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NOVEL TECHNIQUES IN FOURIER PTYCHOGRAPHIC MICROSCOPY FOR MEDICAL IMAGING
Get PDFThe emerging Fourier ptychographic microscopy (FPM) offers a highly efficient approach to enhance the throughput of conventional microscopy. By illuminating the samples with a series of incident angles, FPM computationally reconstructs the high-resolution sample images from the acquired low-resolution measurements. Thus, it overcomes the limitations of traditional optical imaging systems to simultaneously achieve large field of view and adequate spatial resolution. However, to maximize its potential, it is necessary to continuously optimize the performance and verify the clinical utility of FPM system. For this purpose, this dissertation is majorly composed of four different studies. In the first study, we initially explore the feasibility of implementing FPM to reconstruct metaphase chromosomes, aiming to enhance the imaging efficiency by mitigating the trade-off between field of view (FOV) and resolution in conventional microscopic systems. The second study focuses on improving the efficiency of data acquisition of FPM. By employing symmetric illumination and a color detector to accelerate the process, we can potentially increase the data acquisition speed up to 12 times. In the third study, we develop and evaluate a doublet based FPM prototype to further advance the design of more affordable FPM configurations. This prototype replaces the standard 4× objective lens with a commercial achromatic doublet lens of 60mm focal length. Using a 150mm tube lens and a 15×15 LED array, it achieves a theoretical equivalent NA of 0.4. The fourth study is designed to measure the DOF of FPM systems, providing essential insights for the future development of FPM based digital pathology scanners. The measurements follow the principle that DOF is the range along optical axis where the contrast value remains at or above 80% of the maximum as the focus is altered. The corresponding contrast value for each focus position is estimated based on the specific bar pattern where the contrast value of the in-focus MTF curve drops to 0.5. The four studies on FPM investigate its applications, technological advancements, and evaluations, providing a comprehensive exploration of this new technology's potential and supporting its translation toward practical implementation.In addition to the FPM studies, the appendix presents two projects dedicated to computer-aided diagnosis (CAD) scheme developments. These studies utilize radiomics and deep learning techniques to enhance the prediction of chemotherapy outcomes in ovarian cancer treatment with CT scans. The investigations underscore the value of integrating analytical approaches with medical imaging modalities, illustrating how CAD contributes to personalized healthcare through improved diagnostic and prognostic capabilities
Determining the viability of breathwork and meditation as intervention techniques for stress in the forensic science community
Get PDFThe aim of this project was to determine the viability of breathwork and meditation as intervention techniques for stress in the forensic science community. Practitioners in the field and students studying forensic science to become future practitioners were included as participants. The General Well-Being Schedule (GWBS) and the Perceived Stress Scale (PSS) were used to assess the psychological changes in stress and stress responses. Salivary cortisol and cortisone measurements provided statistics to analyze hormonal changes in stress. Participants of the study were requested to partake in practicing cyclic physiological sighing and mindfulness meditation for 30 days, depending on their random assignment into these intervention groups. Subjects in the breathwork group were required to practice the method for five minutes every day, and those in the meditation group had to meditate for 15 minutes every day during the study. They provided survey responses and saliva samples before and after the intervention period, and the hypothesis was that these measurements would reflect a reduction in stress levels. To account for external variables such as previous experience with these methods, exercise habits, religious/spiritual influences, frequency of practice, length of practice during each session, and time of day of practice, these were used to create participant subsets that were analyzed for statistically significant changes (p < 0.05). The data showed that all participants who had previously practiced breathwork (p = 0.012) and students who had previously meditated (p = 0.032), regardless of their randomly assigned intervention in this study, had noticed statistically significant changes in their perceptions of stress. The mean difference of scores on the PSS for the two intervention techniques was calculated to be - 2.4 ± 5.0 for breathwork and - 2.5 ± 5.0 for meditation. The GWBS responses and the salivary measurements did not reflect any statistically significant positive changes in the direction of stress reduction. In most cases, there appeared to be an increase in scores and concentrations of the participants. The inference from the statistics analyzed in this study would suggest that practicing these interventions for 30 days only reduced one’s perception and response to stress. The inner well-being and hormonal measurements either stayed the same or increased in some cases, which could be attributed to multiple factors specific to stressors and the nuances of the cortisol-cortisone dynamic in saliva. The data also suggests that breathwork is more efficient in improving perceptions of stress among this population. The positive changes in college students makes a case for integrating these methods as teachings for healthy coping mechanisms of stress in forensic science curricula. Meditation and breathwork have a track record of improving stress levels in most cases. Therefore, future research efforts should look at implementing these interventions in this population for longer intervention periods to assess if their inner well-being and hormonal responses change significantly. Studies should also be performed to understand the enzymatic activity that converts cortisol to cortisone under the variables of stress, breathwork, and meditation
Revealing Insights in Evaluating Tight Carbonate Reservoirs: Significant Discoveries via Statistical Modeling. An In-Depth Analysis Using Integrated Machine Learning Strategies
Get PDFMore than 65% of the world's hydrocarbon reserves are contained within carbonate reservoirs. From a geological perspective, the majority of carbonate reservoirs exhibit tight characteristics, resulting in a similar resistivity response. However, the differentiating factor lies in the presence or absence of primary and secondary porosity. Given their tight nature, these carbonate reservoirs typically exhibit lower porosity compared to conventionally produced carbonate reservoirs. The main goal of this research is to construct a workflow to evaluate Carbonate reservoir potentials, outlining methodologies for identifying facies, reservoir quality, and fractures. The characterization of heterogeneity through borehole image logs is highlighted, providing detailed information on porosity, permeability, and fracture distribution.
The prediction of carbonate reservoir potentiality traditionally relies on conventional petro-physical analysis. Yet, a more sophisticated alternative emerges by leveraging machine-learning models to cluster wells according to their similarities. Then advanced approach facilitates the classification of these clusters into two categories: those that have demonstrated economic oil rates, representing successful outcomes, and those that have exhibited water or mist flow, characterizing unsuccessful cases. Clustering methods, which group elements based on similarities, offer an improved set of tests over time, enhancing the prediction of potentiality. Typically unsupervised, clustering problems lack a target for model training or direct cluster evaluation. Our developed methodology utilizes a decision tree regression for creating clusters. Tree methods effectively divide data into groups, enabling predictions based on these groups. Widely applied in petroleum-related issues, tree-based models include decision trees, assembly-based models like random forest, and gradient boost-based models such as XGBoost, LightGBM, and CatBoost. While assembly and gradient boost methods enhance prediction power.
Despite decision tree methods often exhibiting inferior performance, their advantage lies in the ability to comprehend how the model divides variables and creates cuts. This transparency can offer valuable insights into the actual problem. Utilizing these cuts, we create clusters based on different conventional log features and then classify them depending on the actual results, deviating from traditional unsupervised methods that solely rely on variables. The advantage of the hybrid approach, integrating both supervised and unsupervised methods, in constructing clusters and predicting the potentiality of A5 carbonate formation, lies in the comprehensive utilization of both labeled and unlabeled data. This combined methodology harnesses the benefits of guided learning from labeled examples while also exploring patterns and structures within the data that may not be evident through explicit supervision, thereby enhancing the accuracy and robustness of potentiality predictions.N
ACCOMMODATIONS AND RESOURCES FOR COLLEGE STUDENTS WITH AUTISM SPECTRUM DISORDER
Get PDFThe purpose of this paper was to see how universities are accommodating their student population on campus that are diagnoses with autism spectrum disorder (ASD) through interviews with directors of the university disability resource center (DRC). First, a systematic literature review was conducted with the current literature covering my topic. That literature review was able to provide a fairly comprehensive list of high and low frequency accommodations and some of the described difficulties surrounding college students with autism. These accommodations are implemented in class and housing. I also sought to discover what these participants thought to be some of the more significant barriers and difficulties that college students with ASD navigate on a college campus with the academic and social rigors. Using a qualitative study design, I collected data using 45 minute interviews with participants over an online video conferencing platform (i.e., Zoom) where I had semi-structured questions prepared. With a general qualitative analysis I was able to use the interview transcripts to use deductive and inductive coding to create all codes and identify key themes. Those themes are detailed in the results section of Chapter 4. Through the coding process, implications for the practice of participants were identified, with an emphasis on university guideline requirements, students obtaining a formal ASD diagnosis, public versus private universities, and employment preparedness
A GENERIC FRAMEWORK FOR DELINEATING THE BASIC UNITS OF SOCIAL-ENVIRONMENTAL SYSTEMS: ENSURING USER CONTROL AND REPRODUCIBILITY
Get PDFThis study investigates the dynamic interplay between environmental services (ES) and human systems across multiple spatial scales, examining the supply of ES by natural ecosystems, the impacts of human actions mediated by socio-political institutions, and their effects on environmental and social subsystems. Emphasizing the pivotal role of these interactions within landscape planning, the research highlights the absence of explicit boundary mapping for fundamental Social-Environmental System (SES) units. To address this gap, a unified, structured framework is introduced, integrating Geographic Information Systems (GIS), dimension reduction, and regionalization techniques to effectively delineate and characterize socio-environmental units. This framework uniquely combines raster and vector data across various scales and dimensions, utilizing spatial optimization techniques to control the spatial properties of the resulting SES units. Advanced dimension reduction algorithms are incorporated to accommodate the non-linear characteristics of SES, enhancing the precision of the delineation process.
Utilizing the socio-environmental geodatabase of the Rio Grande/Bravo basin, the research demonstrates the practical application of the framework. This basin, encompassing diverse cultures, ecosystems, and economies, serves as an ideal case study for testing the methodology. The delineation process considers various factors, including administrative boundaries, estimated total quantities, compactness, spatial contiguity, and similarity in socio-environmental characteristics. A key objective is to enhance the accessibility, reproducibility, and scalability of the methodology by employing open-source Python packages. Addressing computational demands, the study employs the Uniform Manifold Approximation and Projection (UMAP) algorithm for dimension reduction, facilitating efficient processing.
This methodological framework advances the understanding of interactions between environmental and socio-economic subsystems, promoting sustainable resource governance. The proposed framework supports sustainable landscape planning and resource management through robust regionalization and interdisciplinary synthesis, making it transferable to other research contexts using diverse data formats and spatial scales
Group Perceptions in America: Demographic and Ideological Divides
Get PDFWe examine Americans' attitudes towards diverse social and political groups using data from the 2023
SPEER Survey. Employing feeling thermometers, we analyze perceptions of left-sympathetic and rightsympathetic
groups across a wide range of demographic, socioeconomic, and ideological factors. Our
findings reveal significant patterns in group attitudes, with political ideology emerging as a consistent
predictor across both categories. Age, education, gender, race/ethnicity, income, rurality, family
structure, and religious beliefs also play varying roles of significance in shaping those perceptions. Leftsympathetic
groups generally received warmer ratings from younger, more educated, and less religious
respondents, while right-sympathetic groups were viewed more favorably by conservative, rural, and
religiously active individuals. These survey results highlight the complex interplay of factors influencing
group perceptions in American society, contributing to our understanding of affective polarization and
social divisions. These insights begin to document the foundation of feelings toward other groups which
has important implications for social cohesion, political behavior, and policy preferences in an
increasingly polarized society.N
They Arrive, They Compete, But What’s Next?: Exploring the Transition Out of Sport Experiences of Former Division I International College Athletes
Get PDFInternational college athletes (ICAs) represent a unique and rapidly growing subpopulation within National Collegiate Athletic Association (NCAA) member institutions, especially at the Division I (DI) level. These athletes bring a diverse range of national, cultural, religious, racial, and ethnic identities to United States (U.S.) higher education institutions (HEIs). Their numbers have risen significantly in recent decades, with over 25,000 ICAs currently enrolled in U.S. HEIs (NCAA, 2023). Despite this growth, research on the experiences of ICAs, particularly their career readiness, and transition out of athletics and into the workforce, remains scarce.This dissertation addresses this critical gap in the existing literature by exploring and investigating the following research questions:1. What are former DI ICAs’ career readiness and job search experiences as they prepare to transition out of sport and enter the workforce?2. What kind of resources and support systems are available to ICAs prior to graduation as they prepare to enter the workforce?3. What roles do stakeholders within athletic departments, U.S. HEIs, and national/federal organizations play in ICA experiences during their career preparation and transition out of sport journey?To address these questions, this qualitative study employed in-depth, semi-structured interviews with 25 former DI ICAs currently employed in the U.S. or another country. The research and analysis were guided by the theoretical framework of sport labor migration.Findings from the study revealed concerning trends in the treatment of ICAs. Most ICAs were exploited for their athletic abilities and left unprepared for successful careers beyond athletics. They were treated inequitably by NCAA member institutions, often viewed primarily as sources of athletic capital, economic gain, and global reputation (Bale, 1991). Many ICAs reported a lack of awareness regarding career preparation strategies within the U.S. context. They received limited to no career readiness support at various structural levels, from the NCAA, conference offices, college campuses, and athletic departments either integrating them into existing programs (which may not fully address their unique needs) or failing to provide any specialized programs at all. Additionally, excessive athletic demands and strict time constraints were identified as significant barriers, limiting ICAs' opportunities to engage in academic and professional development programs and workshops. Social capital, in the form of relationships built with other international students, teammates, and networks established during their time in the U.S., emerged as a crucial source of support for ICAs navigating career transitions and workforce entry.The lack of career readiness support translated into significant challenges during the job search process. Findings revealed that ICAs often faced personal and financial difficulties while navigating outdated and discriminatory visa laws and immigration policies impacting employment opportunities in the U.S. Exclusionary employer practices and anti-immigrant sentiment within U.S. based organizations further complicated their job search experiences. Additionally, ICAs reported challenges with degree applicability in the U.S. based on their nationality and choice of major, and difficulties with degree transferability upon returning to their home countries. For ICAs who remained in the U.S. and pursued graduate degrees, particularly in STEM fields, a supportive social and professional network proved beneficial in securing employment upon transitioning out of athletics.Based on these findings, I offer recommendations and suggestions for various stakeholders. These include the NCAA, its member institutions, conference offices, organizations across the U.S., the U.S. federal government as well as ICAs themselves. Overall, the study’s aim remains to raise awareness and demand for a more holistic approach that propels ICA career readiness and professional development based on their individual identities and needs, ensuring they are well-equipped for successful careers beyond athletics and empowered to take charge of their own transition out of sport into the workforce journeys. This shift is crucial to move away from a sport and education system that often views and treats ICAs primarily as sport labor migrants, and towards one that provides impactful, useful, integrative, and individualized career readiness and job search support and prepare to ICAs
Aniyvwiya Anisgaya Dinedeyohvsgi Dikanohedi Getsilvquodi Honoring Indigenous Male Professors' Stories: Looking Into Their Journeys Within Higher Education
Get PDFThe purpose of this study is to highlight the stories of Indigenous male professors in higher education institutions, focusing on what those stories could unveil, how they perceived and defined success, and what model could be created from the stories they shared. This qualitative study employs an Indigenous methodological approach to better understand their journeys as faculty members in U.S. higher education institutions. Utilizing Sharing Circles and individual interviews to collect stories, Kovach’s thematic analysis was used to analyze themes, while Tribal Critical Race Theory provided the lens for this study. Further, Tso-i Anadalv, or The Three Sisters, provided a metaphorical emphasis and guided each chapter as a metaphor throughout (e.g., Selu or corn is equated to the literature review, Tuya or beans is the methodology, and Squashi or squash is a part of the stories unfolding).
Fifteen Native men Storytellers participated in this study, with their ranks ranging from assistant professor to full professor and with diverse expertise in fields such as environmental justice, pharmacy, higher education, and educational leadership. The findings reveal five main themes – or lessons – in this study: Stories from their Journey, which explores the support they received throughout their higher education journey while attuning to the various paths taken; the Challenges Endured, which examines the obstacles of racism, tokenism, microaggressions, and more; Defining Success, which discusses how these Native male professors defined success through community impact, establishing presence, and visioning for the future; Conversations About Masculinity, which delves into their perceptions of masculinity, the influence of colonialism, and their efforts to redefine what it means to be a Native man. Finally, the fifth lesson shares what has sustained them, culminating in the Balancing Through the Seasons: Sustaining Indigenous Faculty Model. The study suggests the necessity to expand Indigenous perspectives of success to challenge westernized notions of success, enhance support systems for Native male faculty and future Native male faculty, and for higher education institutions to better implement cultural competence to support Indigenous presence on campus. Overall, this study contributes to the understanding of Indigenous male faculty, honoring their experiences and stories.
Keywords: Indigenous men, Native men, Indigenous male faculty, Indigenous masculinity, support systems, Native facult
Inferential Capabilities Of Multilevel Weibull Regression For The Analysis Of Discrete-State Continuous-Time Behavioral Data
Get PDFThe analysis of discrete states in the psychological sciences are commonplace. One of the most powerful techniques used to analyze transition between states is the Markov model. The Markov model is composed of states and transitions, the transitions measure the probability from moving from one state into another at any point in time. Alternatives to the Markov model include the semi-Markov model, which relaxes some of the assumptions made in the Markov model, and may make it more appropriate for the analysis of behavioral data. As the acquisition of these types of data are now easier given recent technological developments, such as the ubiquity of smartphones, streams of states can now easily be acquired from multiple individuals. Multilevel modeling is capable of pooling across individual's with heterogeneous characteristics to make inferences that are true across the population. The goal of this dissertation is to synthesize three perpetrate streams of modeling together to propose an alternative methodological framework for the analysis of intensive longitudinal data composed of discrete states. The three methodological streams include multilevel modeling, survival analysis, and Markov models. Multilevel modeling provides a framework to make inferences about a population when data are composed of clusters. Survival analysis describes a framework which can be used to estimate when an event is most likely to occur, and incorporates an inferential framework to identify variables which may increase or decrease the likelihood of these events across time. Finally, the Markov model describes a time series analytic framework which is used to identify the probability of a state transition to occur at a specific point in time. By synthesizing these three streams, a multilevel Markov, or semi-Markov model can be estimated in an efficient fashion and can identify predictor variables which influence transition probabilities, and the timing of these probabilities.
In order to showcase the utility of these methods, both a simulation study, and an empirical study are examined. The simulation study is used to examine the resilience of time-to-event models estimated under various simulation factors, and to compare the performance of Markov, semi-Markov, and their multilevel counter parts to estimate the true parameters. The empirical study examines the pre- and post-treatment effects when comparing case versus intervention cohorts and their verbal dynamics during a structured parent-child interaction task. The goal is to examine difference is positive and negative behaviors after the administration of a structured parent child interaction therapy