Kenyon College
Kenyon College: Digital Kenyon - Research, Scholarship, and Creative ExchangeNot a member yet
135065 research outputs found
Sort by
Factors Influencing U.S. College Students’ Preferences for Therapists: A Conjoint Analysis
No full textUntreated mental illness is exceedingly common in college students in the United States, and therapy and mental illness continue to be stigmatized. Many could benefit from the utilization of therapy and thus the current study sought to identify preferences college students hold regarding specific characteristic attributes of potential therapists. We investigated preferences regarding race, gender identity, political affiliation, and modality of therapy. College students in the United States were recruited from Prolific (N=182) and completed an online survey questionnaire. Results from a conjoint analysis procedure showed that gender identity of potential therapists was the most important attribute when it comes to selecting a potential therapist, followed by political affiliation, modality of therapy, and race. We ran paired samples t-tests, and each attribute was found to be significantly more important in therapist selection than the one below it (i.e. gender identity was significantly more important than political affiliation). Our results provide important implications for how we can better meet the mental health needs of college students
Purification of Arabidopsis thaliana 3-Hydroxyisobutyrate Dehydrogenase for Structure-Function Studies
No full text3-Hydroxyisobutyrate dehydrogenase (HIBDH) is an important enzyme in the valine degradation pathway across many organisms. HIBDH oxidizes 3-hydroxyisobutyrate to methylmalonate semialdehyde and 3-hydroxypropionate to malonate semialdehyde, all within the process of converting valine ultimately into acetyl-CoA which is responsible for energy production under extended periods of darkness. While its role in valine degradation is known the relationship between HIBDH’s structure and function is not necessarily as well understood in plants. As such, the Kerry Rouhier lab has taken on the task of performing single-point mutations to determine how different amino acids alter the structure and function of HIBDH in comparison to a non-mutated, “wild-type” (wt) version. This allows us to determine which amino acids play key roles in HIBDH’s structure and function. This summer, I was responsible for purifying 10 of the more than 20 mutated proteins and assessing their enzyme activity (function). Concurrent work in the lab is investigating potential structural changes. Altogether, this data on the structure and function of mutations of HIBDH will help the entire scientific community to better understand how HIBDH works and what it needs to function
Hyperparameter Tuning LIGO Glitch MLAs
No full textLIGO, the Laser Interferometer Gravitational-Wave Observatory, uses advanced laser technology to detect gravitational waves, which are ripples in spacetime caused by massive cosmic events. Because of its extreme sensitivity, LIGO’s detectors are influenced by various sources of noise, from small temperature fluctuations to distant vibrations like passing cars. Loud, transient noise events, known as glitches, are especially challenging for gravitational wave detection. To address this, LIGO records extensive auxiliary sensor data, which can be used to characterize and even predict glitches in the main gravitational-wave channel. This auxiliary data is reduced into feature sets, such as the strength and frequency of noise signals within a time window. Over the summer, I focused on hyperparameter tuning machine learning algorithms (MLAs) designed to read these auxiliary features and predict glitches in the strain data. Our two MLAs, GIANTS and TITAN, can have their performance greatly improved by selecting appropriate hyperparameters. We hypothesized that by utilizing Bayesian Optimization techniques, we could improve their performances. Our main tuning efforts centered on building deep learning models with more hidden layers. In this poster, I present the process and results of hyperparameter tuning. Looking ahead, I plan to compare our MLAs to the current algorithm used by LIGO
Mosque-Madrasa of Sultan Hasan, Entrance
No full texthttps://digital.kenyon.edu/arthistorystudycollection/2772/thumbnail.jp
Shah Mosque Interior
No full texthttps://digital.kenyon.edu/arthistorystudycollection/2768/thumbnail.jp