Matching Items (795)

Filtering by

Clear all filters

131360-Thumbnail Image.png

Iterative Size Reduction of Bead Placement in Nanosphere Lithography

Description

Nanosphere lithography is a high throughput procedure that has important implications
for facile, low cost scaling of nanostructures. However, current benchtop experiments have
limitations based on the placement of molecular species that exhibit greater than singlemolecular binding. In addition, reliance

Nanosphere lithography is a high throughput procedure that has important implications
for facile, low cost scaling of nanostructures. However, current benchtop experiments have
limitations based on the placement of molecular species that exhibit greater than singlemolecular binding. In addition, reliance upon bottom-up self-assembly of close-packed
nanospheres makes it problematic to resolve images using low-cost light microscopes due to the
spacing limitations smaller in magnitude than light wavelength. One method that is created to
resolve this issue is iterative size reduction (ISR), where repetitive ‘iterative’ processes are
employed in order to increase the precision at which single molecules bind to a given substrate.
ISR enables inherent separation of nanospheres and therefore any subsequent single molecule
binding platforms. In addition, ISR targets and encourages single-molecule binding by
systematically reducing binding site size. Results obtained pursuing iteratively reduced
nanostructures showed that many factors are needed to be taken into consideration, including
functionalization of nanosphere particles, zeta potential, and protonation-buffer reactions.
Modalities used for observation of nanoscale patterning and single-molecule binding included
atomic force microscopy (AFM) and ONI super-resolution and fluorescence microscopy. ISR
was also used in conjunction with zero mode waveguides, which are nanoapertures enabling realtime single molecule observation at zeptoliter volumes. Although current limitations and
obstacles still exist with reproducibility and scalability of ISR, it nonetheless exhibits limitless
potential and flexibility in nanotechnology applications.

Contributors

Agent

Created

Date Created
2020-05

131363-Thumbnail Image.png

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.

Contributors

Agent

Created

Date Created
2020-05

131379-Thumbnail Image.png

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.

Contributors

Agent

Created

Date Created
2020-05

Human Physiological Adaptations to Starvation and Caloric Restriction

Description

Throughout history humans have had to adapt to changing conditions in order to survive. Food shortages are one of the major pressures that have shaped past populations. Because of this, the human body has many physiological adaptations that allow

Throughout history humans have had to adapt to changing conditions in order to survive. Food shortages are one of the major pressures that have shaped past populations. Because of this, the human body has many physiological adaptations that allow it to go extended periods of time consuming little to no food. These adaptations also allow the body to recover quickly once food becomes available. They include changes in metabolism that allow different fuel sources to be used for energy, the storing of excess energy absorbed from food in the forms of glycogen and fat to be used in between meals, and a reduction in the basal metabolic rate in response to starvation, as well as physiological changes in the small intestines. Even in places where starvation is not a concern today, these adaptations are still important as they also have an effect on weight gain and dieting in addition to promoting survival when the body is in a starved state.

Disclaimer: The initial goal of this project was to present this information as a podcast episode as a part of a series aimed at teaching the general public about human physiological adaptations. Due to the circumstances with COVID-19 we were unable to meet to make a final recording of the podcast episode. A recording of a practice session recorded earlier in the year has been uploaded instead and is therefore only a rough draft.

Contributors

Agent

Created

Date Created
2020-05

131386-Thumbnail Image.png

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.

Contributors

Agent

Created

Date Created
2020-05

131000-Thumbnail Image.png

Does chronic unpredictable restraint produce dendritic retraction in long-shaft CA3 hippocampal neurons?

Description

Major Depressive Disorder (MDD) is a widespread mood disorder that affects more than 300 million people worldwide and yet, high relapse rates persist. This current study aimed to use an animal model for depression, unpredictable intermittent restraint (UIR), to investigate

Major Depressive Disorder (MDD) is a widespread mood disorder that affects more than 300 million people worldwide and yet, high relapse rates persist. This current study aimed to use an animal model for depression, unpredictable intermittent restraint (UIR), to investigate changes in a subset of neurons within the hippocampus, a region of high susceptibility in MDD. Adult male and female Sprague-Dawley rats were randomly assigned to four treatment groups based on sex (n = 48, n = 12/group). Half of the rats underwent UIR that involved restraint with orbital shaking (30 min or 1 h) for 2-6 consecutive days, followed by one or two days of no stressors; the other half of the rats were undisturbed (CON). UIR rats were stressed for 28 days (21 days of actual stressors) before behavioral testing began with UIR continuing between testing days for nearly 70 days. Rats were then euthanized between 9 and 11 days after the last UIR session. Brains were processed for Golgi stain and long-shaft (LS) neurons within the hippocampal CA3a and CA3b regions were quantified for dendritic complexity using a Camera Lucida attachment. Our findings failed to support our hypothesis that UIR would produce apical dendritic retraction in CA3 hippocampal LS neurons in both males and females. Given that UIR failed to produce CA3 apical dendritic retraction in males, which is commonly observed in the literature, we discuss several reasons for these findings including, time from the end of UIR to when brains were sampled, and the effects of repeated cognitive testing. Given our published findings that UIR impaired spatial ability in males, but not females, we believe that UIR holds validity as a chronic stress paradigm, as UIR attenuated body weight gain in both males and females and produced reductions in thymus gland weight in UIR males. These findings corroborate UIR as an effective stressor in males and warrant further research into the timing of UIR-induced changes in hippocampal CA3 apical dendritic morphology.

Contributors

Agent

Created

Date Created
2020-12

130933-Thumbnail Image.png

Towards Purification of human TRPV1 Pore Domain

Description

The transient receptor potential channel subfamily V member 1 (TRPV1) functions as the heat and capsaicin receptor. It can be activated by heat, protons, pungent chemicals, and a variety of other endogenous mediators of nociception. TRPV1 is a non-selective cation

The transient receptor potential channel subfamily V member 1 (TRPV1) functions as the heat and capsaicin receptor. It can be activated by heat, protons, pungent chemicals, and a variety of other endogenous mediators of nociception. TRPV1 is a non-selective cation channel consisting of 6 transmembrane domains (S1-S6), with helices S1-S4 forming the sensing domain and the S5-S6 helices forming the pore domain. Understanding the TRPV1 channel is imperative due to its relation to a variety of human diseases, including cancer, type II diabetes, hyper and hypothermia, and inflammatory disorders of the airways and bladder. Although TRPV1 is the best-studied thermosensitive-TRP channels of all the 28 family members, the molecular underpinning and the contributions of the human TRPV1 pore domain in thermo-sensing remains elusive. Recently, the human TRPV1 sensing domain was found to contribute to heat activation. It was found to undergo a non-denaturing temperature-dependent conformational change. This finding triggered interest in studying the function and the role of the human TRPV1 pore domain in the heat activation process. Specifically, to identify whether heat activation is intrinsic to the pore domain. This thesis paper explores and optimizes the purification protocol of the human TRPV1 pore domain through three different methods. The first method was using a denaturant, the second method was increasing the length of the histidine tags through Q5 insertion, and the third method was incorporating the protein construct into nanodiscs. In addition to the above three methods, size exclusion chromatography and ion-exchange chromatography were utilized after thrombin cleavage to separate the human TRPV1 pore domain from the cleaved MBP deca-histidine tags as well as the impurities.

Contributors

Agent

Created

Date Created
2020-12

130934-Thumbnail Image.png

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.

Contributors

Agent

Created

Date Created
2020-12

130936-Thumbnail Image.png

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.

Contributors

Agent

Created

Date Created
2020-12

HIV Stigma: A Research and Art Investigation

Description

In the years following the HIV epidemic, much has changed in the way of public health, the social epidemic of stigma has remained. It is the assertion of the authors that stigma can be combatted through the propagation of accurate

In the years following the HIV epidemic, much has changed in the way of public health, the social epidemic of stigma has remained. It is the assertion of the authors that stigma can be combatted through the propagation of accurate education and exposure to the lasting negative impacts of social stigma on persons living with HIV in the United States at present. Although individuals who are not apart of this community cannot truly understand the impacts of HIV-related stigma on those directly impacted by it, a sense of understanding and compassion may be elicited through the breakdown of social stigma into comprehensible components and the provision of stigma-inspired artwork. In addition to providing a background on the scientific basis of Human immunodeficiency virus and its spread, the authors have elected to utilize public engagement by means of an anonymous survey as well as personal interactions with HIV advocates to synthesize paintings. Responses were collected from approximately 300 survey participants via social media with no demographic information collected. It was the hope of the authors that the lack of identifying questions may prompt participants to answer freely and honestly to improve overall understanding of social perceptions of HIV and its related stigma. These paintings and resources deemed appropriate based on the results of the aforementioned survey are to be displayed on a webpage for easier access and engagement with a broader audience.Moreover, this webpage is intended to be maintained and utilized beyond the timeframe of this Undergraduate Honors Thesis for the intended purpose of promoting stigma-free HIV advocacy and education.

Contributors

Agent

Created

Date Created
2018-05