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Search Results: 1 - 10 of 59 matches for " Nikesh Anumula "
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Can CT Perfusion Guide Patient Selection for Treatment of Delayed Cerebral Ischemia?  [PDF]
Rachel Gold, Pina C. Sanelli, Nikesh Anumula, Austin Ferrone, Carl E. Johnson, Joseph P. Comunale, Apostolos J. Tsiouris, Howard Riina, Halinder Mangat, Axel Rosengart, Alan Z. Segal
Advances in Computed Tomography (ACT) , 2013, DOI: 10.4236/act.2013.21002
Abstract:

Purpose: To evaluate qualitative and quantitative CT perfusion (CTP) for different treatment options of delayed cerebral ischemia (DCI) in aneurysmal SAH. Methods: Retrospective study of consecutive SAH patients enrolled in a prospective IRB-approved clinical trial. Qualitative analysis of CTP deficits were determined by two blinded neuroradiologists. Quantitative CTP was performed using standardized protocol with region-of-interest placement sampling the cortex. DCI was assessed by clinical and imaging criteria. Patients were classified into treatment groups: 1) hypertension-hemodilution-hypervolemia (HHH); 2) intra-arterial (IA) vasodilators and/or angioplasty; 3) no treatment. Mean quantitative CTP values were compared using ANOVA pairwise comparisons. Receiver operating characteristic (ROC) curves, standard error (SE) and optimal threshold values were calculated. Results: Ninety-six patients were classified into three treatment groups; 21% (19/96) HHH, 34% (33/96) IA-therapy and 46% (44/96) no treatment. DCI was diagnosed in 42% (40/96); of which 18% (7/40) received HHH, 80% (32/40) IA-therapy, and 2% (1/40) no treatment. CTP deficits were seen in 50% (48/96); occurring in 63% (12/19) HHH, 94% (31/33) IA-therapy, and 11% (5/44) no treatment. Presence of CTP deficits had 83% sensitivity, 89% specificity, 90% positive predictive and 81% negative predic

Systemic treatment with liver X receptor agonists raises apolipoprotein E, cholesterol, and amyloid-β peptides in the cerebral spinal fluid of rats
Sokreine Suon, Jie Zhao, Stephanie A Villarreal, Nikesh Anumula, Mali Liu, Linda M Carangia, John J Renger, Celina V Zerbinatti
Molecular Neurodegeneration , 2010, DOI: 10.1186/1750-1326-5-44
Abstract: We investigated the hypothesis that increased apoE levels and lipidation induced by LXR agonists facilitates Aβ efflux from the brain to the cerebral spinal fluid (CSF). We also examined if the brain expression of major apoE receptors potentially involved in apoE-mediated Aβ clearance was altered by LXR agonists. ApoE, cholesterol, Aβ40, and Aβ42 levels were all significantly elevated in the CSF of rats after only 3 days of treatment with LXR agonists. A significant reduction in soluble brain Aβ40 levels was also detected after 6 days of LXR agonist treatment.Our novel findings suggest that central Aβ lowering caused by LXR agonists appears to involve an apoE/cholesterol-mediated transport of Aβ to the CSF and that differences between the apoE isoforms in mediating this clearance pathway may explain why individuals carrying one or two copies of APOE ε4 have increased risk for AD.Alzheimer's disease (AD) is a neurodegenerative disease characterized by the progressive loss of memory and cognitive function [1]. The presence of amyloid-β (Aβ) peptide deposits in the hippocampal and cortical regions of the brain is a major hallmark of AD pathology. Aβ peptides, mainly Aβ40 and Aβ42, are released from the transmembrane amyloid precursor protein (APP) following sequential cleavage by β- and γ-secretases and have been shown to cause toxicity to both neurons and glia cells in vitro and in vivo [1,2]. The most significant genetic association reported for late-onset AD is with apolipoprotein E (apoE), the main lipid transporter protein in the central nervous system (CNS) [3,4]. Three human apoE isoforms arise from polymorphisms within the APOE gene, named E2, E3 and E4. While only 15% of the normal population carries apoE4, up to 70% of AD patients have one or two copies of apoE4.The mechanism by which apoE4 increases the risk for AD is not yet clear. It has been established that both healthy individuals and AD patients carrying apoE4 have increased brain amyloid burden [5,6].
Modified Vegetable Oil Based Additives as a Future Polymeric Material—Review  [PDF]
Nikesh B. Samarth, Prakash A. Mahanwar
Open Journal of Organic Polymer Materials (OJOPM) , 2015, DOI: 10.4236/ojopm.2015.51001
Abstract: Polymeric materials from renewable resources have attracted a lot of attention in recent years. The development and utilization of vegetable oils for polymeric materials are currently in the spotlight of the polymer and chemical industry, as they are the largest renewable platform due to their universal wide availability, ingrained biodegradability, low cost, and excellent environmental aspects (i.e., low ecotoxicity and low toxicity toward humans). These excellent natural characteristics are now being taken advantage of in research and development, with vegetable oil derived polymers/polymeric materials/composites being used in numerous applications including paints and coatings, adhesives, and nanocomposites. The aim of this review paper is to give a fundamental description of the various vegetable oil applications in polymer materials and its recent developments. Particular emphasis will be placed on study and main application of triglyceride based additive for polymer and to give the reader an insight into the main developments is discussed.
Numerical Feynman integrals with physically inspired interpolation: Faster convergence and significant reduction of computational cost
Nikesh S. Dattani
AIP Advances , 2012, DOI: 10.1063/1.3680607
Abstract: One of the most successful methods for calculating reduced density operator dynamics in open quantum systems, that can give numerically exact results, uses Feynman integrals. However, when simulating the dynamics for a given amount of time, the number of time steps that can realistically be used with this method is always limited, therefore one often obtains an approximation of the reduced density operator at a sparse grid of points in time. Instead of relying only on ad hoc interpolation methods (such as splines) to estimate the system density operator in between these points, I propose a method that uses physical information to assist with this interpolation. This method is tested on a physically significant system, on which its use allows important qualitative features of the density operator dynamics to be captured with as little as two time steps in the Feynman integral. This method allows for an enormous reduction in the amount of memory and CPU time required for approximating density operator dynamics within a desired accuracy. Since this method does not change the way the Feynman integral itself is calculated, the value of the density operator approximation at the points in time used to discretize the Feynamn integral will be the same whether or not this method is used, but its approximation in between these points in time is considerably improved by this method. A list of ways in which this proposed method can be further improved is presented in the last section of the article.
An open source MATLAB program for fast numerical Feynman integral calculations for open quantum system dynamics on GPUs
Nikesh S. Dattani
Physics , 2012, DOI: 10.1016/j.cpc.2013.07.001
Abstract: This MATLAB program calculates the dynamics of the reduced density matrix of an open quantum system modeled by the Feynman-Vernon model. The user gives the program a vector describing the coordinate of an open quantum system, a hamiltonian matrix describing its energy, and a spectral distribution function and temperature describing the environment's influence on it, in addition to the open quantum system's intial density matrix and a grid of times. With this, the program returns the reduced density matrix of the open quantum system at all (or some) moments specified by that grid of times. This overall calculation can be divided into two stages: the setup of the Feynman integral, and the actual calculation of the Feynman integral for time-propagation of the density matrix. When this program calculates this propagation on a multi-core CPU, it is this propagation that is usually the rate limiting step of the calculation, but when it is calculated on a GPU, the propagation is calculated so quickly that the setup of the Feynman integal actually becomes the rate limiting step for most cases tested so far. The overhead of transfrring information from the CPU to the GPU and back seems to have negligible effect on the overall runtime of the program. When the required information cannot fit on the GPU, the user can choose to run the entire program on a CPU.
Numerical Feynman integrals for density operator dynamics using master equation interpolants: faster convergence and significant reduction of computational cost
Nikesh S. Dattani
Physics , 2010,
Abstract: The Feynman integral is one of the most accurate methods for calculating density operator dynamics in open quantum systems. However, the number of time steps that can realistically be used is always limited, therefore one often obtains an approximation of the density operator at a sparse grid of points in time. Instead of relying only on \textit{ad hoc} interpolation methods such as splines to estimate the system density operator in between these points, I propose a method that uses physical information to assist with this interpolation. This method is tested on a physically significant system, on which its use allows important qualitative features of the density operator dynamics to be captured with as little as 2 time steps in the Feynman integral. This method allows for an enormous reduction in the amount of memory and CPU time required for approximating density operator dynamics within a desired accuracy. Since this method does not change the way the Feynman integral itself is calculated, the value of the density operator approximation at the points in time used to discretize the Feynamn integral will be the same whether or not this method is used, but its approximation in between these points in time is considerably improved by this method.
Beryllium monohydride (BeH): Where we are now, after 86 years of spectroscopy
Nikesh S. Dattani
Physics , 2014, DOI: 10.1016/j.jms.2014.09.005
Abstract: BeH is one of the most important benchmark systems for ab initio methods and for studying Born-Oppenheimer breakdown. However the best empirical potential and best ab initio potential for the ground electronic state to date give drastically different predictions in the long-range region beyond which measurements have been made, which is about \sim1000 cm^{-1} for ^{9} BeH, \sim3000 cm^{-1} for ^{9} BeD, and \sim13000 cm^{-1} for ^{9} BeT. Improved empirical potentials and Born-Oppenheimer breakdown corrections have now been built for the ground electronic states X(1^{2}\Sigma^{+}) of all three isotopologues. The predicted dissociation energy for ^{9} BeH from the new empirical potential is now closer to the current best ab initio prediction by more than 66% of the discrepancy between the latter and the previous best empirical potential. The previous best empirical potential predicted the existence of unobserved vibrational levels for all three isotopologues, and the current best ab initio study also predicted the existence of all of these levels, and four more. The present empirical potential agrees with the ab initio prediction of all of these extra levels not predicted by the earlier empirical potential. With one exception, all energy spacings between vibrational energy levels for which measurements have been made, are predicted with an agreement of better than 1 cm^{-1} between the new empirical potential and the current best ab initio potential, but some predictions for unobserved levels are still in great disagreement, and the equilibrium bond lengths are different by orders of magnitude.
Analytic potentials and vibrational energies for Li$_{2}$ states dissociating to $\mbox{Li}\left(2S\right)+\mbox{Li}\left(3P\right)$. Part 1: The $^{2S+1}Π_{u/g}$ states
Nikesh S. Dattani
Physics , 2015,
Abstract: Analytic potentials are built for all four $^{2S+1}\Pi_{u/g}$ states of Li$_{2}$ dissociating to Li$(2S)$ + Li$(3P)$: $3b(3^{3}\Pi_{u})$, $3B(3^{1}\Pi_{u})$, $3C(3^{1}\Pi_{g}),$ and $3d(3^{3}\Pi_{g})$. These potentials include the effect of spin-orbit coupling for large internuclear distances, and include state of the art long-range constants. This is the first successful demonstration of fully analytic diatomic potentials that capture features that are usually considered too difficult to capture without a point-wise potential, such as multiple minima, and shelves. Vibrational energies for each potential are presented for the isotopologues $^{6,6}$Li$_{2}$, $^{6,7}$Li$_{2}$, $^{7,7}$Li$_{2}$, and the elusive `halo nucleonic molecule' $^{11,11}$Li$_{2}$. These energies are claimed to be accurate enough for new high-precision experimental setups such as the one presented in {[}Sebastian \emph{et al.} Phys. Rev. A, \textbf{90}, 033417 (2014){]} to measure and assign energy levels of these electronic states, all of which have not yet been explored in the long-range region. Measuring energies in the long-range region of these electronic states may be significant for studying the \emph{ab initio} vs experiment discrepancy discussed in {[}Tang \emph{et al.} Phys. Rev. A, \textbf{84}, 052502 (2014){]} for the $C_{3}$ long-range constant of Lithium, which has significance for improving the SI definition of the second.
Linear Multistep Numerical Methods for Ordinary Differential Equations
Nikesh S. Dattani
Mathematics , 2008,
Abstract: A review of the most popular Linear Multistep (LM) Methods for solving Ordinary Differential Equations numerically is presented. These methods are first derived from first principles, and are discussed in terms of their order, consistency, and various types of stability. Particular varieties of stability that may not be familiar, are briefly defined first. The methods that are included are the Adams-Bashforth Methods, Adams-Moulton Methods, and Backwards Differentiation Formulas. Advantages and disadvantages of these methods are also described. Not much prior knowledge of numerical methods or ordinary differential equations is required, although knowledge of basic topics from calculus is assumed.
Modeling of neuron-semiconductor interactions in neuronal networks interfaced with silicon chips
Nikesh S. Dattani
Quantitative Biology , 2009,
Abstract: Recent developments in the interfacing of neurons with silicon chips may pave the way for progress in constructing scalable neurocomputers. The assembly of synthetic neuronal networks with predefined synaptic connections and controlled geometric structure has been realized experimentally within the last decade. Furthermore, when such neuronal networks are interfaced with semiconductors, action potentials in neurons of the network can be elicited by capacitative stimulators, and voltage measurements can be made by transistors incorporated into the associated silicon chip. Despite the impressive progress, such preliminary devices have not yet demonstrated the performance of useful computations, and constructing larger devices can be both expensive and time-consuming. Accordingly, an appropriate modeling framework with the capability to simulate current experimental results in such devices may be used to make useful predictions regarding their potential computational power. A proposed modeling framework for functional neuronal networks interfaced with silicon chips is presented below.
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