Improved conversion efficiency of Ag2S quantum dot-sensitized solar cells based on TiO2 nanotubes with a ZnO recombination barrier layer

We improve the conversion efficiency of Ag2S quantum dot (QD)-sensitized TiO2 nanotube-array electrodes by chemically depositing ZnO recombination barrier layer on plain TiO2 nanotube-array electrodes. The optical properties, structural properties, compositional analysis, and photoelectrochemistry properties of prepared electrodes have been investigated. It is found that for the prepared electrodes, with increasing the cycles of Ag2S deposition, the photocurrent density and the conversion efficiency increase. In addition, as compared to the Ag2S QD-sensitized TiO2 nanotube-array electrode without the ZnO layers, the conversion efficiency of the electrode with the ZnO layers increases significantly due to the formation of efficient recombination layer between the TiO2 nanotube array and electrolyte

2-D Equivalent finite element model of quadratic linear electromagnetic actuator

The purpose of this paper is to present a 2-D equivalent finite element model of a quadratic linear electromagnetic actuator that can save space and power as it does not employ an energy conversion system. A 2-D model, while being fairly accurate, is preferable to a 3-D finite element analysis for the design and analysis of a quadratic linear electromagnetic actuator as it requires significantly lower computing resources and results in faster calculations. We calculate the effective coil length for the equivalent 2-D finite element model and validate the accuracy of this model with experimental data

Polarized Raman scattering of epitaxial PbTiO3 thin films with coexisting c- and a-domains

Effects of the orientation of ferroelectric domains on the characteristics of polarized Raman spectra were studied using an epitaxially grown PbTiO3 thin film in which the c-axis oriented domains coexist with the a-axis oriented domains on MgO (001). To obtain polarized spectra for both two distinctive c and a domains, we have employed scattering configurations in which the relevant phonon wave vector, k, is perpendicular to the c axis of the tetragonal unit cell. Compared with the mode frequencies of single-crystal PbTiO3, a softening of the E(TO) phonons was evident for both c and a domains, suggesting the presence of a strong tensile film stress. In addition to this, we observed a splitting of the degenerate "silent" mode into two distinctive B-1 and E modes in an epitaxially grown film on MgO (001). (C) 2002 American Institute of Physics

Statistical identification of gene association by CID in application of constructing ER regulatory network

<p>Abstract</p> <p>Background</p> <p>A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating <it>in silico </it>inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).</p> <p>Results</p> <p>The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's <it>t</it>-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.</p> <p>Conclusion</p> <p>CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.</p> <p>Availability</p> <p>the implementation of CID in R codes can be freely downloaded from <url>http://homepage.ntu.edu.tw/~lyliu/BC/</url>.</p

Genome-wide analysis of DNA methylation patterns in horse

Background: DNA methylation is an epigenetic regulatory mechanism that plays an essential role in mediating biological processes and determining phenotypic plasticity in organisms. Although the horse reference genome and whole transcriptome data are publically available the global DNA methylation data are yet to be known. Results: We report the first genome-wide DNA methylation characteristics data from skeletal muscle, heart, lung, and cerebrum tissues of thoroughbred (TH) and Jeju (JH) horses, an indigenous Korea breed, respectively by methyl-DNA immunoprecipitation sequencing. The analysis of the DNA methylation patterns indicated that the average methylation density was the lowest in the promoter region, while the density in the coding DNA sequence region was the highest. Among repeat elements, a relatively high density of methylation was observed in long interspersed nuclear elements compared to short interspersed nuclear elements or long terminal repeat elements. We also successfully identified differential methylated regions through a comparative analysis of corresponding tissues from TH and JH, indicating that the gene body regions showed a high methylation density. Conclusions: We provide report the first DNA methylation landscape and differentially methylated genomic regions (DMRs) of thoroughbred and Jeju horses, providing comprehensive DMRs maps of the DNA methylome. These data are invaluable resource to better understanding of epigenetics in the horse providing information for the further biological function analyses.open1

Functional characterization of cellulases identified from the cow rumen fungus Neocallimastix patriciarum W5 by transcriptomic and secretomic analyses

<p>Abstract</p> <p>Background</p> <p><it>Neocallimastix patriciarum</it> is one of the common anaerobic fungi in the digestive tracts of ruminants that can actively digest cellulosic materials, and its cellulases have great potential for hydrolyzing cellulosic feedstocks. Due to the difficulty in culture and lack of a genome database, it is not easy to gain a global understanding of the glycosyl hydrolases (<it>GHs</it>) produced by this anaerobic fungus.</p> <p>Results</p> <p>We have developed an efficient platform that uses a combination of transcriptomic and proteomic approaches to <it>N. patriciarum </it>to accelerate gene identification, enzyme classification and application in rice straw degradation. By conducting complementary studies of transcriptome (Roche 454 GS and Illumina GA IIx) and secretome (ESI-Trap LC-MS/MS), we identified 219 putative <it>GH </it>contigs and classified them into 25 <it>GH</it> families. The secretome analysis identified four major enzymes involved in rice straw degradation: β-glucosidase, endo-1,4-β-xylanase, xylanase B and Cel48A exoglucanase. From the sequences of assembled contigs, we cloned 19 putative cellulase genes, including the <it>GH1</it>, <it>GH3</it>, <it>GH5</it>, <it>GH6</it>, <it>GH9</it>, <it>GH18</it>, <it>GH43 </it>and <it>GH48 </it>gene families, which were highly expressed in <it>N. patriciarum </it>cultures grown on different feedstocks.</p> <p>Conclusions</p> <p>These <it>GH </it>genes were expressed in Pichia pastoris and/or Saccharomyces cerevisiae for functional characterization. At least five novel cellulases displayed cellulytic activity for glucose production. One β-glucosidase (W5-16143) and one exocellulase (W5-CAT26) showed strong activities and could potentially be developed into commercial enzymes.</p

Synthesis and Photocatalytic Activity of Anatase TiO2 Nanoparticles-coated Carbon Nanotubes

A simple and straightforward approach to prepare TiO2-coated carbon nanotubes (CNTs) is presented. Anatase TiO2 nanoparticles (NPs) with the average size ~8 nm were coated on CNTs from peroxo titanic acid (PTA) precursor even at low temperature of 100 °C. We demonstrate the effects of CNTs/TiO2 molar ratio on the adsorption capability and photocatalytic efficiency under UV–visible irradiation. The samples showed not only good optical absorption in visible range, but also great adsorption capacity for methyl orange (MO) dye molecules. These properties facilitated the great enhancement of photocatalytic activity of TiO2 NPs-coated CNTs photocatalysts. The TiO2 NPs-coated CNTs exhibited 2.45 times higher photocatalytic activity for MO degradation than that of pure TiO2