Mixed strategy solutions forN-person quadratic games

Mixed strategy -equilibrium points are given forN-person games with cost functions consisting of quadratic, bilinear, and linear terms and strategy spaces consisting of closed balls in Hilbert spaces. The results are applied to linear-quadratic differential games with no information and quadratic integral constraints on the control functions.This work was supported by a Commonwealth of Australia, Postgraduate Research Award.     

Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

ABSTRACT

Existing data on structures and biological activities are limited and distributed unevenly across distinct molecular targets and chemical compounds. The question arises if these data represent an unbiased sample of the general population of chemical-biological interactions. To answer this question, we analyzed ChEMBL data for 87,583 molecules tested against 919 protein targets using supervised and unsupervised approaches. Hierarchical clustering of the Murcko frameworks generated using Chemistry Development Toolkit showed that the available data form a big diffuse cloud without apparent structure. In contrast hereto, PASS-based classifiers allowed prediction whether the compound had been tested against the particular molecular target, despite whether it was active or not. Thus, one may conclude that the selection of chemical compounds for testing against specific targets is biased, probably due to the influence of prior knowledge. We assessed the possibility to improve (Q)SAR predictions using this fact: PASS prediction of the interaction with the particular target for compounds predicted as tested against the target has significantly higher accuracy than for those predicted as untested (average ROC AUC are about 0.87 and 0.75, respectively). Thus, considering the existing bias in the data of the training set may increase the performance of virtual screening.     

Spectrophotometric resolution of ternary mixtures of pseudoephedrine hydrochloride, dextromethorphan hydrobromide, and sodium benzoate in syrups using wavelength selection by net analyte signals calculated with hybrid linear analysis

Hybrid linear analysis (HLA), as a recent factor-based multivariate calibration technique, was applied for the spectrophotometric determination of ternary mixtures of pseudoephedrine hydrochloride (PSU), dextromethorphan hydrobromide (DXT), and sodium benzoate (BNZ). The utilized HLA was assisted by a wavelength selection procedure which was based on the calculation of the net analyte signal (NAS) regression plot in any considered wavelengths window for each test sample, in addition to a moving window strategy for searching the region with maximum linearity of NAS regression plot (minimum error indicator (EI)). HLA was applied because it was simpler to adapt to the NAS regression plot methodology, and also used less factors than partial least squares (PLS). An orthogonal array design was applied for formation of calibration and prediction sets in the concentration ranges 0-7500 μmol L⁻¹ for PSU, 0-300 μmol L⁻¹ for DXT, and 0-1400 μmol L⁻¹ for BNZ. The method had the ability to select wavelength regions that minimize the effect of non-linearity of the spectral data, in addition to that of non-modeled interferences. The application of the selected wavelength regions improved the obtained relative standard error of predictions for PSU, DXT, and BNZ, respectively, from 5.24, 8.67, and 5.48% to 2.19, 5.21, and 3.62% (using lower number of factors). To check the ability of the proposed method in selection of linear regions of spectra, a test for detecting non-linear regions of spectral data in multivariate spectroscopic assays was also described. Additives in the commercial syrup samples did not interfere with their determinations. The method was successfully applied for the determination of pseudoephedrine HCl, dextromethorphan HBr, and sodium benzoate in cough suppressant syrup samples.     

Packings and stationary phases for biopolymer separations by HPLC

Summary Packings and stationary phases applied to high resolution separations of proteins, enzymes, and nucleic acids must satisfy a series of distinct criteria that are different from those usually required by HPLC of low molecular weight non-biologically active analytes. These requirements have been met through substantial improvements in classical gel media together with novel developments in silica supports, and have led to a family of products with tailor-made and reproducible properties. Supports consisting of cross-linked organic gels, and inorganic materials (mostly silicas) are now available with graduated particle sizes, pore sizes, porosities and surface areas as well as non-porous beads. A whole range of stationary phases, such as reversed phase, hydrophobic interaction, ion exchanger and affinity packings, were designed for application as chemical sensors for biopolymer recognition in adsorptive chromatography. The phase systems are operated in the gradient mode, giving high resolution and high peak capacities. In addition, aqueous liquid-liquid partitioning systems have been developed for the fractionation of proteins and nucleic acids. Size exclusion media complete the set of HPLC variants enabling a discrimination of proteins according to their size and shape in an isocratic elution mode. Basically, protein purification and isolation is a multistage process where-by the HPLC variants are combined in a logistic sequence, utilizing the different selectivities of the phase systems and thus maximising resolution, speed and throughput.     

一种新型极性脲丙基-C30固定相的制备和性能评价

以3-脲丙基三甲氧基硅烷为偶联剂，制备了一种新型极性脲丙基-C30（TPU-C30）反相色谱固定相。采用扫描电子显微镜、元素分析、红外光谱和热分析等对该固定相进行表征。结果表明，TPU-C30固定相已成功制备，连续制备3次固定相，其元素含量的相对偏差均小于5%，说明该合成工艺重复性良好。以不同极性、位置异构、碱性化合物为溶质探针，以传统的C18色谱柱与C30色谱柱为参比，对制备的固定相的色谱性能进行了研究。研究结果表明，TPU-C30固定相具有不同于传统C18柱、C30柱的选择性和更优的择形性，明显改善了碱性物质的峰形，其具有广阔的应用空间。     

探地雷达回波信号的特征提取和分类

探地雷达的回波信号具有非平稳特征.为实现非平稳信号的检测和分类,采用了二进小波变换、主分量分析与Fisher线性判别分析和前馈多层感知器分类器分别对探地雷达回波信号进行小波分解、去相关与特征选择和分类.实验结果表明,该算法具有很好的分类效果.     

瑞利衰落信道采用组合发射机SC/接收机 MRC的MQAM性能分析

日益增长的无线业务需求要求提高衰落信道上无线通信的频谱利用率.本文研究一种使用组合发射机SC/接收机MRC(SC/MRC)的MQAM方案,推导其在平坦瑞利衰落信道上的误符号率,分析无线信道时变特性对系统性能的影响.数值计算结果表明该组合空间分集方案可以通过调整发射天线和接收天线的数目来获得比传统接收机分集接收更大的分集增益.     

Brownian distance correlation-directed search: A fast feature selection technique for alternate test

Machine-learning indirect test relies on powerful statistical algorithms to build prediction models that relate cheap measurements to costly performance metrics. Though many works in the past have been focused on proposing different models or on ways to improve the reliability of the results, it appears that the main bottleneck of the approach is the definition of an information-rich input space. Finding the appropriate measurements that are both cheap and meaningful is a task that has not yet been automated. In this framework, feature selection is a necessary tool to explore possible candidates. In this paper a hybrid method is proposed that lay between filtering and wrapper-based methods, trying to strike the right balance between accuracy and speed for the particular case of Alternate Test.     

Random frog: An efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification

The identification of disease-relevant genes represents a challenge in microarray-based disease diagnosis where the sample size is often limited. Among established methods, reversible jump Markov Chain Monte Carlo (RJMCMC) methods have proven to be quite promising for variable selection. However, the design and application of an RJMCMC algorithm requires, for example, special criteria for prior distributions. Also, the simulation from joint posterior distributions of models is computationally extensive, and may even be mathematically intractable. These disadvantages may limit the applications of RJMCMC algorithms. Therefore, the development of algorithms that possess the advantages of RJMCMC methods and are also efficient and easy to follow for selecting disease-associated genes is required. Here we report a RJMCMC-like method, called random frog that possesses the advantages of RJMCMC methods and is much easier to implement. Using the colon and the estrogen gene expression datasets, we show that random frog is effective in identifying discriminating genes. The top 2 ranked genes for colon and estrogen are Z50753, U00968, and Y10871_at, Z22536_at, respectively. (The source codes with GNU General Public License Version 2.0 are freely available to non-commercial users at: http://code.google.com/p/randomfrog/.)