Physical Sciences and Mathematics Commons^™

Why Two Fish Follow Each Other But Three Fish Form A School: A Symmetry-Based Explanation, Shahnaz Shahbazova, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Recent experiments with fish has shown an unexpected strange behavior: when two fish of the same species are placed in an aquarium, they start following each other, while when three fish are placed there, they form (approximately) an equilateral triangle, and move in the direction (approximately) orthogonal to this triangle. In this paper, we use natural symmetries -- such as rotations, shifts, and permutation of fish -- to show that this observed behavior is actually optimal. This behavior is not just optimal with respect to one specific optimality criterion, it is optimal with respect to any optimality criterion -- as …

Predictive Understanding Of Lake Water Temperature And Dissolved Oxygen Profiles Across The Red River Basin Through Interpretable Machine Learning, Isabela Suaza Sierra

Open Access Theses & Dissertations

Accurately predicting lake water temperature (LWT) and dissolved oxygen (DO) is crucial for determining threshold values of fish survivability under warmer global conditions, with recreational fishing in reservoirs significantly contributing to regional economies, such as $779 million and $1,891 million annually to the economies of Oklahoma and Texas, respectively. Current mathematical models for temperature and oxygen profiles, which incorporate multi-layer and turbulent mixing equations, are complex and challenging to parameterize, particularly due to uncertainties in acquiring sufficient data for training and validation. Leveraging the flexibility and information extraction power of machine learning (ML) methods, this master thesis aimed to set …

Fuzzy Ideas Explain Fechner Law And Help Detect Relation Between Objects In Video, Olga Kosheleva, Vladik Kreinovich, Ahnaf Farhan

Departmental Technical Reports (CS)

How to find relation between objects in a video? If two objects are closely related -- e.g., a computer and it mouse -- then they almost always appear together, and thus, their numbers of occurrences are close. However, simply computing the differences between numbers of occurrences is not a good idea: objects with 100 and 110 occurrences are most probably related, but objects with 1 and 5 occurrences probably not, although 5 − 1 is smaller than 110 − 100. A natural idea is, instead, to compute the difference between re-scaled numbers of occurrences, for an appropriate nonlinear re-scaling. In …

There Is Still Plenty Of Room At The Bottom: Feynman's Vision Of Quantum Computing 65 Years Later, Alexis Lupo, Vladik Kreinovich, Victor L. Timchenko, Yuriy P. Kondratenko

Departmental Technical Reports (CS)

In 1959, Nobelist Richard Feynman gave a talk titled "There's plenty of room at the bottom", in which he emphasized that, to drastically speed up computations, we need to make computer components much smaller -- all the way to the size of molecules, atoms, and even elementary particles. At this level, physics is no longer described by deterministic Newton's mechanics, it is described by probabilistic quantum laws. Because of this, computer designers started thinking how to design a reliable computer based on non-deterministic elements -- and this thinking eventually led to the modern ideas and algorithms of quantum computing. So, …

From Quantifying And Propagating Uncertainty To Quantifying And Propagating Both Uncertainty And Reliability: Practice-Motivated Approach To Measurement Planning And Data Processing, Niklas R. Winnewisser, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

When we process data, it is important to take into account that data comes with uncertainty. There exist techniques for quantifying uncertainty and propagating this uncertainty through the data processing algorithms. However, most of these techniques do not take into account that in real world, measuring instruments are not 100% reliable -- they sometimes malfunction and produce values which are far off from the measured values of the corresponding quantities. How can we take into account both uncertainty and reliability? In this paper, we consider several possible scenarios, and we show, for each scenario, what is the natural way to …

Every Feasibly Computable Reals-To-Reals Function Is Feasibly Uniformly Continuous, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that every computable function is continuous; moreover, it is computably continuous in the sense that for every ε > 0, we can compute δ > 0 such that δ-close inputs lead to ε-close outputs. It is also known that not all functions which are, in principle, computable, can actually be computed: indeed, the computation sometimes requires more time than the lifetime of the Universe. A natural question is thus: can the above known result about computable continuity of computable functions be extended to the case when we limit ourselves to feasible computations? In this paper, we prove that this …

From Normal Distribution To What? How To Best Describe Distributions With Known Skewness, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we only have partial information about the probability distribution -- e.g., all we know is its few moments. In such situations, it is desirable to select one of the possible probability distributions. A natural way to select a distribution from a given class of distributions is the maximum entropy approach. For the case when we know the first two moments, this approach selects the normal distribution. However, when we also know the third central moment -- corresponding to skewness -- a direct application of this approach does not work. Instead, practitioners use several heuristic techniques, techniques …

Creating A Positive Learning Environment: Preliminary Results, Kien H. Lim, Hilda Y. Sotelo

Departmental Papers (Math)

No abstract provided.

Investigating The Roles Of Plants, Fungi, And Biocrusts In Nutrient Movement Within Dryland Ecosystems, Catherine E. Cort

Open Access Theses & Dissertations

In dryland ecosystems, plant productivity and microbial decomposition are often separated in space and time due to the asynchronous availability of soil moisture and organic matter inputs. It has been proposed that fungi play a key functional role in connecting these cycles by facilitating movement of water, carbon (C), and nitrogen (N) through a network of shared hyphae between plant roots and biological soil crust (biocrust) communities at the soil surface. This connection, also known as the â??fungal loop,â?? effectively re-couples processes of nutrient release and uptake between primary producers and minimizes ecosystem N losses due to leaching, erosion, and …

Every Relu-Based Neural Network Can Be Described By A System Of Takagi-Sugeno Fuzzy Rules: A Theorem, Barnabas Bede, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While modern deep-learning neural networks are very successful, sometimes they make mistakes, and since their results are "black boxes" -- no explanation is provided -- it is difficult to determine which recommendations are erroneous. It is therefore desirable to make the resulting computations explainable, i.e., to describe their results by using commonsense rules. In this paper, we use "fuzzy" techniques -- techniques developed by Lotfi Zadeh to deal with commonsense rules formulated by using imprecise ("fuzzy") words from natural language -- to show that such a rule-based representation is always possible. Our result does not yet provide the desired explainability, …

Smooth Non-Additive Integrals And Measures And Their Potential Applications, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we explain why non-additive integrals and measures are needed, how non-additive integrals and measures are related, how to use them in decision making, and how they can help in fundamental physics. These four topics are covered, correspondingly, in Sections 2-5 of this paper.

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 …

If We Add Axiom Of Choice To Constructive Analysis, We Get Classical Arithmetic: An Exercise In Reverse Constructive Mathematics, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

A recent paper in Bulletin of Symbolic Logic reminded that the Axiom of Choice is, in general, false in constructive analysis. This result is an immediate consequence of a theorem -- first proved by Tseytin -- that every computable function is continuous. In this paper, we strengthen the result about the Axiom of Choice by proving that this axiom is as non-constructive as possible: namely, that if we add this axiom to constructive analysis, then we get full classical arithmetic.

When Is A Single "And"-Condition Enough?, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, there are several possible decisions. Any general recommendation means specifying, for each possible decision, conditions under which this decision is recommended. In some cases, a single "and"-condition is sufficient: e.g., a condition under which a patient is recommended to take aspirin is that "the patient has a fever and the patient does not have stomach trouble". In other cases, conditions are more complicated. A natural question is: when is a single "and"-condition enough? In this paper, we provide an answer to this question.

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, …

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 …

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 …

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 …

Niobate Nanosheet Catalysts For Cationic Dye Intercalation And Solar-Driven Water Photolysis, Cassandra Idona Monárrez-Grendahl

Open Access Theses & Dissertations

With the goal of creating efficient visible light photocatalysts for water photolysis, in this work we are exploring the synthesis of new porous oxide materials derived from potassium triniobate (KNb3O8) and titanium niobium oxide (KTiNbO5), which are layered wide band gap semiconductors. Generating hydrogen via direct water photolysis holds promise as a way to lower the cost of hydrogen gas production so it can be used as a renewable and clean alternative fuel. My group has demonstrated that layered semiconductor materials have the potential to enable the synthesis of new types of photocatalyst composites with customizable characteristics. In this work, …

Metrics For Comparison Of Complex Networks, Clarissa Reyes

Open Access Theses & Dissertations

Heuristic network statistics are used as a preliminary approach to identify change across networks. In networks where there is known node correspondence (KNC), conventional network comparison methods include taking a norm of the difference matrix, or calculating dissimilarity measures like DeltaCon and cut distance. Since different KNC measures provide varying insight to the network comparison problem, we propose employing Rank Score Characteristic Functions (RSCFs) and the rank-score process as a method for reaching a consensus when ranking quantified change across multiple pairs of networks â?? which is particularly useful for ranking change across subpopulations or subgraphs. Additionally, we propose a …

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.

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 …

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 …

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 …

Enhancing Our Understanding Of Ancient Oceans Through The Investigation Of Molybdenum Behavior Under Sulfidic Conditions, Rachel Faye Phillips

Open Access Theses & Dissertations

The most abundant trace metal in the ocean today, molybdenum (Mo), exhibits distinct behavior in oxygenated water, where it remains predominantly dissolved, compared to euxinic (i.e., oxygen-free and sulfidic) water, in which it is sequestered into the sediment. This dissimilar behavior allows us to use Mo concentrations and isotopic compositions in sediment to reconstruct marine oxygenation conditions throughout geologic history. However, Mo sequestration mechanisms under euxinic conditions remain unresolved, which limits the accuracy and precision of reconstructions made using Mo signatures in the rock record. For my doctoral research, I experimentally investigated abiotic and biotic Mo sequestration mechanisms under various …

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 …

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 …

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, …