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.     

Effect of surfactant additives on nucleate pool boiling heat transfer of refrigerant-based nanofluid

Effect of surfactant additives on nucleate pool boiling heat transfer of refrigerant-based nanofluid was investigated experimentally. Three types of surfactants including Sodium Dodecyl Sulfate (SDS), Cetyltrimethyl Ammonium Bromide (CTAB) and Sorbitan Monooleate (Span-80) were used in the experiments. The refrigerant-based nanofluid was formed from Cu nanoparticles and refrigerant R113. The test surface is horizontal with the average roughness of 1.6 μm. Test conditions include a saturation pressure of 101.3 kPa, heat fluxes from 10 to 80 kW m⁻², surfactant concentrations from 0 to 5000 ppm (parts per million by weight), and nanoparticle concentrations from 0 to 1.0 wt.%. The experimental results indicate that the presence of surfactant enhances the nucleate pool boiling heat transfer of refrigerant-based nanofluid on most conditions, but deteriorates the nucleate pool boiling heat transfer at high surfactant concentrations. The ratio of nucleate pool boiling heat transfer coefficient of refrigerant-based nanofluid with surfactant to that without surfactant (defined as surfactant enhancement ratio, SER) are in the ranges of 1.12-1.67, 0.94-1.39, and 0.85-1.29 for SDS, CTAB and Span-80, respectively, and the values of SER are in the order of SDS > CTAB > Span-80, which is opposite to the order of surfactant density values. The SER increases with the increase of surfactant concentration and then decreases, presenting the maximum values at 2000, 500 and 1000 ppm for SDS, CTAB and Span-80, respectively. At a fixed surfactant concentration, the SER increases with the decrease of nanoparticle concentration. A nucleate pool boiling heat transfer correlation for refrigerant-based nanofluid with surfactant is proposed, and it agrees with 92% of the experimental data within a deviation of ±25%.     

Measurement and correlation of densities and viscosities of pure 1,7-dibromoheptane and 1,7-dibromoheptane in ethanol at temperatures from 288.15 to 323.15 K

The densities and viscosities of pure 1,7-dibromoheptane and 1,7-dibromoheptane in ethanol had been determined from 288.15 to 323.15 K. The relative viscosities were correlated using the Carl L. Yaws equation. The results showed that the model agreed very well with the experimental data.     

石榴子石热红外波谱特征研究

近年来短波红外高光谱技术已成功应用于含水含羟基蚀变矿物及矿床学研究,但是对于不含水不含羟基矿物探测效果不好,而热红外高光谱技术可以弥补这一技术缺陷,对于含Si_nO_k,SO₄,CO₃和PO₄等原子基团的矿物具有良好的应用前景。石榴子石是一种重要的含Si_nO_k 基团的岛状结构硅酸盐矿物,根据成分可分为钙铝榴石、钙铁榴石、镁铝榴石、铁铝榴石及锰铝榴石等不同端元,石榴子石成分对成矿温压环境及成矿中心预测具有重要的研究意义。目前针对石榴子石热红外波谱特征研究非常欠缺。故采集不同成分、不同颜色石榴子石样品16件,创新性地运用美国Agilent4300热红外波谱仪开展热红外波谱特征研究,同时运用美国Niton手持式XRF分析仪开展石榴子石同一测量位置的SiO₂,MgO,Al₂O₃,K₂O,CaO和Fe₂O₃等主量元素含量测试,并分析波谱吸收位置与主量元素含量之间的关系。结果表明石榴子石在热红外波段10~13 μm具有左高右低的双峰式诊断性波谱特征,在11.5 μm附近呈现一个主吸收谷,在12 μm附近有一个次级吸收谷,且主吸收谷及次级吸收谷波长位置与石榴子石Al₂O₃和Fe₂O₃含量具有良好的相关性,相关系数大于0.9,即波谱吸收谷的波长位置与Al₂O₃含量具有线性负相关关系,与Fe₂O₃含量具有线性正相关关系。据此研究结果,可以快速开展石榴子石矿物成分的野外鉴定,还可以快速开展矽卡岩矿床野外蚀变分带研究,进而指导找矿勘查。揭示了不同成分石榴子石矿物的热红外波谱特征,对其他架状硅酸盐、岛状硅酸盐、单链状硅酸盐、碳酸盐、硫酸盐矿物的热红外波谱特征研究具有重要的指导意义。     

Fortran codes for the correlation functions of hard sphere fluids

Our Fortran codes for hard sphere fluids and their mixtures for the correlation functions that arise from the Percus–Yevick theory and the Verlet–Weis semi-empirical correction have proven useful during a period of nearly four decades and continue to be useful. In order to make these codes even more widely available, a brief summary is presented here and listings of these codes are given in the electronically accessible Supplementary Material to this paper.     

一种基于奇异谱的语音激活检测方法

为了提高语音激活检测在低信噪比环境中的检测性能,提出了一种基于奇异谱的语音激活检测方法。首先用多窗口方法计算每一帧语音信号的相关矩阵;然后对相关矩阵进行奇异值分解;利用奇异值可以反映有用信号和噪声分布情况的特性,将每一帧语音信号经过加权处理后的最大奇异值与自适应阈值进行比较进行语音激活检测。该方法原理简单,易于硬件实现,通过实验仿真表明,在低信噪比环境下,和基于对数能量方法相比,本文方法也能够很好的区分语音段和非语音段,有良好的检测性能。     

Robust canonical correlations: A comparative study

Summary  Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods are discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study compares the performance of the different estimators under several kinds of sampling schemes. Robustness is studied as well by breakdown plots.     

Correlation dimension: A pivotal statistic for non-constrained realizations of composite hypotheses in surrogate data analysis

Currently surrogate data analysis can be used to determine if data is consistent with various linear systems, or something else (a nonlinear system). In this paper we propose an extension of these methods in an attempt to make more specific classifications within the class of nonlinear systems.

In the method of surrogate data one estimates the probability distribution of values of a test statistic for a set of experimental data under the assumption that the data is consistent with a given hypothesis. If the probability distribution of the test statistic is different for different dynamical systems consistent with the hypothesis, one must ensure that the surrogate generation technique generates surrogate data that are a good approximation to the data. This is often achieved with a careful choice of surrogate generation method and for noise driven linear surrogates such methods are commonly used.

This paper argues that, in many cases (particularly for nonlinear hypotheses), it is easier to select a test statistic for which the probability distribution of test statistic values is the same for all systems consistent with the hypothesis. For most linear hypotheses one can use a reliable estimator of a dynamic invariant of the underlying class of processes. For more complex, nonlinear hypothesis it requires suitable restatement (or cautious statement) of the hypothesis. Using such statistics one can build nonlinear models of the data and apply the methods of surrogate data to determine if the data is consistent with a simulation from a broad class of models. These ideas are illustrated with estimates of probability distribution functions for correlation dimension estimates of experimental and artificial data, and linear and nonlinear hypotheses.     

Determination of haptoglobin in human serum by high-performance gel-permeation chromatography

Summary A high-performance gel-permeation chromatographic (GPC) method is described for the determination of serum haptoglobin (Hp), based on the estimation of the haptoglobin-hemoglobin (Hp−Hb) complex. Hemoglobin (Hb) is added to the serum and the resulting Hp−Hb complex is separated by GPC and detected at 415 nm. The Hp−Hb complex separated chromatographically from serum migrated electrophoretically with the globulin fraction. It was found to be stable over a period of one week at 4°C. The total analysis time for a serum sample is approximately 20 min. The minimum detection limit is 30mg/L. Relative standard deviation values were below 1% (peak area). No interferences from bilirubin or from turbidity of samples were observed. The results of the GPC analysis correlate well with those obtained by nephelometric assay (r=0.996).     

Eigenvalue density of cross-correlations in Sri Lankan financial market

We apply the universal properties with Gaussian orthogonal ensemble (GOE) of random matrices namely spectral properties, distribution of eigenvalues, eigenvalue spacing predicted by random matrix theory (RMT) to compare cross-correlation matrix estimators from emerging market data. The daily stock prices of the Sri Lankan All share price index and Milanka price index from August 2004 to March 2005 were analyzed. Most eigenvalues in the spectrum of the cross-correlation matrix of stock price changes agree with the universal predictions of RMT. We find that the cross-correlation matrix satisfies the universal properties of the GOE of real symmetric random matrices. The eigen distribution follows the RMT predictions in the bulk but there are some deviations at the large eigenvalues. The nearest-neighbor spacing and the next nearest-neighbor spacing of the eigenvalues were examined and found that they follow the universality of GOE. RMT with deterministic correlations found that each eigenvalue from deterministic correlations is observed at values, which are repelled from the bulk distribution.