Physical Sciences and Mathematics Commons^™

Resource Assessment Report No. 05: West Coast Deep Sea Crustacean Resource 2024 Assessment, Emma-Jade Tuffley, Simon De Lestang

Resource Assessment Reports

The West Coast Deep Sea Crustacean resource consists of crystal crab (snow) (Chaceon albus), champagne crab (spiny) (Hypothalassia acerba) and giant crab (Pseudocarcinus gigas). The resource is mainly accessed by the commercial West Coast Deep Sea Crustacean Managed Fishery (WCDSCMF), which primarily targets crystal crabs. The West Coast Rock Lobster Managed Fishery (WCRLMF) also retains a small amount of champagne crabs as byproduct of deep-water rock lobster fishing. The WCDSCMF is a pot-based fishery using baited pots operated in a long-line formation in shelf edge waters ( > 150 m in depth) off the West …

Resource Assessment Report No. 03: Gascoyne Demersal Scalefish Resource 2024 Assessment, Emily A. Fisher, Rachel Marks, Sybrand A. Hesp, Ainslie Denham, Gary Jackson, David V. Fairclough

Resource Assessment Reports

The Gascoyne Demersal Scalefish Resource (GDSR) comprises over 80 species inhabiting inshore (20-250 m deep) and offshore ( > 250 m deep) waters in the Gascoyne Coast Bioregion (GCB; south of Onslow to north of Kalbarri). The GDSR is primarily targeted by commercial, charter and recreational boat-based line fishers. Snapper and Goldband Snapper are the indicator species selected for monitoring and assessing the status of the inshore suite of the GDSR, while Ruby Snapper and Greybanded Grouper are the indicators for the offshore suite.

Periodic assessments of GDSR indicator species demonstrated that historical fishing of Snapper led to stocks being below …

Resource Assessment Report No. 04: North Coast Demersal Scalefish Resource - Kimberley 2025 Assessment, Fabian Trinnie, Rubie Evans-Powell, Ainslie Denham, Sybrand A. Hesp, Corey Wakefield, Craig L. Skepper, Brett Crisafulli, Stephen J. Newman

Resource Assessment Reports

The North Coast Demersal Scalefish Resource (NCDSR) comprises ecological suites of tropical demersal fish species that occur predominantly in inshore waters (20–250 m deep) and offshore waters ( > 250 m deep) of the North Coast Bioregion (NCB). More than 60 demersal species are landed by fisheries operating in the Kimberley and Pilbara regions of the NCB each year, including high-value snappers (Lutjanidae), groupers (Epinephelidae), and emperors (Lethrinidae). As outlined in the NCDSR Harvest Strategy (DPIRD, 2017), the Kimberley resource is currently monitored through annual reviews of total removals and catch rate trends of indicator species, as well as periodic (every …

Mentors The Hidden Beneficiaries Of Mentoring, Mona Behl, Sarah Clem, Colleen Mouw, Sonya Legg, Erin Hackett, Kristin Burkholder, Kristopher B. Karnauskas, Sarah T. Gille, Lauren A. Freeman, Karan Venayagamoorthy, Jerry L. Miller

Marine Science

The community-based mentorship program MPOWIR (Mentoring Physical Oceanography Women+ to Increase Retention) supports late-stage graduate students and early-career professionals who identify as women or non-binary genders. Its participants engage in mentorship training and professional development, facilitate group mentoring, and draw attention to barriers women and non-binary genders face in physical oceanography. MPOWIR was created to increase the retention of women in physical oceanography in early career stages but has unexpectedly benefited the MPOWIR community beyond graduate students and early career professionals. Senior leaders participating as mentors in MPOWIR report a renewed sense of purpose, new research collaborations, a chance to …

Long-Term Patterns In The Relative Abundance Of Common Snook As A Factor Of Shifting Environmental Conditions In The Florida Coastal Everglades, Jordan A. Massie, Ryan J. Rezek, Rolando O. Santos, W. Ryan James, Natasha M. Viadero, Ross E. Boucek, Jennifer S. Rehage

Marine Science

Objective Environmental variability as a factor of climate change and water management can result in fluctuations in the abundance and distribution of fish populations from year to year, with either negative or positive effects depending on behavioral and physiological requirements and the ability to adapt to changing conditions. Variability in water levels can also influence prey availability, affecting predator abundance in seasonal foraging areas. In this study, our objective was to better understand how environmental variation has affected the relative abundance of Common Snook Centropomus undecimalis in the freshwater/estuarine habitats of Everglades National Park. Methods Electrofishing data over 17 years …

Linking Hydrology, Temperature, And Energetics: Global Change Implications For The Foraging Ecology Of A Generalist Predator, Mack White, W. Ryan James, Justin S. Lesser, Ryan J. Rezek, Jonathan R. Rodemann, Ross E. Boucek, Rolando O. Santos, Jennifer S. Rehage

Marine Science

Objective: The objective of this study was to quantify the effects of temperature, hydrology, and body size on the diet and energy requirements of a generalist predator, Common Snook Centropomus undecimalis (hereafter, “snook”), to gain a better understanding of predator–prey dynamics in the wake of global change. We first ask how temperature, hydrology, and body size influence the occurrence of fish, invertebrates, and empty stomachs in the diet of snook. Next, we model the energetic requirements of snook as a function of body size and temperature. Last, we use predation simulations to test how changes in prey quality, together with …

Quantification Of Terpenes In Various Commercial Cannabis Products By Gas Chromatography-Flame Ionization Detection And Gas Chromatography-Mass Spectrometry, Kaitlyn M. Ignaszak

Forensic Science Master's Projects

The goal of this research project was to identify and quantify the terpenes in five commercial cannabis products (dried bud, kief, two tinctures, and a pain cream) using gas chromatography-flame ionization detection (GC-FID) and gas chromatography-mass spectrometry (GC-MS). Terpene identification and quantification were conducted using GC-MS and GC-FID, with a standard sample containing 21 terpenes of known concentrations. To determine the most effective extraction conditions, three organic solvents (ethanol, acetonitrile, and ethyl acetate) were employed. Additionally, the effects of extraction time on terpene yield were investigated by analyzing aliquots collected at five different time intervals, ranging from one hour to …

Ibi-Dt: A Novel Approach Combining Individualized Bayesian Inference And Decision Tree For Identifying Cancer Drivers And Their Interactions, Md Asad Rahman, Gregory F. Cooper, Jinying Zhao, Xinghua Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cancer is mainly caused by a relatively small portion of somatic genome alterations (SGAs), called cancer drivers. Despite success in identifying a good number of cancer drivers, many more remain to be discovered to explain various cancers. Moreover, limited tools are available to identify potential interactions among cancer drivers for a better understanding of oncogenesis. To tackle these challenges, we have developed a novel approach called individualized Bayesian inference using a decision tree (IBI-DT). IBI-DT recognizes the genetic heterogeneity among cancer patients, where different individuals or patient subgroups of distinct genomic makeup may have different drivers. IBI-DT works by constructing …

Synergetic Adsorptive Mechanisms, Reusability And Cost Evaluations Of Green Fabricated Hybrid Barium Cobalt Nanocomposites For Methylene Blue And Lead Removal From Wastewater, Titus Chinedu Egbosiuba, Chibuike Christogonus Njoku, Ijeoma Jacinta Ani, Godwin Ifeanyi Ogbuehi, Abdulkareem Omeiza Yusuf, Abiodun Azeez Saka, Ugochukwu Ewuzie, Ebuka Emmanuel Ezennajiego, Blessing Onyinye Okafor, Walter Chibuike Anene, Cecilia Chika Unegbu, Florence Acha, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

Barium nanoparticles (BaNPs), cobalt nanoparticles (CoNPs), and hybrid barium-cobalt nanocomposites (BaCoNCs) were synthesized using an eco-friendly green technique with Anacardium occidentale leaf extract for sequestration of methylene blue (MB) dye and lead (Pb (II)) ions from industrial wastewater. The nanoparticles and nanocomposites were characterized using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), high-resolution scanning electron microscopy (HRSEM), and Brunauer-Emmett-Teller (BET) analysis to assess their functional groups, crystalline structure, morphology, and surface properties, confirming successful synthesis. Batch adsorption studies showed that optimal pollutant removal occurred at pH values of 8 for MB and 5 for Pb(II), with a contact time …

The Floodnet Community Engagement Guide, Véronëque Ignace, Sofia Mariyamis, Kendra Krueger, Polly Pierone, Hayley Elszasz, Hannah Eisler Burnett

The Science and Resilience Institute at Jamaica Bay, SRIJB

"At the Intersection of Science, Policy, and Community: The FloodNet NYC Community Engagement Strategy” is a public-facing community engagement guide that documents the strategies, tools, and lessons developed through FloodNet NYC, a cross-sector partnership among researchers at NYU and CUNY and New York City agencies. Designed as a practical resource, this guide shares our approach to community engagement and dissemination so that researchers, practitioners, community organizations, and public agencies can adapt these methods to their own urban climate science projects and other community-centered efforts that address climate challenges.

Grounded in community-based participatory research (CBPR) principles, the guide presents community engagement …

(Si15-068) Advanced Numerical Methods For The Solution Of Nonlinear Fisher Equation, Vikash Vimal, Richa Kumari, Ashish Awasthi

Applications and Applied Mathematics: An International Journal (AAM)

This paper examines the use of advanced numerical techniques to approximate solutions of the Fisher equation with higher-order accuracy. This technique integrates the method of lines with a strong stability-preserving Runge–Kutta scheme of orders four and five stages (SSPRK-54) for the numerical formulation. This scheme is then tested on two examples and the results show that it is more efficient than existing methods and requires less computing power. These equations are widely used across scientific and engineering disciplines, with particular relevance in biomedical studies, such as estimating the boundary size of tumors. The difficulties arising from their nonlinear nature are …

Procedures For Rangeland Condition Assessment In The Pilbara And Southern Rangelands 2025, Department Of Primary Industries And Regional Development, Western Australia

Natural resources published reports

This report defines the procedures used in 2025 by DPIRD to complete rangeland condition assessment (RCA) in the Pilbara and southern rangelands region which has predominantly shrub-based pastures. For the rest of the pastoral estate, DPIRD uses the Procedures for RCA in the Kimberley which has grass pastures.

RCA is the process DPIRD uses to make systematic, station-level assessment of rangeland. Rangeland condition considers both the condition of pastures (defined in the ‘Pasture condition guides for the Pilbara’ and ‘Pasture condition guides for the southern rangelands including the Gascoyne, Murchison and Goldfields-Nullarbor’) and soils as determined by erosion, using the …

Multi-Modal Depth Estimation Using Camera And Mmwave Sensors, Alston D. Devero-Belfon

Student Theses

For accurately estimating the depth of environments with varying lighting conditions, reliable methods are limited. By utilizing wireless sensor technology in conjunction with cameras, a wide range of environments can be visualized, and objects within these environments can be tracked and monitored. Such methods offer cost-effective alternatives and provide a more secure, data-at-rest option for individuals with low vision, while also enhancing machine perception. In this work, we develop such a prototype that utilizes wireless sensors and cameras, which act in sync, enabling us to estimate the depth of objects within varying lighting environments to a level that is recognizable …

How The Inter-Nucleon Force Shapes Emergent Collectivity And Imparts Uncertainties In Ab Initio Nuclear Observables, Kevin Becker

LSU Doctoral Dissertations

The importance of collective motion in atomic nuclei has been well-established for many decades. Even before the advent of the nuclear shell model and its much-needed answers to surprising empirical phenomena, collectivity and surface deformation have played a vital role in broadening our knowledge. Reconciling the collective and single-particle camps into a unified description required tremendous strides in the application of group theory and advances in high-performance supercomputing, and thanks to these efforts the symmetry-adapted no-core shell model, or SA-NCSM, has developed into a reliable model for the study of deformed light and medium-mass nuclei. State-of-the-art calculations reveal remarkably simple …

Fractional Brownian Motion With Mean-Density Interaction: A Myopic Self-Avoiding Fractional Stochastic Process, Jonathan House, Rashad Bakhshizada, Skirmantas Janušonis, Ralf Metzler, Thomas Vojta

Physics Faculty Research & Creative Works

Fractional Brownian motion is a Gaussian stochastic process with long-range correlations in time; it has been shown to be a useful model of anomalous diffusion. Here, we investigate the effects of mutual interactions in an ensemble of particles undergoing fractional Brownian motion. Specifically, we introduce a mean-density interaction in which each particle in the ensemble is coupled to the gradient of the total, time-integrated density produced by the entire ensemble. We report the results of extensive computer simulations for the mean-squared displacements and the probability densities of particles undergoing one-dimensional fractional Brownian motion with such a mean-density interaction. We find …

Single-Molecule Orientation And Localization Microscopy, Sophie Brasselet, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Single-molecule localization microscopy (SMLM) offers enhanced spatial resolution in optical microscopy, providing detailed insights into the spatial organization of proteins in cells at the nanoscale. Over the past decade, SMLM has progressively incorporated the capability to retrieve the orientations of single molecules using their polarized dipolar emission pattern. Here we explore recent advancements in single-molecule orientation and localization microscopy (SMOLM), which yields super-resolved images of molecular three-dimensional (3D) orientations, wobble and 3D positions. This advancement opens possibilities to explore the nanoscale organization and conformation of biological molecules as well as to monitor and design local 3D optical fields in nanophotonics. …

Assessing The Effectiveness Of Crawlers And Large Language Models In Detecting Adversarial Hidden Link Threats In Meta Computing, Junjie Xiong, Mingkui Wei, Zhuo Lu, Yao Liu

Computer Science Faculty Research & Creative Works

In the emerging field of Meta Computing, where data collection and integration are essential components, the threat of adversary hidden link attacks poses a significant challenge to web crawlers. In this paper, we investigate the influence of these attacks on data collection by web crawlers, which famously elude conventional detection techniques using large language models (LLMs). Empirically, we find some vulnerabilities in the current crawler mechanisms and large language model detection, especially in code inspection, and propose enhancements that will help mitigate these weaknesses. Our assessment of real-world web pages reveals the prevalence and impact of adversary hidden link attacks, …

Mixsa: Training-Free Reference-Based Sketch Extraction Via Mixture-Of-Self-Attention, Rui Yang, Xiaojun Wu, Shengfeng He

Research Collection School Of Computing and Information Systems

Current sketch extraction methods either require extensive training or fail to capture a wide range of artistic styles, limiting their practical applicability and versatility. We introduce Mixture-of-Self-Attention (MixSA), a training-free sketch extraction method that leverages strong diffusion priors for enhanced sketch perception. At its core, MixSA employs a mixture-of-self-attention technique, which manipulates self-attention layers by substituting the keys and values with those from reference sketches. This allows for the seamless integration of brushstroke elements into initial outline images, offering precise control over texture density and enabling interpolation between styles to create novel, unseen styles. By aligning brushstroke styles with the …

Neuro-Ins: A Learning-Based One-Shot Node Insertion For Dynamic Routing Problems, Zhiqin Zhang, Jingfeng Yang, Zhiguang Cao, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The rise in instant delivery services necessitates efficient route planning in last-mile delivery scenarios, where new orders arrive dynamically and need to be integrated into existing routes. In such contexts, complete re-optimization of routes are not permitted, and node insertion to existing route sequences is the only viable option. However, many existing heuristics for node insertion, such as the Cheapest Insertion (CI) method, are myopic and often result in suboptimal solutions retrospectively. This paper presents Neuro-Ins, an initial yet novel attempt at harnessing a learning-based framework to handle the insertion of new orders for the Pickup and Delivery Problem (PDP). …

Lighttransfer: Your Long-Context Llm Is Secretly A Hybrid Model With Effortless Adaptation, Xuan Zhang, Fengzhuo Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao, Min Lin

Research Collection School Of Computing and Information Systems

Scaling language models to handle longer contexts introduces substantial memory challenges due to the growing cost of key-value (KV) caches. Motivated by the efficiency gains of hybrid models and the broad availability of pretrained large transformer backbones, we explore transitioning transformer models into hybrid architectures for a more efficient generation. In this work, we propose LightTransfer, a lightweight method that transforms models such as LLaMA into hybrid variants. Our approach identifies lazy layers -- those focusing on recent or initial tokens -- and replaces their full attention with streaming attention. This transformation can be performed without any training for long-context …

Gti: Graph-Based Tree Index With Logarithm Updates For Nearest Neighbor Search In High-Dimensional Spaces, Ruoyao Ma, Yifan Zhu, Baihua Zheng, Lu Chen, Congcong Ge, Yunjun Gao

Research Collection School Of Computing and Information Systems

Nearest neighbor search (NNS) is fundamental for high-dimensional space retrieval and impacts various fields, such as pattern recognition, information retrieval, recommendation systems, and vector database management. Among existing NNS methods, graph-based methods often excel in query accuracy and efficiency. However, these methods face significant challenges, including high construction costs and difficulties with dynamic data updates. Recent efforts have focused on combining graph methods with hashing, quantization, and tree-based approaches to address these issues, but problems with large index sizes and update performance remain unresolved. In response, this paper proposes GTI, a novel, lightweight, and dynamic graph-based tree index for high-dimensional …

Deep Graph Anomaly Detection: A Survey And New Perspectives, Hezhe Qiao, Hanghang Tong, Nanyang Technological University, Irwin King, Charu Aggarwal, Guansong Pang

Research Collection School Of Computing and Information Systems

Graph anomaly detection (GAD), which aims to identify unusual graph instances (e.g., nodes, edges, subgraphs, or graphs), has attracted increasing attention in recent years due to its significance in a wide range of applications. Deep learning approaches, graph neural networks (GNNs) in particular, have been emerging as a promising paradigm for GAD, owing to its strong capability in capturing complex structure and/or node attributes in graph data. Considering the large number of methods proposed for GNN-based GAD, it is of paramount importance to summarize the methodologies and findings in the existing GAD studies, so that we can pinpoint effective model …

The “Founder’S Gaze”: How The Fourth Amendment Is A Surveillance Technology That Enables Ai To Scale Control Over The Subaltern, Diego H. Alcalá Laboy

Michigan Journal of Race and Law

Much has been written about the rise of artificial intelligence and machine learning applications and how the current Fourth Amendment law has been unable to mitigate the privacy harm that these tools produce. This article explores how the development and usage of AI and machine learning models is dependent on the originalism principles of Fourth Amendment Law. Utilizing Critical Surveillance Studies and Anticolonial Theory, I posit that the Fourth Amendment is a surveillance technology that categorizes conduct, persons, and places to impose the material conditions for the subjugation of historically minoritized communities within the United States. Furthermore, this article explores …

Boosting Symbolic Execution For Vulnerability Detection, Haoxin Tu

Dissertations and Theses Collection (Open Access)

Software systems written by humans tend to be unreliable and insecure, hence, bugs or vulnerabilities in them are inevitable. Symbolic execution has shown considerable potential in detecting diverse types of software bugs and also vulnerabilities that have severe security implications. However, existing symbolic execution engines still suffer from at least three fundamental limitations in memory modeling, path exploration, and structured input generation, which significantly impede existing engines from efficiently and effectively detecting software bugs and vulnerabilities.

The objective of this dissertation is to boost existing symbolic execution engines by designing a new memory model, two new path exploration strategies, and …

Memory-Efficient Graph Processing On Gpus: Reducing Intermediate Data Structure Overhead, Chang Ye

Dissertations and Theses Collection (Open Access)

The increasing scale of real-world graphs in domains such as fraud detection, community detection, and biological analysis demands high-throughput, memory-efficient graph processing solutions. GPUs offer massive parallelism for accelerating such workloads, and numerous frameworks have been developed to leverage their computational power. These frameworks primarily focus on optimizing scheduling to better align graph processing with GPU architectures. It performs well for algorithms with low memory demands, such as BFS, SSSP, and PageRank. However, for algorithms that require substantial memory, such as label propagation, and subgraph counting, the limited memory capacity of GPUs often becomes a significant bottleneck.

This dissertation addresses …

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2019 Surface Water, Groundwater Seep, And Soil Characterization 2021-2023 Surface Water And Groundwater Seep Evaluation 2023 Waterloo Aps Soil And Groundwater Evaluation, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft 2025 Interim Site-Wide Surface Water Monitoring Quality Assurance Project Plan, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Uncovering Environmental Justice Disparities: Tree Canopy Inequality In Low-Income Marginalized Communities, Emmanuel Wallace

Tennessee State University Alumni Theses and Dissertations

Tree canopy inequality in low-income marginalized communities is a direct result of decades of environmental injustice within urban communities in the United States, specifically the Home Owner’s Loan Corporation. This phenomenon underscores the disproportionate distribution of tree cover, green spaces, and their myriad benefits in neighborhoods marked by poverty and social vulnerability. Rooted in a history of discriminatory urban planning practices and systemic disparities, tree canopy inequality has profound consequences on residents' health and well-being. It leads to urban heat island effects, reduced air quality, and additional socio-economic disparities. On average, urban communities of color have 33% less tree canopy …

Miscanthus × Giganteus Increases Soil Maximum Water Holding Capacity Compared To Maize, Jessica T. Nelson, Maoz Dor, Andy D. Vanloocke, Jacob E. Studt, Perla K. Schrock, Marshall D. Mcdaniel

School of Earth, Environmental, & Marine Sciences Faculty Publications

Soil ecosystem services, like the ability to store water, have been depleted after a century of conventional, annual cropping, and perennial crops offer a solution to this and other agricultural environmental issues. We assessed the impact of Miscanthus × giganteus (miscanthus), a perennial biomass crop, on soil water holding capacity and structure compared to continuous maize (Zea mays L.) at two sites in Iowa. After three growing seasons, we measured the following: (1) maximum water holding capacity (MWHC) with and without soil structure, and (2) total porosity and pore size distribution (PSD) via micro-computed tomography (microCT). Miscanthus increased MWHC …

Fisheries Science Update - West Coast Demersal Scalefish Resource - September 2025, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Science Updates

The Department of Primary Industries and Regional Development (DPIRD) monitors the status of Western Australia’s demersal scalefish resources by undertaking regular stock assessments on indicator species.

This summary provides key outcomes of the 2025 assessment of the West Coast Demersal Scalefish Resource (Resource Assessment Report No. 2).