Physical Sciences and Mathematics Commons^™

A Framework For Creating Virtual Reality Models For More Effective Coastal Flood Risk Communication, Tina Korani, Alexandrea Martinez

CSU Journal of Sustainability and Climate Change

Coastal cities are exposed to increasing risks of flooding from sea-level rise. Climate change is expected to double the frequency of coastal flooding within the next decade, and some areas could experience floods of a magnitude 100 times higher than currently (Vitousek et al., 2017). People living in at-risk areas often ignore the impact of climate change on flood intensity and frequency. Immersive visual storytelling techniques proved promising and powerful tools to engage with and raise awareness of flood hazards. Here, we are introducing a framework to use Virtual Reality (VR) to reach better people living in coastal cities and …

On Computing Optimal Repairs For Conditional Independence, Alireza Pirhadi

Electronic Thesis and Dissertation Repository

This thesis focuses on the concept of Conditional Independence (CI) and its testing, which holds immense significance across various fields, including economics, social sciences, and biomedical research. Notably, within computer science, CI has become an integral part of building probabilistic and causal models. It aids efficient inference and plays a key role in uncovering causal relationships.

The primary aim of this thesis is to broaden the scope of CI beyond its testing aspect. We introduce the pioneering problem of data repair, designed to adhere to particular CI constraints. The value and pertinence of this problem are highlighted through two contrasting …

Evaluation Of Native Plant Communities On Nebraska Game And Parks Commission State Parks, Robert F. Steinauer

Nebraska Game and Parks Commission: White Papers, Conference Presentations, and Manuscripts

This report evaluates the Native Plant Communities on Nebraska Game and Parks Commission State Parks East Region, also known as Region 3, which includes much of northeast and extreme eastern Nebraska, including portions of the lower Niobrara, Elkhorn and Platte Rivers and nearly the entire east border formed by the Missouri River. Fifteen state-listed threatened and endangered species have been recorded within the boundaries of Region 3 within the last twenty years. Several of these occupy habitats within major river channels.

Surveyed areas which contained habitat for legally protected species include Dead Timber State Recreation Area, Indian Cave State Park, …

Rural Science Teachers Social Network Analysis Matrices, Rebecca L. Sansom, Tracy Poulsen

ScholarsArchive Data

These are the social network matrices for our study of rural science teachers. Each matrix is located on a separate tab on the spreadsheet.

A Simple Method For Determining Shallow Charge Distributions In Dielectrics Via Pulsed Electroacoustic Measurements, Zachary Gibson, J. R. Dennison

Journal Articles

The understanding of charge dynamics in dielectric materials is paramount in mitigating electrostatic discharge events for spacecraft. The most critical spacecraft charging events are found to result from incident electrons in the energy range of 10 keV to 50 keV. The charge embedded in dielectric materials in this energy range are deposited a distance into the material on the order of a few to tens of microns. One way to measure and understand the deposited charge is via pulsed electroacoustic measurements (PEA). However, the typical PEA spatial resolution of ~ 10 μm is not sufficient to resolve or discern charge …

Changes In An Enzyme Ensemble During Catalysis Observed By High Resolution Xfel Crystallography, Nathan J. Smith, Medhanjali Dasgupta, David C. Wych, Cole Dolamore, Raymond G. Sierra, Stella Lisova, Darya Marchany-Rivera, Aina E. Cohen, Sébastien Boutet, Mark S. Hunter, Christopher Kupitz, Frédéric Poitevin, Frank R. Moss Iii, Aaron S. Brewster, Nicholas K. Sauter, Iris D. Young, Alexander M. Wolff, Virendra K. Tiwari, Nivesh Kumar, David B. Berkowitz, Ryan G. Hadt, Michael C. Thompson, Alec H. Follmer, Mark A. Wilson

Chemistry Department: Faculty Publications

Enzymes populate ensembles of structures with intrinsically different catalytic proficiencies that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography (MISC) at an X-ray free electron laser (XFEL) to observe catalysis in a designed mutant (G150T) isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations and formation of the thioimidate catalytic intermediate selects for catalytically competent substates. A prior proposal for active site cysteine charge-coupled conformational changes in ICH is validated by determining structures of the enzyme over a range of pH values. A combination of large …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2023 Residential Metals Abatement Program Baptist Student Union Soil Remedial Action Work Plan (Rawp) (Dated August 8, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final Pre-Design Investigation Work Plan Blacktail Creek Riparian Actions, (Dated August 14, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2023 Residential Metals Abatement Program Gold Hill Lutheran Church (Containing The Creativity Factory Preschool) Soil Remedial Action Work Plan (Rawp) (Dated August 8, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Approval For The Butte Priority Soils Operable Unit (Bpsou) 2023 Residential Metals Abatement Program Stodden Park Soil Remedial Action Work Plan (Rawp) (Dated August 8, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Terahertz From Electrons, Electronics From Terahertz, Clayton D. Moss

Theses and Dissertations

Time-domain terahertz spectroscopy (THz-TDS) is a valuable technique for studying collective ultrafast phenomena. Several mechanisms exist for converting ultrashort optical laser pulses into coherent THz sources. Broadband THz pulses can be obtained from electron currents in air plasma, which requires combinations of different colors of light to be most effective. I report multi-color generation schemes of THz pulses that deliver coherent THz output. Experimental and theoretical work using the photocurrent model describe ways to use non-harmonic color combinations to utilize several sources of light available in a table-top laser setup. Additionally, THz-TDS is used to study a variety of ultrafast …

Using 4most To Refine The Measurement Of Galaxy Properties: A Case Study Of Supernova Hosts, J Dumayne, I M. Hook, S C. Williams, G A. Lowes, D Head, A Fritz, O Graur, Benne Holwerda, A Humphrey, A Milligan, M Nicholl, B F. Roukema, P Wiseman

Faculty and Staff Scholarship

The Rubin Observatory’s 10-year Legacy Survey of Space and Time will observe near to 20 billion galaxies. For each galaxy the properties can be inferred. Approximately 105 galaxies observed per year will contain Type Ia supernovae (SNe), allowing SN host-galaxy properties to be calculated on a large scale. Measuring the properties of SN host-galaxies serves two main purposes. The first is that there are known correlations between host-galaxy type and supernova type, which can be used to aid in the classification of SNe. Secondly, Type Ia SNe exhibit correlations between host-galaxy properties and the peak luminosities of the SNe, which …

A Search For Relativistic Ejecta In A Sample Of Ztf Broad-Lined Type Ic Supernovae, Alessandra Corsi, Anna Y.Q. Ho, S. Bradley Cenko, Shrinivas R. Kulkarni, Shreya Anand, Sheng Yang, Jesper Sollerman, Gokul P. Srinivasaragavan, Conor M.B. Omand, Arvind Balasubramanian, Dale A. Frail, Christoffer Fremling, Daniel A. Perley, Yuhan Yao, Aishwarya S. Dahiwale, Kishalay De, Alison Dugas, Matthew Hankins, Jacob Jencson, Mansi M. Kasliwal, Anastasios Tzanidakis, Eric C. Bellm, Russ R. Laher, Frank J. Masci, Josiah N. Purdum, Nicolas Regnault

Michigan Tech Publications, Part 2

The dividing line between gamma-ray bursts (GRBs) and ordinary stripped-envelope core-collapse supernovae (SNe) is yet to be fully understood. Observationally mapping the variety of ejecta outcomes (ultrarelativistic, mildly relativistic, or nonrelativistic) in SNe of Type Ic with broad lines (Ic - BL) can provide a key test to stellar explosion models. However, this requires large samples of the rare SN Ic - BL events with follow-up observations in the radio, where fast ejecta can be probed largely free of geometry and viewing angle effects. Here, we present the results of a radio (and X-ray) follow-up campaign of 16 SNe Ic …

The Role Of Cytosolic Chaperonin Cct And Its Co-Chaperone Phlp1 In Folding And Assembly Of Signaling Complexes, Yujin Kwon

Theses and Dissertations

CCT, a large (1 MDa) protein-folding machine, is a eukaryotic group II chaperonin that is essential for folding many cellular proteins and is the most complex of all chaperonins with two rings each composed of eight paralogous subunits. CCT captures proteins in its folding chamber to assist the folding of its substrates. CCT utilizes ATP hydrolysis to open and close its chamber and fold its substrates. CCT has been shown to be important in the folding of proteins with - propeller domains which consist of seven WD40 repeat sequences that fold into -sheets that form the blades of a propeller-like …

The Influence Of Political Media On Large Language Models: Impacts On Information Synthesis, Reasoning, And Demographic Representation, Alexander Glenn Shaw

Theses and Dissertations

This thesis investigates the impact of finetuning the LLaMA 33B language model on partisan news datasets, revealing negligible changes and underscoring the enduring influence of pretraining datasets on model opinions. Training nine models across nine distinct news datasets spanning three topics and two ideologies, the study found consistent demographic representation, predominantly favoring liberal, college-educated, high-income, and non-religious demographics. Interestingly, a depolarizing effect emerged from partisan news finetuning, suggesting that intense exposure to topic-specific information might lead to depolarization, irrespective of ideological alignment. Despite the exposure to contrasting viewpoints, LLaMA 33B maintained its common sense reasoning ability, showing minimal variance on …

Separation Of Perrhenate And Perfluoroalkyl Substances By Ion Chromatography With Customized Stationary Phases, Wai Ning Chan

Theses and Dissertations

Ion exchange chromatography (IC) is an analytical technique used to separate charged molecules including ions, proteins, small nucleotides, and amino acids. It can function in anion or cation mode. In this dissertation, anion exchange chromatography was used, and column materials were made in our lab with resorcinarene-based compounds called cavitands. Cavitands create cavities to bind to molecules because of their three-dimensional structure. Two new gradient IC methods were established to identify and quantify perrhenate and perfluoroalkyl substances (PFAS) by customized resorcinarene-based column, zinc cyclen resoecinarene (ZCR) and arginine methyl ester (RUE) columns. The ZCR column accomplished outstanding separation of perrhenate …

Weakly-Supervised Anomaly Detection In Surveillance Videos Based On Two-Stream I3d Convolution Network, Sareh Soltani Nejad

Electronic Thesis and Dissertation Repository

The widespread adoption of city surveillance systems has led to an increase in the use of surveillance videos for maintaining public safety and security. This thesis tackles the problem of detecting anomalous events in surveillance videos. The goal is to automatically identify abnormal events by learning from both normal and abnormal videos. Most of previous works consider any deviation from learned normal patterns as an anomaly, which may not always be valid since the same activity could be normal or abnormal under different circumstances. To address this issue, the thesis utilizes the Two-Stream Inflated 3D (I3D) Convolutional Networks to extract …

Towards Clinical Microscopic Fractional Anisotropy Imaging, Nico Jj Arezza

Electronic Thesis and Dissertation Repository

Microscopic fractional anisotropy (µFA) is a diffusion-weighted magnetic resonance imaging (dMRI) metric that is sensitive to neuron microstructural features without being confounded by the orientation dispersion of axons and dendrites. µFA may potentially act as a surrogate biomarker for neurodegeneration, demyelination, and other pathological changes to neuron microstructure with greater specificity than other dMRI techniques that are sensitive to orientation dispersion, such as diffusion tensor imaging. As with many advanced imaging techniques, µFA is primarily used in research studies and has not seen use in clinical settings.

The primary goal of this Thesis was to assess the clinical viability of …

Applications Of Observational Seismology: Insights Into Volcanic And Near Surface Processes, Justin T. Wilgus

Earth and Planetary Sciences ETDs

The field of observational seismology has made tremendous progress in the past two decades. This progress has been multi-faceted in form, but significant contributions emanated from 1) increases in both the quality and the quantity of seismic data 2) advances in computational power 3) advances in algorithmic capability, including machine learning. In this dissertation I report on three distinctly different seismic applications made possible by the aforementioned progress and discuss the insights these applications have provided in understanding volcanic and near surface processes of the Earth.

In the first chapter titled, “Shear Velocity Evidence of Upper Crustal Magma Storage Beneath …

Season, Not Long-Term Warming, Affects The Relationship Between Ecosystem Function And Microbial Diversity, Melissa S. Shinfuku, Luiz A. Domeignoz-Horta, Mallory J. Choudoir, Serita D. Frey, Kristen M. Deangelis

Faculty Publications

Across biomes, soil biodiversity promotes ecosystem functions. However, whether this relationship will be maintained under climate change is uncertain. Here, using two long-term warming experiments, we investigated how warming affects the relationship between ecosystem functions and microbial diversity across seasons, soil horizons, and warming duration. The soils in these warming experiments were heated +5 °C above ambient for 13 or 28 years. We measured seven different ecosystem functions representative of soil carbon cycling, soil nitrogen cycling, or nutrient pools. We also surveyed bacterial and fungal community diversity. We found that the relationship between ecosystem function and bacterial diversity and the …

Magnetic Nanodoping: Atomic Control Of Spin States In Cobalt Doped Silver Clusters, Vicente Zamudio-Bayer, Konstantin Hirsch, Lei Ma, Kobe De Knijf, X. S. Xu, Arkadiusz Ławicki, Akira Terasaki, Piero Ferrari, Bernd Von Issendorff, Peter Lievens, Walt A. De Heer, J. Tobias Lau, Ewald Janssens

Department of Physics and Astronomy: Faculty Publications

The interaction of magnetic dopants with delocalized electron states can result in interesting many-body physics. Here, the magnetic properties of neutral and charged finite silver metal host clusters with a magnetic cobalt atom impurity were investigated experimentally by exploiting the complementary methods of Stern- Gerlach molecular beam deflection and x-ray magnetic circular dichroism spectroscopy and are accompanied by density functional theory calculations and charge transfer multiplet simulations. The influence of the number of valence electrons and the consequences of impurity encapsulation were addressed in free size-selected, singly cobalt-doped silver clusters CoAg^0,_n+ (n = 2–15). Encapsulation of the …

Towards Efficient And Effective Representation Learning For Image And Video Understanding, Taojiannan Yang

Electronic Theses and Dissertations, 2020-2023

Deep learning has achieved tremendous success on various computer vision tasks. However, deep learning methods and models are usually computationally expensive, making it hard to train and deploy, especially on resource-constrained devices. In this dissertation, we explore how to improve the efficiency and effectiveness of deep learning methods from various perspectives. We first propose a new learning method to learn computationally adaptive representations. Traditional neural networks are static. However, our method trains adaptive neural networks that can adjust their computational cost during runtime, avoiding the need to train and deploy multiple networks for dynamic resource budgets. Next, we extend our …

Annotation Efficient Visual Recognition: From Semi-Supervised To Few-Shot Learning, Mamshad Nayeem Rizve

Electronic Theses and Dissertations, 2020-2023

In recent years, supervised deep learning has achieved remarkable success in solving a wide range of visual recognition problems. Large-scale labeled datasets have been crucial for this success and the progress has primarily been limited to controlled environments. In this dissertation, we present methods to improve the annotation efficiency of deep visual recognition models and also propose methods to improve the performance of annotation-efficient models in unconstrained open-world settings. To address the annotation bottleneck in supervised learning, we introduce a pseudo-labeling framework for semi-supervised learning. While consistency regularization methods dominate the field, they heavily rely on domain-specific data augmentations, limiting …

A Search For Chiral Asymmetry In Secondary Electron Emission From Cysteine Induced By Longitudinally Polarized Electrons, K. J. Ahrendsen, Kenneth Wayne Trantham, D. Tupa, T. J. Gay

Department of Physics and Astronomy: Faculty Publications

We performed experiments searching for chirality-dependent secondary electron emission for a 141 eV longitudinally spin-polarized electron beam incident on a thick solid cysteine target. We determined the secondary electron yield by measuring the positive current produced when the cysteine target was negatively biased. No spin-dependent effects to a level of 10⁻³ were found for the secondary electron emission yield.

Detecting Team Conflict From Multiparty Dialogue, Ayesha Enayet

Electronic Theses and Dissertations, 2020-2023

The emergence of online collaboration platforms has dramatically changed the dynamics of human teamwork, creating a veritable army of virtual teams composed of workers in different physical locations. The global world requires a tremendous amount of collaborative problem solving, primarily virtual, making it an excellent domain for computer scientists and team cognition researchers who seek to understand the dynamics involved in collaborative tasks to provide a solution that can support effective collaboration. Mining and analyzing data from collaborative dialogues can yield insights into virtual teams' thought processes and help develop virtual agents to support collaboration. Good communication is indubitably the …

Electron Beam Lithography And Dimensional Metrology For Fin And Nanowire Devices On Ge, Sige And Geoi Substrates, Nikolay Petkov, Margarita Georgieva, Sinan Bugu, Ray Duffy, Brendan Mccarthy, Maksym Myronov, Ann-Marie Kelleher, Graeme Maxwell, Giorgos Fagas

Physical Sciences Publications

Until now there is no systematic study on the effect of the substrate type on the hydrogen silsesquioxane (HSQ) electron beam lithography (EBL) patterning process. We investigate arrays of line structures with varying width and spacing, starting at 10 nm, exposed at varying dose, and developed by salty NaOH and TMAH developers on group IV semiconductor substrates. We demonstrate that the HSQ EBL process on Ge is much more limited in achieving the smallest obtainable features, having optimal uniformity and fidelity, in comparison to Si. Monte-Carlo simulations of the e-beam/substrate interactions for “pure” Si and Ge substrates, and varying content …

A Multi-Tiered Assessment Of Primary Production In Great Salt Lake, Soren Brothers, Melissa Cobo, R. Douglas Ramsey, Wayne A. Wurtsbaugh, Erin N. Rivers

Watershed Sciences Faculty Publications

Great Salt Lake (GSL) is the largest saline lake in the western hemisphere. Despite this, relatively little is known regarding ecological functioning within the lake, including detailed assessments of rates of primary productivity and ecosystem productivity. Analyses of primary production in GSL are complicated by the high heterogeneity of the system, including a broad salinity gradient from near-fresh conditions at the river confluences in Farmington and Bear River Bays to the hyper-saline conditions of the lake’s northwest arm (Gunnison Bay). Further complicating estimates of primary productivity is the possibility of high rates of benthic primary production (by benthic algae and …

Topological Data Analysis Using The Mapper Algorithm, Jessica Girard

Electronic Theses and Dissertations, 2020-2023

Topological data analysis is an expanding field that attempts to obtain qualitative information from a data set using topological ideas. There are two common methods of topological data analysis: persistent homology and the Mapper algorithm; the focus of this thesis is on the latter. In this thesis, we will be discussing the key ideas behind the Mapper algorithm, following the flow from Morse Theory to Reeb graphs to the topological version of the algorithm and finally to the statistical version. Lastly, we will present an application of Mapper to the USAIR97 data set using the RTDAmapper package.

Efficient Convolutional Neural Networks For Image Classification And Regression, Muhammad Tayyab

Electronic Theses and Dissertations, 2020-2023

Neural networks have been a topic of research since 1970s and the Convolutional Neural Networks (CNNs) were first shown to work well for hand written digits recognition in 1998. These early networks were however still shallow and contained only a few layers. Moreover these networks were mostly trained on a small amount of data in contrast to the modern CNNs which contain hundreds of convolution layers and are trained on millions of images. However, this recent shift in machine learning comes at a cost. Modern neural networks have extremely large number of parameters and require huge amount of computations for …

Deep Video Understanding With Model Efficiency And Sparse Active Labeling, Aayush Jung Bahadur Rana

Electronic Theses and Dissertations, 2020-2023

Videos capture the inherently sequential nature of the real world, making automatic video understanding an essential need for automatic understanding of the real world. Due to major advancements in camera, communication, and storage hardware, videos have become a widely used data format for crucial applications such as home automation, security, analysis, robotics, and autonomous driving. Existing methods for video understanding require heavy computation and large training data for good performance, this limits how quick the videos can be processed and how much data can be labeled for training. Real-world video understanding requires analyzing dense scenes and sequential information, which increases …