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- Genre: Doctoral Dissertation
- Creators: Arizona State University
- Creators: Acharya, Abhinav
- Creators: Gray, Dr. Rob
- Member of: ASU Electronic Theses and Dissertations
- Status: Published
Description
Numerous studies have examined the attachments individuals have to the places they visit, and that those attachments are formed through experiencing a place in person. This study is unique in that it examines pre-trip place attachment formation via the use of mobile technology and social media. It proposes that media experienced through the use of a participant's smartphone can foster the development of positive emotions, which in turn, facilitates greater mental imagery processing that ultimately influences pre-trip place attachment formation. An experimental design was constructed to examine how text and video on a destination's Facebook page influences an individual's emotions, mental imagery, and subsequently attachment to that destination. Specifically, a 2 (narrative text vs. descriptive text) x 2 (short, fast-paced video vs. long, slow-paced video) between-subjects design was used. A total of 343 usable participant responses were included in the analysis. The data was then analyzed through a two-step process using structural equation modeling. Results revealed no significant influence of textual or video media on emotions although the choice in text has a greater influence on emotions than choice in video. Additionally, emotions had a significant impact on mental imagery. Finally, mental imagery processing had a significant impact on only the social bonding dimension of place attachment. In conclusion, while media had no significant impact on emotions, the effect of previous traveler's retelling of personal accounts on the emotions of potential travelers researching a destination should be examined more closely. Further, the study participants had no prior experience with the destination, yet emotions influenced mental imagery, which also influenced social bonding. Thus further research should be conducted to better understand how potential traveler's image of a destination can be affected by the stories or others.
ContributorsPlunkett, Daniel (Author) / Budruk, Megha (Thesis advisor) / Lee, Woojin (Thesis advisor) / Wetmore, Jameson (Committee member) / Wise, Greg (Committee member) / Arizona State University (Publisher)
Created2013
Description
Parkinson's disease, the most prevalent movement disorder of the central nervous system, is a chronic condition that affects more than 1000,000 U.S. residents and about 3% of the population over the age of 65. The characteristic symptoms include tremors, bradykinesia, rigidity and impaired postural stability. Current therapy based on augmentation or replacement of dopamine is designed to improve patients' motor performance but often leads to levodopa-induced complications, such as dyskinesia and motor fluctuation. With the disease progress, clinicians must closely monitor patients' progress in order to identify any complications or decline in motor function as soon as possible in PD management. Unfortunately, current clinical assessment for Parkinson's is subjective and mostly influenced by brief observations during patient visits. Thus improvement or decline in patients' motor function in between visits is extremely difficult to assess. This may hamper clinicians while making informed decisions about the course of therapy for Parkinson's patients and could negatively impact clinical care. In this study we explored new approaches for PD assessment that aim to provide home-based PD assessment and monitoring. By extending the disease assessment to home, the healthcare burden on patients and their family can be reduced, and the disease progress can be more closely monitored by physicians. To achieve these aims, two novel approaches have been designed, developed and validated. The first approach is a questionnaire based self-evaluation metric, which estimate the PD severity through using self-evaluation score on pre-designed questions. Based on the results of the first approach, a smart phone based approach was invented. The approach takes advantage of the mobile computing technology and clinical decision support approach to evaluate the motor performance of patient daily activity and provide the longitudinal disease assessment and monitoring. Both approaches have been validated on recruited PD patients at the movement disorder program of Barrow Neurological Clinic (BNC) at St Joseph's Hospital and Medical Center. The results of validation tests showed favorable accuracy on detecting and assessing critical symptoms of PD, and shed light on promising future of implementing mobile platform based PD evaluation and monitoring tools to facilitate PD management.
ContributorsPan, Di (Author) / Petitti, Diana (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Dhall, Rohit (Committee member) / Arizona State University (Publisher)
Created2013
Description
Mycobacterium tuberculosis (Mtb), the etiological agent of the tuberculosis disease, is estimated to infect one-fourth of the human population and is responsible for 1.5 million deaths annually. The increased emergence of bacterial resistance to clinical interventions highlights the lack in development of novel antimicrobial therapeutics. Prototypical bacterial two-component systems (TCS) allow for sensing of extracellular stimuli and relay thereof to create a transcriptional response. The prrAB TCS is essential for viability in Mtb, presenting itself as an attractive novel drug target. In Mtb, PrrAB is involved in the adaptation to the intra-macrophage environment and recent work implicates PrrAB in the dosR-dependent hypoxia adaptation. This work defines a direct molecular and regulatory connection between Mtb PrrAB and the dosR-dependent hypoxia response. Using electrophoretic mobility shift assays combined with surface plasmon resonance, the Mtb dosR gene is established as a specific target of PrrA, corroborated by fluorescence reporter assays demonstrating a regulatory relationship. Considering the scarce understanding of prrAB essentiality in nontuberculous mycobacteria and the presence of multiple prrAB orthologs in Mycobacterium smegmatis and Mycobacterium abscessus, CRISPR interference was utilized to evaluate the essentiality of PrrAB beyond Mtb. prrAB was found to be inessential for viability in M. smegmatis yet required for in vitro growth. Conversely, M. abscessus prrAB repression led to enhanced in vitro growth. Diarylthiazole-48 (DAT-48) displayed decreased selectivity against M. abscessus but demonstrated enhanced intrinsic activity upon prrAB repression in M. abscessus. Lastly, to aid in the rapid determination of mycobacterial drug susceptibility and the detection of mycobacterial heteroresistance, the large volume scattering imaging (LVSim) platform was adapted for mycobacteria. Using LVSim, Mtb drug susceptibility was detected phenotypically within 6 hours, and clinically relevant mycobacterial heteroresistance was detected phenotypically within 10 generations. The data generated in these studies provide insight into the essential role of PrrAB in Mtb and its involvement in the dosR-dependent hypoxia adaptation, advance the understanding of mycobacterial PrrAB essentiality and PrrAB-associated mycobacterial growth dependency. These studies further establish molecular and mechanistic connection between PrrAB and DAT-48 in Mtb and M. abscessus and develop a rapid phenotypic drug susceptibility testing platform for mycobacteria.
ContributorsHaller, Yannik Alex (Author) / Haydel, Shelley E (Thesis advisor) / Bean, Heather (Committee member) / Nickerson, Cheryl (Committee member) / Plaisier, Christopher (Committee member) / Acharya, Abhinav (Committee member) / Arizona State University (Publisher)
Created2023
Description
Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the 10th leading cause of death, worldwide. The prevalence of drug-resistant clinical isolates and the paucity of newly-approved antituberculosis drugs impedes the successful eradication of Mtb. Bacteria commonly use two-component systems (TCS) to sense their environment and genetically modulate adaptive responses. The prrAB TCS is essential in Mtb, thus representing an auspicious drug target; however, the inability to generate an Mtb ΔprrAB mutant complicates investigating how this TCS contributes to pathogenesis. Mycobacterium smegmatis, a commonly used M. tuberculosis genetic surrogate was used here. This work shows that prrAB is not essential in M. smegmatis. During ammonium stress, the ΔprrAB mutant excessively accumulates triacylglycerol lipids, a phenotype associated with M. tuberculosis dormancy and chronic infection. Additionally, triacylglycerol biosynthetic genes were induced in the ΔprrAB mutant relative to the wild-type and complementation strains during ammonium stress. Next, RNA-seq was used to define the M. smegmatis PrrAB regulon. PrrAB regulates genes participating in respiration, metabolism, redox balance, and oxidative phosphorylation. The M. smegmatis ΔprrAB mutant is compromised for growth under hypoxia, is hypersensitive to cyanide, and fails to induce high-affinity respiratory genes during hypoxia. Furthermore, PrrAB positively regulates the hypoxia-responsive dosR TCS response regulator, potentially explaining the hypoxia-mediated growth defects in the ΔprrAB mutant. Despite inducing genes encoding the F1F0 ATP synthase, the ΔprrAB mutant accumulates significantly less ATP during aerobic, exponential growth compared to the wild-type and complementation strains. Finally, the M. smegmatis ΔprrAB mutant exhibited growth impairment in media containing gluconeogenic carbon sources. M. tuberculosis mutants unable to utilize these substrates fail to establish chronic infection, suggesting that PrrAB may regulate Mtb central carbon metabolism in response to chronic infection. In conclusion, 1) prrAB is not universally essential in mycobacteria; 2) M. smegmatis PrrAB regulates genetic responsiveness to nutrient and oxygen stress; and 3) PrrAB may provide feed-forward control of the DosRS TCS and dormancy phenotypes. The data generated in these studies provide insight into the mycobacterial PrrAB TCS transcriptional regulon, PrrAB essentiality in Mtb, and how PrrAB may mediate stresses encountered by Mtb during the transition to chronic infection.
ContributorsMaarsingh, Jason (Author) / Haydel, Shelley E (Thesis advisor) / Roland, Kenneth (Committee member) / Sandrin, Todd (Committee member) / Bean, Heather (Committee member) / Arizona State University (Publisher)
Created2019
Description
Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats and put user's data at risk. Even though modern mobile platforms such as Android have integrated security mechanisms to protect users, most mechanisms do not easily adapt to user's security requirements and rapidly evolving threats. They either fail to provide sufficient intelligence for a user to make informed security decisions, or require great sophistication to configure the mechanisms for enforcing security decisions. These limitations lead to a situation where users are disadvantageous against emerging malware on modern mobile platforms. To remedy this situation, I propose automated and systematic approaches to address three security management tasks: monitoring, assessment, and confinement of mobile apps. In particular, monitoring apps helps a user observe and record apps' runtime behaviors as controlled under security mechanisms. Automated assessment distills intelligence from the observed behaviors and the security configurations of security mechanisms. The distilled intelligence further fuels enhanced confinement mechanisms that flexibly and accurately shape apps' behaviors. To demonstrate the feasibility of my approaches, I design and implement a suite of proof-of-concept prototypes that support the three tasks respectively.
ContributorsJing, Yiming (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015
Description
The widespread adoption of mobile devices gives rise to new opportunities and challenges for authentication mechanisms. Many traditional authentication mechanisms become unsuitable for smart devices. For example, while password is widely used on computers as user identity authentication, inputting password on small smartphone screen is error-prone and not convenient. In the meantime, there are emerging demands for new types of authentication. Proximity authentication is an example, which is not needed for computers but quite necessary for smart devices. These challenges motivate me to study and develop novel authentication mechanisms specific for smart devices.
In this dissertation, I am interested in the special authentication demands of smart devices and about to satisfy the demands. First, I study how the features of smart devices affect user identity authentications. For identity authentication domain, I aim to design a continuous, forge-resistant authentication mechanism that does not interrupt user-device interactions. I propose a mechanism that authenticates user identity based on the user's finger movement patterns. Next, I study a smart-device-specific authentication, proximity authentication, which authenticates whether two devices are in close proximity. For prox- imity authentication domain, I aim to design a user-friendly authentication mechanism that can defend against relay attacks. In addition, I restrict the authenticated distance to the scale of near field, i.e., a few centimeters. My first design utilizes a user's coherent two-finger movement on smart device screen to restrict the distance. To achieve a fully-automated system, I explore acoustic communications and propose a novel near field authentication system.
In this dissertation, I am interested in the special authentication demands of smart devices and about to satisfy the demands. First, I study how the features of smart devices affect user identity authentications. For identity authentication domain, I aim to design a continuous, forge-resistant authentication mechanism that does not interrupt user-device interactions. I propose a mechanism that authenticates user identity based on the user's finger movement patterns. Next, I study a smart-device-specific authentication, proximity authentication, which authenticates whether two devices are in close proximity. For prox- imity authentication domain, I aim to design a user-friendly authentication mechanism that can defend against relay attacks. In addition, I restrict the authenticated distance to the scale of near field, i.e., a few centimeters. My first design utilizes a user's coherent two-finger movement on smart device screen to restrict the distance. To achieve a fully-automated system, I explore acoustic communications and propose a novel near field authentication system.
ContributorsLi, Lingjun (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Ye, Jieping (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2014
Description
Road networks are valuable assets that deteriorate over time and need to be preserved to an acceptable service level. Pavement management systems and pavement condition assessment have been implemented widely to routinely evaluate the condition of the road network, and to make recommendations for maintenance and rehabilitation in due time and manner. The problem with current practices is that pavement evaluation requires qualified raters to carry out manual pavement condition surveys, which can be labor intensive and time consuming. Advances in computing capabilities, image processing and sensing technologies has permitted the development of vehicles equipped with such technologies to assess pavement condition. The problem with this is that the equipment is costly, and not all agencies can afford to purchase it. Recent researchers have developed smartphone applications to address this data collection problem, but only works in a restricted set up, or calibration is recommended. This dissertation developed a simple method to continually and accurately quantify pavement condition of an entire road network by using technologies already embedded in new cars, smart phones, and by randomly collecting data from a population of road users. The method includes the development of a Ride Quality Index (RQI), and a methodology for analyzing the data from multi-factor uncertainty. It also derived a methodology to use the collected data through smartphone sensing into a pavement management system. The proposed methodology was validated with field studies, and the use of Monte Carlo method to estimate RQI from different longitudinal profiles. The study suggested RQI thresholds for different road settings, and a minimum samples required for the analysis. The implementation of this approach could help agencies to continually monitor the road network condition at a minimal cost, thus saving millions of dollars compared to traditional condition surveys. This approach also has the potential to reliably assess pavement ride quality for very large networks in matter of days.
ContributorsMedina Campillo, Jose Roberto (Author) / Kaloush, Kamil (Thesis advisor) / Underwood, Benjamin S (Thesis advisor) / Mamlouk, Michael (Committee member) / Stempihar, Jeffery (Committee member) / Arizona State University (Publisher)
Created2018
Description
Driving a vehicle is a complex task that typically requires several physical interactions and mental tasks. Inattentive driving takes a driver’s attention away from the primary task of driving, which can endanger the safety of driver, passenger(s), as well as pedestrians. According to several traffic safety administration organizations, distracted and inattentive driving are the primary causes of vehicle crashes or near crashes. In this research, a novel approach to detect and mitigate various levels of driving distractions is proposed. This novel approach consists of two main phases: i.) Proposing a system to detect various levels of driver distractions (low, medium, and high) using a machine learning techniques. ii.) Mitigating the effects of driver distractions through the integration of the distracted driving detection algorithm and the existing vehicle safety systems. In phase- 1, vehicle data were collected from an advanced driving simulator and a visual based sensor (webcam) for face monitoring. In addition, data were processed using a machine learning algorithm and a head pose analysis package in MATLAB. Then the model was trained and validated to detect different human operator distraction levels. In phase 2, the detected level of distraction, time to collision (TTC), lane position (LP), and steering entropy (SE) were used as an input to feed the vehicle safety controller that provides an appropriate action to maintain and/or mitigate vehicle safety status. The integrated detection algorithm and vehicle safety controller were then prototyped using MATLAB/SIMULINK for validation. A complete vehicle power train model including the driver’s interaction was replicated, and the outcome from the detection algorithm was fed into the vehicle safety controller. The results show that the vehicle safety system controller reacted and mitigated the vehicle safety status-in closed loop real-time fashion. The simulation results show that the proposed approach is efficient, accurate, and adaptable to dynamic changes resulting from the driver, as well as the vehicle system. This novel approach was applied in order to mitigate the impact of visual and cognitive distractions on the driver performance.
ContributorsAlomari, Jamil (Author) / Mayyas, AbdRaouf (Thesis advisor) / Cooke, Nancy J. (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
Tissue approximation and repair have been performed with sutures and staples for centuries, but these means are inherently traumatic. Tissue repair using laser-responsive nanomaterials can lead to rapid tissue sealing and repair and is an attractive alternative to existing clinical methods. Laser tissue welding is a sutureless technique for sealing incised or wounded tissue, where chromophores convert laser light to heat to induce in tissue sealing. Introducing chromophores that absorb near-infrared light creates differential laser absorption and allows for laser wavelengths that minimizes tissue damage.
In this work, plasmonic nanocomposites have been synthesized and used in laser tissue welding for ruptured porcine intestine ex vivo and incised murine skin in vivo. These laser-responsive nanocomposites improved tissue strength and healing, respectively. Additionally, a spatiotemporal model has been developed for laser tissue welding of porcine and mouse cadaver intestine sections using near-infrared laser irradiation. This mathematical model can be employed to identify optimal conditions for minimizing healthy cell death while still achieving a strong seal of the ruptured tissue using laser welding. Finally, in a model of surgical site infection, laser-responsive nanomaterials were shown to be efficacious in inhibiting bacterial growth. By incorporating an anti-microbial functionality to laser-responsive nanocomposites, these materials will serve as a treatment modality in sealing tissue, healing tissue, and protecting tissue in surgery.
In this work, plasmonic nanocomposites have been synthesized and used in laser tissue welding for ruptured porcine intestine ex vivo and incised murine skin in vivo. These laser-responsive nanocomposites improved tissue strength and healing, respectively. Additionally, a spatiotemporal model has been developed for laser tissue welding of porcine and mouse cadaver intestine sections using near-infrared laser irradiation. This mathematical model can be employed to identify optimal conditions for minimizing healthy cell death while still achieving a strong seal of the ruptured tissue using laser welding. Finally, in a model of surgical site infection, laser-responsive nanomaterials were shown to be efficacious in inhibiting bacterial growth. By incorporating an anti-microbial functionality to laser-responsive nanocomposites, these materials will serve as a treatment modality in sealing tissue, healing tissue, and protecting tissue in surgery.
ContributorsUrie, Russell Ricks (Author) / Rege, Kaushal (Thesis advisor) / Acharya, Abhinav (Committee member) / DeNardo, Dale (Committee member) / Holloway, Julianne (Committee member) / Thomas, Marylaura (Committee member) / Arizona State University (Publisher)
Created2019
Description
Abnormally low or high blood iron levels are common health conditions worldwide and can seriously affect an individual’s overall well-being. A low-cost point-of-care technology that measures blood iron markers with a goal of both preventing and treating iron-related disorders represents a significant advancement in medical care delivery systems. Methods: A novel assay equipped with an accurate, storable, and robust dry sensor strip, as well as a smartphone mount and (iPhone) app is used to measure total iron in human serum. The sensor strip has a vertical flow design and is based on an optimized chemical reaction. The reaction strips iron ions from blood-transport proteins, reduces Fe(III) to Fe(II), and chelates Fe(II) with ferene, with the change indicated by a blue color on the strip. The smartphone mount is robust and controls the light source of the color reading App, which is calibrated to obtain output iron concentration results. The real serum samples are then used to assess iron concentrations from the new assay and validated through intra-laboratory and inter-laboratory experiments. The intra-laboratory validation uses an optimized iron detection assay with multi-well plate spectrophotometry. The inter-laboratory validation method is performed in a commercial testing facility (LabCorp). Results: The novel assay with the dry sensor strip and smartphone mount, and App is seen to be sensitive to iron detection with a dynamic range of 50 - 300 µg/dL, sensitivity of 0.00049 µg/dL, coefficient of variation (CV) of 10.5%, and an estimated detection limit of ~15 µg/dL These analytical specifications are useful for predicting iron deficiency and overloads. The optimized reference method has a sensitivity of 0.00093 µg/dL and CV of 2.2%. The correlation of serum iron concentrations (N=20) between the optimized reference method and the novel assay renders a slope of 0.95, and a regression coefficient of 0.98, suggesting that the new assay is accurate. Lastly, a spectrophotometric study of the iron detection reaction kinetics is seen to reveal the reaction order for iron and chelating agent. Conclusion: The new assay is able to provide accurate results in intra- and inter- laboratory validations and has promising features of both mobility and low-cost.
ContributorsSerhan, Michael (Author) / Forzani, Erica (Thesis advisor) / Raupp, Gregory (Committee member) / Acharya, Abhinav (Committee member) / Hu, Tony (Committee member) / Smith, Barbara (Committee member) / Arizona State University (Publisher)
Created2020