Browsing by Issue Date, starting with "2016-12-21"

Now showing 1 - 20 of 15751

Lateral amorphous selenium metal-insulator-semiconductor-insulator-metal photodetectors using ultrathin dielectric blocking layers for dark current suppression
(2016-12-21)
Chang, Cheng-Yi
;
Pan, Fu-Ming
;
Lin, Jian-Siang
;
Yu, Tung-Yuan
;
Li, Yi-Ming
We fabricated amorphous selenium (a-Se) photodetectors with a lateral metal-insulator-semiconductor-insulator-metal (MISIM) device structure. Thermal aluminum oxide, plasma-enhanced chemical vapor deposited silicon nitride, and thermal atomic layer deposited (ALD) aluminum oxide and hafnium oxide (ALD-HfO2) were used as the electron and hole blocking layers of the MISIM photodetectors for dark current suppression. A reduction in the dark current by three orders of magnitude can be achieved at electric fields between 10 and 30 V/mu m. The effective dark current suppression is primarily ascribed to electric field lowering in the dielectric layers as a result of charge trapping in deep levels. Photogenerated carriers in the a-Se layer can be transported across the blocking layers to the Al electrodes via Fowler-Nordheim tunneling because a high electric field develops in the ultrathin dielectric layers under illumination. Since the a-Se MISIM photodetectors have a very low dark current without significant degradation in the photoresponse, the signal contrast is greatly improved. The MISIM photodetector with the ALD-HfO2 blocking layer has an optimal signal contrast more than 500 times the contrast of the photodetector without a blocking layer at 15 V/mu m. Published by AIP Publishing.
"Embedded Emitters": Direct bandgap Ge nanodots within SiO2
(2016-12-21)
Kuo, M. H.
;
Chou, S. K.
;
Pan, Y. W.
;
Lin, S. D.
;
George, T.
Microdisk-arrays of vertically stacked 30-70nm Ge nanodots embedded within SiO2 were fabricated using thermal oxidation of Si0.75Ge0.25 abacus-shaped pillars and followed by post-annealing in oxygen-deficient conditions. The Ge nanodots are subjected to increasing quantum-confinement and tensile-strain by reducing dot size. We show that considerable quantum-confinement and tensile-strain can be generated within 30 nm Ge nanodots embedded in SiO2, as evidenced by large Raman red shifts for the Ge-Ge phonon lines in comparison to that for bulk Ge. These large quantum-confinement and tensile-strain facilitate direct-bandgap photoluminescence experimentally observed for the Ge nanodots, and are consistent with the strain-split photoluminescence transitions to the light-hole (LH) and heavy-hole (HH) valence bands at 0.83 eV and 0.88 eV, respectively. Time-resolved photoluminescence measurements conducted from 10-100K show temperature-insensitive carrier lifetimes of 2.7 ns and 5 ns for the HH and LH valence-band transitions, respectively, providing additional strong evidence of direct bandgap photoluminescence for tensile-strained Ge nanodots. Published by AIP Publishing.
InGaN-Based Light-Emitting Diodes Grown on a Micro/Nanoscale Hybrid Patterned Sapphire Substrate
(2016-12-21)
Ke, Wen-Cheng
;
Lee, Fang-Wei
;
Chiang, Chih-Yung
;
Liang, Zhong-Yi
;
Chen, Wei-Kuo
A hybrid patterned sapphire substrate (hybrid-PSS) was prepared using an anodic aluminum oxide etching mask to transfer nanopatterns onto a conventional patterned sapphire substrate with microscale patterns (bare-PSS). The threading dislocation (TD) suppression of light-emitting diodes (LEDs) grown on a hybrid-PSS (HP-LED) exhibits a smaller reverse leakage current compared with that of LEDs grown on a bare-PSS (BP-LED). The strain-free GaN buffer layer and fully strained InGaN active layer were evidenced by cross-sectional Raman spectra and reciprocal space mapping of the X-ray diffraction intensity for both samples. The calculated piezoelectric fields for both samples are close, implying that the quantum-confined Stark effect was not a dominant mechanism influencing the electroluminescence (EL) peak wavelength under a high injection current. The bandgap shrinkage effect of the InGaN well layer was considered to explain the large red-shifted EL peak wavelength under high injection currents. The estimated LED chip temperatures rise from room temperature to 150 degrees C and 75 degrees C for BP-LED and HP-LED, respectively, at a 600-mA injection current. This smaller temperature rise of the LED chip is attributed to the increased contact area between the sapphire and the LED structural layer because of the embedded nanopattern. Although the chip generates more heat at high injection currents, the accumulated heat can be removed to outside the chip effectively. The high diffuse reflection (DR) rate of hybrid-PSS increases the escape probability of photons, resulting in an increase in the viewing angle of the LEDs from 130 degrees to 145 degrees. The efficiency droop was reduced from 46% to 35%, effects which can be attributed to the elimination of TDs and strain relaxation by embedded nanopatterns. In addition, the light output power of HP-LED at 360-mA injection currents exhibits a similar to 22.3% enhancement, demonstrating that hybrid-PSSs are beneficial to apply in high-power LEDs.
Silica-Supported Cu Nanoparticle Catalysts for Alkyne Semihydrogenation: Effect of Ligands on Rates and Selectivity
(2016-12-21)
Fedorov, Alexey
;
Liu, Hsueh-Ju
;
Lo, Hung-Kun
;
Coperet, Christophe
;
應用化學系
Narrowly dispersed, silica-supported Cu nano particles (ca. 2 nm) prepared via surface organometallic chemistry from a mesityl complex [Cu(5)Mes(5)] are highly active for the hydrogenation of a broad range of alkynes. High-throughput experimentation allows for identifying the optimal ligand and reaction conditions to turn these supported Cu nanoparticles into highly chemo- and stereoselective catalysts for the preparation of Z-olefins (overall, 23 examples). For instance, PCy3-modified Cu nanoparticles semihydrogenate 1-phenyl-l-propyne to cis-beta-methylstyrene (20 bar H-2, 40 degrees C) with turnover number and turnover frequency of ca. 540 and 1.9 min(-1), respectively, and with 94% selectivity at full conversion.
SCMBYK: prediction and characterization of bacterial tyrosine-kinases based on propensity scores of dipeptides
(2016-12-22)
Vasylenko, Tamara
;
Liou, Yi-Fan
;
Chiou, Po-Chin
;
Chu, Hsiao-Wei
;
Lai, Yung-Sung
Background: Bacterial tyrosine-kinases (BY-kinases), which play an important role in numerous cellular processes, are characterized as a separate class of enzymes and share no structural similarity with their eukaryotic counterparts. However, in silico methods for predicting BY-kinases have not been developed yet. Since these enzymes are involved in key regulatory processes, and are promising targets for anti-bacterial drug design, it is desirable to develop a simple and easily interpretable predictor to gain new insights into bacterial tyrosine phosphorylation. This study proposes a novel SCMBYK method for predicting and characterizing BY-kinases. Results: A dataset consisting of 797 BY-kinases and 783 non-BY-kinases was established to design the SCMBYK predictor, which achieved training and test accuracies of 97.55 and 96.73%, respectively. Furthermore, the leaveone-phylum-out method was used to predict specific bacterial phyla hosts of target sequences, gaining 97.39% average test accuracy. After analyzing SCMBYK-derived propensity scores, four characteristics of BY-kinases were determined: 1) BY-kinases tend to be composed of a-helices; 2) the amino-acid content of extracellular regions of BY-kinases is expected to be dominated by residues such as Val, Ile, Phe and Tyr; 3) BY-kinases structurally resemble nuclear proteins; 4) different domains play different roles in triggering BY-kinase activity. Conclusions: The SCMBYK predictor is an effective method for identification of possible BY-kinases. Furthermore, it can be used as a part of a novel drug repurposing method, which recognizes putative BY-kinases and matches them to approved drugs. Among other results, our analysis revealed that azathioprine could suppress the virulence of M. tuberculosis, and thus be considered as a potential antibiotic for tuberculosis treatment.
PARRoT - a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms
(2016-12-22)
Gan, Ruei-Chi
;
Chen, Ting-Wen
;
Wu, Timothy H.
;
Huang, Po-Jung
;
Lee, Chi-Ching
Background: Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Results: Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. Conclusions: In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw.
SCMBYK: prediction and characterization of bacterial tyrosine-kinases based on propensity scores of dipeptides
(2016-12-22)
Vasylenko, Tamara
;
Liou, Yi-Fan
;
Chiou, Po-Chin
;
Chu, Hsiao-Wei
;
Lai, Yung-Sung
Background: Bacterial tyrosine-kinases (BY-kinases), which play an important role in numerous cellular processes, are characterized as a separate class of enzymes and share no structural similarity with their eukaryotic counterparts. However, in silico methods for predicting BY-kinases have not been developed yet. Since these enzymes are involved in key regulatory processes, and are promising targets for anti-bacterial drug design, it is desirable to develop a simple and easily interpretable predictor to gain new insights into bacterial tyrosine phosphorylation. This study proposes a novel SCMBYK method for predicting and characterizing BY-kinases. Results: A dataset consisting of 797 BY-kinases and 783 non-BY-kinases was established to design the SCMBYK predictor, which achieved training and test accuracies of 97.55 and 96.73%, respectively. Furthermore, the leaveone-phylum-out method was used to predict specific bacterial phyla hosts of target sequences, gaining 97.39% average test accuracy. After analyzing SCMBYK-derived propensity scores, four characteristics of BY-kinases were determined: 1) BY-kinases tend to be composed of a-helices; 2) the amino-acid content of extracellular regions of BY-kinases is expected to be dominated by residues such as Val, Ile, Phe and Tyr; 3) BY-kinases structurally resemble nuclear proteins; 4) different domains play different roles in triggering BY-kinase activity. Conclusions: The SCMBYK predictor is an effective method for identification of possible BY-kinases. Furthermore, it can be used as a part of a novel drug repurposing method, which recognizes putative BY-kinases and matches them to approved drugs. Among other results, our analysis revealed that azathioprine could suppress the virulence of M. tuberculosis, and thus be considered as a potential antibiotic for tuberculosis treatment.
OPTICAL SHEET, METHOD FOR MANUFACTURING THE SAME, LIGHT EMITTING DIODES MODULE AND DISPLAY USING THE SAME
(2016-12-22)
Chien-Chung LIN
;
Hao-Chung KUO
;
Kuo-Ju CHEN
;
Hau-Vei HAN
An optical sheet is disclosed in the present invention and comprises a substrate, a reflective layer and a plurality of pixels. The reflective layer is disposed on the substrate. The pixels are composed of several quantum dot fluorescent powders respectively and arrayed on the reflective layer. In addition, a method for manufacturing the above optical sheet, a light emitting diodes module and a display using the above optical sheet are also disclosed in the present invention.
ROUTING GATEWAY SELECTING METHOD, CONTROLLER AND VEHICLES NETWORK SYSTEM
(2016-12-22)
Jen-Shun Yang
;
Jyh-Cheng Chen
;
Pei-Chia Hsu
;
Wei-Chen Sim
The disclosure proposes a routing gateway selecting method, a controller and a vehicles network system. The method is adapted to a controller disposed on a fleet of vehicles configured by a plurality of vehicles, and the controller is configured to select a routing gateway among a plurality of gateways for routing an access point (AP). The routing gateway selecting method includes: predicting a bandwidth of each of the gateways; calculating a transmission cost of each of the gateways based on a load condition and the bandwidth of each of the gateways and a hop count between each of the gateways and the AP; and selecting the routing gateway among the gateways for routing the AP according to the transmission cost of each of the gateways.
PARRoT - a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms
(2016-12-22)
Gan, Ruei-Chi
;
Chen, Ting-Wen
;
Wu, Timothy H.
;
Huang, Po-Jung
;
Lee, Chi-Ching
Background: Next-generation sequencing promises the de novo genomic and transcriptomic analysis of samples of interests. However, there are only a few organisms having reference genomic sequences and even fewer having well-defined or curated annotations. For transcriptome studies focusing on organisms lacking proper reference genomes, the common strategy is de novo assembly followed by functional annotation. However, things become even more complicated when multiple transcriptomes are compared. Results: Here, we propose a new analysis strategy and quantification methods for quantifying expression level which not only generate a virtual reference from sequencing data, but also provide comparisons between transcriptomes. First, all reads from the transcriptome datasets are pooled together for de novo assembly. The assembled contigs are searched against NCBI NR databases to find potential homolog sequences. Based on the searched result, a set of virtual transcripts are generated and served as a reference transcriptome. By using the same reference, normalized quantification values including RC (read counts), eRPKM (estimated RPKM) and eTPM (estimated TPM) can be obtained that are comparable across transcriptome datasets. In order to demonstrate the feasibility of our strategy, we implement it in the web service PARRoT. PARRoT stands for Pipeline for Analyzing RNA Reads of Transcriptomes. It analyzes gene expression profiles for two transcriptome sequencing datasets. For better understanding of the biological meaning from the comparison among transcriptomes, PARRoT further provides linkage between these virtual transcripts and their potential function through showing best hits in SwissProt, NR database, assigning GO terms. Our demo datasets showed that PARRoT can analyze two paired-end transcriptomic datasets of approximately 100 million reads within just three hours. Conclusions: In this study, we proposed and implemented a strategy to analyze transcriptomes from non-reference organisms which offers the opportunity to quantify and compare transcriptome profiles through a homolog based virtual transcriptome reference. By using the homolog based reference, our strategy effectively avoids the problems that may cause from inconsistencies among transcriptomes. This strategy will shed lights on the field of comparative genomics for non-model organism. We have implemented PARRoT as a web service which is freely available at http://parrot.cgu.edu.tw.
Estimating survival time of patients with glioblastoma multiforme and characterization of the identified microRNA signatures
(2016-12-22)
Sathipati, Srinivasulu Yerukala
;
Huang, Hui-Ling
;
Ho, Shinn-Ying
;
生物科技學系
;
生物資訊及系統生物研究所
Background: Though glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy in adults, clinical treatment still faces challenges due to poor prognoses and tumor relapses. Recently, microRNAs ( miRNAs) have been extensively used with the aim of developing accurate molecular therapies, because of their emerging role in the regulation of cancer-related genes. This work aims to identify the miRNA signatures related to survival of GBM patients for developing molecular therapies. Results: This work proposes a support vector regression (SVR)-based estimator, called SVR-GBM, to estimate the survival time in patients with GBM using their miRNA expression profiles. SVR-GBM identified 24 out of 470 miRNAs that were significantly associated with survival of GBM patients. SVR-GBM had a mean absolute error of 0.63 years and a correlation coefficient of 0.76 between the real and predicted survival time. The 10 top-ranked miRNAs according to prediction contribution are as follows: hsa-miR-222, hsa-miR-345, hsa-miR-587, hsa-miR-526a, hsa-miR-335, hsa-miR-122, hsa-miR-24, hsa-miR-433, hsa-miR-574 and hsa-miR-320. Biological analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the identified miRNAs revealed their influence in GBM cancer. Conclusion: The proposed SVR-GBM using an optimal feature selection algorithm and an optimized SVR to identify the 24 miRNA signatures associated with survival of GBM patients. These miRNA signatures are helpful to uncover the individual role of miRNAs in GBM prognosis and develop miRNA-based therapies.
A hydrophobic spine stabilizes a surface-exposed alpha-helix according to analysis of the solvent-accessible surface area
(2016-12-22)
Liou, Yi-Fan
;
Huang, Hui-Ling
;
Ho, Shinn-Ying
;
生物科技學系
;
生物資訊及系統生物研究所
Background: Most of hydrophilic and hydrophobic residues are thought to be exposed and buried in proteins, respectively. In contrast to the majority of the existing studies on protein folding characteristics using protein structures, in this study, our aim was to design predictors for estimating relative solvent accessibility (RSA) of amino acid residues to discover protein folding characteristics from sequences. Methods: The proposed 20 real-value RSA predictors were designed on the basis of the support vector regression method with a set of informative physicochemical properties (PCPs) obtained by means of an optimal feature selection algorithm. Then, molecular dynamics simulations were performed for validating the knowledge discovered by analysis of the selected PCPs. Results: The RSA predictors had the mean absolute error of 14.11% and a correlation coefficient of 0.69, better than the existing predictors. The hydrophilic-residue predictors preferred PCPs of buried amino acid residues to PCPs of exposed ones as prediction features. A hydrophobic spine composed of exposed hydrophobic residues of an a-helix was discovered by analyzing the PCPs of RSA predictors corresponding to hydrophobic residues. For example, the results of a molecular dynamics simulation of wild-type sequences and their mutants showed that proteins 1MOF and 2WRP_H16I (Protein Data Bank IDs), which have a perfectly hydrophobic spine, have more stable structures than 1MOF_I54D and 2WRP do (which do not have a perfectly hydrophobic spine). Conclusions: We identified informative PCPs to design high-performance RSA predictors and to analyze these PCPs for identification of novel protein folding characteristics. A hydrophobic spine in a protein can help to stabilize exposed alpha-helices.
A hydrophobic spine stabilizes a surface-exposed alpha-helix according to analysis of the solvent-accessible surface area
(2016-12-22)
Liou, Yi-Fan
;
Huang, Hui-Ling
;
Ho, Shinn-Ying
;
生物科技學系
;
生物資訊及系統生物研究所
Background: Most of hydrophilic and hydrophobic residues are thought to be exposed and buried in proteins, respectively. In contrast to the majority of the existing studies on protein folding characteristics using protein structures, in this study, our aim was to design predictors for estimating relative solvent accessibility (RSA) of amino acid residues to discover protein folding characteristics from sequences. Methods: The proposed 20 real-value RSA predictors were designed on the basis of the support vector regression method with a set of informative physicochemical properties (PCPs) obtained by means of an optimal feature selection algorithm. Then, molecular dynamics simulations were performed for validating the knowledge discovered by analysis of the selected PCPs. Results: The RSA predictors had the mean absolute error of 14.11% and a correlation coefficient of 0.69, better than the existing predictors. The hydrophilic-residue predictors preferred PCPs of buried amino acid residues to PCPs of exposed ones as prediction features. A hydrophobic spine composed of exposed hydrophobic residues of an a-helix was discovered by analyzing the PCPs of RSA predictors corresponding to hydrophobic residues. For example, the results of a molecular dynamics simulation of wild-type sequences and their mutants showed that proteins 1MOF and 2WRP_H16I (Protein Data Bank IDs), which have a perfectly hydrophobic spine, have more stable structures than 1MOF_I54D and 2WRP do (which do not have a perfectly hydrophobic spine). Conclusions: We identified informative PCPs to design high-performance RSA predictors and to analyze these PCPs for identification of novel protein folding characteristics. A hydrophobic spine in a protein can help to stabilize exposed alpha-helices.
Estimating survival time of patients with glioblastoma multiforme and characterization of the identified microRNA signatures
(2016-12-22)
Sathipati, Srinivasulu Yerukala
;
Huang, Hui-Ling
;
Ho, Shinn-Ying
;
生物科技學系
;
生物資訊及系統生物研究所
Background: Though glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy in adults, clinical treatment still faces challenges due to poor prognoses and tumor relapses. Recently, microRNAs ( miRNAs) have been extensively used with the aim of developing accurate molecular therapies, because of their emerging role in the regulation of cancer-related genes. This work aims to identify the miRNA signatures related to survival of GBM patients for developing molecular therapies. Results: This work proposes a support vector regression (SVR)-based estimator, called SVR-GBM, to estimate the survival time in patients with GBM using their miRNA expression profiles. SVR-GBM identified 24 out of 470 miRNAs that were significantly associated with survival of GBM patients. SVR-GBM had a mean absolute error of 0.63 years and a correlation coefficient of 0.76 between the real and predicted survival time. The 10 top-ranked miRNAs according to prediction contribution are as follows: hsa-miR-222, hsa-miR-345, hsa-miR-587, hsa-miR-526a, hsa-miR-335, hsa-miR-122, hsa-miR-24, hsa-miR-433, hsa-miR-574 and hsa-miR-320. Biological analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the identified miRNAs revealed their influence in GBM cancer. Conclusion: The proposed SVR-GBM using an optimal feature selection algorithm and an optimized SVR to identify the 24 miRNA signatures associated with survival of GBM patients. These miRNA signatures are helpful to uncover the individual role of miRNAs in GBM prognosis and develop miRNA-based therapies.
Setting Foot in Asymmetric Wetting Environments: Fabrication of Mushroom-Like Anisotropic Polymer Nanoparticles
(2016-12-22)
Chi, Mu-Huan
;
Fang, Zhi-Xuan
;
Ko, Hao-Wen
;
Chang, Chun-Wei
;
Chen, Jiun-Tai
To achieve multifunctional-materials using a single kind of ingredient.or particle, it is desired to develop simple methods to prepare anisotropic nanoparticles, such as mushroom-like nanoparticles, which can be applied to many fields. Here, we investigate the wetting of polymer nano spheres On the open ends of the nanopores of anodic alumina oxide templates, which offer asymmetric wetting environments, to fabricate mushroom-like anisotropic polymer nanoparticles with controllable morphologies. These nano structures have special dynamic behaviors in aqueous solutions. In addition, we prepare mushroom-like Janus nanoparticles by altering the fabrication processes. This work not only demonstrates a novel method to prepare anisotropic polymer nanoparticles but also provides a detailed understanding of the wetting behaviors under asymmetric environments.
體壇問題叢生　改革露曙光
(2016-12-25)
何家沂
;
Department of Communication and Technology
;
傳播與科技學系
闡述台灣目前的體育發展狀況、疑慮及近日送審一讀的《國民體育法》並期待未來的改革之路。
可移動機器人　運輸新選擇
(2016-12-25)
陳奕璇
;
Department of Communication and Technology
;
傳播與科技學系
介紹運輸機器人及其與社會現況之連結。
游喬茵　用攝影改變世界
(2016-12-25)
林孟盈
;
Department of Communication and Technology
;
傳播與科技學系
介紹擁有燦爛笑容的專職攝影師游喬茵，以及她與攝影的羈絆。
耶誕節前放光明　ERG衛星
(2016-12-25)
陳昶安
;
Department of Communication and Technology
;
傳播與科技學系
為探索宇宙間未知的高能輻射區，台日攜手共造的ERG衛星已於本周二晚間七點順利升空，點亮了太空學界伯利恆的夜晚。
總編輯的話
(2016-12-25)
凃易暄
;
Department of Communication and Technology
;
傳播與科技學系
本期喀報為第257期，以「無人機應用　競速賽新市場」為頭題，闡述無人機作為現今科技的一大新趨勢，不僅是新科技的應用，帶來的周邊產業商機更是無限。