Search

We have analyzed and modeled the reverse-biased gate leakage current in a Schottky-gate AlGaN/GaN high electron mobility transistor. While the Poole–Frenkel emission current along conductive threading dislocations dominates at low negative gate bias, the trap-assisted tunneling of thermally energized electrons and the thermal emission of electrons from threading dislocations aided by dislocation-related states at multiple energy levels within the AlGaN bandgap are dominant at moderate to large reverse bias. Additionally, deep trap levels of high density localized near the gate/AlGaN interface cause significant leakage at 473 K at low to moderate reverse bias, which could be specific to the device we have analyzed. We extracted about 10 12 cm − 2 traps near the AlGaN/GaN interface from the difference of the barrier layer electric field profile obtained from the experimental high-frequency capacitance–gate voltage and the one needed for final matching. The thermionic- and the thermionic field-emission currents are considerably low; the latter, however, dominates in the defect-free case. Finally, the simulation framework we developed here helped us identify various conduction mechanisms contributing to the reverse-biased gate leakage and the density and electronic structure of the responsible defects. [ABSTRACT FROM AUTHOR]

The total coronavirus disease (COVID-19) cases caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have reached 139 million worldwide and nearing 3 million deaths on April 16, 2021. The availability of accurate data is crucial as it makes it possible to analyze correctly the infection trends and make better forecasts. The reported recovered cases for many US states are surprisingly low. This could be due to difficulties in keeping track of recoveries, which resulted in higher numbers for the reported active cases than the actual numbers on the ground. In this work, based on the typical range of recovery rate for COVID-19, we estimate the active data from the total cases and death cases and bring out a correction for the data for all the US states reported on Worldometer. [ABSTRACT FROM AUTHOR]

An analytical expression for the decay rate of quasi-bound states (QBS) in a triangular quantum well is derived by considering the resonance scattering of particles from the triangular potential profile. Asymptotic properties of the Airy functions that are solutions to the Schrödinger equation for a linear or triangular potential and a perturbative expansion for a small broadening of the QBS are utilized to derive the expression for its location E0 as well as the decay rate Γ that further gives the net tunneling current from the well. The triangular well model is commonly used to represent the band-bending near a heterojunction due to the electrostatic field. This compact expression shows excellent agreement with a full numerical solver and improvement over Wentzel–Kramers–Brillouin based calculations is demonstrated. [ABSTRACT FROM AUTHOR]

The reported COVID‐19 cases in the United States of America have crossed over 10 million and a large number of infected cases are undetected whose estimation can be done if country‐wide antibody testing is performed. In this study, we estimate this undetected fraction of the population by a modeling and simulation approach. We employ an epidemic model SIPHERD in which three categories of infection carriers, symptomatic, purely asymptomatic, and exposed are considered with different transmission rates that are taken dependent on the social distancing conditions, and the detection rate of the infected carriers is taken dependent on the tests done per day. The model is first validated for Germany and South Korea and then applied for prediction of the total number of confirmed, active and dead, and daily new positive cases in the United States. Our study predicts the possible outcomes of the infection if social distancing conditions are relaxed or kept stringent. We estimate that around 30.1 million people are already infected, and in the absence of any vaccine, 66.2 million (range: 64.3–68.0) people, or 20% (range: 19.4–20.5) of the population will be infected by mid‐February 21 if social distancing conditions are not made stringent. We find the infection‐to‐fatality ratio to be 0.65% (range: 0.63–0.67). [ABSTRACT FROM AUTHOR]

Introduction: Cervical cancer is one of the commonly occurring cancers among women. More than ninety percent of mortality related cervical cancer are reported from middle and low-income countries. Objectives: To assess the knowledge regarding cervical cancer and HPV vaccination among medical undergraduates in Mangalore. Materials and Method: This cross sectional study was conducted among medical undergraduates studying at Kasturba Medical College, Mangalore. A pre tested semi structured questionnaire was used for collection of the data. Approval from Institutional Ethics Committee of Kasturba Medical College, Mangalore was obtained before commencement of the study. Data was entered and analysed using SPSS ver. 11.5. Results: The study involved 154 (40.3%) males and 228 (59.7%) female students. It was found that that aetiology for cervical cancer was known among 347 (90.8%) and 326 (85.3%) knew about correct mode of transmission. Awareness regarding ideal age for HPV vaccination was observed in 45.5% (n=174) of the participants. Conclusion: The present study showed that awareness regarding cervical cancer was good, but the knowledge regarding HPV vaccination was sub optimal among medical undergraduates [ABSTRACT FROM AUTHOR]

The analysis of retention characteristics is essential for reliability assessment of any type of flash memory. A high-k (HK) material in the Interpoly dielectric (IPD) stack is known to improve the program-erase characteristics and makes the control oxide thicker for better retention time; however, it also brings-in defects along with it, creating undesirable charge loss path that plays a significant role in retention. Accurate modeling of this leakage process is important for optimizing the architecture that is less prone to oxide defects and exhibiting improved charge retention. In this paper, we present a physical model considering all possible charge leakage mechanisms that include inelastic tunneling through multiple traps in addition to direct tunneling (DT). The trap capture process is modeled as an inelastic process from nanocrystal (NC) to trap state, while the trap-to-trap tunneling is calculated by Bardeen's Transfer Hamiltonian approach. The trap emission process and DT from the spherical NC are modeled by computing the lifetime of quasi-bound states with very small decay widths in the finite-element setup. We show that a single trap model in HK cannot explain the retention characteristics. We propose a new asymmetric IPD structure that show significant improvement in retention time. [ABSTRACT FROM AUTHOR]

Motivation: Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. [ABSTRACT FROM AUTHOR]

The program/erase process in floating gate (FG) flash memory devices is modeled by considering sequential quantum tunneling of electrons and taking into account quantum confinement in the channel and FG. We precisely determine location of quasi-bound or decaying quantum states in the inversion layer and in FG comprising a nanocrystal (NC) layer, and compute their lifetime by finding the complex eigenenergy of the resonance transmission problem. Self-consistent solutions to Poisson and Schrödinger equations are obtained for the quantum states of electrons in the inversion layer of MOS devices, and subsequently, sequential Fowler–Nordheim tunneling current to the spherical NCs is obtained using finite-element method considering open boundary conditions. The method described here is capable of determining the tunneling current accurately for arbitrary potential profiles, and can be applied for composite tunnel dielectric stacks. Our results show good agreement with the experimental data for high- $k$ interpoly dielectric flash memory devices. [ABSTRACT FROM PUBLISHER]

Many optimal decision problems in scientific, engineering, and public sector applications involve both discrete decisions and nonlinear system dynamics that affect the quality of the final design or plan. These decision problems lead to mixed-integer nonlinear programming (MINLP) problems that combine the combinatorial difficulty of optimizing over discrete variable sets with the challenges of handling nonlinear functions. We review models and applications of MINLP, and survey the state of the art in methods for solving this challenging class of problems.Most solution methods for MINLP apply some form of tree search. We distinguish two broad classes of methods: single-tree and multitree methods. We discuss these two classes of methods first in the case where the underlying problem functions are convex. Classical single-tree methods include nonlinear branch-and-bound and branch-and-cut methods, while classical multitree methods include outer approximation and Benders decomposition. The most efficient class of methods for convex MINLP are hybrid methods that combine the strengths of both classes of classical techniques.Non-convex MINLPs pose additional challenges, because they contain non-convex functions in the objective function or the constraints; hence even when the integer variables are relaxed to be continuous, the feasible region is generally non-convex, resulting in many local minima. We discuss a range of approaches for tackling this challenging class of problems, including piecewise linear approximations, generic strategies for obtaining convex relaxations for non-convex functions, spatial branch-and-bound methods, and a small sample of techniques that exploit particular types of non-convex structures to obtain improved convex relaxations.We finish our survey with a brief discussion of three important aspects of MINLP. First, we review heuristic techniques that can obtain good feasible solution in situations where the search-tree has grown too large or we require real-time solutions. Second, we describe an emerging area of mixed-integer optimal control that adds systems of ordinary differential equations to MINLP. Third, we survey the state of the art in software for MINLP. [ABSTRACT FROM AUTHOR]

In most patients with hypertensive nephropathy and low glomerular filtration rate (GFR), the kidney function progressively declines despite the adequate control of the hypertension with angiotensin-converting enzyme inhibition. Previously we found that 2 years of oral sodium citrate slowed GFR decline in patients whose estimated GFR (eGFR) was very low (mean 33 ml/min). This treatment also slowed GFR decline in an animal model of surgically reduced nephron mass. Here, we tested if daily oral sodium bicarbonate slowed GFR decline in patients with hypertensive nephropathy with reduced but relatively preserved eGFR (mean 75 ml/min) in a 5-year, prospective, randomized, placebo-controlled, and blinded interventional study. Patients matched for age, ethnicity, albuminuria, and eGFR received daily placebo or equimolar sodium chloride or bicarbonate while maintaining antihypertensive regimens (including angiotensin-converting enzyme inhibition) aiming for their recommended blood pressure targets. After 5 years, the rate of eGFR decline, estimated using plasma cystatin C, was slower and eGFR was higher in patients given sodium bicarbonate than in those given placebo or sodium chloride. Thus, our study shows that in hypertensive nephropathy, daily sodium bicarbonate is an effective kidney protective adjunct to blood pressure control along with angiotensin-converting enzyme inhibition. [ABSTRACT FROM AUTHOR]

BackgroundPreeclampsia (PE), a pregnancy-specific hypertensive syndrome, is one of the leading causes of premature births as well as fetal and maternal death. There is strong evidence that maternal immune system activation, of which Toll-like receptors (TLRs) play a major role, contributes to the development of PE. Viral infections, sensed by TLR3, are associated with hypertensive disorders of pregnancy. We tested the hypothesis that TLR3 activation during pregnancy would cause hypertension, endothelial dysfunction, proteinuria, and intrauterine growth restriction in normal pregnant rats.MethodsWe treated pregnant and nonpregnant rats with the viral mimetic polyinosinic:polycytidylic acid (poly I:C) or vehicle every other day beginning at day 10 of gestation and measured systolic blood pressure, aortic vasodilation, urinary protein concentration, fetal growth, and serum and placental cytokine levels.ResultsPregnant rats treated with poly I:C displayed significantly elevated systolic blood pressures compared to pregnant rats and nonpregnant rats treated with poly I:C on day 18 of gestation. Poly I:C–treated pregnant rats also exhibited significantly decreased aortic vasodilation, significantly increased urinary protein concentrations, and had more malformed pups/litter. Additionally, poly I:C–treated rats exhibited a significant increase in placental TLR3 expression and proinflammatory/anti-inflammatory cytokine ratio compared to vehicle-treated rats. Poly I:C treatment of nonpregnant control rats had no effect on systolic blood pressure, aortic vasodilation, or urinary protein concentrations.ConclusionThese findings demonstrate that sustained maternal immune system activation via TLR3 during pregnancy causes PE-like symptoms in rats and suggest that viral infection during pregnancy may contribute to the development of PE.American Journal of Hypertension 2009; doi:10.1038/ajh.2009.185 [ABSTRACT FROM AUTHOR]

BackgroundHypertensive disorders of pregnancy, including preeclampsia (PE), affect ~7–10% of pregnancies in the US. Clinical and experimental studies strongly suggest that the maternal immune system plays a role in the development of these disorders; however, few therapeutic options exist aside from delivery.MethodsUsing a deoxycorticosterone acetate (DOCA)/salt-low renin rat model, which exhibits hypertension, proteinuria, endothelial dysfunction, and intrauterine growth restriction (IUGR), we measured serum cytokine levels as an indication of immune system activation. In addition, we suppressed the immune system with either azathioprine (Aza) or mycophenolate mofetil (MMF) during the second half of pregnancy to determine whether the these symptoms could be ameliorated.ResultsOur results demonstrate that serum T helper-1 (Th1)-type inflammatory cytokines interleukin (IL)-2, IL-12, interferon-γ (IFNγ), and RANTES were significantly elevated in hypertensive pregnant rats while the Th2-type cytokine IL-4 was elevated in normal pregnant animals. Either Aza or MMF significantly attenuated the hypertension, proteinuria, and endothelial dysfunction as well as the increased proinflammatory Th1 cytokine profile in pregnant rats treated with DOCA/salt, and had no effect on these parameters in normal pregnant rats.ConclusionThese data strongly suggest that maternal immune system activation plays a role in the development of pregnancy-induced hypertension (PIH).American Journal of Hypertension 2009; doi:10.1038/ajh.2009.125 [ABSTRACT FROM AUTHOR]

Arteriolar hyalinosis is a common histological finding in renal transplant recipients treated with the calcineurin inhibitor tacrolimus; however, the pathophysiologic mechanisms remain unknown. In addition to increasing transforming growth factor (TGF)-β levels, tacrolimus inhibits calcineurin by binding to FK506-binding protein 12 (FKBP12). FKBP12 alone also inhibits TGF-β receptor activation. Here we tested whether tacrolimus binding to FKBP12 removes an inhibition of the TGF-β receptor, allowing ligand binding, ultimately leading to receptor activation and arteriolar hyalinosis. We found that specific deletion of FKBP12 from endothelial cells was sufficient to activate endothelial TGF-β receptors and induce renal arteriolar hyalinosis in these knockout mice, similar to that induced by tacrolimus. Tacrolimus-treated and knockout mice exhibited significantly increased levels of aortic TGF-β receptor activation as evidenced by SMAD2/3 phosphorylation, along with increased collagen and fibronectin expression compared to controls. Treatment of isolated mouse aortas with tacrolimus increased TGF-β receptor activation and collagen and fibronectin expression. These effects were independent of calcineurin, absent in endothelial denuded aortic rings, and could be prevented by the small molecule TGF-β receptor inhibitor SB-505124. Thus, endothelial cell TGF-β receptor activation is sufficient to cause vascular remodeling and renal arteriolar hyalinosis. [ABSTRACT FROM AUTHOR]

The total coronavirus disease (COVID-19) cases caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have reached 139 million worldwide and nearing 3 million deaths on April 16, 2021. The availability of accurate data is crucial as it makes it possible to analyze correctly the infection trends and make better forecasts. The reported recovered cases for many US states are surprisingly low. This could be due to difficulties in keeping track of recoveries, which resulted in higher numbers for the reported active cases than the actual numbers on the ground. In this work, based on the typical range of recovery rate for COVID-19, we estimate the active data from the total cases and death cases and bring out a correction for the data for all the US states reported on Worldometer.

Motivation: Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP)., Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs., Availability and Implementation: The software is implemented in Matlab, and is provided as supplementary information ., Contact: hyunseob.song@pnnl.gov., Supplementary Information: Supplementary data are available at Bioinformatics online., (Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.)