Physical Sciences and Mathematics Commons^™

Extreme Heat & Public Perception In Portland, Oregon: Evidence Of A Compounding Vulnerability Effect For Climate Hazards, Brianne Suldovsky, Molly Baer Kramer, Jonathan Fink

Geology Faculty Publications and Presentations

Extreme heat events are a global public health threat, and the frequency of these events are projected to increase significantly in the coming decades. Responding to extreme heat requires that municipalities communicate with public audiences. Generally speaking, risk communication and public engagement efforts are more effective when they are responsive to current risk perception trends. This social scientific study examines extreme heat risk perceptions, emergency response needs, and level of trust in first responders among residents of the Portland (OR) Metro Area. Using quantitative survey data, it demonstrates the compounding influence of three previously identified vulnerability indicators–poverty, disability, and race–on …

Existence And Uniqueness Results For Deformable Fractional Differential Equations, Sreedharan R

Theses and Dissertations

Fractional calculus and fractional differential equations are considered to be the valuable tools in modeling many phenomena in various fields of science and engineering. In the literature, many definitions for fractional order derivatives, such as Riemann-Liouville, Caputo, Jumarie, Hadamard, Weyl, and more, were developed to study the fractional differential equations that govern various phenomena in science and engineering. But these definitions have their own limitations, such as derivatives of constants, product of two functions, quotient of two functions, assertion laws, and limiting values of the derivatives at zero and negative numbers.

To overcome the deficiencies, researchers have recently introduced some …

Computational Tools For Exploring Eigenvector Localization, Robyn Ashley Markee Reid

Dissertations and Theses

We develop computational tools for exploring eigenvector localization for a class of selfadjoint, elliptic eigenvalue problems regardless of the cause for localization. The user inputs a desired region R (not necessarily connected), a tolerance for the amount localization in R, and the desired energy range [a,b]. The tool outputs eigenvectors concentrated within the tolerance inside R and within [a, b]. We develop ample theory that justifies our algorithm, which involves a complex, compact perturbation of the operator L, Ls = L+isχR, for some (small) s > 0. Our central idea can be summarized as follows: if (λ,ψ) is an eigenpair of …

Atmospheric Circulation, Climate Change, And Related Impacts Over The Western United States, Graham Patrick Taylor

Dissertations and Theses

This dissertation characterizes the range of atmospheric circulation patterns and select associated meteorology impacting the northwest United States, the onset timing of rain and wind relevant to wildfire across the western United States, and how these may respond to global warming. The ability of a suite of models contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate observed large-scale atmospheric circulation patterns over the Pacific Northwest of North America is evaluated. Climate model projections of atmospheric circulation patterns, their frequency, and associated temperature and precipitation anomalies under a high-end global warming scenario are assessed over …

Operation Shark: Addressing The Negative Portrayal Of Sharks In Media, Michael R. O'Shea

Masters Theses

Sharks are some of the most well adapted and effective animals in the animal kingdom. Unfortunately, they are also some of the most feared. For many people the word shark evokes images of vicious attacks like those seen in movies such as Jaws. Sharks have also been negatively portrayed in the media. This negative portrayal of sharks has led to misconceptions about sharks that have damaged their populations. Efforts have been made to raise awareness and fight common misconceptions of sharks. However, many people still hold on to the incorrect ideas they have about sharks. This thesis will examine the …

Pet And Polyolefin Plastics Supply Chains In Michigan: Present And Future Systems Analysis Of Environmental And Socio-Economic Impacts, Utkarsh S. Chaudhari, Kamand Sedaghatnia, Barbara K. Reck, Kate Maguire, Anne T. Johnson, David Watkins, Robert M. Handler, Tasmin Hossain, Damon S. Hartley, Vicki S. Thompson, Alejandra Peralta, Jenny L. Apriesnig, David Shonnard

Michigan Tech Publications

Many actions are underway at global, national, and local levels to increase plastics circularity. However, studies evaluating the environmental and socio-economic impacts of such a transition are lacking at regional levels in the United States. In this work, the existing polyethylene terephthalate and polyolefin plastics supply chains in Michigan were compared to a potential future (‘NextCycle’) scenario that looks at increasing Michigan’s overall recycling rate to 45%. Material flow analysis data was combined with environmental and socio-economic metrics to evaluate the sustainability of these supply chains for the modeled scenarios. Overall, the NextCycle scenario for these supply chains achieved a …

Unbiased Estimation Of Gravitational-Wave Anisotropies From Noisy Data, Nikolaos Kouvatsos, Alexander C. Jenkins, Arianna I. Renzini, Joseph D. Romano, Mairi Sakellariadou

Physics & Astronomy Faculty Publications

One of the most exciting targets of current and future gravitational-wave observations is the angular power spectrum of the astrophysical GW background. This cumulative signal encodes information about the large-scale structure of the Universe, as well as the formation and evolution of compact binaries throughout cosmic time. However, the finite rate of compact binary mergers gives rise to temporal shot noise, which introduces a significant bias in measurements of the angular power spectrum if not explicitly accounted for. Previous work showed that this bias can be removed by cross-correlating GW sky maps constructed from different observing times. However, this …

Supplemental Information. Theoretical Rotational And Vibrational Spectral Data For The Hypermagnesium Oxide Species Mg2o And Mg2o+, Athena R. Flint, Brent R. Westbrook, Ryan C. Fortenberry

Faculty and Student Publications

Tables to accompany a forthcoming article in the journal ChemPhysChem.

Exploring Microplastic Concentrations And The Sedimentology Of San Diego's Offshore Benthic Environments, Rachel Sarner

Theses

Marine pollution studies are showing infiltration of plastic debris in remote parts of oceans including the deep sea. Microplastics (MPs) are being discovered not only in the ocean’s water column but also benthic sediments reaching thousands of meters in depth. This is the first study to analyze MP concentrations in conjunction with sedimentary characteristics from varying deep-sea environments (coastal, deep ocean, offshore terrace) in the Southern California Continental Borderland (CCB). Our goal for this study was to observe how the concentration and type (morphology, color, size) of microplastics varied with distance from shore, with water depth, and between different submarine …

A Deep Learning Framework For Blockage Mitigation In Mmwave Wireless, Ahmed Hazaa Almutairi

Dissertations and Theses

Millimeter-Wave (mmWave) communication is a key technology to enable next generation wireless systems. However, mmWave systems are highly susceptible to blockages, which can lead to a substantial decrease in signal strength at the receiver. Identifying blockages and mitigating them is thus a key challenge to achieve next generation wireless technology goals, such as enhanced mobile broadband (eMBB) and Ultra-Reliable and Low-Latency Communication (URLLC). This thesis proposes several deep learning (DL) frameworks for mmWave wireless blockage detection, mitigation, and duration prediction. First, we propose a DL framework to address the problem of identifying whether the mmWave wireless channel between two devices …

Abundance, Distribution, And Diversity Of The Paralarval Cephalopod Community In The Northern Gulf Of Mexico, Shannon Leah Riley

USF Tampa Graduate Theses and Dissertations

The abundance, distribution, and diversity of cephalopod paralarvae from the upper water column (0-130 meters) in the northern Gulf of Mexico (GOM) was studied using samples collected during six ichthyoplankton surveys between 2009 and 2012. A total of 2240 cephalopod paralarvae belonging to 21 families were examined. Octopodidae, Enoploteuthidae, and Ommastrephidae were the most abundant taxa collected in the time series. Five taxa had significantly different abundances between some sampling periods, while no significant differences in abundance occurred between any GOM regions (northwest GOM shelf, north-central GOM shelf, West Florida Shelf, GOM slope, and GOM basin). The majority of taxa …

Geochemistry And Geochronology Of The Steens And Monument Dike Swarm: Implications And Relationships To Magmatic Storage And To Lava Flows Of The Picture Gorge And Steens Basalt, Rachel Anne Sweeten

Dissertations and Theses

The Columbia River Basalt Group (CRBG) is the youngest and best-preserved example of a continental flood basalt province. Vents and dikes for the four main eruptive units (Steens, Imnaha, Grande Ronde, and Picture Gorge Basalt) are the Monument, Steens and Chief Joseph Dike Swarms located in eastern Oregon, southeastern Washington, and northern Nevada.

Here we report on the compositions and timing of the dikes and sills of the Monument Dike Swarm (MDS), as well as their relationship to the subaerial lava flows of the Picture Gorge Basalt (PGB) with implications for crustal storage of these magmas. We evaluate data from …

Ankle Mobility And Balance In A Healthy College-Aged Population: A Correlational Study, Anna G. Johnson, Madelyn M. Roiger, Elisa M. Stewart

Applied Health Sciences Student Works

A review of current literature shows a relationship between ankle mobility and balance in an older population, with limited evidence in younger, healthy populations. To bridge this gap, this study aims to explore this relationship in a healthy, college-aged population. Maintaining upright balance is an integrated effort by the vestibular, somatosensory, and visual systems. Regaining a loss of balance happens with three strategies: an ankle strategy for small perturbations, a hip strategy for moderate perturbations, and a stepping strategy for the largest loss to regain a new base of support. Taking these sequential responses into account, the investigators specifically looked …

Optical Transport Of Ultracold Atoms, David Vera

Undergraduate Honors Theses

At temperatures near absolute zero, bosons form a macroscopic quantum state that can be manipulated and imaged in a very controlled and tunable way. To reach these extreme temperatures near absolute zero, advanced methods in cooling, including laser and evaporative cooling, must be used. In addition to these techniques for cooling, atoms must also be held up against the constant pull of gravity, so additional trapping techniques using lasers and magnets are used. In our lab at University of San Diego, we are implementing a tunable lens system (TLS) to optically transfer atoms to a more optically accessible location. A …

Big Life-Science: Study Of Omics From Microscopic To Mesoscopic Scales, Jiarui Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The human genome project at the turn of the century opened a new era of life science research and formed various omics characterized by holistic high-throughput research. The initial omics research was mainly carried out at the molecular level, such as genomics, transcriptomics, proteomics, etc., showing a new paradigm of data-driven research. With the development of research technologies, the omics research has risen to the mesoscopic level, the representative is the “Human Cell Atlas” project launched in 2017. At present, researchers have been able to carry out omics research at the level of tissues, organs, and even individuals, and resulted …

Progress And Challenges Of Sustainable Development Goals (Sdgs) In The World And In China, Bojie Fu, Junze Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Achieving the 17 Sustainable Development Goals (SDGs) adopted by United Nations is a critical task for countries around the world from 2016 to 2030. Yet, recent assessments indicate that progress on half of the SDGs has stagnated or even regressed, and that most goals are unlikely to be met by 2030. This study reviews the progress globally and in China towards achieving the 17 SDGs, and summarizes five key challenges that are impinging their realization: 1) the data gaps and insufficient monitoring capacity, 2) the high complexity of interlinkages among the SDGs, 3) the influence of regional disparities and negative …

New Frontier In Race For Deep Space Exploration: Lunar Water Resources, Yong Wei, Honglei Lin, Fei He, Hui Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep space exploration has become the commanding heights of science and technology competition. Since the beginning of the 21st century, China has successfully completed the lunar exploration missions of “orbiting, landing, and returning” in just twenty years, and upgraded to a new roadmap of “survey, construction, and utilization”. Meanwhile, lunar exploration worldwide has shown a trend towards normalization and commercialization. The research on lunar water resources has sparked widespread interest and intense competition among countries and space agencies, marking a new focus in human’s deep space exploration. The exploration of lunar water can help reveal crucial processes in the formation …

Advances In Data-Driven Life Sciences Research, Haiping Jiang, Chunchun Gao, Wenhao Liu, Yungui Yang, Xin Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

The field of life sciences is rapidly evolving, driven by advancements in experimental techniques and vast biological big data which gradually arise and play an increasingly important role in life science research. First of all, biological big data has diversity and complexity, including genomic data, epigenomic data, proteomic data and other types. These data provide researchers with more comprehensive information and help reveal the laws behind life phenomena. Second, new data-driven developments and applications in life sciences cover many fields such as gene editing, precision medicine, drug development, etc., providing unprecedented possibilities for human health and quality of life. However, …

Chm110 Principles Of Chemistry Lecture Slides, Leah S. Cohen

Open Educational Resources

These modified slides contain information from the first ten chapters from the General, Organic, and Biochemistry: connecting Chemistry to Your Life textbook by Blei & Odian.

Unveiling Anomalies: A Survey On Xai-Based Anomaly Detection For Iot, Esin Eren, Feyza Yildirim Okay, Suat Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, the rapid growth of the Internet of Things (IoT) has raised concerns about the security and reliability of IoT systems. Anomaly detection is vital for recognizing potential risks and ensuring the optimal functionality of IoT networks. However, traditional anomaly detection methods often lack transparency and interpretability, hindering the understanding of their decisions. As a solution, Explainable Artificial Intelligence (XAI) techniques have emerged to provide human-understandable explanations for the decisions made by anomaly detection models. In this study, we present a comprehensive survey of XAI-based anomaly detection methods for IoT. We review and analyze various XAI techniques, including …

Text-To-Sql: A Methodical Review Of Challenges And Models, Ali Buğra Kanburoğlu, Faik Boray Tek

Turkish Journal of Electrical Engineering and Computer Sciences

This survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English …

Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou

Turkish Journal of Electrical Engineering and Computer Sciences

Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node …

Dpafy-Gcaps: Denoising Patch-And-Amplify Gabor Capsule Network For The Recognition Of Gastrointestinal Diseases, Henrietta Adjei Pokuaa, Adeboya Felix Adekoya, Benjamin Asubam Weyori, Owusu Nyarko-Boateng

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning (DL) models have performed tremendously well in image classification. This good performance can be attributed to the availability of massive data in most domains. However, some domains are known to have few datasets, especially the health sector. This makes it difficult to develop domain-specific high-performing DL algorithms for these fields. The field of health is critical and requires accurate detection of diseases. In the United States Gastrointestinal diseases are prevalent and affect 60 to 70 million people. Ulcerative colitis, polyps, and esophagitis are some gastrointestinal diseases. Colorectal polyps is the third most diagnosed malignancy in the world. This …

Joint Control Of A Flying Robot And A Ground Vehicle Using Leader-Follower Paradigm, Ayşen Süheyla Bağbaşi, Ali Emre Turgut, Kutluk Bilge Arikan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a novel control framework for the collaboration of an aerial robot and a ground vehicle that is connected via a taut tether is proposed. The framework is based on a leader-follower paradigm. The leader follows a desired trajectory while the motion of the follower is controlled by an admittance controller using an extended state observer to estimate the tether force. Additionally, a velocity estimator is also incorporated to accurately assess the leader’s velocity. An essential feature of our system is its adaptability, enabling role switching between the robots when needed. Furthermore, the synchronization performance of the robots …

Stereo-Image-Based Ground-Line Prediction And Obstacle Detection, Emre Güngör, Ahmet Özmen

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, vision systems have become essential in the development of advanced driver assistance systems or autonomous vehicles. Although deep learning methods have been the center of focus in recent years to develop fast and reliable obstacle detection solutions, they face difficulties in complex and unknown environments where objects of varying types and shapes are present. In this study, a novel non-AI approach is presented for finding the ground-line and detecting the obstacles in roads using v-disparity data. The main motivation behind the study is that the ground-line estimation errors cause greater deviations at the output. Hence, a novel …

Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …

05.20.2024 Orsp Connect, Liz Williamson

ORED Newsletter

NIH RPPR Update (Research Performance Progress Report)

A Computational Framework For Consciousness: Integrating Quantum Mechanics And Integrated Information Theory, Allie Ellis

Undergraduate Honors Theses

Integrated Information Theory (IIT) provides a rigorous mathematical framework for consciousness, defining it by a system’s intrinsic causal power, quantified by the integrated information (Φ). A central obstacle to testing IIT is the prohibitive computational complexity of calculating Φ, which scales exponentially with system size. This work investigates whether efficient computational techniques from quantum information theory, specifically tensor network contractions, can be adapted to approximate key structural properties of IIT without directly computing the full Φ. We developed a classical model of 8-node networks with binary states, characterized by their Transition Probability Matrices (TPMs). For these systems, we constructed corresponding …

Signer-Independent Sign Language Recognition With Feature Disentanglement, İnci̇ Meli̇ha Baytaş, İpek Erdoğan

Turkish Journal of Electrical Engineering and Computer Sciences

Learning a robust and invariant representation of various unwanted factors in sign language recognition (SLR) applications is essential. One of the factors that might degrade the sign recognition performance is the lack of signer diversity in the training datasets, causing a dependence on the singer’s identity during representation learning. Consequently, capturing signer-specific features hinders the generalizability of SLR systems. This study proposes a feature disentanglement framework comprising a convolutional neural network (CNN) and a long short-term memory (LSTM) network based on adversarial training to learn a signer-independent sign language representation that might enhance the recognition of signs. We aim to …

Generalizing Parkinson’S Disease Detection Using Keystroke Dynamics: A Self-Supervised Approach, Luca Giancardo

Faculty, Staff and Student Publications

Objective: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability.

Materials and methods: We propose a new type of self-supervised loss combining Barlow Twins loss, which attempts to create similar feature representations with reduced …