Physical Sciences and Mathematics Commons^™

Toward Smart And Efficient Scientific Data Management, Jinzhen Wang

Dissertations

Scientific research generates vast amounts of data, and the scale of data has significantly increased with advancements in scientific applications. To manage this data effectively, lossy data compression techniques are necessary to reduce storage and transmission costs. Nevertheless, the use of lossy compression introduces uncertainties related to its performance. This dissertation aims to answer key questions surrounding lossy data compression, such as how the performance changes, how much reduction can be achieved, and how to optimize these techniques for modern scientific data management workflows.

One of the major challenges in adopting lossy compression techniques is the trade-off between data accuracy …

Data-Driven 2d Materials Discovery For Next-Generation Electronics, Zeyu Zhang

Dissertations

The development of material discovery and design has lasted centuries in human history. After the concept of modern chemistry and material science was established, the strategy of material discovery relies on the experiments. Such a strategy becomes expensive and time-consuming with the increasing number of materials nowadays. Therefore, a novel strategy that is faster and more comprehensive is urgently needed. In this dissertation, an experiment-guided material discovery strategy is developed and explained using metal-organic frameworks (MOFs) as instances. The advent of 7r-stacked layered MOFs, which offer electrical conductivity on top of permanent porosity and high surface area, opened up new …

Variable Resolution Smoothed Particle Hydrodynamics Schemes For 2-D And 3-D Viscous Flows, Francesco Ricci

Dissertations

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian particle-based method for the numerical solution of the partial differential equations that govern the motion of fluids. The main aim of this thesis work is to better enable the applicability of SPH to problems involving multi-scale fluid dynamics. In the first part of the thesis, the capability of the SPH method to simulate three-dimensional isotropic turbulence is investigated with a detailed comparison of Lagrangian and Eulerian SPH formulations. The main reason for this first investigation is to provide an assessment of the error introduced by the particle disorder on the SPH discrete operators …

Computational And Experimental Investigation Of Elemental Sulfur And Polysulfide, Jyoti Sharma

Dissertations

Petroleum processing results in the generation of significant quantities of elemental sulfur (S₈), leading to a surplus of sulfur worldwide. Despite its abundance and low cost, the use of sulfur in value-added organic compound synthesis is limited due to its unpredictable and misunderstood reactivity. This dissertation aims to address this issue by tackling it from two angles. Firstly, by utilizing Density Functional Theory (DFT) calculations, the reactivity of sulfur in the presence of nucleophiles is studied. This facilitates the identification of organic polysulfide intermediates that can be generated under different conditions, as well as the corresponding reactivity for …

Shared Fantasy: Role-Playing Games As Social Worlds By Gary Alan Fine (2002) [Reseña], Cristo Leon

Journal of Roleplaying Studies and STEAM

This classic study still provides one of the most acute descriptions available of an often misunderstood subculture: that of fantasy role playing games like Dungeons & Dragons. Gary Alan Fine immerses himself in several different gaming systems, offering insightful details on the nature of the games and the patterns of interaction among players—as well as their reasons for playing.

Este estudio clásico todavía proporciona una de las descripciones más agudas disponibles de una subcultura a menudo incomprendida: la de los juegos de rol de fantasía como Dungeons & Dragons. Gary Alan Fine se sumerge en varios sistemas de juego diferentes …

Editorial - Un Paso A La Vez, Mauricio Rangel

Journal of Roleplaying Studies and STEAM

Editorial - Un paso a la vez

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 2 [2023], Issue 1., Cristo Leon, Felipe Ignacio García-Soriano, Francisca Faret Moreno, Daniel S. González Cohens, Daniel Serrano Robles, Daniel Romero Benguigui, Ruben Darío Hernández Mendo

Journal of Roleplaying Studies and STEAM

Journal of Roleplaying Studies and STEAM (JRPSSTEAM) Vol. 2 [2023], Issue 1.

Machine Learning And Network Embedding Methods For Gene Co-Expression Networks, Niloofar Aghaieabiane

Dissertations

High-throughput technologies such as DNA microarrays and RNA-seq are used to measure the expression levels of large numbers of genes simultaneously. To support the extraction of biological knowledge, individual gene expression levels are transformed into Gene Co-expression Networks (GCNs). GCNs are analyzed to discover gene modules. GCN construction and analysis is a well-studied topic, for nearly two decades. While new types of sequencing and the corresponding data are now available, the software package WGCNA and its most recent variants are still widely used, contributing to biological discovery.

The discovery of biologically significant modules of genes from raw expression data is …

Trustworthy Machine Learning Through The Lens Of Privacy And Security, Thi Kim Phung Lai

Dissertations

Nowadays, machine learning (ML) becomes ubiquitous and it is transforming society. However, there are still many incidents caused by ML-based systems when ML is deployed in real-world scenarios. Therefore, to allow wide adoption of ML in the real world, especially in critical applications such as healthcare, finance, etc., it is crucial to develop ML models that are not only accurate but also trustworthy (e.g., explainable, privacy-preserving, secure, and robust). Achieving trustworthy ML with different machine learning paradigms (e.g., deep learning, centralized learning, federated learning, etc.), and application domains (e.g., computer vision, natural language, human study, malware systems, etc.) is challenging, …

Ai Approaches To Understand Human Deceptions, Perceptions, And Perspectives In Social Media, Chih-Yuan Li

Dissertations

Social media platforms have created virtual space for sharing user generated information, connecting, and interacting among users. However, there are research and societal challenges: 1) The users are generating and sharing the disinformation 2) It is difficult to understand citizens' perceptions or opinions expressed on wide variety of topics; and 3) There are overloaded information and echo chamber problems without overall understanding of the different perspectives taken by different people or groups.

This dissertation addresses these three research challenges with advanced AI and Machine Learning approaches. To address the fake news, as deceptions on the facts, this dissertation presents Machine …

Mapping Programs To Equations, Hessamaldin Mohammadi

Dissertations

Extracting the function of a program from a static analysis of its source code is a valuable capability in software engineering; at a time when there is increasing talk of using AI (Artificial Intelligence) to generate software from natural language specifications, it becomes increasingly important to determine the exact function of software as written, to figure out what AI has understood the natural language specification to mean. For all its criticality, the ability to derive the domain-to-range function of a program has proved to be an elusive goal, due primarily to the difficulty of deriving the function of iterative statements. …

Importance Of Vegetation In Tsunami Mitigation: Evidence From Large Eddy Simulations With Fluid-Structure Interactions, Abhishek Mukherjee

Dissertations

Communities worldwide are increasingly interested in nature-based solutions like coastal forests for the mitigation of coastal risks. Still, it remains unclear how much protective benefit vegetation provides, particularly in the limit of highly energetic flows after tsunami impact. The present thesis, using a three-dimensional incompressible computational fluid dynamics model with a fluid-structure interaction approach, aims to quantify how energy reflection and dissipation vary with different degrees of rigidity and vegetation density of a coastal forest.

In this study, tree trunks are represented as cylinders, and the elastic modulus of hardwood trees such as pine or oak is used to characterize …

Continuum Modeling Of Active Nematics Via Data-Driven Equation Discovery, Connor Robertson

Dissertations

Data-driven modeling seeks to extract a parsimonious model for a physical system directly from measurement data. One of the most interpretable of these methods is Sparse Identification of Nonlinear Dynamics (SINDy), which selects a relatively sparse linear combination of model terms from a large set of (possibly nonlinear) candidates via optimization. This technique has shown promise for synthetic data generated by numerical simulations but the application of the techniques to real data is less developed. This dissertation applies SINDy to video data from a bio-inspired system of mictrotubule-motor protein assemblies, an example of nonequilibrium dynamics that has posed a significant …

V-Shaped Temperature Dependences And Pressure Dependence Of Elementary Reactions Of Hydroxyl Radicals With Several Organophosphorus Compounds, Xiaokai Zhang

Dissertations

Organophosphorus compounds have brought increasing attention since they are widely used as flame-retardants, which can take effect in combustion via reactions with reactive radicals. These reactions are influenced by variables such as temperature and pressure, resulting in a temperature and pressure dependent rate constant. Studying this reaction kinetics has great importance in both combustion reaction and atmospheric environment.

This study is focused on kinetics of several elementary reactions of combustion importance. The kinetics of hydroxyl radicals were studied using pulsed laser photolysis coupled to transient UV-vis absorption spectroscopy over the 295 - 837 K temperature range and the 1 - …

Coronal Magnetometry And Energy Release In Solar Flares, Yuqian Wei

Dissertations

As the most energetic explosive events in the solar system and a major driver for space weather, solar flares need to be thoroughly understood. However, where and how the free magnetic energy stored in the corona is released to power the solar flares remains not well understood. This lack of understanding is, in part, due to the paucity of coronal magnetic field measurements and the lack of comprehensive understanding of nonthermal particles produced by solar flares. This dissertation focuses on studies that utilize microwave imaging spectroscopy observations made by the Expanded Owens Valley Solar Array (EOVSA) to diagnose the nonthermal …

Deep Hybrid Modeling Of Neuronal Dynamics Using Generative Adversarial Networks, Soheil Saghafi

Dissertations

Mechanistic modeling and machine learning methods are powerful techniques for approximating biological systems and making accurate predictions from data. However, when used in isolation these approaches suffer from distinct shortcomings: model and parameter uncertainty limit mechanistic modeling, whereas machine learning methods disregard the underlying biophysical mechanisms. This dissertation constructs Deep Hybrid Models that address these shortcomings by combining deep learning with mechanistic modeling. In particular, this dissertation uses Generative Adversarial Networks (GANs) to provide an inverse mapping of data to mechanistic models and identifies the distributions of mechanistic model parameters coherent to the data.

Chapter 1 provides background information on …

A Survey On Online Matching And Ad Allocation, Ryan Lee

Theses

One of the classical problems in graph theory is matching. Given an undirected graph, find a matching which is a set of edges without common vertices. In 1990s, Richard Karp, Umesh Vazirani, and Vijay Vazirani would be the first computer scientists to use matchings for online algorithms [8]. In our domain, an online algorithm operates in the online setting where a bipartite graph is given. On one side of the graph there is a set of advertisers and on the other side we have a set of impressions. During the online phase, multiple impressions will arrive and the objective of …

A Computational Study Of Adsorptive Desulfurization In Metal Organic Frameworks, Kyle Concha

Theses

Fossil fuel usage has been related to several concerns about the environment and human health. One of these concerns is related to fuels containing Organic Sulfur Compounds (OSCs) which upon burning produce hazardous compounds such as SO₂ which contributes to acid rain and affects respiratory health. Removal of these OSCs is an important field of study as it can prevent the production of SO_x compounds. One technique to remove OSCs is Adsorptive Desulfurization (ADS) in which Metal Organic Frameworks (MOFs) are potential candidates to be used as adsorbents. Two archetypal MOFs, HKUST-1 and Cu₃HHTP₂, …

Bright Light Therapy And Depression: Assessing Suitability Using Entrainment Maps, Charles A. Mainwaring

Theses

Bright Light Therapy has been shown to be efficacious to mood disorders including Major Depression. Researchers use the Jewett-Forger-Kronauer model of the circadian rhythm with the Unified Model of melatonin including a mathematical term implementing feedback from the melatonin system into the circadian system to quantify the effects of bright light. Early investigations into intrinsic period, light sensitivity, and the circadian pacemaker's sensitivity to blood melatonin concentration may be indicators of subsets of patients with long intrinsic periods exhibiting symptoms of depression.

Cooking With Chemistry: Marshmallows, Admin Stem For Success

STEM for Success Showcase

This lesson plan teaches students thermodynamics, foam, and other chemistry topics by cooking marshmallows.

Magnetic Slime, Admin Stem For Success

STEM for Success Showcase

Students learn chemistry and physics by making magnetic slime.

Earthquake Resistant Buildings, Admin Stem For Success

STEM for Success Showcase

Students learn about earthquakes and engineering by building a structure that can survive an earthquake.

Invisible Ink, Admin Stem For Success

STEM for Success Showcase

Students create invisible ink to hide and reveal a message using chemistry.

Goonie Shooters Activity, Admin Stem For Success

STEM for Success Showcase

Students are asked to design a "Goon Shooter" to launch "goons" as far as possible.

Lesson Plans In Astronomy, Ecology And Biology, Admin Stem For Success

STEM for Success Showcase

This document contains various lesson plan ideas for concepts within the fields of biology, ecology, astronomy, and geology.

Candy Heart Experiment, Admin Stem For Success

STEM for Success Showcase

Students practice the scientific process by running an experiment to discover how well candy hearts dissolve in different liquids.

Sleigh Race Project, Admin Stem For Success

STEM for Success Showcase

Students use their knowledge of physics and design to build both a sleigh and a slope for the sleigh to travel on.

Basketballs And Energy, Admin Stem For Success

STEM for Success Showcase

No abstract provided.

Nail Steam Activity, Admin Stem For Success, Natalie Wilson

STEM for Success Showcase

Activity where students use nails to practice concepts relating to center of gravity

Rubber Band Car Activity, Admin Stem For Success, Natalie Wilson

STEM for Success Showcase

Student learn about forces and engineering by designing a car powered by rubber bands