Electrical instability of amorphous indium-gallium-zinc oxide thin film transistors under monochromatic light illumination

The electrical instability behaviors of a positive-gate-bias-stressed amorphous indium-gallium-zinc oxide (a-IGZO) thin film transistor(TFT) are studied under monochromatic light illumination. It is found that as the wavelength of incident light reduces from 750 nm to 450 nm, the threshold voltage of the illuminated TFT shows a continuous negative shift, which is caused by photo-excitation of trapped electrons at the channel/dielectric interface. Meanwhile, an increase of the sub-threshold swing (SS) is observed when the illumination wavelength is below 625 nm (∼2.0 eV). The SS degradation is accompanied by a simultaneous increase of the field effect mobility (μFE) of the TFT, which then decreases at even shorter wavelength beyond 540 nm (∼2.3 eV). The variation of SS and μFE is explained by a physical model based on generation of singly ionized oxygen vacancies (Vo⁺) and double ionized oxygen vacancies (Vo²⁺) within the a-IGZO active layer by high energy photons, which would form trap states near the mid-gap and the conduction band edge, respectively.This work was supported by the State Key Program for Basic Research of China under Grant Nos. 2010CB327504, 2011CB922100, 2011CB301900; the National Natural Science Foundation of China under Grant Nos. 60825401, 60936004, 11104130, BK2011556, and BK2011050

Mononuclear piano-stool iron 2-ethynylbenzo[b]thiophene complex: crystal structure and reversible oxidation studied by spectro-electrochemical and DFT methods

A mononuclear iron complex with 2-ethynylbenzo[b]thiophene C-coordinated to the (η5 -Cp*)(η2 -dppe)Fe ( Cp* = pentamethylcyclopentadienyl, dppe = 1,2-diphenylphosphinoethane) framework (1) was successfully prepared and characterized by 1H NMR, elemental analysis and single crystal X-ray diffraction. The redox behavior of complex 1 was investigated by voltammetric methods and anodic spectroelectrochemistry in the UV-vis-NIR-IR region and compared with reference complexes including 2-ferrocenylbenzo[b]thiophene (2) and the 2-ethynylpyridine derivative of 1. The spin density distribution along the linear molecular backbone in stable 1 + was analyzed by DFT (BLYP35) and TDDFT calculations of a truncated model complex. The combined experimental and theoretical results have revealed an important role of the ethynylene linker in determining the redox properties of this family of complexes and a sizable participation the 2-ethynylbenzo[b]thiophene framework in the largely iron-based anodic electron transfe

Genome-Wide Association Study in East Asians Identifies Novel Susceptibility Loci for Breast Cancer

Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. We aimed to discover novel genetic susceptibility loci for breast cancer. We conducted a four-stage genome-wide association study (GWAS) in 19,091 cases and 20,606 controls of East-Asian descent including Chinese, Korean, and Japanese women. After analyzing 690,947 SNPs in 2,918 cases and 2,324 controls, we evaluated 5,365 SNPs for replication in 3,972 cases and 3,852 controls. Ninety-four SNPs were further evaluated in 5,203 cases and 5,138 controls, and finally the top 22 SNPs were investigated in up to 17,423 additional subjects (7,489 cases and 9,934 controls). SNP rs9485372, near the TGF-β activated kinase (TAB2) gene in chromosome 6q25.1, showed a consistent association with breast cancer risk across all four stages, with a P-value of 3.8×10−12 in the combined analysis of all samples. Adjusted odds ratios (95% confidence intervals) were 0.89 (0.85–0.94) and 0.80 (0.75–0.86) for the A/G and A/A genotypes, respectively, compared with the genotype G/G. SNP rs9383951 (P = 1.9×10−6 from the combined analysis of all samples), located in intron 5 of the ESR1 gene, and SNP rs7107217 (P = 4.6×10−7), located at 11q24.3, also showed a consistent association in each of the four stages. This study provides strong evidence for a novel breast cancer susceptibility locus represented by rs9485372, near the TAB2 gene (6q25.1), and identifies two possible susceptibility loci located in the ESR1 gene and 11q24.3, respectively

A Collaborative Region Detection and Grading Framework for Forest Fire Smoke Using Weakly Supervised Fine Segmentation and Lightweight Faster-RCNN

Forest fires are serious disasters that affect countries all over the world. With the progress of image processing, numerous image-based surveillance systems for fires have been installed in forests. The rapid and accurate detection and grading of fire smoke can provide useful information, which helps humans to quickly control and reduce forest losses. Currently, convolutional neural networks (CNN) have yielded excellent performance in image recognition. Previous studies mostly paid attention to CNN-based image classification for fire detection. However, the research of CNN-based region detection and grading of fire is extremely scarce due to a challenging task which locates and segments fire regions using image-level annotations instead of inaccessible pixel-level labels. This paper presents a novel collaborative region detection and grading framework for fire smoke using a weakly supervised fine segmentation and a lightweight Faster R-CNN. The multi-task framework can simultaneously implement the early-stage alarm, region detection, classification, and grading of fire smoke. To provide an accurate segmentation on image-level, we propose the weakly supervised fine segmentation method, which consists of a segmentation network and a decision network. We aggregate image-level information, instead of expensive pixel-level labels, from all training images into the segmentation network, which simultaneously locates and segments fire smoke regions. To train the segmentation network using only image-level annotations, we propose a two-stage weakly supervised learning strategy, in which a novel weakly supervised loss is proposed to roughly detect the region of fire smoke, and a new region-refining segmentation algorithm is further used to accurately identify this region. The decision network incorporating a residual spatial attention module is utilized to predict the category of forest fire smoke. To reduce the complexity of the Faster R-CNN, we first introduced a knowledge distillation technique to compress the structure of this model. To grade forest fire smoke, we used a 3-input/1-output fuzzy system to evaluate the severity level. We evaluated the proposed approach using a developed fire smoke dataset, which included five different scenes varying by the fire smoke level. The proposed method exhibited competitive performance compared to state-of-the-art methods

An Efficient Algorithm for the Joint Replenishment Problem with Quantity Discounts, Minimum Order Quantity and Transport Capacity Constraints

The joint replenishment problem has been extensively studied and the joint replenishment strategy has been adopted by a large variety of retailers in recent years. However, the joint replenishment problem under minimum order quantity and other constraints does not receive sufficient attention. This paper analyzes a retailing supply chain involving a supplier that provides quantity discount schedules and limits the order quantity. The order quantity constraints include minimum order requirements for each item and as to the total quantity; additionally, the latter cannot exceed the transport capacity constraint. These are common constraints in the retail industry today and create greater complexity and difficulty in the retailer’s decision-making. To analyze the problem, an integer nonlinear programming model is set up to maximize retailers’ profit with all practical constraints. A two-layer efficient algorithm named the Marginal and Cumulative Profit-Based Algorithm (MCPB) is then proposed to find whether to order and the optimal order quantity for each item. The results of computational experiments show that the proposed algorithm can find near-optimal solutions to the problem efficiently and is a reference for retailers to solve practical joint replenishment problems

Infrared Image Deblurring Based on Lp-Pseudo-Norm and High-Order Overlapping Group Sparsity Regularization

A traditional total variation (TV) model for infrared image deblurring amid salt-and-pepper noise produces a severe staircase effect. A TV model with low-order overlapping group sparsity (LOGS) suppresses this effect; however, it considers only the prior information of the low-order gradient of the image. This study proposes an image-deblurring model (Lp_HOGS) based on the LOGS model to mine the high-order prior information of an infrared (IR) image amid salt-and-pepper noise. An Lp-pseudo-norm was used to model the salt-and-pepper noise and obtain a more accurate noise model. Simultaneously, the second-order total variation regular term with overlapping group sparsity was introduced into the proposed model to further mine the high-order prior information of the image and preserve the additional image details. The proposed model uses the alternating direction method of multipliers to solve the problem and obtains the optimal solution of the overall model by solving the optimal solution of several simple decoupled subproblems. Experimental results show that the model has better subjective and objective performance than Lp_LOGS and other advanced models, especially when eliminating motion blur

Highly Efficient In Vitro Site-Specific Recombination System Based on Streptomyces Phage φBT1 Integrase▿ †

The Streptomyces phage φBT1 encodes a site-specific integrase of the large serine recombinase subfamily. In this report, the enzymatic activity of the φBT1 integrase was characterized in vitro. We showed that this integrase has efficient integration activity with substrate DNAs containing attB and attP sites, independent of DNA supercoiling or cofactors. Both intra- and intermolecular recombinations proceed with rapid kinetics. The recombination is highly specific, and no reactions are observed between pairs of sites including attB and attL, attB and attR, attP and attL, or attP and attR or between two identical att sequences; however, a low but significant frequency of excision recombination between attL and attR is observed in the presence of the φBT1 integrase alone. In addition, for efficient integration, the minimal sizes of attB and attP are 36 bp and 48 bp, respectively. This site-specific recombination system is efficient and simple to use; thus, it could have applications for the manipulation of DNA in vitro

The crystal structure of catena–poly[aqua(1-naphthoato-κ 2 O,O′)-(μ-1-naphthoato-κ 4 O:O,O′:O′)lead(II)], C22H16O5Pb

C22H16O5Pb, orthorhombic, P212121 (no. 19), a = 7.3395(8) Å, b = 10.7768(11) Å, c = 23.034(3) Å, V = 1821.9(3) Å3, Z = 4, R gt(F) = 0.0327, wR ref(F 2) = 0.0735, T = 296(2) K