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Search Results: 1 - 10 of 120169 matches for " LiMin Wang "
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Banana Peel Carbon that Containing Functional Groups Applied to the Selective Adsorption of Au(III) from Waste Printed Circuit Boards  [PDF]
Huajun Zheng, Limin Wang
Soft Nanoscience Letters (SNL) , 2013, DOI: 10.4236/snl.2013.32006

This paper reports a kind of banana peel carbon (BPC) containing -OH, -NH2 functional groups which prepared through controlling carbonization temperature and its application on the selective adsorption of gold from waste printed circuit boards (PCBs). The adsorption of BPC for Au(III) reached equilibrium in 30 min and the adsorption of Au(III) was favorable at pH 2.5. Meanwhile, the adsorption isotherm showed the maximum adsorption capacity of 801.7 mg/g for Au(III). The results displayed that BPC had a strong selectivity for Au(III) and a negligible affinity to base metal ions, such as Cu(II), Ni(II), Fe(III) and Pb(II). The BPC adsorbent, which absorbed gold, can be recovered completely by HCl-thiourea solution.

Neuroprotective effect of panax notoginseng saponins and its main components  [PDF]
Xumei Wang, Shaoxia Wang, Limin Hu
World Journal of Neuroscience (WJNS) , 2014, DOI: 10.4236/wjns.2014.41002

Stroke is the third leading cause of death and the first cause of adult disability in industrial countries [1]. It is charicaterized by hemiplegia, hemianopsia, aphasia, mouth askew and sever sequelae. It is considered that an ischemic disease without any specific treatment method and few effective drugs such as tPA (human tissue-type plasminogen activator) and Edarovone with specific therapeutic window will cause a lot of disadvantages if being used inaccurate. Root of Panax notoginseng (PN) which is one of traditional Chinese medicines (TCMs), was first found in “Shennong’s Classic of Materia Medica” around 200 AD. Panax notogineng saponins(PNS) is a multi-components mixture containing ginseng and saponins as the most important bioactive components which are commonly used in clinical treatment. Also, ginseng and saponins form the main components of many herbal medicines in the market, e.g., Xueshuantong injection [2], Xuesaitong injection [3], Xuesaitong soft capsule [4] and so on. The main monomers of Panax notoginseng saponins (PNS) are Ginsenoside-Rb1, Gensenoside-Rg1, Gensenoside-Re, Gensenoside-Rd and Panax notoginseng saponins-R1 [5]. In this review, we found some important points as well as shortcomings that require special consideration. We therefore highlighted the advances in neuro-protection of PNS and its main monomers in the area of experimental research.

Optimal Iterative Learning Fault-Tolerant Guaranteed Cost Control for Batch Processes in the 2D-FM Model
Limin Wang,Weiwei Dong
Abstract and Applied Analysis , 2012, DOI: 10.1155/2012/748981
Abstract: This paper develops the optimal fault-tolerant guaranteed cost control scheme for a batch process with actuator failures. Based on an equivalent two-dimensional Fornasini-Marchsini (2D-FM) model description of a batch process, the relevant concepts of the fault-tolerant guaranteed cost control are introduced. The robust iterative learning reliable guaranteed cost controller (ILRGCC), which includes a robust extended feedback control for ensuring the performances over time and an iterative learning control (ILC) for improving the tracking performance from cycle to cycle, is formulated such that it cannot only guarantee the closed-loop convergency along both the time and the cycle directions but also satisfy both the ∞ performance level and a cost function having upper bounds for all admissible uncertainties and any actuator failures. Conditions for the existence of the controller are derived in terms of linear matrix inequalities (LMIs), and a design procedure of the controller is presented. Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteed cost controller which minimizes the upper bound of the closed-loop system cost. Finally, an illustrative example of injection molding is given to demonstrate the effectiveness and advantages of the proposed 2D design approach.
An Analysis of Pricing Strategies in the Process of Business Acquisition
Duo Feng,Limin Wang
International Journal of Business and Management , 2009, DOI: 10.5539/ijbm.v4n1p37
Abstract: In the process of enterprise merger, how to make transaction price much more rational has become a difficult problem theoretically and practically. This article applies the method of game theory to analyze the equilibrium price between the buyers and the sellers or just the buyers existing in enterprise merger market, and then puts forward the optimal bidding strategies in the merging process. Moreover, it also indicates that Bayesian balance lies in the competition between the buyers, while the best response of every game player is that its quotation should be half of its evaluation of the merged enterprise.
Research on Decision Forest Learning Algorithm
Limin Wang,Xiongfei Li
Computer and Information Science , 2009, DOI: 10.5539/cis.v1n2p17
Abstract: Decision Forests are investigated for their ability to provide insight into the confidence associated with each prediction, the ensembles increase predictive accuracy over the individual decision tree model established. This paper proposed a novel “bottom-top” (BT) searching strategy to learn tree structure by combining different branches with the same root, and new branches can be created to overcome overfitting phenomenon.
Using Consensus Bayesian Network to Model the Reactive Oxygen Species Regulatory Pathway
Liangdong Hu, Limin Wang
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0056832
Abstract: Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the Bayesian network from microarray data directly. Although large numbers of Bayesian network learning algorithms have been developed, when applying them to learn Bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn Bayesian networks contain too few microarray data. In this paper, we propose a consensus Bayesian network which is constructed by combining Bayesian networks from relevant literatures and Bayesian networks learned from microarray data. It would have a higher accuracy than the Bayesian networks learned from one database. In the experiment, we validated the Bayesian network combination algorithm on several classic machine learning databases and used the consensus Bayesian network to model the 's ROS pathway.
A New Cosmological Model of Quintessence and Dark Matter
Varun Sahni,Limin Wang
Physics , 1999, DOI: 10.1103/PhysRevD.62.103517
Abstract: We propose a new class of quintessence models in which late times oscillations of a scalar field give rise to an effective equation of state which can be negative and hence drive the observed acceleration of the universe. Our ansatz provides a unified picture of quintessence and a new form of dark matter we call "Frustrated Cold Dark Matter" (FCDM). FCDM inhibits gravitational clustering on small scales and could provide a natural resolution to the core density problem for disc galaxy halos. Since the quintessence field rolls towards a small value, constraints on slow-roll quintessence models are safely circumvented in our model.
The Cosmic Microwave Background Bispectrum and Inflation
Limin Wang,Marc Kamionkowski
Physics , 1999, DOI: 10.1103/PhysRevD.61.063504
Abstract: We derive an expression for the non-Gaussian cosmic-microwave-background (CMB) statistic $I_l^3$ defined recently by Ferreira, Magueijo, and G\'orski in terms of the slow-roll-inflation parameters $\epsilon$ and $\eta$. This result shows that a nonzero value of $I_l^3$ in COBE would rule out single-field slow-roll inflation. A sharp change in the slope of the inflaton potential could increase the predicted value of $I_l^3$, but not significantly. This further suggests that it will be difficult to account for such a detection in multiple-field models in which density perturbations are produced by quantum fluctuations in the scalar field driving inflation. An Appendix shows how to evaluate an integral that is needed in our calculation as well as in more general calculations of CMB bispectra.
Development of a Regional Regression Model for Estimating Annual Runoff in the Hailar River Basin of China  [PDF]
Limin Duan, Tingxi Liu, Xixi Wang, Yanyun Luo, Long Wu
Journal of Water Resource and Protection (JWARP) , 2010, DOI: 10.4236/jwarp.2010.211111
Abstract: The Hailar River, a first-grade tributary of the Erguna River that borders China and Russia, is the main water source for the local industry and agriculture. However, because there are only 11 flow gauging stations and those stations cannot monitor all runoff paths, it is hard to directly use the existing flow data to estimate the annual runoffs from all subbasins of interest although such estimation is needed for utilization and protection of the water resources in the Hailar River. Thus, this study implemented an indirect approach (i.e., regional regression model) by correlating annual runoff with annual rainfall and water surface evaporation as well as hydrologic characteristics of the 11 subbasins monitored by the gauging stations. The study used 51 years (from 1956 to 2006) data. The results indicated a significant correlation (R2 > 0.87) between annual runoff and the selected subbasin characteristics and showed the model to be robust because the predicted runoffs for the validation period are compatible with the corresponding observed values. In addition, this model was used to estimate the annual runoffs for the subbasins that are not monitored by the 11 flow gauging stations, which adds new information to existing literature.
Time-Varying Bandpass Filter Based on Assisted Signals for AM-FM Signal Separation: A Revisit  [PDF]
Guanlei Xu, Xiaotong Wang, Xiaogang Xu, Lijia Zhou, Limin Shao
Journal of Signal and Information Processing (JSIP) , 2013, DOI: 10.4236/jsip.2013.43031

In this paper, a new signal separation method mainly for AM-FM components blended in noises is revisited based on the new derived time-varying bandpass filter (TVBF), which can separate the AM-FM components whose frequencies have overlapped regions in Fourier transform domain and even have crossed points in time-frequency distribution (TFD) so that the proposed TVBF seems like a “soft-cutter” that cuts the frequency domain to snaky slices with rational physical sense. First, the Hilbert transform based decomposition is analyzed for the analysis of nonstationary signals. Based on the above analysis, a hypothesis under a certain condition that AM-FM components can be separated successfully based on Hilbert transform and the assisted signal is developed, which is supported by representative experiments and theoretical performance analyses on a error bound that is shown to be proportional to the product of frequency width and noise variance. The assisted signals are derived from the refined time-frequency distributions via image fusion and least squares optimization. Experiments on man-made and real-life data verify the efficiency of the proposed method and demonstrate the advantages over the other main methods.

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