Physical Sciences and Mathematics Commons^™

A Study Of Cellular Calcium Dynamics In Culture Using Fluorescence Microscopy – A Statistical And Mathematical Approach, Richard Adekola Idowu

Doctoral Dissertations

Calcium in its ionic form is very dynamic, especially in excitable cells such as muscle and brain cells, moving from the high concentration exterior of the cell to much lower concentrations inside the cell, where calcium is used as a second messenger. In brain cells, and neurons especially, calcium is a key signaling ion involved in memory and learning with excitatory neurotransmitters such as glutamate turning neurons "on." Glutamate excites the neurons in part by causing large and dynamic changes in the intracellular calcium concentration. While these dynamics are essential for normal signaling in the brain, excessive and sustained elevations …

A Novel Microfluidic Enrichment Technique For Carbonylated Proteins, Bryant C. Hollins

Doctoral Dissertations

Proteins are the building blocks of cells in living organisms, and are composed of amino acids. The expression of proteins is regulated by the processes of transcription and translation. Proteins undergo post-translational modifications in order to dictate their role physiologically within a cell.

Not all post-translational modifications are beneficial for the protein or the cell. One type of post-translational modification, called carbonylation, irreversibly places a carbonyl group onto an amino acid residue, most commonly proline, lysine, arginine, and threonine. This modification can have severe consequences physiologically, including loss of solubility, loss of function, and protein aggregation.

Carbonylated proteins have commonly …

Adaptive Grid Based Localized Learning For Multidimensional Data, Sheetal Saini

Doctoral Dissertations

Rapid advances in data-rich domains of science, technology, and business has amplified the computational challenges of "Big Data" synthesis necessary to slow the widening gap between the rate at which the data is being collected and analyzed for knowledge. This has led to the renewed need for efficient and accurate algorithms, framework, and algorithmic mechanisms essential for knowledge discovery, especially in the domains of clustering, classification, dimensionality reduction, feature ranking, and feature selection. However, data mining algorithms are frequently challenged by the sparseness due to the high dimensionality of the datasets in such domains which is particularly detrimental to the …

Reliability Models For Hpc Applications And A Cloud Economic Model, Thanadech Thanakornworakij

Doctoral Dissertations

With the enormous number of computing resources in HPC and Cloud systems, failures become a major concern. Therefore, failure behaviors such as reliability, failure rate, and mean time to failure need to be understood to manage such a large system efficiently.

This dissertation makes three major contributions in HPC and Cloud studies. First, a reliability model with correlated failures in a k-node system for HPC applications is studied. This model is extended to improve accuracy by accounting for failure correlation. Marshall-Olkin Multivariate Weibull distribution is improved by excess life, conditional Weibull, to better estimate system reliability. Also, the univariate …

Event Shapes In Proton-Proton Collisions At Center Of Mass Energy = 1.96 Tev, Scott Atkins

Doctoral Dissertations

This dissertation presents the analysis of nine different event shapes measured in high energy pp¯ collisions. An event shape can be defined as an event-based quantity that measures how the final energies are distributed in the final event. This analysis will test strong interactions as described by Quantum Chromodynamics (QCD), through their implementation in different Monte Carlo-based models. Each of the event shapes provides information about the flow of energy in QCD events and about the hadronic final states that occur in pp¯ particle collisions, thus allowing the study of the dynamics of QCD multijet events. Any deviation of an …

Study Of Jet Transverse Momentum And Jet Rapidity Dependence Of Dijet Azimuthal Decorrelations With The Dø Detector, Kiran Chakravarthula

Doctoral Dissertations

In a collision experiment involving highly energetic particles such as hadrons, processes at high momentum transfers can provide information useful for many studies involving Quantum Chromodynamics (QCD). One way of analyzing these interactions is through angular distributions. In hadron-hadron collisions, the angular distribution between the two leading jets with the largest transverse momentum (pT) is affected by the production of additional jets. While soft radiation causes small differences in the azimuthal angular distribution of the two leading jets produced in a collision event, additional hard jets produced in the event have more pronounced influence on the distribution of …

The Study Of Pt Dependence Of Dijet Azimuthal Decorrelations In Proton-Proton Collision At Center Of Mass Energy = 7 Tev, Ramasudhakar Dhullipudi

Doctoral Dissertations

The transverse momentum (pT) dependence of azimuthal decorrelations in dijet events is studied with data collected, at an integrated luminosity of [special characters omitted] dt = (36 ± 4) pb−1, from collisions between protons at a center of mass energy of [special characters omitted] = 7 TeV using the ATLAS detector at the Large Hadron Collider. The results of the analysis of jets in a central rapidity of |y| < 0.8 and pT in the range 60 GeV < pT < 1200 GeV are presented. A new observable RΔ&phis;, defined as the fraction of the total dijet cross section corresponding to a particular range of …

Numerical Simulation Of Nanopulse Penetration Of Biological Matter Using The Adi-Fdtd Method, Fei Zhu

Doctoral Dissertations

Nanopulses are ultra-wide-band (UWB) electromagnetic pulses with pulse duration of only a few nanoseconds and electric field amplitudes greater than 105 V/m. They have been widely used in the development of new technologies in the field of medicine. Therefore, the study of the nanopulse bioeffects is important to ensure the appropriate application with nanopulses in biomedical and biotechnological settings. The conventional finite-difference time-domain (FDTD) method for solving Maxwell's equations has been proven to be an effective method to solve the problems related to electromagnetism. However, its application is restricted by the Courant, Friedrichs, and Lewy (CFL) stability condition that confines …

Failure Prediction For High-Performance Computing Systems, Narate Taerat

Doctoral Dissertations

The failure rate in high-performance computing (HPC) systems continues to escalate as the number of components in these systems increases. This affects the scalability and the performance of parallel applications in large-scale HPC systems. Fault tolerance (FT) mechanisms help mitigating the impact of failures on parallel applications. However, utilizing such mechanisms requires additional overhead. Besides, the overuse of FT mechanisms results in unnecessarily large overhead in the parallel applications. Knowing when and where failures will occur can greatly reduce the excessive overhead. As such, failure prediction is critical in order to effectively utilize FT mechanisms. In addition, it also helps …

The Search For An Optimal Means Of Determining The Minmax Control Parameter Using Sensitivity Analysis, John Teye Brown

Doctoral Dissertations

The use of computational methods for design and simulation of control systems allows for a cost-effective trial and error approach. In this work, we are concerned with the robust, real-time control of physical systems whose state space is infinite-dimensional. Such systems are known as Distributed Parameter Systems (DPS). A body whose state is heterogeneous is a distributed parameter. In particular, this work focuses on DPS systems that are governed by linear Partial Differential Equations, such as the heat equation. We specifically focus on the MinMax controller, which is regarded as being a very robust controller. The mathematical formulation of the …

A Failure Index For High Performance Computing Applications, Clayton F. Chandler

Doctoral Dissertations

This dissertation introduces a new metric in the area of High Performance Computing (HPC) application reliability and performance modeling. Derived via the time-dependent implementation of an existing inequality measure, the Failure index (FI) generates a coefficient representing the level of volatility for the failures incurred by an application running on a given HPC system in a given time interval. This coefficient presents a normalized cross-system representation of the failure volatility of applications running on failure-rich HPC platforms. Further, the origin and ramifications of application failures are investigated, from which certain mathematical conclusions yield greater insight into the behavior of these …

Mathematical Modeling Of Pipeline Features For Robotic Inspection, Yang Gao

Doctoral Dissertations

Underground pipeline systems play an indispensable role in transporting liquids in both developed and developing countries. The associated social and economic cost to repair a pipe upon abrupt failure is often unacceptable. Regular inspection is a preventative action that aims to monitor pipe conditions, catch abnormalities and reduce the chance of undesirable surprises. Robots with CCTV video cameras have been used for decades to inspect pipelines, yielding only qualitative information. It is becoming necessary and preferable for municipalities, project managers and engineers to also quantify the 3-D geometry of underground pipe networks. Existing robots equipped specialized hardware and software algorithms …

Near-Optimal Scheduling And Decision-Making Models For Reactive And Proactive Fault Tolerance Mechanisms, Nichamon Naksinehaboon

Doctoral Dissertations

As High Performance Computing (HPC) systems increase in size to fulfill computational power demand, the chance of failure occurrences dramatically increases, resulting in potentially large amounts of lost computing time. Fault Tolerance (FT) mechanisms aim to mitigate the impact of failure occurrences to the running applications. However, the overhead of FT mechanisms increases proportionally to the HPC systems' size. Therefore, challenges arise in handling the expensive overhead of FT mechanisms while minimizing the large amount of lost computing time due to failure occurrences.

In this dissertation, a near-optimal scheduling model is built to determine when to invoke a hybrid checkpoint …