular distraction area after in vivo implantation, with hematoxylin and eosin staining demonstrating new bone formation and vasculogenesis. Immunochemical staining and micro-CT scanning demonstrated increased expression of osteogenic factors (BMP2, OCN and COL-1) and bone density in the HAG scaffolds compared with HA. Based on the above results, we conclude that HAG scaffolds that have a groove structure induce greater osteogenesis and possess improved ostoegenesis which could be utilized in the clinical treatment.

Published
2018

6. New Exact Penalty Function Methods with ∈-approximation and Perturbation Convergence for Solving Nonlinear Bilevel Programming Problems.

Author

Qiang Tuo and Heng-you Lan

Subjects
*PERTURBATION theory, *MATHEMATICAL functions, *BILEVEL programming, *APPROXIMATION theory, *DIFFERENTIAL equations, *MATHEMATICAL optimization
Abstract

In this paper, in order to solve a class of nonlinear bilevel programming problems, we equivalently transform the nonlinear bilevel programming problems into corresponding single level nonlinear programming problems by using the Karush-Kuhn-Tucker optimality condition. Then, based on penalty function theory, we construct a smooth approximation method for obtaining optimal solutions of classic l1-exact penalty function optimality problems, which is equivalent to the single level nonlinear programming problems. Furthermore, using ∈-approximate optimal solution theory, we prove convergence of a simple ∈-approximate optimal algorithm. Finally, through adding parameters in the constraint set of objective function, we prove some perturbation convergence results for solving the nonlinear bilevel programming problems. [ABSTRACT FROM AUTHOR]

Published
2019

7. New Exact Penalty Function Methods with ϵ-approximation and Perturbation Convergence for Solving Nonlinear Bilevel Programming Problems.

Author

Qiang Tuo and Heng-you Lan

Subjects
*NONLINEAR programming, *BILEVEL programming, *GEOMETRIC function theory, *STOCHASTIC convergence, *PERTURBATION theory
Abstract

In this paper, in order to solve a class of nonlinear bilevel programming problems, we equivalently transform the nonlinear bilevel programming problems into corresponding single level nonlinear programming problems by using the Karush-Kuhn-Tucker optimality condition. Then, based on penalty function theory, we construct a smooth approximation method for obtaining optimal solutions of classic l1-exact penalty function optimality problems, which is equivalent to the single level nonlinear programming problems. Furthermore, using e-approximate optimal solution theory, we prove convergence of a simple ϵ-approximate optimal algorithm. Finally, through adding parameters in the constraint set of objective function, we prove some perturbation convergence results for solving the nonlinear bilevel programming problems. [ABSTRACT FROM AUTHOR]

Published
2019

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