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Editorial - Un Paso A La Vez, Mauricio Rangel Jiménez

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 …

Neural Correlates Of Post-Traumatic Brain Injury (Tbi) Attention Deficits In Children, Meng Cao

Dissertations

Traumatic brain injury (TBI) in children is a major public health concern worldwide. Attention deficits are among the most common neurocognitive and behavioral consequences in children post-TBI which have significant negative impacts on their educational and social outcomes and compromise the quality of their lives. However, there is a paucity of evidence to guide the optimal treatment strategies of attention deficit related symptoms in children post-TBI due to the lack of understanding regarding its neurobiological substrate. Thus, it is critical to understand the neural mechanisms associated with TBI-induced attention deficits in children so that more refined and tailored strategies can …

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 …

Pbm And Dem Simulations Of Large-Scale Closed-Circuit Continuous Ball Mill Of Cement Clinker, Nontawat Muanpaopong

Dissertations

Cement milling is known to be inefficient and energy-intensive. Thus, even small improvements in cement milling's performance could significantly reduce operation costs. This dissertation aims to develop a simulation tool for dry milling and generate a fundamental process understanding, which enables process optimization. To this end, a true unsteady-state simulator (TUSSIM) for continuous dry milling is developed and applied to model various processes: (a) open circuit continuous mills, (b) closed-circuit continuous mills, and (c) vertical roller mills. TUSSIM is based on the solution of the cell-based population balance model (PBM) for continuous milling, which consists of a set of differential …

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 …

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 …

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 - …

Large-Scale And Meso-Scale Ion Dynamics Of The Near-Earth Space Environment, Matthew Cooper

Dissertations

The mechanisms whereby low energy (order of lOs to 100s of eV) solar wind and ionosphere sourced particles are accelerated to high energy (order of 10s to 100s keV) in the Earth's magnetosphere are a trending research topic due to impacts on radiation belt populations, coupling to the high-latitude ionosphere, and energy budgets for collision-less plasma in dipole fields. Ultra-low frequency (ULF, order of 1-100 mHz) Alfven waves observed in the nightside inner magnetosphere during geomagnetic activity are one such acceleration mechanism. Several source processes for these waves, including the micro-scale drift-mirror mode, have been previously suggested but observational evidence …

Design, Synthesis, Biological And Computational Studies Of Flavonoid Acetamide Derivatives, Daniel Kasungi Isika

Dissertations

Flavonoid compounds (FC) have extensive biological applications through potent antimicrobial, anti-inflammatory, anticancer, antidiabetic, and antioxidant properties. These applications are nevertheless limited by low bioavailability, poor aqueous solubility, enzymatic degradation, rapid metabolism, and fast body clearance. FC show unique structure-activity relationships (SARs) essential in assessing and mitigating the prevalent challenges impeding their applications. These challenges can be addressed by structural modification of the FC through functionalization of the phenolic rings, modification of the ketone group, and modification of the phenolic hydroxyl groups with bioisosteres.

The objectives of this work are to (i) design and synthesize novel flavonoid acetamide derivatives (FADs) and …

Topics On Asymmetric Classification, Subhrasish Chakraborty

Dissertations

Asymmetric classification refers to a situation where the cost of misclassifying one class is significantly higher than the cost of misclassifying the other class. This problem is common in many real-world scenarios, such as medical diagnosis or fraud detection. In this dissertation two of the common types of asymmetric classification problems have been dealt with — imbalanced classification and ordinal classification. An example of imbalanced classification is to detect fraudulent credit card transactions where the distribution of the normal and fraud transactions are extremely skewed. On the other hand, ordinal classification, also known as ordinal regression, is widely used in …

Domain Decomposition Methods For Linear And Non-Linear Elliptic Problems, Tadanaga Takahashi

Dissertations

The primary purpose of this dissertation is to expand upon the circle of domain decomposition methods (DDM) which are algorithms that reformulate a boundary value problem in terms of multiple localized problems on subdomains. The first project involves expanding upon DDMs in a relatively mature field: the Helmholtz equation for wave scattering applications. The proposed method is an adaptation of a continuous cross-point Finite Element Non-overlapping DDM algorithm. The usual unbounded computational domain is truncated and then the near-field wave pattern is solved with a parallelized finite element method. Several improvements over the standard transmission operator are discussed in this …

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.

Molecular Simulations Of Mechanical Effects Of Adsorption In Gas And Liquid Phases, Alina Emelianova

Dissertations

Fluids adsorbing in nanoporous solids cause high pressures that affect the solids and the properties of the fluids themselves. This work explores the mechanical response of solids to the adsorption of gas and liquid. Chapter 1 outlines the current achievements in investigating the mechanical response of adsorbents to the adsorption process, specifically, the computational approaches to predict adsorption-induced deformation. Chapter 2 introduces the theoretical and computational methods employed in this work. Chapters 3-7 address the design and application of the computational techniques for such prediction in different systems: mesoporous silica, microporous zeolites, and metal-organic frameworks, and Chapter 8 focuses on …

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, …

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 …

Multi-Physics Numerical Simulation Of Corrosion And Service Life Evaluation Of Novel Reinforced Concrete Systems, Jin Fan

Dissertations

Durability challenges of reinforced concrete materials can shorten the service life and increase the carbon footprint of civil infrastructure systems. Novel alternative materials, such as high-performance fiber reinforced cementitious composites (HPFRCCs) and recycled aggregate concrete (RAC), offer an alternative to tradi-tional concrete materials by increasing the service life of infrastructure or reducing raw material consumption, thereby reducing the life-cycle carbon footprint. Due, in part, to a lack of robust numerical tools, predicting the durability response of these emerging cementitious materials has been insufficiently addressed. A time-dependent multi-physics modeling framework is proposed and adopted to investigate the chloride induced deterioration mechanisms …

Development Of Novel Hybrid Structures For Fast Dissolution Of Hydrophobic Drugs, Mohammad Saiful Islam

Dissertations

Nanomaterials have proven to be highly effective in the design and development of biomedicine. Complementary nanostructured hybrid particles show great promise in drug delivery applications. By improving functionalization, the physicochemical properties of the particles can be enhanced resulting in a high surface area, tunable hydrophilicity and porosity. These characteristics can provide a suitable environment for drug encapsulation, biocompatibility, high drug loading, and customizable release capabilities.

The formulation of drugs with poor water solubility faces multiple challenges, such as insufficient dissolution and inconsistent therapeutic efficacy, particularly when administered orally over an extended period. To overcome these challenges, some of the beneficial …

Egg Drop Challenge, Admin Stem For Success

STEM for Success Resources

This interactive activity plan challenges students to build a container using limited materials that will protect a raw egg from a 4-6 foot drop.

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.

How To Create 3rd - 5th Grade Activity Plans, Admin Stem For Success

STEM for Success Showcase

This flier provides elementary school teacher with a guide for how to create science activities and labs for their students.

Cs 280: Programming Language Concepts​​, Bassel Arafeh

Computer Science Syllabi

No abstract provided.

Cs 608: Cryptography And Security, Fuad Hamidli

Computer Science Syllabi

No abstract provided.

Math 333-041, 042, 141, Summer 2023: Probability And Statistics, Mathematical Sciences Department

Mathematical Sciences Syllabi

No abstract provided.

Math 337-041, 141, Summer 2023: Linear Algebra, Peter Ward

Mathematical Sciences Syllabi

No abstract provided.