Matching Items (172)
Filtering by
- All Subjects: Technology
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
For as long as humans have been working, they have been looking for ways to get that work done better, faster, and more efficient. Over the course of human history, mankind has created innumerable spectacular inventions, all with the goal of making the economy and daily life more efficient. Today, innovations and technological advancements are happening at a pace like never seen before, and technology like automation and artificial intelligence are poised to once again fundamentally alter the way people live and work in society. Whether society is prepared or not, robots are coming to replace human labor, and they are coming fast. In many areas artificial intelligence has disrupted entire industries of the economy. As people continue to make advancements in artificial intelligence, more industries will be disturbed, more jobs will be lost, and entirely new industries and professions will be created in their wake. The future of the economy and society will be determined by how humans adapt to the rapid innovations that are taking place every single day. In this paper I will examine the extent to which automation will take the place of human labor in the future, project the potential effect of automation to future unemployment, and what individuals and society will need to do to adapt to keep pace with rapidly advancing technology. I will also look at the history of automation in the economy. For centuries humans have been advancing technology to make their everyday work more productive and efficient, and for centuries this has forced humans to adapt to the modern technology through things like training and education. The thesis will additionally examine the ways in which the U.S. education system will have to adapt to meet the demands of the advancing economy, and how job retraining programs must be modernized to prepare workers for the changing economy.
ContributorsCunningham, Reed P. (Author) / DeSerpa, Allan (Thesis director) / Haglin, Brett (Committee member) / School of International Letters and Cultures (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Many factors are at play within the genome of an organism, contributing to much of the diversity and variation across the tree of life. While the genome is generally encoded by four nucleotides, A, C, T, and G, this code can be expanded. One particular mechanism that we examine in this thesis is modification of bases—more specifically, methylation of Adenine (m6A) within the GATC motif of Escherichia coli. These methylated adenines are especially important in a process called methyl-directed mismatch repair (MMR), a pathway responsible for repairing errors in the DNA sequence produced by replication. In this pathway, methylated adenines identify the parent strand and direct the repair proteins to correct the erroneous base in the daughter strand. While the primary role of methylated adenines at GATC sites is to direct the MMR pathway, this methylation has also been found to affect other processes, such as gene expression, the activity of transposable elements, and the timing of DNA replication. However, in the absence of MMR, the ability of these other processes to maintain adenine methylation and its targets is unknown.
To determine if the disruption of the MMR pathway results in the reduced conservation of methylated adenines as well as an increased tolerance for mutations that result in the loss or gain of new GATC sites, we surveyed individual clones isolated from experimentally evolving wild-type and MMR-deficient (mutL- ;conferring an 150x increase in mutation rate) populations of E. coli with whole-genome sequencing. Initial analysis revealed a lack of mutations affecting methylation sites (GATC tetranucleotides) in wild-type clones. However, the inherent low mutation rates conferred by the wild-type background render this result inconclusive, due to a lack of statistical power, and reveal a need for a more direct measure of changes in methylation status. Thus as a first step to comparative methylomics, we benchmarked four different methylation-calling pipelines on three biological replicates of the wildtype progenitor strain for our evolved populations.
While it is understood that these methylated sites play a role in the MMR pathway, it is not fully understood the full extent of their effect on the genome. Thus the goal of this thesis was to better understand the forces which maintain the genome, specifically concerning m6A within the GATC motif.
To determine if the disruption of the MMR pathway results in the reduced conservation of methylated adenines as well as an increased tolerance for mutations that result in the loss or gain of new GATC sites, we surveyed individual clones isolated from experimentally evolving wild-type and MMR-deficient (mutL- ;conferring an 150x increase in mutation rate) populations of E. coli with whole-genome sequencing. Initial analysis revealed a lack of mutations affecting methylation sites (GATC tetranucleotides) in wild-type clones. However, the inherent low mutation rates conferred by the wild-type background render this result inconclusive, due to a lack of statistical power, and reveal a need for a more direct measure of changes in methylation status. Thus as a first step to comparative methylomics, we benchmarked four different methylation-calling pipelines on three biological replicates of the wildtype progenitor strain for our evolved populations.
While it is understood that these methylated sites play a role in the MMR pathway, it is not fully understood the full extent of their effect on the genome. Thus the goal of this thesis was to better understand the forces which maintain the genome, specifically concerning m6A within the GATC motif.
ContributorsBoyer, Gwyneth (Author) / Lynch, Michael (Thesis director) / Behringer, Megan (Committee member) / Geiler-Samerotte, Kerry (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Pandora is a play exploring our relationship with gendered technology through the lens of artificial intelligence. Can women be subjective under patriarchy? Do robots who look like women have subjectivity? Hoping to create a better version of ourselves, The Engineer must navigate the loss of her creation, and Pandora must navigate their new world. The original premiere run was March 27-28, 2018, original cast: Caitlin Andelora, Rikki Tremblay, and Michael Tristano Jr.
ContributorsToye, Abigail Elizabeth (Author) / Linde, Jennifer (Thesis director) / Abele, Kelsey (Committee member) / Department of Information Systems (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.
ContributorsJurgenson, Alex (Co-author) / Nguyen, Duy (Co-author) / Kolder, Sean (Co-author) / Wang, Chenxi (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Management (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Breast cancer is the leading cause of cancer-related deaths of women in the united states. Traditionally, Breast cancer is predominantly treated by a combination of surgery, chemotherapy, and radiation therapy. However, due to the significant negative side effects associated with these traditional treatments, there has been substantial efforts to develop alternative therapies to treat cancer. One such alternative therapy is a peptide-based therapeutic cancer vaccine. Therapeutic cancer vaccines enhance an individual's immune response to a specific tumor. They are capable of doing this through artificial activation of tumor specific CTLs (Cytotoxic T Lymphocytes). However, in order to artificially activate tumor specific CTLs, a patient must be treated with immunogenic epitopes derived from their specific cancer type. We have identified that the tumor associated antigen, TPD52, is an ideal target for a therapeutic cancer vaccine. This designation was due to the overexpression of TPD52 in a variety of different cancer types. In order to start the development of a therapeutic cancer vaccine for TPD52-related cancers, we have devised a two-step strategy. First, we plan to create a list of potential TPD52 epitopes by using epitope binding and processing prediction tools. Second, we plan to attempt to experimentally identify MHC class I TPD52 epitopes in vitro. We identified 942 potential 9 and 10 amino acid epitopes for the HLAs A1, A2, A3, A11, A24, B07, B27, B35, B44. These epitopes were predicted by using a combination of 3 binding prediction tools and 2 processing prediction tools. From these 942 potential epitopes, we selected the top 50 epitopes ranked by a combination of binding and processing scores. Due to the promiscuity of some predicted epitopes for multiple HLAs, we ordered 38 synthetic epitopes from the list of the top 50 epitope. We also performed a frequency analysis of the TPD52 protein sequence and identified 3 high volume regions of high epitope production. After the epitope predictions were completed, we proceeded to attempt to experimentally detected presented TPD52 epitopes. First, we successful transduced parental K562 cells with TPD52. After transduction, we started the optimization process for the immunoprecipitation protocol. The optimization of the immunoprecipitation protocol proved to be more difficult than originally believed and was the main reason that we were unable to progress past the transduction of the parental cells. However, we believe that we have identified the issues and will be able to complete the experiment in the coming months.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Background: Noninvasive MRI methods that can accurately detect subtle brain changes are highly desirable when studying disease-modifying interventions. Texture analysis is a novel imaging technique which utilizes the extraction of a large number of image features with high specificity and predictive power. In this investigation, we use texture analysis to assess and classify age-related changes in the right and left hippocampal regions, the areas known to show some of the earliest change in Alzheimer's disease (AD). Apolipoprotein E (APOE)'s e4 allele confers an increased risk for AD, so studying differences in APOE e4 carriers may help to ascertain subtle brain changes before there has been an obvious change in behavior. We examined texture analysis measures that predict age-related changes, which reflect atrophy in a group of cognitively normal individuals. We hypothesized that the APOE e4 carriers would exhibit significant age-related differences in texture features compared to non-carriers, so that the predictive texture features hold promise for early assessment of AD. Methods: 120 normal adults between the ages of 32 and 90 were recruited for this neuroimaging study from a larger parent study at Mayo Clinic Arizona studying longitudinal cognitive functioning (Caselli et al., 2009). As part of the parent study, the participants were genotyped for APOE genetic polymorphisms and received comprehensive cognitive testing every two years, on average. Neuroimaging was done at Barrow Neurological Institute and a 3D T1-weighted magnetic resonance image was obtained during scanning that allowed for subsequent texture analysis processing. Voxel-based features of the appearance, structure, and arrangement of these regions of interest were extracted utilizing the Mayo Clinic Python Texture Analysis Pipeline (pyTAP). Algorithms applied in feature extraction included Grey-Level Co-Occurrence Matrix (GLCM), Gabor Filter Banks (GFB), Local Binary Patterns (LBP), Discrete Orthogonal Stockwell Transform (DOST), and Laplacian-of-Gaussian Histograms (LoGH). Principal component (PC) analysis was used to reduce the dimensionality of the algorithmically selected features to 13 PCs. A stepwise forward regression model was used to determine the effect of APOE status (APOE e4 carriers vs. noncarriers), and the texture feature principal components on age (as a continuous variable). After identification of 5 significant predictors of age in the model, the individual feature coefficients of those principal components were examined to determine which features contributed most significantly to the prediction of an aging brain. Results: 70 texture features were extracted for the two regions of interest in each participant's scan. The texture features were coded as 70 initial components andwere rotated to generate 13 principal components (PC) that contributed 75% of the variance in the dataset by scree plot analysis. The forward stepwise regression model used in this exploratory study significantly predicted age, accounting for approximately 40% of the variance in the data. The regression model revealed 5 significant regressors (2 right PC's, APOE status, and 2 left PC by APOE interactions). Finally, the specific texture features that contributed to each significant PCs were identified. Conclusion: Analysis of image texture features resulted in a statistical model that was able to detect subtle changes in brain integrity associated with age in a group of participants who are cognitively normal, but have an increased risk of developing AD based on the presence of the APOE e4 phenotype. This is an important finding, given that detecting subtle changes in regions vulnerable to the effects of AD in patients could allow certain texture features to serve as noninvasive, sensitive biomarkers predictive of AD. Even with only a small number of patients, the ability for us to determine sensitive imaging biomarkers could facilitate great improvement in speed of detection and effectiveness of AD interventions..
ContributorsSilva, Annelise Michelle (Author) / Baxter, Leslie (Thesis director) / McBeath, Michael (Committee member) / Presson, Clark (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Multiple sclerosis is a neurological disease that attacks the nerves in the central nervous system of the brain and spinal cord. Multiple sclerosis is a neurological disease that attacks the nerves in the central nervous system of the brain and spinal cord. The severity of multiple sclerosis varies based on the each person and the progression of the disease. There are roughly 2.5 million people that suffer from this disease that life is changed dramatically from being diagnosed with no main way to ease into adjusting to a new lifestyle. The increase of people that are diagnosed with multiple sclerosis, and with a majority of those people being diagnosed in their early 20’s, there is a need for an application that will help patients manage their health. Multiple sclerosis leads to a lifestyle change, which includes various treatment options as well as routine doctor appointments. The creation of the myMS Specialist application will allow patients with multiple sclerosis to live a more comfortable lifestyle while they easily track and manage their health through their mobile devices. Our application has seven components that all play an important role in adjusting to the new everyday lifestyle for a patient with multiple sclerosis. All seven components are largely intertwined with each other to help patients realize patterns in their diet, sleep, exercise and the weather that causes their symptoms to worsen. Our application not only connects to a patient’s doctor so that there is full access of information at all time to the doctor but provides beneficial research to help further the understanding of multiple sclerosis. This application will be marketed and available for purchase to not only patients but doctors. It is our goal to lessen the burden of a new lifestyle to a patient, create constant communication with one’s doctor and provide beneficial data to researchers.
ContributorsSaenz, Devon (Co-author) / Peterson, Tyler (Co-author) / Chomina-Chavez, Aram (Thesis director) / Staats, Cody (Committee member) / W. P. Carey School of Business (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of Accountancy (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Mammary gland development in humans during puberty involves the enlargement of breast tissue, but this is not true in non-human primates. To identify potential causes of this difference, I examined variation in substitution rates across genes related to mammary development. Genes undergoing purifying selection show slower-than-average substitution rates, while genes undergoing positive selection show faster rates. These may be related to the difference between humans and other primates. Three genes were found to be accelerated were FOXF1, IGFBP5, and ATP2B2, but only the latter one was found in humans and it seems unlikely that it would be related to the differences between mammary gland development at puberty between humans and non-human primates.
ContributorsArroyo, Diana (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Schwartz, Rachel (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The foundations of legacy media, especially the news media, are not as strong as they once were. A digital revolution has changed the operation models for and journalistic organizations are trying to find their place in the new market. This project is intended to analyze the effects of new/emerging technologies on the journalism industry. Five different categories of technology will be explored. They are as follows: the semantic web, automation software, data analysis and aggregators, virtual reality and drone journalism. The potential of these technologies will be broken up according to four guidelines, ethical implications, effects on the reportorial process, business impacts and changes to the consumer experience. Upon my examination, it is apparent that no single technology will offer the journalism industry the remedy it has been searching for. Some combination of emerging technologies however, may form the basis for the next generation of news. Findings are presented on a website that features video, visuals, linked content, and original graphics. Website found at http://www.explorenewstech.com/
ContributorsMaxwell, Gavin William (Author) / McGuire, Tim (Thesis director) / Cornelius, David (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Company X has developed RealSenseTM technology, a depth sensing camera that provides machines the ability to capture three-dimensional spaces along with motion within these spaces. The goal of RealSense was to give machines human-like senses, such as knowing how far away objects are and perceiving the surrounding environment. The key issue for Company X is how to commercialize RealSense's depth recognition capabilities. This thesis addresses the problem by examining which markets to address and how to monetize this technology. The first part of the analysis identified potential markets for RealSense. This was achieved by evaluating current markets that could benefit from the camera's gesture recognition, 3D scanning, and depth sensing abilities. After identifying seven industries where RealSense could add value, a model of the available, addressable, and obtainable market sizes was developed for each segment. Key competitors and market dynamics were used to estimate the portion of the market that Company X could capture. These models provided a forecast of the discounted gross profits that could be earned over the next five years. These forecasted gross profits, combined with an examination of the competitive landscape and synergistic opportunities, resulted in the selection of the three segments thought to be most profitable to Company X. These segments are smart home, consumer drones, and automotive. The final part of the analysis investigated entrance strategies. Company X's competitive advantages in each space were found by examining the competition, both for the RealSense camera in general and other technologies specific to each industry. Finally, ideas about ways to monetize RealSense were developed by exploring various revenue models and channels.
ContributorsDunn, Nicole (Co-author) / Boudreau, Thomas (Co-author) / Kinzy, Chris (Co-author) / Radigan, Thomas (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / WPC Graduate Programs (Contributor) / Department of Psychology (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Science (Contributor) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05