Physical Sciences and Mathematics Commons^™

The Effect Of The Species, Stage Of Maturity And Level Of Intake Of Grass On The Efficiency Of Microbial Protein Synthesis In The Rumen Of Cattle, F J. Hart, Jane Leibholz

IGC Proceedings (1977-2023)

This study was undertaken because there is a paucity of information in the literature on the efficiency of microbial protein synthesis in the rumen of cattle when grass is fed as the sole diet. There is also little experimental data available on the factors which affect the efficiency of microbial protein synthesis. The work involved feeding six rumen fistulated Friesian steers with three species of grass which were harvested at various tages of maturity. In addition each maturity of forage was fed at three 15levels of orp5 nic matter ( OM) intake.

as sampled at the omasum and microbial protein …

The Influence Of Aging On Forage Quality Of Individual Switchgrass Leaves And Stems, B Anderson

IGC Proceedings (1977-2023)

Cattle selectrively graze switchgrass (Panicum virgatum L.) tops prior to the boot stage and prefer vegetative culms and new tillers following heading. Therefore, a study was conducted to evaluate the changes in forage composition of individual leaves and stems during growth to determine if grazing selection may be influenced by aging. Plants were cut periodically at ground level from collaring of the first leaf until anthesis. Leaves (leaf blade plus sheath) of different ages, stems, and the whorl were hand separated at each harvest. Crude protein, in vitro dry matter disappearance (IVDMD), neutral and acid detergent fiber, lignin, and …

Harvesting Alyceclover For Maximum Dry Matter Yield And Nutrient Value, D D. Baltensperger, W G. Blue, W H. Anderson

IGC Proceedings (1977-2023)

Limited information is available on the quality of alyceclover (Alysicarpus vaginalis) in relation to plant stress. This study was undertaken to clarify the relationship between plant maturity and forage yield, quality and mineral composition in order to optimize each at harvest. Alyceclover was grown for two summers and new plots were harvested weekly through the pod-fill stage of development beginning eight weeks after planting. Samples were analyzed for dry matter, organic matter, In vitro dry matter digestibility, nitrogen, phosphorus, potassium, calcium, magnesium, manganese, copper, iron and zinc. Dry matter yields increased through the flowering stage of development except …

Adaptation Of The Inra System Of Determination And Expression Of The Nutritive Value Of Forages To The Tropical Conditions In The Caribbean Island, A Xande, R Garcia-Trujillo

IGC Proceedings (1977-2023)

This program have undertaken a series of trials of systematic measure of nu tritive value on the tropical forages. The choice of the calculation and of the way of expression of energetic and nitrogen values required comparation measures in different systems as well as attempts in alimentation before adopting the new french INRA system of energy (UFL-UFV) and of the protein value (POI). The general results of this study is a preamble to the diffusion of the table of nutritive value of the tropical forages. For this purpose 450 samples of forages have been analysed on sheep in cage of …

Discovering And Designing Novel Perovskite Photovoltaic Materials Via Machine Learning, Junyeong Ahn

Discovery Undergraduate Interdisciplinary Research Internship

Perovskite semiconductors are promising materials for high-efficiency photovoltaics due to their outstanding optoelectronic properties, emerging as a sustainable energy source through solar cell applications. Perovskites with the ABX₃ composition (A, B = metal or organic cations with varying oxidation states; X = chalcogen or halogen anions) have gained interest for their excellent phase stability and compositional tunability. However, combinatorial possibilities arising from the many choices of A, B, and X site species, and their respective mixing fractions, a large number of possible ABX₃ perovskites remain undiscovered. In this work, we used machine learning (ML) methods to design new stable and …

Analysis Of The Impact And Adaptation Of Tidal Floods From Coastal Landscape Area Communities In Poasia District, Kendari City, Indonesia, La Ode Hadini, La Aba, Noor Husna Khairisa, Nikita Jasmine Almira

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

Poasia District is located in the coastal area of the southern part of Kendari City, which is highly susceptible to tidal flooding. However, the extent of the community's exposure to these events and their subsequent adaptation measures remain to be fully delineated. This study examines the impacts of tidal flooding and the adaptation patterns of the Poasia Coastal Community to the tidal flood disaster. This research employed a descriptive qualitative method, which was carried out through document review, interviews involving 34 respondents, and field observations. The results of this study indicate that tidal flooding exerts a negative impact on the …

Non-Spectator Behavior Of A Neutral Phosphine Ligand Driven By A Redox-Active Boron Cluster, Jared R. Riffle, Cash L. Jowers, Sarah Luna, Mark D. Smith, Dmitry V. Peryshkov

Faculty Publications

A new concept of ligand ambiphilicity that relies on the redox behavior of the indirectly coordinated boron cluster scaffold instead of the direct involvement of a single center in a ligand is introduced. A copper(I) complex of a carboranyl-based triphosphine, [t^BuP-closo-{C₂B₁₀}-^PhP-closo-{C₂B₁₀}-t^BuP]CuPF₆, in acetonitrile solution coordinates an exogenous X− anion (X− = Cl− or N3−) at the phosphorus center of the ligand and not at the cationic metal site to form [t^BuP(X)-nido-{C₂B …

Measuring The Impact On Landscape And Sediment Transport Of Climate And Anthropogenic Influence In The Mississippi River Since 2000 Bce, Bailey Wycoff

LSU Master's Theses

Understanding river dynamics is crucial to being able to interpret the geological history preserved in sediment deposited on continental margins, deltas, and alluvial plains. Sediment buffering can be a key control on the sediment flux to the ocean and involves sediment storage and recycling in flood plains. The efficiency of the transport varies depending on climatic and more recently anthropogenic influences. Sediment moving through meandering streams may be temporarily deposited in a point bar on the convex side of a meandering river. Meanders are sometimes cut off, creating an oxbow lake and filled in. The area of study, False River, …

Gene Regulatory Network Prediction Using Machine Learning, Deep Learning, And Hybrid Approaches, Sai Teja Mummadi, Md Khairul Islam, Victor Busov, Hairong Wei

Michigan Tech Publications

Construction of gene regulatory networks (GRNs) is essential for elucidating the regulatory mechanisms underlying metabolic pathways, biological processes, and complex traits. In this study, we developed and evaluated machine learning, deep learning, and hybrid approaches for constructing GRNs by integrating prior knowledge and large-scale transcriptomic data from Arabidopsis thaliana, poplar, and maize. Among these, hybrid models that combined convolutional neural networks and machine learning consistently outperformed traditional machine learning and statistical methods, achieving over 95% accuracy on the holdout test datasets. These models not only identified a greater number of known transcription factors regulating the lignin biosynthesis pathway but also …

Learning From Conditional Data Distributions, Jizhou Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional machine learning paradigms often rely on a single global model trained on an entire dataset, aiming for broad generalization across all instances. However, in many real-world applications, the underlying data distribution is heterogeneous, and meaningful predictions often require models that focus on specific subpopulations rather than treating the data as a whole. This motivates the study of learning from conditional distributions, a framework where predictive models are designed to capture the structure and properties of restricted subsets of the data, leading to improved accuracy, fairness, and interpretability. This dissertation explores three key subproblems that exemplify different aspects of learning …

Adaptive Crop Switching For Irrigated Agriculture In Response To Climate Change In The Western U.S., Shahryar Fazli, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Aqil Tariq, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Adaptive irrigation strategies are crucial for balancing water use, economic viability, and food security in the arid Western United States. However, as a key indicator vital in regulating agricultural productivity and crop irrigation, water use efficiency (WUEc) is becoming increasingly complex to estimate due to climate change. This study explores the critical role of key meteorological drivers, such as maximum temperature (tmax) and vapor pressure deficit (vpd), and their impacts on crop-specific WUEc. Future impacts are also assessed through integrating machine learning models with climate projections from the CMIP6 framework under SSP2–4.5 and SSP5–8.5 scenarios to forecast WUEc trends from …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Computational And In Vitro Investigation Of P. Crocatum Bioactive Compounds As Pancreatic Lipase Inhibitors, Gusnia Meilin Gholam, Dimas Andrianto, Dewi Anggraini Septaningsih, Mega Safithri

Karbala International Journal of Modern Science

Obesity, a prevalent metabolic disorder characterized by excessive fat accumulation, can severely affect overall health if left untreated. This study investigated the potential of a 70% ethanol extract from Piper crocatum (red betel) leaves as an in vitro inhibitor of pancreatic lipase (PL), supported by computational analyses to identify alternative compounds to orlistat. The phytochemical profile was characterized using LC-MS/MS, revealing alkaloids and terpenoids with contents of 1.1 ± 0.01 mg CE/g and 3.14 ± 0.3 mg UAE/g, respectively. The extract exhibited 49 ± 9.1% inhibition of PL activity. Molecular docking identified three promising compounds: calanolide A (10.43 kcal/mol), myricanone …

In Silico Prediction Of Cytotoxic T-Cell Epitopes From Helicobacter Pylori Virulence Factors Using An Immunoinformatics Approach, Demy Valerie Chacon, Kiana Alika Co, Daphne Noreen Enriquez, Aubrey Love Labarda, Reanne Eden Manongsong, Edward Kevin B. Bragais

Biology Faculty Publications

Background: Helicobacter pylori infects approximately half of the global population, leading to gastric and duodenal ulcers. Despite the availability of antibiotics, challenges such as patient reluctance, high treatment costs, and antibiotic resistance limit their effectiveness, making vaccination a promising alternative. This study used immunoinformatics to identify candidate epitopes for a multiepitope vaccine construct against H. pylori.

Material and methods: The protein variability server was utilized for conservation analysis. The epitopes were screened for antigenicity, allergenicity, toxicity, cross-reactivity, and population coverage. Selected epitopes were docked with their corresponding human leukocyte antigen (HLA) alleles, and thermodynamic quantities were determined. Five virulence …

Comparative Study Of Machine Learning Models For Predicting The Market Value Of Professional Football Players, Álvaro Salvador López

Master's Theses or Doctor of Nursing Practice

The market value of professional football players is a critical factor in decision-making for clubs, agents, and analysts. Accurate player valuation impacts transfers, contract negotiations, and financial planning. In recent years, data-driven approaches have emerged to support traditional scouting with predictive analytics. This thesis presents a comparative study of machine learning models to estimate the market value of football players based on historical performance and personal attributes.

This thesis presents a comparative study of two independently developed machine learning systems designed to predict the market value of football players for the 2020–2021 season. Both systems were trained using real data …

A Data-Driven Approach To Time Series Forecasting And Clustering Of U.S. Regional Drug Overdose Mortality, Koshali Hamy Muthunama Gonnage

Mathematics & Statistics ETDs

The increasing rate of drug overdose deaths in the United States poses a critical public health challenge, particularly due to the surge in synthetic opioids and other high-risk substances. This study presents a data-driven framework that integrates time series forecasting and clustering techniques. Monthly mortality data for five key drug types: cocaine, fentanyl, heroin, methamphetamine, and oxycodone were analyzed using four time series forecasting models: ARIMA, ETS, TBATS, and NNAR. These models were evaluated using standard accuracy metrics RMSE, MAPE, and MAE to assess predictive performance. Signal decomposition approach based on Singular Value Decomposition and subspace modeling was employed to …

Improved Rational Approximations Of Pi, Nelson Carella

Publications and Research

The irrationality exponent of a real number α is defined by maximal value μ(α) ≥ 1 such that the inequality |p/q − α| < 1/qμ(α) is true for finitely many rational approxi- mations by relatively prime pairs p/q. The earliest result introduced the upper bound μ(π) ≤ 42 for the irrationality exponent of π. Subsequently, it was improved by many authors. The more recent result introduced the improved upper bound μ(π) ≤ 7.6063. This note introduces an improved irrationality exponent μ(π) ≤ 3. The optimal value is expected to be μ(π) = 2.

Optimizing Distributed Boundary Exchanges For Benchmarks, Solvers And Sparse Matrix Operations, Gerald Collom

Computer Science ETDs

Boundary exchanges dominate the cost of both stenciled codes and those that rely on sparse matrix operations. The performance of large boundary exchanges is limited by synchronization overheads and injection bandwidth limitations. Irregular boundary exchanges incur additional overheads due to the large number of required messages. This thesis investigates multiple methods for improving the performance and scalability of both Cartesian and irregular boundary exchanges. Since boundary exchanges are typically performed iteratively, persistent communication presents an opportunity for optimization by sharing and amortizing setup costs. Partitioned communication is also explored to increase asynchrony, reducing bottlenecks from synchronization overheads and data congestion. …

The Isoperimetric Inequality For Asymptotically Cat(0) Groups, Edric D. Dabu

Master's Theses

An asymptotically CAT(0) space is one where every ball of radius r is f(r)-CAT(0) for a fixed sublinear function f. An asymptotically CAT(0) group Γ is a group which acts properly and cocompactly by isometries on an asymptotically CAT(0) space X. Fix x0 ∈ X, choose D > 0 such that X = S γ∈Γ �� γ · B �� x0, D 3 ?? , define A = {a ∈ Γ : d(x0, a · x0) ≤ D + 1}, and let R be the set of reduced words in A of length at most 10 that represent the identity in …

Exploring Adversarial Threats To Neuralhash: A Perceptual Hashing Algorithm, Gurleen Kaur

Student Theses

Perceptual hashing algorithms are algorithms that generate content-based image hashes by extracting perceptual features from the images. Unlike cryptographic hashes, which exhibit significant changes with even slight input alterations, perceptual hashes do not change when modifications like compression, color correction and brightness are applied to the images. These hashes are designed to remain similar for inputs that are visually or perceptually alike, which has led to their widespread application in detecting duplicate images, finding similar images for reverse image search and to detecting inappropriate content of Child sexual abuse (CSAM) images by comparing image hashes with dataset of known perceptual …

Datasets Associated With Caballero Et Al. (2025): Sentinel-3 Coastal Analysis Ready Data (S3card): An Operational Framework For Coastal Water Applications, Cassia B. Caballero, Vitor S. Martins, Rejane S. Paulino, Thainara M. A. Lima, Elliott Butler, Eric Sparks

Research Data

This dataset provides access to twelve .zip archives containing pre-processed tiles from the S3CARD (Sentinel-3 Coastal Analysis Ready Data) framework. Each archive corresponds to a 2.5° × 2.5° coastal grid that includes an AERONET-OC (Aerosol Robotic Network – Ocean Color) station used for validation in Caballero et al. (2025). The data include atmospherically corrected, glint- and adjacency-corrected surface reflectance images derived from Sentinel-3 OLCI imagery.

Each tile includes:

- 21-band surface reflectance images in GeoTIFF format (valid water pixels only)

- Metadata files with acquisition geometry and processing details

These datasets support reproducibility and enable users to evaluate the S3CARD …

Reviving The Lost Art: Historical Foundations And Future Pathways For Bespoke Service In Luxury Retail, Andrew Burnstine

Faculty and Staff Publications & Presentations

The mid-20th century witnessed a zenith of deeply personalized, bespoke service within iconic luxury specialty retailers. This paper critically analyzes the foundational principles of this historical bespoke service model, extending Service-Dominant (S-D) Logic and retail evolution theory, to propose a robust framework for its modern revival. Employing a rigorous qualitative, multiple-case study approach, grounded in extensive historical and media analysis of four archetypal American and British luxury boutiques, and uniquely informed by an insider-ethnographic perspective on the central case exemplar ("Martha's"), the study distills six core principles: Profound Client Knowledge, Visionary Curation & Styling, Anticipatory & Proactive Service, The Exclusive …

Transforming Recruitment: The Power Of Data-Driven Decision Making, Dylan Klim

Faculty and Staff Publications & Presentations

Dylan Klim, senior assistant director in Admission presented at the National Small College Enrollment Conference (NSCEC) in Charlotte, North Carolina. Klim's presentation was titled, "Transforming Recruitment: The Power of Data-Driven Decision Making."

The NSCEC conference focuses on small colleges and universities that provide essential education and networking opportunities for small college professionals.

Phase Nanoscopy With Correlated Frequency Combs, Xiaobing Zhu

Optical Science and Engineering ETDs

In this dissertation a sensing method applying to any physical quantity that modifies optical phase is developed. Two pulses are produced inside a synchronously pumped Optical Parametric Oscillator, generating two identical, undistinguishable frequency combs. The physical quantity to be measured applies a small phase shift/round trip to one of the pulses, resulting in a frequency shift of the corresponding comb. The latter frequency is measured as a beat by interfering the two combs on a detector. A world record resolution, close to the quantum limit, of 0.033 nanoradian (corresponding to 0.006 fm in displacement) is achieved. A detailed analysis of …

Advancing Diamond Quantum Sensors: Isotropic Flux Concentrators And Phase Noise Mitigation, Maziar Saleh Ziabari

Optical Science and Engineering ETDs

Two methods for improving the sensitivity of nitrogen vacancy quantum sensors in diamond are explored. First, by passively concentrating the magnetic flux, three orthogonally oriented ferrite truncated cone pairs amplify the field isotropically by 19 times, allowing measurement of Earth's field without a bias field and increasing sensitivity. Through thorough analysis, modeling and tuning a novel 3-dimensional flux concentrator system, we achieve a fractional standard deviation of less than 1% anisotropy and quantify minimal deadzones and ambient temperature-limited variations below 40 nT/hour. Second, we characterize, model and calculate phase noise in NV experiments, which in NV sensors is effectively indistinguishable …

A Systematic Approach To The Characterization Of Liquid-Vapor Coexistence In Platinum, Meghan K. Lentz

Physics & Astronomy ETDs

Platinum is a material standard used in high pressure and shock compression experiments at Sandia National Laboratories. During experiments, materials are subjected to a very large range of thermodynamic conditions, during which materials regularly enter the liquid-vapor coexistence region. Despite its status as a standard, the region around the liquid-vapor critical point is poorly understood for platinum, with reported critical temperatures spanning approximately 7000 K. In this dissertation we conduct density functional theory based molecular dynamics (DFTMD) simulations for platinum for a range of temperatures and densities near liquid-vapor coexistence. The phase diagram for platinum is refined near the critical …

Using Triple Oxygen Isotopes To Investigate Water Usage In Desert Ecosystems, Cloe V. Knutson

Earth and Planetary Sciences ETDs

In arid environments, maintaining water balance can be more critical for survival than obtaining food. As droughts intensify, understanding how animals manage body water is essential. Triple oxygen isotope analysis provides a novel way to trace water sources in animals, distinguishing contributions from free water, food-derived oxygen, and atmospheric O₂. We developed an equilibration method using CO₂–H₂O oxygen exchange and measured δ^’18O and Δ^’17O values via tunable infrared laser direct spectroscopy (TILDAS). Validated against traditional fluorination methods, this technique enables streamlined analysis of whole blood and plant samples. Applied to …

Modeling Mars Chaos Terrains As Fracture Mosaics, Aidan C. Buie

Earth and Planetary Sciences ETDs

Chaos terrain exists on several planetary bodies but most notably on Mars. With 30 different named terrains and hundreds of chaotic or ”chaos-like” terrains, they are one of the most prominent and visible features on the planet. Chaos terrains have many visible similarities to each other: they all are comprised of polygonal blocks separated by fractures or channels. These blocks vary from angular to rounded and from flat plateaus to small hills, and the fractures vary from flat floored to ”v” shaped. Often, a single chaos will contain all of these morphologies. Most of the 30 named chaoses on Mars …

A Mutational Analysis Of Thatisin: How Single Point Mutations Impact The Biosynthetic Process Of A Group 16 Graspetide, John F. Boynton Jr

Chemistry and Chemical Biology ETDs

Abstract:

Graspetides are a family of Ribosomally synthesized and Post-translationally modified Peptide (RiPP) natural products named for their ATP Grasp Macrocyclases. We identified several Graspetide Biosynthetic Gene Clusters containing common double glycine cleavage motifs and attempted characterization of the mature Graspetides. One of the resulting peptides, Thatisin, has a topology with two interlocking macrolactones installed by a single ATP Grasp Ligase named ThtC. Here we use single and double point mutations to observe the impact or variation on the installation of these macrocycles. Alanine scan mutagenesis is used to assess leader peptide residues in the precursor peptide ThtA to determine …