Matching Items (12,524)
Filtering by
- Creators: Arizona State University
- Member of: Theses and Dissertations
- Status: Published
Description
My dissertation combines the notion of residential sorting from Tiebout (1956) with Grossman’s (1972) concept of a health production function to develop a new empirical framework for investigating what individuals’ residential location choices reveal about their valuation of amenities, the welfare effects of climate change, the forces underlying environmental justice, and the value of a statistical life. Location
choices are affected by age, health, and financial constraints, and by exposure to local amenities that affect people’s health and longevity. Chapter 1 previews how I formalize this idea and investigate its empirical implications in three interrelated essays. Chapter 2 investigates interactions between health, the environment, and income. Seniors tend to move at higher rates after being diagnosed with new chronic medical conditions. While seniors generally tend to move to locations with less polluted air, those who have been diagnosed with respiratory conditions move to relatively more polluted locations. This counterintuitive pattern is reconciled by documenting that new diagnoses bring about increases in medical expenditures, thereby limiting disposable income that can be spent on housing. Relatively cheaper places tend to be more polluted, and higher exposure to pollution leaves seniors more vulnerable to future health shocks. In Chapter 3, I combine information about housing prices with estimates of location-specific effects on mortality to estimate the Value of a Statistical Life (VSL) for seniors - one of the most important statistics used to evaluate policies affecting mortality. Since local amenities correlate with causal mortality effects, but also provide utility independently, the difficulty in controlling for local amenities implies that my VSL estimates are best interpreted as bounds. Chapter 4 builds a new structural framework for evaluating spatially heterogeneous changes to local amenities. I estimate a dynamic model of location choice with a sample of 5.5 million seniors from 2001-2013. Their average annual willingness-to-pay to avoid future climate change in the United States under a “business as usual” scenario ranges from $962 for older, sicker groups who are more vulnerable to climate change’s negative effects on health to -$1,894 for younger, healthier groups, who value warmer winters and are relatively resilient.
choices are affected by age, health, and financial constraints, and by exposure to local amenities that affect people’s health and longevity. Chapter 1 previews how I formalize this idea and investigate its empirical implications in three interrelated essays. Chapter 2 investigates interactions between health, the environment, and income. Seniors tend to move at higher rates after being diagnosed with new chronic medical conditions. While seniors generally tend to move to locations with less polluted air, those who have been diagnosed with respiratory conditions move to relatively more polluted locations. This counterintuitive pattern is reconciled by documenting that new diagnoses bring about increases in medical expenditures, thereby limiting disposable income that can be spent on housing. Relatively cheaper places tend to be more polluted, and higher exposure to pollution leaves seniors more vulnerable to future health shocks. In Chapter 3, I combine information about housing prices with estimates of location-specific effects on mortality to estimate the Value of a Statistical Life (VSL) for seniors - one of the most important statistics used to evaluate policies affecting mortality. Since local amenities correlate with causal mortality effects, but also provide utility independently, the difficulty in controlling for local amenities implies that my VSL estimates are best interpreted as bounds. Chapter 4 builds a new structural framework for evaluating spatially heterogeneous changes to local amenities. I estimate a dynamic model of location choice with a sample of 5.5 million seniors from 2001-2013. Their average annual willingness-to-pay to avoid future climate change in the United States under a “business as usual” scenario ranges from $962 for older, sicker groups who are more vulnerable to climate change’s negative effects on health to -$1,894 for younger, healthier groups, who value warmer winters and are relatively resilient.
ContributorsMathes, Sophie (Author) / Kuminoff, Nicolai V. (Thesis advisor) / Murphy, Alvin D (Thesis advisor) / Bishop, Kelly C. (Committee member) / Ketcham, Jonathan (Committee member) / Bick, Alexander (Committee member) / Arizona State University (Publisher)
Created2020
Description
ABSTRACT
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
ContributorsTendolkar, Tanvi Gopal (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Committee member) / Craig, Scotty (Committee member) / Arizona State University (Publisher)
Created2020
Description
This thesis focuses on serial crystallography studies with X-ray free electron lasers
(XFEL) with a special emphasis on data analysis to investigate important processes
in bioenergy conversion and medicinal applications.
First, the work on photosynthesis focuses on time-resolved femtosecond crystallography
studies of Photosystem II (PSII). The structural-dynamic studies of the water
splitting reaction centering on PSII is a current hot topic of interest in the field, the
goal of which is to capture snapshots of the structural changes during the Kok cycle.
This thesis presents results from time-resolved serial femtosecond (fs) crystallography
experiments (TR-SFX) where data sets are collected at room temperature from a
stream of crystals that intersect with the ultrashort femtosecond X-ray pulses at an
XFEL with the goal to obtain structural information from the transient state (S4)
state of the cycle where the O=O bond is formed, and oxygen is released. The most
current techniques available in SFX/TR-SFX to handle hundreds of millions of raw
diffraction patterns are discussed, including selection of the best diffraction patterns,
allowing for their indexing and further data processing. The results include two 4.0 Å
resolution structures of the ground S1 state and triple excited S4 transient state.
Second, this thesis reports on the first international XFEL user experiments in
South Korea at the Pohang Accelerator Laboratory (PAL-XFEL). The usability of this
new XFEL in a proof-of-principle experiment for the study of microcrystals of human
taspase1 (an important cancer target) by SFX has been tested. The descriptions of
experiments and discussions of specific data evaluation challenges of this project in
light of the taspase1 crystals’ high anisotropy, which limited the resolution to 4.5 Å,
are included in this report
In summary, this thesis examines current techniques that are available in the
SFX/TR-SFX domain to study crystal structures from microcrystals damage-free,
with the future potential of making movies of biological processes.
(XFEL) with a special emphasis on data analysis to investigate important processes
in bioenergy conversion and medicinal applications.
First, the work on photosynthesis focuses on time-resolved femtosecond crystallography
studies of Photosystem II (PSII). The structural-dynamic studies of the water
splitting reaction centering on PSII is a current hot topic of interest in the field, the
goal of which is to capture snapshots of the structural changes during the Kok cycle.
This thesis presents results from time-resolved serial femtosecond (fs) crystallography
experiments (TR-SFX) where data sets are collected at room temperature from a
stream of crystals that intersect with the ultrashort femtosecond X-ray pulses at an
XFEL with the goal to obtain structural information from the transient state (S4)
state of the cycle where the O=O bond is formed, and oxygen is released. The most
current techniques available in SFX/TR-SFX to handle hundreds of millions of raw
diffraction patterns are discussed, including selection of the best diffraction patterns,
allowing for their indexing and further data processing. The results include two 4.0 Å
resolution structures of the ground S1 state and triple excited S4 transient state.
Second, this thesis reports on the first international XFEL user experiments in
South Korea at the Pohang Accelerator Laboratory (PAL-XFEL). The usability of this
new XFEL in a proof-of-principle experiment for the study of microcrystals of human
taspase1 (an important cancer target) by SFX has been tested. The descriptions of
experiments and discussions of specific data evaluation challenges of this project in
light of the taspase1 crystals’ high anisotropy, which limited the resolution to 4.5 Å,
are included in this report
In summary, this thesis examines current techniques that are available in the
SFX/TR-SFX domain to study crystal structures from microcrystals damage-free,
with the future potential of making movies of biological processes.
ContributorsKetawala, Gihan Kaushyal (Author) / Fromme, Petra (Thesis advisor) / Liu, Wei (Committee member) / Kirian, Richard (Committee member) / Arizona State University (Publisher)
Created2020
Description
Cancer is a worldwide burden in every aspect: physically, emotionally, and financially. A need for innovation in cancer research has led to a vast interdisciplinary effort to search for the next breakthrough. Mathematical modeling allows for a unique look into the underlying cellular dynamics and allows for testing treatment strategies without the need for clinical trials. This dissertation explores several iterations of a dendritic cell (DC) therapy model and correspondingly investigates what each iteration teaches about response to treatment.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
ContributorsDickman, Lauren (Author) / Kuang, Yang (Thesis advisor) / Baer, Steven M. (Committee member) / Gardner, Carl (Committee member) / Gumel, Abba B. (Committee member) / Kostelich, Eric J. (Committee member) / Arizona State University (Publisher)
Created2020
Description
Social animals benefit from the aggregation of knowledge and cognitive processing power. Part of this benefit comes from individual heterogeneity, which provides the basis to group-level strategies, such as division of labor and collective intelligence. In turn, the outcomes of collective choices, as well as the needs of the society at large, influence the behavior of individuals within it. My dissertation research addresses how the feedback between individual and group-level behavior affects individuals and promotes collective change. I study this question in the context of seed selection in the seed harvester ant, Pogonomyrmex californicus. I use both field and laboratory studies to explore questions relating to individual behavior: how forager decision-making is affected through information available in the nest and at the seed pile; how workers interact with seeds in the nest; and how forager preferences diverge from each other’s and the colony’s preference. I also explore the integration between individual and colony behavior, specifically: how interactions between the foraging and processing tasks affect colony collection behavior; how individual behavior changes affect colony preference changes and whether colony preference changes can be considered learning behavior. To answer these questions, I provided colonies with binary choices between seeds of unequal or similar quality, and measured individual, task group, and colony-level behavior. I found that colonies are capable of learning to discriminate between seeds, and learned information lasts at least one month without seed interaction outside of the nest. I also found that colony learning was coordinated by foragers receiving updated information from seeds in the nest to better discriminate and make choices between seed quality during searches for seeds outside of the nest. My results show that seed processing is essential for stimulating collection of novel seeds, and that foraging and processing are conducted by behaviorally and spatially overlapping but distinct groups of workers. Finally, I found that foragers’ preferences are diverse yet flexible, even when colonies are consistent in their preference at the population level. These combined experiments generate a more detailed and complete understanding of the mechanisms behind the flexibility of collective colony choices, how colonies incorporate new information, and how workers individually and collectively make foraging decisions for the colony in a decentralized manner.
ContributorsBespalova, Ioulia Ivanovna (Author) / Fewell, Jennifer (Thesis advisor) / Hölldobler, Bert (Committee member) / Liebig, Jürgen (Committee member) / Pinter-Wollman, Noa (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2020
Description
Introduction: A diet high in fermented, oligio-, di-, monosaccharide, and polyols
(FODMAP) has been shown to exacerbate symptoms of irritable bowel syndrome
(IBS). Previous literature has shown significant improvement in IBS symptoms after
adherence to a low FODMAP diet (LFD). However, dietary adherence to the LFD is
difficult with patients stating that information provided by healthcare providers
(HCPs) is generalized and nonspecific requiring them to search for supplementary
information to fit their needs. Notably, studies that have used a combination of
online and in-person methods for treatment have shown improved adherence to the
LFD. Objective: To determine whether a novel artificial intelligence (AI) dietary
mobile application will improve adherence to the LFD compared to a standard online
dietary intervention (CON) in populations with IBS or IBS-like symptoms over a 4-
week period. Methods: Participants were randomized into two groups: APP or CON.
The intervention group was provided access to an AI mobile application, a dietary
resource verified by registered dietitians which uses artificial intelligence to
individualize dietary guidance in real-time with the ability to scan menus and
barcodes and provide individuals with food scores based on their dietary preferences.
Primary measures included mobile app engagement, dietary adherence, and
manifestation of IBS-like symptoms. Baseline Results: A total of 58 participants
were randomized to groups. This is an ongoing study and this thesis details the
methodology and baseline characteristics of the participants at baseline and
intervention start. Validation of the application could improve the range of offerings
for lifestyle diseases treatable through dietary modification.
(FODMAP) has been shown to exacerbate symptoms of irritable bowel syndrome
(IBS). Previous literature has shown significant improvement in IBS symptoms after
adherence to a low FODMAP diet (LFD). However, dietary adherence to the LFD is
difficult with patients stating that information provided by healthcare providers
(HCPs) is generalized and nonspecific requiring them to search for supplementary
information to fit their needs. Notably, studies that have used a combination of
online and in-person methods for treatment have shown improved adherence to the
LFD. Objective: To determine whether a novel artificial intelligence (AI) dietary
mobile application will improve adherence to the LFD compared to a standard online
dietary intervention (CON) in populations with IBS or IBS-like symptoms over a 4-
week period. Methods: Participants were randomized into two groups: APP or CON.
The intervention group was provided access to an AI mobile application, a dietary
resource verified by registered dietitians which uses artificial intelligence to
individualize dietary guidance in real-time with the ability to scan menus and
barcodes and provide individuals with food scores based on their dietary preferences.
Primary measures included mobile app engagement, dietary adherence, and
manifestation of IBS-like symptoms. Baseline Results: A total of 58 participants
were randomized to groups. This is an ongoing study and this thesis details the
methodology and baseline characteristics of the participants at baseline and
intervention start. Validation of the application could improve the range of offerings
for lifestyle diseases treatable through dietary modification.
ContributorsRafferty, Aaron (Author) / Johnston, Carol (Thesis advisor) / Hall, Richard (Committee member) / Fitton, Renee (Committee member) / Arizona State University (Publisher)
Created2020
Description
This dissertation aims at developing novel materials and processing routes using alkali activated aluminosilicate binders for porous (lightweight) geopolymer matrices and 3D-printing concrete applications. The major research objectives are executed in different stages. Stage 1 includes developing synthesis routes, microstructural characterization, and performance characterization of a family of economical, multifunctional porous ceramics developed through geopolymerization of an abundant volcanic tuff (aluminosilicate mineral) as the primary source material. Metakaolin, silica fume, alumina powder, and pure silicon powder are also used as additional ingredients when necessary and activated by potassium-based alkaline agents. In Stage 2, a processing route was developed to synthesize lightweight geopolymer matrices from fly ash through carbonate-based activation. Sodium carbonate (Na2CO3) was used in this study to produce controlled pores through the release of CO2 during the low-temperature decomposition of Na2CO3. Stage 3 focuses on 3D printing of binders using geopolymeric binders along with several OPC-based 3D printable binders. In Stage 4, synthesis and characterization of 3D-printable foamed fly ash-based geopolymer matrices for thermal insulation is the focus. A surfactant-based foaming process, multi-step mixing that ensures foam jamming transition and thus a dry foam, and microstructural packing to ensure adequate skeletal density are implemented to develop foamed suspensions amenable to 3D-printing. The last stage of this research develops 3D-printable alkali-activated ground granulated blast furnace slag mixture. Slag is used as the source of aluminosilicate and shows excellent mechanical properties when activated by highly alkaline activator (NaOH + sodium silicate solution). However, alkali activated slag sets and hardens rapidly which is undesirable for 3D printing. Thus, a novel mixing procedure is developed to significantly extend the setting time of slag activated with an alkaline activator to suit 3D printing applications without the use of any retarding admixtures. This dissertation, thus advances the field of sustainable and 3D-printable matrices and opens up a new avenue for faster and economical construction using specialized materials.
ContributorsAlghamdi, Hussam Suhail G (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Abbaszadegan, Morteza (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2019
Description
More underrepresented minority (URM) healthcare professionals are needed to improve health equity. Although holistic review in admissions has the potential to increase URM participation in health professions, recent data suggest that its impact varies substantially. The purpose of the dissertation research described here was to identify interventions to increase diversity among healthcare professionals and explore holistic review use in physician assistant (PA) program admissions to advance understanding of effective practices. PA programs were selected as an important prototype for exploratory studies since the extent of holistic review use in PA programs was unknown; at the same time, URM representation among PA students has decreased over the last 15 years.
A critical review of the literature revealed that various holistic review practices have been used by several health professions programs to successfully increase URM enrollment and that organizational culture may be a factor that promotes success. Following this, 2017 Physician Assistant Education Association survey data were analyzed to assess the frequency of holistic review in PA programs and examine its association with URM matriculation. Results from 221 of the 223 PA programs accredited at the time showed that 77.5% used holistic review, and its use modestly correlated with proportion of first-year students identified as ethnic minorities (rs = .20, p < .01). Of particular interest, some programs using holistic review had substantially higher proportions of URM students than others. This finding laid the foundation for a qualitative multiple case study to explore the role of organizational culture as a hypothesized antecedent to effective holistic admissions processes.
Survey study responses were used to select two PA program ‘cases’ that met criteria consistent with a proposed conceptual framework linking organizational culture that values diversity (or ‘diversity culture’) to holistic admissions associated with high URM enrollment. Directed content analysis of data revealed that diversity culture appears to be a strong driver of practices that support enrolling diverse classes of students.
Overall, this mixed methods program of research advances understanding of holistic review, its utility, and the influence of organizational culture. The research generated important insights with ramifications for current practice and future studies within PA and across health professions programs.
A critical review of the literature revealed that various holistic review practices have been used by several health professions programs to successfully increase URM enrollment and that organizational culture may be a factor that promotes success. Following this, 2017 Physician Assistant Education Association survey data were analyzed to assess the frequency of holistic review in PA programs and examine its association with URM matriculation. Results from 221 of the 223 PA programs accredited at the time showed that 77.5% used holistic review, and its use modestly correlated with proportion of first-year students identified as ethnic minorities (rs = .20, p < .01). Of particular interest, some programs using holistic review had substantially higher proportions of URM students than others. This finding laid the foundation for a qualitative multiple case study to explore the role of organizational culture as a hypothesized antecedent to effective holistic admissions processes.
Survey study responses were used to select two PA program ‘cases’ that met criteria consistent with a proposed conceptual framework linking organizational culture that values diversity (or ‘diversity culture’) to holistic admissions associated with high URM enrollment. Directed content analysis of data revealed that diversity culture appears to be a strong driver of practices that support enrolling diverse classes of students.
Overall, this mixed methods program of research advances understanding of holistic review, its utility, and the influence of organizational culture. The research generated important insights with ramifications for current practice and future studies within PA and across health professions programs.
ContributorsCoplan, Bettie (Author) / Lamb, Gerri (Thesis advisor) / Evans, Bronwynne (Committee member) / Todd, Michael (Committee member) / Arizona State University (Publisher)
Created2019
Description
The lack of fungibility in Bitcoin has forced its userbase to seek out tools that can heighten their anonymity. Third-party Bitcoin mixers utilize obfuscation techniques to protect participants from blockchain analysis. In recent years, various centralized and decentralized Bitcoin mixing implementations have been proposed in academic literature. Although these methods depict a threat-free environment for users to preserve their anonymity, public Bitcoin mixers continue to be associated with theft and poor implementation.
This research explores the public Bitcoin mixer ecosystem to identify if today's mixing services have adopted academically proposed solutions. This is done through real-world interactions with publicly available mixers to analyze both implementation and resistance to common threats in the mixing landscape. First, proposed decentralized and centralized mixing protocols found in literature are outlined. Then, data is presented from 19 publicly announced mixing services available on the deep web and clearnet. The services are categorized based on popularity with the Bitcoin community and experiments are conducted on five public mixing services: ChipMixer, MixTum, Bitcoin Mixer, CryptoMixer, and Sudoku Wallet.
The results of the experiments highlight a clear gap between public and proposed Bitcoin mixers in both implementation and security. Today's mixing services focus on presenting users with a false sense of control to gain their trust rather then employing secure mixing techniques. As a result, the five selected services lack implementation of academically proposed techniques and display poor resistance to common mixer-related threats.
This research explores the public Bitcoin mixer ecosystem to identify if today's mixing services have adopted academically proposed solutions. This is done through real-world interactions with publicly available mixers to analyze both implementation and resistance to common threats in the mixing landscape. First, proposed decentralized and centralized mixing protocols found in literature are outlined. Then, data is presented from 19 publicly announced mixing services available on the deep web and clearnet. The services are categorized based on popularity with the Bitcoin community and experiments are conducted on five public mixing services: ChipMixer, MixTum, Bitcoin Mixer, CryptoMixer, and Sudoku Wallet.
The results of the experiments highlight a clear gap between public and proposed Bitcoin mixers in both implementation and security. Today's mixing services focus on presenting users with a false sense of control to gain their trust rather then employing secure mixing techniques. As a result, the five selected services lack implementation of academically proposed techniques and display poor resistance to common mixer-related threats.
ContributorsPakki, Jaswant (Author) / Doupe, Adam (Thesis advisor) / Shoshitaishvili, Yan (Committee member) / Wang, Ruoyu (Committee member) / Arizona State University (Publisher)
Created2020
Description
Background: Process mining (PM) using event log files is gaining popularity in healthcare to investigate clinical pathways. But it has many unique challenges. Clinical Pathways (CPs) are often complex and unstructured which results in spaghetti-like models. Moreover, the log files collected from the electronic health record (EHR) often contain noisy and incomplete data. Objective: Based on the traditional process mining technique of using event logs generated by an EHR, observational video data from rapid ethnography (RE) were combined to model, interpret, simplify and validate the perioperative (PeriOp) CPs. Method: The data collection and analysis pipeline consisted of the following steps: (1) Obtain RE data, (2) Obtain EHR event logs, (3) Generate CP from RE data, (4) Identify EHR interfaces and functionalities, (5) Analyze EHR functionalities to identify missing events, (6) Clean and preprocess event logs to remove noise, (7) Use PM to compute CP time metrics, (8) Further remove noise by removing outliers, (9) Mine CP from event logs and (10) Compare CPs resulting from RE and PM. Results: Four provider interviews and 1,917,059 event logs and 877 minutes of video ethnography recording EHRs interaction were collected. When mapping event logs to EHR functionalities, the intraoperative (IntraOp) event logs were more complete (45%) when compared with preoperative (35%) and postoperative (21.5%) event logs. After removing the noise (496 outliers) and calculating the duration of the PeriOp CP, the median was 189 minutes and the standard deviation was 291 minutes. Finally, RE data were analyzed to help identify most clinically relevant event logs and simplify spaghetti-like CPs resulting from PM. Conclusion: The study demonstrated the use of RE to help overcome challenges of automatic discovery of CPs. It also demonstrated that RE data could be used to identify relevant clinical tasks and incomplete data, remove noise (outliers), simplify CPs and validate mined CPs.
ContributorsDeotale, Aditya Vijay (Author) / Liu, Huan (Thesis advisor) / Grando, Maria (Thesis advisor) / Manikonda, Lydia (Committee member) / Arizona State University (Publisher)
Created2020