Investigation of degradation caused by charge trapping at etching-stop layer under AC gate-bias stress for InGaZnO thin film transistors

A great amount of literatures has been focusing on bias-induced instability issues including threshold voltage shift (ΔVt ) and subthreshold swing (S.S) degradations [1]. However, in practical TFT operation circuits, very limited knowledge could be applied since operation modes are mostly applied with alternative current (AC). Based on these backgrounds, in this work, Indium-Gallium-Zinc-Oxide Thin Film Transistors (IGZO TFTs) are applied with AC PBS degradations. Compared with previous work, this work observed a structure dependent degradation. An etch-stop structure IGZO TFT observed a serious threshold voltage shift after AC stress but shown great stability after direct current (DC) stress. The device structure and transfer characteristic curves are demonstrated in Figure 1(a) and (b) respectively. From results of DC PBS/NBS, a favorable stability indicating a great quality of gate insulator. Therefore, the positive threshold voltage shift is believed to be origin from electron trapping at the etching stop layer (ESL), since ESL possesses a relatively poor quality compared to the gate insulator. The charge trapping at etching stop layer could be confirmed by results of asymmetric source/drain metal under AC stress, illustrated in Figure 1(c). Please click Additional Files below to see the full abstract

A Study on Factors Affecting the Abstention of Drug Abuse in Private Rehabilitation Institutes in Taiwan — Operation Dawn Taiwan as an Example

The purpose of this study is to understand problems of the abstention of drug abuse in Taiwan. Comparing the model of Operation Dawn Taiwan with that of the government’s official rehabilitation institutes, this paper aims to identify advantages and disadvantages of the model in private institutes. The opinions of all inmates and tutors in Operation Dawn Taiwan, the biggest private rehabilitation institute in Taiwan, were collected via questionnaires. This study’s findings show that factors of relapse for a drug abuser after leaving rehabilitation institutes include: 1) the enticement from drug fellows; 2) incapability to resist the allure of drugs; 3) unemployment or hindrances to job-finding; 4) psychological depression; and 5) his/her desire for drugs. Inmates and tutors hold the same opinion on all models of the abstention of drug abuse. Specific suggestions of the abstention of drug abuse in Taiwan will also be discussed in this paper. Finally, inmates consider that career planning has significant positive correlations with abstention

Simple method for the generation of multiple homogeneous field volumes inside the bore of superconducting magnets

International audienceStandard Magnetic Resonance magnets produce a single homogeneous field volume, where the analysis is performed. Nonetheless, several modern applications could benefit from the generation of multiple homogeneous field volumes along the axis and inside the bore of the magnet. In this communication, we propose a straightforward method using a combination of ring structures of permanent magnets in order to cancel the gradient of the stray field in a series of distinct volumes. These concepts were demonstrated numerically on an experimentally measured magnetic field profile. We discuss advantages and limitations of our method and present the key steps required for an experimental validation

Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task.

Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions' temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions' neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed

Pseudozyma spp. and Barnettozyma spp. effectively kill cancer cells in vitro

AbstractCancer is the overall leading cause of death in developed countries and also worldwide, and being able to exploit an effective anticancer drug is the aim of all cancer scientists. However, many of the synthetic drugs produced so far usually cause serious side effects, which reduces their therapeutic efficacy. Discovering new drugs or auxiliary therapies derived from natural products might thus provide a novel opportunity for cancer therapy. A recent study reported that some lethal toxins can maintain their activity after being injected into mice. We therefore used two Pseudozyma spp. and three Barnettozyma spp. to examine whether these killer yeasts can preserve their lethal effect on cancer cells under the physical environment (optimum pH, temperature and osmolality, supporting a living cell accomplishes to proliferate, metabolize, differentiate and survive). Our preliminary results showed that both Barnettozyma spp. and Pseudozyma spp. have stronger cytotoxicity against HepG2 than Chang’s liver cells. According to the results of two-dimensional difference gel electrophoresis (2D-DIGE), a total of 115 and 27 proteins differentially expressed by 1.5-fold or more were observed for HepG2 and Chang’s liver cells, respectively. Furthermore, we explored the mechanism involved in the effect of the lethal yeast filtrates on liver cancer cells using 2D-DIGE and mass spectrometry

Predicting protein-protein interactions in unbalanced data using the primary structure of proteins

<p>Abstract</p> <p>Background</p> <p>Elucidating protein-protein interactions (PPIs) is essential to constructing protein interaction networks and facilitating our understanding of the general principles of biological systems. Previous studies have revealed that interacting protein pairs can be predicted by their primary structure. Most of these approaches have achieved satisfactory performance on datasets comprising equal number of interacting and non-interacting protein pairs. However, this ratio is highly unbalanced in nature, and these techniques have not been comprehensively evaluated with respect to the effect of the large number of non-interacting pairs in realistic datasets. Moreover, since highly unbalanced distributions usually lead to large datasets, more efficient predictors are desired when handling such challenging tasks.</p> <p>Results</p> <p>This study presents a method for PPI prediction based only on sequence information, which contributes in three aspects. First, we propose a probability-based mechanism for transforming protein sequences into feature vectors. Second, the proposed predictor is designed with an efficient classification algorithm, where the efficiency is essential for handling highly unbalanced datasets. Third, the proposed PPI predictor is assessed with several unbalanced datasets with different positive-to-negative ratios (from 1:1 to 1:15). This analysis provides solid evidence that the degree of dataset imbalance is important to PPI predictors.</p> <p>Conclusions</p> <p>Dealing with data imbalance is a key issue in PPI prediction since there are far fewer interacting protein pairs than non-interacting ones. This article provides a comprehensive study on this issue and develops a practical tool that achieves both good prediction performance and efficiency using only protein sequence information.</p

Effect of different a-InGaZnO TFTs channel thickness upon self-heating stress

In this work, Indium-Galium-Zinc-Oxide Thin Film Transistors (IGZO TFTs) with different channel thickness has been compared after self-heating stress (SHS). In previous literatures, self-heating of TFTs has been widely discussed and Joule Heat caused during driving TFTs has been compared with different channel length and width [1]. However, different channel thickness hasn’t been investigated. Although TFTs with a larger channel thickness possess a greater drain current, a less degradation is observed when comparing with small channel thickness structures, demonstrated in Figure 1(a). The ΔVt shift in the transfer characteristics are well described by the stretched-exponential equation. The Eτ value, which is the average effective barrier height for electron transport, is extracted in Figure (b). Results has shown that in the thick IGZO TFTs, the value is almost twice of that in the thin IGZO TFTs. From COMSOL simulations demonstrated in Figure 1(c), in could be noticed that different channel thickness effects the electrical field locating at the gate insulator. Therefore, a model is proposed to explain the degradation difference, illustrated in Figure (4). Please click Additional Files below to see the full abstract

PDA: Pooled DNA analyzer

BACKGROUND: Association mapping using abundant single nucleotide polymorphisms is a powerful tool for identifying disease susceptibility genes for complex traits and exploring possible genetic diversity. Genotyping large numbers of SNPs individually is performed routinely but is cost prohibitive for large-scale genetic studies. DNA pooling is a reliable and cost-saving alternative genotyping method. However, no software has been developed for complete pooled-DNA analyses, including data standardization, allele frequency estimation, and single/multipoint DNA pooling association tests. This motivated the development of the software, 'PDA' (Pooled DNA Analyzer), to analyze pooled DNA data. RESULTS: We develop the software, PDA, for the analysis of pooled-DNA data. PDA is originally implemented with the MATLAB(® )language, but it can also be executed on a Windows system without installing the MATLAB(®). PDA provides estimates of the coefficient of preferential amplification and allele frequency. PDA considers an extended single-point association test, which can compare allele frequencies between two DNA pools constructed under different experimental conditions. Moreover, PDA also provides novel chromosome-wide multipoint association tests based on p-value combinations and a sliding-window concept. This new multipoint testing procedure overcomes a computational bottleneck of conventional haplotype-oriented multipoint methods in DNA pooling analyses and can handle data sets having a large pool size and/or large numbers of polymorphic markers. All of the PDA functions are illustrated in the four bona fide examples. CONCLUSION: PDA is simple to operate and does not require that users have a strong statistical background. The software is available at