Physical Sciences and Mathematics Commons^™

Accurately Valuing Blue Carbon Sequestration And Storage To Foster Coastal Conservation Via Evidence-Based Policymaking And Model Environmental Services Statute Methodologies, John Shelton Penton Jr

LSU Doctoral Dissertations

Blue carbon ecosystems, especially mangrove forests, provide one of nature’s most effective means for sequestering carbon from the atmosphere and storing it in subsurface soils. The six nearshore coastal morphologies found in tropical and subtropical regions each possess a conspicuous environmental signature that can be employed to accurately estimate and predict mangrove forests’ carbon storage in above-ground biomass, below-ground biomass, and the soils by system type. The consistent geomorphology and geophysical processes within each of these coastal environmental settings, that is, the wave and tidal forcings, the rate of coastal sediment accretions, nutrient load and limitations (e.g., nitrogen-to-phosphorus …

Dipole Cooperativity And Polarization Frustration Determine The Secondary Structure Distribution Of Short Alanine Peptides In Water, Ying Yuan, Feng Wang

Chemistry & Biochemistry Faculty Publications and Presentations

The physical driving forces for secondary structure preferences of hydrated alanine peptide are investigated with B3LYP-D3(BJ) and the adaptive force matching (AFM) method. The AFM fit to the DFT surface, ALA2022, provides excellent agreement with the nuclear magnetic resonance scalar coupling constants from experiments. In turn, the model is used to gain insight into the physical driving forces behind secondary structure preferences of hydrated peptides. DFT calculations with and without the Conductor-like Screening Model (COSMO) show that the α helix is stabilized by solvent polarization due to dipole cooperativity. The two adjacent amide groups in β strand form a near-planar …

Beyond News Values On Twitter: Predicting Factors That Drive User Engagement In News, Zhiyan Zhong

Dartmouth College Master’s Theses

When deciding on what news stories to cover, traditional journalism determines news values by following several elements of newsworthiness, such as impact, timeliness, and prominence. However, these guidelines do not always seem to correspond with the success of content on social media. As people are increasingly turning to social media for news, our research aims to understand and predict factors that drive user engagement for news on social media. In this study, we analyze news content published on Twitter, and examine a diverse set of characteristics like metrics retrieved from the Twitter API and semantics by natural language processing, including …

Computational Investigation Of Porphyrin-Based Host Design For Anions And Ion Pairs, Symphony Hill

Honors Theses

Little research has heretofore been devoted to studying the binding interactions between porphyrin-based molecular hosts and anions or ion pairs. Such interactions could be important in synthesizing molecules capable of detecting, binding, extracting, and transporting ions of biological, environmental, and industrial significance. With this in mind, computational studies of nine different porphyrin hosts were performed to examine the structural and binding properties of each molecule and potential ion guests. Using the Spartan computational chemistry software, each porphyrin was modeled and binding was tested with a number of ions of different shapes and sizes. Data was then collected regarding the distances …

Substituent Effect Analysis On Halogen Bonding Interactions, Summer Hanson

Honors Theses

This study was used to determine the significance of substituents placed on aromatic molecules and how electron-donating groups (EDG) and electron-withdrawing groups (EWG) affect the strength of the halogen bond. Each study involved the same substituents, each differing in electron-withdrawing and electron-donating capability. Five different systems were created on computational software to evaluate the distance between the halogen bond donor and halogen bond acceptor. In two studies, the goal was to find the best electron-donor on the halogen bond acceptor (donor of electron density) while the halogen bond donor remained constant. For one study, the goal was to determine the …

Evaluating Species-Specific Replenishment Solution Effects On Plant Growth And Root Zone Nutrients With Hydroponic Arugula (Eruca Sativa L.) And Basil (Ocimum Basilicum L.), Lauren L. Houston, Ryan W. Dickson, Matthew B. Bertucci, Trenton L. Roberts

Horticulture Faculty Publications and Presentations

Managing nutrients in recirculating solutions can be challenging in hydroponic production, and poor management practices can rapidly result in root zone nutrient imbalances in reduced yield. Using mass balance principles to formulate hydroponic replenishment solutions is a proposed strategy to reduce nutrient imbalances and the need to periodically replace the hydroponic solution. Objectives were to (1) formulate species-specific nutrient replenishment solutions for arugula (Eruca sativa L.) and basil (Ocimum basilicum L.) using mass balance principles and (2) evaluate the effects of using these replenishment solutions on plant growth and root zone nutrients over time. In the first experiment, …

An Exploration Of Computational Text Analysis Of Co-Design Discourse In A Research-Practice Partnership, Mei Tan, Victor R. Lee

Publications

In combination with contextualized human interpretation, computational text analysis offers a quantitative approach to interrogating the nature of participation and social positioning in discourse. Using meeting transcript data from the development of a co-design research-practice partnership, we examine the roles and forms of participation that contribute to an effective collaboration between a multileveled school system and researcher partners. We apply computational methods to explore the language of co-design and multi-stakeholder perspectives in support of educational improvement science efforts and our theoretical understanding of partnership roles. Results indicate participation patterns align with documented roles in co- design partnerships and highlight the …

Geometry And Coding: Introducing An Interactive And Integrated Mathematics-Computer Science Unit, Kimberly Beck, Jessica F. Shumway

Publications

As part of a collaborative project between Utah State University, the Cache County School District, and Stanford, instructional units were designed for fifth-grade students. These units integrated math concepts of geometrical shapes and computer science concepts of sequences, conditionals, and loops. One component of the unit was implemented in math classrooms by math teachers, and the other component was implemented in computer labs. This presentation will focus on the math unit as presented at the National Council of Teachers of Mathematics (NCTM-V).

Why Is Biomedical Informatics Hard? A Fundamental Framework

Faculty, Staff and Student Publications

Building on previous work to define the scientific discipline of biomedical informatics, we present a framework that categorizes fundamental challenges into groups based on data, information, and knowledge, along with the transitions between these levels. We define each level and argue that the framework provides a basis for separating informatics problems from non-informatics problems, identifying fundamental challenges in biomedical informatics, and provides guidance regarding the search for general, reusable solutions to informatics problems. We distinguish between processing data (symbols) and processing meaning. Computational systems, that are the basis for modern information technology (IT), process data. In contrast, many important challenges …

Convolutional Neural Network For Biomarker Discovery For Triple Negative Breast Cancer With Rna Sequencing Data, Anneliese Gonzalez, Zhongming Zhao, Jingchun Chen

Faculty, Staff and Student Publications

Triple negative breast cancers (TNBCs) are tumors with a poor treatment response and prognosis. In this study, we propose a new approach, candidate extraction from convolutional neural network (CNN) elements (CECE), for discovery of biomarkers for TNBCs. We used the GSE96058 and GSE81538 datasets to build a CNN model to classify TNBCs and non-TNBCs and used the model to make TNBC predictions for two additional datasets, the cancer genome atlas (TCGA) breast cancer RNA sequencing data and the data from Fudan University Shanghai Cancer Center (FUSCC). Using correctly predicted TNBCs from the GSE96058 and TCGA datasets, we calculated saliency maps …

Application Of An Ontology For Model Cards To Generate Computable Artifacts For Linking Machine Learning Information From Biomedical Research

Faculty, Staff and Student Publications

Model card reports provide a transparent description of machine learning models which includes information about their evaluation, limitations, intended use, etc. Federal health agencies have expressed an interest in model cards report for research studies using machine-learning based AI. Previously, we have developed an ontology model for model card reports to structure and formalize these reports. In this paper, we demonstrate a Java-based library (OWL API, FaCT++) that leverages our ontology to publish computable model card reports. We discuss future directions and other use cases that highlight applicability and feasibility of ontology-driven systems to support FAIR challenges.

De Novo Mutations Disturb Early Brain Development More Frequently Than Common Variants In Schizophrenia, Xiangning Chen, Zhongming Zhao

Faculty, Staff and Student Publications

Investigating functional, temporal, and cell-type expression features of mutations is important for understanding a complex disease. Here, we collected and analyzed common variants and de novo mutations (DNMs) in schizophrenia (SCZ). We collected 2,636 missense and loss-of-function (LoF) DNMs in 2,263 genes across 3,477 SCZ patients (SCZ-DNMs). We curated three gene lists: (a) SCZ-neuroGenes (159 genes), which are intolerant to LoF and missense DNMs and are neurologically important, (b) SCZ-moduleGenes (52 genes), which were derived from network analyses of SCZ-DNMs, and (c) SCZ-commonGenes (120 genes) from a recent GWAS as reference. To compare temporal gene expression, we used the BrainSpan …

Discerning Conversational Context In Online Health Communities For Personalized Digital Behavior Change Solutions Using Pragmatics To Reveal Intent In Social Media (Prism) Framework, Amy Franklin, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Online health communities (OHCs) have emerged as prominent platforms for behavior modification, and the digitization of online peer interactions has afforded researchers with unique opportunities to model multilevel mechanisms that drive behavior change. Existing studies, however, have been limited by a lack of methods that allow the capture of conversational context and socio-behavioral dynamics at scale, as manifested in these digital platforms.

OBJECTIVE: We develop, evaluate, and apply a novel methodological framework, Pragmatics to Reveal Intent in Social Media (PRISM), to facilitate granular characterization of peer interactions by combining multidimensional facets of human communication.

METHODS: We developed and applied …

K-8 Preservice Teachers’ Statistical Thinking When Determining Best Measure Of Center, Ha Nguyen, Eryn M. Stehr Maher, Gregory Chamblee, Sharon Taylor

Mathematical Sciences: Faculty Publications

The purpose of this study was to determine K-8 preservice teacher (PST) candidates’ statistical thinking when selecting the best center representation for the given data. Forty-four PSTs enrolled in a Statistics and Probability for K-8 Teachers course in a university located in the southeastern region of the United States were asked to complete a 2007 National Assessment of Educational Progress test item. All 44 PSTs’ data were qualitatively analyzed for correctness and statistical thinking strategies used. Findings were that most PSTs either incorrectly selected the mean, rather than median, as the best measure of center for the given data or …

Logic And Rationality, Rohit J. Parikh

Publications and Research

Logic aims at truth, or more accurately, at deriving some truths from other truths. But why are we interested in truth in the first place? Surely one reason is that relying on truth makes it easier to make better choices.

One could think of Game theory as a tool which bridges the gap between logic and rationality.

Decision theory - or single agent game theory tells us when to make the best choice in a game of us against nature. But nature has no desire to further or frustrate our efforts. Nature is mysterious but not malign. Things change when …

Engaging Students Through Conversational Chatbots And Digital Content: A Climate Action Perspective, Thomas Menkhoff, Benjamin Gan

Research Collection Lee Kong Chian School Of Business

In this case study, we report experiences deploying a conversational chatbot as a pre-class and post-class engagement tool for undergraduate students enrolled in sustainability-related courses aimed at educating them about the severity of climate change and the importance of climate action by offsetting one’s carbon footprint (e.g, by planting trees or mangroves in SEA). The intitiative supports the university’s sustainability efforts in general and our new sustainability major in particular aimed at helping students to achieve sustainability-related learning outcomes with reference to climate change and climate action (SDG 13), one of the 17 Sustainable Development Goals established by the United …

Polycyclic Aromatic Hydrocarbon (Pah) Contamination In Urban Soils: Testing And Management, Melissa Chilinski, Paul Grossl, Melanie Stock

All Current Publications

Polycyclic aromatic hydrocarbons (PAHs) are a large class of chemicals and common environmental pollutants. Understanding which PAHs and soil test levels may impact human health is an important aspect of gardening and micro-farming, particularly in urban environments that are at increased risk of soil contamination. Land use histories, such as sites associated with vehicle and industrial emissions, burning, and dumping, can elevate concentrations of PAHs in soils. This fact sheet provides instructions on assessing your site for PAHs that may present health risks to humans, testing the soil, and first steps for interpretation and management.

Analyzing Syntactic Constructs Of Java Programs With Machine Learning, Francisco Ortin, Guillermo Facundo, Miguel Garcia

Department of Computer Science Publications

The massive number of open-source projects in public repositories has notably increased in the last years. Such repositories represent valuable information to be mined for different purposes, such as documenting recurrent syntactic constructs, analyzing the particular constructs used by experts and beginners, using them to teach programming and to detect bad programming practices, and building programming tools such as decompilers, Integrated Development Environments or Intelligent Tutoring Systems. An inherent problem of source code is that its syntactic information is represented with tree structures, while traditional machine learning algorithms use -dimensional datasets. Therefore, we present a feature engineering process to translate …

Apparatus-Dependent Corrections To The Electron G-2 Revisited, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We revisit the derivation of the apparatus-dependent correction to the energy levels of quantum cyclotron states, as previously outlined [Boulware et al., Phys. Rev. D 32, 729 (1985)PRVDAQ0556-282110.1103/PhysRevD.32.729]. We evaluate the leading corrections to the axial, magnetron, cyclotron, and spin-projection-dependent energy levels due to the altered photon field quantization in the vicinity of a conducting wall. Our work significantly extends previous considerations. Quantum cyclotron states are used for the determination of the electron g factor in Penning traps. Our calculations show that the numerically largest apparatus-dependent corrections can be expected for the axial and magnetron frequencies, where they can be …

Phenotypic And Target-Based Drug Discovery, Angelica Veronica Carmona

Theses & Dissertations

Batten Disease or Neuronal Ceroid Lipofuscinosis (NCL) is a group of rare, fatal, inherited pediatric neurodegenerative lysosomal storage disorders. NCLs are characterized by intracellular accumulation of an auto-fluorescent lipopigment called ceroid lipofuscin and neurodegeneration. Several forms of NCLs exist, some of which share some of the same features and symptoms but vary in severity and onset of symptoms with respect to age. Some common symptoms include progressive loss of vision, mental and motor deterioration, epileptic seizures, premature death, and in the rare adult-onset, dementia. Subtypes of NCLs occur when one of 13 different genes are mutated, and only two subtypes …

Regulating Artificial Intelligence In International Investment Law, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

The interaction between artificial intelligence (AI) and international investment treaties is an uncharted territory of international law. Concerns over the national security, safety, and privacy implications of AI are spurring regulators into action around the world. States have imposed restrictions on data transfer, utilised automated decision-making, mandated algorithmic transparency, and limited market access. This article explores the interaction between AI regulation and standards of investment protection. It is argued that the current framework provides an unpredictable legal environment in which to adjudicate the contested norms and ethics of AI. Treaties should be recalibrated to reinforce their anti-protectionist origins, embed human-centric …

Design Of A Mini Leo Gnss Constellation And A Custom Gnss Signal Simulator Development, Mohamed Mohamed Yaser

Theses

This thesis is concerned with Low Earth Orbit (LEO) Global Navigation Satellite Systems (GNSS) constellations and signals, and how can they provide rapid Positioning, Navigation, and Timing (PNT) services for the emerging technologies. The first objective of this thesis is to perform a simulation of a new mini-LEO GNSS constellation at 1000 km and assess its performance in different scenarios. The second objective is to design a signal simulator for two signals that are propriety of the Global Navigation Satellite Augmentation Systems (GNSSaS), which are the BOC(2,2) and ATLBOC(7.5, BOC(2,2)) modulation schemes. To simulate the mini-LEO GNSS constellation, two software …

Data-Driven Modeling Of Student Performance In The Time Of Distance Learning, Iman Saad Megdadi

Theses

One of the important aspects that all academic institutions work towards improving is Student Performance. It is obviously the primary indicator of success or failure of institutions. Student performance predictions are vital to instructors and educational decision makers to help, across all levels, tailor learning according to the students’ needs. Therefore, it is essential for Higher Education Institutions to predict student performance in distance learning which has been, and remains, the primary method of learning in some countries due to Corona Virus pandemic. For this reason, this research is going to predetermine a fitting definition of student performance in time …

Interconnectedness And Financial Stability In The Era Of Artificial Intelligence, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

This chapter explains AI use cases may amplify some threats to the stability of the financial system. It argues that lack of a consistent approach to AI Governance by financial regulators and limited oversight on some AI models in terms of systemic risks need to be addressed to preserve the stability of the financial system. To illustrate the problem and propose specific policy recommendations, the chapter first explains how the widespread use AI in finance impacts systemic risk in the financial sector. Then, it explains why trustworthiness of AI encompasses not only the typical ethical principles about transparency, explainability, fairness, …

Informational Content Of Factor Structures In Simultaneous Discrete Response Models, Shakeeb Khan, Arnaud Maurel, Yichong Zhang

Research Collection School Of Economics

We study the informational content of factor structures in discrete triangular systems. Factor structures have been employed in a variety of settings in cross sectional and panel data models, and in this paper we attempt to formally quantify their informational content in a bivariate system often employed in the treatment effects literature. Our main findings are that under the factor structures often imposed in the literature, point identification of parameters of interest, such as both the treatment effect and the factor load, is attainable under weaker assumptions than usually required in these systems. For example, we show is that an …

Moral Injury To Inform Analysis Of Post-Traumatic Stress Disorder, Amanda Julia Manea

Senior Theses

Post-traumatic stress disorder (PTSD) is a mental health condition that almost one out of ten veterans struggle with. Although the National Center for PTSD has made extensive progress in characterizing and developing new treatments for PTSD, most veterans still experience symptoms of PTSD following treatment. Novel avenues of investigation, such as developing algorithms to review electronic health record (EHR) data and better understanding moral injury, are being pursued to address the gap that still exists when it comes to treating veterans. Moral injury is the individual evaluation of exposure to a potentially morally injurious event (PMIE) and can lead to …

Consumers And Eco-Labels: A Quantitative Analysis Of The Effects Of Various Sustainability Certification Models On Consumer Opinions, William F. Joseph

Senior Theses

This research consists of an econometric analysis of the efficacy of a privatized sustainability certification model versus a proposed government-endorsed sustainability certification model within the United Sates market. Today, the widely accepted model of sustainability certification is constituted by a large market of private certifiers. By analyzing the effects of the current model and alongside the effects of a hypothetical government-endorsed system on consumer preferences for sustainably produced goods, the thesis aims to motivate further discussion into the possible benefit of adopting a government-sponsored sustainability certification system. In general, analysis of the data suggests much more promising and significant effects …

Modeling The Probability Of A Successful Stolen Base Attempt In Major League Baseball, Cade Stanley

Senior Theses

In Major League Baseball (MLB), the outcome of a stolen base attempt has important implications. Success moves the runner closer to scoring, while failure records an out and removes the runner from the basepaths altogether. Therefore, it is important that the decision by a coach or player to steal a base is well-informed. In this thesis, I explore a statistical approach to making this decision. I train logistic regression and random forest models, using data about the game situation and about the runner, pitcher, and catcher involved in the stolen base attempt, to estimate the probability that a stolen base …

Structure Of Extremal Unit Distance Graphs, Kaylee Weatherspoon

Senior Theses

This thesis begins with a selective overview of problems in geometric graph theory, a rapidly evolving subfield of discrete mathematics. We then narrow our focus to the study of unit-distance graphs, Euclidean coloring problems, rigidity theory and the interplay among these topics. After expounding on the limitations we face when attempting to characterize finite, separable edge-maximal unit-distance graphs, we engage an interesting Diophantine problem arising in this endeavor. Finally, we present a novel subclass of finite, separable edge-maximal unit distance graphs obtained as part of the author's undergraduate research experience.

Making Music Social: Creating A Spotify-Based Social Media Platform, Dalton J. Craven

Senior Theses

DKMS is a new type of social media platform for music lovers and groups of friends. It integrates tightly with Spotify, one of the largest music streaming services in the world. Users of DKMS can see what their friends are listening to, receive recommendations of new songs to listen to, and analyze their several key numerical metrics (happiness, danceability, loudness, and energy) of their top songs.

DKMS was built as part of the year-long Capstone senior design course at the University of South Carolina. A deployed app is visible at https://dkms.vercel.app, and the open-source code is visible at https://github.com/SCCapstone/DKMS.