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- Creators: School of Molecular Sciences
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Breast microcalcifications are a potential indicator of cancerous tumors. Current visualization methods are either uncomfortable or impractical. Impedance measurement studies have been performed, but not in a clinical setting due to a low sensitivity and specificity. We are hoping to overcome this challenge with the development of a highly accurate impedance probe on a biopsy needle. With this technique, microcalcifications and the surrounding tissue could be differentiated in an efficient and comfortable manner than current techniques for biopsy procedures. We have developed and tested a functioning prototype for a biopsy needle using bioimpedance sensors to detect microcalcifications in the human body. In the final prototype a waveform generator sends a sin wave at a relatively low frequency(<1KHz) into the pre-amplifier, which both stabilizes and amplifies the signal. A modified howland bridge is then used to achieve a steady AC current through the electrodes. The voltage difference across the electrodes is then used to calculate the impedance being experienced between the electrodes. In our testing, the microcalcifications we are looking for have a noticeably higher impedance than the surrounding breast tissue, this spike in impedance is used to signal the presence of the calcifications, which are then sampled for examination by radiology.
ContributorsWen, Robert Bobby (Co-author) / Grula, Adam (Co-author) / Vergara, Marvin (Co-author) / Ramkumar, Shreya (Co-author) / Kozicki, Michael (Thesis director) / Ranjani, Kumaran (Committee member) / School of Molecular Sciences (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Breastfeeding has been shown by a number of studies to have numerous benefits on both the mother and the infant. Major health organizations such as the World Health Organization (WHO), now agree that breastfeeding should be encouraged and supported in all countries. But like many things, the wheels of the law are slow to catch up with scientific evident. Although breastfeeding is supported, working women do not have the option of breastfeeding without consequences. For example, in 2003, Kirstie Marshall, a then member of parliament in Australia was ejected from the lower house chamber on February 23, for breastfeeding her baby [3]. According to standing order 30 at the time, "Unless by order of the House, no Member of this House shall presume to bring any stranger into any part of the House appropriated to the Members of this House while the House, or a Committee of the whole House, is sitting" [3]. The rules did not specify the age of strangers, so the then 11-day-old baby, Charlotte Louise and her mother were shown the exit door of parliament. She had to choose between being present at times of major discussions or leaving the house to breastfeed her child, she chose to leave. More recent statistics show that developed nations like the US and Australia which also have high rates of women employment had low rates of breastfeeding. This might mean that workplace policies do not favor breastfeeding or expressing milk at work. Fortunately, laws have since been introduced in both the United States and Australia that support breastfeeding at the workplace. The next step would be to access how these laws affect breastfeeding statistics and how variation between these two countries like the paid parental leave in Australia (which is not present in all US states) would affect these numbers.
ContributorsSakala, Lydia (Author) / Alison, Alison (Thesis director) / Reddy, Swapna (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The number of undergraduate students participating in short-term experiences in global health (STEGHs) abroad has increased dramatically in recent years (Eyler 2002, Drain et al. 2007). These experiences, in tandem with classroom learning, are designed to help students master skills related to global health competencies, including cultural humility and sensitivity, collaborating with community partners, and sociocultural and political awareness. Although STEGHs offer potential benefits to both students and to sending institutions, these experiences can sometimes be problematic and raise ethical challenges. As the number of students engaged in STEGHs continues to increase, it is important to better understand the impact of these programs on student learning. Current ethical and best practice guidelines for STEGHs state that programs should establish evaluation methods to solicit feedback from students both during and on completion of the program (Crump et al. 2010). However, there is currently no established method for gathering this feedback because of the many different global health competency frameworks, types and duration of programs, and different models of student engagement in such programs. Assessing the quality of a STEGH is a profoundly important and difficult question that cannot be answered as succinctly and quantitatively as classroom performance, which has more standard and established assessment metrics. The goal of this project is to identify the most appropriate and useful assessment metric(s) for determining educational quality and impact for STEGHs at ASU by comparing a typical quantitative evaluation tool (pre-post survey with brief open-ended questions) to a more in-depth qualitative method (key informant interviews). In performing my analysis I seek to examine if the latter can produce a richer narrative of student experiences to inform ongoing program evaluations. My research questions are: 1. What are the current qualitative and quantitative evaluation methods available to assess student learning during short-term experiences in global health? 2. How can current methodology for assessing student experiences with short-term experiences in global health be adapted to collect the most information from students? 3. How do student knowledge and attitudes change before and after their short-term experience in global health? Why is understanding those changes important for adapting programs? My end goal would be to use these new, optimal assessment methods for gathering student perspectives and experiences to adapt pre-departure trainings and post-experience debriefings for study abroad programs, both of which I believe will lead to more sustainable partnerships and a healthier understanding of global health work for students.
ContributorsHale, Brittany Ann (Author) / Jehn, Megan (Thesis director) / Wutich, Amber (Committee member) / School of Human Evolution and Social Change (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Leveraging Machine Learning and Wireless Sensing for Robot Localization - Location Variance Analysis
Description
Object localization is used to determine the location of a device, an important aspect of applications ranging from autonomous driving to augmented reality. Commonly-used localization techniques include global positioning systems (GPS), simultaneous localization and mapping (SLAM), and positional tracking, but all of these methodologies have drawbacks, especially in high traffic indoor or urban environments. Using recent improvements in the field of machine learning, this project proposes a new method of localization using networks with several wireless transceivers and implemented without heavy computational loads or high costs. This project aims to build a proof-of-concept prototype and demonstrate that the proposed technique is feasible and accurate.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
Modern communication networks heavily depend upon an estimate of the communication channel, which represents the distortions that a transmitted signal takes as it moves towards a receiver. A channel can become quite complicated due to signal reflections, delays, and other undesirable effects and, as a result, varies significantly with each different location. This localization system seeks to take advantage of this distinctness by feeding channel information into a machine learning algorithm, which will be trained to associate channels with their respective locations. A device in need of localization would then only need to calculate a channel estimate and pose it to this algorithm to obtain its location.
As an additional step, the effect of location noise is investigated in this report. Once the localization system described above demonstrates promising results, the team demonstrates that the system is robust to noise on its location labels. In doing so, the team demonstrates that this system could be implemented in a continued learning environment, in which some user agents report their estimated (noisy) location over a wireless communication network, such that the model can be implemented in an environment without extensive data collection prior to release.
ContributorsChang, Roger (Co-author) / Kann, Trevor (Co-author) / Alkhateeb, Ahmed (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Ketone bodies are produced in the liver from the acetyl CoA derived from fatty acids that cannot enter the Krebs cycle. This is a sub-analysis of a larger study which had numerous outcome markers. This analysis focuses on the relationship between ketone blood levels and cognition. The study looked at the relationship between Time Restricted Feeding (TRF), a method of intermittent fasting. TRF is something that can be easily adapted into an individual’s lifestyle and has been shown to have multiple advantages. This 8-week study began with 23 enrolled participants, but due to COVID-19 only 11 participants could be tested for cognition and blood ketone levels after week 4. All participants had similar ranges of weight, height, age, BMI, hip, and waist measurements at baseline. Moreover, these demographic variables were not related to ketone levels or cognition. The data indicate that ketone bodies increased in participants practicing TRF and that the increase in ketone bodies in the blood, specifically β-hydroxybutyrate was strongly correlated to increased cognitive function. This is consistent with theories that elevated ketone levels allowed for early hunter-gather communities and other mammals to survive prolonged periods of nutrient deprivation while keeping high cognitive function.
ContributorsTaha, Basel Mahmoud (Author) / Johnston, Carol (Thesis director) / Karen, Sweazea (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together with machine learning tools to automate the process of Parkinson’s disease classification and severity assessment. An automated, stable, and accurate method to evaluate Parkinson’s would be significant in streamlining diagnoses of patients and providing families more time for corrective measures. We propose a methodology which incorporates TDA into analyzing Parkinson’s disease postural shifts data through the representation of persistence images. Studying the topology of a system has proven to be invariant to small changes in data and has been shown to perform well in discrimination tasks. The contributions of the paper are twofold. We propose a method to 1) classify healthy patients from those afflicted by disease and 2) diagnose the severity of disease. We explore the use of the proposed method in an application involving a Parkinson’s disease dataset comprised of healthy-elderly, healthy-young and Parkinson’s disease patients.
ContributorsRahman, Farhan Nadir (Co-author) / Nawar, Afra (Co-author) / Turaga, Pavan (Thesis director) / Krishnamurthi, Narayanan (Committee member) / Electrical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The purpose of this thesis experiment was to design and create an Acoustically Active Cannula (AAC), which is furnished by a piezoelectric crystal placed at its tip that produces an acoustic navigation signal. I tested the functionality of the cannula in vitro and demonstrated its navigational abilities in vivo in anesthetized pigs. This experiment was based upon ultrasound science and technology, and thus some practical experience with conventional (B-mode) and Doppler ultrasound was achieved as well. The results of bench and experimental animal studies indicated proper functionality of the AAC for identification and spatial navigation of its tip with color Doppler ultrasound imaging.
ContributorsShamsa, Kayvan (Author) / Tyler, William (Thesis director) / Belohlavek, Marek (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The academic study of eSports, or professional competition through the medium of video games, has tended to focus on players' motivations to play and watch eSports as well as marketing concerns of huge eSports corporations. Instead of utilizing marketing or psychology to analyze this phenomenon, I investigate three areas of focus in accordance with available literature: the fans and their characteristics, the design of the game itself, and the relationship between fans and the game's developer. This investigation was conducted by first examining existing literature surrounding eSports fans, then collecting public domain data such as Reddit posts, forum posts, and YouTube videos, and last by studying interviews with developers and players. With this thesis, I apply a fan studies approach to eSports by creating a series of indicators based in each of the three focus areas which can be utilized as a systematic method of evaluating an eSport's popularity and growth.
ContributorsHilliker, Noah Henry (Author) / Ingram-Waters, Mary (Thesis director) / Schmidt, Peter (Committee member) / Anderson, Sky (Committee member) / School of Molecular Sciences (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Due to artificial selection, dogs have high levels of phenotypic diversity, yet, there appears to be low genetic diversity within individual breeds. Through their domestication from wolves, dogs have gone through a series of population bottlenecks, which has resulted in a reduction in genetic diversity, with a large amount of linkage disequilibrium and the persistence of deleterious mutations. This has led to an increased susceptibility to a multitude of diseases, including cancer. To study the effects of artificial selection and life history characteristics on the risk of cancer mortality, we collected cancer mortality data from four studies as well as the percent of heterozygosity, body size, lifespan and breed group for 201 dog breeds. We also collected specific types of cancer breeds were susceptible to and compared the dog cancer mortality patterns to the patterns observed in other mammals. We found a relationship between cancer mortality rate and heterozygosity, body size, lifespan as well as breed group. Higher levels of heterozygosity were also associated with longer lifespan. These results indicate larger breeds, such as Irish Water Spaniels, Flat-coated Retrievers and Bernese Mountain Dogs, are more susceptible to cancer, with lower heterozygosity and lifespan. These breeds are also more susceptible to sarcomas, as opposed to carcinomas in smaller breeds, such as Miniature Pinschers, Chihuahuas, and Pekingese. Other mammals show that larger and long-lived animals have decreased cancer mortality, however, within dog breeds, the opposite relationship is observed. These relationships could be due to the trade-off between cellular maintenance and growing fast and large, with higher expression of growth factors, such as IGF-1. This study further demonstrates the relationships between cancer mortality, heterozygosity, and life history traits and exhibits dogs as an important model organism for understanding the relationship between genetics and health.
ContributorsBalsley, Cassandra Sierra (Author) / Maley, Carlo (Thesis director) / Wynne, Clive (Committee member) / Tollis, Marc (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
DescriptionThis project is designed to generate enthusiasm for science among refugee students in hopes of inspiring them to continue learning science as well as to help them with their current understanding of their school science subject matter.
ContributorsSipes, Shannon Paige (Author) / O'Flaherty, Katherine (Thesis director) / Gregg, George (Committee member) / School of Molecular Sciences (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12