Texas A&M University – Corpus Christi
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Bobby Galvan, Manuel Garcia, Chester Rupe, Raul Rios and Walter Furley
No full textBobby Galvan, Manuel Garcia, Chester Rupe, Raul Rios and Walter Furley holding their instrument
Assessing the occurrence, social vulnerability, and legal implications of sargassum influxes in Puerto Rico using a social-ecological systems approach
No full textA dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Coastal and Marine Systems Science.Sargassum spp. influxes are causing significant alterations to both natural and human systems in the Wider Caribbean Region. To understand and respond to this situation, a holistic approach is needed that considers the distribution and dynamics of pelagic sargassum and the impacts and feedback between the natural and human systems. This research aimed to provide information for the decision-making processes regarding sargassum accumulations on the coasts of Puerto Rico. Remote sensing techniques implemented in Google Earth Engine were used to detect and spatiotemporally assess sargassum accumulations along the shoreline. The model developed was able to identify both fresh and decomposing sargassum, as well as Sargassum-brown-tide generated from decomposing sargassum. A combination of a participatory exercise and surveys were used to assess the social vulnerability of an impacted coastal community and to identify factors to reduce their social sensitivity and improve their adaptive capacity, such as establishing mitigation actions to reduce the exposure of residents to toxic gases and improving access to sargassum information. Lastly, legal barriers to implementing effective mitigation strategies and agencies jurisdictions in the permitting process were clarified using a co-production approach with local and federal agencies. Recommendations provided include the development of a territory-wide and priority areas response plans and the continuation of meetings with agencies to clarify legal aspects of sargassum mitigation actions including its disposal on land. This dissertation provides much needed information for household, community, and national decision-making. Methods and findings of this dissertation can also be applied to inform decisions in other coastal areas in the region affected by these recurrent events.Physical and Environmental SciencesCollege of Scienc
Improving the voltage and lifetime in aqueous redox flow batteries utilizing the organometallic [Fe(bpy)3]2+/3+
No full textDepartment of Physical and Environmental Sciences, College of ScienceLong term battery storage is needed for renewable energy sources to buffer their variable output. Redox flow batteries (RFBs) have the potential to store large amounts of energy for on-demand power generation. Current issue: low energy density due to poor solubility of the active species and low voltage outputs. Robust, high voltage catholytes are needed. Iron (II/III) tris-2,2’-bipyridine ([Fe(bpy)3]2+/3+) is a suitable catholyte. This work introduces a new way to synthesize [Fe(bpy)3]2+ and methods to improve performance.This research was supported by funding from The Welch Foundation. Dr. Mark Olson – Chemistry Program Coordinato
The effects of women's, gender, and sexuality studies courses on the development of privilege awareness and intersectional awareness
Get PDFA Thesis Submitted In Partial Fulfillment of the Requirements for the Degree of MASTER OF ARTS in CLINICAL PSYCHOLOGY Department of Psychology from Texas A&M University-Corpus Christi.Privilege is the unearned advantages and benefits an individual experiences based on their gender, race, sexuality, social status, ability, or ethnicity (McIntosh, 1988) while intersectionality posits the interconnectedness of an individual’s social identities that manifest in their life experiences (Collins, 2000; Crenshaw, 1989; Davis, 2008). Privilege studies?(Case, 2007; Case & Rios, 2017) generally focus?on the effect that a single intervention has on one area?of?privilege,?for?example, gender?or race. Fewer?studies (Case, 2012) have analyzed the effects of attending college on?the development of?intersectionality. Building on work showing that the college experience contributes to students’ general identity development (Syed & Amitiza, 2009) and that diversity courses positively influence the development of privilege awareness (Case, 2007; Case & Stewart, 2009), the present study?focuses on whether taking lower-division courses?compared with taking an upper-division?Women’s, Gender, and Sexuality Studies course affects?a student’s?privilege awareness?or intersectional awareness.?Participants (N=118) were attending a Hispanic-serving state university in South Texas with one group (n=75) taking a General Psychology (GP) course and the second group (n=43) taking a WGST course. Demographic data and responses to two surveys were collected using a pre-and post-test design over two consecutive semesters. Results of the GP and WGST students’ scores on both scales indicate no change in their understanding of privilege or intersectional awareness. WGST students, however, demonstrate an overall greater understanding of privilege and intersectional awareness than GP students. Discussion centers on how these results contribute to an understanding of identity development among college students and on ways to improve the measurement of privilege and intersectional privilege for future studies.PsychologyCollege of Liberal Art
Uncoupling techniques for multispecies diffusion–reaction model
Get PDFWe consider the multispecies model described by a coupled system of diffusion–reaction equations, where the coupling and nonlinearity are given in the reaction part. We construct a semi-discrete form using a finite volume approximation by space. The fully implicit scheme is used for approximation by time, which leads to solving the coupled nonlinear system of equations at each time step. This paper presents two uncoupling techniques based on the explicit–implicit scheme and the operator-splitting method. In the explicit–implicit scheme, we take the concentration of one species in coupling term from the previous time layer to obtain a linear uncoupled system of equations. The second approach is based on the operator-splitting technique, where we first solve uncoupled equations with the diffusion operator and then solve the equations with the local reaction operator. The stability estimates are derived for both proposed uncoupling schemes. We present a numerical investigation for the uncoupling techniques with varying time step sizes and different scales of the diffusion coefficient.The research of S.S. was funded by the Ministry of Education and Science of the Russian Federation under grant No. FSRG-2023-0025
Jake Stephens Orchestra playing at an Event
No full textA Picture taken of the Jake Stephens Orchestra playing at an Even
Artificial neural networks for approximating the solutions to nonlinear ordinary differential equations
Get PDFA Thesis Submitted In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE in Mathematics from Texas A&M University-Corpus Christi.Artificial 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.MathematicsCollege of Scienc