Physical Sciences and Mathematics Commons^™

Activity Patterns Of Whiptail Lizards (Aspidoscelis) Found In The Northern Chihuahuan Desert, Guillermo Alvarez

Open Access Theses & Dissertations

Traditional lizard pitfall traps were modified to allow organisms to escape, while collecting valuable ecological data. Modified camera traps were capable of detecting the same species as traditional traps in a semi-arid environment, without posing the associated mortality risks. Pitfall-camera traps were used to sample the activity of the Side-blotched Lizard (Uta stansburiana) and the Southwestern Fence Lizard (Sceloporus cowlesi) in an urban wetland during four continuous years. Evaluations on activity pattern and the activity overlap between the two species revealed extensive overlap, with minor but significant seasonal shifts mediating coexistence. Traps were also effective at detecting other reptiles, invertebrates, …

Investigating Seismicity And Structure Of The Pecos, Texas Region Of The Delaware Basin Using A Temporary Nodal Network, Jenna Lynn Faith

Open Access Theses & Dissertations

With increasing earthquakes in the Delaware Basin since 2009, earthquake studies, including accurate hypocenters, are critically needed in the Delaware Basin to identify the structures producing earthquakes, and to determine if they are related to unconventional petroleum development and production. In 2018, with funding from the Texas Seismological Network (TexNet), the University of Texas at El Paso deployed and maintained a nodal network of 25 Magseis Fairfield Z-Land Generation 2 5-Hz seismic nodes in the Pecos, Texas region of the Delaware Basin, known as The Pecos Array. The network was deployed from November 2018 until the beginning of January 2020, …

Computation-Assisted Molecular Discovery For Biomedical Applications: Seeking Small Molecules And Dna Sequences With High Affinity Target Binding, Payam Kelich

Open Access Theses & Dissertations

Binding affinity between two molecules is an essential property in drug and sensor discovery. Several computational and experimental methods exist to find molecules with high binding affinities to desired target molecules. These methods are often complementary, where fast computational methods can be used for the initial screening of molecules, and experimental methods can then screen and determine the molecules of interest and sometimes define the structures of bound complexes. After these steps, computational methods, like molecular dynamics (MD) simulations, can provide detailed insights into atomic interactions and binding, and machine learning approaches can analyze experiment-derived data to discern patterns and …

Green Analytical Methods For The Determination Of Perfluorocarboxylic Acids (Pfcas) And Fluorotelomer Alcohols (Ftohs) In Water, Ahsan Habib

Open Access Theses & Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a large group of synthetic organic compounds manufactured for their heat, water, and stain-resistant properties. PFAS can be found ubiquitously in the environment because they are widely used in everyday consumer products such as fast-food wrappers, non-stick cookware, stain-resistant products, cosmetics, aqueous film-forming foams, etc. As a result, PFAS are commonly detected in surface water, wastewater, and biosolids from wastewater treatment plants (WWTPs). These are the direct sources of PFAS contamination in drinking water supplies, which are substantial sources of human exposure. Among these PFAS chemicals, two major groups are perfluoroalkyl carboxylic acids (PFCAs) …

Co2-Dependent Nanoscale Organization In Bulk And Interfacial Carbon Dioxide Capture Liquids Elucidated Using X-Ray Scattering, Daniel Eduardo Moran

Open Access Theses & Dissertations

The pressing need to control carbon dioxide emissions has propelled extensive research efforts employing a variety of approaches across the globe. In flue-gas recovery of CO2, the water-lean amine-based solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (2-EEMPA), has shown exceptional performance. Recent studies show that 2-EEMPA exhibits intermediate-range order (IRO), beyond the first nearest neighbor length scale, consisting of tetrameric clusters. In view of the need to find solutions for direct air capture (DAC) of CO2, this system may represent a critical linkage in a DAC strategy, yet structural insights on EEMPA's behavior at solid surfaces are still lacking. To this end, we applied the …

Using Shallow Electromagnetic And Magnetic Techniques To Map Soil Texture And Characterize Salinity And Water Dynamics Below Pecan Orchards, El Paso County, Texas, Kristina Sasser

Open Access Theses & Dissertations

Non-invasive, near surface geophysical tools provide a time efficient and cost-effective approach to study the shallow subsurface. Electromagnetic induction (EMI) instruments are a category of these near surface methods that provide spatial and temporal information (2-D to 4-D) about shallow (<6 m) subsurface properties, from which soil salinity, clay content, and water content can be estimated. However, deconstructing soil apparent electrical conductivity (ECa) from EMI methods into its component parts remains a challenge. This research uses EMI and magnetic geophysical techniques to: (1) compare and contrast the distribution and behavior of ECa, both spatially and temporally, at two flood irrigated agricultural sites (pecan orchards) with different soil layers, properties, and controls on electrical conductivities that lie within the same floodplain in far west Texas; and (2) develop a one-dimensional inversion model using ECa and soil texture data at specified layers from established sites of known high and low ECa to determine soil layer resistivities at various dates during the irrigation season. Data are compared to soil sensor bulk EC and volumetric water content data at corresponding depths to validate results. Soils at both sites exhibit large ECa contributions from textural controls, and irrigation frequency. The combination of these two controls dictate where and how quickly secondary minerals precipitate, clog soil pores, reduce infiltration, and salinize the groundwater. Insight from this research aids in ongoing efforts to characterize vadose zone hydrology in dryland critical zones with high infiltration and serves as a guide for locations where future soil sampling will occur.

Diverse Impacts Of Commercial Ev Charging Load Infrastructure On Electric Power Grid, Antonio Avila

Open Access Theses & Dissertations

With the rising prominence of electric vehicles (EVs) in the transportation sector, this thesis delves into the critical nexus between commercial EVs, charging infrastructure, and their consequential impacts on the power grid. As commercial EVs, particularly medium and heavy-duty variants, gain traction as viable alternatives in the commercial transportation landscape, understanding the intricacies of their charging requirements becomes paramount. This thesis critically examines the technological and logistical dimensions of the charging infrastructure for supporting commercial EVs, evaluating the consequential implications on the power grid and proposing strategies for mitigation through the utilization of Distributed Energy Resources (DERs). In tandem with …

Viability Of Magnetic Nanoparticles For Magnetic Hyperthermia Cancer Therapy, Marcos Adrian Garcia

Open Access Theses & Dissertations

Over the last few decades magnetic nanoparticles have gained an extraordinary amount of attention in the science community. Their versatile use in many different research areas such as medicine, engineering and technology and many other areas has made them a popular subject. In this thesis, the synthesis of different systems of magnetic nanoparticles will be explored along with the potential use of the MNP's as viable candidates for Magnetic Hyperthermia Cancer Therapy. With values of over 200 emu/g for Iron-Silver magnetic nanoparticles with particle sizes ranging from 30-70nm and their heating properties under an AC magnetic field. As well of …

Study Of Human Circadian Protein (Hrory) And Lipid-Protein Interaction In Giant Virus (Pbcv-1), Laila Noor

Open Access Theses & Dissertations

Project 1: Circadian rhythm is a 24-hour cycle that regulates physical and behavioral changes such as sleep-wake patterns in humans, tailoring the daily light and dark changes. Long-term disruption in circadian rhythms can cause sleep disorders such as sleep apnea, insomnia, et al. Limited research has been done on potential drugs to treat against circadian related sleep disorders. Inside the cell at molecular level, the circadian rhythm is regulated by interlocked time-delayed feedback loops, which involve positive and negative transcriptional regulators. Experimental results showed transcriptional factors Retinoic Acid Receptor-Related Orphan Receptors (RORs) improve the stability and functionality of the circadian …

Towards Explaining Neural Networks: Tools For Visualizing Activations And Parameters, Juan Puebla

Open Access Theses & Dissertations

There is a growing number of applications using neural networks for making decisions. However, there is a general lack of understanding of how neural networks work. Neural networks have even been described as black boxes which has led to a lack of trust in artificially intelligent programs. To remedy this, explainable artificial intelligence has risen as a means to validate the decision-making processes and the results of computer programs that use artificial intelligence. The work in this masterâ??s thesis is our contribution to explainable artificial intelligence, focusing on neural networks with the goal of helping users make more sense of …

Upcyclying Of Polyethylene Terephtalate By Addition Of Thermoplastic Elastomer, Diego Francisco Bermudez

Open Access Theses & Dissertations

Continual overconsumption of single-use plastics has generated challenges of solid waste management across the United States. Common plastic waste management solutions, such as landfill, have caused the migration of contaminants into the environment consequently affecting not only the health of wildlife, but also that of human beings. Alternative strategies for the handling of single-use plastic such as polyethylene terephthalate (PET), used in the food packaging industry, can ultimately help mitigate the noxious consequences of single-use plastics affecting entire ecosystems. This study demonstrates a potential avenue of materials upcycling by studying the effects of coupling PET with the thermoplastic elastomer styrene-ethylene-butylene-styrene …

Synthesis And Characterization Of Acetaminophen-Derived Nanoparticles: A Novel Approach To Inhibit Fibril Formation, Hannia Elena Mendoza-Dickey

Open Access Theses & Dissertations

In the realm of nanotechnology, nanoparticles (NPs), have garnered significant notoriety in recent scientific research due to their unique physical and chemical properties, such as fluorescence emissions, nanoscale dimensions (typically <1000 nm), ease of surface modification, and biocompatibility. Nanoparticles have shown their potential across a variety of areas, including advanced industrial applications and cutting-edge biomedical research. Considering their cost-effective synthesis, they have shown promise as therapeutic agents for a variety of bioimaging and biomedical applications. This thesis describes the synthesis and detailed analysis of acetaminophen-derived nanoparticles. Techniques such as Dynamic Light Scattering (DLS), Thioflavin T (THT) assay, Attenuated Total Reflectance Infrared Spectroscopy (ATR-IR), 1H NMR spectroscopy, and Ultraviolet-Visible Spectroscopy (UV-VIS) were utilized for structural and functional assessments. Acetaminophen derived nanoparticles (ANPs) exhibit potential to hinder the amyloidogenic conversion of soluble amyloid-forming proteins into their toxic form. The novelty of this research focuses on the utilization of chemical structures capable of traversing the Blood Brain Barrier (BBB) to mitigate xenotoxicant-induced neuronal damage, a notable contributor to neurodegenerative disorders. This thesis describes the synthesis and characterization of acetaminophen derived-nanoparticles (ANPs). Our nanoparticles possess anti-amyloidogenic properties as evidenced by their ability to disrupt in the soluble-to-toxic trajectory of HEWL. The prevalence and evolution of amyloid fibrils are consistent features in the pathology of neurodegenerative diseases such as Parkinson's disease (PD), Alzheimerâ??s Disease (AD), and Huntingtonâ??s Disease (HD), as well as metabolic disorders like Type 2 diabetes (T2D). The relationship between amyloidogenic pathways and these disorders highlights the imperative for enhanced understanding and the formulation of specific therapeutic interventions.

Intercomparison Of Planetary Boundary Layer Over El Paso-Juarez Region Using Vaisala Ceilometers, Vianey Arvilla

Open Access Theses & Dissertations

Vaisala ceilometers (models CL 31 and Cl 51) were used to monitor and study the planetary boundary layer (PBL). There were four ceilometer stations that we connected to create the Paso del Norte ceilometer network. These stations are located at: UTEP, Socorro, Ivanhoe, and Juarez. This network has been automatized and its hourly averaged mean boundary layer height data is being downloaded into a computer accessible to TCEQ (Texas Commission on Environmental Quality) and to the public. In this study, data from each ceilometer was used to produce scatter plots. These scatter plots were analyzed to obtain the PBL heights …

Evaluation Of Evapotranspiration Estimates Using An Existing Hybrid Machine Learning Model In A Natural And A Managed Dryland Site, Katya Esquivel Herrera

Open Access Theses & Dissertations

Evapotranspiration (ET) is a critical component of the hydrologic cycle, encompassing both evaporative water loss from surfaces and transpiration through plant stomata. The environmental factors influencing ET include water and energy availability, atmospheric capacity for water uptake, and various meteorological variables. ET serves as a unique climate variable linking water, energy, and carbon cycles. In agroecosystems, accurate ET quantification is vital for optimizing water use efficiency, irrigation management, and crop yield. Traditional methods for ET estimation involve direct measurements and indirect models, with both presenting limitations.

Recent years have witnessed the integration of remote sensing and machine learning (ML) algorithms …

A Noninvasive Urine-Based Method For Kidney Cancer Early Detection, Kiana Holbrook

Open Access Theses & Dissertations

Based on the traditional serological uses to obtain diagnoses of cancer and biopsy techniques, common cancer detection could be not only invasive but expensive and some tests are also unreliable. Currently, urine is one of the most frequently used and collected specimens in the clinical diagnoses. While the areas of urinalysis and metabolomic profiling has received interest in the top clinical research, there are limited components to the validity, specificity, as well as sensitivity of endogenous urine substrates to detect early stages of cancers. Although there is research showcasing that urine is impacted by age, cancer type, geographical location, and …

Bitcoin's Technical Foundation And Its Potential For A Decentralized And Environmentally Friendly Future, Iqtiar Md Siddique

Open Access Theses & Dissertations

This research examines a systematic analysis of Bitcoin, employing a Coefficient of Variation (CV) approach to gauge its degree of decentralization. Bitcoin, an innovative decentralized digital currency, has received much attention for its potential to revolutionize traditional financial systems. This study employs the Coefficient of Variation (CV) to acquire insights into the wealth distribution and concentration among Bitcoin users. This research demonstrates how decentralized the network of Bitcoin is. The methodology uses real data on Bitcoin addresses and their holdings to compute the Coefficient of Variation (CV). This approach provides valuable insights into the ongoing discourse surrounding Bitcoin's decentralization, offering …

Preliminary Assessment For Critical Minerals In The Terlingua Quicksilver District, Texas And Tres Marias Mine, Chihuahua, Mexico, Eduardo Lee Zuniga

Open Access Theses & Dissertations

The Terlingua Quicksilver district was discovered around the 1880s and was a mercury producing district from 1900 through 1946. The most productive years were during World War one and two. From 1900-1946 the Terlingua Quicksilver District (TQD) produced 150,000 flasks; 80% came from three mines: the Rainbow-Chisos, Mariposa, and Study Butte mines. The structural controls of the Mercury mineralization within these mines are breccia pipes and fractures, often located near igneous intrusions. This study will assess the potential for Critical Minerals and Rare Earth Elements in the Terlingua Quicksilver District. Fifty-five samples have been collected and analyzed for forty-four different …

Why Sigmoid Transformation Helps Incorporate Logic Into Deep Learning: A Theoretical Explanation, Chitta Baral, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional neural networks start from the data, they cannot easily handle prior knowledge -- this is one of the reasons why they often take very long to train. It is desirable to incorporate prior knowledge into deep learning. For the case when this knowledge consists of propositional statements, a successful way to incorporate this knowledge was proposed in a recent paper by van Krieken et al. That paper uses the fact that a neural network does not directly return a truth value, it returns a real value -- in effect, the degree of confidence in the corresponding statement -- from …

Effect Of Self-Interaction Correction On Molecular Polarizabilities And Core Ionization Energies, Sharmin Akter

Open Access Theses & Dissertations

Density Functional Theory (DFT) is one of the most successful and popular computational Quantum Mechanical approaches to understanding materials. DFT allows the prediction of material properties from the electron density. Although in principle, density functional theory is exact, it, however, relies on approximate functional for exchange-correlation energy. Due to the approximate nature of the exchange-correlation functional, the self-Coulomb energy of the electrons is not exactly canceled out by the self-exchange, leading to the spurious self-interaction error (SIE). Due to this error, the potential shows incorrect behavior which leads to errors in calculated properties such as ionization energies, electron affinities, polarizabilities, …

Addressing Binational Issues For Water Quality Along The United States-Mexico Border And The Use Of The 1944 Water Treaty As A Means For Developing Transboundary Aquifer Agreements, Gilbert Anaya

Open Access Theses & Dissertations

The water resources of the United States (U.S.) and Mexico are under tremendous pressure due to declining reservoir levels, changes in climate, and prolonged drought. The U.S.-Mexico border region relies on the Rio Grande and Colorado River, and shared groundwater resources that are transboundary in nature. These resources are vital to the U.S.-Mexico border and are susceptible to drought that leads to reduced flow and allocation to the users. In addition, there are impacts to water quality caused by return flows and from failing sanitation infrastructure. In this study, we focus on 1) the contribution of springs in an area …

Context-Aware Temporal Embeddings For Text And Video Data, Ahnaf Farhan

Open Access Theses & Dissertations

Recent years have seen an exponential increase in unstructured data, primarily in the form of text, images, and videos. Extracting useful features and trends from large-scale unstructured datasets -- such as news outlets, scientific papers, and videos like security cameras or body cam recordings -- is faced with substantial challenges of volume, scalability, complexity, and semantic understanding. In analyzing trends, comprehending the temporal context is vital for uncovering patterns and narratives that are not apparent from a single video frame or text document. Despite its importance, many existing data mining and machine learning approaches overlook extracting evolutionary contextual features in …

Integrating Machine Learning Methods For Medical Diagnosis, Jazmin Quezada

Open Access Theses & Dissertations

Abstract:The rapid advancement of machine learning techniques has revolutionized the field of medical diagnosis by offering powerful tools to analyze complex data sets and make accurate predictions. In this proposed method, we present a novel approach that integrates machine learning and optimization models to enhance the accuracy of medical diagnoses. Our method focuses on fine-tuning and optimizing the parameters of machine learning algorithms commonly used in medical diagnosis, such as logistic regression, support vector machines, and neural networks. By employing optimization techniques, we systematically explore the parameter space of these algorithms to discover the most optimal configurations. Moreover, by representing …

From Type-2 Fuzzy To Type-2 Intervals And Type-2 Probabilities, Vladik Kreinovich, Olga Kosheleva, Luc Longpré

Departmental Technical Reports (CS)

Our knowledge comes from observations, measurements, and expert opinions. Measurements and observations are never 100% accurate, there is always a difference between the measurement result and the actual value of the corresponding quantity. We gauge the resulting uncertainty either by an interval of possible values, or by a probability distribution on the set of possible values, or by a membership function that describes to what extent different values are possible. The information about uncertainty also comes either from measurements or from expert estimates and is, therefore, also uncertain. It is important to take such "type-2" uncertainty into account. This is …

Which Random-Set Representation Of A Fuzzy Set Is The Simplest?, Vladik Kreinovich, Olga Kosheleva, Hung T. Nguyen

Departmental Technical Reports (CS)

One of the ways to elicit membership degrees is by polling. For example, we ask a group of people how many believe that 30 C is hot. If 8 out of ten say that it is hot, we assign the degree 8/10 to the statement "30 C is hot". In precise mathematical terms, polling can be described via so-called random sets. It is known that every fuzzy set can be obtained this way, i.e., that every fuzzy set can be represented by an appropriate random set. Moreover, it is known that for many fuzzy sets, there are several different random-set …

Uncertainty Quantification For Results Of Ai-Based Data Processing: Towards More Feasible Algorithms, Christoph Q. Lauter, Martine Ceberio, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

AI techniques have been actively and successfully used in data processing. This tendency started with fuzzy techniques, now neural network techniques are actively used. With each new technique comes the need for the corresponding uncertainty quantification (UQ). In principle, for both fuzzy and neural techniques, we can use the usual UQ methods -- however, these techniques often require an unrealistic amount of computation time. In this paper, we show that in both cases, we can use specific features of the corresponding techniques to drastically speed up the corresponding computations.

Giant Footprints Of Buddha And Generalized Limits, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

In many places in Asia, there are footprints claimed to be left by Buddha. Many of them are much larger than the usual size of human feet, up to 150 cm and more in length. In this paper, we provide a possible mathematical explanation for such unusual sizes.

Usually, Either Left And Right Brains Are Equally Active Or Only One Of Them Is Active: First-Principles Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that in most practical situations, either both left and right brains are equally active, or only one of them is active. A recent paper showed that this empirical phenomenon can be explained by a realistic model of the brain effectiveness. In this paper, we show that this conclusion can be made without any specific assumptions about the brain, based on first principles.

How To Efficiently Propagate P-Box Uncertainty, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, to get the desired estimate or prediction, we need to process existing data. This data usually comes from measurements, and measurements are never 100% accurate. Because we only know the input values with uncertainty, the results of processing this data also comes with uncertainty. To make an appropriate decision, we need to know how accurate is the resulting estimate, i.e., how the input uncertainty "propagates" through the data processing algorithm. In the ideal case, when we know the probability distribution of each measurement error, we can, in principle, use Monte-Carlo simulations to describe the uncertainty of …

How To Deal With Inconsistent Intervals: Utility-Based Approach Can Overcome The Limitations Of The Purely Probability-Based Approach, Kittawit Autchariyapanitkul, Tomoe Entani, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many application areas, we rely on experts to estimate the numerical values of some quantities. Experts can provide not only the estimates themselves, they can also estimate the accuracies of their estimates -- i.e., in effect, they provide an interval of possible values of the quantity of interest. To get a more accurate estimate, it is reasonable to ask several experts -- and to take the intersection of the resulting intervals. In some cases, however, experts overestimate the accuracy of their estimates, their intervals are too narrow -- so narrow that they are inconsistent: their intersection is empty. In …

Why Micro-Funding? Why Small Businesses Are Important? Analysis Based On First Principles, Hein D. Tran, Edwin Tomy George, Vladik Kreinovich

Departmental Technical Reports (CS)

On the one hand, in economics, there is a well-known and well-studied economy of scale: when two smaller companies merge, it lowers their costs and thus, makes them more effective and therefore more competitive. At first glance, this advantage of big size would make economy dominated by big companies -- but in reality, small business remain a significant and important economic sector. Similarly, it is well known and well studied that research collaboration enhances researchers' productivity -- but still a significant portion of important results come from individual efforts. In several applications areas, there are area-specific explanations for this seemingly …