Digital Commons Network^™

Superconducting Non-Elliptical Cavities (Tem Cavity Designs), Subashini De Silva

Physics Faculty Publications

This lecture will present fundamental of RF to accelerate or reflect beams. The lecture will cover the electrical design method of the SRF high/medium/low beta cavities. The difference in the cavity design between TM mode and TE will be emphasized.

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.

Deeply Virtual Compton Scattering Using A Positron Beam In Hall C, V. Berdnikov, A. Camsonne, M. Carmignotto, R. Ent, J. Grames, D. Higinbotham, C. Keppel, M. Mccaughan, P. Paremuzyan, B. Sawatzky, A. Somov, B. Wojtsekhowski, S. Wood, C. Zorn, R. Dupré, M. Ehrhart, M. Guidal, S. Habet, A. Hobart, D. Marchand, C. Muñoz Camacho, S. Niccolai, E. Voutier, M. Mazouz, T. Horn, G. Kalicy, M. Muhoza, I. Pegg, R. Trotta, A. Asaturyan, A. Mkrtchyan, H. Mkrtchyan, V. Tadevosyan, H. Voskanyan, S. Zhamkochyan, M. Amaryan, C. Hyde, M. Kerver, J. Murphy, J. Roche, P. Markowitz, A. Afanasev, W. J. Briscoe, I. Strakovsky, M. Boer, T. Forest, J.R.M. Annand, D. J. Hamilton, B. Mckinnon, D. Day, M. A. I. Fernando, D. Keller, R. Rondon, J. Zhang, K. Brinkmann, S. Diehl, R. Novotny, P. Gueye, V. Bellini, D. Dutta, E. Kinney, P. Nadel-Turonski, G. Niculescu, S. Sirca, I. Albayrak, M. Defurne, Z. Huang, Z. Ye

Physics Faculty Publications

We propose to use the High Momentum Spectrometer of Hall C combined with Neutral Particle Spectrometer (NPS) to perform high precision measurement of the deeply virtual compton scattering (DVCS) cross section using a beam of positrons. The combination of measurements with oppositely charged incident beams is the only unambiguous way to disentange the contribution of the DVCS² term in the photon electroproduction cross section from its interference with the Bethe-Heitler amplitude. This provies a stronger way to constrain the Generalized Parton Distributions of the nucleon. A range of kinematics accessible with an 11 GeV beam off an unpolarized proton target …

Development Of A Novel Readout Concept For An Eic Dirc, K. Dehmelt, A. Deshpande, R. Dzhygadlo, T. K. Hemmick, Md. I. Hossain, C. E. Hyde, Y. Ilieva, G. Kalicy, P. Nadel-Turonski, C. Schwarz, J. Schwiening, N. Shankman, J. Stevens, N. Wickramaarachchi, C. Woody

Physics Faculty Publications

The objective of this program is to pursue opportunities to reduce the material budget and the cost of the DIRC counter for the EIC, without loss of performance, by investigating fundamental DIRC performance limits and new optical configurations. The barrel high-performance DIRC (hpDIRC) has been adopted for the ePIC detector and is an attractive solution for Detector-2. In this program, we study the DIRC performance with an innovative optical configuration consisting of narrow, thin radiator bars coupled to wide plates, focusing lenses, and small expansion volume prisms. The outcomes of these studies would be applicable to both ePIC and, in …

Analytic And Numerical Calculation Of Collider Luminosity With Crab Dynamics, H. Huang, T. Satogata, Y. Zhang, Y. Roblin, F. Lin, S. Zhao

Physics Faculty Publications

For an integral part of electron-ion collider (EIC) design, the crab crossing scheme provides a head-on collision for beams with a nonzero crossing angle. Recently we provided a framework for accurate numerical simulations of beam-beam effects with crabbing crossing dynamics. The framework was implemented in a simulation code package named “CASA BeamBeam”. We offer com-prehensive formulas for calculation of collider luminosity for various cases in the code package. The luminosity calculation module of CASA Beam-Beam now includes the hourglass effect, the beam-tilt effects and the beam offset effect. The benchmarking results show good agreement between the numerical calculation and analytic …

The Post-Shock Nonequilibrium Relaxation In A Hypersonic Plasma Flow Involving Reflection Off A Thermal Discontinuity, Anna Markhotok

Physics Faculty Publications

The evolution in the post shock nonequilibrium relaxation in a hypersonic plasma flow was investigated during a shock’s reflection off a thermal discontinuity. Within a transitional period, the relaxation zone parameters past both, the reflected and transmitted waves, evolve differently compared to that in the incident wave. In a numerical example for the non-dissociating N₂ gas heated to 5000 K/10,000 K across the interface and M = 3.5, the relaxation time for the transmitted wave is up to 50% shorter and the relaxation depth for both waves is significantly reduced, thus resulting in a weakened wave structure. The …

Quantum Efficiency Enhancement In Simulated Nanostructured Negative Electron Affinity Gaas Photocathodes, Md Aziz Ar Rahman, Shukui Zhang, Hani E. Elsayed-Ali

Physics Faculty Publications

Nanostructured negative electron affinity GaAs photocathodes for a polarized electron source are studied using finite difference time domain optical simulation. The structures studied are nanosquare columns, truncated nanocones, and truncated nanopyramids. Mie-type resonances in the 700–800 nm waveband, suitable for generation of polarized electrons, are identified. At resonance wavelengths, the nanostructures can absorb up to 99% of the incident light. For nanosquare columns and truncated nanocones, the maximum quantum efficiency (QE) at 780 nm obtained from simulation is 27%, whereas for simulated nanopyramids, the QE is ∼21%. The high photocathode quantum efficiency is due to the shift of Mie resonance …

Oscillating Icebergs, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Exploding Haystacks, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Modeling The Spread Of Covid-19 In Spatio-Temporal Context, S.H. Sathish Indika, Norou Diawara, Hueiwang Anna Jeng, Bridget D. Giles, Dilini S.K. Gamage

Mathematics & Statistics Faculty Publications

This study aims to use data provided by the Virginia Department of Public Health to illustrate the changes in trends of the total cases in COVID-19 since they were first recorded in the state. Each of the 93 counties in the state has its COVID-19 dashboard to help inform decision makers and the public of spatial and temporal counts of total cases. Our analysis shows the differences in the relative spread between the counties and compares the evolution in time using Bayesian conditional autoregressive framework. The models are built under the Markov Chain Monte Carlo method and Moran spatial correlations. …

Another Angle On Perspective: Solutions For Fermi Questions, May 2023, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Not Your Typical Tower Of Sauron, John Adam

Mathematics & Statistics Faculty Publications

The picture is of the tapering Chester Shot Tower, located in Chester, England. It was built in 1799 for the manufacture of lead shot for use in the Napoleonic Wars. Molten lead was poured through a sieve at the top of the tower, with the tiny droplets forming perfect spheres during the fall; these were then cooled in a vat of water at the base. This process was less labor intensive than an earlier method using molds. It is the oldest of the three remaining shot towers in the UK.

Question 1: Using the parked van at the base, estimate …

Adjusting For Gene-Specific Covariates To Improve Rna-Seq Analysis, Hyeongseon Jeon, Kyu-Sang Lim, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

Summary

This paper suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by employing two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning …

Dental Floss, Calculus, And Jail, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Dental Floss, Calculus, And Jail: Solutions For Fermi Questions, October 2023, John Adam

Mathematics & Statistics Faculty Publications

No abstract provided.

Jet Noise Reduction: A Fresh Start, Christopher K. Tam, Fang Q. Hu

Mathematics & Statistics Faculty Publications

Attempts to reduce jet noise began some 70 years ago. In the literature, there have been many publications written on this topic. By now, it is common knowledge that jet noise consists of a number of components. They possess different spectral and radiation characteristics and are generated by different mechanisms. It appears then that one may aim at the suppression of the noise of a single component instead of trying to reduce jet noise overall. The objective of the present project is to reduce large turbulence structures noise. It is the most dominant noise component radiating in the downstream direction. …

Poisson Regression Model With Application To Wastewater Surveillance Under A Threshold Linear Mixed Model For Covid-19 Sensitivity Rates, Norou Diawara, Hueiwang Anna Jeng, Kyle Curtis, Raul Gonzalez, Nancy Welch, Cynthia Jackson, Rekha Singh, David Jurgens, Sasanka Adikari, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

A Threshold Linear Mixed Model (TLMM) has been developed to identify specific thresholds based on wastewater SARS-CoV-2 viral concentrations, which reflect COVID-19 cases. The thresholds can guide decisions regarding public health responses and prevention measures. To assess the practical application of TLMM, a simple simulation was conducted using a sample size of 100 and 500 replications. The simulation allowed for comparing parameter estimators by assessing bias and standard deviation and the root of the mean square error. The model and estimation procedures were applied to reported wastewater and clinic data to test its application for real-world scenarios. Our results demonstrated …

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Readiness For Transfer: A Mixed-Methods Study On Icu Transfers Of Care, Soo-Hoon Lee, Clarice Wee, Phillip Phan, Yanika Kowitlawakul, Chee-Kiat Tan, Amartya Mukhopadhyay

Management Faculty Publications

Objective Past studies on intensive care unit (ICU) patient transfers compare the efficacy of using standardised checklists against unstructured communications. Less studied are the experiences of clinicians in enacting bidirectional (send/receive) transfers. This study reports on the differences in protocols and data elements between receiving and sending transfers in the ICU, and the elements constituting readiness for transfer.

Methods Mixed-methods study of a 574-bed general hospital in Singapore with a 74-bed ICU for surgical and medical patients. Six focus group discussions (FGDs) with 34 clinicians comprising 15 residents and 19 nurses, followed by a structured questionnaire survey of 140 clinicians …

Robustembed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training, Javad Asl, Eduardo Blanco, Daniel Takabi

School of Cybersecurity Faculty Publications

Pre-trained language models (PLMs) have demonstrated their exceptional performance across a wide range of natural language processing tasks. The utilization of PLM-based sentence embeddings enables the generation of contextual representations that capture rich semantic information. However, despite their success with unseen samples, current PLM-based representations suffer from poor robustness in adversarial scenarios. In this paper, we propose RobustEmbed, a self-supervised sentence embedding framework that enhances both generalization and robustness in various text representation tasks and against diverse adversarial attacks. By generating high-risk adversarial perturbations to promote higher invariance in the embedding space and leveraging the perturbation within a novel contrastive …

An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas

School of Cybersecurity Faculty Publications

Consumer Internet of Things (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem, like a smart home. Due to security and privacy concerns, blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their machine learning (ML) models using end-user data. Federated learning (FL) uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralized aggregator to safeguard the ecosystem. However, blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research introduces a novel architecture, emphasizing …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Hashes Are Not Suitable To Verify Fixity Of The Public Archived Web, Mohamed Aturban, Martin Klein, Herbert Van De Sompel, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Web archives, such as the Internet Archive, preserve the web and allow access to prior states of web pages. We implicitly trust their versions of archived pages, but as their role moves from preserving curios of the past to facilitating present day adjudication, we are concerned with verifying the fixity of archived web pages, or mementos, to ensure they have always remained unaltered. A widely used technique in digital preservation to verify the fixity of an archived resource is to periodically compute a cryptographic hash value on a resource and then compare it with a previous hash value. If the …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Comparison Of Physics-Based Deformable Registration Methods For Image-Guided Neurosurgery, Nikos Chrisochoides, Yixun Liu, Fotis Drakopoulos, Andriy Kot, Panos Foteinos, Christos Tsolakis, Emmanuel Billias, Olivier Clatz, Nicholas Ayache, Andrey Fedorov, Alex Golby, Peter Black, Ron Kikinis

Computer Science Faculty Publications

This paper compares three finite element-based methods used in a physics-based non-rigid registration approach and reports on the progress made over the last 15 years. Large brain shifts caused by brain tumor removal affect registration accuracy by creating point and element outliers. A combination of approximation- and geometry-based point and element outlier rejection improves the rigid registration error by 2.5 mm and meets the real-time constraints (4 min). In addition, the paper raises several questions and presents two open problems for the robust estimation and improvement of registration error in the presence of outliers due to sparse, noisy, and incomplete …

Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen

Computer Science Faculty Publications

Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million …