Matching Items (12,990)
Filtering by
- Creators: Arizona State University
Description
Depression and anxiety are among the most prevalent psychiatric disorders for adults and adolescents and can be intergenerationally transmitted from parents to their children. Moreover, depressive and anxiety disorders often develop during adolescence. Additionally, family environment and the parent-child relationship are significant predictors of mental health among adolescents. Yet, few studies have considered how adolescent depression and anxiety problems may influence the family environment and mental health of parents. Moreover, even fewer studies have examined how depressive and anxious intergenerational pathways may vary by racial/ethnic status. As such, bidirectional effects of parent and adolescent depressive and anxiety problems were investigated using data from the Adolescent Brain and Cognitive Development (ABCD) study at Time 1 (T1)(Mage = 9.92, n=11,861), Time 2 (T2), and Time 3 (T3). Each follow-up was approximately one-year apart. Multiple path analysis models were used to examined bidirectional associations between parent and adolescent A) depressive problems B) anxiety problems and C) depressive and anxiety problems from T1 to T3 and how family conflict and adolescent-reported parental acceptance at T2 mediated these associations. Measurement invariance testing and multigroup analyses were conducted across non-Hispanic White, Hispanic, and non-Hispanic Black participants to examine if depressive and anxious pathways or measurement differed by racial-ethnic status. Findings revealed that both adolescent and parent depression problems at T1 predicted increases in depression at T3. Greater adolescent or parent anxiety problems at T1 predicted increases in adolescent and parent anxiety problems at T3. Greater family conflict and lower perceived parental acceptance at T2 predicted increases in adolescent depressive problems but did not predict adolescent anxiety problems over time. Parental depressive and anxiety problems at T1 did not predict adolescent-reported parental acceptance at T2 but did predict greater family conflict. Measurement noninvariance was found for family conflict and adolescent depressive problems. Multigroup analyses revealed that the association between both depressive and anxiety problems from T1 to T3 was weaker among Black adolescents compared to White and Hispanic adolescents. In summary, this research contributes valuable insights into the measurement of and relationship between parent and adolescent mental health, family dynamics, and adolescent perceived parental acceptance.
ContributorsJamil, Belal (Author) / Su, Jinni (Thesis advisor) / Doane, Leah (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2024
Description
In an attempt to summarize two years worth of work in one hundred and fiftywords... This reflection oriented document categorizes my project, “category FIVE”, into chapters of development and actualization. Accounting for the collaborative nature of the project, I advise that this specific document is only half of what the entire work saw through the eyes of Isabella Lepp. Beginning with background information, moving into making the work, and ending with production and reflection of the work, this document follows a mostly chronological timeline in telling the process of making, “category FIVE”, an immersive dance experience. Enjoy.
ContributorsLepp, Isabella Victoria (Author) / Jackson, Naomi (Thesis advisor) / Lerman, Liz (Committee member) / Ortel, Sven (Committee member) / Arizona State University (Publisher)
Created2024
Description
As screen time (ST) constitutes an integral part of the daily lives of young children today, parents, educators, and researchers have started to explore the associations of ST with children’s cognitive, behavioral, and social outcomes. The majority of existing studies have primarily focused on the duration of ST in relation to these outcomes despite the importance of other aspects such as content and type of device in the context of an evolving digital landscape marked by high mobility, ubiquity, and diversity. Addressing this gap, the current study aimed to explore the intricate relations between multiple aspects of ST (i.e., duration and content), executive function (EF) difficulties, and school adjustment in school-aged children, with a particular focus on the mediating role of EF difficulties linking the relations between ST and school adjustment. The current study employed data from the Panel Study on Korean Children, tracking 1,484 South Korean children from third to fourth grade. The duration of ST was measured by the average daily hours spent on smart devices and computers. Parent reports of the levels of engagement in recreational and educational ST and EF difficulties were assessed on Likert scales. School adjustment was reported on by teachers. The results from a half-longitudinal mediation model demonstrated that more frequent engagement in educational ST was related to fewer EF difficulties, which was in turn associated with better school adjustment. The current findings suggest that multiple approaches are needed to effectively guide children’s ST use in their everyday lives and interventions that target EF might be an effective way to promote children's behavioral and social adjustment in school settings.
ContributorsKim, Juyoung (Author) / Tsethlikai, Monica (Thesis advisor) / Buman, Matthew (Committee member) / Eggum, Natalie (Committee member) / Valiente, Carlos (Committee member) / Arizona State University (Publisher)
Created2024
Description
Vector control plays an important role in the prevention and control of mosquito-borne diseases (MBDs). As there are no (prophylactic) drugs and/or vaccines available for many arboviral diseases (such as zika, chikungunya, Saint Louis encephalitis, Ross River virus), the frontline approach to prevent or reduce disease morbidity and mortality is through the reduction of the mosquito vector population size and/or reducing vector-human contact using insecticides. Frontline tools in malaria (an MBD caused by a parasite) control and elimination have been drugs (targeting the malaria parasite) and insecticides (targeting the vectors) through indoor residual spraying (IRS) (spraying the internal walls and sometimes the roofs of dwellings with residual insecticides to kill adult mosquito vectors), and long-lasting insecticidal nets (LLINs), while arboviral vectors are frequently targeted using outdoor fogging and space spraying (indoor or outdoor spraying of insecticides to kill adult mosquito vectors). Integrative and novel vector control efforts are urgently needed since the aforementioned tools may not be as effective against those mosquito species that are resistant to insecticides and/or have a different (or changed) behavior allowing them to avoid existing tools. In Chapters 2 and 3, I investigate mosquito vector surveillance in Arizona by (i) discussing the species composition and public health implications of the State’s mosquito fauna, and (ii) comparing the effectiveness of 4 different carbon dioxide (CO2) sources in attracting different mosquito species on the Arizona State University Tempe Campus. In Chapters 4 and 5, I investigate a novel vector control tool by (i) completing a literature review on using electric fields (EFs) to control insects, and (ii) presenting novel data on using Insulated Conductor Wires (ICWs) to generate EFs that prevent host-seeking female Aedes aegypti from entering spaces. In Chapter 6, I discuss the non-target effects of chemical malaria control on other arthropods, including other biological and mechanical infectious disease vectors. Overall, this dissertation highlights the important role that the development of novel surveillance and vector control tools could play in improved mosquito control, which ultimately will reduce disease morbidity and mortality.
ContributorsJobe, Ndey Bassin (Author) / Paaijmans, Krijn (Thesis advisor) / Cease, Arianne (Committee member) / Hall, Sharon (Committee member) / Huijben, Silvie (Committee member) / Arizona State University (Publisher)
Created2024
Description
This study examined bite force generation in American monkfish (Lophius americanus) and how it scaled with size, focusing in particular on the roles of the quadratomandibularis (QM) muscle and mechanical advantage in jaw closure in this species. Considering the feeding strategy of other anglerfishes, it was hypothesized that monkfish would trend towards force optimization rather than speed optimization in terms of the jaw closing system. The data revealed that bite force has a slightly positive allometric scaling relationship with size, while mechanical advantage was constant throughout growth. Maximum theoretical bite force ranged from 8 N to 87 N, with total lengths ranging from 17 cm to 51 cm. When comparing the bite force of the American monkfish to that of 10 other fish species, small monkfish exhibit a bite comparable to similarly sized species. However, larger monkfish were estimated to have a stronger bite than organisms of similar size.
ContributorsSawant, Sarika (Author) / Ferry, Lara (Thesis advisor) / Barley, Anthony (Committee member) / Shiffman, David (Committee member) / Arizona State University (Publisher)
Created2024
Description
Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders
include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease,
and multiple sclerosis. With the aging population, an increase in the prevalence of
neurodegenerative disorders is expected. Electrophysiological monitoring of neural
signals has been the gold standard for clinicians in diagnosing and treating neurological
disorders. However, advances in detection and stimulation techniques have paved the
way for relevant information not seen by standard procedures to be captured and
used in patient treatment. Amongst these advances have been improved analysis of
higher frequency activity and the increased concentration of alternative biomarkers,
specifically pH change, during states of increased neural activity. The design and
fabrication of devices with the ability to reliably interface with the brain on multiple
scales and modalities has been a significant challenge.
This dissertation introduces a novel, concentric, multi-scale micro-ECoG array
for neural applications specifically designed for seizure detection in epileptic patients.
This work investigates simultaneous detection and recording of adjacent neural tissue
using electrodes of different sizes during neural events. Signal fidelity from electrodes
of different sizes during in vivo experimentation are explored and analyzed to highlight
the advantages and disadvantages of using varying electrode sizes. Furthermore, the
novel multi-scale array was modified to perform multi-analyte detection experiments
of pH change and electrophysiological activity on the cortical surface during epileptic
events. This device highlights the ability to accurately monitor relevant information
from multiple electrode sizes and concurrently monitor multiple biomarkers during
clinical periods in one procedure that typically requires multiple surgeries.
ContributorsAkamine, Ian (Author) / Blain Christen, Jennifer (Thesis advisor) / Abbas, Jimmy (Committee member) / Muthuswamy, Jitendran (Committee member) / Goryll, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2024
Description
This article uses the S&P 500 index as an example to analyze the impact of macroeconomic factors on stock returns. By using the S&P 500 index data from 1968 to 2020 as the dependent variable, and the monthly data of 221 macroeconomic variables such as the consumer price index and the US mid-term election as the independent variable, this paper finds that: (1) a wavelet denoising method helps to capture the low-frequency and long-term fluctuations in monthly returns of the index, which can effectively remove the short-term fluctuations in returns, better reflect the macroeconomic trend, and improve the power of out-of-sample forecasting. (2) the Granger causality test may be used to pick the top 30 most significant variables, which can be incorporated into several prediction models. Among all the prediction models, the combined prediction algorithm has the best out-of-sample prediction effect. (3) investors need to consider investment practices under timing strategies. Elastic network, scaling principal component analysis, combination prediction, and other algorithms are used to select the time, and the best results are obtained based on the scaling principal component analysis algorithm and the combination prediction algorithm when the transaction fee is set to 5‰. The returns based on these two algorithms have reached 14.00% and 12.59%, their Sharpe ratios are the highest among all algorithms, reaching 0.69 and 0.62, respectively, and this result is significantly better than the historical mean model used as a measurement benchmark (with the average return of 8.14%, and aii
Sharpe ratio of 0.34). (4) explore investment practice under a stock-picking strategy. We use methods such as sector rotation strategy and mean-variance of sectors for stock selection, and find that the strategy returns achieved by investing in stocks using the sector rotation strategy are the best, reaching 14.30%, and the Sharpe ratio is the highest at 0.79, significantly better than the benchmark S&P 500 index (with the average return of 8.8% and a Sharpe ratio of 0.57).
ContributorsGuo, Yangui (Author) / Wu, Xu (Thesis advisor) / Yan, Hong (Thesis advisor) / Zhang, Huibing (Committee member) / Arizona State University (Publisher)
Created2024
Description
Background: Despite research aimed at understanding the mechanisms of metabolic syndrome (MetS), this prevalence continues to rise. Recent literature indicates that dietary fiber may offer prevention and management of MetS in various studies involving human and animal subjects. Objective: This six-week study aimed to test the efficacy of a novel fiber-rich complex in young male Sprague-Dawley rats by examining the effects on high-fat diet-induced weight gain, adiposity, high blood sugar, lipid imbalance, and oxidative stress.
Methods: 24 six-week-old male Sprague Dawley rats were randomly assigned into three diet groups (regular chow, high-fat, or high-fat + fiber) and fed for six weeks. Blood from the animals was collected at weeks 0, 3, and 6 for fasting blood glucose (FBG) analysis and at weeks 0 and 6 for lipid profile assessment. Body mass was weighed weekly. Organ mass, nasoanal, and tail length were measured at week 6. Findings were considered significant at p-value < 0.05. Data collected at week 6 were analyzed by one-way ANOVA, whereas data collected at multiple time points were analyzed by two-way ANOVA with diet and time as factors. Student-Newman-Keuls posthoc analyses were used to compare differences between and within groups.
Results: No significant differences were found in the size of rats fed each diet as measured by tail length (p = 0.599) or nasoanal length (p = 0.875). Abdominal circumference was not significantly different (p = 0.477). There were no significant differences between groups in fasting whole blood HDL cholesterol (p = 0.297), fasting whole blood HDL triglycerides (p = 0.624), plasma total triglycerides (p = 0.137), or beta-hydroxybutyrate (p=0.185) after six weeks of each dietary treatment. Similarly, plasma true triglycerides and free glycerol were not significantly different between groups (p = 0.148 and 0.529, respectively). Thiobarbituric acid reactive substances (TBARS) were also not significantly different between groups (p = 0.412).
Conclusion: The addition of the novel fiber-rich complex did not significantly affect high-fat diet-induced weight gain, adiposity, high blood sugar, lipid imbalance, or oxidative stress in this experimental design.
ContributorsLing, Jingyu (Author) / Sweazea, Karen (Thesis advisor) / Sears, Dorothy (Committee member) / Kim, Min-Hyun (Committee member) / Arizona State University (Publisher)
Created2024
Description
Image denoising, a fundamental task in computer vision, poses significant challenges due to its inherently inverse and ill-posed nature. Despite advancements in traditional methods and supervised learning approaches, particularly in medical imaging such as Medical Resonance Imaging (MRI) scans, the reliance on paired datasets and known noise distributions remains a practical hurdle. Recent progress in noise statistical independence theory and diffusion models has revitalized research interest, offering promising avenues for unsupervised denoising. However, existing methods often yield overly smoothed results or introduce hallucinated structures, limiting their clinical applicability. This thesis tackles the core challenge of progressing towards unsupervised denoising of MRI scans. It aims to retain intricate details without smoothing or introducing artificial structures, thus ensuring the production of high-quality MRI images. The thesis makes a three-fold contribution: Firstly, it presents a detailed analysis of traditional techniques, early machine learning algorithms for denoising, and new statistical-based models, with an extensive evaluation study on self-supervised denoising methods highlighting their limitations. Secondly, it conducts an evaluation study on an emerging class of diffusion-based denoising methods, accompanied by additional empirical findings and discussions on their effectiveness and limitations, proposing solutions to enhance their utility. Lastly, it introduces a novel approach, Unsupervised Multi-stage Ensemble Deep Learning with diffusion models for denoising MRI scans (MEDL). Leveraging diffusion models, this approach operates independently of signal or noise priors and incorporates weighted rescaling of multi-stage reconstructions to balance over-smoothing and hallucination tendencies. Evaluation using benchmark datasets demonstrates an average gain of 1dB and 2% in PSNR and SSIM metrics, respectively, over existing approaches.
ContributorsVora, Sahil (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Zhou, Yuxiang (Committee member) / Arizona State University (Publisher)
Created2024
Description
This thesis focuses on large-scale direct simple shear (LDSS) testing to analyze the behavior of coarse mine tailings subject to cyclic loading. The motivation behind this research stems from recent failures of tailings dams, prompting mine owners globally to reassess the safety of their tailing’s impoundments. Testing was carried out at the Arizona State University (ASU) Enamul and Mahmuda Hoque geotechnical laboratory using a unique LDSS device. Cyclic shearing, at different levels of strains, under constant normal stress test was carried out to investigate the modulus reduction and damping behavior of the tailings. Constant volume tests were conducted to simulate the undrained behavior of the tailings and provide insight to the tailings’ liquefaction potential. In both the constant normal stress and constant volume tests the tailings were sheared to the strain limit of the device to assess the post-cyclic shear behavior of the tailings. Testing was also conducted on tailings from the same parent material after screening the larger particle to evaluate the effect of the particle size. The thesis also includes recommendations for improving future test results. This thesis provides valuable insights on the behavior of coarse mine tailings which ultimately contributes to enhancing safety and environmental sustainability in the mining industry.
ContributorsDangi, Rajesh (Author) / Kavazanjian, Edward (Thesis advisor) / Zapata, Claudia (Committee member) / Tirkolaei, Hamed Khodadadi (Committee member) / Arizona State University (Publisher)
Created2024