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Microfluidic platforms have been exploited extensively as a tool for the separation of particles by electric field manipulation. Microfluidic devices can facilitate the manipulation of particles by dielectrophoresis. Separation of particles by size and type has been demonstrated by insulator-based dielectrophoresis in a microfluidic device. Thus, manipulating particles by size has been widely studied throughout the years. It has been shown that size-heterogeneity in organelles has been linked to multiple diseases from abnormal organelle size. Here, a mixture of two sizes of polystyrene beads (0.28 and 0.87 μm) was separated by a ratchet migration mechanism under a continuous flow (20 nL/min). Furthermore, to achieve high-throughput separation, different ratchet devices were designed to achieve high-volume separation. Recently, enormous efforts have been made to manipulate small size DNA and proteins. Here, a microfluidic device comprising of multiple valves acting as insulating constrictions when a potential is applied is presented. The tunability of the electric field gradient is evaluated by a COMSOL model, indicating that high electric field gradients can be reached by deflecting the valve at a certain distance. Experimentally, the tunability of the dynamic constriction was demonstrated by conducting a pressure study to estimate the gap distance between the valve and the substrate at different applied pressures. Finally, as a proof of principle, 0.87 μm polystyrene beads were manipulated by dielectrophoresis. These microfluidic platforms will aid in the understanding of size-heterogeneity of organelles for biomolecular assessment and achieve separation of nanometer-size DNA and proteins by dielectrophoresis.
ContributorsOrtiz, Ricardo (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2021
Description
Meditation app usage is associated with decreases in stress, anxiety, and depression symptoms. Many meditation app subscribers, however, quickly abandon or reduce their app usage. This dissertation presents three manuscripts which 1) determined the behavioral, demographic, and socioeconomic factors associated with the abandonment of a meditation app, Calm, during the COVID-19 pandemic, 2) determined which participant characteristics predicted meditation app usage in the first eight weeks after subscribing, and 3) determined if changes in stress, anxiety, and depressive symptoms from baseline to Week 8 predicted meditation app usage from Weeks 8-16. In Manuscript 1, a survey was distributed to Calm subscribers in March 2020 that assessed meditation app behavior and meditation habit strength, and demographic information. Cox proportional hazards regression models were estimated to assess time to app abandonment. In Manuscript 2, new Calm subscribers completed a baseline survey on participants’ demographic and baseline mental health information and app usage data were collected over 8 weeks. In Manuscript 3, new Calm subscribers completed a baseline and Week 8 survey on demographic and mental health information. App usage data were collected over 16 weeks. Regression models were used to assess app usage for Manuscripts 2 and 3. Findings from Manuscript 1 suggest meditating after an existing routine decreased risk of app abandonment for pre-pandemic subscribers and for pandemic subscribers. Additionally, meditating “whenever I can” decreased risk of abandonment among pandemic subscribers. No behavioral factors were significant predictors of app abandonment among the long-term subscribers. Findings from Manuscript 2 suggest men had more days of meditation than women. Mental health diagnosis increased average daily meditation minutes. Intrinsic motivation for meditation increased the likelihood of completing any meditation session, more days with meditation sessions, and more average daily meditation minutes. Findings from Manuscript 3 suggest improvements in stress increased average daily meditation minutes. Improvements in depressive symptoms decreased daily meditation minutes. Evidence from this three-manuscript dissertation suggests meditation cue, time of day, motivation, symptom changes, and demographic and socioeconomic variables may be used to predict meditation app usage.
ContributorsSullivan, Mariah (Author) / Stecher, Chad (Thesis advisor) / Huberty, Jennifer (Committee member) / Buman, Matthew (Committee member) / Larkey, Linda (Committee member) / Chung, Yunro (Committee member) / Arizona State University (Publisher)
Created2022
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
In cold chain tracking systems, accuracy and flexibility across different temperatures ranges plays an integral role in monitoring biospecimen integrity. However, while two common cold chain tracking systems are currently available (electronic and physics/chemical), there is not an affordable cold chain tracking mechanism that can be applied to a variety of temperatures while maintaining accuracy for individual vials. Hence, our lab implemented our understanding of biochemical reaction kinetics to develop a new cold chain tracking mechanism using the permanganate/oxalic acid reaction. The permanganate/oxalic acid reaction is characterized by the reduction of permanganate (MnVII) to Mn(II) with Mn(II)-autocatalyzed oxidation of oxalate to CO2, resulting in a pink to colorless visual indicator change when the reaction system is not in the solid state (i.e., frozen or vitrified). Throughout our research, we demonstrate, (i) Improved reaction consistency and accuracy along with extended run times with the implementation of a nitric acid-based labware washing protocol, (ii) Simulated reaction kinetics for the maximum length reaction and 60-minute reaction based on previously developed MATLAB scripts (iii) Experimental reaction kinetics to verify the simulated MATLAB maximum and 60-minute reactions times (iv) Long-term stability of the permanganate/oxalic acid reaction with water or eutectic solutions of sodium perchlorate and magnesium perchlorate at -80°C (v) Reaction kinetics with eutectic solvents, sodium perchlorate and magnesium perchlorate, at 25°C, 4°C, and -8°C (vi) Accelerated reaction kinetics after the addition of varying concentrations of manganese perchlorate (vii) Reaction kinetics of higher concentration reaction systems (5x and 10x; for darker colors), at 25°C (viii) Long-term stability of the 10x higher concentration reaction at -80°C.
ContributorsLjungberg, Emil (Author) / Borges, Chad (Thesis director) / Levitus, Marcia (Committee member) / Williams, Peter (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor)
Created2022-12
Description
Young adult collegiate women, particularly students with adverse childhood experiences (ACEs) and who have experienced intimate partner violence (IPV) victimization, report a myriad of adverse mental health and academic difficulties. Practicing yoga has demonstrated promising findings among adults as a healing modality in the aftermath of interpersonal violence victimization and traumatization. Less known are the associations between collegiate women’s yoga participation and their mental health, body connection, and academic well-being examined through a yoga feminist- trauma conceptual framework. Among young adult collegiate women, this study examined (1) associations amongst socio-demographics, mental health service use, IPV types, and yoga participation (2) the strength and direction of associations on measures of ACEs, mental health, body connection, and academic well-being, (3) whether yoga participation predicted students’ mental health, body connection, and academic well-being after controlling for confounding variables, including ACEs and IPV victimization, and (4) whether socio-demographics, mental health service use, ACEs, and IPV types predicted yoga participation. This study was observational, cross-sectional, and gathered self-report quantitative data. Eligible participants were current collegiate women enrolled at an urban, public university in the southwestern United States who were 18 to 24 years of age. The main sub-sample (n = 93) included students who were ever in an intimate relationship and practiced yoga within the past year. IRB approval was obtained. Findings demonstrated that yoga participation was not a significant predictor of students’ mental health, body connection, or academic well-being. Socio-demographics, mental health service use, ACEs, and IPV did not predict yoga participation. However, women with greater ACEs fared worse on measures of mental health (i.e., depression and post-traumatic stress disorder symptoms), and women with experiences of IPV harassment reported greater post-traumatic stress disorder symptoms. Further, employed women reported fewer depression symptoms and were less likely to experience emotional IPV. Lastly, students with greater body connection (more awareness) fared better academically. This research supports prior literature on the adverse mental health outcomes among young adult collegiate women with histories of interpersonal violence. Further examination is warranted into employment and body connection, particularly related to yoga, as protective factors of students' health, safety, and academic well-being.
ContributorsKappas Mazzio, Andrea Alexa (Author) / Messing, Jill T (Thesis advisor) / Mendoza, Natasha (Committee member) / Huberty, Jennifer (Committee member) / Arizona State University (Publisher)
Created2022
Description
Plasma and serum are the most commonly used liquid biospecimens in biomarker research. These samples may be subjected to several pre-analytical variables (PAVs) during collection, processing and storage. Exposure to thawed conditions (temperatures above -30 °C) is a PAV that is hard to control, and track and could provide misleading information, that fail to accurately reveal the in vivo biological reality, when unaccounted for. Hence, assays that can empirically check the integrity of plasma and serum samples are crucial. As a solution to this issue, an assay titled ΔS-Cys-Albumin was developed and validated. The reference range of ΔS-Cys-Albumin in cardio vascular patients was determined and the change in ΔS-Cys-Albumin values in different samples over time course incubations at room temperature, 4 °C and -20 °C were evaluated. In blind challenges, this assay proved to be successful in identifying improperly stored samples individually and as groups. Then, the correlation between the instability of several clinically important proteins in plasma from healthy and cancer patients at room temperature, 4 °C and -20 °C was assessed. Results showed a linear inverse relationship between the percentage of proteins destabilized and ΔS-Cys-Albumin regardless of the specific time or temperature of exposure, proving ΔS-Cys-Albumin as an effective surrogate marker to track the stability of clinically relevant analytes in plasma. The stability of oxidized LDL in serum at different temperatures was assessed in serum samples and it stayed stable at all temperatures evaluated. The ΔS-Cys-Albumin requires the use of an LC-ESI-MS instrument which limits its availability to most clinical research laboratories. To overcome this hurdle, an absorbance-based assay that can be measured using a plate reader was developed as an alternative to the ΔS-Cys-Albumin assay. Assay development and analytical validation procedures are reported herein. After that, the range of absorbance in plasma and serum from control and cancer patients were determined and the change in absorbance over a time course incubation at room temperature, 4 °C and -20 °C was assessed. The results showed that the absorbance assay would act as a good alternative to the ΔS-Cys-Albumin assay.
ContributorsJehanathan, Nilojan (Author) / Borges, Chad (Thesis advisor) / Guo, Jia (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2022
Description
This work presents a thorough analysis of reconstruction of global wave fields (governed by the inhomogeneous wave equation and the Maxwell vector wave equation) from sensor time series data of the wave field. Three major problems are considered. First, an analysis of circumstances under which wave fields can be fully reconstructed from a network of fixed-location sensors is presented. It is proven that, in many cases, wave fields can be fully reconstructed from a single sensor, but that such reconstructions can be sensitive to small perturbations in sensor placement. Generally, multiple sensors are necessary. The next problem considered is how to obtain a global approximation of an electromagnetic wave field in the presence of an amplifying noisy current density from sensor time series data. This type of noise, described in terms of a cylindrical Wiener process, creates a nonequilibrium system, derived from Maxwell’s equations, where variance increases with time. In this noisy system, longer observation times do not generally provide more accurate estimates of the field coefficients. The mean squared error of the estimates can be decomposed into a sum of the squared bias and the variance. As the observation time $\tau$ increases, the bias decreases as $\mathcal{O}(1/\tau)$ but the variance increases as $\mathcal{O}(\tau)$. The contrasting time scales imply the existence of an ``optimal'' observing time (the bias-variance tradeoff). An iterative algorithm is developed to construct global approximations of the electric field using the optimal observing times. Lastly, the effect of sensor acceleration is considered. When the sensor location is fixed, measurements of wave fields composed of plane waves are almost periodic and so can be written in terms of a standard Fourier basis. When the sensor is accelerating, the resulting time series is no longer almost periodic. This phenomenon is related to the Doppler effect, where a time transformation must be performed to obtain the frequency and amplitude information from the time series data. To obtain frequency and amplitude information from accelerating sensor time series data in a general inhomogeneous medium, a randomized algorithm is presented. The algorithm is analyzed and example wave fields are reconstructed.
ContributorsBarclay, Bryce Matthew (Author) / Mahalov, Alex (Thesis advisor) / Kostelich, Eric J (Thesis advisor) / Moustaoui, Mohamed (Committee member) / Motsch, Sebastien (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2023
Description
Trace evidence is an essential component of forensic investigations. Anthropogenicmaterials such as fibers and glass have been well studied for use in forensic trace evidence, but the potential use of retroreflective beads found in soils for forensic investigations is largely unexplored. Retroreflective glass beads are tiny spheres mixed into pavement markings to create reflective surfaces to reduce lane departure accidents. Retroreflective glass beads are a potentially new source of trace evidence for forensic investigations.
Analysis of the spatial distribution and chemical compositions of retroreflective glass beads recovered from 17 soil samples were analyzed and compared to see if there are striking variations that can distinguish samples by source. Soil samples taken near marked roads showed significantly higher concentrations of glass beads, averaging from 0.18 bead/g of soil sample to 587 beads/g of soil, while soil samples taken near unmarked roads had average range of concentration of 0 bead/g of soil to 0.21 bead/g of soil. Retroreflective glass beads come from pavement markings, thus soil samples near marked roads are expected to have higher concentrations of glass beads. Analysis of spatial distribution of glass beads showed that as sample collection moved further from the road, concentration of glass beads decreased.
ICP-MS results of elemental concentrations for each sample showed discriminative differences between samples, for most of the elements. An analysis of variance for elemental concentrations was conducted, and results showed statistically significant differences, beyond random chance alone for half of the elements analyzed. For forensic comparisons, a significant difference in even just one element is enough to conclude that the samples came from different sources. The elemental concentrations of glass beads collected from the same location, but of varying differences, was also analyzed. ANOVA results show significant differences for only one or two elements. A pair-wise t-test was conducted to determine which elements are most discriminative among all the samples. Rubidium was found to be the most discriminative, showing significant difference for 67% of the pairs. Beryllium, potassium, and manganese were also highly discriminative, showing significant difference for at least 50% of all the pairs.
ContributorsGomez, Janelle Kate Pacifico (Author) / Montero, Shirly (Thesis advisor) / Herckes, Pierre (Thesis advisor) / Borges, Chad (Committee member) / Gordon, Gwyneth (Committee member) / Arizona State University (Publisher)
Created2023
Description
Type 1 diabetes (T1D) is the result of an autoimmune attack against the insulin-producing β-cells of the pancreas causing hyperglycemia and requiring the individual to rely on life-long exogenous insulin. With the age of onset typically occurring in childhood, there is increased physical and emotional stress to the child as well as caregivers to maintain appropriate glucose levels. The majority of T1D patients have antibodies to one or more antigens: insulin, IA-2, GAD65, and ZnT8. Although antibodies are detectable years before symptoms occur, the initiating factors and mechanisms of progression towards β-cell destruction are still not known. The search for new autoantibodies to elucidate the autoimmune process in diabetes has been slow, with proteome level screenings on native proteins only finding a few minor antigens. Post-translational modifications (PTM)—chemical changes that occur to the protein after translation is complete—are an unexplored way a self-protein could become immunogenic. This dissertation presents the first large sale screening of autoantibodies in T1D to nitrated proteins. The Contra Capture Protein Array (CCPA) allowed for fresh expression of hundreds of proteins that were captured on a secondary slide by tag-specific ligand and subsequent modification with peroxynitrite. The IgG and IgM humoral response of 48 newly diagnosed T1D subjects and 48 age-matched controls were screened against 1632 proteins highly or specifically expressed in pancreatic cells. Top targets at 95% specificity were confirmed with the same serum samples using rapid antigenic protein in situ display enzyme-linked immunosorbent assay (RAPID ELISA) a modified sandwich ELISA employing the same cell-free expression as the CCPA. For validation, 8 IgG and 5 IgM targets were evaluated with an independent serum sample set of 94 T1D subjects and 94 controls. The two best candidates at 90% specificity were estrogen receptor 1 (ESR1) and phosphatidylinositol 4-kinase type 2 beta (PI4K2B) which had sensitivities of 22% (p=.014) and 25% (p=.045), respectively. Receiver operating characteristic (ROC) analyses found an area under curve (AUC) of 0.6 for ESR1 and 0.58 for PI4K2B. These studies demonstrate the ability and value for high-throughput autoantibody screening to modified antigens and the frequency of Type 1 diabetes.
ContributorsHesterman, Jennifer (Author) / LaBaer, Joshua (Thesis advisor) / Borges, Chad (Committee member) / Sweazea, Karen (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022
Description
Plasticizers are plastic additives used to enhance the physical properties of plastic and are ubiquitous in the environment. A class of plasticizer compounds called phthalate esters that are not fully eliminated in wastewater treatment facilities are relevant to the ecological health of downstream ecosystems and urban areas due to their ecotoxicity, tendency for soil accumulation, and the emerging concern about their effects on public health. However, plasticizer concentrations in a constructed wetland environment have rarely been studied in the United States, prompting the need for a method of plasticizer quantification in the Tres Rios Constructed Wetlands which are sustained by the effluent of the 91st Avenue Wastewater Treatment Plant in Phoenix, Arizona. The concentrations of four common plasticizer compounds (dimethyl: DMP, diethyl: DEP, di-n-butyl: DnBP, and bis(2-ethylhexyl): DEHP phthalate) at five sites across the wetland surface water were quantified using solid-phase extraction followed by gas chromatography coupled with mass spectrometry (GC/MS). The sampling period included four sample sets taken from March 2022 to September 2022, which gave temporal data in addition to spatial concentration data. Quantification and quality control were performed using internal standard calibration, replicate samples, and laboratory blanks. Higher molecular weight phthalates accumulated in the wetland surface water at significantly higher average concentrations than those of lower molecular weight at a 95% confidence level, ranging from 8 ng/L to 7349 ng/L and 4 ng/L to 27876 ng/L for DnBP and DEHP, respectively. Concentrations for dimethyl phthalate and diethyl phthalate were typically less than 50 ng/L and were often below the method detection limit. Average concentrations of DnBP and DEHP were significantly higher during periods of high temperatures and arid conditions. The spatial distribution of phthalates was analyzed. Most importantly, a method for successful ultra-trace quantification of plasticizers at Tres Rios was established. These results confirm the presence of plasticizers at Tres Rios and a significant seasonal increase in their surface water concentrations. The developed analytical procedure provides a solid foundation for the Wetlands Environmental Ecology Lab at ASU to further investigate plasticizers and contaminants of emerging concern and determine their ultimate fate through volatilization, sorption, photodegradation, hydrolysis, microbial biodegradation, and phytoremediation studies.
ContributorsStorey, Garrett (Author) / Herckes, Pierre (Thesis director) / Childers, Dan (Committee member) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05