An efficient optimized independent component analysis method based on genetic algorithm

Three simulation experiments are designed to evaluate and compare the performance of three common independent component analysis implementation algorithms – FastICA, JADE, and extended-Infomax. Experiment results show that the above three algorithms can’t separate the mixtures of super-Gaussian and sub-Gaussian precisely, and FastICA fails in recovering weak source signals from mixed signals. In this case an independent component analysis algorithm, which applies genetic algorithm to minimize the difference between joint probability and product of marginal probabilities of separated signals, is proposed. The computation procedure, especially the fitness evaluation when signals are in discrete form, is discussed in detail. The validity of the proposed algorithm is proved by simulation tests. Moreover, the results indicate that the proposed algorithm outperforms the above three common algorithms significantly. Finally the proposed algorithm is applied to separate the mixture of rolling bearing sound signal and electromotor signal, and the results are satisfied

Bis[4-(4-pyridyl)pyridinium] (4-carboxy­pyridine-2,6-dicarboxyl­ato-κ3 O 2,N,O 6)(pyridine-2,4,6-tricarboxyl­ato-κ3 O 2,N,O 6)ferrate(III) trihydrate

In the title salt, (C10H9N2)2[Fe(C8H2NO6)(C8H3NO6)]·3H2O, the FeIII atom is O,N,O′-chelated by dianionic and trianionic ligands in a slightly distorted octa­hedral coordination geometry. The cations and ferrate anions are linked into a layered structure; the layers are connected through the uncoordinated water mol­ecules into a hydrogen-bonded three-dimensional supra­molecular structure. One of the uncoordinated water molecules is disordered around an inversion centre and was refined with half-occupancy for each position

Thorium-doping induced superconductivity up to 56 K in Gd1-xThxFeAsO

Following the discovery of superconductivity in an iron-based arsenide LaO1-xFxFeAs with a superconducting transition temperature (Tc) of 26 K[1], Tc was pushed up surprisingly to above 40 K by either applying pressure[2] or replacing La with Sm[3], Ce[4], Nd[5] and Pr[6]. The maximum Tc has climbed to 55 K, observed in SmO1-xFxFeAs[7, 8] and SmFeAsO1-x[9]. The value of Tc was found to increase with decreasing lattice parameters in LnFeAsO1-xFx (Ln stands for the lanthanide elements) at an apparently optimal doping level. However, the F- doping in GdFeAsO is particularly difficult[10,11] due to the lattice mismatch between the Gd2O2 layers and Fe2As2 layers. Here we report observation of superconductivity with Tc as high as 56 K by the Th4+ substitution for Gd3+ in GdFeAsO. The incorporation of relatively large Th4+ ions relaxes the lattice mismatch, hence induces the high temperature superconductivity.Comment: 4 pages, 3 figure

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness

BACKGROUND: Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins. RESULTS: Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs). CONCLUSION: The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies

A comparative study on communication structures of Chinese journals in the social sciences

We argue that the communication structures in the Chinese social sciences have not yet been sufficiently reformed. Citation patterns among Chinese domestic journals in three subject areas -- political science and marxism, library and information science, and economics -- are compared with their counterparts internationally. Like their colleagues in the natural and life sciences, Chinese scholars in the social sciences provide fewer references to journal publications than their international counterparts; like their international colleagues, social scientists provide fewer references than natural sciences. The resulting citation networks, therefore, are sparse. Nevertheless, the citation structures clearly suggest that the Chinese social sciences are far less specialized in terms of disciplinary delineations than their international counterparts. Marxism studies are more established than political science in China. In terms of the impact of the Chinese political system on academic fields, disciplines closely related to the political system are less specialized than those weakly related. In the discussion section, we explore reasons that may cause the current stagnation and provide policy recommendations

iTRAQ Quantitative Analysis of Multidrug Resistance Mechanisms in Human Gastric Cancer Cells

Multidrug resistance (MDR) is a major obstacle towards a successful treatment of gastric cancer. However, the mechanisms of MDR are intricate and have not been fully understood. To elucidate the molecular mechanisms of MDR in gastric cancer, we employed the proteomic approach of isobaric tags for relative and absolute quantification (iTRAQ), followed by LC-MS/MS, using the vincristine-resistant SGC7901/VCR cell line and its parental SGC7901 cell line as a model. In total, 820 unique proteins were identified and 91 proteins showed to be differentially expressed in SGC7901/VCR compared with SGC7901. Several differentially expressed proteins were further validated by western blot analysis. Furthermore, the association of MVP, one of the highly expressed proteins in SGC7901/VCR, with MDR was verified. Our study is the first application of iTRAQ technology for MDR mechanisms analysis in gastric cancer, and many of the differentially expressed proteins identified have not been linked to MDR in gastric cancer before, which showed the value of this technology in identifying differentially expressed proteins in cancer