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2021

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Articles 26281 - 26310 of 27884

Full-Text Articles in Physical Sciences and Mathematics

Eic Crab Cavity Multipole Analysis, Q. Wu, Y. Luo, B. Xiao, Subashini De Silva, J. A. Mitchell Jan 2021

Eic Crab Cavity Multipole Analysis, Q. Wu, Y. Luo, B. Xiao, Subashini De Silva, J. A. Mitchell

Physics Faculty Publications

Crab cavities are specialized RF devices designed for colliders targeting high luminosities. It is a straightforward solution to retrieve head-on collision with crossing angle existing to fast separate both beams after collision. The Electron Ion Collider (EIC) has a crossing angle of 25 mrad, and will use local crabbing to minimize the dynamic aperture requirement throughout the rings. The current crab cavity design for the EIC lacks axial symmetry. Therefore, their higher order components of the fundamental deflecting mode have a potential of affecting the long-term beam stability. We present here the multipole analysis and preliminary particle tracking results from …

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Hom Damper Design For Bnl Eic 197mhz Crab Cavity, Binping Xiao, Jean R. Delayen, Subashini U. De Silva, Z. Li, R. Rimmer, S. Verdu-Andres, Qiong Wu Jan 2021

Hom Damper Design For Bnl Eic 197mhz Crab Cavity, Binping Xiao, Jean R. Delayen, Subashini U. De Silva, Z. Li, R. Rimmer, S. Verdu-Andres, Qiong Wu

Physics Faculty Publications

The interaction region (IR) crab cavity system is a special RF system to compensate the loss of luminosity due to a 25 mrad crossing angle at the interaction point (IP) for Brookhaven National Lab electron ion collider (BNL EIC). There will be six crab cavities, with four 197 MHz crab cavities and two 394 MHz crab cavities, installed on each side of the IP in the proton/ion ring, and one 394 MHz crab cavity on each side of the IP in the electron ring. Both rings share identical 394 MHz crab cavity design to minimize the cost and risk in …

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Measurements Of Magnetic Field Penetration In Superconducting Materials For Srf Cavities, Iresha Harshani Senevirathne, Alex Gurevich, Jean R. Delayen, A.-M. Valente-Feliciano Jan 2021

Measurements Of Magnetic Field Penetration In Superconducting Materials For Srf Cavities, Iresha Harshani Senevirathne, Alex Gurevich, Jean R. Delayen, A.-M. Valente-Feliciano

Physics Faculty Publications

Superconducting radiofrequency (SRF) cavities used in particle accelerators operate in the Meissner state. To achieve high accelerating gradients, the cavity material should stay in the Meissner state under high RF magnetic field without penetration of vortices through the cavity wall. The field onset of flux penetration into a superconductor is an important parameter of merit of alternative superconducting materials other than Nb which can enhance the performance of SRF cavities. There is a need for a simple and efficient technique to measure the onset of field penetration into a superconductor directly. We have developed a Hall probe experimental setup for …

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A Proposed Beam-Beam Test Facility Combine, E. Nissen, Geoffrey Krafft, Jean Delayen Jan 2021

A Proposed Beam-Beam Test Facility Combine, E. Nissen, Geoffrey Krafft, Jean Delayen

Physics Faculty Publications

The COmpact Machine for Beam-beam Interactions in Non-Equilibrium systems (COMBINE) is a proposed, dedicated, beam-beam test facility. The base design would make use of a pair of identical octagonal rings (2.5 meters per side) one rotated 180 degrees from the other, meeting at their common interaction point. These would be fed by an electron gun producing up to 125 keV electrons. The low energy will allow for beam-beam tune shifts commensurate with existing colliders, some linac-ring type systems, and will also allow for an exploration of the predicted effects of gear-changing, which would be performed using a variable pathlength scheme. …

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A Hard X-Ray Compton Source At Cbeta, K.E. Deitrick, J. Crone, C. Franck, G.H. Hoffstaetter, Geoffrey A. Krafft, B. D. Muratori, H. L. Owen, Balša Terzić, P. H. Williams Jan 2021

A Hard X-Ray Compton Source At Cbeta, K.E. Deitrick, J. Crone, C. Franck, G.H. Hoffstaetter, Geoffrey A. Krafft, B. D. Muratori, H. L. Owen, Balša Terzić, P. H. Williams

Physics Faculty Publications

Inverse Compton scattering (ICS) holds the potential for future high flux, narrow bandwidth x-ray sources driven by high quality, high repetition rate electron beams. CBETA, the Cornell-BNL Energy recovery linac (ERL) Test Accelerator, is the world’s first superconducting radiofrequency multi-turn ERL, with a maximum energy of 150 MeV, capable of ICS production of x-rays above 400 keV. We present an update on the bypass design and anticipated parameters of a compact ICS source at CBETA. X-ray parameters from the CBETA ICS are compared to those of leading synchrotron radiation facilities, demonstrating that, above a few hundred keV, photon beams produced …

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Beam Dynamics Study In A Dual Energy Storage Ring For Ion Beam Cooling*, B. Dhital, Y. S. Derbenev, D. Douglas, A. Hutton, Geoffrey A. Krafft, F. Lin, V. S. Morozov, Y. Zhang Jan 2021

Beam Dynamics Study In A Dual Energy Storage Ring For Ion Beam Cooling*, B. Dhital, Y. S. Derbenev, D. Douglas, A. Hutton, Geoffrey A. Krafft, F. Lin, V. S. Morozov, Y. Zhang

Physics Faculty Publications

A dual energy storage ring designed for beam cooling consists of two closed rings with significantly different energies: the cooling and damping rings. These two rings are connected by an energy recovering superconducting RF structure that provides the necessary energy difference. In our design, the RF acceleration has a main linac and harmonic cavities both running at crest that at first accelerates the beam from low energy E_{L} to high energy E_{H} and then decelerates the beam from E_{H} to E_{L} in the next pass. The purpose of the harmonic cavities is to extend the bunch length in a dual …

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Effect Of A Mean Free Path On Nonlinear Losses Of Trapped Vortices Driven By A Rf Field, Manula Randhika Pathirana Walive Pathiranage, Alex Gurevich Jan 2021

Effect Of A Mean Free Path On Nonlinear Losses Of Trapped Vortices Driven By A Rf Field, Manula Randhika Pathirana Walive Pathiranage, Alex Gurevich

Physics Faculty Publications

We report extensive numerical simulations on nonlinear dynamics of a trapped elastic vortex under rf field, and its dependence on electron mean free path li. Our calculations of the field-dependent residual surface resistance Ri(H) take into account the vortex line tension, the linear Bardeen-Stephen viscous drag and random distributions of pinning centers. We showed that Ri(H) decreases significantly at small fields as the material gets dirtier while showing field independent behavior at higher fields for clean and dirty limit. At low frequencies Ri(H) increases smoothly with the field amplitude at small H and levels off at higher fields. The mean …

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Tubular J-Aggregates Of Cyanine Dyes In The Near-Infrared, Austin Bailey, Arundhati Deshmukh, Timothy Luke Atallah, Ulugbek Barotov, Monica Pengshung Jan 2021

Tubular J-Aggregates Of Cyanine Dyes In The Near-Infrared, Austin Bailey, Arundhati Deshmukh, Timothy Luke Atallah, Ulugbek Barotov, Monica Pengshung

Faculty Publications

No abstract provided.

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Characterizing Visual Programming Approaches For End-User Developers: A Systematic Review, Mohammad Amin Kuhail, Shahbano Farooq, Rawad Hammad, Mohammed Bahja Jan 2021

Characterizing Visual Programming Approaches For End-User Developers: A Systematic Review, Mohammad Amin Kuhail, Shahbano Farooq, Rawad Hammad, Mohammed Bahja

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Recently many researches have explored the potential of visual programming in robotics, the Internet of Things (IoT), and education. However, there is a lack of studies that analyze the recent evidence-based visual programming approaches that are applied in several domains. This study presents a systematic review to understand, compare, and reflect on recent visual programming approaches using twelve dimensions: visual programming classification, interaction style, target users, domain, platform, empirical evaluation type, test participants' type, number of test participants, test participants' programming skills, evaluation methods, evaluation measures, and accessibility of visual programming tools. The results show that most of the selected …

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Explicit Tight Frames For Simulating A New System Of Fractional Nonlinear Partial Differential Equation Model Of Alzheimer Disease, Mutaz Mohammad, Alexander Trounev Jan 2021

Explicit Tight Frames For Simulating A New System Of Fractional Nonlinear Partial Differential Equation Model Of Alzheimer Disease, Mutaz Mohammad, Alexander Trounev

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This paper is devoted to develop a new mathematical model for Alzheimer disease based on a system of fractional-order partial differential equations. The system of Alzheimer disease includes neurons, astrocytes, microglias and peripheral macrophages, as well as amyloid β aggregation and hyperphosphorylated tau proteins. We consider the Caputo fractional derivative definition to analyze the formulated system by simulating the effect of drugs that either failed or currently in clinical trials. To simulate the model, we use tight frame (framelet) systems generated using the unitaryand oblique extension principle. According to the simulation results, and based on using such new direction of …

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Files Cryptography Based On One-Time Pad Algorithm, Ahmad Mohamad Al-Smadi, Ahmad Al-Smadi, Roba Mahmoud Ali Aloglah, Nisrein Abu-Darwish, Ahed Abugabah Jan 2021

Files Cryptography Based On One-Time Pad Algorithm, Ahmad Mohamad Al-Smadi, Ahmad Al-Smadi, Roba Mahmoud Ali Aloglah, Nisrein Abu-Darwish, Ahed Abugabah

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The Vernam-cipher is known as a one-time pad of algorithm that is an unbreakable algorithm because it uses a typically random key equal to the length of data to be coded, and a component of the text is encrypted with an element of the encryption key. In this paper, we propose a novel technique to overcome the obstacles that hinder the use of the Vernam algorithm. First, the Vernam and advance encryption standard AES algorithms are used to encrypt the data as well as to hide the encryption key; Second, a password is placed on the file because of the …

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Convolutional Neural Network Based Vehicle Classification In Adverse Illuminous Conditions For Intelligent Transportation Systems, Muhammad Atif Butt, Asad Masood Khattak, Sarmad Shafique, Bashir Hayat, Saima Abid, Ki Il Kim, Muhammad Waqas Ayub, Ahthasham Sajid, Awais Adnan Jan 2021

Convolutional Neural Network Based Vehicle Classification In Adverse Illuminous Conditions For Intelligent Transportation Systems, Muhammad Atif Butt, Asad Masood Khattak, Sarmad Shafique, Bashir Hayat, Saima Abid, Ki Il Kim, Muhammad Waqas Ayub, Ahthasham Sajid, Awais Adnan

All Works

© 2021 Muhammad Atif Butt et al. In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed to incorporate the above-mentioned issues in traditional methods. However, convolutional neural networks require piles of …

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Autobiographical Meaning Making Protects The Sense Of Self-Continuity Past Forced Migration, Christin Camia, Rida Zafar Jan 2021

Autobiographical Meaning Making Protects The Sense Of Self-Continuity Past Forced Migration, Christin Camia, Rida Zafar

All Works

Forced migration changes people’s lives and their sense of self-continuity fundamentally. One memory-based mechanism to protect the sense of self-continuity and psychological well-being is autobiographical meaning making, enabling individuals to explain change in personality and life by connecting personal experiences and other distant parts of life to the self and its development. Aiming to replicate and extend prior research, the current study investigated whether autobiographical meaning making has the potential to support the sense of self-continuity in refugees. We therefore collected life narratives from 31 refugees that were coded for autobiographical reasoning, selfevent connections, and global narrative coherence. In line …

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A Comprehensive Review On Medical Diagnosis Using Machine Learning, Kaustubh Arun Bhavsar, Ahed Abugabah, Jimmy Singla, Ahmad Ali Alzubi, Ali Kashif Bashir, Nikita Jan 2021

A Comprehensive Review On Medical Diagnosis Using Machine Learning, Kaustubh Arun Bhavsar, Ahed Abugabah, Jimmy Singla, Ahmad Ali Alzubi, Ali Kashif Bashir, Nikita

All Works

The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high accuracy. The use of machine …

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Smart Pansharpening Approach Using Kernel-Based Image Filtering, Ahmad A.L. Smadi, Shuyuan Yang, Atif Mehmood, Ahed Abugabah, Min Wang, Muzaffar Bashir Jan 2021

Smart Pansharpening Approach Using Kernel-Based Image Filtering, Ahmad A.L. Smadi, Shuyuan Yang, Atif Mehmood, Ahed Abugabah, Min Wang, Muzaffar Bashir

All Works

Remote sensing image fusion plays important roles in numerous applications, including monitoring, metrology, and agriculture. Image fusion gathers essential information from several image sources and consolidates them into a single image called a fused image. The fused image involves relevant data, and it is more informative than any other images extracted from one source. This study proposed a pansharpening technique based on image filtering utilising a bilateral filter to generate high-frequency details from panchromatic image. The various types of side window guided filters are employed to enhance the multispectral band from panchromatic image and then used these filters to adjust …

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The Impact Of Arabic Part Of Speech Tagging On Sentiment Analysis: A New Corpus And Deep Learning Approach, Abdul Munem Nerabie, Manar Alkhatib, Sujith Samuel Mathew, May El Barachi, Farhad Oroumchian Jan 2021

The Impact Of Arabic Part Of Speech Tagging On Sentiment Analysis: A New Corpus And Deep Learning Approach, Abdul Munem Nerabie, Manar Alkhatib, Sujith Samuel Mathew, May El Barachi, Farhad Oroumchian

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Sentiment Analysis is achieved by using Natural Language Processing (NLP) techniques and finds wide applications in analyzing social media content to determine people’s opinions, attitudes, and emotions toward entities, individuals, issues, events, or topics. The accuracy of sentiment analysis depends on automatic Part-of-Speech (PoS) tagging which is required to label words according to grammatical categories. The challenge of analyzing the Arabic language has found considerable research interest, but now the challenge is amplified with the addition of social media dialects. While numerous morphological analyzers and PoS taggers were proposed for Modern Standard Arabic (MSA), we are now witnessing an increased …

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Variational Autoencoders And Wasserstein Generative Adversarial Networks For Improving The Anti-Money Laundering Process, Zhiyuan Chen, Waleed Soliman, Amril Nazir, Mohammad Shorfuzzaman Jan 2021

Variational Autoencoders And Wasserstein Generative Adversarial Networks For Improving The Anti-Money Laundering Process, Zhiyuan Chen, Waleed Soliman, Amril Nazir, Mohammad Shorfuzzaman

All Works

There has been much recent work on fraud and Anti Money Laundering (AML) detection using machine learning techniques. However, most algorithms are based on supervised techniques. Studies show that supervised techniques often have the limitation of not adapting well to new irregular fraud patterns when the dataset is highly imbalanced. Instead, unsupervised learning can have a better capability to find anomalous and irregular patterns in new transaction. Despite this, unsupervised techniques also have the disadvantage of not being able to give state-of-the-art detection results. We propose a suite of unsupervised and deep learning techniques to implement an anti-money laundering and …

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Rfid Adaption In Healthcare Organizations: An Integrative Framework, Ahed Abugabah, Louis Sanzogni, Luke Houghton, Ahmad Ali Alzubi, Alaa Abuqabbeh Jan 2021

Rfid Adaption In Healthcare Organizations: An Integrative Framework, Ahed Abugabah, Louis Sanzogni, Luke Houghton, Ahmad Ali Alzubi, Alaa Abuqabbeh

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Radio frequency identification (RFID), also known as electronic label technology, is a non-contact automated identification technology that recognizes the target object and extracts relevant data and critical characteristics using radio frequency signals. Medical equipment information management is an important part of the construction of a modern hospital, as it is linked to the degree of diagnosis and care, as well as the hospital's benefits and growth. The aim of this study is to create an integrated view of a theoretical framework to identify factors that influence RFID adoption in healthcare, as well as to conduct an empirical review of the …

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Efficientnet-Lite And Hybrid Cnn-Knn Implementation For Facial Expression Recognition On Raspberry Pi, Mohd Nadhir Ab Wahab, Anthony Tan Zhen Ren, Amril Nazir, Mohd Halim Mohd Noor, Muhammad Firdaus Akbar, Ahmad Sufril Azlan Mohamed Jan 2021

Efficientnet-Lite And Hybrid Cnn-Knn Implementation For Facial Expression Recognition On Raspberry Pi, Mohd Nadhir Ab Wahab, Anthony Tan Zhen Ren, Amril Nazir, Mohd Halim Mohd Noor, Muhammad Firdaus Akbar, Ahmad Sufril Azlan Mohamed

All Works

Facial expression recognition (FER) is the task of determining a person’s current emotion. It plays an important role in healthcare, marketing, and counselling. With the advancement in deep learning algorithms like Convolutional Neural Network (CNN), the system’s accuracy is improving. A hybrid CNN and k-Nearest Neighbour (KNN) model can improve FER’s accuracy. This paper presents a hybrid CNN-KNN model for FER on the Raspberry Pi 4, where we use CNN for feature extraction. Subsequently, the KNN performs expression recognition. We use the transfer learning technique to build our system with an EfficientNet-Lite model. The hybrid model we propose replaces the …

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Community-Scale Beach Nourishment And Groin Construction Decisions Along Human-Modified Coasts : The Interplay Between Socioeconomics, Coordination, Tourism, And Shoreline Change, Arye Max Janoff Jan 2021

Community-Scale Beach Nourishment And Groin Construction Decisions Along Human-Modified Coasts : The Interplay Between Socioeconomics, Coordination, Tourism, And Shoreline Change, Arye Max Janoff

Theses, Dissertations and Culminating Projects

In response to coastal erosion driven by storms, sea-level rise, and local gradients in sediment supply, communities defend their homes and maintain beach recreation by widening beaches via soft engineering (i.e., beach nourishment) or hard engineering (i.e., groins). Past research has found that, at regional scales, the net effect of these interventions has in many cases not only counteracted historically observed beach erosion, but has reversed erosional trends, on average shifting shorelines seaward. While groins trap sediments locally at and upcoast of the structure relative to the direction of alongshore transport, however, they often have adverse downcoast impacts, resulting in …

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Binary Black Widow Optimization Algorithm For Feature Selection Problems, Ahmed Al-Saedi Jan 2021

Binary Black Widow Optimization Algorithm For Feature Selection Problems, Ahmed Al-Saedi

Theses and Dissertations (Comprehensive)

This thesis addresses feature selection (FS) problems, which is a primary stage in data mining. FS is a significant pre-processing stage to enhance the performance of the process with regards to computation cost and accuracy to offer a better comprehension of stored data by removing the unnecessary and irrelevant features from the basic dataset. However, because of the size of the problem, FS is known to be very challenging and has been classified as an NP-hard problem. Traditional methods can only be used to solve small problems. Therefore, metaheuristic algorithms (MAs) are becoming powerful methods for addressing the FS problems. …

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Random Matrix Theory: A Combinatorial Proof Of Wigner's Semicircle Law, Vanessa Wolf Jan 2021

Random Matrix Theory: A Combinatorial Proof Of Wigner's Semicircle Law, Vanessa Wolf

Scripps Senior Theses

A combinatorial proof of Wigner’s semicircle law for the Gaussian Unitary Ensemble (GUE) is presented using techniques from free probability. Motivating examples taken from the symmetric Bernoulli ensemble and the GUE show the distribution of eigenvalues of sample n x n matrices approaching Wigner’s semicircle as n get large. The concept of crossing and non-crossing pairings is developed, along with proofs of Wick’s Formula for real and complex Gaussians. It is shown that Wigner’s semicircle distribution has moments given by the Catalan numbers. Wick’s Formula and several additional lemmas (proved in sequence) lead to a "method of moments" proof that …

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Computationally Recovering Preferred Factorizations Of Quantum Hilbert Space, Louisa Cornelis Jan 2021

Computationally Recovering Preferred Factorizations Of Quantum Hilbert Space, Louisa Cornelis

Scripps Senior Theses

This thesis addresses the question of the preferred factorization of the quantum mechanical Hilbert Space into sub parts. Specifically, I computationally implement streamlined aspects of the recent “in principle” proposal of Carroll and Singh in their paper Quantum Mereology: Factorizing Hilbert Space into Subsystems with Quasi-Classical Dynamics. The goal is to link the selection of a preferred tensor product factorization to the appearance of quasi-classical behavior in this preferred factorization. Carroll and Singh quantify quasi-classical behavior through the criteria of “robustness” and “predictability” using the purity and pointer entropies. This work tests whether it is necessary to use both entropies …

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Secularism, The Oxford Movement, And Religious Aesthetics In John Keble, Christina Rossetti, Adelaide Anne Procter, And Gerard Manley Hopkins, Mary Harmon Jan 2021

Secularism, The Oxford Movement, And Religious Aesthetics In John Keble, Christina Rossetti, Adelaide Anne Procter, And Gerard Manley Hopkins, Mary Harmon

Dissertations

This dissertation examines the relationship between secularism and the development of Oxford Movement poetry. The members of the movement sought to restore pre-Reformation religious practices in the Anglican Church while maintaining its distinctiveness from the Roman Catholic and Orthodox traditions, which led to the development of unique liturgy, architecture, hymns, and poetry, among other art forms. I argue that secularism simultaneously made the movement more possible while also making it more unstable. Secularism gave the theologians and poets of the movement enough freedom to borrow from older Christian traditions, yet the movement failed to revive the Anglican Church (several members …

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Writing At The Horizon: How Producing Imagined Narratives Affects Mood, David Yu-Zhong Liang Jan 2021

Writing At The Horizon: How Producing Imagined Narratives Affects Mood, David Yu-Zhong Liang

Senior Projects Fall 2021

The present study explores the effect of three different writing activities and their subsequent effects on participant mood. Writing has been of particular interest for psychologists due to its use in interventions aimed at working through traumatic or stressful periods, and recent research has begun to explore the use of narrative in placing traumatic events and experiences in greater context. However, purely therapeutic, intervention-based writing exercises exclude a large amount of more expressive, imagined creations and narratives, which may have the capacity to reorient, contextualize, and otherwise positively affect a person’s mood. This study investigates whether employing the imagination may …

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Using Augmented Reality As A Tool For Distance Learning Of Vsepr Theory, Isabelle Lopez Jan 2021

Using Augmented Reality As A Tool For Distance Learning Of Vsepr Theory, Isabelle Lopez

Scripps Senior Theses

Distance learning poses challenges in most academic settings, especially at the undergraduate laboratory level. Improving this mode of learning diminishes the impact of current events on young scientists’ development of foundational laboratory concepts. Our work explores the use of augmented reality (AR) in a laboratory setting. We developed a completely virtual valence shell electron pair repulsion (VSEPR) theory lab activity consistent with the goals of Keck Science Department’s Introduction to Chemistry course’s in-person VSEPR lab activity. We were able to maintain a hands-on learning experience for students while using a tool many students already own: an iPhone as an alternative …

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Influence Of Iceberg-Discharge Events On The Climate And Circulation Of The Central North Atlantic Ocean During The Last Glaciation, Ava Mcilvaine Jan 2021

Influence Of Iceberg-Discharge Events On The Climate And Circulation Of The Central North Atlantic Ocean During The Last Glaciation, Ava Mcilvaine

Scripps Senior Theses

The repeated occurrence of episodic iceberg-discharge events and abrupt climate change in the North Atlantic Ocean is well-documented for the late Quaternary period. However, much of the evidence for these periods known as Heinrich Events comes from the subpolar region, where deposition can be dominated by ice-rafted debris (IRD) and overwhelm other oceanographic and climatic indicators. Thus, the following analysis of coarse sediment from Integrated Ocean Drilling Program (IODP) Core Site U1313 (41°0.0'N, 32°57.42'W) evaluated ocean cooling related to ice-rafting, water mass migration, and climate change over the approximate last 100,000 years. Site U1313 is located near the North Atlantic …

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Fixed-Point Proximity Minimization: A Theoretical Review And Numerical Study, Daniel Weddle, Jianfeng Guo Jan 2021

Fixed-Point Proximity Minimization: A Theoretical Review And Numerical Study, Daniel Weddle, Jianfeng Guo

OUR Journal: ODU Undergraduate Research Journal

This study examines the relatively recent development of a “fixed-point proximity” approach to one type of minimization problem, considers its application to image denoising, and explores convergence and divergence of the iterative algorithm beyond a (previously supplied) theoretically guaranteed convergence bound on one of the parameters (𝜆). While reviewing the fixed-point proximity approach and its application to image denoising, we aim to communicate the concepts and details in a way that will facilitate understanding for undergraduates and for scholars from other subfields. In the latter portion of our study, the numerical experiment provides thought-provoking data on the effects that parameters …

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Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard Jan 2021

Carbon Dioxide And Particulate Matter Concentration On Hampton Roads Air Quality, Gregory Hubbard

OUR Journal: ODU Undergraduate Research Journal

Hampton Roads has been a maritime crossroads for the last 400 years. Industrialization has impacted the coastal region for the last 250 years. The expansion of the Port of Virginia in 2019 has created dense traffic in the region resulting in impacts to air quality. Two waste products that affect humans are particulate matter and carbon dioxide. Both respective emissions can cause adverse effects on humans, such as asthma, some lung cancers, and other respiratory distress. Scientists and health practitioners are studying the effects of particulate matter on human health. Hampton Roads, in particular, because of its unique location on …

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Development Of Quantitative Intensity-Based Single-Molecule Assays, Benjamin Croop Jan 2021

Development Of Quantitative Intensity-Based Single-Molecule Assays, Benjamin Croop

Electronic Theses and Dissertations, 2020-2023

Fluorescence microscopy has emerged as a popular and powerful tool within biology research, owing to its exceptional signal contrast, specificity, and the versatility of the various microscope designs. Fluorescence microscopy has been used to study samples across orders of magnitude in physical scale ranging from tissues to cells, down to single-molecules, and as such has led to breakthroughs and new knowledge in a wide variety of research areas. In particular, single-molecule techniques are somewhat unique in their ability to study biomolecules in their native state, which enables the visualization of short-lived interactions and rare events which can be highly relevant …

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