Physical Sciences and Mathematics Commons^™

First Use Of A Longitudinally Polarized Target With Clas12, C. D. Keith, J. Brock, C. Carlin, T. Kageya, V. Lagerquist, J. Maxwell, P. Pandey

Physics Faculty Publications

Run Group C comprises eight experiments utilizing the CLAS12 detector system in Hall B at Jefferson Lab to study the multidimensional partonic structure of nucleons. The experiments scatter electrons from polarized protons and neutrons in samples of solid NH3 and ND3, dynamically polarized at a temperature of 1 K in a 5 T magnetic field. After a brief description of the target system, the current status of the target and preliminary results of its performance in the experiment are presented.

Measurement Of The Helicity Asymmetry E For The 𝛾p → P𝛑⁰ Reaction In The Resonance Region, C. W. Kim, N. Zachariou, M. Bashkanov, W. J. Briscoe, S. Fegan, V. L. Kashevarov, K. Nikonov, A. Sarantsev, A. Schmidt, I. I. Strakovsky, D. P. Watts, R. L. Workman, P. Achenbach, Z. Akbar, M. J. Amaryan, G. Angelini, W. R. Armstrong, H. Atac, L. Baashen, M. Zurek, Et Al., The Clas Collaboration

Physics Faculty Publications

The double-spin-polarization observable E for 𝛾^→ p^→ → p𝛑⁰ has been measured with the CEBAF Large Acceptance Spectrometer (CLAS) at photon beam energies E𝛾 from 0.367 to 2.173 GeV (corresponding to center-of-mass energies from 1.240 to 2.200 GeV) for pion center-of-mass angles, cos θ^c.m._𝛑⁰, between - 0.86 and 0.82. These new CLAS measurements cover a broader energy range and have smaller uncertainties compared to previous CBELSA data and provide an important independent check on systematics. These measurements are compared to predictions as well as new global fits from The George Washington University, Mainz, and Bonn-Gatchina …

Status And Future Plans For C³ R&D, Emilio A. Nanni, Martin Breidenbach, Zenghai Li, Caterina Vernieri, Faya Wang, Glen White, Mei Bai, Sergey Belomestnykh, Pushpalatha Bhat, Tim Barklow, William J. Berg, Valery Borzenets, John Byrd, Ankur Dhar, Ram C. Dhuley, Chris Doss, Joseph Duris, Auralee Edelen, Claudio Emma, Joseph Frisch, Annika Gabriel, Spenser Gessner, Carsten Hast, Chunguang Jing, Arkadiy Klebaner, Dongsung Kim, Anatoly Krasnykh, John Lewellen, Matthias Liepe, Michael Litos, Xueying Lu, Jared Maxon, David Montanari, Pietro Musumeci, Sergei Nagaitsev, Alireza Nassiri, Cho-Kuen Ng, David A. K. Othman, Marco Oriunno, Dennis Palmer, J. Ritchie Patterson, Michael E. Peskin, Thomas J. Peterson, John Power, Ji Qiang, James Rosenzweig, Vladimir Shiltsev, Muhammad Shumail, Evgenya Simakov, Emma Snively, Bruno Spataro, Sami Tantawi, Harry Van Der Graaf, Brandon Weatherford, Juhao Wu, Kent P. Wootton

Physics Faculty Publications

C³ is an opportunity to realize an e⁺e^- collider for the study of the Higgs boson at √s = 250 GeV, with a well defined upgrade path to 550 GeV while staying on the same short facility footprint [2,3]. C³ is based on a fundamentally new approach to normal conducting linear accelerators that achieves both high gradient and high efficiency at relatively low cost. Given the advanced state of linear collider designs, the key system that requires technical maturation for C³ is the main linac. This paper presents the staged approach towards a …

Understanding The Field And Frequency Dependence Of Rf Loss In Srf Cavities, Pashupati Dhakal, G. Ciovati, Alex V. Gurevich, Bashu D. Khanal

Physics Faculty Publications

SRF cavities subjected to heat treatment below 200 °C in the presence of nitrogen showed an improvement in quality factor while maintaining an accelerating gradient above 25 MV/m. Here, we report the rf performance of several single-cell superconducting radio frequency cavities with frequency ranging from 0.75 - 3.0 GHz subjected to low temperature heat treatment in nitrogen environment. The cavities were treated at temperature 120 - 175 oC for 24 - 48 hours in low partial pressure of ultra-pure nitrogen gas. The improvement in Q₀ with Q-rise was observed when nitrogen gas was injected ~300 °C during the furnace treatment. …

Numerical Calculations Of Superheating Field In Superconductors With Nanostructured Surfaces, M.R.P. Walive Pathiranage, A. Gurevich

Physics Faculty Publications

We re­port cal­cu­la­tions of a dc su­per­heat­ing field Hs in su­per­con­duc­tors with nanos­truc­tured sur­faces. Par­tic­u­larly, we per­formed nu­mer­i­cal sim­u­la­tions of the Ginzburg-Lan­dau (GL) equa­tions for a su­per­con­duc­tor with an in­ho­mo­ge­neous pro­file of im­pu­rity con­cen­tra­tion, a thin su­per­con­duct­ing layer on top of an­other su­per­con­duc­tor, and S-I-S mul­ti­lay­ers. The su­per­heat­ing field was cal­cu­lated tak­ing into ac­count the in­sta­bil­ity of the Meiss­ner state at a fi­nite wave­length along the sur­face de­pend­ing on the value of the GL pa­ra­me­ter. Sim­u­la­tions were done for the ma­te­ri­als pa­ra­me­ters of Nb and Nb₃Sn at dif­fer­ent val­ues of the GL pa­ra­me­ter and the mean free paths. We show …

Quantum Computations Of The O(3) Model Using Qumodes, R. Jha, Felix Ringer, G. Siopsis, Shane Thompson

Physics Faculty Publications

We express the discrete 1+1-dimensional O(3) non-linear sigma model (NLσM) in a form well-suited for the continuous variable approach to quantum computing. Within the Schwinger boson formulation, we need two qumodes (quantum-mechanical oscillators) at each lattice site. We envision that it might be possible to reach the scaling regime of this model and observe asymptotic freedom on near-term photonic quantum devices in the coming decade.

Methanol As An Eco-Environmental Alternative Fuel For Ships: A Case Study, Samar K. Sallam, Mohamed M. Elgohary, Ibrahim S. Seddiek

Journal of Marine Science and Technology

Global emissions of Green House Gases and air pollutants are significantly influenced by shipping. Diesel fuel use for energy production is primarily responsible for these emissions. The substitution of traditional marine diesel oil with methanol as a marine fuel is recommended in this study. Moreover, the methanol-diesel dual-fuel engine's environmental and financial benefits are investigated numerically. A cruise passenger ship named Costa Toscana has been evaluated as a case study. Based on the data, the suggested dual-fuel engine reduces emissions of CO2, NOx, SOx, and PM by 25.7%, 38.46%, 45%, and 45%, respectively, with a cost-effectiveness of 286.5, 6645, 268403.4, …

Rapid Species Identification Of Meretrix Lusoria And Three Other Meretrix Clams Using Pcr And Rflp Analysis Of The Mitochondrial Coii Gene., Chia-Hsuan Sung, Liang-Jong Wang, Chang-Wen Huang

Journal of Marine Science and Technology

Meretrix clams are among the most economically important species of bivalves in Eastern Asia and Taiwan. In the past, the identification of these hard clams depended on the shell morphology; however, species identification based on shell markings and shapes confuses the taxonomy of the Meretrix genus. The DNA molecular information is useful and can easily identify them accurately and quickly, especially the sequence of mitochondrial DNA. In this study, a PCR method to analyze the mitochondrial cytochrome c oxidase II (COII) gene was developed to rapidly identify of M. lusoria, M. lamarckii, M. lyrata and M. petechialis. Four different species …

An Mrf Model-Based Study On The Effect Of Fishes Upon The Characteristics Of Flow Field Of An Aquaculture Tank, Xian-Ying Shi, Zheng-Zheng Huang, Meng Li, Yinxin Zhou, Xiao-Zhong Ren, Hang-Fei Liu, Shu-Peng Du

Journal of Marine Science and Technology

The study aims to investigate the effect of fish movement on the flow field in the aquaculture tank of a recirculating water aquaculture system. Herein, based on the Navier-Stokes equations and the RNG k-ε turbulence model, the flow field in the aquaculture tank with fish movement was numerically simulated using the multiple reference frame (MRF) model and compared with the numerical simulation results of the fishless aquaculture tank. The results revealed that the overall mean flow velocity in the tank decreased significantly when the fish swam counter-currently with a fixed trajectory, and the overall mean flow velocity increased slightly when …

Research On The Collision Risk Of Ships Off Keelung Based On Ais Data, Shih-Tzung Chen, Ming-Feng Yang, Sheng-Long Kao, Mengru Tu, Jun-Yuan Kuo, Yen-Ting Chao, Huang-Kai Hsu

Journal of Marine Science and Technology

In previous literature, several computational methods have been proposed to analyze collision risks for vessels navigating at sea, most of which rely on the calculation of DCPA and TCPA between two vessels. However, this study adopts an enhanced version of the Vessel Conflict Ranking Operator (VCRO) to assess vessel collision risks. This approach not only considers the relative distance and relative velocity between two vessels but also takes their relative aspect into account. This methodology was applied to real-world vessels’ dynamic data collected through AIS. From a near-collision perspective, it identifies high-risk areas near Keelung water where commercial vessels and …

Microbial Community And Genome Structure In Coastal Seawater From A Commercial Port And Nearby Offshore Island In Northern Taiwan, Chi-Yu Shih, Ching-Hsiang Chin, Shiow-Yi Chen, Chun-Ru Hsu, Lee-Kuo Kan, Wen-Shyong Tzou

Journal of Marine Science and Technology

The pollution stemming from the use of petroleum by boats, the presence of deceased marine life, hazardous chemicals, and wastewater is a major issue in human-made commercial ports. This pollution poses a considerable challenge to the diverse organisms inhabiting the seawater. To comprehend the impact of this pollution on the microbiome, we conducted a study in which we collected surface water samples from a commercial port called Keelung Port, as well as a nearby offshore island known as Keelung Islet. These locations are situated in northern Taiwan, along the Northwestern Pacific Ocean. Through the use of whole-metagenome shotgun sequencing, we …

Tiny Language Models Enriched With Multimodal Knowledge From Multiplex Networks, Clayton Fields, Osama Natouf, Andrew Mcmains, Catherine Henry, Casey Kennington

Computer Science Faculty Publications and Presentations

Large transformer language models trained exclusively on massive quantities of text are now the standard in NLP. In addition to the impractical amounts of data used to train them, they require enormous computational resources for training. Furthermore, they lack the rich array of sensory information available to humans, who can learn language with much less exposure to language. In this study, performed for submission in the BabyLM challenge, we show that we can improve a small transformer model’s data efficiency by enriching its embeddings by swapping the learned word embeddings from a tiny transformer model with vectors extracted from a …

Exploring Transformers As Compact, Data-Efficient Language Models, Clayton Fields, Casey Kennington

Computer Science Faculty Publications and Presentations

Large scale transformer models, trained with massive datasets have become the standard in natural language processing. The huge size of most transformers make research with these models impossible for those with limited computational resources. Additionally, the enormous pretraining data requirements of transformers exclude pretraining them with many smaller datasets that might provide enlightening results. In this study, we show that transformers can be significantly reduced in size, with as few as 5.7 million parameters, and still retain most of their downstream capability. Further we show that transformer models can retain comparable results when trained on human-scale datasets, as few as …

Pacific Northwest Streamflow Data Landscape: A Report From The 2022 Streamflow Data Roundtables, Kendra E. Kaiser

Geosciences Faculty Publications and Presentations

This project was funded by the U.S. Geological Survey Northwest Climate Adaptation Science Center to catalog the location, temporal extent and purpose of non-USGS streamflow datasets. As part of this project, roundtable meetings convened local, state and federal agencies, and nonprofits to explore the complexity of gathering and integrating the identified datasets and identify issues surrounding data-sharing across organizations.

This report synthesizes discussions from each of the state roundtable discussions convened in the spring of 2022, and highlights common challenges and needs across the region. Additional information from organizations not able to be present at the meetings were added after …

Cyberinfrastructure Deployments On Public Research Clouds Enable Accessible Environmental Data Science Education, Tyler L. Mcintosh, Erick Verleye, Jennifer K. Balch, Megan E. Cattau, Nayani T. Ilangakoon, Nathan Korinek, R. Chelsea Nagy, James Sanovia, Edwin Skidmore, Tyson L. Swetnam, Ty Tuff, Nathan Quarderer, Carol A. Wessman

Human-Environment Systems Research Center Faculty Publications and Presentations

Modern science depends on computers, but not all scientists have access to the scale of computation they need. A digital divide separates scientists who accelerate their science using large cyberinfrastructure from those who do not, or who do not have access to the compute resources or learning opportunities to develop the skills needed. The exclusionary nature of the digital divide threatens equity and the future of innovation by leaving people out of the scientific process while over-amplifying the voices of a small group who have resources. However, there are potential solutions: recent advancements in public research cyberinfrastructure and resources developed …

Drivers Of Spatiotemporal Patterns Of Surface Water Inputs In A Catchment At The Rain-Snow Transition Zone Of The Water-Limited Western United States, E. Trujillo, J. Mcnamara

Geosciences Faculty Publications and Presentations

Spatial and temporal dynamics of rainfall and snowmelt (i.e., surface water inputs, SWI) control soil moisture, groundwater recharge, and streamflow at annual, seasonal, and event scales. In the rain-snow transition zone, comprising a large portion of the mountainous western United States, there is limited understanding of the sensitivity of spatiotemporal SWI dynamics across hydrologically variable water years (WYs). We modeled rainfall and snowpack dynamics in a small headwater catchment (1.8 km²) spanning the rain-snow transition in southwestern Idaho, USA, for two hydrologically distinct WYs (2011 and 2014). In wet WY 2011 and dry WY 2014, total precipitation drove …

Ethics Of Emerging Communication And Collaboration Technologies For Children, Juan Pablo Hourcade, Elizabeth Bonsignore, Tamara Clegg, Flannery Currin, Jerry A. Fails, Georgie Qiao Jin, Summer R. Schmuecker, Lana Yarosh

Computer Science Faculty Publications and Presentations

This SIG will provide child-computer interaction researchers and practitioners, as well as other interested CSCW attendees, an opportunity to discuss topics related to the ethics of emerging communication and collaboration technologies for children. The child-computer interaction community has conducted many discussions on ethical issues, including a recent SIG at CHI 2023. However, the angle of communication and collaboration has not been a focus, even though emerging technologies could affect these aspects in significant ways. Hence, there is a need to consider emerging technologies, such as extended reality, and how they may impact the way children communicate and collaborate in face-to-face, …

Social Networks Impact Flood Risk Mitigation Behavior: A Case Study Of Lidar Adoption In The Pacific Northwest, Us, Tara Pozzi, Vicken Hillis

Human-Environment Systems Research Center Faculty Publications and Presentations

Flood risk and damage are expected to increase in the Pacific Northwest due to climate change. Light Detection and Ranging (lidar) is a remote sensing technology that generates high-resolution topographic data and can therefore produce higher accuracy floodplain maps, an important tool that communities use to assess their flood risk. Despite the promise of lidar for flood risk mitigation, both the availability of lidar data and the use of that data when available varies across the U.S. What factors drive the adoption of technology, such as lidar, for flood risk management? How can we better promote the use of technologies …

A Machine Learning Approach To Classify Open Water And Ice Cover On Slave River Delta, Ida Moalemi

Theses and Dissertations (Comprehensive)

Seasonal temperature trend and ice phenology in Great Slave lake (GSL), are strongly influenced by warmer inflow from Slave river. The Slave river flows to GSL through Slave river delta (SRD), bringing a rise in temperature that triggers the ice break-up process of the lake. Slave river discharge is subject to multiple stressors including climate warming and upstream water activities, which in turn, directly affects the GSL break-up process. Consequently, monitoring the break-up process at SRD, where the river connects to the lake, serves as an indicator to better understand the cascading effects on GSL ice break-up. This research aims …

Distributed Spatial Data Sharing: A New Era In Sharing Spatial Data, Majid Hojati

Theses and Dissertations (Comprehensive)

The advancements in information and communications technology, including the widespread adoption of GPS-based sensors, improvements in computational data processing, and satellite imagery, have resulted in new data sources, stakeholders, and methods of producing, using, and sharing spatial data. Daily, vast amounts of data are produced by individuals interacting with digital content and through automated and semi-automated sensors deployed across the environment. A growing portion of this information contains geographic information directly or indirectly embedded within it. The widespread use of automated smart sensors and an increased variety of georeferenced media resulted in new individual data collectors. This raises a new …

Computational Investigation Of The Ionization Potential Of Lead Sulfide Quantum Dots, Jessica Beyer

Scripps Senior Theses

The purpose of this work was to determine the impact of quantum dot size on ionization potential and to determine how the presence of carbonyl-based ligands affect the ionization potential of lead sulfide quantum dot systems. Ionization potential (IP) is defined as the energy required to remove an electron from an atom, molecule, or material. IP helps scientists determine how reactive the material of interest is, which is crucial information when manufacturing nanomaterials. Accurate quantum chemical calculations of ionization potential are challenging due to the computational cost associated with the numerical solution of the Dyson equation. In this work, the …

Method Development For The Quantification Of Heavy Metals In Biological Matrices And Its Application To Clinical And Environmental Samples, Michelle Catherine Gende

Dissertations

A three-fold approach was taken to develop a method for the detection of heavy metals in different matrices and had to be performed sequentially. The first was to develop a method capable of quantifying lead in complex matrices by graphite furnace atomic absorption (GFAA). The developed method needed to meet specific analytical requirements, namely, to be robust, sensitive, and accurate. Initially, four different sample preparation methods were explored for the quantification of lead using Escherichia coli (E. coli) as a sample matrix. The sample preparation procedures attempted were acidic dilution, matrix modification, conventional heating digestion, and microwave assisted acid digestion …

Quantifying The Carbon Stored And Sequestered By The Trees On Pomona College’S Campus, Paola A. Giron-Carson

Scripps Senior Theses

We are experiencing a climate crisis that must be confronted with strategic mitigation. Pomona College contributes to the climate crisis through its emissions for which there is a baseline record. However there is no baseline record of the climate mitigation currently performed by the trees on Pomona’s campus through carbon storage. This study seeks to determine a current baseline quantity of carbon stored and sequestrated by Pomona’s trees as well as possible courses of climate mitigation for Pomona College to take. Initial information gathering was conducted through interviews with several stakeholders. This study was conducted using data collected prior to …

A Machine Learning Approach To Sector Based Market Efficiency, Angus Zuklie

Honors Projects

In economic circles, there is an idea that the increasing prevalence of algorithmic trading is improving the information efficiency of electronic stock markets. This project sought to test the above theory computationally. If an algorithm can accurately forecast near-term equity prices using historical data, there must be predictive information present in the data. Changes in the predictive accuracy of such algorithms should correlate with increasing or decreasing market efficiency.

By using advanced machine learning approaches, including dense neural networks, LSTM, and CNN models, I modified intra day predictive precision to act as a proxy for market efficiency. Allowing for the …

Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim

OUR Journal: ODU Undergraduate Research Journal

Object detection was introduced by researchers for face detection. Researchers explain how the detected face is divided into minor frames to be recognized by the algorithm. Due to COVID-19 and government regulations, many people face problems going to shopping centers and shop safely. It has been very hard for both the government and the people to manage social distancing. In our study, we developed a system using Raspberry Pi-4 that will detect the distance between people along with counting the number of distance and mask violations. An error message will appear on the screen in red, showing the total number …

Analysis Of Ab Initio Protein Structure Prediction Methods, Maytha Alshammari, Jing He

College of Sciences Posters

Protein structure prediction produces atomic models of three-dimensional structure of a protein from its amino acid sequence. Understanding the function mechanism of proteins requires knowledge of three-dimensional structures. When developing new enzymes and drugs, it's essential to understand the structure of the target protein. In this study, we analyze models predicted using two ab initio protein structure prediction methods, trRosetta and Quark. A set of thirty protein chains was used to evaluate the effectiveness of the methods. The thirty chains were collected from Protein Data Bank (June – November, 2020). The length and the relative position of the predicted secondary …

A Bootstrap Test For Informative Intra-Cluster Group Sizes In Clustered Data, Hasika K. Wickrama Senevirathne, Sandipan Dutta

College of Sciences Posters

Clustered data are frequently observed in various domains of scientific and social studies. In a typical clustered data, units within a cluster are correlated while units between different clusters are independent. An example of such clustered data can be found in dental studies where individuals are treated as clusters and the teeth in an individual are the units within a cluster. While analyzing such clustered data, it has been observed that the number of units present in a cluster can be informative in terms of being associated with the outcome from that cluster. Specifically, when the aim is to compare …

Hydrodynamics And Sediment Transport In The Tidally Influenced James River, Ollie Gilchrest, Rip Hale

The Graduate School Posters

The tidally influenced James River is an important economic, ecologic, and cultural resource for VA residents. Tidal rivers have been historically understudied, however they are critical transition zones, the dynamics of which have implications for freshwater supply and sediment trapping. Globally, estimates suggest that >30% of fluvial sediment is trapped in the tidal zone, the location and dynamics of which are actively changing due to sea level rise and saltwater encroachment. In addition, analysis of historical water levels on the James River has shown a decrease in the tidal range since 1940. The present study combines >1-year’s worth of hydrographic …

Organic Matter Content And Grain Size Analysis In Seagrass Sediments, Adriana Amrhein, Rip Hale

College of Sciences Posters

Anthropogenic stresses including increased water temperatures, decreased water quality, sea level rise, ocean acidification and sediment biogeochemical processes have caused a significant loss in seagrass meadow acreage. Seagrass meadows provide coastal protection from storms and recently have been emphasized for their importance in sequestering and storing “Blue Carbon” from the atmosphere and ocean. Seagrass meadows can trap this blue carbon in their sediment as organic carbon, and it can be stored for hundreds to thousands of years. Restoration efforts of seagrass meadows in the Virginia coast started in the 1990s and effects of increasing seagrass density can be observed in …

Dust Deposition To The Bermuda Region: A Comparison Of Estimates Using Seasonally-Resolved Measurements Of Aluminum In Water-Column, Aerosol, And Rain Samples, Tara Williams, Peter Sedwick, Bettina Sohst, Joe Resing, Kristen Buck, Salvatore Caprara, Rod Johnson, Dan Ohnemus, Ben Twining, Alessandro Tagliabue

College of Sciences Posters

Dust deposition is a major source of bioactive trace elements to the surface ocean, yet this flux remains difficult to constrain. Previously, time-averaged dust flux has been estimated using surface ocean dissolved aluminum (DAl) concentrations, assumed values for aerosol aluminum solubility (%Al_S), and the residence time of DAl in the surface mixed layer (SML). We apply this method to estimate dust deposition in the Bermuda Atlantic Time-series Study (BATS) region using water-column DAl data from cruises in 2019, which is compared with direct flux estimates from contemporaneous measurements of aluminum in aerosols and rain collected on Bermuda. Seasonal …