Ab Initio Investigation of Charge Trapping Across the Crystalline- Si -Amorphous- Si O2 Interface

Accurate microscopic description of the charge-trapping process from semiconductor to defects in the dielectric-oxide layer is of paramount importance for understanding many microelectronic devices such as complementary metal-oxide-semiconductor (CMOS) transistors, as well as electrochemical reactions. Unfortunately, most current microscopic descriptions of such processes are based on empirical models with parameters fitted to experimental device performance results or simplified approximations like the Wentzel-Kramers-Brillouin (WKB) method. Some critical questions are still unanswered, including: What controls the charge-hopping rate, the coupling strength between the defect level to semiconductor level, or the energy difference? How does the hopping rate decay with defect-semiconductor distance? What is the fluctuation of the defect level, especially in amorphous dielectrics? Many of these questions can be answered by ab initio calculations. However, to date, there are few ab initio studies for this problem mainly due to technical challenges from atomic-structure construction to large-system calculations. Here, using the latest advances in calculation methods and codes, we study the carrier-trapping problem using density-functional theory (DFT) based on the Heyd-Scuseria-Ernzerhof (HSE) exchange correlation functional. The valence bond random-switching method is used to construct the crystalline-Si-amorphous-SiO2 (c-Si/a-SiO2) interfacial atomic structure, and the HSE yields a band offset that agrees well with experiments. The hopping rate is calculated with the Marcus theory, and the hopping-rate dependences on the gate potential and defect distances are revealed, as well as the range of fluctuation results from amorphous structural variation. We also analyze the result with the simple WKB model and find a major difference in the description of the coupling constant decay with the defect-semiconductor distance. Our results provide the ab initio simulation insights for this important carrier-trapping process for device operation

Vehicle Detection Using Alex Net and Faster R-CNN Deep Learning Models: A Comparative Study

This paper has been presented at : 5th International Visual Informatics Conference (IVIC 2017)This paper presents a comparative study of two deep learning models used here for vehicle detection. Alex Net and Faster R-CNN are compared with the analysis of an urban video sequence. Several tests were carried to evaluate the quality of detections, failure rates and times employed to complete the detection task. The results allow to obtain important conclusions regarding the architectures and strategies used for implementing such network for the task of video detection, encouraging future research in this topic.S.A. Velastin is grateful to funding received from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 600371, el Ministerio de Economía y Competitividad (COFUND2013-51509) and Banco Santander. The authors wish to thank Dr. Fei Yin for the code for metrics employed for evaluations. Finally, we gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research. The data and code used for this work is available upon request from the authors

Magnetism and its microscopic origin in iron-based high-temperature superconductors

High-temperature superconductivity in the iron-based materials emerges from, or sometimes coexists with, their metallic or insulating parent compound states. This is surprising since these undoped states display dramatically different antiferromagnetic (AF) spin arrangements and N$\rm \acute{e}$el temperatures. Although there is general consensus that magnetic interactions are important for superconductivity, much is still unknown concerning the microscopic origin of the magnetic states. In this review, progress in this area is summarized, focusing on recent experimental and theoretical results and discussing their microscopic implications. It is concluded that the parent compounds are in a state that is more complex than implied by a simple Fermi surface nesting scenario, and a dual description including both itinerant and localized degrees of freedom is needed to properly describe these fascinating materials.Comment: 14 pages, 4 figures, Review article, accepted for publication in Nature Physic

A novel tumor suppressor gene ECRG4 interacts directly with TMPRSS11A (ECRG1) to inhibit cancer cell growth in esophageal carcinoma

<p>Abstract</p> <p>Background</p> <p>The esophageal carcinoma related gene 4 (ECRG4) was initially identified and cloned from human normal esophageal epithelium in our laboratory (GenBank accession no.<ext-link ext-link-id="AF325503" ext-link-type="gen">AF325503</ext-link>). ECRG4 has been described as a novel tumor suppressor gene associated with prognosis in esophageal squamous cell carcinoma (ESCC).</p> <p>Methods</p> <p>In this study, binding affinity assay in vitro and co-immunoprecipitation experiment in vivo were utilized to verify the physical interaction between ECRG4 and transmembrane protease, serine 11A (TMPRSS11A, also known as ECRG1, GenBank accession no. <ext-link ext-link-id="AF 071882" ext-link-type="gen">AF 071882</ext-link>). Then, p21 protein expression, cell cycle and cell proliferation regulations were examined after ECRG4 and ECRG1 co-transfection in ESCC cells.</p> <p>Results</p> <p>We revealed for the first time that ECRG4 interacted directly with ECRG1 to inhibit cancer cell proliferation and induce cell cycle G1 phase block in ESCC. Binding affinity and co-immunoprecipitation assays demonstrated that ECRG4 interacted directly with ECRG1 in ESCC cells. Furthermore, the ECRG4 and ECRG1 co-expression remarkably upregulatd p21 protein level by Western blot (P < 0.001), induced cell cycle G1 phase block by flow cytometric analysis (P < 0.001) and suppressed cell proliferation by MTT and BrdU assay (both P < 0.01) in ESCC cells.</p> <p>Conclusions</p> <p>ECRG4 interacts directly with ECRG1 to upregulate p21 protein expression, induce cell cycle G1 phase block and inhibit cancer cells proliferation in ESCC.</p

NuSTAR and XMM-Newton observations of NGC 1365: Extreme absorption variability and a constant inner accretion disk

We present a spectral analysis of four coordinated NuSTAR+XMM-Newton observations of the Seyfert galaxy NGC 1365. These exhibit an extreme level of spectral variability, which is primarily due to variable line-of-sight absorption, revealing relatively unobscured states in this source for the first time. Despite the diverse range of absorption states, each of the observations displays the same characteristic signatures of relativistic reflection from the inner accretion disk. Through time-resolved spectroscopy we find that the strength of the relativistic iron line and the Compton reflection hump relative to the intrinsic continuum are well correlated, as expected if they are two aspects of the same broadband reflection spectrum. We apply self-consistent disk reflection models to these time-resolved spectra in order to constrain the inner disk parameters, allowing for variable, partially covering absorption to account for the vastly different absorption states observed. Each of the four observations is treated independently to test the consistency of the results obtained for the black hole spin and the disk inclination, which should not vary on observable timescales. We find both the spin and the inclination determined from the reflection spectrum to be consistent, confirming NGC 1365 hosts a rapidly rotating black hole; in all cases the dimensionless spin parameter is constrained to be a* > 0.97 (at 90% statistical confidence or better)

Graphene Photonics and Optoelectronics

The richness of optical and electronic properties of graphene attracts enormous interest. Graphene has high mobility and optical transparency, in addition to flexibility, robustness and environmental stability. So far, the main focus has been on fundamental physics and electronic devices. However, we believe its true potential to be in photonics and optoelectronics, where the combination of its unique optical and electronic properties can be fully exploited, even in the absence of a bandgap, and the linear dispersion of the Dirac electrons enables ultra-wide-band tunability. The rise of graphene in photonics and optoelectronics is shown by several recent results, ranging from solar cells and light emitting devices, to touch screens, photodetectors and ultrafast lasers. Here we review the state of the art in this emerging field.Comment: Review Nature Photonics, in pres

Protandim, a Fundamentally New Antioxidant Approach in Chemoprevention Using Mouse Two-Stage Skin Carcinogenesis as a Model

Oxidative stress is an important contributor to cancer development. Consistent with that, antioxidant enzymes have been demonstrated to suppress tumorigenesis when being elevated both in vitro and in vivo, making induction of these enzymes a more potent approach for cancer prevention. Protandim, a well-defined combination of widely studied medicinal plants, has been shown to induce superoxide dismutase (SOD) and catalase activities and reduce superoxide generation and lipid peroxidation in healthy human subjects. To investigate whether Protandim can suppress tumor formation by a dietary approach, a two-stage mouse skin carcinogenesis study was performed. At the end of the study, the mice on a Protandim-containing basal diet had similar body weight compared with those on the basal diet, which indicated no overt toxicity by Protandim. After three weeks on the diets, there was a significant increase in the expression levels of SOD and catalase, in addition to the increases in SOD activities. Importantly, at the end of the carcinogenesis study, both skin tumor incidence and multiplicity were reduced in the mice on the Protandim diet by 33% and 57% respectively, compared with those on basal diet. Biochemical and histological studies revealed that the Protandim diet suppressed tumor promoter-induced oxidative stress (evidenced by reduction of protein carbonyl levels), cell proliferation (evidenced by reduction of skin hyperplasia and suppression of PKC/JNK/Jun pathway), and inflammation (evidenced by reduction of ICAM-1/VCAM-1 expression, NF-κB binding activity, and nuclear p65/p50 levels). Overall, induction of antioxidant enzymes by Protandim may serve as a practical and potent approach for cancer prevention

The Seroprevalence and Seroincidence of Enterovirus71 Infection in Infants and Children in Ho Chi Minh City, Viet Nam

Enterovirus 71 (EV71)-associated hand, foot and mouth disease has emerged as a serious public health problem in South East Asia over the last decade. To better understand the prevalence of EV71 infection, we determined EV71 seroprevalence and seroincidence amongst healthy infants and children in Ho Chi Minh City, Viet Nam. In a cohort of 200 newborns, 55% of cord blood samples contained EV71 neutralizing antibodies and these decayed to undetectable levels by 6 months of age in 98% of infants. The EV71 neutralizing antibody seroconversion rate was 5.6% in the first year and 14% in the second year of life. In children 5–15 yrs of age, seroprevalence of EV71 neutralizing antibodies was 84% and in cord blood it was 55%. Taken together, these data suggest EV71 force of infection is high and highlights the need for more research into its epidemiology and pathogenesis in high disease burden countries

Prediction of potential drug targets based on simple sequence properties

<p>Abstract</p> <p>Background</p> <p>During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets.</p> <p>Results</p> <p>Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research.</p> <p>Conclusion</p> <p>We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.</p