Physical Sciences and Mathematics Commons^™

Decreased Moderate To Vigorous Physical Activity Levels In Children With Asthma Are Associated With Increased Traffic-Related Air Pollutants, Juan Aguilera, Soyoung Jeon, Amit U. Raysoni, Wen-Whai Li, Leah D. Whigham

School of Earth, Environmental, & Marine Sciences Faculty Publications

People with asthma, particularly young children, are more adversely aected by trac emissions-and regular exercise reduces asthma symptoms and improves lung function. We studied the relationship between air pollution and objectively measured physical activity in children with asthma who were attending a school near a freeway. We continuously monitored air pollutants-PM2.5, PM10, nitrogen dioxide (NO2), and ozone (O3)-at the school for 10 weeks and measured physical activity levels via accelerometry in children (n = 12, ages 6-12 years). Concentrations of PM2.5, PM10, and NO2 were negatively associated with moderate to vigorous physical activity (PM2.5 and PM10: p < .001; NO2: p = …

Oxygen And Hydrogen Isotopic Evidence That KamaʻEhuakanaloa (LōʻIhi) Seamount Hydrothermal Systems Are Recharged By Deep Pacific Seawater, Eric W. Chan, Brianna A. Alanis, Christopher R. German, Darlene S. S. Lim, John A. Breier

School of Earth, Environmental, & Marine Sciences Faculty Publications

We observed negative and positive δ18O and δ2H deviations from fluids collected at Kamaʻehuakanaloa (previously known as Lōʻihi) seamount relative to Pacific seawater from the same depth. Hydrothermal vents on the crater floor of Pele's Pit at Kamaʻehuakanaloa, at a depth of 1320 m, had δ18O and δ2H values as low as −0.19‰ and −0.3‰, respectively. Seawater collected within the caldera, within a zone 45 m above the crater floor, had δ18O and δ2H values as high as 1.15‰ and 6.5‰, respectively. In comparison, Pacific seawater at 1200 m and 1400 m at nearby station ALOHA exhibit intermediate δ18O and …

A Convolutional Neural Network Based Approach To Study The Gravitational Waves From Core-Collapse Supernovae In Ligo's Third Observation Run: Detection Efficiency And Parameter Estimation, Bhawana Sedhai

Theses and Dissertations

Core-Collapse Supernova (CCSN) is one of the most anticipated sources of Gravitational Waves (GW) arriving at the advanced LIGO detectors during the fourth observation run (O4). CCSN are rare, weak and unmodeled having a very low rate of occurrence in our galaxy (estimated 2 per century). Thus, detection of GW from CCSN is a challenging problem. An analysis pipeline used in this study is Multi-Layer Signal Enhancement with cWB and CNN or MuLaSEcC that combines Machine Learning methods with a network of Gravitational Wave detectors to identify and reconstruct signals from core collapse supernovae, while minimizing false alarms through the …

Cadmium And Salinity Stressor Antagonism On Vallisneria Neotropicalis, Christopher P. Mikolaitis

Graduate Theses and Dissertations (2019 - present)

Submerged macrophytes form the foundation of freshwater ecosystems. These organisms are sessile and are very susceptible to shifts in their environment. Heavy metals are of particular concern as they can be sequestered indefinitely in sediments and are readily taken up by rooted vegetation. In the presence of saltwater intrusions, these metals can interact with salt ions potentially changing their availability to submerged vegetation. In this study a freshwater macrophyte, Vallisneria neotropicalis, was used as a test species for interactive effects between Cd, a non-essential heavy metal, and salt stress. The metrics used to establish the individual as well as …

State Of The Fisheries: Status Reports And Aquatic Resources Of Western Australia 2021/22, Department Of Primary Industries And Regional Development, Western Australia, S J. Newman, B S. Wise, K G. Santaro, D J. Gaughan

Status Reports of the Fisheries and Aquatic Resources

Aquatic resources within Western Australia (WA) are in good condition, and this has positioned WA as a global leader in sustainable fisheries management. The sustainable fisheries of WA continue to support our strong economy and regional communities. Nonetheless, the lack of a consistent approach to build in the knowledge of Traditional Owners remains a gap in our longer-term fisheries science in Western Australia.

Climate change and climate variability continues to impact fish stocks, challenging our ability to effectively monitor, assess, and manage fish stocks. We are continually working with our stakeholders, and the broader community to be adaptive, responsive, and …

Mapping, Intensities And Future Prediction Of Land Use/Land Cover Dynamics Using Google Earth Engine And Ca- Artificial Neural Network Model, Maysoon A.A. Osman, Elfatih M. Abdel-Rahman, Joshua Orungo Onono, Lydia A. Olaka, Muna M. Elhag, Marian Adan, Henri E.Z. Tonnang

All Peer-Reviewed Publications

Mapping of land use/ land cover (LULC) dynamics has gained significant attention in the past decades. This is due to the role played by LULC change in assessing climate, various ecosystem functions, natural resource activities and livelihoods in general. In Gedaref landscape of Eastern Sudan, there is limited or no knowledge of LULC structure and size, degree of change, transition, intensity and future outlook. Therefore, the aims of the current study were to (1) evaluate LULC changes in the Gedaref state, Sudan for the past thirty years (1988–2018) using Landsat imageries and the random forest classifier, (2) determine the underlying …

Institute For Global Health And Development : Issue 5 - July 2023, Institute For Global Health And Development

IGHD Newsletters

• Research Highlights
• Key Publications
• IGHD in the News
• Webinars, Academics & Conferences
• ‘Choice’ Programme - Technical Advisory Group
• Welcome New Team Members
• Mark your Calendars: Upcoming Event
• Congratulations Team IGHD
• Collaborate With Us

Fast Inference Of Genetic Recombination Rates In Biobank Scale Data

Faculty, Staff and Student Publications

Although rates of recombination events across the genome (genetic maps) are fundamental to genetic research, the majority of current studies only use one standard map. There is evidence suggesting population differences in genetic maps, and thus estimating population-specific maps, are of interest. Although the recent availability of biobank-scale data offers such opportunities, current methods are not efficient at leveraging very large sample sizes. The most accurate methods are still linkage disequilibrium (LD)-based methods that are only tractable for a few hundred samples. In this work, we propose a fast and memory-efficient method for estimating genetic maps from population genotyping data. …

Weakly Supervised Spatial Relation Extraction From Radiology Reports

Faculty, Staff and Student Publications

OBJECTIVE: Weak supervision holds significant promise to improve clinical natural language processing by leveraging domain resources and expertise instead of large manually annotated datasets alone. Here, our objective is to evaluate a weak supervision approach to extract spatial information from radiology reports.

MATERIALS AND METHODS: Our weak supervision approach is based on data programming that uses rules (or labeling functions) relying on domain-specific dictionaries and radiology language characteristics to generate weak labels. The labels correspond to different spatial relations that are critical to understanding radiology reports. These weak labels are then used to fine-tune a pretrained Bidirectional Encoder Representations from …

Multi-Task Learning With Dynamic Re-Weighting To Achieve Fairness In Healthcare Predictive Modeling, Xiaoqian Jiang, Kai Zhang

Faculty, Staff and Student Publications

The emphasis on fairness in predictive healthcare modeling has increased in popularity as an approach for overcoming biases in automated decision-making systems. The aim is to guarantee that sensitive characteristics like gender, race, and ethnicity do not influence prediction outputs. Numerous algorithmic strategies have been proposed to reduce bias in prediction results, mitigate prejudice toward minority groups and promote prediction fairness. The goal of these strategies is to ensure that model prediction performance does not exhibit significant disparity among sensitive groups. In this study, we propose a novel fairness-achieving scheme based on multitask learning, which fundamentally differs from conventional fairness-achieving …

Authenticated Public Key Elliptic Curve Based On Deep Convolutional Neural Network For Cybersecurity Image Encryption Application, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek M. Hassan

Research outputs 2022 to 2026

The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE …

Life Cycle Assessment Of Calcium Oxide Pretreatment Of Corn Stover With Carbon Dioxide Neutralization For Ethanol Production, Jikai Zhao, Danyi Feng, Juhee Lee

School of Earth, Environmental, & Marine Sciences Faculty Publications

This work used life-cycle assessment (LCA) to determine the environmental and human health impacts of four ethanol production scenarios (S1: CaO pretreatment + H2SO4 neutralization + C6 yeast fermentation; S2: CaO pretreatment + CO2 neutralization + C6 yeast fermentation; S3: CaO pretreatment + H2SO4 neutralization + C6/C5 yeast fermentation; and S4: CaO pretreatment + CO2 neutralization + C6/C5 yeast fermentation), with the functional unit being 1 kg of 95 % ethanol. The LCA results showed that the total ozone depletion, global warming potential, smog, acidification, eutrophication, and ecotoxicity values were comparable when CO2 or H2SO4 were used to adjust the …

Self-Healing In Cyber–Physical Systems Using Machine Learning: A Critical Analysis Of Theories And Tools, Obinna Johnphill, Ali Safaa Sadiq, Feras Al-Obeidat, Haider Al-Khateeb, Mohammed Adam Taheir, Omprakash Kaiwartya, Mohammed Ali

All Works

The rapid advancement of networking, computing, sensing, and control systems has introduced a wide range of cyber threats, including those from new devices deployed during the development of scenarios. With recent advancements in automobiles, medical devices, smart industrial systems, and other technologies, system failures resulting from external attacks or internal process malfunctions are increasingly common. Restoring the system’s stable state requires autonomous intervention through the self-healing process to maintain service quality. This paper, therefore, aims to analyse state of the art and identify where self-healing using machine learning can be applied to cyber–physical systems to enhance security and prevent failures …

Analyzing Taxi Drivers’ Decision-Making And Recommending Strategies For Enhanced Performance: A Data-Driven Approach, Mengyu Ji

Dissertations and Theses Collection (Open Access)

This thesis focuses on analyzing the decision-making process of taxi drivers and providing data-driven strategies to enhance their performance. By examin- ing comprehensive historical data encompassing passenger demand patterns, drivers’ spatial dynamics, and fare structures, valuable insights are gained into drivers’ choices regarding optimal routes, timing, and areas with high demand. Integrating real-time information sources, such as GPS data and passenger updates, allows drivers to adapt their strategies dynamically to changing traffic conditions and emerging demand patterns. Predictive analytics models, includ- ing ARIMA, XGBoost, and Linear Regression, are utilized to forecast demand flow at key locations, enabling proactive decision-making and …

Reinforcement Learning For Sequential Decision Making With Constraints, Jiajing Ling

Dissertations and Theses Collection (Open Access)

Reinforcement learning is a widely used approach to tackle problems in sequential decision making where an agent learns from rewards or penalties. However, in decision-making problems that involve safety or limited resources, the agent's exploration is often limited by constraints. To model such problems, constrained Markov decision processes and constrained decentralized partially observable Markov decision processes have been proposed for single-agent and multi-agent settings, respectively. A significant challenge in solving constrained Dec-POMDP is determining the contribution of each agent to the primary objective and constraint violations. To address this issue, we propose a fictitious play-based method that uses Lagrangian Relaxation …

Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han

Mathematics and Statistics Faculty Research & Creative Works

This paper presents fully kinetic particle simulations of plasma charging at lunar craters with the presence of lunar lander modules using the recently developed Parallel Immersed-Finite-Element Particle-in-Cell (PIFE-PIC) code. The computation model explicitly includes the lunar regolith layer on top of the lunar bedrock, taking into account the regolith layer thickness and permittivity as well as the lunar lander module in the simulation domain, resolving a nontrivial surface terrain or lunar lander configuration. Simulations were carried out to study the lunar surface and lunar lander module charging near craters at the lunar terminator region under mean and severe plasma environments. …

Logarithmic Terms In Atom-Surface Potentials: Limited Applicability Of Rational Approximations For Intermediate Distance, Ulrich D. Jentschura, C. Moore

Physics Faculty Research & Creative Works

It is usually assumed that interaction potentials, in general, and atom-surface potential, in particular, can be expressed in terms of an expansion involving integer powers of the distance between the two interacting objects. Here, we show that, in the short-range expansion of the interaction potential of a neutral atom and a dielectric surface, logarithms of the atom-wall distance appear. These logarithms are accompanied with logarithmic sums over virtual excitations of the atom interacting with the surface in analogy to Bethe logarithms in quantum electrodynamics. We verify the presence of the logarithmic terms in the short-range expansion using a model problem …

Galaxy Clustering In The Mira-Titan Universe. I. Emulators For The Redshift Space Galaxy Correlation Function And Galaxy-Galaxy Lensing, Juliana Kwan, Shun Saito, Alexie Leauthaud, Katrin Heitmann, Salman Habib, Nicholas Frontiere, Hong Guo, Song Huang, Adrian Pope, Sergio Rodriguéz-Torres

Physics Faculty Research & Creative Works

We construct accurate emulators for the projected and redshift space galaxy correlation functions and excess surface density as measured by galaxy-galaxy lensing, based on halo occupation distribution modeling. Using the complete Mira-Titan suite of 111 N-body simulations, our emulators vary over eight cosmological parameters and include the effects of neutrino mass and dynamical dark energy. We demonstrate that our emulators are sufficiently accurate for the analysis of the Baryon Oscillation Spectroscopic Survey DR12 CMASS galaxy sample over the range 0.5 ≤ r ≤ 50 h −1 Mpc. Furthermore, we show that our emulators are capable of recovering unbiased cosmological constraints …

Algebraic Approach To Relativistic Landau Levels In The Symmetric Gauge, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We use an algebraic approach to the calculation of Landau levels for a uniform magnetic field in the symmetric gauge with a vector potential A→=12(B→xr→), where B→ is assumed to be constant. The magnetron quantum number constitutes the degeneracy index. An overall complex phase of the wave function, given in terms of Laguerre polynomials, is a consequence of the algebraic structure. The relativistic generalization of the treatment leads to fully relativistic bispinor Landau levels in the symmetric gauge, in a representation which writes the relativistic states in terms of their nonrelativistic limit, and an algebraically accessible lower bispinor component. Negative-energy …

Memory-Multi-Fractional Brownian Motion With Continuous Correlations, Wei Wang, Michał Balcerek, Krzysztof Burnecki, Aleksei V. Chechkin, Skirmantas Janušonis, Jakub Ślȩzak, Thomas Vojta, Agnieszka Wyłomańska, Ralf Metzler

Physics Faculty Research & Creative Works

We propose a generalization of the widely used fractional Brownian motion (FBM), memory-multi-FBM (MMFBM), to describe viscoelastic or persistent anomalous diffusion with time-dependent memory exponent α(t) in a changing environment. In MMFBM the built-in, long-range memory is continuously modulated by α(t). We derive the essential statistical properties of MMFBM such as its response function, mean-squared displacement (MSD), autocovariance function, and Gaussian distribution. In contrast to existing forms of FBM with time-varying memory exponents but a reset memory structure, the instantaneous dynamic of MMFBM is influenced by the process history, e.g., we show that after a steplike change of α(t) the …

Understanding Mitochondrial Dysfunction In Neurodegenerative Diseases Using Novel Neuron Cell Models, Amy Apfelbaum, Anthony Grillo Phd, Raghav Dutta Phd, Alaa Hassan

Annual Student Research Poster Session

This past summer I worked Dr. Anthony Grillo’s lab under my mentors Raghav Dutta and Alaa Hassan at the University of Cincinnati. The Grillo Lab is focused on understanding the mechanisms of mitochondrial complex 1 dysfunction in neurodegenerative diseases. It has been shown that an early feature of neurodegeneration is complex 1 dysfunction; we were trying to determine if this is a cause or an effect of these diseases. This summer, we focused on identifying different types of neuron subtypes in brain tissue samples, isolating primary neurons by first identifying and visualizing the types of brain cells present in brain …

Crosssections, Summer 2023, University Of Northern Iowa. Department Of Physics.

CrossSections

Contents:

A Message from the Department Head, Dr. Paul Shand --- 1
Department Happenings --- 2
Faculty Profile: Andrew Stollenwerk --- 7
Student Profile: Lukas Stuelke --- 8
Student Focus: Jenna Heinen --- 11
Physics Education --- 13
Alumni Profile: Sam Prophet --- 14
Alumni News: Shawn Poellet --- 15
New Physics: Quantum Mechanics Must Be Complex --- 17

Outdoor Performance Of The Black Globe Temperature Sensor On A Hot And Humid Tropical Region, Juan A. Acero, Angela Dissegna, Yon Sun Tan, Adrian Tan, Leslie K. Norford

Research Collection School of Social Sciences

A crucial variable to evaluate thermal comfort is the mean radiant temperature (Tmrt). In this paper we evaluate the performance of the 150 mm black globe thermometer to provide reliable Tmrt values for outdoor settings in Singapore. Accurate Tmrt values are calculated by the method of integral radiation measurements. Based on these, the mean convection coefficient of the black globe has been re-calibrated. Results show an improvement in the estimation of Tmrt with the new coefficient in comparison with the default version suggested in ISO7726:1998. Increasing the averaging periods of the measured variables improved the performance of the derived mean …

Hurricane Impacts On Land In The Central And Eastern Caribbean Since 1494 Ce From Written Records, Michael Chenoweth, Ian Howard

Geosciences Faculty Publications and Presentations

Written accounts of hurricanes and their impacts in the Caribbean region date back to 1494 CE We report a new compilation of hurricanes in the longest settled regions of the central and eastern Caribbean region (CECR) that is the most complete yet produced and present basic statistics. We assess likely undercounts of hurricanes due to incomplete documentary records in the earliest part of the record by using the most complete reporting from Puerto Rico relative to the remainder of the CECR. We compare our results with other documentary and proxy data from the region and demonstrate using wavelet analysis significant …

Forecasting Sea Level Rise-Driven Inundation In Diked And Tidally Restricted Coastal Lowlands, K. M. Befus, A. P.D. Kurnizki, K. D. Kroeger, M. J. Eagle, T. P. Smith

Geosciences Faculty Publications and Presentations

Diked and drained coastal lowlands rely on hydraulic and protective infrastructure that may not function as designed in areas with relative sea-level rise. The slow and incremental loss of the hydraulic conditions required for a well-drained system make it difficult to identify if and when the flow structures no longer discharge enough water, especially in tidal settings where two-way flows occur through the dike. We developed and applied a hydraulic mass-balance model to quantify how water levels in the diked and tidally restricted coastal wetlands and water bodies dynamically respond to sea-level rise, specifically applied to the Herring River Estuary …

The Sound Of Geological Targets On Mars From The Absolute Intensity Of Laser-Induced Sparks Shock Waves, C. Alvarez-Llamas, J. Laserna, J. Moros, P. Purohit, L. García-Gómez, S. M. Angel Ph.D., P. Bernardi, B. Bousquet, A. Cadu, E. Dauson, O. Forni, T. Fouchet, O. Gasnault, X. Jacob, G. Lacombe, N. L. Lanza, C. Larmat, J. Lasue, R. D. Lorenz, P. Y. Meslin, D. Mimoun, F. Montmessin, N. Murdoch, A. M. Ollila, P. Pilleri, N. Randazzo, A. L. Reyes-Newell, S. Schröder, A. Stott, J. Ten Cate, A. Udry, D. Vogt

Faculty Publications

Inspection of geological material is one of the main goals of the Perseverance rover during its journey across the landscape of the Jezero crater in Mars. NASA's rover integrates SuperCam, an instrument capable of performing standoff characterization of samples using a variety of techniques. Among those tools, SuperCam can perform laser-induced breakdown spectroscopy (LIBS) studies to elucidate the chemical composition of the targets of interest. Data from optical spectroscopy can be supplemented by simultaneously-produced laser-produced plasma acoustics in order to expand the information acquired from the probed rocks thanks to the SuperCam's microphone (MIC) as it can be synchronized with …

Dissolved Oxygen Dynamics And Nutrient Cycling In Marine And Lacustrine Benthic Communities, Corrianna R. Boucher

Theses and Dissertations

The delivery of biodetritus to the sediment water interface supports a complex series of biogeochemical reactions collectively referred to as early diagenesis. From the abyssal ocean to littoral freshwater ecosystems, this work explores the dynamics of these reactions in deep ocean detrital aggregates and lacustrine benthic algal mats. In the ocean, periods of increased export flux to abyssal depths increase the organic carbon export as aggregates to the seafloor while in littoral freshwater, proliferations of benthic algae such as Microseira wollei have grown to fill much of the shallow water column they inhabit.

Data collected at Station M (Sta. M) …

Nitrous Oxide Cycling In The Eastern Tropical North Pacific Oxygen Deficient Zone From Concentrations, Stable Isotopes And Isotopomers, Margaret Ann Gaspar

Theses and Dissertations

Nitrous oxide (N₂O) is a potent greenhouse gas and ozone depleting substance. It is estimated that the ocean accounts for about one third of total atmospheric emissions, which mostly occur in Oxygen Deficient Zones (ODZs) connected to coastal upwelling regions. Modeling efforts and high-resolution datasets are starting to provide a clearer picture of global marine N₂O fluxes, spatiotemporal variability, and the impacts of submesoscale processes on N₂O distributions. We measured nitrous oxide concentrations, stable isotope ratios and isotopomers at 7 open ocean stations along a transect crossing the Eastern Tropical North Pacific ODZ as …

Study Of Digital Algan Alloy Based Heterostructures Using Aln/Gan Short Period Superlattice, Mohammad Kamal Hussain

Theses and Dissertations

Ultrawide Bandgap (UWBG) and Extreme Bandgap (EBG) AlxGa1-xN (x > 0.40) alloys with EG > 4.2 eV are potential candidates for high temperature and high voltage applications, compared to Wide Bandgap (WBG) GaN-based lateral channel devices. Since critical electric field (Ec) scales as (Eg)^2.5, theoretically AlGaN alloys can sustain large electric field before breaking down. However, achieving linear ohmic contacts to the 2-dimensional electron gas (2DEG) formed at the interface of AlyGa_1-xN/ Al_xGa_1-xN (y – x ≥ 0.20) High Electron Mobility Transistors (HEMTs) is challenging. Direct contact through the AlGaN barrier is difficult due …

Approaches To Detecting And Modeling Over-And Underdispersion In Alternative Count Data Distributions And An Application Of Logistic Regression And Random Forest Modeling To Improve Screening Tools For Tic Disorders In Children, Rebecca C. Wardrop

Theses and Dissertations

This dissertation focuses on theory and application of discrete data methods, particularly approaches to over- and underdispersion relative to the Poisson distribution and an application of random forest and logistic regression modeling. The first chapter derives a score test for over- and underdispersion in the heaped generalized Poisson distribution. Equi-, over-, and underdispersed heaped generalized Poisson and heaped negative binomial data are simulated to evaluate the performance of the score test by comparing the power it achieves to that of Wald and likelihood ratio tests. We find that the score test we derive performs comparably to both the Wald and …