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匹配条件: “Qi Yuan” ,找到相关结果约36155条。
Synthesis of Ferrocene Tertiary Amine Cyclopalladium Compounds and Its Application in Suzuki and Sonogashira Reactions  [PDF]
Qi Yuan
Open Access Library PrePrints (OALib PrePrints) , 2017, DOI: 10.4236/oalib.preprints.1200181
Ynones, also known as α, β-acetylenic ketones, have been widespread used in modern synthetic organic chemistry. They exist in biologically active compounds, and are used as vital building blocks in complex molecule synthesis. Consequently, a number of methodologies involving ynones have been developed to access a wide range scaffold using this simple building block. In this paper, the synthesis of a ferrocene tertiary amine cyclopalladium compounds and its application in Suzuki & Sonogashira reactions were our main works, to achieve the goal of discovering new ynones. The contents including the following three aspects: (1) The Schiff bases synthesized by ferrocene methylamine and cinnamaldehyde were underwent sodium borohydride reduction, then the corresponding cyclopalladium compounds were obtained by Mannich reaction and cyclopalladation. The structures of products were characterized by NMR spectroscopy and X-ray single crystal diffraction. (2) Suzuki coupling reactions between 3,4-dimethoxyphenylboronic acid and a series of aryl halides were studied, and several biphenyl coupling products were characterized by NMR spectroscopy. Besides, we also optimized the reaction conditions and expanded the range of substrates. (3) Sonogashira coupling reactions between phenylacetylene and series of acid chlorides were discovered, and several ynones derivatives were characterized by NMR spectroscopy. We also optimized the conditions of reaction and expanded the range of substrates.
Modularity and Dynamics of Cellular Networks
Yuan Qi,Hui Ge
PLOS Computational Biology , 2006, DOI: 10.1371/journal.pcbi.0020174
A WebGIS-Based Information System for Monitoring and Warning of Geological Disasters for Lanzhou City, China
Fang Miao,Qi Yuan
Advances in Meteorology , 2013, DOI: 10.1155/2013/769270
Abstract: Monitoring and warning of geological disasters accurately and in a timely fashion would dramatically mitigate casualties and economic losses. This paper takes Lanzhou city as an example and designs a Web-based system, namely the information system for geological disaster monitoring and warning (ISGDMW). Presented are its framework, key developing technologies, database, and working flow. The information system adopts a Browser/Server (B/S) structure and has three-tier architecture, combining in-situ monitoring instruments, the wireless sensor network, WebGIS techniques and the grey system theory. The framework of the ISGDMW can be divided into three categories: (1) in-situ monitoring system, it aims to monitor geological disaster sites and get state information of geological disaster sites; (2) database, manage in-situ monitoring data, antecedent field investigating data and basic data; (3) analyzing and warning system, analyze in-situ monitoring data, understand the deformation trend of the potential geological disaster, and release disaster warning information to the public. The ISGDMW allow the processes of geological disaster monitoring, in-situ monitoring data analysis, geological disaster warning to be implemented in an efficient and quick way, and can provide scientific suggestions to commanders for quick response to the possibility of geological disaster. 1. Introduction To mitigate geological disaster, we should depend on both real-time in situ data and quick response to the possibility of geological disaster. WebGIS is the integrated product of geographic information system (GIS) and internet technologies; in WebGIS, the internet technologies are connected with GIS in order to take advantage of their special characteristics, such as easy usability, use of the GIS data such as input, adjustment, manipulation, analysis, and output of geographical information and to bring out related service on the internet. Whereas previous standalone GIS had restricted application capability on the network, the WebGIS makes it possible to retrieve and analyze spatial data through the web. The internet also provides a medium for processing georelated information with no location restrictions [1]. In addition, WebGIS promotes the sharing and synthesis of multisource data and enables widespread sharing of spatial data and geosciences models [2]. Therefore, WebGIS offers a powerful and advanced approach to prevent and mitigate geological disaster, and it has played a significant role in terms of transmitting catastrophe data, analyzing the disaster condition, and
EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning
Yuan Qi,Feng Yan
Computer Science , 2011,
Abstract: It is a challenging task to select correlated variables in a high dimensional space. To address this challenge, the elastic net has been developed and successfully applied to many applications. Despite its great success, the elastic net does not explicitly use correlation information embedded in data to select correlated variables. To overcome this limitation, we present a novel Bayesian hybrid model, the EigenNet, that uses the eigenstructures of data to guide variable selection. Specifically, it integrates a sparse conditional classification model with a generative model capturing variable correlations in a principled Bayesian framework. We reparameterize the hybrid model in the eigenspace to avoid overfiting and to increase the computational efficiency of its MCMC sampler. Furthermore, we provide an alternative view to the EigenNet from a regularization perspective: the EigenNet has an adaptive eigenspace-based composite regularizer, which naturally generalizes the $l_{1/2}$ regularizer used by the elastic net. Experiments on synthetic and real data show that the EigenNet significantly outperforms the lasso, the elastic net, and the Bayesian lasso in terms of prediction accuracy, especially when the number of training samples is smaller than the number of variables.
Message passing with relaxed moment matching
Yuan Qi,Yandong Guo
Computer Science , 2012,
Abstract: Bayesian learning is often hampered by large computational expense. As a powerful generalization of popular belief propagation, expectation propagation (EP) efficiently approximates the exact Bayesian computation. Nevertheless, EP can be sensitive to outliers and suffer from divergence for difficult cases. To address this issue, we propose a new approximate inference approach, relaxed expectation propagation (REP). It relaxes the moment matching requirement of expectation propagation by adding a relaxation factor into the KL minimization. We penalize this relaxation with a $l_1$ penalty. As a result, when two distributions in the relaxed KL divergence are similar, the relaxation factor will be penalized to zero and, therefore, we obtain the original moment matching; In the presence of outliers, these two distributions are significantly different and the relaxation factor will be used to reduce the contribution of the outlier. Based on this penalized KL minimization, REP is robust to outliers and can greatly improve the posterior approximation quality over EP. To examine the effectiveness of REP, we apply it to Gaussian process classification, a task known to be suitable to EP. Our classification results on synthetic and UCI benchmark datasets demonstrate significant improvement of REP over EP and Power EP--in terms of algorithmic stability, estimation accuracy and predictive performance.
EigenGP: Gaussian Process Models with Adaptive Eigenfunctions
Hao Peng,Yuan Qi
Computer Science , 2014,
Abstract: Gaussian processes (GPs) provide a nonparametric representation of functions. However, classical GP inference suffers from high computational cost for big data. In this paper, we propose a new Bayesian approach, EigenGP, that learns both basis dictionary elements--eigenfunctions of a GP prior--and prior precisions in a sparse finite model. It is well known that, among all orthogonal basis functions, eigenfunctions can provide the most compact representation. Unlike other sparse Bayesian finite models where the basis function has a fixed form, our eigenfunctions live in a reproducing kernel Hilbert space as a finite linear combination of kernel functions. We learn the dictionary elements--eigenfunctions--and the prior precisions over these elements as well as all the other hyperparameters from data by maximizing the model marginal likelihood. We explore computational linear algebra to simplify the gradient computation significantly. Our experimental results demonstrate improved predictive performance of EigenGP over alternative sparse GP methods as well as relevance vector machine.
Research on Survivability of Mobile Ad-hoc Network  [PDF]
Yuan Zhou, Chunhe Xia, Haiquan Wang, Jianzhong Qi
Journal of Software Engineering and Applications (JSEA) , 2009, DOI: 10.4236/jsea.2009.21008
Abstract: In this paper, we analyze the survivability of Mobile Ad Hoc Network systemically and give a detailed description of the survivability issues related to the MANET. We begin our work with analyzing the requirements of survivability of ad hoc network, and then we classify the impacts that affect survivability into three categories: dynamic topology, faults and attacks. The impacts of these factors are analyzed individually. A simulation environment for the MANET towards survivability is designed and implemented as well. Experiments that under the requirements and the impacts we de-clared are done based on this environment.
The Landscape Structure and Heterogeneity of the West Part of Ecotone Between Agriculture and Animal Husbandry

QI Yuan,

生态学报 , 2002,
Abstract: The transitional region between cropland in semi\|humid regions and grassland (pasture) in semi\|arid regions, is an important ecological barrier, which prevents the desert from extending into the plains of eastern China. It is also a region with severe environmental problems such as desertification, vegetation degradation and soil salinization due to its natural fragility enhanced by human activities. These problems directly affect the environment of central and eastern China. In this paper we analyze the landscape structure and spatial heterogeneity in selected districts within the transitional region, and study the relationship between landscape structure, natural features and human activities. By applying remote sensing and GIS techniques, which are efficient ways of tracing long\|term inapparent environmental changes, we analyzed landscape structure and spatial heterogeneity based on a series of land\|use/land\|cover data extracted from Thematic Mapper and Spot images. Five landscape districts were chosen for analysis: 1. a forest\|shrub\|steppe district in the Helan Mountains, 2. an irrigated cropland district in the Yinchuan plains, 3. a desert\|steppe district in the Yanchi, Tongxin and Xiangshan Hills, 4. a nonirrigated farmland\|steppe district in southern Ningxia, and 5. a forest\|meadow district in the Liupan Mountains. Landscape metrics were calculated using Fragstats 3.0, and many indices are included in the soft such as patch density, edge density, landscape shape index, etc.Patch density ( PD ), edge density ( ED ), and landscape shape index ( LSI ) are lower in district 4 than in district 3 due to the loess topography of district 4, even though both districts are dominated by grassland and cropland and have similar human activities. Due to the loess topography of the forest\|meadow district of the Liupan Mountains, PD, ED and LSI are greater here than in the similar forest\|shrub\|steppe district of the Helan Mountains. In the Helan district, the landscape structure is affected by large elevation differences and less human activities, causing the contagion index to be higher than in the Liupan district. In the irrigated cropland district of the Yinchuan plains, which is greatly influenced by human activities, PD is higher than distract 1 and 3, while ED and LSI are lower than distract 4 and 5. The human activities are the main influence. Using GIS and Ningxia statistical data, we selected four natural factors (temperature, precipitation, altitude, and slope) and four human activity factors (population density, carrying capacity, irrigation channel density, and road density) to determine their influence on these five distracts. Precipitation and slope not only determine landscape structure but also the human manner in these distracts. VAGUE In addition, comparing PD and LSI with precipitation and slope along a landscape transect, the regular gradient change along the transect reflected the relation between landscape indices and na
Biocompatibility of Porous Spherical Calcium Carbonate Microparticles on Hela Cells  [PDF]
Yaran Zhang, Ping Ma, Yao Wang, Juan Du, Qi Zhou, Zhihong Zhu, Xu Yang, Junlin Yuan
World Journal of Nano Science and Engineering (WJNSE) , 2012, DOI: 10.4236/wjnse.2012.21005
Abstract: Recently there has been a wide concern on inorganic nanoparticles as drug delivery carriers. CaCO3 particles have shown promising potential for the development of carriers for drugs, but little research had been performed regarding their safe dosage for maximizing the therapeutic activity without harming biosystems. In this study, we assessed the biological safety of porous spherical CaCO3 microparticles on Hela cells. The reactive oxygen species (ROS), glutathione (GSH), carbonyl content in proteins (CCP), DNA-protein crosslinks (DPC) and cell viability were measured. Results showed that with the exposure concentration increase, ROS and CCP in Hela cells presented a significant increase but GSH contents in Hela cells and cell viability showed a significant decrease respectively compared with the control. DPC coefficient ascended, but no statistically significant changes were observed. The results indicated that porous spherical CaCO3 microparticles may induce oxidative damage to Hela cells. But compared with other nanomaterials, porous spherical CaCO3 appeared to have good biocompatibility. The results implied that porous spherical calcium carbonate microparticles could be applied as relatively safe drug vehicles, but with the caveat that the effect of high dosages should not be ignored when attempting to maximize therapeutic activity by increasing the concentration.
On Properties of Differences Polynomials about Meromorphic Functions
Jianming Qi,Jie Ding,Wenjun Yuan
Discrete Dynamics in Nature and Society , 2012, DOI: 10.1155/2012/569305
Abstract: We study the value distribution of a special class difference polynomial about finite order meromorphic function. Our methods of the proof are also different from ones in the previous results by Chen (2011), Liu and Laine (2010), and Liu and Yang (2009).

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