Empirical analysis of self-adaptive differential evolution

Differential evolution (DE) is generally considered as a reliable, accurate, robust and fast optimization technique. DE has been successfully applied to solve a wide range of numerical optimization problems. However, the user is required to set the values of the control parameters of DE for each problem. Such parameter tuning is a time consuming task. In this paper, a self-adaptive DE (SDE) algorithm which eliminates the need for manual tuning of control parameters is empirically analyzed. The performance of SDE is investigated and compared with other well-known approaches. The experiments conducted show that SDE generally outperform other DE algorithms in all the benchmark functions. Moreover, the performance of SDE using the ring neighborhood topology is investigated.     

Porous glass as a support for chemically bonded stationary phases for HPLC

Summary Two different types of porous glass (PG) were submitted to a thermal treatment in a temperature range from 620°C–700°C for 2 to 100 h. The materials thereby obtained have been characterized by static Secondary Ion Mass Spectrometry (SIMS). Special attention was paid to the change of the boron surface concentration. In addition we studied the specific surface area (S_BET) dependence on the thermal treatment parameters, such as heating time and heating temperature. Selected PG materials have been modified with organosilanes and characterized prior to their use as packings in RP-HPLC.Dedicated to B. B.'s parents on their 60th birthday     

Reference gene stability in peripheral blood mononuclear cells determined by qPCR and NanoString

Quantitative real-time PCR (qPCR) is commonly used for gene expression analyses with defined documentation guidelines to compare published results. To minimize the impact of variances from qPCR performance, sample handling and processing reference genes are used. Their selection process cannot be completely aligned due to variations in experimental conditions. Furthermore, the named sources of error are also present when determining the stability of the reference genes themselves. Even software applications that are used to identify the best reference genes rarely coincide on their rankings and can be misleading under certain conditions. In previous experiments, peripheral blood mononuclear cells (PBMC) were analyzed to identify the most stable reference gene(s). Twelve of the 13 investigated genes showed sample type specific differences in the expression. Direct mRNA measurement was performed in the form of a NanoString analysis, a multiplexed absolute quantification method. The external validation showed a high concordance of the reference gene expression levels. However, it identified the same sample type specific expression pattern for only some of the tested reference genes. By comparing various combinations of reference genes with both methods we are able to suggest a set of well-performing reference genes. Figure

We here compare the expression of reference genes for qPCR and NanoString data and determine the value of the latter method as a bias-free mRNA quantification method     

On q-analogues and stability theorems

In this survey recent results about q-analogues of some classical theorems in extremal set theory are collected. They are related to determining the chromatic number of the q-analogues of Kneser graphs. For the proof one needs results on the number of 0-secant subspaces of point sets, so in the second part of the paper recent results on the structure of point sets having few 0-secant subspaces are discussed. Our attention is focussed on the planar case, where various stability results are given.     

Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity

The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain significantly smaller numbers of informative variables than the existing SVR-PPRV, UVE-GA-PLS and UVE-iPLS methods without loss of prediction ability. Contrary to UVE-GA-PLS and UVE-iPLS, there is no variability in the number of retained variables in each PPRV(R) method. Renewed variable ranking, after deletion of a variable, followed by remodelling, combined with the possibility to decrease the PLS model complexity, is beneficial. A preferred PPRVR-CAM method is proposed.     

SL2-modules of small homological dimension

Let V _n be the SL₂-module of binary forms of degree n and let V = V_n1 ???V_np V = {V_{{n_1}}} \oplus \cdots \oplus {V_{{n_p}}} . We consider the algebra R = O(V)^{\textS\textL₂} R = \mathcal{O}{(V)^{{\text{S}}{{\text{L}}_2}}} of polynomial functions on V invariant under the action of SL₂. The measure of the intricacy of these algebras is the length of their chains of syzygies, called homological dimension hd R. Popov gave in 1983 a classification of the cases in which hd R ≤ 10 for a single binary form (p = 1) or hd R ≤ 3 for a system of two or more binary forms (p > 1). We extend Popov’s result and determine for p = 1 the cases with hd R ≤ 100, and for p > 1 those with hd R ≤ 15. In these cases we give a set of homogeneous parameters and a set of generators for the algebra R.     

Local structure of porous silicon studied by means of X-ray emission spectroscopy

2,3 X-ray emission spectra of porous silicon (P-Si) and of spark-processed silicon (sp-Si). Both types of Si-structure display strong photoluminescence in the visible range of the spectrum. Porous samples were prepared by anodization of n^-- and p⁺-Si-wafers. Whereas for the P-Si processed from p⁺-Si the presence of some amorphous silicon is detected, the X-ray emission spectra of porous Si prepared from n^--Si display a higher content of SiO₂. For spark-processed Si the Si L_2,3 X-ray emission spectra reveal a much stronger degree of oxidation which extends to depths larger than 10000 Å. Furthermore, the chemical state of silicon atoms of sp-Si measured at the center of the processed area is close to that of silicon dioxide, and it has an influence on the photoluminescence energy. Specifically, green photoluminescent sp-Si shows a higher degree of oxidation than the blue luminescent specimen. However, the depth of oxidation consistently decreases in areas with weak or no PL. Possible origins of the observed photoluminescence are discussed. Accepted: 6 March 1997     

Effects of brain polarization on reaction times and pinch force in chronic stroke

Background  

Previous studies showed that anodal transcranial DC stimulation (tDCS) applied to the primary motor cortex of the affected hemisphere (M1_{affected hemisphere}) after subcortical stroke transiently improves performance of complex tasks that mimic activities of daily living (ADL). It is not known if relatively simpler motor tasks are similarly affected. Here we tested the effects of tDCS on pinch force (PF) and simple reaction time (RT) tasks in patients with chronic stroke in a double-blind cross-over Sham-controlled experimental design.     

A Consistent BGK-Type Model for Gas Mixtures

We introduce a relaxation collision operator for a mixture of gases which satisfies several fundamental properties. Different BGK type collision operators for gas mixtures have been introduced earlier but none of them could satisfy all the basic physical properties: positivity, correct exchange coefficients, entropy inequality, indifferentiability principle. We show that all those properties are verified for our model, and we derive its Navier–Stokes limit by a Chapman–Enskog expansion.