Physical Sciences and Mathematics Commons^™

A Molten Salt Test Loop For Component And Instrumentation Testing, T L. Head, Allison M. Berry, Keaton J. Brewster, Robert L. Brown, Hailey N. Burden, Reuben Byrd, Timothy Doty, Jess Dowdy, Kameron A. Hill, R. A. Jinkerson, Timothy J. Kennedy, Ronald C. Laehn, Dakotah Martinez, Samuel L. Mulder, Charles Onstead, Kim L. Pamplin, Dylan C. Pfeifer, Michael B. Ranger, Aaron D. Robison, Nathaniel T. Rowlands, Raymond E. Smith, Matthew T. Steele, R. S. Towell, Travis Towell, Olive Tuyishimire, T. S. Watson

Chemistry and Biochemistry

Molten salt is an effective coolant for a wide range of applications, including nuclear reactors, concentrated solar power, and other high temperature industrial heat transfer processes. The technical readiness level of components and instrumentation for high-temperature molten salt applications needs improvement for molten salt to be more widely adopted. A molten salt test loop was designed, built, and commissioned as a test bed to address these issues. The molten salt test loop at Abilene Christian University was built out of 316 stainless steel with a forced flow centrifugal-type pump, and was instrumented for remote operation. A low-temperature molten nitrate salt …

Topological Data Analysis Of Convolutional Neural Networks Using Depthwise Separable Convolutions, Eliot Courtois

Dissertations

In this dissertation, we present our contribution to a growing body of work combining the fields of Topological Data Analysis (TDA) and machine learning. The object of our analysis is the Convolutional Neural Network, or CNN, a predictive model with a large number of parameters organized using a grid-like geometry. This geometry is engineered to resemble patches of pixels in an image, and thus CNNs are a conventional choice for an image-classifying model.

CNNs belong to a larger class of neural network models, which, starting at a random initialization state, undergo a gradual fitting (or training) process, often a …

High Resolution Intracavity Laser Absorption Spectroscopy Of Transition Metal-Containing Diatomic Molecules, Kristin Bales

Dissertations

Three transition metal-containing diatomic molecules have been studied using intracavity laser spectroscopy. Many of the transitions were recorded using a Fourier-transform spectrometer for detection, allowing collection at Doppler-limited resolution for the gas phase molecules. Several vibrational bands in two electronic transition systems of tantalum fluoride (TaF) have been analyzed, and new molecular constants provided. Transitions involving six electronic states of tungsten sulfide (WS) have been analyzed, with new and updated constants provided, including a deperturbation analysis of three vibrational bands in two of the states. Finally, a fresh perspective on two electronic states of tungsten oxide (WO) included a deperturbation …

Degradation Of Oligo[Poly(Ethylene Glycol) Fumarate] Hydrogels Through Stimulus-Mediated Pendent Group Cyclization, Andrew Chung, Burak Tavsanli, Elizabeth Gillies

Chemistry Publications

Hydrogels are of interest for a wide range of applications including drug delivery, regenerative medicine, agriculture, and personal care products. Among the water-soluble synthetic polymers that can be processed to form hydrogels, oligo[poly(ethylene glycol) fumarate] (OPF) has attracted significant attention. The degradation of OPF can be tuned to some extent based on the poly(ethylene glycol) chain length and amount of cross-linker incorporated, but the degradation is generally quite slow, occurring over several months. Here we introduce a new approach to tune and trigger the degradation of OPF. Fumarate alkenes were functionalized to introduce protected pendent amines, that after deprotection could …

Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Residential Metals Abatement Program (Rmap) Park Soil Field Sampling Plan (Fsp) Submittal #10 [Covering Original Mine Yard] (Dated July 14, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

New Chemical Dopant And Counterion Mechanism For Organic Electrochemical Transistors And Organic Mixed Ionic–Electronic Conductors, Vianna N. Le, Joel H. Bombile, Gehan S. Rupasinghe, Kyle N. Baustert, Ruipeng Li, Iuliana P. Maria, Maryam Shahi, Paula Alacon Espejo, Iain Mcculloch, Kenneth R. Graham, Chad Risko, Alexandra F. Paterson

Chemistry Faculty Publications

Organic mixed ionic–electronic conductors (OMIECs) have varied performance requirements across a diverse application space. Chemically doping the OMIEC can be a simple, low-cost approach for adapting performance metrics. However, complex challenges, such as identifying new dopant materials and elucidating design rules, inhibit its realization. Here, these challenges are approached by introducing a new n-dopant, tetrabutylammonium hydroxide (TBA-OH), and identifying a new design consideration underpinning its success. TBA-OH behaves as both a chemical n-dopant and morphology additive in donor acceptor co-polymer naphthodithiophene diimide-based polymer, which serves as an electron transporting material in organic electrochemical transistors (OECTs). The combined effects enhance OECT …

Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Fourth Quarter 2022 (Dated March 30, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Generative Relevance Feedback With Large Language Models, Iain Mackie, Shubham Chatterjee, Jeffrey Dalton

Computer Science Faculty Research & Creative Works

Current query expansion models use pseudo-relevance feedback to improve first-pass retrieval effectiveness; however, this fails when the initial results are not relevant. Instead of building a language model from retrieved results, we propose Generative Relevance Feedback (GRF) that builds probabilistic feedback models from long-form text generated from Large Language Models. We study the effective methods for generating text by varying the zero-shot generation subtasks: queries, entities, facts, news articles, documents, and essays. We evaluate GRF on document retrieval benchmarks covering a diverse set of queries and document collections, and the results show that GRF methods significantly outperform previous PRF methods. …

Neuro-Symbolic Representations For Information Retrieval, Laura Dietz, Hannah Bast, Shubham Chatterjee, Jeff Dalton, Jian Yun Nie, Rodrigo Nogueira

Computer Science Faculty Research & Creative Works

This tutorial will provide an overview of recent advances on neuro-symbolic approaches for information retrieval. A decade ago, knowledge graphs and semantic annotations technology led to active research on how to best leverage symbolic knowledge. At the same time, neural methods have demonstrated to be versatile and highly effective. From a neural network perspective, the same representation approach can service document ranking or knowledge graph reasoning. End-to-end training allows to optimize complex methods for downstream tasks. We are at the point where both the symbolic and the neural research advances are coalescing into neuro-symbolic approaches. The underlying research questions are …

Interpretable Timbre Synthesis Using Variational Autoencoders Regularized On Timbre Descriptors, Anastasia Natsiou, Luca Longo, Sean O'Leary

Conference papers

Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such as Variational Autoencoders (VAEs) have the ability to generate a high-level representation of audio while providing a structured latent space. Despite their advantages, the interpretability of these latent spaces in terms of human perception is often limited. To address this limitation and enhance the control over timbre generation, we propose a regularized VAE-based latent space that incorporates timbre descriptors. Moreover, we suggest a more concise representation of sound by utilizing its harmonic …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Fourth Quarter 2022 (Dated March 30, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Computation Of The Basic Reproduction Numbers For Reaction-Diffusion Epidemic Models, Chayu Yang, Jin Wang

Department of Mathematics: Faculty Publications

We consider a class of k-dimensional reaction-diusion epidemic models (k = 1; 2; • • • ) that are developed from autonomous ODE systems. We present a computational approach for the calculation and analysis of their basic reproduction numbers. Particularly, we apply matrix theory to study the relationship between the basic reproduction numbers of the PDE models and those of their underlying ODE models. We show that the basic reproduction numbers are the same for these PDE models and their associated ODE models in several important scenarios. We additionally provide two numerical examples to verify our analytical results.

Connecting The Optical Regime To The X-Ray In Neutron Star Low Mass X-Ray Binaries, Alexander B. Igl

LSU Doctoral Dissertations

Using Rossi X-Ray Timing Explorer and Otto Struve Telescope data of low mass X-ray binaries (LMXBs) Cyg X-2 and Sco X-1, the optical regime’s relationship to the X-ray was investigated through several angles. Discrete cross correlations using the optical and X-ray data revealed evidence of reprocessing in both datasets. These were more consistently present in Sco X-1, where both small and obvious features were seen at less than 4 s of optical lag. The size of these lags makes it likely that most of the reprocessing is taking place on the accretion disk. Parameterization of the Z tracks led to …

Sustainability Of Permanent Grassland On A Low Moor Soil With Different N And K Nutrient Management, K. Orlovius, J. Pickert

IGC Proceedings (1977-2023)

After the reunification of Germany fertilisation with P and K was strongly reduced in the eastern states of Germany due to the poor financial situation of the farms. Particularly on sites with a low nutrient delivery capacity, such a nutrient management strategy implies the risk of decreasing soil fertility. On a low moor soil with permanent grassland a 4 - year trial with different N and K fertilisation was set up to study the development of dry matter production and K concentrations in the grass.

A Newfangled Interpretation On Fermatean Neutrosophic Dombi Fuzzy Graphs, D. Sasikala, B. Divya

Neutrosophic Systems with Applications

Neutrosophic Dombi fuzzy graph is an advancement of the Dombi fuzzy graph and intuitionistic Dombi fuzzy graph. In this paper, we have initiated a new concept of the Fermatean neutrosophic Dombi fuzzy graph. Further, we identified a few products of the direct, cartesian, composition of Fermatean neutrosophic Dombi fuzzy graphs. Also, we examined the related proposition with suitable illustrations with graphs.

Fault Aware Task Scheduling In Cloud Using Min-Min And Dbscan, S. M.F.D.Syed Mustapha, Punit Gupta

All Works

Cloud computing leverages computing resources by managing these resources globally in a more efficient manner as compared to individual resource services. It requires us to deliver the resources in a heterogeneous environment and also in a highly dynamic nature. Hence, there is always a risk of resource allocation failure that can maximize the delay in task execution. Such adverse impact in the cloud environment also raises questions on quality of service (QoS). Resource management for cloud application and service have bigger challenges and many researchers have proposed several solutions but there is room for improvement. Clustering the resources clustering and …

External Behavior Of A Logic Program And Verification Of Refactoring, Jorge Fandinno, Zachary Hansen, Yuliya Lierler, Vladimir Lifschitz, Nathan Temple

Computer Science Faculty Publications

Refactoring is modifying a program without changing its external behavior. In this paper, we make the concept of external behavior precise for a simple answer set programming language. Then we describe a proof assistant for the task of verifying that refactoring a program in that language is performed correctly.

Evaluation Of Bio-Friendly Formulations From Siderophore-Producing Fluorescent Pseudomonas As Biocontrol Agents For The Management Of Soil-Borne Fungi, Fusarium Oxysporum And Rhizoctonia Solani, Gaber Attia Abo-Zaid, Ahmed Salah Abdullah, Nadia Abdel-Mohsen Soliman, Ebaa Ebrahim El-Sharouny, Abdulaziz A. Al-Askar, Yiming Su, Ahmed Abdelkhalek, Soraya Abdel-Fattah Sabry

Civil and Environmental Engineering Faculty Publications

Secretion of siderophores by Pseudomonas aeruginosa F2 and P. fluorescens JY3 was evaluated on chrome azurol S (CAS) agar plates and their inhibitory effect was inspected against Fusarium oxysporum and Rhizoctonia solani. Production of siderophores as biocontrol agents from F2 and JY3 was accomplished in two optimized media. Afterward, cell-free supernatants of the bacterial cultures containing siderophores were used for the preparation of two bio-friendly formulations for the management of F. oxysporum and R. solani under greenhouse conditions. The investigated bacterial isolates, F2 and JY3, showed antagonistic activity in vitro against F. oxysporum and R. solani and produced siderophores …

Topological Comparison Of Some Dimension Reduction Methods Using Persistent Homology On Eeg Data, Eddy Kwessi

Mathematics Faculty Research

In this paper, we explore how to use topological tools to compare dimension reduction methods. We first make a brief overview of some of the methods often used in dimension reduction such as isometric feature mapping, Laplacian Eigenmaps, fast independent component analysis, kernel ridge regression, and t-distributed stochastic neighbor embedding. We then give a brief overview of some of the topological notions used in topological data analysis, such as barcodes, persistent homology, and Wasserstein distance. Theoretically, when these methods are applied on a data set, they can be interpreted differently. From EEG data embedded into a manifold of high dimension, …

Rhodium-Catalyzed Asymmetric Synthesis Of P-P And P-C Bonds, Sarah T. Chachula

Dartmouth College Ph.D Dissertations

Chapter 1: Synthesis, Structure, Dynamics, and Enantioface-Selective η3-Benzyl Coordination in the Chiral Rhodium Complexes Rh(diphos*)(η3-CH2Ph) Abstract: The rhodium benzyl complexes Rh(diphos*)(η3-CH2Ph) (1-14, diphos* = chiral bis(phosphine)) were prepared either by treatment of Rh(COD)(η3-CH2Ph) (15, COD = 1,5-cyclooctadiene) with diphos*, or from the reaction of [Rh(diphos*)(Cl)]2 (16- 20) with PhCH2MgCl. For C2-symmetric diphos*, observation of one set of NMR signals for complexes 1-12 suggested that the two diastereomers in which different 3-benzyl enantiofaces were coordinated to rhodium interconverted rapidly on the NMR time scale via suprafacial shifts; observation of five inequivalent aryl 1H NMR signals showed that antarafacial shifts were slow …

A Newfangled Interpretation On Fermatean Neutrosophic Dombi Fuzzy Graphs, D. Sasikala, B. Divya

Neutrosophic Systems with Applications

Neutrosophic Dombi fuzzy graph is an advancement of the Dombi fuzzy graph and intuitionistic Dombi fuzzy graph. In this paper, we have initiated a new concept of the Fermatean neutrosophic Dombi fuzzy graph. Further, we identified a few products of the direct, cartesian, composition of Fermatean neutrosophic Dombi fuzzy graphs. Also, we examined the related proposition with suitable illustrations with graphs.

How Technology May Be Used For Future Disease Predictions, Rich P. Manprisio

Journal of Applied Disciplines

Exasperated by the ongoing global pandemic, the healthcare system is grappling with the formidable challenges posed by proper and effective disease treatments. Nevertheless, amidst these growing difficulties, the healthcare field has witnessed significant technological advancements, offering promising avenues for disease prediction. Notably, a positive correlation exists between the utilization of technologies and their potential to serve as valuable tools for disease prediction. As our reliance on technological sophistication continues progressing, current research highlights numerous viable options to augment the healthcare sector. This review explores the current state of utilizing technologies and their potential to enhance healthcare, shedding light on their …

Influence Of Cutting Parameters On The Performance Of Plough During Hard Rock Cutting In Coal Mining, Sathish Kumar Palaniappan, Moganapriya Chinnasamy, Samir Kumar Pal, Rajasekar Rathanasamy

Journal of Sustainable Mining

Coal ploughs have proved very successful on many faces in various parts of the world. Recently, there has been a general tendency in longwall working to increase the speed at which the machine progresses along the coal face. An increase in production rate demands enhances either due to depth of penetration or cutting speed. This, in turn, results in increasing power demand and also the force acting on an individual pick. To get maximum efficiency from a cutting machine, a number of parameters need to be investigated. The first and foremost thing of interest is naturally the pick geometry. The …

The Relationship Between Water Temperature And Proximity To Surface Urban Heat Islands Within The Lower Chesapeake Bay Watershed For The Summer Of 2019, Sarah Kerner

Departmental Honors & Graduate Capstone Projects

Surface urban heat islands (SUHIs) are land surfaces with high concentrations of impervious surfaces like roofs, roads, sidewalks and other infrastructures that trap, absorb, and re-emit heat throughout the day/night and typically present higher temperatures than their surrounding rural areas. In this study, I evaluate how presence of and distance to SUHIs are associated with water temperature in the lower Chesapeake Bay watershed for the summer of 2019. When heavy precipitation events occur, flooding creates stormwater runoff, which is exposed to the hotter temperatures in urban areas. This introduces thermal pollution to nearby rivers and streams disrupting aquatic ecosystems. The …

The Rayleigh–Bénard Problem For Water With Maximum Density Effects, Mahanthesh Basavarajappa, Dambaru Bhatta

School of Mathematical & Statistical Sciences Faculty Publications

Linear stability and weakly nonlinear stability analyses are developed for Rayleigh–Bénard convection in water near 3.98 °C subject to isothermal boundary conditions. The density–temperature relationship (equation of state) is approximated by a cubic polynomial, including linear, quadratic, and cubic terms. The continuity equation, the Navier–Stokes momentum equation, the equation of state, and the energy equation constitute the governing system. Linear stability analysis is used to investigate how the maximum density property of water affects the onset of convective instability and the choice of unstable wave number for four different types of boundary conditions. Then, a weakly nonlinear stability study is …

Detecting Mental Distresses Using Social Behavior Analysis In The Context Of Covid-19: A Survey, Sahraoui Dhelim, Liming Chen, Sajal K. Das, Huansheng Ning, Chris Nugent, Gerard Leavey, Dirk Pesch, Eleanor Bantry-White, Devin Michael Burns

Computer Science Faculty Research & Creative Works

Online social media provides a channel for monitoring people's social behaviors from which to infer and detect their mental distresses. During the COVID-19 pandemic, online social networks were increasingly used to express opinions, views, and moods due to the restrictions on physical activities and in-person meetings, leading to a significant amount of diverse user-generated social media content. This offers a unique opportunity to examine how COVID-19 changed global behaviors regarding its ramifications on mental well-being. In this article, we surveyed the literature on social media analysis for the detection of mental distress, with a special emphasis on the studies published …

Synthesis Of Small Molecule Modulators Of Non-Traditional Drug Targets, Jamie Nunziata

USF Tampa Graduate Theses and Dissertations

This work details the effort toward structure-activity-relationship (SAR) studies and synthesis of the small molecule modulators of two non-traditional drug targets. The first part of this manuscript (chapters 1–2) will discuss the collaborative work and synthesis of an inhibitor of Slingshot Homology 1 (SSH1) with the potential therapeutic application toward Alzheimer’s Disease (AD) treatment. The second part (chapters 3–6) will discuss the synthetic efforts toward modulation of a protein target known as STING, or stimulator of interferon genes, with the therapeutic application toward autoimmune disease or anti-tumor activity.

AD is a progressive and degenerative illness that holds the title of …

Synthesis Of Tools For The Investigation And Treatment Of Infectious Diseases, Grant Lawrence

USF Tampa Graduate Theses and Dissertations

Modern medicine’s ability to treat a wide array of diseases is due mainly to the development of small-molecule drug discovery. Thousands of years of traditional medicines have been dwarfed in less than a hundred years. In addition, drug discovery has becoming a more consistent process with the introduction of the clinical trials process as well.Plasmodium is a genus of tropical parasites that have the potential to wreak havoc on billions of people globally. Current methods of drug discovery aimed at defeating these parasites require expensive assays that use radioactive material. By using an alkyne-labeled agent instead of a tritium-labeled agent, …

It's All About Perspective, Erik Johnson

Natural Science Faculty

When we travel, we see obvious differences in the environment, such as terrain, wildlife, and climate. Our mostly spherical planet causes the sky to look different from different locations as well.

Using Machine Learning Techniques To Model Encoder/Decoder Pair For Non-Invasive Electroencephalographic Wireless Signal Transmission, Ernst Fanfan

Master of Science in Computer Science Theses

This study investigated the application and enhancement of Non-Invasive Brain-Computer Interfaces (NI-BCIs), focused on enhancing the efficiency and effectiveness of this technology for individuals with severe physical limitations. The core research goal was to improve current limitations associated with wires, noise, and invasive procedures often associated with BCI technology. The key discussed solution involves developing an optimized Encoder/Decoder (E/D) pair using machine learning techniques, particularly those borrowed from Generative Adversarial Networks (GAN) and other Deep Neural Networks, to minimize data transmission and ensure robustness against data degradation. The study highlighted the crucial role of machine learning in self-adjusting and isolating …