Theses
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Item 2D and 3D Mapping of a Littoral Zone with UAS and Structure from Motion Photogrammetry(2015-05) Giessel, Justin ZacharyAdvancements in the miniaturization of sensors and their integration in light‐weight, smallscale unmanned aerial systems (UAS) have resulted in an explosion of uses for inexpensive and easily obtained remotely sensed data. This study examines the capabilities of a small‐scale UAS equipped with a consumer grade RGB camera for 2D and 3D mapping of a sandy bay shoreline using Structure from Motion (SfM) photogrammetry. Several key components are analyzed in order to assess the utility of UAS‐based SfM photogrammetry for beach and boundary surveying of the littoral zone. First, the accuracy of the 3D point cloud produced by the SfM densification process over the beach is compared to high accuracy RTK GPS transects. Results show a mean agreement of approximately 7.9 cm over the sub‐aerial beach with increased error in shallow water. Minimal effects of beach slope on vertical accuracy were observed. Secondly, bathymetric measurements extracted from the UAS/SfM point cloud are examined, and an optical inversion approach is implemented where the SfM method fails. Results show that a hybrid elevation model of the beach and littoral zone consisting of automatic SfM products, post‐processed SfM products, and optical inversion provide the most accurate results when mapping over turbid water. Finally, SfM‐derived shoreline elevation contour (boundary) is compared to a shoreline elevation contour derived using the currently accepted RTK GPS method for conducting legal littoral boundary surveys in the state of Texas. Results show mean planimetric offsets < 25 cm demonstrating the potential of UAS‐based SfM photogrammetry for conducting littoral boundary surveys along non‐occluded, sandy shorelines.Item 3-D Hybrid Trajectory Modeling for Unmanned Aerial Vehicles (UAVS)(2019-08) Wang, Baoqian; Xie, Junfei; Garcia Carrillo, Luis Rodolfo; Zhang, NingThe burgeoning use of unmanned aerial vehicles (UAVs) evidences forthcoming environments where innumerable UAVs will appear in the National Airspace System (NAS). The UAS traffic man- agement (UTM) aims to provide solutions to enable safe integration of numerous UAVs into the NAS, but the design of effective UTM strategies faces significant challenges. One of the challenges is to develop high-fidelity trajectory models for UAVs of partially known or unknown dynamics. Tradi- tional physics-based models that require costly system identifications and field tests, and data-based models that require large amount of real flight data may not be feasible. To address this challenge, this paper introduces a hybrid 3-dimensional (3-D) UAV trajectory modeling framework, which in- tegrates the physics-based and data-based models to capture the dynamics of UAVs of interest with high accuracy using only a small amount of real flight data. Simulation studies and field tests validate and demonstrate the good performance of the proposed framework.Item 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, PatrickThe 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.Item 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, FrankIncreased 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.Item Analyses of biological communities and development of indices of biotic integrity for monitoring tidal streams along the upper Texas coast(2020-05) Margo, Abraham; Pollack, Jennifer Beseres; Withers, Kim; Tolan, JamesTidal streams along the upper Texas coast are characterized by large heterogeneity in abiotic conditions and biotic communities, posing challenges to managers seeking to assess their ecological condition and develop effective management strategies. There is currently no standardized protocol for assessing ecological condition in Texas tidal stream systems. The goal of the current study was to create multimetric indices of biotic integrity (IBIs) from nekton and benthic macroinfaunal community metrics that were effective in discriminating between degraded “test” and non-degraded “reference” streams (classified by watershed land-cover data). Fifteen tidal streams were sampled twice per year in 2018 and 2019 to assess water quality, nekton, and benthic macroinfaunal dynamics. In order to create the multimetric indices of biotic integrity, multiple univariate metrics were assessed to determine the extent to which they differentiated between test and reference sites. Selected metrics were used as components in developing the multimetric IBIs, which give higher scores to samples that have similar biotic characteristics to our reference condition samples. Multivariate analyses provided a complementary approach to selection of IBI metrics by visualizing, comparing, and identifying community-level changes as well as taxa that associate with the test or reference condition. Results indicated that overall differences in biological communities between test and reference sites were often not extremely strong. Multivariate analyses indicated nekton communities exhibited stronger differentiation between test and reference samples whereas benthic macrofaunal communities were influenced more by year to year variations. However, several univariate metrics highlighted components of communities that did differ between test and reference sites, and these metrics were used to form the IBI. Comparing IBIs for both nekton and benthic macroinfauna can provide a more comprehensive understanding of biotic integrity in tidal streams than focusing on one or the other. Results should be interpreted with some caution but could help inform water resource management decisions that seek to support aquatic life use while balancing human needs for food, recreation, and industry.Item Analysis and applications of the weighted central direction method(2016-12) Choi, HaekyoungIterative methods yield an approximated solution to a given problem by producing a sequence of points that converges to the exact solution. Due to the effectiveness of these methods, they become one of the core mathematical procedures widely used in many major mathematical areas such as Differential Equations, Linear Algebra, and Matrix Analysis. The Methods of Alternating Projection, which we will use in this thesis, form a class of iterative methods based on the relevant projection algorithm introduced by John von Neumann. This outstanding algorithm received considerable attention by mathematicians which contributed to a number of different algorithms to solve several problems. Recently, two former graduate students at Texas A&M University-Corpus Christi, Melina Wijaya and Zulema Cervantes, introduced a couple of new algorithms in this area. Wijaya presented the Weighted Direction algorithm, and Cervantes introduced the Weighted Central Direction algorithm by combining the Weighted Direction and the Central Direction. The algorithm with the combination of two directions achieved a faster convergence than the algorithm with the Weighted Direction only. However, the Weighted Central Direction algorithm needs a parameter which depends on the size of the problems. This thesis carries two objectives. Firstly, study the role of the wide angle condition which guarantees the convergence in the Weighted Direction algorithm in order to analyze if this condition is necessary for the convergence of the algorithm. Secondly, improve the algorithms developed by Wijaya and Cervantes in order to obtain a faster convergence by finding an adequate ratio between the Weighted Direction and the Central Direction that is independent of the size of the problems.Item An analysis of community resilience indicators in the South Texas Bend region(2022-12) Sheasby, Yvonne Marie; Yoskowitz, David; Porter, Kateryna; Jorgensen, DanielCommunity Resilience is the collective ability to diversify the strengths in a community and establish safeguards to better mitigate impacts from disasters. The application of community resilience is different in every community because of their unique characteristics and what hazards they face. This is one of the reasons why measuring community resilience at the local level is vital. Since Hurricane Harvey hit the Texas mid-coast in 2017, the Coastal Bend region and all the local governments within have shifted their focus increasingly toward community resilience and currently need assistance with resilience capacity-building. To identify their needs and what capacity exists already, communities in the Coastal Bend region should conduct an analysis of community resilience indicators and the assessment methodologies they are included in. Though there are several community resilience assessment methodologies worldwide, only 8 out of 73 indices met the selection criteria established during this study and were included in the analysis. It is difficult to know which assessment methodology is best to use for different types of communities and situations. Many communities, especially in rural and underserved areas, lack the resources to conduct and implement resilience measurements. The purpose of this study is to develop a new methodology to determine which community resilience assessment tool(s) are best to use at the local level by conducting a case study analysis in three counties in the South Texas Coastal Bend region, which include Nueces, Refugio, and San Patricio. After distributing two surveys and conducting two focus group sessions, the results were used to help evaluate if community resilience measurement at the local level can be adapted to take into account all shocks and stressors.Item An analysis of emergency management agencies gis data for planning 9-1-1 services for the border counties of the lower Rio Grande Valley(2017-08) Nino, Orlando; Smith, Richard; Jeffress, Gary; Huang, YuxiaTexas 9-1-1 entities collect data that can be used to gain knowledge on 9-1-1 call patterns and trends. It is ideal to know these issues too efficiently maximize monies appropriated to local emergency management agencies. This research will analyze 9-1-1 calls and two police departments calls for service using Geographic Information Science (GIS). This information provided by multiple emergency management agencies to better plan 9-1-1 services in the border counties of the Rio Grande Valley. The data that was used is recorded daily by these agencies. Many emergency management organizations keep their own GIS data in-house and they need to be analyzed with 9-1-1 data. Analyzing various GIS databases can yield better results, in finding correlation within each dataset, hotspots and inadequate data collection. These results can then be used by the organizations that contributed the data and shared to all stakeholders.Item Analytic solutions for the harmonic potentials involving concentric layered dielectric spheres(2018-05) Cisneros, Frank; Palaniappan, Devanayagam; Sadovski, Alexey L.; Zimmer, BeateThe mathematical problem of a conducting spherical core of radius 𝑎 concentrically covered by a dielectric phase of radius 𝑏 placed in an arbitrary external electric field is investigated. The vector field equations for the electric field (Maxwell equations) and the boundary conditions are transformed to a scalar boundary value problem (BVP) in terms of the harmonic potential functions. The harmonic potentials denoted by Φ𝐼(𝑟,𝜃,𝜙) and Φ𝐼𝐼(𝑟,𝜃,𝜙) where (𝑟,𝜃,𝜙) are spherical coordinates, satisfy the Laplace equations in the regions 𝑏<𝑟 and 𝑎 < 𝑟 < 𝑏, respectively. General analytical solutions for the potentials in the two phases are determined in infinite series form using spherical harmonics methods. Exact closed form solutions are also derived via an alternative approach. The latter solutions contain integrals involving harmonic functions. Our general solutions are applicable for arbitrary external potentials disturbed by a conducting spherical core with a dielectric coating. Several illustrative examples are investigated and exact solutions for them are constructed using our general solutions. The non-dimensional parameter 𝑘= 𝜀𝐼/(𝜀𝐼+𝜀𝐼𝐼) , where 𝜀𝐼 is the dielectric constant for the region 𝑟 > 𝑏 and 𝜀𝐼𝐼 is the dielectric constant for the region 𝑎 < 𝑟 < 𝑏, influences the potential patterns in the case of externally imposed constant and linear fields. Our results for the source induced field indicate that the force is positive or negative depending on 𝑘 < 0.5 or 𝑘 > 0.5. Furthermore, the force is greater than zero when the core radius 𝑎 approaches the value of the outer radius 𝑏. We believe that our mathematical results are of interest where coated dielectric objects are exposed to external electric fields.Item Antibacterial properties of plant extracts from curanderismo (Mexican herbal medicine) on pathogenic strains of Vibrio Vulnificus isolated from the Coastal Bend region of Texas(2022-12) Patel, Hinal Arvindbhai; Buck, Gregory; Sparks, Mary Jean; Daru, BarnabasVibrio vulnificus, a Gram-negative mesophilic bacterium that belongs to the gamma Proteobacteria phylum and family Vibrionaceae, is halophilic and asporogenous and is autochthonous to marine and estuarine environments. Between April and October, the organism reaches peak levels in the Gulf of Mexico. Previous studies indicate that antibiotic resistance is increasing in Vibrio vulnificus. Finding a solution to this antibiotic resistance problem is critical for both aquaculture and medical care with persons exposed to Vibrio. One possible treatment modality to control the effects of antibiotic resistant bacteria is Curanderismo, a popular alternative plant-based medicine derived from Mexican culture, which has been overlooked by scientific investigation and may be used in lieu of pharmacologic antimicrobial agents. This study hypothesizes that certain plants may be used for treatment of antimicrobial-resistant strains (AMR) of Vibrio vulnificus. The objectives are to (1) investigate the effect of active plant extracts and tinctures on strains of Vibrio vulnificus by Kirby-Bauer disk diffusion susceptibility testing; (2) Investigate the effect of active plant extracts on the ability of Vibrio vulnificus to form biofilms, which indirectly observe quorum-sensing (QS)-regulated virulence traits. Ten typical herbal treatments of Curanderismo used to treat wounds and infections in south Texas were made as tinctures in against the four Vibrio vulnificus strains. In addition, biofilm assays revealed these six plant extracts showed better antimicrobial and anti-biofilm activity compared to the bacterial control. These findings demonstrate that certain plant tinctures may be plausible treatment methods and future studies will investigate specific plant tinctures on a wider range of south Texas Vibrio vulnificus strains.Item Applicability of the microfragmentation technique to propagate corals in a fisherfolk community in the Philippines(2019-12) Broquet, Nicole C.; Scarpa, John; Siccardi, Anthony; Pollack, Jennifer Beseres; Vaughan, DavidCoral nursery implementation is becoming a highly prevalent method of coral restoration in the Philippines. These nurseries primarily focus on fast-growing branching corals and do not commonly include massive corals. This is due to the slow growth rate and morphology of these corals, which are not conducive to traditional nursery methods. Microfragmentation is a relatively new technique that has displayed positive results for massive coral propagation. This method utilizes small coral fragments (≈1-3 cm) that are mounted on platforms, then placed in ex-situ or in-situ nurseries. The fragments exhibit rapid growth, which decreases the duration of the nursery phase before transplantation. Though microfragmentation is becoming more practiced, there is no published literature specifically focused on this method in the Philippines. The present study aimed to determine if: 1) coral specimen (i.e., putative genotype) significantly influenced growth, and 2) this method was viable in a fisherfolk community in the Western Visayas of the Philippines. Five corals of opportunity (putative genotypes) of the lobe coral, Porites lobata, were fragmented with hammer and chisel by several volunteer fisherfolk. The fragments were cultured from April-August 2018 in an in-situ fixed-leg nursery at a depth of approximately 2m. Maintenance was performed weekly and measurements of growth (i.e., volume change) were conducted monthly. The fragments were then transplanted to a selected restoration site and monitored for one month. A hierarchical Bayesian log-linear regression model indicated that 59.7% of growth (volume change) variation was attributed to coral specimen (i.e., putative genotype) and 26.4% of growth variation was attributed to the individual fragment. Overall, the average monthly increase in particular specimen’s fragment volume was 23.5% per month (95% CI, 3.43% - 43.9%/month) with the greatest monthly increase for a specimen at 30.1% per month (95% CI, 19.3 – 40.3%/month). Mean tissue spreading was determined to be 43.24cm2 /month (95% CI 44.5 – 79.4 cm2 /month) and mean linear extension was estimated to be 1.55 cm/month (95% CI, 0.92 – 2.02 cm/yr). Though high growth rates for P. lobata were documented in this study, nursery maintenance was significant due to lack of resources and location of nursery. This method may be viable and highly beneficial in established coral nurseries in the Philippines, but may not be feasible in a remote fisherfolk communityItem Application of UAS photogrammetry and geospatial AI techniques for palm tree detection and mapping(2023-08) Regmi, Pratikshya; Starek, Michael; Chu, Tianxing; Medrano, AntonioUncrewed 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.Item Applications of deep learning and multi-perspective 2D/3D imaging streams for remote terrain characterization of coastal environments(2021-12) Pashaei, Mohammad; Starek, Michael J.; Tissot, Philippe; King, Scott A.; Glennie, Craig L.; Lynch-Davis, KathleenThreats from storms, sea encroachment, and growing population demands put coastal communities at the forefront of engineering and scientific efforts to reduce vulnerabilities for their long-term prosperity. Updated and accurate geospatial information about land cover and elevation (topography) is necessary to monitor and assess the vulnerability of natural and built infrastructure within coastal zones. Advancements in remote sensing (RS) and autonomous systems extend surveying and sensing capabilities to difficult environments, enabling more geospatial data acquisition flexibility, higher spatial resolutions, and allowing humans to “see” in ways previously unattainable. Recent years have witnessed enormous growth in the application of small, unmanned aircraft systems (UASs) equipped with digital cameras for hyperspatial resolution imaging and dense three-dimensional (3D) mapping using structure-from-motion (SfM) photogrammetry techniques. In contrast to photogrammetry, light detection and ranging (lidar) is an active RS technique that uses a pulsed laser mounted on a static or mobile platform (from air or land) to scan in high definition the 3D structure of a scene. Rapid proliferation in lidar technology has resulted in new scanning and imaging modalities with ever increasing capabilities such as geodetic-grade terrestrial laser scanning (TLS) with ranging distances of up to several kilometers from a static tripod. TLS enables 3D sampling of the vertical structure of occluding objects, such as vegetation, and underlying topography. Full waveform (FW) lidar systems have led to a significant increase in the level of information extracted from a backscattered laser signal returned from a scattering object. With this technological advance and increase in remote sensing capabilities and data resolution, comes an increase in information gain at the cost of highly more complex and challenging big data sets to process and extract meaningful information. In this regard, utilizing end-to-end analyzing techniques recently developed in artificial intelligence (AI), in particular, convolutional neural network (CNN), developed under deep learning (DL) framework, seems applicable. DL techniques have recently outperformed state-of-the-art analysis techniques in a wide range of applications including RS. This work presents the application of DL for efficient exploitation of hyperspatial UAS-SfM photogrammetry and FW TLS data for land cover monitoring and topographic mapping in a coastal zone. Hyperspatial UAS images and TLS point cloud data with additional information about the scattering properties of illuminated target in the footprint of the laser beam encoded in returned waveform signals provide valuable geospatial data resources to uncover the accurate 3D structure of the surveyed environment. This study presents three main contributions: 1) Evaluation of different DCNN architectures, and their efficiencies, to classify land cover within a complex wetland setting using UAS imagery is investigated; 2) DCNN-based single image super-resolution (SISR) is employed as a pre-processing technique on low-resolution UAS images to predict higher resolution images over coastal terrain with natural and built land cover, and its effectiveness for enhancing dense 3D scene reconstruction with SfM photogrammetry is tested; 3) Full waveform TLS data is employed for point cloud classification and ground surface detection in vegetation using a developed DCNN framework that works directly off of the raw, digitized echo waveforms. Results show that returned raw waveform signals carry more information about a target’s spatial and radiometric properties in the footprint of the laser beam compared to waveform attributes derived from traditional waveform processing techniques. Collectively, this study demonstrates useful information retrieval from hyperspatial resolution 2D/3D RS data streams in a DL analysis framework.Item Applying segmentation and neural networks to detect and quantify marine debris from aerial images captured by unmanned aerial system and mobile device(2018-08) Tran, Kieu; Conkle, Jeremy; Starek, Michael J.; Gibeaut, JamesMarine debris is a global issue with adverse impacts on the marine environment, wildlife, economy, and human health. Its presence on beaches may vary due to topography, hydrological conditions, proximity to litter sources, and the extent of beach use. Studies of these parameters on beach litter are essential for understanding spatial and temporal patterns; however, this work is labor-intensive and time-consuming. To overcome these obstacles while gaining higher spatial and temporal resolution data, two methods were developed (1) segmentation and (2) regions with convolutional neural networks (R-CNN) to detect and quantify marine macro-debris using high-resolution imagery. Data to develop and test the methods were collected using a small rotary Unmanned Aerial System (UAS) with an RGB sensor at various altitudes over a 100m section of sandy beach of Mustang Island, Texas. Images were processed through structure-from-motion photogrammetry to derive orthomosaics for each flight. Orthomosaics were then run through an image processing, and classification workflow developed for segmentation and delineation of imaged debris. The segmentation algorithm detected the most debris at the lowest altitude (215 of 341 total at 15m), with decreasing detections at 22m (101) and 35m (50). The second method applied deep learning object detection to smartphone images. Based on the dataset and the network architecture, R-CNN mean average precision can range from 31.4% to 66% (Girshick et al., 2014). Training for R-CNN consisted of three stages: extract region proposals, train AlexNet to classify objects, and train a bounding box regression model to locate the debris. Average precision for the Specifically Engineered Algorithm for Gathering and Understanding Litter Location (SEAGULL) detector was ~22%, meaning it has a low performance at detecting all the debris in the testing dataset and correctly predicting whether or not that region was debris or not. Object detection has been a challenging task for decades, and with a low overall debris detection accuracy, it needs to be further improved with the use of a larger dataset or adjusting the training parameters. Few studies have been published on this topic, but this work demonstrates that remote sensing with UAS has the potential to increase research efficiency.Item Aqui is anywhere we choose to call home(2022-05) Negreros, Jacqueline; O'Malley, Ryan; Katz, Louis; Aubrey, Meg; Peña, Joe; Hinojosa, YndalecioJacqueline Negreros draws upon her parents’ experience as immigrants in Aquí Is Anywhere We Choose to Call Home to highlight themes of tradition, immigration, and assimilation conveyed through memories shared by the artist and her family. She uses food as a metaphorical device to probe cultural attitudes of authenticity and otherness through ingredients that remain traditional and those that have grown with her. Aquí centers around the communal preparation of barbacoa de pozo – from its roots in her parents’ village of Zacapala, Puebla, Mexico to its evolution into barbacoa al vapor, using a steam pot, adapted from her family’s life in the United States. Through printmaking and sculpture, Negreros explores the duality immigrants contend with after leaving their homeland for a new nation and how customs can evolve across generations. Rice embossed paper depicts objects fundamental to the preparation of this meal and signifies cultural and familial traditions. Veils sewn from guaje seed pods and arranged carizzo stalks are relics from the landscape of Zacapala. Collected around Corpus Christi and considered invasive, they form a border between belonging and otherness. El pozo in the middle of the gallery is the portal by which everything enters or emerges, a point of origin. Comprised of dirt from the Texas Mexico border and sand from the beach at Texas A&M-Corpus Christi, El pozo merges physical spaces from the past and present for experiences to coexist. La Pancita signifies matriarchal bonds and the importance of ritual. The installation and preparation of this meal create an intimate view into the artist’s use of food to traverse time, and this supporting paper serves as an archive of her family history and this important recipe.Item Artificial neural networks for approximating the solutions to nonlinear ordinary differential equations(2023-05) Martinez, Mara Rose; Muddamallappa, Mallikarjunaiah; Ekici, Celil; Palaniappan, DevanayagamArtificial neural networks (ANNs) are the computer archetype of biological networks in the human brain. An ANN is a group of interconnected nodes stacked in layers and each layer is connected with its preceding and succeeding one via specified weights. The numerical algorithms based on ANN have been shown to perform well in approximating the differential and integral operators. In this thesis investigation, a neural network architecture is proposed for approximating the numerical solutions to the nonlinear ordinary differential equations. A comparative study is performed between the ANN predictions and the approximation obtained from finite element method (FEM). The solution finding problem using ANN is formulated as a minimization of a total loss function, an L2-type function or root mean square type function, which is a sum of differential equation loss and the boundary loss terms. For the minimization, a feedforward-type unsupervised neural network architecture is examined in this thesis. Recent works have shown that such an unsupervised minimization yields highly accurate prediction which can approximate the numerical solution to the differential equation. However, currently no study is available in the literature on a comprehensive unified ANN method with particular choice of the loss function and network’s hyperparameters and how such choices influence the accuracy of the network prediction. In this thesis, we addressed some issues concerning the design of the network to obtain highly accurate numerical results. The sensitivity in the network’s accuracy with respect to the size of the training data, activation functions, optimizers, number of hidden layers, and the number of neurons in each hidden layer is also studied. Our trail solution consists of two parts: the first part satisfying the differential equation; the second part stems from satisfying boundary conditions. At the training phase access to the exact solution is not needed, however, the network adjusts its training based on the linear interpolation of the randomly chosen data points from the computational domain. A backpropogation step is needed for a calibration of the network parameters to obtain accurate prediction. We investigate the proposed ANN method to approximate the numerical solutions to two nonlinear boundary value problems from fluid dynamics: Electrohydrodynamic fluid model; one-dimensional Darcy-Brinkman-Forchheimer model. A comparison of the network solution is made with that of the one obtained from classical continuous finite elements. We report that ANN method developed in this thesis performs better in achieving higher accuracy within the fewer number of data points. We believe that the proposed architecture along with the “correctly” chosen hyperparameters constitute a better numerical approximator for the partial differential equations in higher dimensions.Item Assessing embryonic toxicity and end fates of nanoplastics in freshwater environments using gastropod Biomphalaria Glabrata(2022-07-22) Merrill, MacKenzie Leigh; Xu, Wei; Bahr, Keisha; Wagner, Daniel; Mozzachiodi, RiccardoThe wide use of plastics has resulted in not only the accumulation of macroplastic pollution in the aquatic environment but also plastic particles at micro and nano levels (MPs and NPs). Accumulation of these MPs and NPs have numerous adverse effects on the morphology, behavior, and reproduction of living organisms. In this study, we investigated the effects of NPs on the embryonic development of Biomphalaria glabrata, a commonly used gastropod in toxicology studies. This study identified the adsorption of NPs by the embryos of B. glabrata and showed evidence of NP absorption by the hatched juveniles. NP bioaccumulation subsequently triggered the alteration in the expression of several stress response genes, including heat shock protein-70 (HSP70), cytochrome P450 (CYP450), and macrophage migration inhibitory factor (MIF). With the influence of NPs, the hatching rates of B. glabrata embryos varied depending on the sizes of NPs. In addition, the NPs with mean diameters of 1.0 µm or 0.03 µm led to higher embryo mortality rates than 0.5 µm NPs. This preliminary study demonstrated the impact of NPs on the development of B. glabrata embryos. Further studies on the mechanism of NP toxic effects are desired.Item Assessing short-term sediment accretion rates and hydrological influences on a microtidal estuarine wetland: Mustang Island, TX(2015-12) Martinez, MelindaAs sea level rises there has been a growing concern whether salt marsh wetlands can withstand an accelerated rise in sea level by vertically accreting. Sediment accretion is a natural process that changes the elevation of the marsh surface relative to sea level. For a wetland to persist in the long-term, its accretion rate must at least match the rate of relative sea level rise. This study describes sedimentation rates in the estuarine wetlands located on Mustang Island, TX, a sandy barrier island. Sedimentation rates were measured bi-weekly from June 2014 to July 2015 using sediment plates and erosion pins, and over periods of 2.4 to 3.3 years (2012- 2014/2015) using horizon marker techniques. Water level loggers were used to assess hydrological controls on bi-weekly sedimentation patterns. Shallow cores (~15 cm) were collected from the horizon marker plots in August 2014 and July 2015. Vertical accretion rates were compared across different timescales including decadal rates determined using 137Cs from a previous study on Mustang Island, TX. Results indicated sediment accretion across the study area was not significantly influenced by hydrological patterns, with the exception of low marsh environments near tidal creeks (r2=0.52, p < 0.1). The most important factor in determining sediment deposition on sediment plates located near the main tidal creek was the number of flooding events, suggesting that deposition increases as frequency of flooding events increases. The total accumulation deposited on plates was dominated by inorganic sediments, suggesting there is a limit of detrital organic matter contribution for this area. Average vertical accretion using horizon markers was 8.15 ± 5.21 mm yr-1 in upland environments; 4.51 ± 5.21 mm yr-1 in high marsh environments; 3.36 ± 3.57 mm yr-1 in high flat environments; 11.92 ± 9.73 mm yr-1 in low marsh environments; and 1.88 ± 2.54 mm yr-1 in low flat environments. There was a significant difference in vertical accretion rates between both horizon markers and erosion pins, which provide annual-scale accretion rates, when compared to 137Cs, which provide decadal-scale accretion rates (p < 0.1). On average annual vertical accretion rates were 2.8 times higher than decadal rates. Differences between annual and decadal accretion rates are mostly attributed to shallow sediment compaction within the top 3 cm of the wetland surface. Variation in wetland vertical accretion rates increased significantly going from decadal (± 0.41 mm) to annual (± 2.87 mm) to annualized biweekly rates (± 9.60 mm). Annual-scale accretion rates measured using horizon markers in low marsh and upland environments appear to be keeping up with relative sea level rise (RSLR), which is 5.27 ± 0.48 mm yr-1 as measured since the 1950’s at a nearby tide gauge. However horizon marker vertical accretion rates in tidal flats and high marsh environments are not sufficient to overcome sea level rise. Vertical accretion rates were positively correlated with organic and inorganic accretion for all horizon markers (p < 0.1); however, the relative contribution of organic matter decreases as inorganic matter increases. Our findings anticipate environmental shifts in habitats with accretion rates below RSLR. Furthermore, vertical accretion was dominated by inorganic matter, making the wetlands reliant on constant wind and episodic storms to transport sediment to the area. Importantly, these data suggest that storm-induced sedimentation acts to stabilize coastal wetlands and helps certain environments cope with RSLR, but is not sufficient to prevent shifts in the relative composition of the wetland.Item Assessing the acute toxicity of photodegraded anthracene with in vitro and in vivo skin models(2022-07-20) Brzezinski, Molly; Xu, Wei; Seemann, Frauke; Conkle, Jeremy; Zhu, LinThe Gulf Coast of Texas is heavily inundated with petroleum refineries that release Polycyclic Aromatic Hydrocarbons (PAHs) into nearby waters, and these chemicals may pose a threat to human health when they interact with environmental conditions. PAHs are a group of hundreds of different chemicals, and the Environmental Protection Agency has identified 16 priority PAHs. Many of these chemicals are acute skin irritants and can cause skin, lung, bladder, and liver cancer with chronic exposure. Humans can be exposed when they interact with contaminated air, soil, and water. Recent studies have demonstrated that abiotic factors such as UV light, salinity, and pH can modify PAH structure, however, it is unknown how these modifications affect acute toxicity to the human skin barrier. The objectives of this study were to characterize the phototoxic effects of a priority PAH, anthracene by testing photodegradation treatments on cell culture and animal models. Gas chromatography and mass-spectroscopy confirmed the presence of 1,9-anthraquinone and phthalic acid, both known skin irritants, in photodegradation products. Keratinocyte cell culture was used to assess the impacts of photodegraded anthracene on cell migration, viability, and stratification development. We found that longer photodegradation times resulted in decreased cell viability and increased migration. A unique three-dimensional stratification assay demonstrated that photodegraded anthracene reduces differentiation in apical keratinocytes. Relative gene expression analysis suggests that keratinocytes bypass TLR-4 activation and utilize IL-1?, IL-1?, and TNF-? to produce an inflammatory response. Mus musculus studies indicate that extracellular matrix remodeling may be induced by 4, 8, and 24-hour photodegraded intermediates by keratinocyte-derived Il-1?, S100a9, Mmp1, and Connexin43. The results of this study indicate that photodegradation can produce intermediates that may elicit dermal inflammation, and the presence of these intermediates should be evaluated in bays with high foot-traffic.Item Assessing the influence of genotypic diversity on sulfur dynamics in the seagrass halodule wrightii using stable isotope analysis(2022-07-19) Girard, Allyson; Larkin, Patrick; Abdulla, Hussain; Felix, JosephCoastal development and other mounting anthropogenic pressures are threatening valuable seagrass habitats. The greatest risks posed to seagrasses are the effects of coastal eutrophication, which stimulates primary productivity and ultimately supplies abundant organic matter to marine sediments. The decomposition of this material is initially facilitated by aerobic microorganisms, depleting dissolved oxygen and generating anoxic conditions. Under these conditions, anaerobic microorganisms such as sulfate-reducing bacteria begin to dominate the degradation process, which reduce sulfate (SO42-) to sulfide (H2S) for energy production. The accumulation of H2S in marine sediments is problematic for seagrasses, as this molecule can be highly toxic. Yet, seagrasses can withstand relatively high concentrations of H2S in their environments. Stable isotope analyses have been used to investigate sulfide intrusion in seagrass meadows, as the unique isotopic signature of sediment-derived sulfur can be used to trace the uptake of H2S and its distribution throughout the plant. This technique has allowed the study of factors that may influence sulfide production and intrusion, such as reduced light availability, organic matter enrichment, and high temperatures. However, few studies have examined the biological or biochemical features that enable seagrasses to withstand relatively high sedimentary sulfide levels. One biological feature that may help confer resistance is population genetic diversity, which has been identified as an important trait in the survival and performance of seagrass meadows under environmental stress. In general, genetic diversity is thought to play an important role in population resistance to environmental disturbance, as a wider assortment of functional traits encoded at the molecular level results in a variety of phenotypes likely to possess morphological and physiological differences that are complementary. This genotypic complementarity may extend to biochemical strategies associated with tolerance to, or detoxification of, H2S. The purpose of this study was to determine whether sulfide intrusion differs between genotypes of the seagrass Halodule wrightii, a prominent species in the Gulf of Mexico. Further, as the sulfur isotopic composition of marine sediments and seagrass vegetation is known to exhibit high spatial variability, this study also sought to assess sulfide intrusion between populations from distinct sites along the Texas Gulf Coast. Stable isotope data was used to infer the proportion of sulfur in H. wrightii tissues that was derived from sedimentary sulfide, while total sulfur (TS) data was also considered to understand the extent of sulfur accumulation within the plant. H. wrightii genotypes were determined by screening each sample at a series of microsatellite loci previously identified for this species. Although no difference in sulfide intrusion was observed between genotypes, sulfide uptake and distribution was significantly different between the three study sites. The results offer important insight to the effect of local conditions on sulfide intrusion in seagrass meadows and may guide future investigations concerned with the influence of genotypic diversity on H2S metabolism in seagrasses.