ScholarWorks@UMassAmherst
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Recent Submissions
Publication Engineering Solutions for Public Health: A Multi-Disease Modeling Approach with Social Determinants(2024-09)This dissertation employs mathematical modeling to enhance public health policy, with a particular focus on behavioral and structural interventions for infectious disease control. Initially, a deterministic compartment model is developed for coronavirus disease 2019 (COVID-19) within a university setting, progressing beyond the effective reproductive number (R_0) to independently analyze transmission and contact rates. Although this model does not explicitly incorporate social conditions, it provides a foundation for evaluating nonpharmaceutical interventions (NPIs) and determining vaccination thresholds. The research then expands to integrate modeling of human immunodeficiency virus (HIV) and human papillomavirus (HPV), acknowledging their biological connections and shared social risk factors. By applying a recently developed mixed compartment and agent-based model, the study underscores the significance of behavioral and structural interventions in disease mitigation. Building upon the integrated HIV and HPV model, the study further incorporates social conditions to explore the impact of addressing the social needs of disadvantaged populations. This exploration examines hypothetical scenarios to assess how structural and behavioral interventions can influence both diseases via improvements in HIV care behavior and sexual behavior. Key findings indicate that interventions targeting social conditions can significantly reduce disease prevalence and incidence, particularly among high-risk groups. The study provides a comprehensive framework for policymakers to simulate and evaluate various intervention strategies, highlighting the necessity of integrating behavioral, structural, and pharmaceutical approaches for effective public health outcomes. Overall, this dissertation contributes to the field by developing and refining simulation models that offer practical tools for addressing complex health challenges, ultimately aiming to improve health outcomes and equity on a broader scale."Publication Inclusive Education of Students with Autism Spectrum Disorders in China: Parents' Attitude and Stress(2024-09)This dissertation explores the attitudes of Chinese parents of children with Autism Spectrum Disorders (ASD) or related concerns towards the inclusive education of children with ASD in China. The study employed an online survey design, gathering data from 295 participants, of whom 223 met the inclusion criteria of being parents to children diagnosed with or undergoing assessment for ASD. The instruments used included the Chinese versions of the Attitude Survey Inclusive Education-Parents (ASIE-P) and the Autism Parenting Stress Inventory (C-APSI). The findings indicate that parents generally hold positive attitudes toward inclusive education of children with ASD. Importantly, no direct linear relationship was found between parenting stress levels and attitudes towards inclusive education. The study further assessed which demographic variables significantly affected attitude scores and performed moderating analyses to explore how parenting stress might moderate the relationship between these demographic variables and attitudes towards inclusive education. Overall, this study highlights that although stress doesn't directly change parents' attitudes towards inclusive education for children with ASD, it significantly moderates the relationship between these attitudes and various demographic factors.Publication Graphene-Enabled High-Performance Bioelectronics(2024-09)High-performance biological sensing and modulation are essential for uncovering fundamental biological processes and enabling a range of downstream biomedical applications. Miniaturized electronics enabled by nanomaterials, which offer advanced stability, resolution, and spatiotemporal specificity, have emerged as promising tools to achieve these goals. However, the complexity of biological systems, with their intricate and multi-scale interactions with nanomaterials, poses significant challenges for nanoelectronics in delivering biologically significant performance and functionality to meet diverse needs. Building on recent progress in nanoscience and bioelectronics, my PhD work has focused on understanding electrical transduction properties at nano-bio interfaces and applying this knowledge to develop graphene-enabled, high-performance bioelectronics to address these challenges across various biological systems, including micro-biofluids, biomolecules, and cells. For micro-biofluids, I will show that graphene single microelectrodes, which harvest charge from continuous aqueous flow, provide an effective biofluid flow sensing strategy. In particular, over six-months stability and sub-micrometer/second resolution in real-time quantification of whole-blood flows with multiscale amplitude-temporal characteristics are obtained in a graphene microfluidic chip. For biomolecules, I will demonstrate that oscillational DNA strands tethered to a graphene transistor, driven by an alternating electric field, induce transistor-current spectral characteristics that resist interference interactions. These spectral characteristics enable DNA sensing with ultrahigh specificity and a detection limit improvement of two orders of magnitude compared to typical methods. Besides, I will discuss a model suggesting that the high specificity and sensitivity of our approach are due to the inherent difference in pliability between unpaired and paired DNA strands. At the cellular scale, I will present a microdevice that integrates microelectrolytic pH modulation with graphene-nanoelectronic pH sensing functions, enabling real-time regulation of cell-microenvironmental pH with high spatial specificity and pH precision. In addition, I will show real-time pH-based control of bacteria motility and cardiomyocytic calcium signaling, providing insights into their dynamic responses to time-variable extracellular-pH modulations. Together, the unique capabilities of our graphene-enabled electronics open up new opportunities for high-performance sensing and modulation of complex biological systems across diverse spatiotemporal scales for both fundamental research and translational applications.Publication Trendyol Influencers: Gender, Precarious Work, and Platform Labor at the Intersection of E-Commerce and Influencer Industries in Turkey(2024-09)This dissertation investigates the integration between e-commerce and influencer industries in Turkey, and how this integration shapes content creation, digital labor, and platform work. I use digital observations and interviews to examine the Turkish e-commerce platform Trendyol’s (owned by Alibaba) impact on the emergence of new forms of platformized cultural production, digital labor, and labor organizing. By doing so, I raise critical questions about feminization of work in platformized cultural production, platform contingency, and precarity experienced by content creators. Trendyol invested in influencer marketing from its early days to leverage social media entertainment and shoppability to increase platform selling. The large influencer network built by the platform was essential to gain the trust of a consumer base that largely contained women. Even if the platform’s influencer program first appealed to creators due to its flexibility, premise of profitability, and perceived autonomy, Trendyol has the platform power to govern the labor of its creators through the large influencer and sales data it owns. Content creators who helped building a feminine shopping community through different promotional forms, such as promotional live streams, are often perceived as having financial security and living glamorous lives by the audiences. However, Trendyol turned influencing into a gig type of work that is highly platform contingent and precarious, particularly due to the flexible work arrangement and sudden changes in the monetization system. Creators who take part in the Trendyol influencer program experience precarity at multiple levels, including the monetization system, dependence on predatory influencer agencies, algorithms, and the local context. To navigate this precariousness, creators adopt various forms of individual and collective tactics of resistance. The rich case demonstrated by the Trendyol influencers expands on the previous scholarship on creator and platform studies and emphasizes the importance of adopting a simultaneously global and local approach to study the impact of platformization on cultural production and labor relations that arise out of it.Publication From LoRa Sensing to Coexistence of LoRa Sensing and Communication(2024-09)Wireless sensing is an exciting new research area which can benefit a large spectrum of disciplines including elderly care, HCI, environment monitoring, and disaster response. The key difference between wireless sensing and traditional sensor-based sensing is that the target does not need to be equipped with any sensors and the wireless signal itself is utilized to sense the context information of humans. The rationale behind wireless sensing is that wireless signals vary with human movement. For instance, when a person moves in a room covered by WiFi, the WiFi signal reflected from this person varies with his/her movement. By analyzing the signal variation, the motion information such as target moving speed and respiration rate can be obtained. The contact-free and sensor-free nature of wireless sensing makes it particularly appealing in challenging scenarios such as pandemic and disaster survivor detection. During the COVID-19 pandemic, it is preferred that the patients' respiration rates can be monitored in a contact-free manner through walls. In disasters such as building collapse where the survivors do not have any sensors with them, wireless sensing can be crucial in detecting their presence and saving lives. % While promising in many aspects, there are several critical issues that hinder wireless sensing from being widely deployed in real-life scenarios. % critical issues still exist. These issues include (1) very limited sensing range due to the intrinsic nature of employing weak reflection signals for sensing; (2) strong interference from other objects in the environment; and (3) severe degradation of sensing performance in the presence of ongoing communication function of wireless technologies. This thesis explores the exciting opportunity of employing LoRa~--~the emerging wireless protocol designed for IoT device connections~--~to realize long-range wide-area wireless sensing. This thesis addresses these fundamental issues by making the following contributions. First, we adopt a chirp concentration scheme which fully exploits the property of LoRa chirp to improve the signal power and accordingly boost the sensing range. Second, to mitigate the impact of interference, we propose the concept of ``virtual fence'' to constrain sensing only within the area of interest. The location and size of virtual fence can be flexibly controlled in software to meet the requirements of different applications. Finally, to make LoRa-based wireless sensing work in the presence of ongoing communication, we propose to employ the reversed chirp, i.e., downchirp, for sensing and keep the original upchirp for communication. This design smartly leverages the orthogonality between downchirp and upchirp to address the issue of communication interference on sensing. While the upchirp-downchirp design can remove most of the interference, we further adopt a novel chirp rotation method to deal with the remaining power leakage interference from upchirp to downchip, enhancing the sensing performance.
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