Tag: Uniquely Their Own

Using machine learning to classify bacterial species from fluorescent image data

Presenter: Noah Pettinari – Physics

Faculty Mentor(s): Raghuveer Parthasarathy

Session: (In-Person) Oral Panel—Uniquely Their Own

The study of host-microbe interactions has been of growing interest in recent years, with new research highlighting their importance in ecology, human health, developmental biology, and immunology. Fluorescent imaging of larger multispecies bacterial communities within the host microbiome is generally limited to one species per fluorescent channel, greatly limiting the ability to image several species simultaneously. Additionally, the creation and integration of new fluorophores is a slow and labor intensive process, further limiting the use of fluorescent imaging. We assess an algorithm for classifying two bacterial species in vitro within one fluorescent channel using machine learning techniques on morphology data. We then applied this machine learning model to bacterial communities in the rotifer gut, testing new algorithms for removing unwanted autofluorescence along the way.

The Pine Mountain Observatory Deep Field

Presenter: Ellis Mimms – Physics

Faculty Mentor(s): Scott Fisher

Session: (In-Person) Oral Panel—Uniquely Their Own, Poster Presentation

The Hubble Space Telescope is a telescope that was launched into low Earth orbit as part of international cooperation between the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). Weighing over 10,886 kilograms and containing a 2.4 diameter meter mirror, it is one of the largest, most versatile space telescopes in the world and one of the most renowned. While Hubble has been used to observe many different celestial objects and phenomena, one of the most famous pieces of data to come from it is known as the Hubble Deep Field Image. For 10 straight days in 1995, Hubble stared at a tiny, nearly empty patch of sky near the Big Dipper. The telescope gathered all the light it could, slowly building the picture that would come to be known as the Hubble Deep Field Image. This image, showing a sliver of our early universe, contains over 3,000 galaxies, large and small, shapely and amorphous, burning in the depths of space. With the Pine Mountain Observatory Deep Field (PMODF), we have created our own deep field image, instead imaging the central region of the Coma Cluster to determine how many galaxies we can detect within it. With our data, we have been able to determine to what magnitude the telescopes at Pine Mountain can see into space. Collecting around 10 hours of data, The Pine Mountain Observatory Deep Field represents some of the deepest imagery taken at Pine Mountain Observatory to date.

Dark Quarks Detection via Magnetic Dipole Interaction

Presenter: Chester Mantel − Physics

Faculty Mentor(s): Graham Kribs

Session: (In-Person) Oral Panel—Uniquely Their Own

Fermionic dark matter could arise from a strongly interacting dark sector. Dark quarks are bound into neutral composite dark baryons, which can be probed by direct detection experiments through a magnetic dipole interaction. We consider theories where the strong interaction consists of Nc colors, where Nc is odd and large, and place bounds on the parameter space of the theory using direct detection and cosmological constraints.

Progress Towards Single-Photon Time-of-Flight Imaging

Presenter(s): Kevin Eckrosh — Physics

Faculty Mentor(s): Brian Smith, Markus Allgaie

Session: (In-Person) Oral Panel—Uniquely Their Own

An array of fibers with different lengths are fused into a single output fiber. A photon-counting detector is used to record the arrival time of photons incident on the array, allowing to reconstruct which fiber the photons entered. This scheme allows us to measure the spatial light distribution of single photons.

Olympic Postponement and the Future of Japan: A Qualitative Study of Tokyo 2020

Presenter: Hermya Brock − Global Studies

Faculty Mentor(s): Yoav Dubinsky

(In-Person) Oral Panel—Uniquely Their Own

For the first time in Olympic history, the 2020 Tokyo Olympics were postponed for one year, taking place in July and August 2021 due to the COVID-19 emergency. This paper explores the effect hosting the Olympics during a pandemic has had on Japan’s image using the frameworks of soft power and sports diplomacy. In this thesis, I code interview responses for themes to explore shifts in Japan’s country image as a result of Tokyo 2020. The trends that emerge in the findings of this paper are Japan’s handling of the pandemic and mental health advocacy. These findings indicate significant opportunities for Japan to improve its image using the 2020 Tokyo Olympics as a catalyst. As such, these historic Games establish Tokyo 2020 as the benchmark for future Olympics to take place in a pandemic-affected world.