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Search Results: 1 - 10 of 8237 matches for " SHAO YuanZhi "
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Stochastic resonance in the growth of a tumor induced by correlated noises
Weirong Zhong,Yuanzhi Shao,Zhenhui He
Chinese Science Bulletin , 2005, DOI: 10.1007/BF03183733
Abstract: Multiplicative noise is found to divide the growth law of tumors into two parts in a logistic model, which is driven by additive and multiplicative noises simultaneously. The Fokker-Planck equation was also derived to explain the fact that the influence of the intensity of multiplicative noise on the growth of tumor cells has a stochastic resonance-like characteristic. An appropriate intensity of multiplicative noise is benefit to the growth of the tumor cells. The correlation between two sorts of noises weakens the stochastic resonance-like characteristic. Homologous noises promote the growth of the tumor cells.
Nonequilibrium dynamic transition in a kinetic Ising model driven by both deterministic modulation and correlated stochastic noises
Yuanzhi Shao,Weirong Zhong,Zhenhui He
Chinese Science Bulletin , 2005, DOI: 10.1007/BF03183630
Abstract: We report the nonequilibrium dynamical phase transition (NDPT) appearing in a kinetic Ising spin system (ISS) subject to the joint application of a deterministic external field and the stochastic mutually correlated noises simultaneously. A time-dependent Ginzburg-Landau stochastic differential equation, including an oscillating modulation and the correlated multiplicative and additive white noises, was addressed and the numerical solution to the relevant Fokker-Planck equation was presented on the basis of an average-period approach of driven field. The correlated white noises and the deterministic modulation induce a kind of dynamic symmetry-breaking order, analogous to the stochastic resonance in trend, in the kinetic ISS, and the reentrant transition has been observed between the dynamic disorder and order phases when the intensities of multiplicative and additive noises were changing. The dependencies of a dynamic order parameterQ upon the intensities of additive noiseA and multiplicative noiseM, the correlation λ between two noises, and the amplitude of applied external fieldh were investigated quantitatively and visualized vividly. Here a brief discussion is given to outline the underlying mechanism of the NDPT in a kinetic ISS driven by an external force and correlated noises.
Nonequilibrium dynamic transition in a kinetic Ising model driven by both deterministic modulation and correlated stochastic noises
Yuanzhi Shao,Weirong Zhong,Zhenhui He
Physics , 2006,
Abstract: We report the nonequilibrium dynamical phase transition (NDPT) appearing in a kinetic Ising spin system (ISS) subject to the joint application of a deterministic external field and the stochastic mutually correlated noises simultaneously. A time-dependent Ginzburg-Landau stochastic differential equation, including an oscillating modulation and the correlated multiplicative and additive white noises, was addressed and the numerical solution to the relevant Fokker-Planck equation was presented on the basis of an average-period approach of driven field. The correlated white noises and the deterministic modulation induce a kind of dynamic symmetry-breaking order, analogous to the stochastic resonance in trend, in the kinetic ISS, and the reentrant transition has been observed between the dynamic disorder and order phases when the intensities of multiplicative and additive noises were changing. The dependencies of a dynamic order parameter Q upon the intensities of additive noise A and multiplicative noise M, the correlation lmda between two noises, and the amplitude of applied external field h were investigated quantitatively and visualized vividly. A brief discussion was given to outline the underlying mechanism of the NDPT in a kinetic ISS driven by an external force and correlated noises. Keywords: Ising spin system, nonequilibrium dynamical phase transition, stochastic resonance, correlated noises, TDGL model. PACS: 75.10.Hk, 64.60.Ht, 05.10.Gg, 76.20.+q
Scaling Dynamic Response and Destructive Metabolism in an Immunosurveillant Anti-Tumor System Modulated by Different External Periodic Interventions
Yuanzhi Shao,Wenyong Hu,Weirong Zhong,Li Li
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0016115
Abstract: On the basis of two universal power-law scaling laws, i.e. the scaling dynamic hysteresis in physics and the allometric scaling metabolism in biosystem, we studied the dynamic response and the evolution of an immunosurveillant anti-tumor system subjected to a periodic external intervention, which is equivalent to the scheme of a radiotherapy or chemotherapy, within the framework of the growth dynamics of tumor. Under the modulation of either an abrupt or a gradual change external intervention, the population density of tumors exhibits a dynamic hysteresis to the intervention. The area of dynamic hysteresis loop characterizes a sort of dissipative-therapeutic relationship of the dynamic responding of treated tumors with the dose consumption of accumulated external intervention per cycle of therapy. Scaling the area of dynamic hysteresis loops against the intensity of an external intervention, we deduced a characteristic quantity which was defined as the theoretical therapeutic effectiveness of treated tumor and related with the destructive metabolism of tumor under treatment. The calculated dose-effectiveness profiles, namely the dose cumulant per cycle of intervention versus the therapeutic effectiveness, could be well scaled into a universal quadratic formula regardless of either an abrupt or a gradual change intervention involved. We present a new concept, i.e., the therapy-effect matrix and the dose cumulant matrix, to expound the new finding observed in the growth and regression dynamics of a modulated anti-tumor system.
The growth dynamics of tumor subject to both immune surveillance and external therapy intervention
YuanZhi Shao,WeiRong Zhong,FengHua Wang,ZhenHui He,ZhongJun Xia
Chinese Science Bulletin , 2007, DOI: 10.1007/s11434-007-0234-9
Abstract: Considering the growth of tumor cells modeled by an enzyme dynamic process under an immune surveillance, we studied in anti-tumor immunotherapy the single-variable growth dynamics of tumor cells subject to a multiplicative noise and an external therapy intervention simultaneously. The law of tumor growth of the above anti-tumor immunotherapy model was revealed through numerical simulations to the relevant stochastic dynamic differential equation. Two simulative parameters of therapy, i.e., therapy intensity and therapy duty-cycle, were introduced to characterize a treatment process similar to a tumor clinic therapy. There exists a critical therapy boundary which, in an exponent-decaying form, divides the parameter region of therapy into an invalid and a valid treatment zone, respectively. A greater critical therapy duty-cycle is necessary to achieve a valid treatment for a lower therapy intensity while the critical therapy intensity decreases accordingly with an enhancing immunity. A primary clinic observation of the patients with the typical non-hodgekin’s lymphoma was carried out, and there appears a basic agreement between clinic observations and dynamic simulations.
Government Subsidy and Crash Risk  [PDF]
Yuanzhi Chen, Chunqiang Wu
Journal of Financial Risk Management (JFRM) , 2016, DOI: 10.4236/jfrm.2016.53019
Abstract:
Using the sample of companies listed on Chinese GEM between 2009 and 2015, we examines the impact of government subsidy on companies’ future stock price crash risk and explores how the earning information opacity moderates the relation between government subsidy and crash risk. We find that: 1) the government subsidies for the listed companies increase their crash risk; 2) the firms with higher information opacity are exposed to higher stock price crash risk; 3) considering the cross effect of opacity and government subsidy, the positive correlation between government subsidy and crash risk is weakened under the high information opacity environment. With further analysis, we find that that government subsidy dominates the earning management level of Jones model while measuring firm’s information opacity. This paper not only enriches the study of external influencing factors of crash risk, but also broadens the study of government subsidy efficiency and provides a new decision basis for the investors to recognize the firms’ earning information quality.
Research on Relationship between “Direct Investment + Sponsor” Mode and IPO Pricing Efficiency  [PDF]
Yuanzhi Chen, Qixin Wang
Modern Economy (ME) , 2018, DOI: 10.4236/me.2018.92017
Abstract: The paper takes 996 IPO companies in China from 2012 to 2016 as samples and investigates the effect on IPO pricing efficiency under the Direct Investment + Sponsor Mode. The research shows that there is no significant difference between companies that intend to IPO under the Direct Investment + Sponsor mode and companies that intend to IPO under the non-Direct Investment + Sponsor mode in the discount of new stocks and one-year returns. The result shows that the firewall mechanism between the direct investment department and the investment banking department of Chinese securities traders is in good condition, verifies the rationality of not abolishing Direct Investment + Sponsor mode in Guidelines for Direct Investment Business of Securities Companies introduced by China Securities Regulatory Commission in July 2011 and powerfully refutes the markets long-lasting query that China Securities Regulatory Commission retains Direct Investment + Sponsor
The growth dynamics of tumor subject to both immune surveillance and external therapy intervention
SHAO YuanZhi,ZHONG WeiRong,WANG FengHua,HE ZhenHui,XIA ZhongJun,
SHAO
,YuanZhi,ZHONG,WeiRong,WANG,FengHua,HE,ZhenHui,XIA,ZhongJun

科学通报(英文版) , 2007,
Abstract: Considering the growth of tumor cells modeled by an enzyme dynamic process under an immune surveillance, we studied in anti-tumor immunotherapy the single-variable growth dynamics of tumor cells subject to a multiplicative noise and an external therapy intervention simultaneously. The law of tumor growth of the above anti-tumor immunotherapy model was revealed through numerical simulations to the relevant stochastic dynamic differential equation. Two simulative parameters of therapy, i.e., therapy intensity and therapy duty-cycle, were introduced to characterize a treatment process similar to a tumor clinic therapy. There exists a critical therapy boundary which, in an exponent-decaying form, divides the parameter region of therapy into an invalid and a valid treatment zone, respectively. A greater critical therapy duty-cycle is necessary to achieve a valid treatment for a lower therapy intensity while the critical therapy intensity decreases accordingly with an enhancing immunity. A primary clinic observation of the patients with the typical non-hodgekin’s lymphoma was carried out, and there appears a basic agreement between clinic observations and dynamic simulations. Supported by the National Natural Science Foundation of China (Grant No. 60471023)
Computerized Segmentation and Characterization of Breast Lesions in Dynamic Contrast-Enhanced MR Images Using Fuzzy c-Means Clustering and Snake Algorithm
Yachun Pang,Li Li,Wenyong Hu,Yanxia Peng,Lizhi Liu,Yuanzhi Shao
Computational and Mathematical Methods in Medicine , 2012, DOI: 10.1155/2012/634907
Abstract: This paper presents a novel two-step approach that incorporates fuzzy c-means (FCMs) clustering and gradient vector flow (GVF) snake algorithm for lesions contour segmentation on breast magnetic resonance imaging (BMRI). Manual delineation of the lesions by expert MR radiologists was taken as a reference standard in evaluating the computerized segmentation approach. The proposed algorithm was also compared with the FCMs clustering based method. With a database of 60 mass-like lesions (22 benign and 38 malignant cases), the proposed method demonstrated sufficiently good segmentation performance. The morphological and texture features were extracted and used to classify the benign and malignant lesions based on the proposed computerized segmentation contour and radiologists’ delineation, respectively. Features extracted by the computerized characterization method were employed to differentiate the lesions with an area under the receiver-operating characteristic curve (AUC) of 0.968, in comparison with an AUC of 0.914 based on the features extracted from radiologists’ delineation. The proposed method in current study can assist radiologists to delineate and characterize BMRI lesion, such as quantifying morphological and texture features and improving the objectivity and efficiency of BMRI interpretation with a certain clinical value. 1. Introduction Breast cancer is the most common cancer and a leading cause of deaths in cancer for women worldwide [1]. In the United States, the chance of developing invasive breast cancer in a woman’s life is nearly 1 in 8 [2]. Medical imaging, specifically, magnetic resonance imaging (MRI) plays a crucial role in detecting and diagnosing breast lesions and tumors. While mammography, as recently reported, might fail to spot up to 20 percent of tumors, MRI can detect breast cancer missed by mammography [3, 4]. Because of MRI’s effectiveness in detecting breast cancer, American Cancer Society has published the guidelines for recommending women with high risk of breast cancer to receive MRI screening [5]. With its high sensitivity and variable specificity, MRI has been increasingly used for a breast cancer detection and characterization [6–8]. As a result, there is an urgent need to develop a computer-aided diagnosis system to release radiologists from the heavy works of medical image analysis. Unfortunately, compared with mammography, relatively fewer automated CADs have been developed specifically for breast MRI. Chen et al. [9] applied the region-growing method to segment lesions and later they [10] proposed a semiautomated
Study for solving the path on the three-dimensional surface based on Cellular Automata method
wang yuanzhi
Modern Applied Science , 2010, DOI: 10.5539/mas.v4n5p196
Abstract: For the path optimization problem on the irregular surface of three-dimension, three-dimensional surface is discretized with grid. Based on the parallel character of cellular automata in the cellular space, with the dynamic cellular neighbors , the time evolution interval is defined as the minimum remaining weight. The new shortest path algorithm is structured, based on cellular automaton model. That is to say, through the simple rules of evolution of cellular state, the shortest path is got. The method can achieve the efficiency of ant colony algorithm, and a new way of application of the Cellular Automata model is provided.
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