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    Two-Species competition model with diffustion and harvesting: A numerical study
    (2023-12) Caro, Jasmin Tiana; Palaniappan, D.; Rao, B. Veena S.N.; Vasilyeva, Maria; Gaurdiola, Jose
    Predicting well observed states in ecology such as co-existence, competitive exclusion of one competitor, and bi-stability is vital during multi-species competitions. Models that examine these aspects of living systems have extensive applications in the overlapping areas of applied mathematics, population ecology, invasion science, evolutionary biology, and economics. The present study investigated a twin species Lotka-Volterra competition system accommodating diffusion and harvesting environments – a scenario widely anticipated in mathematical ecology. Our mathematical setup converts the diffusion and harvesting incorporated physical model into a system of second order nonlinear partial differential equations (PDES) describing the competition of the two species in closed domains. A finite difference numerical scheme is developed to solve the nonlinear boundary value problem (BVP) with Neumann boundary conditions. We applied our model results to the case of Brown and Pink shrimp in southeastern Gulf of Campeche that compete for resources in Marine Protected Areas (MPAs). For this specific example, we computed theoretical results for the sustainable biomass yield due to the competition and the mobility in the presence of multiple fishing zones. Our numerical solutions reveal that the speed or mobility of species is critical for the design of MPAs to attain a maximum sustainable biomass yield. Additionally, the results indicate that harvesting rate is adjustable for larger number of MPAs along the coastal line for efficient fishing. Further, it is observed that a sustainable biomass can be achieved for low mobile species such as the brown and pink shrimps by having smaller MPAs and both the species can co-exist in Gulf of Campeche.
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    Physiological assessment of common bottlenose dolphins (Tursiops truncatus) across a salinity gradient
    (2023-12) Guinn, Makayla; Orbach, Dara; Seemann, Frauke; Pollack, Jennifer
    Common bottlenose dolphins (Tursiops truncatus) are important bioindicators of ecosystem welfare and can inhabit environments with variable natural salinities. Anthropogenically-induced climate change exacerbates natural fluctuations in salinity and magnifies physiological imbalances in marine species. Bottlenose dolphins are well-suited model organisms to study the effects of environmental disturbances because they accumulate indices of stress in their blubber. Prolonged low salinity (< 10 ppt) exposure in dolphins elevates adrenal steroid hormones (i.e., aldosterone, cortisol) and promotes lesion development. However, the tolerances of and consequences for dolphins in hypersaline systems remain unknown. I assessed the physiological condition of three dolphin stocks in the Gulf of Mexico inhabiting areas of different natural salinities: Mississippi Sound, MS (0 – 30 ppt), Redfish Bay, TX ( 22 – 35 ppt), and Upper Laguna Madre, TX (37 + ppt). Steroid hormones were measured in remotely biopsied dolphin blubber using high-resolution liquid chromatography-mass spectrometry. Skin lesions were assessed using images of the dorsal fins and bodies of dolphins photographed from a research boat. There is a positive relationship between cortisol and salinity, indicating high salinity may impose physiological stress in dolphins. Testosterone concentrations in males are seasonal, with peaks in the fall and winter months. Progesterone levels in females were highest in the spring and summer and were indicative of gestation events. Skin lesions are most prominent on dolphins in the fall and winter, and a negative correlation between lesion prevalence and water temperature suggests cold water has a strong effect on epidermal integrity and lesion susceptibility in dolphins. I present here the first physiological assessment of free-ranging dolphins in a natural hypersaline bay. The dolphin health data collected from this research can help fill national data gaps for GoM dolphin stocks outlined by the National Oceanic and Atmospheric Administration, fill local data gaps for RB and ULM dolphin stocks, inform coastal communities of local marine ecosystem health and potential impact on human health by utilizing dolphins as bioindicators, and contribute to the understanding of how global climate change impacts the ability of marine organisms to adapt to highly variable environmental conditions. Additionally, this research will contribute to the planning of environmentally sustainable infrastructure (e.g., desalination plants) and promote environmental stewardship, ecotourism, and appreciation for natural resources.
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    Distribution of polymer types in Matagorda Bay & biofilm presence on surface of plastic pollution: A study using attenuated total reflectance-Fourier Transform Infrared Spectroscopy and principal component analysis
    (2023-12) Ivy, Kiersten M; Abdulla, Hussain; Conkle, Jeremy; Olson, Mark
    Global plastic pollution presents significant environmental and economic challenges, exacerbated by mismanagement and low recycling rates. Studies have shown other pollutants like persistent organic pollutants (POPs) and heavy metals can sorb to plastic debris in aquatic ecosystems, making them more readily dispersed throughout ecosystems. This study (1) quantified the spatial and seasonal distribution of different plastic polymer types along the Matagorda Bay system, and (2) explored the nature of the biofilm form on these plastic debris and any correlation between biofilm type and polymer type throughout different seasons. This comprehensive study, the most extensive of its kind with over 3,000 samples, investigates the distribution of plastic polymers AND biofilm formation in the Matagorda and San Antonio Bays across three seasons in 2022. Attenuated total reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR) along with Principal Component Analysis (PCA) was employed to identify polymer types and investigate biofilm formation on the collected samples. Polyethylene and polypropylene were the predominant polymer types observed across all sites and seasons. PCA suggested that biofilm was prevalent across all polymer types and seasons, and it is made mainly of extracellular polymer substances (EPS) that are rich in carbohydrates and proteins. Spectra integration showed a positive linear relationship between carbohydrate and protein biofilm components. This study not only provides a deeper understanding of biofilm roles in pollutant adsorption, but also introduces a novel, nondestructive approach for examining bacterial biofilms, paving the way for improved environmental management strategies.
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    Macroinvertebrate communities and decomposition rates of leaf and stem litter in a Texas saltmarsh-mangrove ecotone
    (2023-12) McGuigan, Molly; Proffitt, C. Edward; Devlin, Donna J.; Montagna, Paul A.
    After an extreme freeze event in 2021 caused extensive mangrove mortality and widespread top-kill to surviving mangroves and salt marsh vegetation along much of the Texas coast, it produced a massive flush of dead leaf and stem material in the ensuing litterfall. I questioned if there was a difference in macroinvertebrate community composition in leaf and stem litter and litter decomposition rates between Avicennia germinans (L) L, the black mangrove, and Batis maritima L, a halophytic succulent forb. In a field experiment, I used mesh litter bags to either allow or exclude macroinvertebrates and found no difference in macroinvertebrate community composition between the two litter types, suggesting they are generalists within a mesohaline and hypersaline environment. Wetness level of bags varied from dry, partially damp, mostly damp, and wet, and was significant in determining community composition parameters, with mostly damp bags having the highest abundance, richness, and diversity of macroinvertebrates. However, wetness level was not significant in determining litter decomposition (k). I found that leaf and stem litter is rapidly colonized and decomposed at 2-weeks post placement and then faunal abundance and diversity decline after 2 weeks, suggesting litter serves as a temporary “oasis” for macroinvertebrates. There was no difference in litter decomposition rate between mesh sizes, implicating that colonization by macroinvertebrates does not have a significant effect on litter decomposition, and rather it is likely being affecting by other abiotic and biotic factors or a combination of both. This study was the first to quantify B. maritima litter decomposition, with a rate of 0.098 g day-1, as compared to A. germinans litter decomposition of 0.024 g day-1. This research should inform management decisions by coastal land managers and conservationists when making management decisions concerning small invertebrate use of and effects on litter as communities shift from herbaceous saltmarsh to woody mangrove and influence the food webs of which small invertebrates are an important component.
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    Effect of observation on exhaustion and social physique anxiety
    (2023-12) Parikh, Vishwa Sameer; Davis, Liana; Snarr, Ronald; Ricard, Richard
    Introduction: Exercising in a crowd could make some people more anxious regarding their body which can affect exercise performance (McCann et al., 2007; Gammage et al., 2009). A construct within anxiety, social physique anxiety (SPA) combines body image with social anxiety, by measuring the apprehension reported when one worries about others’ perception of one’s body structure (Hart et al., 1989). General anxiety has been found to be associated with fatigue (McCann et al., 2007), but whether crowd-related anxiety is also associated with more risk of fatigue is uncertain. Purpose Statement: This study examined the differences in exhaustion and SPA following exercising while being observed versus without observation. Methods: Fifteen recreationally active volunteers were recruited as participants. Exercise testing was performed in two different sessions through the cycling maximal oxygen consumption test, at fixed speed for each participant. SPA scoring was done using a nine-item questionnaire before and after each session. While one session of testing for everyone involved no recording, another included a recording device being set up. After each session, participants were requested to give their rate of perceived exertion (RPE) ratings. Repeated measure nonparametric test was used to analyze the differences in all scores between and within the two sessions. Results: Differences in each question of SPA were trivial to moderate. Large difference was observed for male participants’ respiratory exchange ratio (RER). Trivial differences were observed between the two sessions for time to exhaustion. Small negative correlations were noted between RPE and SPA and between SPA and time to exhaustion (TTE).
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    Comparative statistical analysis of sea surface temperature time series modeling in the Gulf of Mexico
    (2023-12) Riba, Madison; Jin, Lei; Hu, Xinping; Guardiola, Jose; Sadovski, Alexey
    This work provides an analysis of sea surface temperature (SST) data in the Gulf of Mexico (GoM), and compares modeling methods to assess their performance through statistical simulation. The GoM is a region of global economic and environmental importance, including the notable Flower Garden Banks National Marine Sanctuary’s coral habitats. However, the area has largely not been focused on in terms of advanced SST modeling. The objective of this work is to provide insight into SST variability in the GoM by modeling time series data, concentrating on seasonal patterns and the overall linear warming trend. In the study, varying methods compared include a dynamic seasonal mean model, a dynamic sinusoidal regression model, a cyclic spline model, and a seasonal mean regression model with sandwich estimator. At the 95% nominal confidence level, methods ignoring the autocorrelation of error terms maintain empirical coverage between 60% and 80% to capture the linear yearly warming trends in the simulation. The recommended modeling approach, a dynamic sinusoidal regression model, provides such coverage of approximately 91.6%. It also offers a balance between accuracy, simplicity, and continuity, especially for frequently collected data. Analysis estimates the East Flower Garden Bank has an annual warming trend of approximately 0.028 ± 0.016°C. This comparative analysis of modeling techniques contributes to a better understanding of SST dynamics in this critical marine ecosystem.
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    Icthyoplanktonic vertical distribution & ingress in the Aransas Pass inlet system
    (2023-12) Robson, Olivia Ann; Portnoy, David; Tolan, James; Withers, Kim
    In the Coastal Bend region of Texas desalination plants have been proposed as a solution to water usage problems. These plants take in brackish/marine water and dispose of brine, which in coastal inlets would create a plume of water with higher salinity and temperature. Desalination plants could impact estuarine dependent fishes whose larvae pass through the inlets on their way to nursery habitat. In this study I sample the Aransas Pass Inlet system, in the vicinity of one of the proposed desalination plans, during day and night and during both incoming and outgoing tides at three different depth strata, to provide data on larval assemblages in the channel. Results showed that larval were greatest in the deepest stratum and during nighttime hours. Key spawning months for several important families were also confirmed. Briny discharge may adversely affect larval development and survival depending on sensitivity to abrupt changes in salinity and temperature, which differs by species and developmental stage. Currently there are no specific regulations addressing desalination plant discharge, but this research suggests those regulations should limit the location and timing of discharge to mitigate potential negative impacts on local ichthyofauna.
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    Benthic infaunal long term response to wastewater diffuser discharge in Lavaca Bay, Texas
    (2023-12) Sellers Jr., Crandon Dewylde; Montagna, Paul; Smith-Engle, Jennifer; Proffitt, Ed
    The Lavaca-Colorado Estuary (LCE) is one of seven major estuarine systems located on the Texas coast. As the second largest estuary in Texas, the LCE provides local and statewide residents with industrial, recreational, and agricultural benefits and historically known to be an abundant and diverse ecosystem for marine organisms. Previous studies have shown there has been long-term decline in benthic abundance, biomass, and diversity in the LCE since 1988. A more recent study found that in fact there was a long-term increase in benthic abundance, biomass, and diversity in the LCE since 1993. Multiple stressors, natural and anthropogenic in origin, are affecting biological community structure. Therefore, these stressors are transforming ecosystems. The purpose of this research is to continue the previous studies to determine if long-term diffuser discharge has any effect on benthic infauna communities in the sediment of Lavaca Bay. This thesis analyzes a 29-year long-term monitoring/time series dataset that was designed to evaluate the impact a discharge pipeline had on constituents of ecological and biological conditions in Lavaca Bay. The purpose of this study was to answer environmental questions about Lavaca Bay. The primary question is: Does the industrial discharge affect the ecological health of Lavaca Bay? If so, are the benthos being affected more near the diffuser site, or is the effect constant throughout the bay? The overall goal was to perform an analysis to determine which parts of the bay are being most affected and to reach conclusions about the overall bay health. Bay health can be indicated by a decline in benthic integrity (i.e., diversity), decreased survival rates of organisms exposed to sediments, and sediment chemical contaminant concentrations over threshold limits. The results revealed that industrial discharge does affect ecological health in localized areas near the outfall. Sediment characteristics closest to the outfall had higher combinations of silt and clay, possibly due to diffuser outflows disturbing the sediment and increasing turbidity. The water column had lower pH, temperature, and DO closer to the outfall. Survival predictions showed an increase over time suggesting that the diffuser does not negatively affect the survival rates of the benthic communities within the bay. However, benthic community diversity means were higher as distance increases away from the outfall. Therefore, even though the diffuser isn’t negatively affecting the overall benthic bay health, it has a negative local effect when compared to stations further away from the outfall area.
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    A diversity baseline of benthic macrofauna along the northwestern insular slope of Cuba (Gulf of Mexico)
    (2023-12) Schiereck, Samantha; Montagna, Paul; Pollack, Jennifer; Schwing, Patrick
    The Gulf of Mexico (GoM) is a unique ecosystem due to the physical characteristics influenced primarily by the Mississippi River in the North and the Loop Current, which originates in the south, resulting in a gradient of organic to carbonate sediment composition. The continental slope of the northern (US) and southwestern (Mexico) portions of the GoM are generally well studied; however, very little is known about the southeastern GoM along the slope of Cuba. To fill this knowledge gap, sediment cores were collected in 2017 at nine stations (974–1580 m depth) to gather baseline data and determine controls on the deep-sea benthic macrofauna community. Oceanographic data indicated a stratified water column typical of an oligotrophic ocean and no evidence of hypoxia. Sediment texture and composition indicated a west-east gradient likely determined by downslope transport of terrigenous material in the eastern part with a high proportion of carbonate in the west. Heavy metals (Cu, Hg, Pb, and Zn) at concentrations known to cause benthic effects were present in the east near the major city of Havana, with the macrofauna community showing characteristics indicative of environmental stress. Stations had a low overall average diversity (15 families/79 cm2) and abundance (7,980/ m2), with high variability among replicates within the stations. The diversity was 48% less, and the abundance was 14% less than in the northern GoM. The major factors influencing macrofauna communities in the continental slope off northwestern Cuba are most likely the lack of organically rich sediment, low sediment deposition rates, and the strong current.
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    Conservation genomic assessment of two imperiled freshwater fishes, Leon Springs Pupfish (Cyprinodon Bovinus) and Pecos Gambusia (Gambusia Nobilis)
    (2023-12) Bretzing-Tungate, Robert James; Portnoy, David; Conway, Kevin; Hollenbeck, Christopher
    Freshwater fishes are increasingly recognized as one of the most imperiled groups of vertebrates, with a growing body of research highlighting the significant threat posed to their biodiversity by human activities. Anthropogenic actions, such as habitat modification and destruction, pollution, overexploitation, and the introduction of invasive species, have led to a decline in the number of freshwater fish species worldwide. Addressing this imminent crisis requires comprehensive conservation efforts, stricter regulatory frameworks, habitat restoration, and heightened public awareness. This project aimed to provide data important for the conservation of two imperiled desert freshwater fishes, Cyprinodon bovinus and Gambusia nobilis, both of which are federally listed as endangered and have undergone range contractions throughout the western United States due to anthropogenic activity. Using genomic techniques, I assessed patterns of genetic diversity within and between populations of both species and screened for evidence of hybridization with introduced congeners. No evidence of contemporary hybridization was found between C. bovinus and C. variegatus, but admixture was detected among G. nobilis and its respective invasive congeners (G. geiseri and G. affinis). Fine-scale population structure was evident for both species of interest and estimates of effective population sizes were low for both species. The results of the study will help update conservation management plans to help mitigate the threat of extinction for both species.
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    Accumulation of epiphytes on Halodule Wrightii in response to nutrient enrichment in East Flats, Corpus Christi Bay and Nighthawk Bay, Upper Laguna Madre, Texas
    (2010-08) Sweatman, Jennifer L.; Cammarata, Kirk; Smee, Lee; Shirley, Thomas; Withers, Kim; Mott, Joanna; Pezold, Frank
    Increased epiphyte abundance on seagrasses is often associated with anthropogenic eutrophication of estuarine ecosystems, but the quantitative relationships are complex and not fully understood. A nutrient enrichment experiment was conducted at two sites during three seasons to measure epiphyte accumulation on Halodule wrightii and artificial seagrass substrates. A novel fluorescence imaging technique, based on excitation of phycobilin and fucoxanthin accessory pigments, was used to quantify epiphyte abundance. For natural seagrasses, significant dose-dependent increases in epiphyte accumulation occurred due to the introduction of nutrients at East Flats, during early summer and fall sampling seasons. Significant nutrient responses were also detected during late summer at East Flats, and during early summer and fall only at a hypersaline lagoon site, Nighthawk Bay. Additionally, nutrient enrichment caused significant decreases in combined seagrass and epiphyte biomass across all seasons at Nighthawk Bay, and during late summer at East Flats. At East Flats, biomass increased with increasing nutrient treatments during early summer and fall seasons. Artificial substrates failed to corroborate results of the natural seagrass experiment; however, a change in species composition was evident, but results were inconsistent across seasons and sites. These findings imply that epiphyte abundance is sensitive to nutrient enrichment under a wide range of ambient conditions, including different predominant grazer abundances, and is likely to increase with eutrophication.
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    Effects of foliarly applied amino acids on sunflower tolerance to arsenic and molybdenum, and DNA methods to characterize associated rhizosphere bacterial communities
    (2011-08) Riis-Due, Stephanie; Cammarata, Kirk; Mott, Joanna; Buck, Gregory; Balasubramanya, M.K.; Pezold, Frank
    Arsenic contamination of soil is a worldwide concern due to its impact on human health and agriculture. Phytoremediation is an emerging technology that uses plants to remediate metal contaminated sites in situ. Helianthus argophyllus is a sunflower plant that is native to South Texas, and is currently under study as a promising prospect for phytoremediation. This investigation focused on the use of foliarily applied amino acids, glycine or a mixture of cysteine and glutamate, to enhance the tolerance of Helianthus argophyllus to weekly treatments of arsenic+molybdenum (2 mM each). Plants typically died over a treatment period of 2-5 weeks, but foliar applications of glycine, in particular, reduced the yellowing of leaves and delayed the onset of toxicity symptoms and death. Other data suggests that the foliar amino acid effects are due to enhanced exclusion of the metalloids from the above-ground plant parts, possibly implicating amino acid-altered plant-rhizosphere interactions The second component of this study developed methods for the comparison of the rhizosphere communities of sunflower plants among the various treatment groups by using PCR amplification of 16S rRNA followed by denaturing gradient gel electrophoresis. Two DNA extraction kits were compared for their effectiveness at extracting amplifiable DNA from sandy and organic soils. Two sets of primers were also compared. Universal rRNA primers failed to produce any bands by DGGE. However, DGGE banding patterns form a second eubacteria-specific primer set revealed a more complex profile, including a number of unique bands, for a growth chamber soil containing a sunflower plant compared to a growth chamber control soil (without a plant) and a wild sunflower sample.
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    Microbial diversity of bleached nurdles in the NorthWest Gulf of Mexico
    (2023-08) O'Donnell, Colin Andrew; Turner, Jeffrey; Buck, Gregory; Conkle, Jeremy; Tunnell, Jace
    Nurdles are the raw material in the manufacture of plastic products. They are mass produced and transported worldwide, but accidental and negligent spills pollute marine environments. In the Gulf of Mexico (GoM), a citizen science initiative, the Nurdle Patrol, revealed that 20 of the highest nurdle-polluted beaches are found in Texas. Microorganisms, including potentially pathogenic bacteria, rapidly colonize nurdles. The purpose of this study was to broaden the understanding of nurdle-bacterial coupling through the following objectives: 1) characterize the microbial diversity of nurdles on a recreational beach compared to a natural substrate and 2) isolate potentially pathogenic members of the nurdle community and further analyze those isolates through whole-genome sequencing (WGS) and antimicrobial resistome analysis. Results show that the nurdles were colonized by a distinct (Faith’s phylogenetic distance, P < 0.001) and more uniform microbial community than beach sand. The nurdle community was dominated by Proteobacteria (69.5%) and Bacteroidota (21.7%) at the phylum level, and Rhodobacteraceae (26.2%) at the family level. Culturable members of the nurdle community included potentially pathogenic Bacillus licheniformis and Bacillus paralicheniformis. Isolates possessed antimicrobial resistance genes (e.g., ATP-binding cassette (ABC) antibiotic efflux pumps and class A Bacillus cereus Bc beta-lactamases), and two B. paralicheniformis isolates appeared to be multidrug resistant (i.e., peptide, macrolide, and penam resistant). Results demonstrate that nurdles were colonized by a distinct community compared to a natural substrate. Additionally, nurdles supported the growth of potentially pathogenic Bacillus species with the genetic potential for antimicrobial resistance. Overall, these results establish a baseline knowledge of nurdle microbial diversity in the northwest GoM.
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    Application of UAS photogrammetry and geospatial AI techniques for palm tree detection and mapping
    (2023-08) Regmi, Pratikshya; Starek, Michael; Chu, Tianxing; Medrano, Antonio
    Uncrewed aircraft systems (UAS), commonly known as drones, underwent significant advance ments in recent years, particularly in the development of improved sensors and cameras that enabled high-resolution imagery and precise measurements. This study utilized a UAS to capture aerial imagery of Texas A & M University-Corpus Christi (TAMUCC) main campus, which was then processed using Structure-from-Motion (SfM) photogrammetric software to generate orthomosaic imagery. The primary purpose of this study was to utilize the orthomosaic imagery acquired from UAS to detect, map, and quantify the number of palm trees. Initially, three deep-learning models were trained using the same set of training samples. The model exhibiting the highest performance in terms of precision, recall, and F1-Score was selected as the optimal model. The model obtained through the fine-tuning of a pre-trained GIS-based model with additional training samples was identified as the optimal choice, yielding the following values: precision=0.88, recall=0.95, and F1-score=0.91. This model successfully detected a total of 1414 sabal palm trees within our study area. The chosen optimal model was employed to examine the impact of ground sampling distance (GSD) on the deep learning model. GSD values were varied, namely 5 cm, 10 cm, 20 cm, and 40 cm. The findings revealed that the model’s performance deteriorated as the resolution decreased. Furthermore, the optimal model was subjected to an additional test using multi-temporal datasets with approximately the same GSD (1.5 cm). These datasets included one acquired a year prior to the model’s training datasets, and another obtained three months after the training datasets. Remarkably, the results demonstrated that the model maintained a comparable level of accuracy across all three testing datasets. The obtained results were verified using ground truth values taken in a small portion of the study area. This study concludes that deep learning models for object detection exhibit superior performance when fine-tuned with training samples specific to the area of interest. Furthermore, it is evident that the optimal model’s effectiveness diminishes significantly when the imagery resolution is reduced. Additionally, the performance of the deep learning model remains relatively consistent when applied to datasets acquired at different time frames, as long as the resolution of the testing data remains the same. In summary, the application of deep learning demonstrates its efficacy, user-friendliness, and time-saving capabilities for object detection. This study shows how we can use UAS and deep learning to detect palm trees. It helps us develop better ways to monitor and manage palm trees.
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    Quarter von Mises distribution
    (2023-08) Myers, Mason Gene; Guardiola, Jose; Gajamannage, Kelum; Jin, Lei
    The world today is increasingly relying on data science and statistics to analyze various types of directional data, such as text data, health studies, image processing, wireless sensor networks, environmental monitoring, robotics, and materials science. In many cases, these data exhibit positive orientation and require probability distributions that are confined to positive regions, such as the positive quarter of the unit circle. These facts highlight the main objective of this thesis, which is to propose a new transformation of the von Mises distribution specifically tailored for the positive quarter of the unit circle. Currently, no such distribution exists. The newly introduced distribution, referred to as the Quarter von Mises Distribution, has been thoroughly investigated in this work. The research includes characterizing the distribution through moments and developing its main properties. Additionally, methods for estimating the distribution parameters using maximum likelihood estimation are presented, along with a hypothesis testing approach using the likelihood ratio test. Furthermore, practical data applications are demonstrated to showcase the effectiveness of these methods. Overall, this thesis contributes to the field of data science and statistics by providing a novel distribution that can accurately model directional data restricted to the positive quarter of the unit circle.
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    A comparative analysis of georeferencing techniques for crop canopy height estimation using UAS photogrammetry
    (2023-08) Landivar Scott, Jose Luis; Starek, Michael; Bhandari, Mahendra; Chu, Tianxing
    In the rapidly evolving fields of geospatial engineering and precision agriculture, the accuracy and reliability of georeferencing techniques and Uncrewed Aircraft System (UAS) methodologies are crucial for effective decision-making and crop management. This research aims to enhance UAS Structure-from-Motion (SfM) photogrammetry data quality for crop canopy height estimation in high-throughput phenotyping. The study investigates and compares the accuracy and reliability of three distinct methods used for georeferencing of the UAS imagery, which subsequently enables more accurate SfM 3D reconstruction: Global Navigation Satellite System (GNSS) without any correction aiding (GNSS-only), GNSS+Real-Time Kinematic (RTK), receiving RTK corrections from a local base station, GNSS+Real-Time Network (RTN), receiving RTK corrections from the Texas Department of Transportation (TxDOT) GNSS reference station network. The study further assesses the correlation between manually measured plant heights and those estimated from UAS-SfM point cloud data, exploring three different Digital Terrain Model (DTM) generation techniques. The research was conducted at the Texas A&M AgriLife Research and Extension Center in Corpus Christi, Texas, USA, on corn crops grown during the 2022 agricultural season. The three DTM generation methods under consideration included 1) using a DTM acquired from a flight conducted before plant emergence, 2) creating a DTM by interpolating ground height points, and 3) implementing automatic classification algorithms. Findings initially revealed that the GNSS+RTK method consistently outperformed the other georeferencing techniques, delivering more accurate results across various dates. Despite these overall trends, there were some instances where the GNSS+RTK method did not consistently outperform the other techniques. The use of one ground control point (GCP) improved georeferencing accuracy compared to scenarios with no GCPs used, while GNSS-only without correction aiding reported the least accurate results as expected. Regarding plant height estimation, the highest accuracy was generally achieved with greater canopy cover percentages, with the optimal percentage varying depending on the data collection date and DTM creation method. The highest coefficient of determination (R2) of 0.92 between manual measurements and UAS-SfM derived plant heights was found when the DTM was either interpolated from ground height points or obtained from a pre-emergence flight.
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    Development of bis-bipyridinium and anthracene carboxyimide-based stimuli-responsive soft matter
    (2023-08) Jakharia, Vandan Paresh; Olson, Mark; Billiot, Fereshteh; Billiot, Eugene
    This thesis focuses on the design and synthesis of an array of novel amphiphilic and polymeric molecules as precursors for developing dynamic stimuli-responsive supramolecular materials by harnessing the competency of non-covalent interactions. Over the past decades, bipyridinium-based derivatives have gained tremendous attention due to their applicability as functional units in tunable supramolecular complexes. The innate propensity of functionalized bipyridinium salts to serve as a ?-electron deficient acceptor allows them to undergo ?-? stacking donor-acceptor CT interactions in the presence of ?-electron rich organic molecules. This characteristic feature was employed to develop novel bipyridinium-functionalized amphiphiles and bio-polymeric materials that are capable of engaging in molecular recognition with and facilitating the extraction of melatonin, a neurotransmitter from water. The first project reports the design and development of heptyl and glycol-bridged bis-bipyridinium-based gemini amphiphiles that can undergo template-directed self-assembly. Previous studies indicated that the electrophilic aromatic nature of tetra-cationic bis-bipyridinium gemini amphiphiles can be exploited to form ?-? stacking charge-transfer interactions with ?-electron rich molecules. Thus, in an effort to establish structure-property relationships and understand the effect of the bridging unit, varied bridged bis-bipyridinium gemini amphiphiles were synthesized. They were investigated for their use of melatonin as a template for directed self-assembly processes. The charge-transfer interactions between the units lead to absorption band formation in the visible region of the electromagnetic radiation that can be exploited for various material applications. Upon comparing, the two derivatives in detail, their micellization behavior, surface properties, thermodynamic parameters, UV-Vis absorption, and micellar size exhibited similar characteristics. However, the heptyl-bridged gemini amphiphile responded to templation much more strongly, while the glycol-bridged gemini amphiphile exhibited higher solubility, they both portrayed excellent amphiphile and surface-active characteristics. The second part of this work focuses on employing ?-electron deficient bipyridinium units to design and process functional lipoic ester-based polymeric materials for the indole-base molecular targets from water. A series of lipoic-ester based-bipyridinium functionalized polymers with varying alkyl tail lengths were developed and studied to determine structure-property correlations and analyze their material characteristics. Out of the eight-novel functionalized polymeric materials, bipyridinium-bridged lipoic ester polymer (BLEP) formed polymeric sheets while nonyl-bipyridinium-functionalized lipoic ester polymer (9C-BFLEP) formed coacervates in water. Both materials showed comparable and acceptable efficiency in adsorbing melatonin out of solution by harnessing ?-? stacking charge-transfer interactions in conjugation with the hydrophobic effect. This approach provided a quick and promising method for the remediation of indole-cored molecules from water. Lastly, an anthracene carboxyimide derivative was synthesized with the ability to undergo a photo-induced [4+4] cycloaddition dimerization process. The dimerization can easily be reversed upon heating. The compound was found to be able to have a special feature that allows them to undergo single crystal-to-single crystal photo-dimerization upon exposure to UV light. This controlled switchable characteristic property of anthracene carboxyimide are unique and can be utilized for developing tunable molecular switches with applications where stimuli-responsive materials are required.
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    Numerical investigation of the population distribution in heterogenous domain
    (2023-08) Henry, Stephen Andre; Sadosvki, Alexey; Vasilyeva, Maria; Denny, Diane; Muddamallappa, Mallikarjunaiah
    We consider the spatial-temporal model of multi-species population distribution in two-dimensional heterogeneous domains. A coupled system of time-dependent diffusion-reaction equations describes the mathematical model of such problems. To solve the problem numerically, we construct an unstructured grid that resolves inclusions on the grid level and produces a semi-discrete system using a finite element method. For time approximation, we apply an explicit-implicit scheme where the reaction term of the equation is taken from the previous time layer. We present numerical results for several test problems to investigate the influence of the geometry and parameters on time to reach equilibrium and the final equilibrium state. An extension of the model is also considered, where we add a memory effect by introducing a time-fractional multi-species model. We derive an implicit finite difference approximation for time discretization based on Caputo’s time fractional derivative. A numerical investigation is performed for various orders of the time derivative.
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    Fraud detection using optimized machine learning tools under imbalance classes
    (2023-08) Isangediok, Mary; Gajamannage, Kelum; Guardiola, Jose; Mallikarjunaiah, Muddamallappa
    Fraud detection is considered to be a challenging task due to the changing nature of fraud patterns over time and the limited availability of fraud examples to learn such sophisticated patterns. Thus, fraud detection with the aid of smart versions of machine learning (ML) tools is essential to assure safety. Fraud detection is a primary ML classification task; however, the optimum performance of the corresponding ML tool relies on the usage of the best hyperparameter values. Moreover, classification under imbalanced classes is quite challenging as it causes poor performance in minority classes, which most ML classification techniques ignore. Thus, we investigate four ML techniques, namely, logistic regression, decision trees, random forest, and extreme gradient boost, that are suitable for handling imbalance classes to maximize recall and simultaneously reduce false negatives. First, these classifiers are trained on two original benchmark unbalanced fraud detection datasets, namely, phishing website URLs and fraudulent credit card transactions. Then, three synthetically balanced datasets are produced for each original data set by implementing the sampling frameworks, namely, random under sampler, synthetic minority oversampling technique (SMOTE), and SMOTE edited nearest neighbor (SMOTEENN). The optimum hyperparameters for all 16 experiments are revealed using the method RandomzedSearchCV. The validity of the 16 approaches in the context of fraud detection is compared using two benchmark performance metrics, namely, area under the curve of receiver operating characteristics (AUC ROC) and area under the curve of precision and recall (AUC PR). For both Malware datasets, phishing website URLs, and credit card fraud transaction datasets, the results indicate that extreme gradient boost trained on the original data shows trustworthy performance in the imbalanced dataset and manages to outperform the other three methods in terms of both AUC ROC and AUC PR.
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    PH effects on solid phase extractable dissolved organic matter: Expanding the analytical window
    (2023-08) Elliott, Justin Yoshida; Abdulla, Hussain; Felix, Joseph; Hu, Xinping
    Marine dissolved organic matter (DOM) is the largest exchangeable organic carbon pool, holding comparable amounts of carbon as CO2 in the atmosphere and exceeding all biomass. DOM constituents are made up of thousands of unique organic compounds with astounding molecular diversity, featuring a wide range of hydrophobicity, size, and acidic or basic properties. Modern high resolution, high accuracy, and fast cycle time mass spectrometers can provide deep molecular insights into complex mixtures but require compatible samples. The inorganic matrix and low DOM concentrations have required organic biogeochemists to rely on Agilent Bond Elut Priority PoLutant (PPL) Solid Phase Extraction (SPE) to isolate and concentrate DOM through hydrophobic interactions. Currently, the standard SPE method has been optimized to maximize recovery? of dissolved organic carbon (DOC) through sample acidification and methanol elution. However, there is a lack of full understanding of the effect of adjusting the sample pH on the extraction efficiency of different DOM compounds. This study investigated the effects of pH modification on the SPE recoveries and the effects of various procedures on the isolated DOM. This study collected water samples from three sites to represent different marine systems (Lavaca River, Baffin Bay and Gulf of Mexico) with unique sources and signatures of DOM. Samples were acidified to pH 2, kept at natural pH, basified to pH 10 or run sequentially where the permeate was further isolated. Various modified methanol elution solvents were tested, comparing methanol, acidic methanol, basic methanol, and combinations of both. The isolated DOM was chemically characterized in positive mode separated with reverse-phase high performance liquid chromatography (RP-HPLC) and in negative mode with Anion Exchange Ion Chromatography (AEX-IC) on an Orbitrap Fusion Tribrid mass spectrometer (OT-FTMS) using data dependent acquisition (DDA). The standard SPE procedure with acidification yielded the highest recoveries but showed bias against dissolved organic nitrogen (DON). The samples that were not acidified, including natural pH or pH 10, yielded a different fraction of enigmatic DOM with a higher nitrogen percentage than the DOM isolates using the standard procedure. We found that through isolating DOM from a water sample at natural pH and pH 2, two fractions of DOM can be isolated, including hydrophobic DOM, acidic DOM, and basic DOM. These results suggest in order to better represent DOM from marine systems, collecting both fractions and analyzing in both positive and negative modes provide a more comprehensive and representative isolate of DOM.