基于光学小波微分预处理的联合变换相关目标识别

提出了一种基于光学小波变换微分预处理的光电混合联合变换相关系统,该系统利用同一光路可实时实现对输入图象的小波变换微分预处理和联合变换相关识别.实验结果表明:该系统能得到很尖锐的互相关峰,可显著提高联合变换相关器的识别能力.     

3（或）4—取代苯甲亚氨酸酯中取代基效应的^13C—NMR研究

本文测定了三个3(或4)-取代苯甲亚氨酸乙酯(1)和八个N-氰甲基-3(或4)-取代苯甲亚氨酸乙酯(2)的~(13)C-NMR谱。归属了1 和2和各碳化学位移。求得了的取代基化学位移(substituent Chemical Shift,SCS)。碳-13化学位移与单取代苯的取代基化学位移(SCS)的相关分析表明:4-取代苯甲亚氨酸酯1 b～g和2b～e中,除C_(2,6)外,其他各芳碳的化学位移值与加和规则基本相符;3-取代苯甲亚氨酸酯1h～j和2f～h中,除C_1外,其他各芳碳的化学位移值与加和规则基本相符。另外,本文还进行了碳-13化学位移与σ_(I)/σ_(R)~O和F/M的双参数相关分析。     

Analysis of patient self-assessment visual analogue scales

The present paper describes an example of practical analysis of data from an application of visual analogue scales. Potentially useful and simple methods for analysing visual analogue scales are described for effective handling of complex data when the desire is to compare two or more groups of patients. Visual analogue scales were used to assess subjective tolerability in the International Prospective Primary Prevention Study in Hypertension, a large scale clinical trial. The methods are illustrated on the IPPPSH data.     

可可西里-金沙江地震带震级频度关系及其参数的相关性分析

本文通过可可西里-金沙江地震带震级频度关系的确定及其参数b值与a值、ν值(地震年平均发生率)和Mmax(最大震级a/b)之间的相关性分析, 以说明地震危险性概率分析中的地震活动性参数ν值与b值也应有某种相关性。当地震带未来一定时期内地震活动震级上限Muz和b值被确定后, 未来地震活动的ν值的取值范围似将受到一定的限制。如假设可可西里-金沙江地震带的Muz为8级, b值为0.73后, 相应的ν值若取13.943, 可能偏小。     

Determination and correlation of the solubility of tricin in water and ethanol mixtures

The solubility of tricin in water and ethanol mixtures was measured over the temperature range of (288.15 to 328.15) K. The concentrations of tricin in the aqueous mixtures were assayed by the ultraviolet spectrophotometric method. The experimental solubility data indicated that the solubility of tricin increases with an increase in temperature and an enrichment in ethanol content. The two models, including the modified Apelblat equation and λh equation were used to correlate the experimental solubility data. The calculated solubility of tricin shows good agreement with the experimental results. Additionally, the estimation of thermodynamic properties including the activity coefficients, dissolution enthalpy, and entropy were obtained from the experimental data. Within the studied temperature range the dissolution process of tricin is endothermic, and the driving force is the entropy.     

ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations

Most variable selection techniques for high-dimensional models are designed to be used in settings, where observations are independent and completely observed. At the same time, there is a rich literature on approaches to estimation of low-dimensional parameters in the presence of correlation, missingness, measurement error, selection bias, and other characteristics of real data. In this article, we present ThrEEBoost (Thresholded EEBoost), a general-purpose variable selection technique which can accommodate such problem characteristics by replacing the gradient of the loss by an estimating function. ThrEEBoost generalizes the previously proposed EEBoost algorithm (Wolfson 2011 Wolfson, J. (2011), “EEBoost: A General Method for Prediction and Variable Selection Based on Estimating Equations,” Journal of the American Statistical Association, 106, 296–305.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) by allowing the number of regression coefficients updated at each step to be controlled by a thresholding parameter. Different thresholding parameter values yield different variable selection paths, greatly diversifying the set of models that can be explored; the optimal degree of thresholding can be chosen by cross-validation. ThrEEBoost was evaluated using simulation studies to assess the effects of different threshold values on prediction error, sensitivity, specificity, and the number of iterations to identify minimum prediction error under both sparse and nonsparse true models with correlated continuous outcomes. We show that when the true model is sparse, ThrEEBoost achieves similar prediction error to EEBoost while requiring fewer iterations to locate the set of coefficients yielding the minimum error. When the true model is less sparse, ThrEEBoost has lower prediction error than EEBoost and also finds the point yielding the minimum error more quickly. The technique is illustrated by applying it to the problem of identifying predictors of weight change in a longitudinal nutrition study. Supplementary materials are available online.     

Solubility of β-carotene in ethanol- and triolein-modified CO2

Modification of an experimental device and methodology improved speed and reproducibility of measurement of solubility of β-carotene in pure and modified SuperCritical (SC) CO₂ at (313 to 333) K. Solubilities of β-carotene in pure CO₂ at (17 to 34) MPa ranged (0.17 to 1.06) μmol/mol and agreed with values reported in literature. The solubility of β-carotene in CO₂ modified with (1.2 to 1.6) % mol ethanol increased by a factor of 1.7 to 3.0 as compared to its solubility in pure CO₂ under equivalent conditions. The concentration of triolein in equilibrated ternary (CO₂ + β-carotene + triolein) mixtures having excess triolein reached values (0.01 to 0.39) mmol/mol corresponding to its solubility in pure SC CO₂ under equivalent conditions. Under these conditions, the solubility of β-carotene in triolein-modified CO₂ increased by a factor of up to 4.0 in relation with its solubility in pure CO₂ at comparable system temperature and pressure, reaching an uppermost value of 3.3 μmol/mol at 333 K and 32 MPa. Unlike in the case of ethanol, where enhancements in solubility where relatively independent on system conditions, solubility enhancements using triolein as co-solvent increased markedly with system pressure, being larger than using (1.2 to 1.6) % mol ethanol at about (24 to 28) MPa, depending on system temperature. The increase in the solubility β-carotene in SC CO₂ as a result of using ethanol or triolein as co-solvent apparently does not depend on the increase in density associated with the dissolution of the co-solvent in CO₂. Enhancements may be due to an increase in the polarizability of SC CO₂, which possibly growths markedly as triolein dissolves in it when the system pressure becomes higher.     

油纸复合介质中水分子扩散行为的分子动力学模拟

对不同温度下水分子在油纸复合介质中的扩散行为进行了分子动力学模拟研究. 通过分析水分子与纤维素形成的氢键发现, 油中的水分子在模拟过程中会逐渐扩散到纤维素内并与之形成氢键, 而纤维素内的水分子则与纤维素形成氢键后被束缚于纤维素中. 通过分析水分子的扩散系数发现, 由于油和纤维素的极性不同, 使得水分子在油和纤维素两种单介质中的扩散行为有较大差别, 而在复合介质中的扩散系数受水分子在油和纤维素中的比例影响较大, 两者表现出很强的相关性. 水分子和两介质的相互作用与两介质的极性也存在很大的关系, 且不同温度下水分子与两介质的相互作用能和水分子在油和纤维素中的比例也表现出了较强的相关性. 不同温度下水分子的不同分布弱化了温度对扩散系数的影响.     

icoshift: An effective tool for the alignment of chromatographic data

The Interval Correlation Optimised Shifting algorithm (icoshift) has recently been introduced for the alignment of nuclear magnetic resonance spectra. The method is based on an insertion/deletion model to shift intervals of spectra/chromatograms and relies on an efficient Fast Fourier Transform based computation core that allows the alignment of large data sets in a few seconds on a standard personal computer. The potential of this programme for the alignment of chromatographic data is outlined with focus on the model used for the correction function. The efficacy of the algorithm is demonstrated on a chromatographic data set with 45 chromatograms of 64,000 data points. Computation time is significantly reduced compared to the Correlation Optimised Warping (COW) algorithm, which is widely used for the alignment of chromatographic signals. Moreover, icoshift proved to perform better than COW in terms of quality of the alignment (viz. of simplicity and peak factor), but without the need for computationally expensive optimisations of the warping meta-parameters required by COW. Principal component analysis (PCA) is used to show how a significant reduction on data complexity was achieved, improving the ability to highlight chemical differences amongst the samples.