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In this research, I surveyed existing methods of characterizing Epilepsy from Electroencephalogram (EEG) data, including the Random Forest algorithm, which was claimed by many researchers to be the most effective at detecting epileptic seizures [7]. I observed that although many papers claimed a detection of >99% using Random Forest, it was not specified “when” the detection was declared within the 23.6 second interval of the seizure event. In this research, I created a time-series procedure to detect the seizure as early as possible within the 23.6 second epileptic seizure window and found that the detection is effective (> 92%) as early as the first few seconds of the epileptic episode. I intend to use this research as a stepping stone towards my upcoming Masters thesis research where I plan to expand the time-series detection mechanism to the pre-ictal stage, which will require a different dataset.
ContributorsBou-Ghazale, Carine (Author) / Lai, Ying-Cheng (Thesis director) / Berisha, Visar (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2022-05
Description
HIV/AIDS remains a pressing global health challenge, not only because of its medical complexities but also due to associated stigma and the lack of knowledge of the illness in communities around the world. This thesis analyzed cross-cultural differences and long-term changes in women’s knowledge and stigma around HIV/AIDS in low- and middle-income countries. Using Demographic and Health Survey (DHS) data from 24 countries for knowledge and stigma from 2000-2018, we examined changes in HIV/AIDS knowledge score and stigma score. The findings shed light on the perception of HIV/AIDS knowledge improving while stigma persisted indicative of remaining concerns about the illness amongst women.
ContributorsMurala, Divya Sruthi (Author) / Hruschka, Daniel (Thesis director) / Loebenberg, Abby (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Department of Information Systems (Contributor)
Created2023-12
Description
Predicting nonlinear dynamical systems has been a long-standing challenge in science. This field is currently witnessing a revolution with the advent of machine learning methods. Concurrently, the analysis of dynamics in various nonlinear complex systems continues to be crucial. Guided by these directions, I conduct the following studies. Predicting critical transitions and transient states in nonlinear dynamics is a complex problem. I developed a solution called parameter-aware reservoir computing, which uses machine learning to track how system dynamics change with a driving parameter. I show that the transition point can be accurately predicted while trained in a sustained functioning regime before the transition. Notably, it can also predict if the system will enter a transient state, the distribution of transient lifetimes, and their average before a final collapse, which are crucial for management. I introduce a machine-learning-based digital twin for monitoring and predicting the evolution of externally driven nonlinear dynamical systems, where reservoir computing is exploited. Extensive tests on various models, encompassing optics, ecology, and climate, verify the approach’s effectiveness. The digital twins can extrapolate unknown system dynamics, continually forecast and monitor under non-stationary external driving, infer hidden variables, adapt to different driving waveforms, and extrapolate bifurcation behaviors across varying system sizes. Integrating engineered gene circuits into host cells poses a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback. I conducted systematic studies on hundreds of circuit structures exhibiting various functionalities, and identified a comprehensive categorization of growth-induced failures. I discerned three dynamical mechanisms behind these circuit failures. Moreover, my comprehensive computations reveal a scaling law between the circuit robustness and the intensity of growth feedback. A class of circuits with optimal robustness is also identified. Chimera states, a phenomenon of symmetry-breaking in oscillator networks, traditionally have transient lifetimes that grow exponentially with system size. However, my research on high-dimensional oscillators leads to the discovery of ’short-lived’ chimera states. Their lifetime increases logarithmically with system size and decreases logarithmically with random perturbations, indicating a unique fragility. To understand these states, I use a transverse stability analysis supported by simulations.
ContributorsKong, Lingwei (Author) / Lai, Ying-Cheng (Thesis advisor) / Tian, Xiaojun (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2023
Description
Latest estimates show that roughly 188 individuals in the United States die everyday due to an opioid-related overdose. This dissertation explores three avenues for
mitigating opioid use disorder (OUD) and the opioid epidemic in the United States (1.)
How can researchers and public health professionals identify areas most in need of
treatment for OUD in an easy-to-use and publicly accessible interface?; (2.) What do
practitioners see as opportunities for reducing barriers to treatment?; and (3.) Why do
differences in opioid mortality exist between demographic groups? To address question
one, I developed an interactive web-based to assist in identifying those counties with the
greatest unmet need of medically assisted treatment (MAT). To answer question two, I
conducted a study of stakeholders (medical providers, peer support specialists, public
health practitioners, etc.) in four New Mexico counties with high unmet need of MAT. to
identify cultural and structural barriers to MAT provision in underserved areas as well as
opportunities for improving access. To answer the third question. I conducted a
systematic review of peer-reviewed literature and government reports to identify how
previous research accounts for race/ethnic and sex disparities in opioid-related
mortality. While many opioid mortality studies show demographic differences, little is
known about why they exist. According to the findings of this systematic review, research
needs to go beyond identifying demographic differences in opioid-related mortality to
understand the reasons for those differences to reduce these inequities.
ContributorsDrake, Alexandria (Author) / Hruschka, Daniel (Thesis advisor) / Jehn, Megan (Committee member) / Scott, Mary Alice (Committee member) / Arizona State University (Publisher)
Created2023
Description
Previous work suggests that lower-income individuals are more likely to engage in mutual aid as a means to manage risk, giving rise to a psychology that is other-oriented, including an empathetic disposition and a proclivity to help people in need. While no study has directly investigated whether helping in times of need increases dispositional empathic concern over time, this assumption is deep-seated among social psychologists. Employing a two-year longitudinal survey of US adults (N = 915), I show that people who experience more needs report helping others when in need a greater number of times, in turn leading to a small but positive increase in their empathetic disposition. This study also identifies the types of needs that elicit empathic concern (i.e., those that arise from unpredictable sources of risk), and shows why cultivating an empathetic disposition is likely to pay off in the long run: those who provide help are more likely to receive help during future times of need. Moreover, this study identifies the types of targets for whom providing help might cultivate an empathetic disposition: those with whom people are likely to share lower interdependence. While previous theoretical frameworks posit that empathic concern selectively directs investment towards interdependent others, providing help to non-interdependent targets might allow people to build positive interdependence with prospective risk pooling partners. Cultivating an empathetic disposition and building interdependence with prospective risk pooling partners can allow people to manage needs that arise from unpredictable sources of risk.
ContributorsGuevara Beltran, Diego (Author) / Aktipis, Athena (Thesis advisor) / Hruschka, Daniel (Committee member) / Kenrick, Douglas (Committee member) / Shiota, Michelle (Committee member) / Arizona State University (Publisher)
Created2023
Description
Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.
ContributorsClauss, Colleen (Author) / Hruschka, Daniel (Thesis director) / Davis, Mary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / Department of Psychology (Contributor)
Created2022-05
Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise.
Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state
switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
ContributorsGoetz, Hanah Elizabeth (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2022
Description
Breast cancer is one of the leading causes of cancer-related deaths among women in the United States. Uninsured women are less likely to receive breast cancer screenings, more likely to be diagnosed at an advanced stage, and more likely to have poorer outcomes following a breast cancer diagnosis (Abdelsattar et al., 2016; Akinlotan et al., 2021; Ko et al., 2020; & Ntiri et al., 2018). Women in underserved communities often experience socioeconomic barriers which impact obtaining preventative screenings, such as mammograms. Lack of patient navigation, transportation, and financial concerns interfere with obtaining breast cancer screening (Akinlotan et al., 2021 & Miller et al., 2019). Through the intervention of mobile mammography, uninsured women in underserved communities can be reached and access to screening mammograms can be achieved (Stanley et al., 2017 & Vang et al., 2018). Two mobile mammography events were hosted at the project site which provided 35 women with screening mammograms. All scheduled mammogram time slots at the events were filled and completed. Offering mobile mammography to this population has the potential to increase breast cancer surveillance.
ContributorsGlessner-Vallee, Paula (Author) / Santerre, Jennifer (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-26
Description
Introduction: The objective of this study is to emphasize the significance of exclusive breastfeeding (EB) and investigate methods to encourage and sustain it within a hospital environment. Using the self-efficacy theory, the study seeks to improve the current support system for breastfeeding mothers and their families. Methods: The project was approved by the university IRB and facility IRB; guidelines were maintained. The project takes place in a non-profit organization in the southwestern United States. Education was conducted at a required staff meeting for Women and Infant Services (WIS) floor about supporting breastfeeding mothers. A pre- and post-education Breastfeeding Knowledge Scale (BKS) survey was performed, effectiveness was measured using a two-tailed t-test. The reliability of the BKS scale is 0.83 and the validity of the scale is reported to be strong. The hospital measures the EB rates of patients that are greater than 37 weeks gestation without need for neonatal intensive unit care and the mom requests to breastfeed. Results: The goal was 42% rate of EB in the first 48 hours after birth. After education the average rate of EB was 39.6%, lower than the goal but higher than the 33.7% rate before education. A two-tailed paired sample t-test (n=27) was used for BKS and the results were significant based on an alpha value; thus, showing significant knowledge gain. Conclusion: Consistent staff education improves breastfeeding support for moms in the hospital, leading to successful exclusive breastfeeding. This project benefits various settings, such as pediatric, postpartum, labor and delivery, and pediatric offices.
ContributorsHudson, Jennifer (Author) / Esperas, Amanda (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-26
Description
Introduction: Depression screening in the pediatric setting is a crucial part of the adolescent's examination. A standardized screening tool and protocol streamlines the process of assessing adolescents and minimizes the chances of serious mental health disorders going undetected and untreated. Evaluation of current evidence demonstrates the use of a standardized tool improves detection, diagnosis, and management of depression and other mental health illnesses.
Method: The Patient Health Questionnaire—modified for adolescents (PHQ9-A) was administered to all eligible adolescents, ages 12-18, during an annual well visit for a period of 6 weeks. Lewin's Change Theory guided a system change in the electronic health record, and the questionnaire results were documented and provided to the pediatric provider at the time of the appointment. A chart review was conducted to determine whether all eligible patients were administered the questionnaire and if a depression diagnosis or mental health referral had been made.
Results: Out of 76 eligible well visits, 65 (86%) patients completed the PHQ9-A. The average score was 5.29 (SD = 6.49) with a maximum score of 25. Out of those that completed screening, 11 (17%) had a positive PHQ9-A score resulting in 8 referrals to mental health services and 2 mental health diagnoses in the clinic.
ContributorsCoomer, Meagan (Author) / Rauton, Monica (Thesis advisor) / College of Nursing and Health Innovation (Contributor)
Created2023-04-27