Physical Sciences and Mathematics Commons^™

The Ability Of Ruppia Polycarpa To Regenerate From Seed Depends On Seasonal Porewater Salinity Dynamics And Declining Winter Rainfall Could Delay Recruitment, Chanelle L. Webster, Paul S. Lavery, Simone Strydom, Jessica Billinghurst, Kathryn Mcmahon

Research outputs 2022 to 2026

For many plants, regeneration from seed is vital for population recovery. Climate change is modifying the global hydrological cycle and a primary factor controlling germination of marine plants: salinity. How altered salinity regimes, and especially altered porewater salinity regimes, will regulate early life history stages of estuarine seagrasses is poorly understood. Here, we quantified the porewater salinity dynamics in two ephemeral estuaries that are dominated by the cosmopolitan genus Ruppia. Seedbank, germlings (germinated seeds) and seedlings were found in salinities ranging from 5 to 110 over an annual cycle. To understand the germination ecology of the dominant species, Ruppia polycarpa, …

Chatgpt In Higher Education: Considerations For Academic Integrity And Student Learning, Miriam Sullivan, Andrew Kelly, Paul Mclaughlan

Research outputs 2022 to 2026

The release of ChatGPT has sparked significant academic integrity concerns in higher education. However, some commentators have pointed out that generative artificial intelligence (AI) tools such as ChatGPT can enhance student learning, and consequently, academics should adapt their teaching and assessment practices to embrace the new reality of living, working, and studying in a world where AI is freely available. Despite this important debate, there has been very little academic literature published on ChatGPT and other generative AI tools. This article uses content analysis to examine news articles (N=100) about how ChatGPT is disrupting higher education, concentrating specifically on Australia, …

Heterogeneous Activation Of Persulfate By Macroscopic Nitrogen-Doped Graphene Oxide Cubes For The Degradation Of Antibiotic Contaminants In Water, Rajan A. K. Hirani, Abdul H. Asif, Nasir Rafique, Lei Shi, Shu Zhang, Martin Saunders, Wenjie Tian, Shaobin Wang, Hongqi Sun

Research outputs 2022 to 2026

As a sustainable and green approach, carbocatalysis, a metal-free strategy, has shown exceptional results in advanced oxidation processes (AOPs). Nonetheless, the recovery of these catalysts has been a major shortcoming over the years. Herein, three-dimensional nitrogen-doped graphene macrostructures (3D-NGMs), in the form of macro cubes, were synthesised by a simple cross-linking and thermal annealing procedure, after which they were employed in the activation of peroxydisulfate (PS) for the degradation of sulfamethoxazole (SMX). The catalytic cubes were loaded with different amounts of nitrogen precursor to investigate the role of nitrogen configuration in the sp2 hybridised carbon network on AOPs. NGC3 cubes …

A Review Of Multi-Factor Authentication In The Internet Of Healthcare Things, Tance Suleski, Mohiuddin Ahmed, Wencheng Yang, Eugene Wang

Research outputs 2022 to 2026

Objective: This review paper aims to evaluate existing solutions in healthcare authentication and provides an insight into the technologies incorporated in Internet of Healthcare Things (IoHT) and multi-factor authentication (MFA) applications for next-generation authentication practices. Our review has two objectives: (a) Review MFA based on the challenges, impact and solutions discussed in the literature; and (b) define the security requirements of the IoHT as an approach to adapting MFA solutions in a healthcare context. Methods: To review the existing literature, we indexed articles from the IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink databases. The search was refined to combinations …

Photocatalytic Reforming Of Lignocellulose: A Review, Xinyuan Xu, Lei Shi, Shu Zhang, Zhimin Ao, Jinqiang Zhang, Shaobin Wang, Hongqi Sun

Research outputs 2022 to 2026

Biomass has been considered as a promising energy resource to combat the exhaustion of fossil fuels, as it is renewable, sustainable, and clean. Photocatalytic reforming is a novel technology to utilize solar energy for upgrading biomass in relatively mild conditions. This process efficiently reforms and recasts biomass into hydrogen and/or valuable chemicals. To date, lignocellulose, including cellulose, hemicellulose and lignin, has attracted extensive studies in facile photocatalytic valorisation. This review summarizes and analyzes the most recent research advances on photoreforming of lignocellulose to provide insights for future research, with a particular emphasis on the reformation of lignin because of its …

Utilizing Proteomics To Identify And Optimize Microalgae Strains For High-Quality Dietary Protein: A Review, Sara Hamzelou, Damien Belobrajdic, James A. Broadbent, Angéla Juhász, Kim L. Chang, Ian Jameson, Peter Ralph, Michelle L. Colgrave

Research outputs 2022 to 2026

Algae-derived protein has immense potential to provide high-quality protein foods for the expanding human population. To meet its potential, a broad range of scientific tools are required to identify optimal algal strains from the hundreds of thousands available and identify ideal growing conditions for strains that produce high-quality protein with functional benefits. A research pipeline that includes proteomics can provide a deeper interpretation of microalgal composition and biochemistry in the pursuit of these goals. To date, proteomic investigations have largely focused on pathways that involve lipid production in selected microalgae species. Herein, we report the current state of microalgal proteome …

Knowledge Organization System For Partial Automation To Improve The Security Posture Of Iomt Networks, Kulsoom Saima Bughio

Research outputs 2022 to 2026

Remote patient monitoring is a healthcare delivery model that uses technology to collect and transmit patient data from a remote location to healthcare providers for analysis and treatment. Remote patient monitoring systems rely on a network infrastructure to gather and transmit data from patients to healthcare providers through a network. While these systems become more prevalent, they may also become targets for cyberattacks. This paper deals with the development of a domain ontology to facilitate partial automation to improve the security posture of IoT networks used in remote patient monitoring. For this purpose, it captures the semantics of the concepts …

A Review Of Cyber Vigilance Tasks For Network Defense, Oliver A. Guidetti, Craig Speelman, Peter Bouhlas

Research outputs 2022 to 2026

The capacity to sustain attention to virtual threat landscapes has led cyber security to emerge as a new and novel domain for vigilance research. However, unlike classic domains, such as driving and air traffic control and baggage security, very few vigilance tasks exist for the cyber security domain. Four essential challenges that must be overcome in the development of a modern, validated cyber vigilance task are extracted from this review of existent platforms that can be found in the literature. Firstly, it can be difficult for researchers to access confidential cyber security systems and personnel. Secondly, network defense is vastly …

Noncovalent Chalcogen And Tetrel Bonding Interactions: Spectroscopic Study Of Halide-Carbonyl Sulfide Complexes, Christian T. Haakansson, Peter D. Watson, Timothy R. Corkish, Hayden T. Robinson, Allan J. Mckinley, Duncan A. Wild

Research outputs 2022 to 2026

Chalcogen and tetrel intermolecular bonding interactions formed between carbonyl sulfide and halide anions have been studied utilizing a combined experimental and theoretical approach. In particular, high-level CCSD(T) energetics and experimental anion photoelectron spectroscopy have been used in order to assign the dominant binding motif exhibited in these complexes. Halide anions solvated by multiple carbonyl sulfide molecules have also been investigated in order to ascertain the effect that additional binding partners has on the strength of the noncovalent interactions. The experimental and computational results support the main binding motif of carbonyl sulfide molecules with halide anions being chalcogen bonding, both in …

The Wacdt, A Modern Vigilance Task For Network Defense, Oliver A. Guidetti, Craig Speelman, Peter Bouhlas

Research outputs 2022 to 2026

Vigilance decrement refers to a psychophysiological decline in the capacity to sustain attention to monotonous tasks after prolonged periods. A plethora of experimental tasks exist for researchers to study vigilance decrement in classic domains such as driving and air traffic control and baggage security; however, the only cyber vigilance tasks reported in the research literature exist in the possession of the United States Air Force (USAF). Moreover, existent cyber vigilance tasks have not kept up with advances in real-world cyber security and consequently no longer accurately reflect the cognitive load associated with modern network defense. The Western Australian Cyber Defense …

Communety: Deep Learning-Based Face Recognition System For The Prediction Of Cohesive Communities, Syed Afaq Ali Shah, Weifeng Deng, Muhammad Aamir Cheema, Abdul Bais

Research outputs 2022 to 2026

Effective mining of social media, which consists of a large number of users is a challenging task. Traditional approaches rely on the analysis of text data related to users to accomplish this task. However, text data lacks significant information about the social users and their associated groups. In this paper, we propose CommuNety, a deep learning system for the prediction of cohesive networks using face images from photo albums. The proposed deep learning model consists of hierarchical CNN architecture to learn descriptive features related to each cohesive network. The paper also proposes a novel Face Co-occurrence Frequency algorithm to quantify …

Long Future Frame Prediction Using Optical Flow Informed Deep Neural Networks For Enhancement Of Robotic Teleoperation In High Latency Environments, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam

Research outputs 2022 to 2026

High latency in teleoperation has a significant negative impact on operator performance. While deep learning has revolutionized many domains recently, it has not previously been applied to teleoperation enhancement. We propose a novel approach to predict video frames deep into the future using neural networks informed by synthetically generated optical flow information. This can be employed in teleoperated robotic systems that rely on video feeds for operator situational awareness. We have used the image-to-image translation technique as a basis for the prediction of future frames. The Pix2Pix conditional generative adversarial network (cGAN) has been selected as a base network. Optical …

Leveraging Machine Learning To Analyze Sentiment From Covid-19 Tweets: A Global Perspective, Md Mahbubar Rahman, Nafiz Imtiaz Khan, Iqbal H. Sarker, Mohiuddin Ahmed, Muhammad Nazrul Islam

Research outputs 2022 to 2026

Since the advent of the worldwide COVID-19 pandemic, analyzing public sentiment has become one of the major concerns for policy and decision-makers. While the priority is to curb the spread of the virus, mass population (user) sentiment analysis is equally important. Though sentiment analysis using different state-of-the-art technologies has been focused on during the COVID-19 pandemic, the reasons behind the variations in public sentiment are yet to be explored. Moreover, how user sentiment varies due to the COVID-19 pandemic from a cross-country perspective has been less focused on. Therefore, the objectives of this study are: to identify the most effective …

Spatial Heterogeneity In Sediment And Carbon Accretion Rates Within A Seagrass Meadow Correlated With The Hydrodynamic Intensity, Jiarui Lei, Rachel Schaefer, Phil Colarusso, Alyssa Novak, Juliet C. Simpson, Pere Masqué, Heidi Nepf

Research outputs 2022 to 2026

The majority of the carbon stored in seagrass sediments originates outside the meadow, such that the carbon storage capacity within a meadow is strongly dependent on hydrodynamic conditions that favor deposition and retention of fine organic matter within the meadow. By extension, if hydrodynamic conditions vary across a meadow, they may give rise to spatial gradients in carbon. This study considered whether the spatial gradients in sediment and carbon accretion rates correlated with the spatial variation in hydrodynamic intensity within a single meadow. Field measurements were conducted in three depth zones across a Zostera marina L. (eelgrass) meadow in Nahant …

Ranking The Risk Of Co2 Emissions From Seagrass Soil Carbon Stocks Under Global Change Threats, Martin Dahl, Kathryn Mcmahon, Paul S. Lavery, Serena H. Hamilton, Catherine E. Lovelock, Oscar Serrano

Research outputs 2022 to 2026

Seagrass meadows are natural carbon storage hotspots at risk from global change threats, and their loss can result in the remineralization of soil carbon stocks and CO2 emissions fueling climate change. Here we used expert elicitation and empirical evidence to assess the risk of CO2 emissions from seagrass soils caused by multiple human-induced, biological and climate change threats. Judgments from 41 experts were synthesized into a seagrass CO2 emission risk score based on vulnerability factors (i.e., spatial scale, frequency, magnitude, resistance and recovery) to seagrass soil organic carbon stocks. Experts perceived that climate change threats (e.g., gradual ocean warming and …

A Cross-Domain Trust Model Of Smart City Iot Based On Self-Certification, Yao Wang, Yubo Wang, Zhenhu Ning, Sadaqat Ur Rehman, Muhammad Waqas

Research outputs 2022 to 2026

Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced …

Identity-Based Edge Computing Anonymous Authentication Protocol, Naixin Kang, Zhenhu Ning, Shiqiang Zhang, Sadaqat Ur Rehman, Muhammad Waqas

Research outputs 2022 to 2026

With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based …

Testing The Affect Of Modified Sense Of Place, Conservation Ethic, And Good Farmer Identity Measures On Predicting The Adoption Of Cover Crops In Working Landscapes In Iowa, Elizabeth A. Bennett, Morey Burnham, Jessica D. Ulrich-Schad, J. Gordon Arbuckle, Weston M. Eaton, Sarah P. Church, Francis R. Eanes, Jennifer Eileen Cross, Matthew A. Williamson

Human-Environment Systems Research Center Faculty Publications and Presentations

While sense of place (SOP) has been used in amenity landscapes to understand pro-environmental behavior, in working landscapes, SOP has not been a valid or reliable predictor for explaining conservation behavior. In this paper, we advance theory on SOP in working landscapes by assessing the relationship between several new and modified sense of place measures and farmer adoption of cover crops in Iowa. We used data from a 2018 survey of Iowa farmers and a Bayesian logistic regression, finding that physical dependence and economic dependence are distinct dimensions of SOP in working landscapes and the addition of a measure beyond …

Towards A Prototype Paleo-Detector For Supernova Neutrino And Dark Matter Detection, Emilie Marie Lavoie-Ingram

UNF Graduate Theses and Dissertations

Using ancient minerals as paleo-detectors is a proposed experimental technique expected to transform supernova neutrino and dark matter detection. In this technique, minerals are processed and closely analyzed for nanometer scale damage track remnants from nuclear recoils caused by supernova neutrinos and possibly dark matter. These damage tracks present the opportunity to directly detect and characterize the core-collapse supernova rate of the Milky Way Galaxy as well as the presence of dark matter. Current literature presents theoretical estimates for these potential tracks, however, there is little research investigating the experimental feasibility of this technique. At the University of North Florida, …

Apparent Contours For Piecewise Smooth Surfaces, Sarah Marie Jackman

UNF Graduate Theses and Dissertations

The set of points on an embedded surface $M$ that are tangent to a set viewing direction $\mathbf{v}$ is called the contour generator of $M$. The projection of those points to an image plane is called a surface's apparent contour. Apparent contours hold certain properties that allow for reconstruction of the original surface using only the information of the apparent contour. In this paper, we explore the structure of the apparent contour through contact classes and singularity types. Additionally we examine the properties of apparent contours that allow for 3 dimensional reconstruction. Our goal is to extend the properties of …

Automated Short-Answer Grading And Misconception Detection Using Large Language Models, Nazmul H. Kazi

UNF Graduate Theses and Dissertations

As education technology continues to evolve, the domains of Automatic Short-Answer Grading (ASAG) and Automated Misconception Detection (AMD) stand at the forefront of innovative approaches to educational assessment. We explore the transformative potential of Large Language Models (LLMs) in revolutionizing these critical areas. Leveraging the remarkable capabilities of LLMs in semantic inference, contextual understanding, and transfer learning, we embark on a comprehensive journey to enhance both ASAG and AMD. On ASAG, we illuminate the efficacy of transfer learning by fine-tuning RoBERTa Large, a state-of-the-art LLM, on task-related corpora, e.g. the Multi-Genre Natural Language Inference (MNLI) corpus. The model's adaptability across …

Improving Connectivity For Remote Cancer Patient Symptom Monitoring And Reporting In Rural Medically Underserved Regions, Esther Max-Onakpoya

Theses and Dissertations--Computer Science

Rural residents are often faced with many disparities when compared to their urban counterparts. Two key areas where these disparities are apparent are access to health and Internet services. Improved access to healthcare services has the potential to increase residents' quality of life and life expectancy. Additionally, improved access to Internet services can create significant social returns in increasing job and educational opportunities, and improving access to healthcare. Therefore, this dissertation focuses on the intersection between access to Internet and healthcare services in rural areas. More specifically, it attempts to analyze systems that can be used to improve Internet access …

A Secure And Distributed Architecture For Vehicular Cloud And Protocols For Privacy-Preserving Message Dissemination In Vehicular Ad Hoc Networks, Hassan Mistareehi

Theses and Dissertations--Computer Science

Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can …

Multi-Domain Adaptation For Image Classification, Depth Estimation, And Semantic Segmentation, Yu Zhang

Theses and Dissertations--Computer Science

The appearance of scenes may change for many reasons, including the viewpoint, the time of day, the weather, and the seasons. Traditionally, deep neural networks are trained and evaluated using images from the same scene and domain to avoid the domain gap. Recent advances in domain adaptation have led to a new type of method that bridges such domain gaps and learns from multiple domains.

This dissertation proposes methods for multi-domain adaptation for various computer vision tasks, including image classification, depth estimation, and semantic segmentation. The first work focuses on semi-supervised domain adaptation. I address this semi-supervised setting and propose …

Debertnext: A Multimodal Fake News Detection Framework, Kamonashish Saha

Electronic Theses and Dissertations

There is a rapid influx of fake news nowadays, which poses an immense threat to our society. Fake news has been impacting us in several ways which include changing our thoughts, manipulating opinions, and also causing chaos due to misinformation. With the ease of access and sharing information on social media platforms, such fake news or misinformation has been spreading in different modalities which include text, image, audio, and video. Although there have been a lot of approaches to detecting fake news in textual format only, however, multimodal approaches are less frequent as it is difficult to fully use the …

Spectral Sequences And Khovanov Homology, Zachary J. Winkeler

Dartmouth College Ph.D Dissertations

In this thesis, we will focus on two main topics; the common thread between both will be the existence of spectral sequences relating Khovanov homology to other knot invariants. Our first topic is an invariant MKh(L) for links in thickened disks with multiple punctures. This invariant is different from but inspired by both the Asaeda-Pryzytycki-Sikora (APS) homology and its specialization to links in the solid torus. Our theory will be constructed from a Z^n-filtration on the Khovanov complex, and as a result we will get various spectral sequences relating MKh(L) to Kh(L), AKh(L), and APS(L). Our …

Oh The Places Snow Blows: Observations And Impacts Of Snow Redistribution On Arctic Sea Ice, David Clemens-Sewall

Dartmouth College Ph.D Dissertations

Arctic sea ice has declined dramatically due to climate change. This decline impacts Arctic communities, ecosystems, international trade, and the world's climate. However, due to uncertain physical processes, climate models generally do not capture the severity of the observed decline---adding uncertainty to projections of future climate change. A major uncertainty in the Arctic sea ice component of climate models is how much heat passes through the snow on top of the ice in the winter. This heat flux controls how much ice grows each winter, impacting how much ice survives the summer melt. Snow is an excellent thermal insulator (about …

Clear: Spatially Resolved Emission Lines And Active Galactic Nuclei At 0.6 < Z < 1.3, Bren E. Backhaus, Joanna S. Bridge, Jonathan R. Trump, Nikko J. Cleri, Casey Papovich, Raymond C. Simons, Ivelina Momcheva, Benne Holwerda, Zhiyuan Ji, Intae Jung, Jasleen Matharu

Faculty and Staff Scholarship

We investigate spatially resolved emission-line ratios in a sample of 219 galaxies (0.6 < z < 1.3) detected using the G102 grism on the Hubble Space Telescope Wide Field Camera 3 taken as part of the CANDELS Lyα Emission at Reionization survey to measure ionization profiles and search for low-luminosity active galactic nuclei (AGN). We analyze [O III] and Hβ emission-line maps, enabling us to spatially resolve the [O III]/Hβ emission-line ratio across the galaxies in the sample. We compare the [O III]/Hβ ratio in galaxy centers and outer annular regions to measure ionization differences and investigate the potential of sources with nuclear ionization to host AGN. We investigate some of the individual galaxies that are candidates to host strong nuclear ionization and find that they often have low stellar mass and are undetected in X-rays, as expected for low-luminosity AGN in low-mass galaxies. We do not find evidence for a significant population of off-nuclear AGN or other clumps of off-nuclear ionization. We model the observed distribution of [O III]/Hβ spatial profiles and find that most galaxies are consistent with a small or zero difference between their nuclear and off-nuclear line ratios, but 6%–16% of galaxies in the sample are likely to host nuclear [O III]/Hβ that is ∼0.5 dex higher than in their outer regions. This study is limited by large uncertainties in most of the measured [O III]/Hβ spatial profiles; therefore, deeper data, e.g., from deeper HST/ WFC3 programs or from JWST/NIRISS, are needed to more reliably measure the spatially resolved emission-line conditions of individual high-redshift galaxies.

Environmental Health Justice Across The Globe, Arnita Gadson, Rochelle H. Holm

Faculty and Staff Scholarship

No abstract provided.

Synthesis And Characterization Of Polymer Grafted Nanoparticles, Eric Gerald Ruzicka

Theses and Dissertations

This dissertation focuses on the design, synthesis, and characterization of well controlled interfaces on nanoparticle surfaces. Reversible addition-fragmentation chain transfer (RAFT) polymerization was used to synthesize block copolymers and polymer grafted silica nanoparticles (PGNs) with precise control over molecular weight, graft density, and architectures.

In the first chapter, polymer molecular weights were determined through diffusion ordered spectroscopy NMR (DOSY NMR) as an alternative to size exclusion chromatography (SEC). Polymer standards of known molecular weight were analyzed through DOSY to obtain their respective diffusion coefficients. A calibration curve was generated correlating diffusion coefficients with polymer molecular weights. The reliability of the …