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A Theory of Change: How the Mind, the Heart, and the Future can be Shaped Through Creative Expression

Description

The goal of this thesis was to create a theory of change for an annual Multicultural Arts Camp (MAC) that offers youth with trauma histories opportunities to cultivate protective factors associated with resilience. MAC is designed to promote four primary

The goal of this thesis was to create a theory of change for an annual Multicultural Arts Camp (MAC) that offers youth with trauma histories opportunities to cultivate protective factors associated with resilience. MAC is designed to promote four primary protective outcomes among its participants: (1) safety, (2) self-expression, (3) skill-building and (4) self-efficacy through exploration of various multicultural art forms and connecting with caring adults. The theory of change was informed by my observations during my experience as a MAC volunteer and my review of academic literature to better define and understand how various factors involved in the MAC program are linked to resilience processes. Arts programming can provide opportunities for youth who have experienced trauma to feel safe enough to engage in self-expression and build corresponding skills that promote feelings of self-efficacy. Building these protective factors thereby strengthens children’s capacity for resilience. Accordingly, the theory of change articulates program activities and processes that promote these outcomes among participating youth. Program directors may draw on the theory of change for strategic planning and evaluation efforts assessing the program’s processes and corresponding impact.

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2020-05

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The Impact of Legally Blonde on Women Entering the Legal Profession

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This thesis seeks to understand how the film Legally Blonde has portrayed the interaction between femininity and women. Specifically, this paper will consider how feminism—defined through the context of the era and Legally Blonde—has empowered women to enter male-dominated professional

This thesis seeks to understand how the film Legally Blonde has portrayed the interaction between femininity and women. Specifically, this paper will consider how feminism—defined through the context of the era and Legally Blonde—has empowered women to enter male-dominated professional workspaces—specifically in consideration of the legal profession. The feminism presented in Legally Blonde can be characterized through Elle Wood’s simultaneous displays of intelligence and focus on typical feminine interests: such as marriage, cosmetics, and the like (Marsh, 2005; Lucia, 2005; Hoffman-Longtin & Feldner, 2016). The “third-wave” feminist era surrounding Legally Blonde promotes the duality of women in expressing femininity and holding agentic capability (Dole, 2008). This thesis uses the film’s definition of feminism to consider the changes in women entering the legal profession, the identity of women who connect to the film, and the media’s responses and portrayal of the film. Legally Blonde defines feminism by presenting women as both intelligent and typically feminine—challenging the typical gender role of women in society with her expression of capability and seriousness. While the film elucidates a definition of feminism based on femininity and female agency, some women may not fit into this definition based on the lack of consideration of intersectionality in the film. While the film underlines a changing shift in acceptance of women’s expression of femininity, the film’s message may not apply to all women. Yet, Elle Woods remains a role model for many women to attend law school and her impact is emphasized in popular culture even today.

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2020-05

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Feature Extraction on Sentiment Attitude Values to Better Predict the Stock Market Using Twitter Sentiment

Description

Behavioral economics suggests that emotions can affect an individual’s decision making. Recent research on this idea’s application on large societies hints that there may exist some correlation or maybe even some causation relationship between public sentiment—at least what can be

Behavioral economics suggests that emotions can affect an individual’s decision making. Recent research on this idea’s application on large societies hints that there may exist some correlation or maybe even some causation relationship between public sentiment—at least what can be pulled from Twitter—and the movement of the stock market. One major result of consistent research on whether or not public sentiment can predict the movement of the stock market is that public sentiment, as a feature, is becoming more and more valid as a variable for stock-market-based machine learning models. While raw values typically serve as invaluable points of data, when training a model, many choose to “engineer” new features for their models—deriving rates of change or range values to improve model accuracy.
Since it doesn’t hurt to attempt to utilize feature extracted values to improve a model (if things don’t work out, one can always use their original features), the question may arise: how could the results of feature extraction on values such as sentiment affect a model’s ability to predict the movement of the stock market? This paper attempts to shine some light on to what the answer could be by deriving TextBlob sentiment values from Twitter data, and using Granger Causality Tests and logistic and linear regression to test if there exist a correlation or causation between the stock market and features extracted from public sentiment.

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2020-05

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Effect of Rexinoids on Inducing Effector T Cell Chemotaxis

Description

The retinoid-X receptor (RXR) can form heterodimers with both the retinoic-acid
receptor (RAR) and vitamin D receptor (VDR). The RXR/RAR dimer is activated by ligand all
trans retinoic acid (ATRA), which culminates in gut-specific effector T cell migration. Similarly,

The retinoid-X receptor (RXR) can form heterodimers with both the retinoic-acid
receptor (RAR) and vitamin D receptor (VDR). The RXR/RAR dimer is activated by ligand all
trans retinoic acid (ATRA), which culminates in gut-specific effector T cell migration. Similarly,
the VDR/RXR dimer binds 1,25(OH)2D3 to cause skin-specific effector T cell migration.
Targeted migration is a potent addition to current vaccines, as it would induce activated T cell
trafficking to appropriate areas of the immune system and ensure optimal stimulation (40).
ATRA, while in use clinically, is limited by toxicity and chemical instability. Rexinoids
are stable, synthetically developed ligands specific for the RXR. We have previously shown that
select rexinoids can enhance upregulation of gut tropic CCR9 receptors on effector T cells.
However, it is important to establish whether these cells can actually migrate, to show the
potential of rexinoids as vaccine adjuvants that can cause gut specific T cell migration.
Additionally, since the RXR is a major contributor to VDR-mediated transcription and
epidermotropism (15), it is worth investigating whether these compounds can also function as
adjuvants that promote migration by increasing expression of skin tropic CCR10 receptors on T
cells.
Prior experiments have demonstrated that select rexinoids can induce gut tropic migration
of CD8+ T cells in an in vitro assay and are comparable in effectiveness to ATRA (7). The effect
of rexinoids on CD4+ T cells is unknown however, so the aim of this project was to determine if
rexinoids can cause gut tropic migration in CD4+ T cells to a similar extent. A secondary aim
was to investigate whether varying concentrations in 1,25-Dihydroxyvitamin D3 can be linked to
increasing CCR10 upregulation on Jurkat CD4+ T cells, with the future aim to combine 1,25
Dihydroxyvitamin D3 with rexinoids.
These hypotheses were tested using murine splenocytes for the migration experiment, and
human Jurkat CD4+ T cells for the vitamin D experiment. Migration was assessed using a
Transwell chemotaxis assay. Our findings support the potential of rexinoids as compounds
capable of causing gut-tropic migration in murine CD4+ T cells in vitro, like ATRA. We did not
observe conclusive evidence that vitamin D3 causes upregulated CCR10 expression, but this
experiment must be repeated with a human primary T cell line.

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2020-05

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Role of Metabolism in Antibiotic Resistance

Description

Each year, more and more multi-drug resistant bacterial strains emerge, thus complicating treatment and increasing the average stay in the intensive care unit. As antibiotics are being rendered inefficient, there is a need to look into ways of weakening the

Each year, more and more multi-drug resistant bacterial strains emerge, thus complicating treatment and increasing the average stay in the intensive care unit. As antibiotics are being rendered inefficient, there is a need to look into ways of weakening the internal state of bacterial cells to make them more susceptible to antibiotics. For this, we first need to understand what methods bacteria employ to fight against antibiotics. In this work, we have reviewed how bacteria respond to antibiotics. There is a similarity in response to antibiotic exposure and starvation (stringent stress) which changes the metabolic state. We have delineated what metabolism changes take place and how they are associated with oxidative stress. For example, there is a common change in NADH concentration that is tied to both metabolism and oxidative stress. Finally, we have compared the findings in literature with our research on an antibiotic-resistant RNA polymerase mutant that alters the gene expression profile in the general areas of metabolism and oxidative stress. Based on this thesis, we have suggested a couple of strategies to make antibiotics more efficient; however, as antibiotic-mediated killing is very complex, researchers need to delve deeper to understand and manipulate the full cellular response.

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2020-05

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Input-Elicitation Methods for Crowdsourced Human Computation

Description

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task

Collecting accurate collective decisions via crowdsourcing
is challenging due to cognitive biases, varying
worker expertise, and varying subjective scales. This
work investigates new ways to determine collective decisions
by prompting users to provide input in multiple
formats. A crowdsourced task is created that aims
to determine ground-truth by collecting information in
two different ways: rankings and numerical estimates.
Results indicate that accurate collective decisions can
be achieved with less people when ordinal and cardinal
information is collected and aggregated together
using consensus-based, multimodal models. We also
show that presenting users with larger problems produces
more valuable ordinal information, and is a more
efficient way to collect an aggregate ranking. As a result,
we suggest input-elicitation to be more widely considered
for future work in crowdsourcing and incorporated
into future platforms to improve accuracy and efficiency.

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Date Created
2020-05

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The Sustainability and Safety of Student Stage Managers in Educational Theatre

Description

An auto-ethnographic overview of the author's personal experiences in professional and educational stage management in Arizona. Provides a critique of ASU's stage management program and offers solutions to improve the sustainability and safety of student stage managers.

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Date Created
2020-12

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Automatic Water Shutoff Web Server Infrastructure and Smart Home Integration

Description

This thesis covers the continued development of an automatic water shutoff product developed as a capstone project by students in the college of engineering. The continued development covers the process of setting up a publicly accessible web server along

This thesis covers the continued development of an automatic water shutoff product developed as a capstone project by students in the college of engineering. The continued development covers the process of setting up a publicly accessible web server along with required server components and creating an Alexa skill for smart home integration.

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Date Created
2020-12

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Hana: An Open-Domain Chatbot Application for Language Learning

Description

Learning a new language can be very challenging. One significant aspect of learning a language is learning how to have fluent verbal and written conversations with other people in that language. However, it can be difficult to find other people

Learning a new language can be very challenging. One significant aspect of learning a language is learning how to have fluent verbal and written conversations with other people in that language. However, it can be difficult to find other people available with whom to practice conversations. Additionally, total beginners may feel uncomfortable and self-conscious when speaking the language with others. In this paper, I present Hana, a chatbot application powered by deep learning for practicing open-domain verbal and written conversations in a variety of different languages. Hana uses a pre-trained medium-sized instance of Microsoft's DialoGPT in order to generate English responses to user input translated into English. Google Cloud Platform's Translation API is used to handle translation to and from the language selected by the user. The chatbot is presented in the form of a browser-based web application, allowing users to interact with the chatbot in both a verbal or text-based manner. Overall, the chatbot is capable of having interesting open-domain conversations with the user in languages supported by the Google Cloud Translation API, but response generation can be delayed by several seconds, and the conversations and their translations do not necessarily take into account linguistic and cultural nuances associated with a given language.

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Date Created
2020-12

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The Impact of Time Constraints on HackerRank Assessments

Description

Technical interviews have become the standard for assessing candidates for software development roles. The purpose of this study is to determine whether time constraints impact the performance of individuals on HackerRank coding assessments. During the surveys and HackerRank assessment, subjects

Technical interviews have become the standard for assessing candidates for software development roles. The purpose of this study is to determine whether time constraints impact the performance of individuals on HackerRank coding assessments. During the surveys and HackerRank assessment, subjects wore two physiological sensors: a galvanic skin response bracelet, Shimmer3+GSR that measures emotional intensity and an EEG headset, B-Alert X24 that measures cognitive workload, engagement, and distraction. Subjects were also monitored by external sensors, such as an eye tracker to measure visual attention and by a facial-based emotion recognition system through a webcam to measure their visual attention and emotions. Through these metrics, as well as a Big Five personality demographic survey and mental demand survey, the study examines the difference in performance between strictly timed assessments and timed assessments with time to revise.

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Date Created
2018-05