Tag: Podium Presentation

Maci Kesler¹
Faculty Mentor: Bernard Zygelman, Ph.D.^1
1College of Sciences, Department of Physics and Astronomy

ABSTRACT
This project explores the dynamics of charged matter under the influence of a magnetic monopole field. Centuries of speculation has centered on the existence of magnetic monopoles. The lack of observational evidence of these particles has left us with a gap in our understanding of electromagnetism. Within Maxwell’s equations, the equations that describe electricity are not symmetric to those that describe magnetism. Modern quantum theories for the fundamental constituents of matter demand that magnetic monopoles were created copiously in the early Universe. Despite many unsuccessful attempts to find evidence of their existence, efforts in that search continue. More recently, theoretical and laboratory studies have demonstrated how effective magnetic monopole structures can manifest in spin ices created in the laboratory. In this study, we explore the dynamics of charged matter in the environment of a magnetic monopole and calculate the radiation signature of that encounter. We propose that the latter serve as a diagnostic in laboratory and astrophysical searches for these elusive particles. We derive the equations of motion using conservation laws and provide analytic solutions to scattering events. We used the analytical results to verify the predictions of our numerical algorithm. We developed a robust program capable of providing accurate solutions under a wide variety of parameter settings. Our results confirm that the scattering trajectories lie on the surface of a cone, as previous studies have found under more restrictive conditions. Our approach has provided a comprehensive analysis of charged matter’s motion and radiation signature in a monopole field.

Nabih Ghani¹
Natnael Basazinew¹
Ching Lan (Lanie) Chang²
Richard Gu³
Hayley Baker¹
Van Vo, Ph.D.²
Faculty Mentor: Edwin Oh, Ph.D.^2
1College of Sciences, Department of Life Sciences
²College of Sciences, Nevada Institute of Personalized Medicine
³College of Sciences, Department of Chemistry and Biochemistry

ABSTRACT
DEAD-box proteins are RNA helicases that are characterized by a conserved Asp-Glu-Ala-Asp motif. These proteins are involved in a variety of processes within cells, ranging from cell cycle progression to the innate immune response. DDX3X is a protein-coding gene found on the X chromosome that codes for a DEAD-box RNA helicase and variants in this gene are believed to be involved in 1-3% of unexplained intellectual disabilities in females. The DDX3X protein is vital for cell viability and is found in all tissues within the body. While mutations in the human DDX3X gene have been characterized to cause intellectual disabilities, seizures, and autism, the mechanism that associates the genetic lesions to pathology is still under investigation. Here, we use mass spectrometry to characterize a complex interactome of DDX3X in the mouse brain. We also verify the novel interactions using immunoblotting techniques and show that phenotypes associated with loss of function DDX3X mutations can be explained through some centrosomal proteins identified in our screen. The data suggest that the loss of DDX3X from the centrosome can perturb neuronal development.

Aurora Emini¹
Lorena Samentar, Ph.D.¹
Faculty Mentor: Nora Caberoy, Ph.D.^1
1College of Sciences, Department of Life Sciences

ABSTRACT
Alzheimer’s disease is a progressive neurodegenerative disease affecting about 5.8M Americans and nearly 48M people worldwide. Currently, there is no cure for Alzheimer’s. Available treatments only address the cognitive and behavioral symptoms but do not delay or stop the progression of the disease. One characteristic of Alzheimer’s is the deposition of amyloid beta plaques in the brain. Clearance of these plaques involves receptors on the cell surface whose activation results to the release of harmful inflammatory factors. This leads to the eventual death of nerve cells. At the Caberoy Lab, we develop a novel Alzheimer’s therapy through amyloid beta clearance without causing inflammation by using the hybrid protein that we have engineered. We have previously demonstrated that our hybrid facilitated amyloid beta clearance. So our main question here is, can our hybrid reduce inflammation in Alzheimer’s disease? We observe a significant reduction in levels of harmful oxidative and inflammatory factors in the presence of our hybrid compared to the control. This implies that our hybrid does not only facilitate clearance of plaques but also reduce inflammation. Our promising result is very exciting as we join the race in developing a cure for Alzheimer’s disease.

Jessica Farnsworth¹
Faculty Mentor: Joshua O. Island, Ph.D.^1
1College of Sciences, Department of Physics and Astronomy

ABSTRACT
Molybdenum disulfide transistor devices were fabricated utilizing muscovite mica as dielectrics in order to test the hydrophilic behavior of mica. This was done by probing the device for its transconductance plot to show hysteretic patterns. Devices were fabricated using a clean van der Waals technique to stack two-dimensional materials into heterostructures. The devices showed a hysteretic trend in the transconductance curve. We compared the hysteretic behavior from mica with that of another well-known dielectric, silicon dioxide. The devices with mica dielectrics showed larger hysteresis in the gate sweeps than silicon dioxide. Devices utilizing mica as dielectrics are expected to have hysteretic behaviors due to the interfacial water on the mica surface. It is also speculated that water accumulation will continue to grow on the surface as long as the device is in ambient conditions, so the hysteresis may worsen over time. We aim to mitigate water absorption at the surface of mica and suggest future work to accomplish this goal.

Adrianne Dizon¹
Faculty Mentor: Katherine Hertlein, Ph.D.^2
1College of Sciences, Department of Life Sciences
²Kirk Kerkorian School of Medicine, Department of Psychiatry

ABSTRACT
Amidst the COVID-19 pandemic, couples dealt with tremendous challenges such as financial insecurity, social seclusion, and an onset of public health restrictions. The pandemic has exacerbated many existing and novel stressors affecting couple intimacy and satisfaction. Extant literature reveals financial strain and social isolation induced by a stressful event, like a health crisis or natural disaster, influences relationship contentment; however, behaviors towards public health restrictions have not been explored. The aim of this study was to evaluate how pandemic-related stressors, namely financial strain, social isolation, and public restriction behaviors, influence relational intimacy and relationship satisfaction. The study sample (N=160) consisted of mostly college-aged females (M=25, SD= 8.66) with an average relationship length of 4.31 years (SD= 5.36). Using a multiple-regression two-dependent variable model, the contribution of each pandemic-related measure to variance level was assessed while the junction of the three stressors was associated with intimacy and satisfaction. Results indicate combined COVID-related stressors had a negative association with relational intimacy and relationship satisfaction. Social isolation contributed the most variance (15%) to the level of relational intimacy and relationship satisfaction (R2= 0.151). A comprehensive discussion on the long-term implications of social isolation on couples is provided. Additional insight is presented on how couples and family therapists provide coping strategies and interventions for distressed couples.

Natnael Basazinew¹
Nabih Ghani¹
Ching Lan (Lanie) Chang²
Richard Gu³
Hayley Baker¹
Moonis Ghani¹
Van Vo, Ph.D.²
Faculty Mentor: Edwin Oh, Ph.D.^2
1College of Sciences, Department of Life Sciences
²College of Sciences, Nevada Institute of Personalized Medicine
³College of Sciences, Department of Chemistry and Biochemistry

ABSTRACT
The 15q11.2 microdeletion syndrome results in neurodevelopmental deficits that include developmental delay and psychiatric conditions. While comprehensive microarray studies have demonstrated that four genes (NIPA1, NIPA2, CYFIP1, and TUBGCP5) within the 15q11.2 locus are associated with behavioral and anatomical pathology, a unifying hypothesis to correlate gene function to phenotype has not been established. Copy number variations within chromosome 15 are relatively frequent in approximately 1% of the population. An increasing number of genes are associated with intellectual disability (ID) and autism spectrum disorders (ASDs). Fragile X mental retardation gene 1 (FMR1), whose silencing causes the Fragile X syndrome, is the most common form of ID and autism. The precise functional significance of the CYFIP/FMRP interaction is not understood fully; however, among the interactors of FMRP, CYFIP1/2 are good candidates for ID and autism, based on their genetic implication and functional properties. CYFIP1 and CYFIP2 represent a link between Rac1, the WAVE complex, and FMRP, favoring the cross-talk between actin polymerization and translational control. Thus, the role of Cyfip1 in brain connectivity is yet to be explored. Using mass spectrometry, immunoblotting, and immunoprecipitation datasets, we will characterize protein-protein interactions and mechanisms associated with the manifestation of neural disorders linked with the 15q11.2 microdeletion syndrome, and more specifically, with CYFIP1 copy number variation.

Justin Alvarez¹
Kayla Cerminara¹
Faculty Mentor: Joshua O. Island, Ph.D.^1
1College of Sciences, Department of Physics and Astronomy

ABSTRACT
The quantum anomalous hall effect (QAHE) is a phase of matter in which a dissipationless current is made to flow around the edge of a two dimensional (2D) material. Making use of this effect for next generation electronics could lead to faster processors and low power devices. There are very few materials that exist in nature that intrinsically possess the QAHE, however by sandwiching target 2D materials together we can establish this highly sought after phase. By using three 2D materials: graphene, molybdenum disulfide (MoS2) and chromium tri-iodide (CrI3) forming a van der Waals heterostructure we can create a proximity induced magnetism effect. Here, we took highly sensitive capacitance measurements of graphene on MoS2 devices at low temperatures and high magnetic fields. By taking measurements of the penetration field capacitance vs charge density and polarization of a graphene and MoS2 device at 2 Kelvin and zero external magnetic field, we are able to see the charge neutrality point in graphene and the conduction band of MoS2. Using this method of capacitance measurements we plan to integrate thin CrI3 flakes into our graphene and MoS2 devices to develop a full device to study the proximity induced QAHE.

This research was funded by the Southern Nevada Northern Arizona (SNNA) Louis Stokes Alliance for Minority Participation (LSAMP), which is housed within UNLV’s Center for Academic Enrichment and Outreach and supported by a grant (HRD – 1712523) from the National Science Foundation (NSF). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF. 

Janelle Domantay¹
Faculty Mentor: Brendan Morris, Ph.D.^2
1Howard R. Hughes College of Engineering, Department of Computer Science
²Howard R. Hughes College of Engineering, Department of Electrical and Computer Engineering

ABSTRACT
Awareness detection technologies have been gaining traction in a variety of enterprises; Most often used for driver fatigue detection, recent research has shifted towards using computer vision technologies to analyze user attention in stationary environments such as online classrooms. This study aims to extend previous research on distraction detection by analyzing which visual features contribute most to predicting awareness and fatigue. We utilized the open source facial analysis toolkit OpenFace in order to analyze visual data of subjects at varying levels of attentiveness. Then, using a Support Vector Machine (SVM) we created several prediction models for user attention and identified Histogram of Oriented Gradients (HOGS) to be the greatest predictor of the features we tested. We also compared the performance of this SVM to deep learning approaches that utilize Convolutional and/or Recurrent neural networks (CNN’s and CRNN’s). Interestingly, CRNN’s did not appear to perform significantly better than their CNN counterparts. While deep learning methods definitively performed better, SVMs utilized less resources and, using certain parameters, were able to approach the performance of deep learning methods.