Digital Commons Network^™

A Study On Large-Scale Deep Learning In Bioinformatics And Biomedical Applications, Shayan Shams

LSU Doctoral Dissertations

Recent advances in Artificial Intelligence and deep learning have provided researchers in various fields insights into the analysis of multiple datasets. These applications include image analysis, text analysis, and many more. However, the effectiveness of deep learning in some areas, such as biomedical imaging and genomic research, has been overshadowed by the variance in the types and complexity of data. This is in addition to the expensive labeling process and the limited size of datasets in these fields. These challenges require advanced deep learning models capable of learning from a small dataset and also from a small number of labeled …

Stray Radiation Dose From X-Ray And Proton Beam Radiation Therapies, Christopher William Schneider

LSU Doctoral Dissertations

The growing population of cancer survivors at risk of radiation induced side-effects is a public health concern. These side-effects include serious conditions such as second cancers, the majority of which occur outside of the primary treatment volume. Radiotherapy treatment planning systems systematically underestimate the dose to tissues out-of-field. Attempts to predict and reduce the risks of radiogenic side effects require accurate and personalized knowledge of the out-of-field radiation dose to patients. The long-term goal of this research is to provide clinical and research tools necessary to reduce the risk of radiotherapy side effects and improve the health outcomes of radiotherapy …

Approaches For Sample Characterization And Lithography With Nanoparticles Using Modes Of Scanning Probe Microscopy, Jayne C. Garno, Temitope O. Jegede, Kathryn B. Mckee, Melissia Porter, Autumn E. Webb, Jin Gyun Lee, Neepa Mk Kuruppu Arachchige, Justin R. Ragains, Noémie Elgrishi

Faculty Publications

Measurement and imaging modes of scanning probe microscopy (SPM) have been routinely applied for characterizing systems of nanoparticles; however the evolution of fabrication methods to prepare arrangements of nanoparticles remains a challenge. Reproducible fabrication of surface structures which integrate nanoparticles within ultra-small patterns will require innovative approaches to achieve high throughput and precision. Strategies for nanoscale lithography have been introduced for preparing defined arrangements of nanoparticles on surfaces based on physical or chemical interactions. For example, physisorption was employed for attaching nanoparticles based on colloidal lithography and site-directed assembly. Microfabricated atomic force microscope (AFM) tips with capillary channels have been …

Rare Earth Geochemistry Of Apatitic Fossils From The Middle-Upper Ordovician Southern Margin Of Laurentia, Rafael Adrian Villanueva

LSU Master's Theses

Widespread deposition of phosphate and a transition from tropical to cool water carbonates is seen throughout Middle-Upper Ordovician Nashville Dome area spanning the M4/M5 sequence boundary. Hypotheses explaining the onset of these lithologic changes have included the onset of glaciation, drawdown of CO₂ related to the Guttenburg Isotope Carbon Excursion (GICE), and siliciclastic weathering, yet none of these studies have provided definitive evidence that shows any of these are the sole factor driving paleoenvironmental changes across the M4/M5 boundary. In order to test whether rapid subsidence along the southeastern margin of Laurentia may have caused an influx of phosphate …

Cognitive Intra-Individual Variability: The Effects Of Affect In A Healthy Young Adult Sample, Tovah M.D. Cowan

LSU Master's Theses

Cognition is foundational to our experience of the world, but also to how psychologists understand dysfunctions. Cognitive impairment is a feature of a variety of mental disorders, but traditional assessment measures have key limitations in prediction and classification. A proposed alternative is cognitive intraindividual variability (cIIV), which is suggested to measure cognitive control or neural inefficiencies, fluctuating within a task, or over short periods of time. cIIV has been shown to be more sensitive in classification for a variety of conditions than overall performance, including in affective disorders. Further, some research suggests that cIIV is related to self-report cognitive abilities, …

System Identification Based On Errors-In-Variables System Models, Hyundeok Kang

LSU Doctoral Dissertations

We study the identification problem for errors-in-variables (EIV) systems. Such an EIV model assumes that the measurement data at both input and output of the system involve corrupting noises. The least square (LS) algorithm has been widely used in this area. However, it results in biased estimates for the EIV-based system identification. In contrast, the total least squares (TLS) algorithm is unbiased, which is now well-known, and has been effective for estimating the system parameters in the EIV system identification.

In this dissertation, we first show that the TLS algorithm computes the approximate maximum likelihood estimate (MLE) of the system …

High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami

LSU Doctoral Dissertations

Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …

Application Of Pressure And Rate Transient Analyses To Stress-Sensitive Multi-Fractured Composite Systems And Compartmentalized Reservoirs, Oscar Mauricio Molina

LSU Doctoral Dissertations

Pressure transient analysis (PTA) is one of the most robust and commonly interpretation tools available for reservoir characterization. Common applications of PTA include estimation of near-wellbore and reservoir properties, detection of reservoir limits and identification of depletion mechanisms. In addition, PTA allows the identification of sealing and leaky faults and the characterization of its properties, such as permeability and transmissibility hence direction of leakage within the fault.

The purpose of this dissertation is to introduce the analytical solution for pressure-transient behavior for three novel reservoir models. First, we develop the analytical model of a multi-fracture horizontal well (MFHW) with pressure-dependent …

Teachers As Change Agents: An Investigation Into The Literary Practices Of Effective Tier 2 Charter School Teachers In South Louisiana, Earlisha Jenkins Whitfield

LSU Doctoral Dissertations

A Southern Louisiana charter school is in the initial phases of a Response To Intervention (RTI). General education classroom teachers are responsible for all Tier 1 and 2 instruction that included interventions in Tier 2. However, many teachers were unsure about the implementation, of RTI and had negative experiences with RTI, describing the process as frustrating and overwhelming. This case study examines teachers that have been effective in the process as evidenced by an increase in in reading levels and student interest. The research explores the teachers’ perceptions, experience, and knowledge of the current implementation of RTI. This qualitative research …

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …

A Low-Cost Experimental Testbed For Multi-Agent System Coordination Control, Victor Fernandez-Kim

LSU Master's Theses

A multi-agent system can be defined as a coordinated network of mobile, physical agents that execute complex tasks beyond their individual capabilities. Observations of biological multi-agent systems in nature reveal that these ``super-organisms” accomplish large scale tasks by leveraging the inherent advantages of a coordinated group. With this in mind, such systems have the potential to positively impact a wide variety of engineering applications (e.g. surveillance, self-driving cars, and mobile sensor networks). The current state of research in the area of multi-agent systems is quickly evolving from the theoretical development of coordination control algorithms and their computer simulations to experimental …

Maximizing And Modeling Malonyl-Coa Production In Escherichia Coli, Tatiana Thompson Silveira Mello

LSU Master's Theses

In E. coli, fatty acid synthesis is catalyzed by the enzyme acetyl-CoA carboxylase (ACC), which converts acetyl-CoA into malonyl-CoA. Malonyl-CoA is a major building block for numerous of bioproducts. Multiple parameters regulate the homeostatic cellular concentration of malonyl-CoA, keeping it at a very low level. Understanding how these parameters affect the bacterial production of malonyl-CoA is fundamental to maximizing it and its bioproducts. To this end, competing pathways consuming malonyl-CoA can be eliminated, and optimal nutritional and environmental conditions can be provided to the fermentation broth. Most previous studies utilized genetic modifications, expensive consumables, and high-cost quantification methods, making …

Reproductive Parameters And Methodologies For The Culture Of Golden Topminnows (Fundulus Chrysotus) And Bluenose Shiners (Pteronotropis Welaka), Jacob A. Fetterman

LSU Master's Theses

The global ornamental fish trade has expanded over the past 20 years, requiring captive rearing methods to be improved or developed for species of interest. Aquaculture of desirable species is preferable over wild harvest to conserve natural habitats and biodiversity. This thesis focused on improving culture methods for Golden Topminnows Fundulus chrysotus and developing culture methods for Bluenose Shiners Pteronotropis welaka, both native fishes of the southeastern United States with ornamental demand. A combination of reproductive metric analyses, examination of historical collections, and captive spawning trials were employed to target specific objectives for each species. In female Golden Topminnows, …

Cost Effective, Highly Efficient Wireless Power Transfer Systems For Ev Battery Charging, Amir Masoud Bozorgi

LSU Doctoral Dissertations

The impact of changing inner diameter of wireless power transfer (WPT) coils on coupling coefficient is studied. It is demonstrated that at a certain outer and inner coil diameter, turn space variation has minor effect on the coupling coefficient. Next, two compensation networks, namely primary LCC and secondary LCC, which offer load-independent voltage transfer ratio and zero voltage switching for WPT, are presented. For both compensation networks, the condition for having zero voltage switching operation are derived. In addition, load-independent voltage transfer ratio (VTR) frequencies are obtained and VTR at each frequency is derived. Then, required equations for calculation of …

Basalt Tectonic Discrimination Using Combined Machine Learning Approach, Qiubing Ren, Mingchao Li, Shuai Han, Ye Zhang, Qi Zhang, Jonathan Shi

Faculty Publications

Geochemical discrimination of basaltic magmatism from different tectonic settings remains an essential part of recognizing the magma generation process within the Earth’s mantle. Discriminating among mid-ocean ridge basalt (MORB), ocean island basalt (OIB) and island arc basalt (IAB) is that matters to geologists because they are the three most concerned basalts. Being a supplement to conventional discrimination diagrams, we attempt to utilize the machine learning algorithm (MLA) for basalt tectonic discrimination. A combined MLA termed swarm optimized neural fuzzy inference system (SONFIS) was presented based on neural fuzzy inference system and particle swarm optimization. Two geochemical datasets of basalts from …

Spatiotemporal Coupling Of Attosecond Pulses, Cord L. Arnold, Hampus Wikmark, Chen Guo, Jan Vogelsang, Peter W. Smorenburg, Helene Coudert-Alteirac, Jan Lahl, Jasper Peschel, Piotr Rudawski, Hugo Dacasa, Stefanos Carlstrom, Sylvain Maclot, Mette B. Gaarde, Per Johnsson, Anne Lahuillier

Faculty Publications

Attosecond pulses in the extreme ultraviolet (XUV) spectral range are today routinely generated via high-order harmonic generation (HHG), when intense ultrashort laser pulses are focused into a gaseous generation medium. The effect is most easily understood in a semi-classical picture [1]. An electron can tunnel ionize from the distorted atomic potential, pick up kinetic energy in the laser field, potentially return to its parent ion and recombine. The excess energy is emitted as XUV photon. The process repeats for every half-cycle of the driving field, resulting in a train of attosecond pulses and in the frequency domain in the well-known, …

Sexually Dimorphic Oxytocin Receptorexpressing Neurons In The Preoptic Area Of The Mouse Brain, Kaustubh Sharma, Ryan Leblanc, Masudul Haque, Katsuhiko Nishimori, Madigan M. Reid, Ryoichi Teruyama

Faculty Publications

© 2019 Sharma et al. Oxytocin is involved in the regulation of social behaviors including parental behaviors in a variety of species. Oxytocin triggers social behaviors by binding to oxytocin receptors (OXTRs) in various parts of the brain. OXTRs are present in the preoptic area (POA) where hormone-sensitive sexually dimorphic nuclei exist. The present study was conducted to examine whether sex differences exist in the distribution of neurons expressing OXTRs in the POA. Using OXTR-Venus (an enhanced variant of yellow fluorescent protein) mice, the distribution of OXTR-Venus cells in the POA was compared between sexes. The total number of OXTR-Venus …

Generalized Laminar Matroids, Tara Fife, James Oxley

Faculty Publications

Nested matroids were introduced by Crapo in 1965 and have appeared frequently in the literature since then. A flat of a matroid M is Hamiltonian if it has a spanning circuit. A matroid M is nested if and only if its Hamiltonian flats form a chain under inclusion; M is laminar if and only if, for every 1-element independent set X, the Hamiltonian flats of M containing X form a chain under inclusion. We generalize these notions to define the classes of k-closure-laminar and k-laminar matroids. This paper focuses on structural properties of these classes noting that, while the second …

The Enskog Process For Hard And Soft Potentials, Martin Friesen, Barbara Rüdiger, Padmanabhan Sundar

Faculty Publications

The density of a moderately dense gas evolving in a vacuum is given by the solution of an Enskog equation. Recently we have constructed in Albeverio et al. (J Stat Phys 167:90–122, 2017) the stochastic process that corresponds to the Enskog equation under suitable conditions. The Enskog process is identified as the solution of a McKean–Vlasov equation driven by a Poisson random measure. In this work, we continue the study for a wider class of collision kernels that includes hard and soft potentials. Based on a suitable particle approximation of binary collisions, the existence of an Enskog process is established.

Hopf Algebras Of Prime Dimension In Positive Characteristic, Siu Hung Ng, Xingting Wang

Faculty Publications

We prove that a Hopf algebra of prime dimension p over an algebraically closed field, whose characteristic is equal to p, is either a group algebra or a restricted universal enveloping algebra. Moreover, we show that any Hopf algebra of prime dimension p over a field of characteristic q > 0 is commutative and cocommutative when q = 2 or p < 4q. This problem remains open in positive characteristic when 2 < q < p/4.

Increasing C-Additive Processes, Nadjib Bouzar

Communications on Stochastic Analysis

No abstract provided.

A Limiting Process To Invert The Gauss-Radon Transform, Jeremy J. Becnel

Communications on Stochastic Analysis

No abstract provided.

Spectral Theorem Approach To The Characteristic Function Of Quantum Observables, Andreas Boukas, Philip J. Feinsilver

Communications on Stochastic Analysis

No abstract provided.

Smoothing Parameters For Recursive Kernel Density Estimators Under Censoring, Yousri Slaoui

Communications on Stochastic Analysis

No abstract provided.

Strong Convergence Rate In Averaging Principle For The Heat Equation Driven By A General Stochastic Measure, Vadym Radchenko

Communications on Stochastic Analysis

No abstract provided.

Fairness-Aware Energy-Efficient Resource Allocation In D2d Communication Networks, Shengjie Guo, Xiangwei Zhou, Sa Xiao, Mingxuan Sun

Faculty Publications

In this paper, the energy efficiency in a cellular network with device-to-device communications is studied from user fairness perspective. A mixed-integer max-min optimization problem is formulated, in which both mode selection and resource allocation are considered. Since the optimal solution requires exhaustive search, which is NP-hard, two suboptimal methods are derived. First, a Lagrangian decomposition-based method is proposed to jointly solve subcarrier assignment and power allocation with integer constraint relaxation under different modes. To further reduce the computational complexity, a low-complexity decomposition (LCD) method is derived. A novel mode selection scheme, a subcarrier assignment scheme, a power allocation scheme, and …

Predicting Climate Types For The Continental United States Using Unsupervised Clustering Techniques, D. Sathiaraj, X. Huang, J. Chen

Faculty Publications

The problem of clustering climate data observation sites and grouping them by their climate types is considered. Machine learning–based clustering algorithms are used in analyzing climate data time series from more than 3,000 climate observation sites in the United States, with the objective of classifying climate type for regions across the United States. Understanding the climate type of a region has applications in public health, environment, actuarial science, insurance, agriculture, and engineering. In this study, daily climate data measurements for temperature and precipitation from the time period 1946–2015 have been used. The daily data observations were grouped into three derived …

Classical Axisymmetric Gravity In Real Ashtekar Variables, Rodolfo Gambini, Esteban Mato, Javier Olmedo, Jorge Pullin

Faculty Publications

We formulate axisymmetric general relativity in terms of real Ashtekar-Barbero variables. We study the constraints and equations of motion and show how the Kerr, Schwarzschild and Minkowski solutions arise. We also discuss boundary conditions. This opens the possibility of a midisuperspace quantization using loop quantum gravity techniques for spacetimes with axial symmetry and time dependence.

Long-Term Dust Formation By Core Collapse Supernovae, Kelsie Marie Krafton

LSU Doctoral Dissertations

Studying long-term dust formation by CCSNe is an important step toward understanding the large dust masses found in early galaxies. The amazing new discovery of approximately a solar mass of cold dust in the ejecta of SN 1987A has caused a complete re-evaluation of dust formation in core collapse supernovae (CCSNe). CCSNe form only a small amount of dust after three years, but SN 1987A has a dust mass that is several orders of magnitude larger after 25 years. A recent study of SN 2010jl by Gall et al. (2014) made the fascinating suggestion that dust is continuously forming in …

Computational Feasibility Of Simulating Whole-Organ Vascular Networks And Their Response To Injury, William Patrick Donahue

LSU Doctoral Dissertations

Healthy vasculature is critical to sustaining the function of normal tissues in the human body. Radiation therapy for cancer causes injury of the vasculature of non-cancerous tissues. These changes have been associated with potentially deadly conditions such as necrosis of the brain tissue. There are currently no computational methods to study the effects of radiation vascular injury in whole-organ vasculatures because of the large number of vessels involved. The goal of this work was to test the feasibility of simulating radiation damage to whole-brain vascular networks and calculate the resulting change in blood flow. To accomplish this, we developed algorithms …