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GROUP COOPERATIVE LEARNING IN UNIVERSITY ADVANCED MATHEMATICS
Zhijun Luo
Journal of Global Research in Mathematical Archives , 2013,
Abstract: Advanced Mathematics is one of the most important and fundamental courses for students of engineering and science. In this paper, we consider how to enhance advanced mathematics teaching. Group cooperative learning is applied to the advanced mathematics classroom; the traditional teaching mode can be transformed in student-cantered environment so that students can study with each other under relaxing circumstances. It can enhance learners study motivation, foster their self-esteem and develop their interpersonal skills. Keywords: Advanced Mathematics research; Group cooperative learning; Assessment
A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization
Zhijun Luo,Lirong Wang
Journal of Mathematics , 2014, DOI: 10.1155/2014/461902
Abstract: A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved. 1. Introduction Consider the following inequality constrained optimization problems: where , are continuously differentiable. We denote To solve the problem (1), there are two type methods with superlinear convergence: sequential quadratic programming (SQP) type algorithms (see [1–4], etc.) and SSLE (sequential system of linear equations) type algorithms (see [5–9], etc.). In general, since SQP algorithms are necessary to solve one or more quadratic programming subproblems in single iteration, the computation effort is very large. SSLE algorithms were proposed to solve the problem (1), in which an iteration similar to the following linear system was considered: where is Lagrangian function, is an estimate of the Hessian of , is the current estimate of a solution , is the search direction, and is the next estimate of the Kuhn-Tucker multiplier vector associated with . Obviously, it is simpler to solve system of linear equations than to solve the QP (quadratic programming) problem with inequality constraints. In addition, parallel variable distribution (PVD) algorithm [10] is a method that distributes the variables among parallel processors. The problem is parted into many respective subproblems and each subproblem is arranged to a different processor in it. Each processor has the primary responsibility for updating its block of variables while allowing the remaining secondary variables to change in a restricted fashion along some easily computable directions. In 2002, Sagastizábal and Solodov [11] proposed two new variants of PVD for the constrained case. Without assuming convexity of constraints, but assuming block-separable structure, they showed that PVD subproblems can be solved inexactly by solving their quadratic programming approximations. Han et al. [12] proposed an asynchronous PVT algorithm for solving large-scale linearly constrained convex minimization problems with the idea in 2009, which is based on the idea that a constrained optimization problem is equivalent to a differentiable unconstrained optimization problem by introducing the Fischer
Geometric Buildup Algorithms for Sensor Network Localization
Zhenzhen Zheng,Xinlong Luo,Zhijun Wu
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/927031
Abstract: We present a geometric buildup algorithm for solving the sensor network localization problem with either accurate or noisy distance data. The algorithm determines the locations of the sensors, one at a time, by using the distances between the determined sensors and the undetermined ones. Each time, only a small system of distance equations needs to be solved and therefore, in an ideal case when the required distances are available for every sensor to be determined, the computation can be completed in steps if sensors are to be determined. An algorithm with two buildup phases is also implemented to handle not only noisy but also sparse distance data with for example only a few distant anchors. We show our test results and compare them with other approaches.
A Global Convergence of LS-CD Hybrid Conjugate Gradient Method
Xiangfei Yang,Zhijun Luo,Xiaoyu Dai
Advances in Numerical Analysis , 2013, DOI: 10.1155/2013/517452
Abstract: Conjugate gradient method is one of the most effective algorithms for solving unconstrained optimization problem. In this paper, a modified conjugate gradient method is presented and analyzed which is a hybridization of known LS and CD conjugate gradient algorithms. Under some mild conditions, the Wolfe-type line search can guarantee the global convergence of the LS-CD method. The numerical results show that the algorithm is efficient. 1. Introduction Consider the following nonlinear programs: where denotes an -dimensional Euclidean space and is continuously differentiable function. As you know, conjugate gradient method is a line search method that takes the following form: where is a descent direction of at and is a stepsize obtained by some one-dimensional line search. If is the current iterate, we denote , , and , respectively. If is available and inverse, then leads to the Newton method and results in the steepest descent method [1]. The search direction is generally required to satisfy , which guarantees that is a descent direction of at [2]. In order to guarantee the global convergence, we sometimes require to satisfy a sufficient descent condition as follows: where is a constant and is the Euclidean norm. In line search methods, the well-known conjugate gradient method has the following form: Different conjugate gradient algorithms correspond to different choices for the parameter , where can be defined by or by other formulae. The corresponding methods are called FR (Fletcher-Reeves) [3], PRP (Polak-Ribiére-Polyak) [4, 5], DY (Dai-Yuan) [6], CD (conjugate descent [7]), LS (Liu-Storey [8]), and HS (Hestenes-Stiefel [9]) conjugate gradient method, respectively. Although the above mentioned conjugate gradient algorithms are equivalent to each other for minimizing strong convex quadratic functions under exact line search, they have different performance when using them to minimize nonquadratic functions or when using inexact line searches. For general objective function, the FR, DY, and CD methods have strong convergence properties, but they may have modest practical performance due to jamming. On the other hand, the methods of PRP, LS, and HS in general may not be convergent, but they often have better computational performance. Touati-Ahmed and Storey [10] have given the first hybrid conjugate algorithm; the method is combinations of different conjugate gradient algorithms; mainly it is being proposed to avoid the jamming phenomenon. Recently, some kinds of new hybrid conjugate gradient methods are given in [11–17]. Based on the new method, we
Lysyl Oxidase, A Critical Intra- and Extra-Cellular Target in the Lung for Cigarette Smoke Pathogenesis
Wande Li,Jing Zhou,Lijun Chen,Zhijun Luo,Yinzhi Zhao
International Journal of Environmental Research and Public Health , 2011, DOI: 10.3390/ijerph8010161
Abstract: Cigarette smoke (CS), a complex chemical mixture, contains more than 4,800 different compounds, including oxidants, heavy metals, and carcinogens, that individually or in combination initiate or promote pathogenesis in the lung accounting for 82% of chronic obstructive pulmonary disease (COPD) deaths and 87% of lung cancer deaths. Lysyl oxidase (LO), a Cu-dependent enzyme, oxidizes peptidyl lysine residues in collagen, elastin and histone H1, essential for stabilization of the extracellular matrix and cell nucleus. Considerable evidences have shown that LO is a tumor suppressor as exemplified by inhibiting transforming activity of ras, a proto oncogene. CS condensate (CSC), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and cadmium (Cd), major components of CS, down-regulate LO expression at such multiple levels as mRNA, protein and catalytic activity in lung cells in vitro and in vivo indicating LO as a critical intra- and extracellular target for CS pathogenesis in the lung. In view of multiple biological functions and regulation characteristics of the LO gene, molecular mechanisms for CS damage to lung LO and its role in emphysema and cancer pathogenesis are discussed in this review.
Effects of ulinastatin and docataxel on breast tumor growth and expression of IL-6, IL-8, and TNF-α
Xiaoliang Zhao, Xin Sun, Feng Gao, Jie Luo, Zhijun Sun
Journal of Experimental & Clinical Cancer Research , 2011, DOI: 10.1186/1756-9966-30-22
Abstract: MDA-MB-231 human breast carcinoma cells were cultured in vitro and injected into nude mice to establish breast tumor xenografts in vivo. Cultured cells and mice with tumors were randomly divided into four groups for treatment with TAX, UTI, and TAX+UTI. The effects of these drug treatments on cell proliferation and apoptosis was measured using the MTT assay and the Annexin V/propidium iodide (PI) double-staining method, respectively. IL-6, IL-8, and TNF-α expression levels were determined by measuring mRNA transcripts in cultured cells by RT-PCR and cytokine proteins in solid tumors using immunohistochemistry.UTI, TAX, and UTI+TAX inhibited the growth of MDA-MB-231 cells in vitro and tumors in vivo. These two drugs, particularly when used in combination, promote tumor cell apoptosis and down-regulate the expression IL-6, IL-8, and TNF-α cytokines.Both UTI and TAX inhibited the growth of MDA-MB-231 breast carcinoma cells. UTI enhanced the inhibitory effect of TAX by a mechanism consistent with the down-regulated expression of IL-6, IL-8, and TNF-α.Along with the increasing incidence of breast cancer tumors, which now account for 18% of all female tumors, 1.2 million women suffer from breast cancer worldwide. Many important problems pertaining to the oncological details of invasion and metastasis pose significant challenges to scientists.With the development of new techniques in molecular biology, further exploration into the mechanisms related to the occurrence of breast cancer have become a hotspot in the field of cancer research. The cytokines, which play regulatory roles in disease development have become an important topic for many researchers. IL-6, IL-8, and TNF-α are one group of cytokines produced by mononuclear macrophages and endotheliocytes involved in activating and inducing T cells, B cells, and natural killer cells to target and phagocytosize pathogenic cells. Additionally, these cytokines are important factors in inflammation and pathophysiology.In thi
Development and Control of Compliant Hybrid Joints for Human-Symbiotic Mobile Manipulators
Zhijun Li,Jun Luo,Ning Xi,Aiguo Ming
International Journal of Advanced Robotic Systems , 2008,
Abstract: In this paper, we develop a robot with the ability to secure human safety in humanrobot collisions arising in our living and working environments. The humansymbiotic service robot using compliant hybrid joints realizes human safety, absorbs impact force, and fulfills task. In unexpected or expected collisions with human, the arising impulse force is attenuated effectively by the proposed physical model. Owing to the displacement of the links, several recovery controls have been developed for the endeffector to maintain its desired task position after the collision. The force attenuation property has been verified through collision simulations and experiments in that the capability of the proposed passive arm in overcoming the limitations of active compliance control has been demonstrated.
A Feasible SQP Method with Superlinear Convergence for General Constrained Optimization
Ajuan Ren,Fujian Duan,Zhibin Zhu,Zhijun Luo
Journal of Applied Sciences , 2007,
Abstract: In this study, optimization problems with general equality and inequality constraints are discussed. Firstly, the original problems are changed into parametric programming problems with only inequality constraints and these two problems are equivalent with each other if the parameter is suitable. Then, we give a new idea called first-order feasible condition, which is used to solve the changed problems. Under some reasonable conditions, the global and superlinear convergence is shown.
AMPK exerts dual regulatory effects on the PI3K pathway
Rong Tao, Jun Gong, Xixi Luo, Mengwei Zang, Wen Guo, Rong Wen, Zhijun Luo
Journal of Molecular Signaling , 2010, DOI: 10.1186/1750-2187-5-1
Abstract: In the present study we further investigated the mechanism of AMPK-regulated insulin signaling. Our results showed that 5-aminoimidazole-4-carboxamide-1 ribonucleoside (AICAR) greatly enhanced the ability of insulin to stimulate the insulin receptor substrate-1 (IRS1)-associated PI3K activity in differentiated 3T3-F442a adipocytes, leading to increased Akt phosphorylation at S473, whereas insulin-stimulated activation of mTOR was diminished. In 3T3-F442a preadipocytes, these effects were attenuated by expression of a dominant negative mutant of AMPK α1 subunit. The enhancing effect of ACIAR on Akt phosphorylation was also observed when the cells were treated with EGF, suggesting that it is regulated at a step beyond IR/IRS1. Indeed, when the cells were chronically treated with AICAR in the absence of insulin, Akt phosphorylation was progressively increased. This event was associated with an increase in levels of phosphatidylinositol -3,4,5-trisphosphate (PIP3) and blocked by Wortmannin. We then expressed the dominant negative mutant of PTEN (C124S) and found that the inhibition of endogenous PTEN per se did not affect phosphorylation of Akt at basal levels or upon treatment with AICAR or insulin. Thus, this result suggests that AMPK activation of Akt is not mediated by regulating phosphatase and tensin homologue (PTEN).Our present study demonstrates that AMPK exerts dual effects on the PI3K pathway, stimulating PI3K/Akt and inhibiting mTOR/S6K.AMP-activated protein kinase (AMPK) is a heterotrimeric enzyme consisting of an α catalytic subunit (α1, α2), and β (β1, β2) and γ (γ1, γ2, γ3) regulatory subunits [1]. The activation of AMPK occurs by binding of 5' AMP to the γ subunit and phosphorylation of T172 in the activation loop of the α catalytic subunit by upstream kinases such as LKB1 and CaMKK [1]. AMPK is activated in response to hypoxia, glucose deprivation, and muscle exercise, under which the AMP to ATP ratio is increased. In addition, AMPK activity is increase
Motor Imagery did not Improve Strength of Biceps Brachii  [PDF]
Lanxiang He, Zhijun Tian
Engineering (ENG) , 2012, DOI: 10.4236/eng.2012.410B025
Abstract:
Numerous studies have confirmed that motor imagery may result in plastic change in motor system as actual physical activity. However, whether motor imagery can improve muscle strength of the trained persons remains unclear. The aim of this study is to investigate the effect of motor imagery on muscle strength. Totally 12 healthy college students were involved in 4 weeks of mental rehearsal of right upper limb movements (flexion and extension of elbow) during 30 min supervision session three times a week. Electromyogram (EMG) and peak torque of biceps brachii, reaction time of subjects were analyzed. Results showed that no significant change in EMG of biceps brachii was observed during motor imagery. After motor rehearsal for 4 weeks, statistically significant difference in EMG, peak torque and reactivity were not observed (P > 0.05) when compared with the baseline data. Therefore, motor imagery could not enhance muscle strength of subjects. Whether mental practice is a valid rehabilitation technique needs to be investigated further.
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