Physical Sciences and Mathematics Commons^™

Growth Characteristics Of Superior Lines Of Zoysia Grass (Zoysia Japonica) And Development Of Its Dna Markers, Y. W. Rim, K. Y. Kim, M. J. Kim, B. R. Sung, Y. C. Lim, E. S. Chung

IGC Proceedings (1993-2023)

Demand for turf grass has steadily increased for recreation and sport fields after the 2002 Korea-Japan World Cup in Korea. Zoysia grass has the advantage of easy management, including low water and fertiliser requirement, but has limitations such as low recovery, low shoot density and short green period (Kim et al., 1999). Objectives of this research were to select superior lines in the collected clones, compare the superior lines of zoysia grass with other standard cultivars for growth characteristics and to develop the DNA markers of superior lines.

Quality Legume-Based Forage Systems For Contrasting Environments: Cost Action 852, A. Helgadottir, John Connolly, M. Fothergill, R. P. Collins, Claudio Porqueddu, Andreas Lüscher, M. T. Sebastia, Michael Kreuzer, M. Wachendorf

IGC Proceedings (1993-2023)

Agricultural systems that reduce environmental degradation, sustain agricultural productivity and economic viability, maintain stable rural communities, enhance the quality of life and respond to increasing demand for livestock products are promoted in developed countries. Though major challenges exist, forage legumes, adapted to a wide range of soil types, climatic conditions and management systems, will become increasingly important components of sustainable agricultural production systems in Europe. Temporal and spatial variation in legume performance often occurs. Compared to pure grass systems, legume-based systems may lead to increased N losses. To what extent ruminants can use the protein from forage legumes, and whether …

Higher Yield And Fewer Weeds In Four-Species Grass/Legume Mixtures Than In Monocultures: Results From The First Year At 20 Sites Of Cost Action 852, Laura Kirwan, Gilles Bélanger, J. A. Finn, M. Fothergill, Bodil E. Frankow-Lindberg, R. Garcia-Sarrion, A. Ghesquiere, P. Golinski, A. Helgadóttir, M. Jørgensen, Z. Kadžiuliene, D. Nyfeler, P. Nykänen-Kurki, G. Parente, V. Vasileva, R. Collins, J. Connolly, Andreas Lüscher, Claudio Porqueddu, M. T. Sebastià

IGC Proceedings (1993-2023)

Utilisation of grass/legume mixtures instead of grass monocultures is a sensible alternative for low input, efficient agricultural systems that reduce production costs, promote environmental policy and maintain a living countryside. Consequently, widely adapted forage legumes will become increasingly important. Instability of simple grass / legume mixtures with only one grass and one legume species is a major problem (Wachendorf et al., 2001). An experiment was established in 39 sites in Europe, Australia and Canada within COST Action 852 to: (1) assess the benefits of grass / legume mixtures in terms of forage production, (2) test whether the combination of …

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 …

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 …

Exploring Improvements To Space-Bounded Derandomization From Better Pseudorandom Generators, Boxian Wang

Computer Science Senior Theses

Saks and Zhou used Nisan’s PRG in a recursive manner to obtain BPL ⊆ L^(3/2). We describe how this framework could be generalized to use arbitrary PRGs following Armoni’s sampler idea. We then give a theorem relating the seed length of a better PRG to the implied improvements in derandomizing BPL. Recently, Hoza used Armoni’s PRG in the Saks-Zhou framework to obtain an even better derandomization. We describe the construction of Armoni’s PRG and conjecture that by using basic components other than extractors, parameters in that construction could be improved. Under some assumptions, we calculate the extent to which such …

Interpreting Business Strategy And Market Dynamics: A Multi-Method Ai Approach, Lobna Jbeniani

Computer Science Senior Theses

This research paper presents an integrated approach that combines Long Short-Term Memory (LSTM), Q-Learning, Monte Carlo methods, and Text-to-Text Transfer Transformer (T5) to analyze and evaluate the business strategies of public companies. Leveraging a large and diverse dataset sourced from multiple reliable sources, the study examines corporate strategies and their impact on market dynamics. LSTM and Q-Learning are employed to process sequential data, enabling informed decision-making in simulated market environments and providing insights into potential outcomes of different strategies. The Monte Carlo method manages uncertainty, allowing for a comprehensive analysis of risks and rewards associated with specific strategies. T5 interprets …

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, …

Dimensions Of Vaccination Attitudes In Nigeria: A Study Of The Impacts Of Covid-19 Vaccine Risk Perception And Acceptance, Abiodun Musbau Lawal, Babatola Dominic Olawa, Ikenna Maximillian Odoh, Ayodeji Olorunfemi Olawole, Olubukola Ajayi, Judith Chineye Azikiwe, Israel Oluwatosin Ayodele, Emmanuel Kolawole Odusina, Thomas Attah, Ezekiel Adeyemi Odedokun, Stephen Ishola Babatunde, Teslim Alabi Oladejo, Confidence Chioma Otoghile, Saheed Abiola Saka

Kesmas

Nigeria has been affected by the COVID-19 pandemic, and vaccination is a key strategy. However, the country faces vaccination hesitancy, poor risk perception, and low acceptance. This study aimed to assess the direct and interactive impacts of COVID-19 vaccine risk perception and acceptability on COVID-19 vaccination attitudes in the general Nigerian population. In a cross-sectional approach, participants completed a structured questionnaire including demographics, COVID-19 vaccine risk perception, acceptance, and vaccination attitude from April 2-30, 2021. The sample included 1,026 participants from different ethnicities across four regions (Southwest, South, Southeast, and North Central) in Nigeria, which were selected using the convenience …

Extremely Hot Ambient Temperature And Injury-Related Mortality, Mien T N Nguyen, Man V M Nguyen, Huong V T Le, Hoai Viet Nguyen, Vu Anh Nguyen, Ngoan Tran Le

Kesmas

This pilot study aimed to evaluate the effects of extremely hot ambient temperatures on the total number of fatal injuries. Data were collected from a population-based mortality registry of Thanh Hoa, a province in the North Central region of Vietnam. This study qualified the distributed lag non-linear model and calculated the RR and 95% CI adjusted for long-term trend and absolute humidity. For the entire study population with 3,949 registered deaths due to injuries collected during 2005-2007, after the onset of extremely hot ambient temperatures, an increased risk of death was observed on the 9th day RR (95% CI) = …

Effects Of Using An Application For Postpartum Contraceptive Use In Family Planning Counseling During Pregnancy, Lia Nurcahyani, Dyah Widiyastuti, Arief Tarmansyah Iman, Yanti Cahyati, Yeni Fitrianingsih

Kesmas

A decision-making tool for family planning flipchart is used for contraceptive counseling, but the use of this flipchart is suboptimal. In this study, primary study resulted in innovative decision-making tools for family planning applications. “Si KB Pintar” was also developed, a tool that women can use to discuss contraceptives with their husbands after family planning counseling. This study analyzed the effectiveness of family planning counseling during pregnancy by applying postpartum contraceptive use. Analytical quantitative quasi-experimental methods were used with a control group design. The sampling method was two-stage sampling. In the first stage, from 22 primary health care (PHC) in …

Modelling Hoe Performance With An Extended Source; Experimental Investigation Using Misaligned Point Sources, Jorge Lasarte, Kevin Murphy, Izabela Naydenova, Jesús Atencia, Mª Victoria Collados, Suzanne Martin

Conference Papers

Holographic Optical Elements (HOEs) have the potential to enable more compact, versatile and lightweight optical designs, but many challenges remain. Volume HOE’s have the advantage of high diffraction efficiency but they present both chromatic selectivity and chromatic dispersion which impact on their use with wide spectrum light sources. Single-colour LED sources have a narrow spectrum that reduces these issues and this makes them better suited for use with volume HOEs. However, the LED source size must be taken into consideration for compact volume HOE-LED systems. To investigate the design limits for compact HOE-LED systems, a theoretical and experimental study was …

Connecting Linguistic Expressions And Pain Relief Through Transformer Model Construction And Analysis, Sarah M. Chacko

Computer Science Senior Theses

Chronic pain is a widespread problem that significantly impacts quality of life. Overprescription and abuse of pain medication continues to be a major public health issue and can further burden patients due to a fragmented health care system. Previous research has suggested a possible psychological basis to pain and the potential for safer, non-pharmacological alternatives for pain relief. This project leverages language models to study chronic pain development and relief through psychological treatments, which will be assessed through responses to post-treatment interviews. A transformer-based natural language processing model is employed to identify connections between language expressions and pain on a …

Investigating English-Language Dialect-Adjusted Models, Samiha Datta

Computer Science Senior Theses

This thesis describes several approaches to better understand how large language models interpret different dialects of the English language. Our goal is to consider multiple contexts of textual data and to analyze how English-language dialects are realized in them, as well as how a variety of machine learning techniques handle these differences. We focus on two genres of text data: news and social media. In the news context, we establish a dataset covering news articles from five countries and four US states and consider language modeling analysis, topic and sentiment distributions, and manual analysis before performing nine experiments and evaluating …

Utilizing Natural Language Processing For Automated Clinical Text Review: Identification Of Care Preference Documentation In Patients’ Discharge Summaries, Saksham Arora

Computer Science Senior Theses

Improving patient-centered care necessitates accurate documentation of care preferences, a crucial aspect often underrepresented in administrative data. Most studies apply care documentation to specific patient populations, rather than more appropriately broad population of `seriously ill' patients. This paper addresses this gap by leveraging transformer-based machine learning models, exhibiting an improvement over traditional keyword-based search methods in identifying care preference documentation.

In order to capture a broad spectrum of seriously ill patients, we matched decedent patients to non-decedent counterparts by utilizing a propensity score matching, accounting for important variables like age, gender, primary diagnoses and commodities. We trained and fine-tuned Bio_ClinicalBERT …

Unmasking Bias: Investigating Strategies For Minimizing Discrimination In Ai Models, Julia L. Martin

Computer Science Senior Theses

Artificial Intelligence (AI) models are increasingly used as predictive tools with real-world applications occurring in diverse fields ranging from the healthcare industry to the criminal justice system. While AI often offers efficient and relatively effective solutions, there are growing concerns regarding AI’s role in decision-making processes due to potential biases embedded in these models. In many cases, bias in AI models can produce unfair outcomes, perpetuate social inequities, and undermine the trustworthiness of AI systems. This thesis explores this problem and spotlights certain biased models that are currently utilized in real-world situations. One such example is a highly biased AI …

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 - …

Record High Room Temperature Resistance Switching In Ferroelectric-Gated Mott Transistors Unlocked By Interfacial Charge Engineering, Yifei Hao, Xuegang Chen, Le Zhang, Myung-Geun Han, Wei Wang, Yue-Wen Fang, Hanghui Chen, Yimei Zhu, Xia Hong

Department of Physics and Astronomy: Faculty Publications

The superior size and power scaling potential of ferroelectric-gated Mott transistors makes them promising building blocks for developing energyefficientmemory and logic applications in the post-Moore’s Law era. The close to metallic carrier density in the Mott channel, however, imposes the bottleneck for achieving substantial field effect modulation via a solid-state gate. Previous studies have focused on optimizing the thickness, charge mobility, and carrier density of single-layer correlated channels, which have only led to moderate resistance switching at room temperature. Here, we report a record high nonvolatile resistance switching ratio of 38,440% at 300 K in a prototype Mott transistor consisting …

Automated Approaches To Enable Innovative Civic Applications From Citizen Generated Imagery, Hye Seon Yi

USF Tampa Graduate Theses and Dissertations

Smart governance is an area, that is increasingly becoming important, not only in advanced countries, but all across the globe. Thanks to global scale network connectivity, permeance of smart-devices of various form-factors, and overall improvement in digital literary, we are now seeing "smartness" everywhere, or if not, the general public is expecting the same. Ultimately, the goal of smart governance is to facilitate state-of-the-art technologies to improve citizens’ lives. With the ubiquity of smart phone technologies today, citizens more readily participate in collaboration with public officials for improved quality of life and their communities. By utilizing optimal tools, public officials …

What Effects Do Large Language Models Have On Cybersecurity, Josiah Marshall

Cybersecurity Undergraduate Research Showcase

Large Language Models (LLMs) are artificial intelligence (AI) tools that can process, summarize, and translate texts and predict future words in a sentence, letting the LLM generate sentences similar to how humans talk and write. One concern that needs to be flagged is that, often, the content generated by different LLMs is inaccurate. LLMs are trained on code that can be used to detect data breaches, detect ransomware, and even pinpoint organizational vulnerabilities in advance of a cyberattack. LLMs are new but have unbelievable potential with their ability to generate code that brings awareness to cyber analysts and IT professionals. …

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.

Assessment Of Rabies Control Attitudes During The Covid-19 Pandemic Through Partial Least Square-Structural Equation Modeling, Sang Gede Purnama, Ni Wayan Arya Utami, Made Subrata, Putu Erma Pradnyani, Karang Agustina, Ibn Swacita

Kesmas

The COVID-19 pandemic disrupts rabies control activities in the community. A new approach is needed to control rabies during the COVID-19 pandemic through digital health interventions by conducting digital surveillance and education. This study aimed to determine key attitude indicators in controlling rabies during the COVID-19 pandemic. A cross-sectional study on 166 participants in Denpasar City with a total of 31 indicators measuring five variables: perceptions of the benefits of rabies control (6 indicators), perceptions of rabies risk (6 indicators), perceptions of obstacles to rabies control (5 indicators), perceptions of the need for technology (7 indicators), and attitudes toward rabies …

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 …

An Algorithmic Approach To Jazz Guitar Voice-Leading Chord Fingerings, Matthew B. Keating

Computer Science Senior Theses

A problem in guitar practice is choosing chord voicings that fit together in sequence, a process known as voice leading. In jazz, a guitarist follows voice leading by maintaining stepwise or limited motion for smoother harmony. The main avenues to learn jazz guitar voice leading theory are through a guitar instructor or chord books. To our knowledge, no computational method of generating voice-leading given chord labels exists. First, we demonstrate the complexity of this problem by presenting a graph search algorithm to optimize for a simplified version of voice leading. Then, we present a novel approach to algorithmically derive tablature …