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Analyzing Incident Rates of COVID-19 Before and After Stay-At-Home Orders Throughout the Southwestern U.S. with Respect to Limited Mobility Models

ContributorsTilleman, Karl Benson (Author) / Albuquerque, Fabio Suzart de (Thesis director) / Powers, Brian (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Mathematical and analytical approach at the floor and diffuser of a Formula 1 vehicle and how they produce downforce. Reaches a conclusion about how engineers and aerodynamicists creates the desired effects underneath the vehicle to produce substantial downforce.

ContributorsMarcantonio, Nicholas Joseph (Author) / Rajadas, John (Thesis director) / Hillery, Scott (Committee member) / College of Integrative Sciences and Arts (Contributor) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Preeclampsia is a disease that occurs during pregnancy and affects upwards of 10% of pregnancies around the world (Osungbade & Ige, 2011). African American pregnant women are particularly vulnerable and die at a disproportionate rate compared to other races. In this literature review, three research studies were analyzed to determine

Preeclampsia is a disease that occurs during pregnancy and affects upwards of 10% of pregnancies around the world (Osungbade & Ige, 2011). African American pregnant women are particularly vulnerable and die at a disproportionate rate compared to other races. In this literature review, three research studies were analyzed to determine if African American pregnant women were included in preeclampsia Studies. Only one of the studies included in this review met all criteria by including African American pregnant women. One research study met half of the criteria; however, the authors noted that there was not enough evidence for Black Americans. The third research article also only met half of the criteria. We conclude that further studies are needed that include African American women in studies on preeclampsia.

ContributorsCheeks, Maiya (Author) / Lateef, Dalya (Thesis director) / Briggs, Georgette (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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A research project turned creative project focusing on the narrative of the student's perspective in the Next Generation Service Corps scholarship program. Using survey results from the program members, narratives of their experiences were compiled to offer insight and direction for the growth of the program.<br/><br/>A video of the defense

A research project turned creative project focusing on the narrative of the student's perspective in the Next Generation Service Corps scholarship program. Using survey results from the program members, narratives of their experiences were compiled to offer insight and direction for the growth of the program.<br/><br/>A video of the defense can be found at this link: https://youtu.be/O63NRz0z1Ys

ContributorsJanezic, John Henry (Author) / Hunt, Brett (Thesis director) / Smith, Jacqueline (Committee member) / College of Integrative Sciences and Arts (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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An X class solar flare has the potential to remove our satellites from orbit, permanently deactivate our main forms of communication and bring humanity into a technology-free age. By using Geant4, it is possible to simulate several layers of the Earth's atmosphere and send a simulated solar flare and coronal

An X class solar flare has the potential to remove our satellites from orbit, permanently deactivate our main forms of communication and bring humanity into a technology-free age. By using Geant4, it is possible to simulate several layers of the Earth's atmosphere and send a simulated solar flare and coronal mass ejection. This thesis will show the interaction of photons and protons of various energies with several kilometers of atmosphere.

ContributorsDolghier, Kristian Adrian (Author) / Shovkovy, Igor (Thesis director) / Steinkamp, Brian (Committee member) / Economics Program in CLAS (Contributor) / College of Integrative Sciences and Arts (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The Founders lab is a year-long program that gives its students an opportunity to participate in a unique team-based, experiential Barrett honors thesis project to design and apply marketing and sales strategies, as well as business and financial models to start up and launch a new business. This honors thesis

The Founders lab is a year-long program that gives its students an opportunity to participate in a unique team-based, experiential Barrett honors thesis project to design and apply marketing and sales strategies, as well as business and financial models to start up and launch a new business. This honors thesis project focuses on increasing the rate of vaccination outcomes in a country where people are increasingly busy (less time) and unwilling to get a needle through a new business venture that provides a service that brings vaccinations straight to businesses, making them available for their employees. Through our work with the Founders Lab, our team was able to create this pitch deck.

ContributorsGomez, Isaias Abraham (Co-author) / Hanzlick, Emily (Co-author) / Zatonskiy, Albert (Co-author) / Byrne, Jared (Thesis director) / Hall, Rick (Committee member) / Silverstein, Taylor (Committee member) / College of Integrative Sciences and Arts (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Bacteria are often regarded s pathogens, with deleterious impacts on the human body. However, it is known that the presence of trillions of bacteria on and in the human body impart beneficial effects on human health. Like a fingerprint, each individual’s microbiome is unique. The composition of bacteria in one

Bacteria are often regarded s pathogens, with deleterious impacts on the human body. However, it is known that the presence of trillions of bacteria on and in the human body impart beneficial effects on human health. Like a fingerprint, each individual’s microbiome is unique. The composition of bacteria in one person’s gut is different from the gut bacteria in another individual. Together, the human gut microbiome is a complex mix of organisms that is commonly referred to as “the second brain.� Its role in the human body goes beyond digestion and immune system function. The health of the microbiome factors into risk for illnesses as diverse as depression, obesity, bowel disorders and autism (Perlmutter et al., 2015). In context of the myriad of bacteria that live on and within the human body, the composition of bacteria in the gut may have the most significant impact on an individual’s well-being. This “superorganism� co-evolved with its host in order to provide essential and mutually beneficial functions (Ragonnaud et al., 2021).

Affecting millions of Americans, depression is one of the leading causes of the Global Burden of Disease (GBD), followed by anxiety (Gibson-Smith et al., 2018). Communication that occurs between the human brain and the gut microbiome has been found to be a major contributor towards mental health. The human gut microbiome is comprised of many microbes that can communicate with the brain through the gut-brain axis. However, factors such as stress and diets can interfere with this process, especially after increasing the permeability of the intestine (Khoshbin et al., 2020). Perturbation of the gut-brain axis has been implicated across a wide scale of neurodegenerative disorders, with respect to psychopathology (Bonaz et al., 2018). The environment of the gut, along with which species reside there, can help determine the link between gut function and disease. Therefore, it may be possible to prevent the degradation of an individual’s immune function and well-being through alteration of the gut microbiome. (abstract)
ContributorsPisarczyk, Nicole (Author) / Penton, Christopher (Thesis director) / Huffman, Holly (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
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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

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
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This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013