Physical Sciences and Mathematics Commons^™

Introduction To Classical Field Theory, Charles G. Torre

All Complete Monographs

This is an introduction to classical field theory. Topics treated include: Klein-Gordon field, electromagnetic field, scalar electrodynamics, Dirac field, Yang-Mills field, gravitational field, Noether theorems relating symmetries and conservation laws, spontaneous symmetry breaking, Lagrangian and Hamiltonian formalisms.

Tunable Physical Properties In Bi-Based Layered Supercell Multiferroics Embedded With Au Nanoparticles, Jianan Shen, Zihao He, Di Zhang, Ping Lu, Julia Deitz, Zhongxia Shang, Matias Kalaswad, Haohan Wang, Xiaoshan S. Xu, Haiyan Wang

Department of Physics and Astronomy: Faculty Publications

Multiferroic materials are an interesting functional material family combining two ferroic orderings, e.g., ferroelectric and ferromagnetic orderings, or ferroelectric and antiferromagnetic orderings, and find various device applications, such as spintronics, multiferroic tunnel junctions, etc. Coupling multiferroic materials with plasmonic nanostructures offers great potential for optical-based switching in these devices. Here, we report a novel nanocomposite system consisting of layered Bi_1.25AlMnO_3.25 (BAMO) as a multiferroic matrix and well dispersed plasmonic Au nanoparticles (NPs) and demonstrate that the Au nanoparticle morphology and the nanocomposite properties can be effectively tuned. Specifically, the Au particle size can be tuned from …

Virtual Expeditions Facilitated By Open Source Solutions Broaden Student Participation In Natural History Research, Richelle L. Tanner, Talia Y. Moore

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

From its genesis in the Victorian era as an activity for the elite to today's emphasis on “Big Data” and continuous monitoring, natural history has a prominent role in scientific discoveries for many fields. However, participation in field expeditions is limited by funding, space, accessibility, and safety constraints. Others have detailed the active exclusion of minoritized groups from field expeditions and harm/discrimination faced by the few who do participate, but we provide one solution to broaden opportunities for participation in natural history: Virtual Expeditions. Virtual Expeditions are broadly defined as open source, web-facilitated research activities designed to analyze bulk-collected digital …

Mapping Ecosystem Service Flows Of Estuary Restoration Projects On The Oregon Coast To Identify Impacted Stakeholders, Shersten King Finley

Dissertations and Theses

The recent impetus for estuarine restoration has largely focused on resolving key ecological problems; however, less is known about how people might benefit or be impacted by restoration. By mapping benefits that flow from functional salt marshes and estuarine systems I examined how different social groups might be impacted by restoration based on race and class. In this study, I considered three ecosystem services (recreation, aesthetics, cultural/historical/spiritual) and where they might impact surrounding communities. In this paper I argue that stakeholder groups can be identified by mapping ecosystem service flow areas. I hypothesized that these three ecosystem services would have …

Draft Final 2021 Unreclaimed Sites Sampling Ur-33 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

"We've Created Cheap Energy Off The Backs Of Salmon": Dam Removal Politics And Alliances In The Lower Snake River Basin, Krista Harrington

Dissertations and Theses

Dams, once considered by many to be good for water development in the Western U.S., might not be a part of a climate resilient future. Dams have come under increasing scrutiny due to undesirable ecological implications. Although dam removal proposals are growingly popular in recent decades, they are controversial since they impact different stakeholders in different ways. In the Pacific Northwest, the Lower four Snake River dams have long been criticized for their negative impacts on salmon. In February 2021, US Congressman Mike Simpson (R-Idaho) proposed a comprehensive framework to deconstruct the Lower four Snake River dams as an attempt …

Vims Marine Science Day, Virginia Institute Of Marine Science

Miscellaneous

Brochure describing demonstrations and activities on this day of community outreach.

The Tails Of Two Avian Schistosomes: Paired Exposure Study Demonstrates Trichobilharzia Stagnicolae Penetrates Human Skin More Readily Than A Novel Avian Schistosome From Planorbella, Nathaniel J. Anderson, Curtis L. Blankespoor, Randall J. Dejong

University Faculty Publications and Creative Works

A novel schistosome from Planorbella snails currently known as avian schistosomatid sp. C (ASC) was recently described as being capable of causing the papules associated with swimmer’s itch. We conducted a paired study with 24 human volunteers, exposing each of their forearms to five drops of water containing cercariae of ASC or Trichobilharzia stagnicolae, and examined the skin for papules 1–3 days later. A mixed effects model showed that only the parasite species significantly affected the number of papules, while prior experimental exposure, swimming history, and swimmer’s itch experience did not. The total number of papules produced by the two …

Flecs: A Federated Learning Second-Order Framework Via Compression And Sketching, Artem Agafonov, Dmitry Kamzolov, Rachael Tappenden, Alexander Gasnikov, Martin Takac

Machine Learning Faculty Publications

Inspired by the recent work FedNL (Safaryan et al, FedNL: Making Newton-Type Methods Applicable to Federated Learning), we propose a new communication efficient second-order framework for Federated learning, namely FLECS. The proposed method reduces the high-memory requirements of FedNL by the usage of an L-SR1 type update for the Hessian approximation which is stored on the central server. A low dimensional 'sketch' of the Hessian is all that is needed by each device to generate an update, so that memory costs as well as number of Hessian-vector products for the agent are low. Biased and unbiased compressions are utilized to …

Fertilizer Waste Mistreatment Facilities: Investigating The Barrier That Keep Waste In And Attention Out At Central Florida's Phosphogypsum Stacks., Harsha Devaraj

Masters Theses

This project investigates the physical and narrative barriers constructed by the phosphate mining and processing industry to dissuade public engagement with its phosphogypsum sites in Central Florida, USA. The barriers around PG utilize decades of misinformation, racial geographies, and misrepresentations of scale, origin, and risk to create powerful narratives about how we should imagine and relate to these materials. These barriers hinder sustained public attention to their sites, enabling extractive industries to expand while avoiding oversight and responsibility. Attention to how these barriers around phosphogypsum are constructed allows us to recognize these strategies at work in how we see and …

The Synthesis Of Deuterated Isohumulones For Use As Internal Standards In Lc-Ms Stable Isotope Dilution Assays, Patrick Gleason, Bruce Hamper Dr.

Undergraduate Research Symposium

Humulones are compounds that are prevalent in the hops flowers (Humulus Lupulus) used in beer brewing. These compounds undergo isomerization during the brewing process, and the resulting isohumulones are considered to be the primary contributors to the bitter flavors present in beer. As such, quantifying their presence, and the relative presence of their homologs(n-, co-, ad-), is of great importance in the characterization of beer. In this effort, one of the homologs of humulone (co) was isolated before being subsequently isomerized and deuterated for the purpose of analyzing beer by stable isotope dilution assay mass spectrometry(SIDA-MS). The addition of this …

Session 4: Plunging Into Deep Water: An Immersion In Fintech, Defi (Decentralized Finance), & Web3, Joseph M. Vincent

SITIE Symposiums

This panel featured entrepreneurs providing their expert insight into the background, workings, and expected developments of the FinTech industry. Moderated by Adjunct Professor of Law Joseph M. Vincent, the panel features Ron Oliveira, Kory Hoang, and Jonathan Blanco.

The panelists provided insight on topics regarding: (1) the fundamental changes in financial services since the advent of FinTech; (2) background on the Stablecoin industry including a background of what Stablecoin is, and why it has been under recent scrutiny; and (3) the NFT market and the direction the NFT space is heading. In a Q&A session, the panelists also offered their …

Session 3: Deep Innovation Dive In Health Equity: Truveta (“Saving Lives With Data”), Steve Tapia, Dave Heiner

SITIE Symposiums

This session is a “deep dive” into health equity and research via a moderated discussion with Truveta, a new data partnership company poised for research breakthroughs in the healthcare sector. In it, Dave Heiner, General Counsel and Chief Policy Officer for Truveta, discusses the company’s healthcare-centered mission and the key role that data plays in the healthcare field.

Session 2: Diversity Perspectives: In-House Counsel, Debbie Akhbari

SITIE Symposiums

This expert panel addressed diversity perspectives in the legal field. Moderated by Debbie Akhbari, six panelists shared their stories. The panelists were Leticia Hernández, Bernadette Lopez, Elida Moran, Catherine Romero, Rachel Seals, and Katina Thornock. Each panelist's stories have been broken into its own section in the summary of proceedings.

Many diverse candidates have incorrect assumptions made about them, resulting in doors being closed by those in positions of power. This panel shared their personal stories and encouraged students and newer attorneys to keep “knocking on those doors” and for those in positions of power to open those doors. Through …

Psychological Understanding Of Textual Journals Using Natural Language Processing Approaches, Amirmohammad Kazemeinizadeh

Electronic Thesis and Dissertation Repository

Recent NLP advancements have improved the state-of-the-art in well-known datasets and are appealing more attention day by day. However, as the models become more complicated, the ability to provide interpretable and understandable results is becoming harder so the trade-off between accuracy and interpretability is a concern that is yet to be addressed. In this project, the aim is to utilize state-of-the-art NLP models to provide meaningful insight from psychological real-world documents that contain complex structures. The project involves two main chapters each including a different dataset. The first chapter is related to binary classification on a personality detection dataset, while …

Session 1: Innovation In Legal Services, Steven W. Bender, Michael Cherry, Matthew Spencer

SITIE Symposiums

This panel featured two “disrupters” who detailed their experiences innovating in the legal services space. The first panelist spoke about data-driven regulatory reform and the other spoke as an entrepreneur whose product introduces artificial intelligence (AI) into the legal recruiting process. Two additional panelists provided commentary regarding the second panelist’s presentation.

The panel provided insight on the topics of: (1) the legal regulatory process at large; (2) how a data-driven and feedback-oriented sandbox provides an alternative regulatory process; (3) the legal hiring and recruiting process and (4) how AI allows law firms to consider alternative hiring metrics when assessing candidates …

Introduction To The 5th Annual Innovation And Technology Law Conference, Annette Clark

SITIE Symposiums

Seattle University School of Law’s then dean, now Dean Emerita, Annette Clark, opens the 5^th annual Innovation and Technology Law Conference, co-sponsored by the Seattle Journal of Technology, Environmental, and Innovation Law (SJTEIL) at Seattle University School of Law. Annette Clark has been involved with the planning and organization of the Innovation and Technology Law Conference since the conference’s inception. The theme of the 5^th annual 2022 conference is “deep innovation dives.”

Annette Clark explains that “This conference is part of our continuing efforts at Seattle [University] Law to expand educational opportunities for our students and community in …

Offline Reinforcement Learning With Causal Structured World Models, Zheng-Mao Zhu, Xiong-Hui Chen, Hong-Long Tian, Kun Zhang, Yang Yu

Machine Learning Faculty Publications

Model-based methods have recently shown promising for offline reinforcement learning (RL), aiming to learn good policies from historical data without interacting with the environment. Previous model-based offline RL methods learn fully connected nets as world-models to map the states and actions to the next-step states. However, it is sensible that a world-model should adhere to the underlying causal effect such that it will support learning an effective policy generalizing well in unseen states. In this paper, We first provide theoretical results that causal world-models can outperform plain world-models for offline RL by incorporating the causal structure into the generalization error …

5th Annual Innovation And Technology Law Conference: Deep Innovation Dives, Steven W. Bender

SITIE Symposiums

Steven W. Bender, Seattle University School of Law Professor and organizer of the SITIE Symposium series, details the history of the SITIE symposiums and the 2022 proceedings. He discusses how this year's symposium builds on themes and issues raised in previous symposiums and looks ahead to the 2023 SITIE symposium.

Synthesis, Physicochemical Characterization, And Catalytic Evaluation Of Fe3+-Containing Ssz-70 Zeolite, Christopher M. Lew, Cong Yan Chen, Gary J. Long, Fernande Grandjean, Andrew S. Ichimura, Dan Xie, Nicolás A. Grosso-Giordano, Khetpakorn Chakarawet, Howard S. Lacheen, Kurt O. Jensen, Abraham Martinez, Alexander Katz, Bi Zeng Zhan, Stacey I. Zones

Chemistry Faculty Research & Creative Works

Whereas one-dimensional, 10-membered ring zeolites are typically used for hydroisomerization, Fe3⁺-containing SSZ-70 (Fe-SSZ-70) shows remarkable isomerization selectivity for a zeolite containing 12- and partially blocked 14-membered rings, in addition to 10-membered rings. Fe-SSZ-70 was compared to Al3⁺-containing SSZ-70 (Al-SSZ-70) in constraint index and n-decane hydrocracking tests. Fe-SSZ-70 exhibited a 74% total isomer yield (64% yield of monobranched isomers and 10% cracking yield) at 85% conversion compared to 49% total isomer yield (41% yield of monobranched isomers and 36% cracking yield) for Al-SSZ-70 at the same conversion. The selectivity to isomerization is attributed to the weaker acid …

Magnetic-Field-Dependent Stimulated Emission From Nitrogen-Vacancy Centers In Diamond, Felix A. Hahl, Lukas Lindner, Xavier Vidal, Tingpeng Luo, Takeshi Ohshima, Shinobu Onoda, Shuya Ishii, Alexander M. Zaitsev, Marco Capelli, Brant C. Gibson, Andrew D. Greentree, Jan Jeske

Publications and Research

Negatively charged nitrogen-vacancy (NV) centers in diamond are promising magnetic field quantum sensors. Laser threshold magnetometry theory predicts improved NV center ensemble sensitivity via increased signal strength and magnetic field contrast. Here, we experimentally demonstrate laser threshold magnetometry. We use a macroscopic high-finesse laser cavity containing a highly NV-doped and low absorbing diamond gain medium that is pumped at 532 nm and resonantly seeded at 710 nm. This enables a 64% signal power amplification by stimulated emission. We test the magnetic field dependency of the amplification and thus demonstrate magnetic field-dependent stimulated emission from an NV center ensemble. This emission …

Collaborative Research: Surface-Specific Aerosol Chemistry: Direct Observations, Kinetics, And Environmental Impact, Yi Rao

Funded Research Records

No abstract provided.

A Raft To Coastal Resilience: Odu Researchers Collaborate To Help Rural Communities Combat Flooding Impacts, News @ Odu

News Items

No abstract provided.

Noncanonical Amino Acid Mutagenesis In Response To Recoding Signal-Enhanced Quadruplet Codons, Yan Chen, Xinyuan He, University Of Nebraska-Lincoln, Kun Liu, Tian Gao, Wei Niu, Jiantao Guo

Chemistry Department: Faculty Publications

While amber suppression is the most common approach to introduce noncanonical amino acids into proteins in live cells, quadruplet codon decoding has potential to enable a greatly expanded genetic code with up to 256 new codons for protein biosynthesis. Since triplet codons are the predominant form of genetic code in nature, quadruplet codon decoding often displays limited efficiency. In this work, we exploited a new approach to significantly improve quadruplet UAGN and AGGN (N = A, U, G, C) codon decoding efficiency by using recoding signals imbedded in mRNA. With representative recoding signals, the expression level of mutant proteins containing …

All-Sky, All-Frequency Directional Search For Persistent Gravitational-Waves From Advanced Ligo's And Advanced Virgo's First Three Observing Runs, R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, Teviet Creighton, Mario C. Diaz, F. Llamas, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics and Astronomy Faculty Publications and Presentations

We present the first results from an all-sky all-frequency (ASAF) search for an anisotropic stochastic gravitational-wave background using the data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. Upper limit maps on broadband anisotropies of a persistent stochastic background were published for all observing runs of the LIGO-Virgo detectors. However, a broadband analysis is likely to miss narrowband signals as the signal-to-noise ratio of a narrowband signal can be significantly reduced when combined with detector output from other frequencies. Data folding and the computationally efficient analysis pipeline, PyStoch, enable us to perform the radiometer …

Monotonicity Properties Of Functionals Under Ricci Flow On Manifolds Without And With Boundary, Paul Bracken

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, the idea of the Ricci flow is introduced and its significance and importance to related problems in mathematics had been discussed. Several functionals are defined and their behavior is studied under Ricci flow. A unique minimizer is shown to exist for one of the functionals. This functional evaluated at the minimizer is strictly increasing. The results for the first functional considered are extended to manifold with boundary. Finally, two physically motivated examples are presented.

Geochronological And Geochemical Investigation Into Rhyolite Volcanism Of The High Lava Plains And Columbia River Basalt Group Provinces Of Eastern Oregon, Usa, Vanessa Marie Swenton

Dissertations and Theses

Voluminous and widespread bimodal volcanism has significantly impacted the Pacific Northwest, USA, throughout the Miocene to present day. The two primary volcanic provinces of eastern Oregon include the Columbia River Basalt Group (CRBG) province and the High Lava Plains (HLP) trend. The magmatic and tectonic processes responsible for generating bimodal volcanism, and particularly rhyolites of the ~17-15 Ma CRBG and 12-0 Ma HLP provinces has recently been a popular topic of debate. Rhyolite volcanism of the HLP province has been ascribed to either buoyancy-driven westward plume spreading or to slab rollback and mantle convection spanning from southeast Oregon to Newberry …

Using Hospital Bed Capacity Prediction During Covid-19 To Determine Feature Importance, Helene Barrera, Justin Ehly, Blake Freeman, Chris Papesh, Brad Blanchard

SMU Data Science Review

The COVID-19 pandemic has exacerbated existing hospital capacity limitations in the United States, causing hospitals in certain regions to hit maximum capacity. The purpose of this study is to investigate key features of COVID-19 related admissions to help create a higher level of public understanding and help guide healthcare management professionals and governments when considering preventive measures. The introduction of preventative measures and new regulations during the pandemic have led to the generation of multiple types of models and feature selection methods in the field of Machine Learning that are increasingly complicated. This study focuses on the exploration of feature …

A Machine Learning Approach To Revenue Generation Within The Professional Hair Care Industry, Alexander K. Sepenu, Linda Eliasen

SMU Data Science Review

The cosmetic and beauty industry continues to grow and evolve to satisfy its patrons. In the United States, the industry is heavily science-driven, innovative, and fast-paced, suggesting that to remain productive and profitable, companies must seek smart alternatives to their current modus operandi or risk losing out on this multi-billion-dollar industry to fierce competition. In this paper, the authors seek to utilize machine learning models such as clustering and regression to improve the efficiency of current sales and customer segmentation models to help HairCo (pseudonym for confidentiality), a professional hair products manufacturer, strategize their marketing and sales efforts for revenue …

Analysis Of The Electric Power Outage Data And Prediction Of Electric Power Outage For Major Metropolitan Areas In Texas Using Machine Learning And Time Series Methods, Renfeng Wang, Venkata Leela 'Mg' Vanga, Zachary B. Zaiken, Jonathan Bennett

SMU Data Science Review

With growing energy usage, power outages affect millions of households. This case study focuses on gathering power outage historical data, modifying the data to attach weather attributes, and gathering ERCOT energy market conditions for Dallas-Fort Worth and Houston metropolitan areas of Texas. The transformed data is then analyzed using machine learning algorithms including, but not limited to, Regression, Random Forests and XGBoost to consider current weather and ERCOT features and predict power outage percentage for locations. The transformed data is also trained using time series models and serially correlated models including Autoregression and Vector Autoregression. This study also focuses on …