Digital Commons Network^™

Applications Of Parallel Discrete Event Simulation, Erik J. Jensen

Modeling, Simulation and Visualization Student Capstone Conference

This work presents three applications of parallel discrete event simulation (PDES), which describe the motivation for and the benefits of using PDES, the kinds of synchronization algorithms that are used, and scaling behavior with these different synchronization algorithms.

Active Polar Liquid Crystal Channel Flows: Analyzing The Roles Of Nematic Strength And Activation Parameter, Lacey Schenk, Ruhai Zhou

College of Sciences Posters

Suspensions of active polar liquid crystalline polymers (APLC) exhibit complex phenomena such as spontaneous flows, pattern formations and defects. Using the Kinetic Model, which couples the Smoluchowski Equation and the Navier-Stokes Equations, we conduct numerical simulations of APLC in a microfluidic channel to investigate the competitive effect among different material constants, such as the nematic concentration (the strength of the potential for nematic order) and active strength (the individual nano-rods strength of their individual movement) with and without a pressure gradient. Both Dirichlet and Neumann boundary conditions on the mathematical model are employed. Steady states, including isotropic and nematic states, …

A Machine Learning Approach To Denoising Particle Detector Observations In Nuclear Physics, Polykarpos Thomadakis, Angelos Angelopoulos, Gagik Gavalian, Nikos Chrisochoides

College of Sciences Posters

With the evolution in detector technologies and electronic components used in the Nuclear Physics field, experimental setups become larger and more complex. Faster electronics enable particle accelerator experiments to run with higher beam intensity, providing more interactions per time and more particles per interaction. However, the increased beam intensities present a challenge to particle detectors because of the higher amount of noise and uncorrelated signals. Higher noise levels lead to a more challenging particle reconstruction process by increasing the number of combinatorics to analyze and background signals to eliminate. On the other hand, increasing the beam intensity can provide physics …

Clostridioides Difficile Spore Production In Response To Antibiotic And Immune Stress, Adenrele Oludiran, Erin B. Purcell

College of Sciences Posters

Clostridioides (Clostridium) difficile, an anaerobic, spore-forming Gram-positive pathogenic bacterium, is a major cause of hospital-acquired infections and can persist as surface-attached biofilms for protection from antibiotic and immune stress. C. difficile can form biofilms as a single species or with other anaerobic intestinal bacteria. The environmental signals that cause individual cells to secrete toxins, form biofilms, or develop into spores that can spread the infection to new patients are unknown. In these studies, we investigate bacterial responses to different stress. Antimicrobial host-defense peptides (HDPs) produced by animal immune systems are promising candidates to develop novel therapies for bacterial infection …

Lattice Optics Optimization For Recirculatory Energy Recovery Linacs With Multi-Objective Optimization, Isurumali Neththikumara, Todd Satogata, Alex Bogacz, Ryan Bodenstein, Arthur Vandenhoeke

College of Sciences Posters

Beamline optics design for recirculatory linear accelerators requires special attention to suppress beam instabilities arising due to collective effects. The impact of these collective effects becomes more pronounced with the addition of energy recovery (ER) capability. Jefferson Lab’s multi-pass, multi-GeV ER proposal for the CEBAF accelerator, ER@CEBAF, is a 10- pass ER demonstration with low beam current. Tighter control of the beam parameters at lower energies is necessary to avoid beam break-up (BBU) instabilities, even with a small beam current. Optics optimizations require balancing both beta excursions at high-energy passes and overfocusing at low-energy passes. Here, we discuss an optics …

A Spatially And Temporally Second Order Method For Solving Parabolic Interface Problems, Kumudu Gamage, Yan Peng

College of Sciences Posters

Parabolic interface problems have many applications in physics and biology, such as hyperthermia treatment of cancer, underground water flow, and food engineering. Here we present an algorithm for solving two-dimensional parabolic interface problems where the coefficient and the forcing term have a discontinuity across the interface. The Crank-Nicolson scheme is used for time discretization, and the direct immersed interface method is used for spatial discretization. The proposed method is second order in both space and time for both solution and gradients in maximum norm.

Empirically Adjusted Weighted Ordered P-Values Method, Wimarsha Jayanetti, Sinjini Sikdar, N. Rao Chaganty

College of Sciences Posters

Recent advancements in high-throughput technologies have enabled simultaneous inference of thousands of genes. With the abundance of public databases, it is now possible to rapidly access the results of several genomic studies, each of which includes the significance testing results of a large number of genes. Researchers frequently aggregate genomic data from multiple studies in the form of a meta-analysis. Most traditional meta-analysis methods aim at combining summary results to find signals in at least one of the studies. However, often the goal is to identify genes that are differentially expressed in a consistent pattern across multiple studies. Recently, a …

Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun

College of Sciences Posters

Protein structure prediction produces atomic models from its amino acid sequence. Three-dimensional structures are important for understanding the function mechanism of proteins. Knowing the structure of a given protein is crucial in drug development design of novel enzymes. AlphaFold2 is a protein structure prediction tool with good performance in recent CASP competitions. Phenix is a tool for determination of a protein structure from a high-resolution 3D molecular image. Recent development of Phenix shows that it is capable to refine predicted models from AlphaFold2, specifically the poorly predicted regions, by incorporating information from the 3D image of the protein. The goal …

Physics-Informed Neural Networks (Pinns) For Dvcs Cross Sections, Manal Almaeen, Jake Grigsby, Joshua Hoskins, Brandon Kriesten, Yaohang Li, Huey-Wen Lin, Simonetta Liuti, Sorawich Maichum

College of Sciences Posters

We present a physics informed deep learning technique for Deeply Virtual Compton Scattering (DVCS) cross sections from an unpolarized proton target using both an unpolarized and polarized electron beam. Training a deep learning model typically requires a large size of data that might not always be available or possible to obtain. Alternatively, a deep learning model can be trained using additional knowledge gained by enforcing some physics constraints such as angular symmetries for better accuracy and generalization. By incorporating physics knowledge to our deep learning model, our framework shows precise predictions on the DVCS cross sections and better extrapolation on …

Medical Devices And Cybersecurity, Hilary Finch

School of Cybersecurity Posters

I begin by looking at the role of cybersecurity in the medical world. The healthcare industry adopted information technology quite quickly. While the advancement was obviously beneficial and necessary to keep up with an ever-growing demand, the healthcare industry did not place any kind of pointed focus on the security of their IT department, or the sensitive information housed therein.

When rapid advancements of technology outpaced the gradual advancement of hospital cybersecurity, security concerns became a difficult issue to control. There is a serious need for more advancements in hospital security. Each interconnected medical device has its own unique security …

Application Of U.S. Sanction Laws And Ransomware Payments, Trinity Woodbury

Cybersecurity Undergraduate Research Showcase

Ransomware is a major threat that widely affects individuals and organizations, including businesses. Ransomware victims face the situation of potentially paying ransom payments to threat actors, some of whom might be foreign-based criminals. Ransomware affects victims from all sectors and industries.

Cova Cci Undergrad Cyber Research, Nana Jeffrey

Cybersecurity Undergraduate Research Showcase

Is your digital assistant your worst enemy? Modern technology has impacted our lives in a positive way making tasks that were once time consuming become more convenient. For example a few years ago writing down your grocery list with a paper and pen was a norm, now with technology we have access to IoT devices such as smart fridges that can inform us on what items are low in stock, send a message to our digital assistants such as iOS Siri and Amazon's Alexa to remind us to buy those groceries. Although these digital assistants have helped make our daily …

How Online Platforms Are Used By Child Predators And What Are The Effective Preventive Measures?, Kayla Macpherson

Cybersecurity Undergraduate Research Showcase

As technology has evolved greatly in the twenty-first century alone, younger generations have had an opportunity to grow up with devices at their fingertips none have ever before. This accessibility has strengthened their ability of quick use, skill, and a strong feeling of comfort with using and having access to technology. There seems to be more children with access to the internet than there are without, but there is also an ongoing issue behind the screens.

A Super Fast Algorithm For Estimating Sample Entropy, Weifeng Liu, Ying Jiang, Yuesheng Xu

Mathematics & Statistics Faculty Publications

: Sample entropy, an approximation of the Kolmogorov entropy, was proposed to characterize complexity of a time series, which is essentially defined as − log(B/A), where B denotes the number of matched template pairs with length m and A denotes the number of matched template pairs with m + 1, for a predetermined positive integer m. It has been widely used to analyze physiological signals. As computing sample entropy is time consuming, the box-assisted, bucket-assisted, x-sort, assisted sliding box, and kd-tree-based algorithms were proposed to accelerate its computation. These algorithms require O(N²) or …

Circulation, Volume 27, No. 2, Center For Coastal Physical Oceanography, Old Dominion University

CCPO Circulation

Spring 2022 issue of CCPO Circulation featuring the article "Looking Back While Moving Forward," by Sönke Dangendorf.

Partial Muon Capture Rates In A = 3 And A = 6 Nuclei With Chiral Effective Field Theory, G. B. King, S. Pastore, M. Piarulli, Rocco Schiavilla

Physics Faculty Publications

Searches for neutrinoless double-β decay rates are crucial in addressing questions within fundamental symmetries and neutrino physics. The rates of these decays depend not only on unknown parameters associated with neutrinos, but also on nuclear properties. In order to reliably extract information about the neutrino, one needs an accurate treatment of the complex many-body dynamics of the nucleus. Neutrinoless double-β decays take place at momentum transfers on the order of 100MeV /c and require both nuclear electroweak vector and axial current matrix elements. Muon capture, a process in the same momentum transfer regime, has readily available experimental data to validate …

A Technological Skills Gap: What Can We Do About It?, Will Moore

Cybersecurity Undergraduate Research Showcase

In the last thirty years, education has transformed faster than ever before. As a society we have developed new classroom technologies that allow for better communication and access to more information than ever before. However, at the same time, education seems rockier than ever before. Several major companies, including Tesla, Apple, Google and Netflix, no longer require a college degree for employment, and many companies, such as Amazon, Google, and Microsoft, have begun programs to train their own employees in skills and create their own certification programs to help employees learn necessary skills (Akhtar, O’Donnell). Why do these major corporations …

Understanding The Mechanism Of Deep Learning Frameworks In Lesion Detection For Pathological Images With Breast Cancer, Wei-Wen Hsu, Chung-Hao Chen, Chang Hao, Yu-Ling Hou, Xiang Gao, Yun Shao, Xueli Zhang, Jingjing Wang, Tao He, Yanhong Tai

Electrical & Computer Engineering Faculty Publications

With the advances of scanning sensors and deep learning algorithms, computational pathology has drawn much attention in recent years and started to play an important role in the clinical workflow. Computer-aided detection (CADe) systems have been developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing misdetections. In this study, we conducted four experiments to demonstrate that the features learned by deep learning models are interpretable from a pathological perspective. In addition, classifiers such as the support vector machine (SVM) and random forests (RF) were used in experiments to replace the fully connected layers and decompose the end-to-end …

The Influence Of Particle Concentration And Bulk Characteristics On Polarized Oceanographic Lidar Measurements, Brian L. Collister, Richard C. Zimmerman, Charles I. Sukenik, William M. Balch, Victoria J. Hill

OES Faculty Publications

Oceanographic lidar measurements of the linear depolarization ratio, δ, contain information on the bulk characteristics of marine particles that could improve our ability to study ocean biogeochemistry. However, a scarcity of information on the polarized light-scattering properties of marine particles and the lack of a framework for separating single and multiple scattering effects on δ have hindered the development of polarization-based retrievals of bulk particle properties. To address these knowledge gaps, we made single scattering measurements of δ for several compositionally and morphologically distinct marine particle assemblages. We then used a bio-optical model to explore the influence of multiple …

Climate Change Could Make Allergy Season Longer, Odu Expert Says, Amber Kennedy

News Items

No abstract provided.

Odu’S Peter Bernath Participates In Study That Reveals Damage To Ozone Layer From Extreme Wildfires, Tiffany Whitfield

News Items

No abstract provided.

Empirically Derived Thermal Thresholds Of Four Coral Species Along The Red Sea Using A Portable And Standardized Experimental Approach, Nicolas R. Evensen, Christian R. Voolstra, Maoz Fine, Gabriela Perna, Carol Buitrago-López, Anny Cárdenas, Guilhem Banc-Prandi, Katherine Rowe, Daniel J. Barshis

Biological Sciences Faculty Publications

Global warming is causing an unprecedented loss of species and habitats worldwide. This is particularly apparent for tropical coral reefs, with an increasing number of reefs experiencing mass bleaching and mortality on an annual basis. As such, there is a growing need for a standardized experimental approach to rapidly assess the thermal limits of corals and predict the survival of coral species across reefs and regions. Using a portable experimental system, the Coral Bleaching Automated Stress System (CBASS), we conducted standardized 18 h acute thermal stress assays to quantitively determine the upper thermal limits of four coral species across the …

Diabetic Foot Exam System, Stephanie Trusty

Undergraduate Research Symposium

The diabetic foot exam system aims to perform certain aspects of the dermatological and musculoskeletal assessments that are typical to a 3-minute diabetic foot exam. Utilizing the RaspberryPi computer and camera module, the system seeks to capture a series of images of the patient’s foot. It then evaluates these images for calluses, blisters, and three types of deformities: claw toe deformities, hammertoe deformities, and bunions. This evaluation is performed using a trained TensorFlow image classification model, which categorizes the image as a callus, blister, or deformity. The system was tested using six different images: four callus images, a hammertoe deformity …

Covid-19 Classroom Occupancy Detection System, Stephanie Trusty

Undergraduate Research Symposium

The classroom occupancy detection system aims to limit the spread of COVID-19 and support mitigation efforts advised by national and international health organizations by enforcing social distancing in classroom environments. Utilizing the RaspberryPi computer and its compatible camera module, the system accomplishes this by capturing an overhead image of a classroom and assessing the image for violations. Here, violations are defined as the presence of adjacent occupied seats. As such, for an acceptable state to be detected, there must be at least one vacant seat between all students seated in the classroom. The system communicates the classroom’s state with two …

Objective Measure Of Working Memory Capacity Using Eye Movements, James Owens, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas G. Ashok, Sampath Jayarathna

Undergraduate Research Symposium

Human-autonomy teaming (HAT) has become an important area of research due to the autonomous systems being developed for different applications, such as remotely controlled aircraft. Many remotely controlled vehicles will be controlled by automated systems, with a human monitor that may be monitoring multiple vehicles simultaneously. The attention and working memory capacity of operators of remote-controlled vehicles must be maintained at appropriate levels during operation. However, there is currently no direct method of determining working memory capacity, which is important because it is a measure for how memory is being stored for a short term and interacting with long term …

Access To Nitrogen Heterocycles Via Borrowing Hydrogen Catalysis, Robert P. Reynolds, Kellen P. Mcguire, Conor T. Mccormick, Kyle M. Lambert

Undergraduate Research Symposium

Nitrogen heterocycles are ubiquitous motifs which occur as the core structure of several alkaloid natural products exhibiting inherent biological activity against an array of bacteria, fungi, viruses, and cancer cell lines. These azacycles serve as key synthetic building blocks for medicinal chemists to access more structurally complex and diverse compounds with tunable biological properties. A synthetic approach to these valuable motifs employing intramolecular borrowing hydrogen catalysis has been developed. The utility of the developed chemistry will be applied to synthetic efforts towards the recently isolated Cylicomorphins A-E.

Oxidation Of Thiols To Disulfides Using An Environmentally “Green” Organocatalyst And New Mechanistic Insights, Kosta V. Vlasakakis, Olivia M. White, Robert P. Reynolds, Shayne M. Weierbach, Shannon M. Weaver, Ramsey T. Ritter, Nishi H. Patel, Eric C. Hayes, Sydney Dunmire, Kyle M. Lambert

Undergraduate Research Symposium

The selective oxidation of thiols to disulfides is an area of great importance in the areas of materials and medicinal chemistry research. The production of polymers, rubber, pharmaceuticals, and the folding of proteins in biological systems all rely on the formation of disulfide bonds. Herein, we introduce a stoichiometric and electrocatalytic method for the oxidation of various pharmaceutically and biologically relevant thiols into their respective disulfides in more environmentally benign solvents such as water and alcohol solvents. The scope of the transformation was evaluated and a detailed mechanistic study involving control experiments, experimental kinetic studies, and computational investigations led to …

Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin

Undergraduate Research Symposium

Studying facial expressions can provide insight into the development of social skills in children and provide support to individuals with developmental disorders. In afflicted individuals, such as children with Autism Spectrum Disorder (ASD), atypical interpretations of facial expressions are well-documented. In computer vision, many popular and state-of-the-art deep learning architectures (VGG16, EfficientNet, ResNet, etc.) are readily available with pre-trained weights for general object recognition. Transfer learning utilizes these pre-trained models to improve generalization on a new task. In this project, transfer learning is implemented to leverage the pretrained model (general object recognition) on facial expression classification. Though this method, the …

Natural Phaeosphaeride A Derivatives Overcome Drug Resistance Of Tumor Cells And Modulate Signaling Pathways, Victoria Abzianidze, Natalia Moiseeva, Diana Suponina, Sofya Zakharenkova, Nadezhda Rogovskaya, Lidia Laletina, Alvin A. Holder, Denis Krivorotov, Alexander Bogachenkov, Alexander Garabadzhiu, Anton Ukolov, Vyacheslav Kosorukov

Chemistry & Biochemistry Faculty Publications

n the present study, natural phaeosphaeride A (PPA) derivatives are synthesized. Anti-tumor studies are carried out on the PC3, K562, HCT-116, THP-1, MCF-7, A549, NCI-H929, Jurkat, and RPMI8226 tumor cell lines, and on the human embryonic kidney (HEK293) cell line. All the compounds synthesized turned out to have better efficacy than PPA towards the tumor cell lines listed. Among them, three compounds exhibited an ability to overcome the drug resistance of tumor cells associated with the overexpression of the P-glycoprotein by modulating the work of this transporter. Luminex xMAP technology was used to assess the effect of five synthesized compounds …

4,6-O-Phenylethylidene Acetal Protected D-Glucosamine Carbamate-Based Gelators And Their Applications For Multi-Component Gels, Pooja Sharma, Guijun Wang

Chemistry & Biochemistry Faculty Publications

The self-assembly of carbohydrate-based low molecular weight gelators has led to useful advanced soft materials. The interactions of the gelators with various cations and anions are important in creating novel molecular architectures and expanding the scope of the small molecular gelators. In this study, a series of thirteen new C-2 carbamates of the 4,6-O-phenylethylidene acetalprotected D-glucosamine derivatives has been synthesized and characterized. These compounds are rationally designed from a common sugar template. All carbamates synthesized were found to be efficient gelators and three compounds are also hydrogelators. The resulting gels were characterized using optical microscopy, atomic force microscopy, …