Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification

Stochastic spectral methods are efficient techniques for uncertainty quantification. Recently they have shown excellent performance in the statistical analysis of integrated circuits. In stochastic spectral methods, one needs to determine a set of orthonormal polynomials and a proper numerical quadrature rule. The former are used as the basis functions in a generalized polynomial chaos expansion. The latter is used to compute the integrals involved in stochastic spectral methods. Obtaining such information requires knowing the density function of the random input {\it a-priori}. However, individual system components are often described by surrogate models rather than density functions. In order to apply stochastic spectral methods in hierarchical uncertainty quantification, we first propose to construct physically consistent closed-form density functions by two monotone interpolation schemes. Then, by exploiting the special forms of the obtained density functions, we determine the generalized polynomial-chaos basis functions and the Gauss quadrature rules that are required by a stochastic spectral simulator. The effectiveness of our proposed algorithm is verified by both synthetic and practical circuit examples.Comment: Published by IEEE Trans CAD in May 201

GASTRO-PROTECTION OF ATORVASTATIN IN INDOMETHACIN-INDUCED ULCER: ROLE OF TUMOR NECROSIS FACTOR-ALPHA AND PROSTAGLANDINS

Using non-steroidal anti-inflammatory drugs as over-the-counter pain-killers may predispose to gastric ulcer as a side effect.The objective of this study is to investigate the possible benefit of a common statin used in hyperlipedemic patients;atorvastatin (AtoR), in ameliorating the ulcerogenic effect of indomethacin (IndoM), and to explore the possible mechanismsinvolved. AtoR (10 mg/kg/day) was administered orally for 7 days. At day 7, gastric ulcer was induced by a single dose ofIndoM (40 mg/kg i.p.), with or without AtoR pre-treatment. IndoM induced gastric ulcer as evident by notable gastriculceration in histopathological sections compared to normal control. Gastric tissue in rats receiving IndoM showedsignificantly higher oxidative stress markers as lipid peroxidation represented by increased malondialdehyde (MDA)content, with significant decrease in gastric tissue nitric oxide (NO) and prostaglandin E2 (PGE2) levels, as well as reductionin catalase and superoxide dismutase antioxidant enzymatic activities. In addition, IndoM induced inflammatory signs asshown by the significant increase in tumor necrosis factor-alpha (TNF-α) level assessed via ELISA. Pre-administration ofAtoR significantly decreased ulcer index (16±1) compared to that of IndoM alone (34±2). In addition, AtoR restored normalgastric histological structure and reverted oxidative and inflammatory markers tested. AtoR confers gastro-protection againstIndoM-induced ulceration via reducing gastric oxidative stress and increasing gastric NO and PGE2 levels, as well asdecreasing the inflammatory marker; TNF-α

Bayesian inference with optimal maps

We present a new approach to Bayesian inference that entirely avoids Markov chain simulation, by constructing a map that pushes forward the prior measure to the posterior measure. Existence and uniqueness of a suitable measure-preserving map is established by formulating the problem in the context of optimal transport theory. We discuss various means of explicitly parameterizing the map and computing it efficiently through solution of an optimization problem, exploiting gradient information from the forward model when possible. The resulting algorithm overcomes many of the computational bottlenecks associated with Markov chain Monte Carlo. Advantages of a map-based representation of the posterior include analytical expressions for posterior moments and the ability to generate arbitrary numbers of independent posterior samples without additional likelihood evaluations or forward solves. The optimization approach also provides clear convergence criteria for posterior approximation and facilitates model selection through automatic evaluation of the marginal likelihood. We demonstrate the accuracy and efficiency of the approach on nonlinear inverse problems of varying dimension, involving the inference of parameters appearing in ordinary and partial differential equations.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Grant DE-SC0002517)United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Grant DE-SC0003908

Hepatocyte Lysosomal Membrane Stabilization by Olive Leaves against Chemically Induced Hepatocellular Neoplasia in Rats

Extensive efforts are exerted looking for safe and effective chemotherapy for hepatocellular carcinoma (HCC). Specific and sensitive early biomarkers for HCC still in query. Present work to study proteolytic activity and lysosomal membrane integrity by hepatocarcinogen, trichloroacetic acid (TCA), in Wistar rats against aqueous olive leaf extract (AOLE).TCA showed neoplastic changes as oval- or irregular-shaped hepatocytes and transformed, vesiculated, and binucleated liver cells. The nuclei were pleomorphic and hyperchromatic. These changes were considerably reduced by AOLE. The results added, probably for the first time, that TCA-induced HCC through disruption of hepatocellular proteolytic enzymes as upregulation of papain, free cathepsin-D and nonsignificant destabilization of lysosomal membrane integrity, a prerequisite for cancer invasion and metastasis. AOLE introduced a promising therapeutic value in liver cancer, mostly through elevating lysosomal membrane integrity. The study substantiated four main points: (1) the usefulness of proteolysis and lysosomalmembrane integrity in early prediction of HCC. (2) TCA carcinogenesis is possibly mediated by lysosomal membrane destabilization, through cathepsin-D disruption, which could be reversed by AOLE administration. (3) A new strategy for management of HCC, using dietary olive leaf system may be a helpful phytotherapeutic trend. (4) A prospective study on serum proteolytic enzyme activity may introduce novel diagnostic tools

Field solver technologies for variation-aware interconnect parasitic extraction

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 207-213).Advances in integrated circuit manufacturing technologies have enabled high density onchip integration by constantly scaling down the device and interconnect feature size. As a consequence of the ongoing technology scaling (from 45nm to 32nm, 22nm and beyond), geometrical variabilities induced by the uncertainties in the manufacturing processes are becoming more significant. Indeed, the dimensions and shapes of the manufactured devices and interconnect structures may vary by up to 40% from their design intent. The effect of such variabilities on the electrical characteristics of both devices and interconnects must be accurately evaluated and accounted for during the design phase. In the last few years, there have been several attempts to develop variation-aware extraction algorithms, i.e. algorithms that evaluate the effect of geometrical variabilities on the electrical characteristics of devices and interconnects. However, most algorithms remain computationally very expensive. In this thesis the focus is on variation-aware interconnect parasitic extraction. In the first part of the thesis several discretization-based variation-aware solver techniques are developed. The first technique is a stochastic model reduction algorithm (SMOR) The SMOR guarantees that the statistical moments computed from the reduced model are the same as those of the full model. The SMOR works best for problems in which the desired electrical property is contained in an easily defined subspace.(cont.) The second technique is the combined Neumann Hermite expansion (CNHE). The CNHE combines the advantages of both the standard Neumann expansion and the standard stochastic Galerkin method to produce a very efficient extraction algorithm. The CNHE works best in problems for which the desired electrical property (e.g. impedance) is accurately expanded in terms of a low order multivariate Hermite expansion. The third technique is the stochastic dominant singular vectors method (SDSV). The SDSV uses stochastic optimization in order to sequentially determine an optimal reduced subspace, in which the solution can be accurately represented. The SDSV works best for large dimensional problems, since its complexity is almost independent of the size of the parameter space. In the second part of the thesis, several novel discretization-free variation aware extraction techniques for both resistance and capacitance extraction are developed. First we present a variation-aware floating random walk (FRW) to extract the capacitance/resistance in the presence of non-topological (edge-defined) variations. The complexity of such algorithm is almost independent of the number of varying parameters. Then we introduce the Hierarchical FRW to extract the capacitance/resistance of a very large number of topologically different structures, which are all constructed from the same set of building blocks. The complexity of such algorithm is almost independent of the total number of structures. All the proposed techniques are applied to a variety of examples, showing orders of magnitude reduction in the computational time compared to the standard approaches. In addition, we solve very large dimensional examples that are intractable when using standard approaches.by Tarek Ali El-Moselhy.Ph.D

Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos

Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge number of repeated simulations in conventional Monte Carlo flows, this paper presents an intrusive spectral simulator for statistical circuit analysis. Our simulator employs the recently developed generalized polynomial chaos expansion to perform uncertainty quantification of nonlinear transistor circuits with both Gaussian and non-Gaussian random parameters. We modify the nonintrusive stochastic collocation (SC) method and develop an intrusive variant called stochastic testing (ST) method. Compared with the popular intrusive stochastic Galerkin (SG) method, the coupled deterministic equations resulting from our proposed ST method can be solved in a decoupled manner at each time point. At the same time, ST requires fewer samples and allows more flexible time step size controls than directly using a nonintrusive SC solver. These two properties make ST more efficient than SG and than existing SC methods, and more suitable for time-domain circuit simulation. Simulation results of several digital, analog and RF circuits are reported. Since our algorithm is based on generic mathematical models, the proposed ST algorithm can be applied to many other engineering problems

Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits

This brief proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical implementation of a stochastic shooting Newton solver is presented for both forced and autonomous circuits. Simulation results on some analog/RF circuits are reported to show the effectiveness of our proposed algorithms

Series Operation of Direct Current Xenon Chloride Excimer Sources

Stable, direct current microhollow cathode discharges in mixtures of hydrochloric acid, hydrogen, xenon, and neon have been generated in a pressure range of 200–1150 Torr. The cathode hole diameter was 250 μm. Sustaining voltages range from 180 to 250 V at current levels of up to 5 mA. The discharges are strong sources of xenon chloride excimer emission at a wavelength of 308 nm. Internal efficiencies of approximately 3% have been reached at a pressure of 1050 Torr. The spectral radiant power at this pressure was measured as 5 mW/nm at 308 nm for a 3 mA discharge. By using a sandwich electrode configuration, consisting of five perforated, alternate layers of metal and dielectric, a tandem discharge—two discharges in series—could be generated. For an anode–cathode–anode configuration the excimer irradiance, recorded on the axis of the discharge, was twice as large as that of a single discharge. The extension of this basic tandem electrode structure to a multiple electrode configuration allows the generation of high irradiance excimer sources. Placing such a structure with a string of microhollow cathode discharge into an optical resonator promises to lead to a direct current microexcimer laser