Physical Sciences and Mathematics Commons^™

Weekly Spatiotemporal Dynamics Of Forest Fire Hotspots In Tak Province, Thailand : A Gis-Based Directional Analysis, Suphatphong Ruthamnong

Applied Environmental Research

Forest fires are recurrent dry-season hazards in northern and western Thailand, yet their short-term spatial dynamics remain insufficiently understood. In this study, weekly spatiotemporal dynamics of forest fire hotspots in Tak Province, Thailand, were examined using Visible Infrared Imaging Radiometer Suite (VIIRS) active-fire data and GIS-based directional analysis. Hotspots from five fire seasons (2021–2025) were grouped into 24 weekly intervals beginning on 1 December. The analysis integrated weekly hotspot counts, forest-type compositions, mean-center trajectories, standard deviational ellipses, temporal changes in topographic characteristics, and fishnet-based hotspot persistence mapping. The results revealed that fire activity was highly concentrated during the middle of …

Effects Of The Psb-To-Ow Ratio And Light Intensity On Biogas Composition During Phototrophic-Assisted Anaerobic Fermentation Of Organic Waste, Kridsana Jirasansawat, Sirilak Prasertkulsak, Nitiwist Teangthai

Applied Environmental Research

The integration of phototrophic processes into anaerobic fermentation offers a promising strategy for improving biogas quality; however, the combined effects of the photosynthetic bacteria-to-organic waste (PSB-to-OW) ratio and light intensity remain unclear. In this study, the photosynthetic bacteria (PSB)-assisted anaerobic fermentation of municipal organic waste under varying PSB-to-OW ratios and light intensities was evaluated. An optimal PSB-to-OW ratio of 1:2 resulted in significantly higher CH4 concentrations and lower CO2 and H2S concentrations than the other tested ratios did (p < 0.05). At this ratio, moderate illumination (2000 lx) resulted in the highest CH4 concentration (68.2 ± 0.3%), compared with 1000 lx (61.5 ± 0.4%) and 4000 lx (63.1 ± 0.5%). Under illumination, the CO2 and H2S concentrations were lower than those under dark conditions, indicating a more favorable biogas composition. Kinetic analysis indicated that CO2 and H2S exhibited apparent first-order behavior under illumination, with the highest rates occurring at 2000 lx (kH2S = 0.093 day-1; kCO2 = 0.059 day-1), suggesting light-dependent transformation processes. Metagenomic analysis revealed a microbial community dominated by sulfide-oxidizing (Chlorobium sp.), photoheterotrophic (Rhodopseudomonas sp.), and syntrophic bacteria, supporting coupled carbon conversion and sulfur transformation. Overall, optimization of the …

Investigating The Effects Of Pressure On Fe And Co Intercalated 2h-Tas2 Through First-Principle Calculations, Ronald E. Putnam Jr.

UNF Graduate Theses and Dissertations

Using first-principles methods, we investigate the effects of applied isotropic pressure on the electronic and magnetic properties of intercalated Fe1/3TaS2 and Co1/3TaS2. Fe1/3TaS2 has been shown to be a ferromagnet that undergoes structural and magnetic phase transitions under applied pressure. The magnetic phase transitions are observed to be linked to the structural shift, and a mixture of magnetic phase states is present between 3 GPa and 6 GPa. Co1/3TaS2 was found to be antiferromagnetic, as confirmed by experimental work. One- and two-unit-cell systems of Co1/3TaS2 are analyzed, both showing band splitting that disappears under pressure. The application of pressure forces …

Reclaiming Agency: Ai Hallucinations And Translingual Interrogations In The City Tech Writing Center,, Joseph Franklin, Anna Laura Falvey

Publications and Research

No abstract provided.

Flood-Regime Shifts Across The Lower Midwest, Usa: Identifying Patterns Through Flood Magnitude–Frequency Analysis And Clustering, Kaiser Mostafiz

Graduate Theses/Dissertations

Flood regimes describe how flood behavior changes in magnitude, recurrence, and occurrence through time. Changes in these flood characteristics can affect flood hazards, river systems, infrastructure, and floodplain management. This thesis examines flood-regime change across the Lower Midwest, focusing on Nebraska, Iowa, Kansas, and Missouri from 1961 to 2020. Records from 1,452 U.S. Geological Survey gaging stations were initially compiled, and 208 stations were retained after screening for record availability and analytical consistency. Flood-regime change was evaluated between two 30-year study periods: Period 1 (1961–1990) and Period 2 (1991–2020). The analysis combined Log-Pearson Type III flood-frequency analysis using L-moments in …

The Effects Of Financing Green And Brown Sectors: What Do Theories And Evidence Say?, Hao Liang, Maria Teresa Punzi

Research Collection Lee Kong Chian School Of Business

This paper critically examines the economic and welfare implications of financing green and brown sectors. Drawing on a comprehensive review of recent theoretical and empirical literature, we highlight that while conventional green finance—allocating capital toward environmentally friendly (“green”) sectors and away from carbon-intensive (“brown”) sectors—can promote decarbonization, it may also produce unintended externalities. In particular, it can inadvertently incentivize higher emissions from brown firms and contribute to economic disruption. Using a dynamic stochastic general equilibrium (DSGE) model, we demonstrate that lowering the cost of capital for green sectors leads to only modest reductions in emissions, whereas raising it for brown …

Fluid Agency In Ai Systems: A Case For Functional Equivalence In Copyright, Patent, And Tort, Anirban Mukherjee, Hannah H. Chang

Research Collection Lee Kong Chian School Of Business

Modern Artificial Intelligence (AI) systems exhibit fluid agency in multi-step workflows: lacking human-like consciousness or culpability, yet they display behavior that is (i) stochastic (probabilistic and path‑dependent), (ii) dynamic (co‑evolving with user interaction), and (iii) adaptive (able to reorient across contexts). These properties generate valuable outputs but collapse attribution, irreducibly entangling human and machine inputs. Doctrines that assume traceable provenance—authorship, inventorship, and liability—fracture under this unmappability, yielding ownership gaps and moral “crumple zones.”This Article argues that only functional equivalence stabilizes doctrine under unmappability: Where provenance is indeterminate, legal frameworks should treat human and AI contributions as equivalent for allocating rights …

Ecosystem Functions And Services - Landscaping For Water Quality (March 25, 2026 Gbnerr), Julia Peterson

UNH Cooperative Extension

No abstract provided.

Marketing Water Quality Friendly Services, Julia Peterson

UNH Cooperative Extension

No abstract provided.

2026 Water Quality Considerations In Landscaping, Thomas Swenson

UNH Cooperative Extension

2026 Water Quality Considerations in Landscaping

Estuary, Kelle Loughlin

UNH Cooperative Extension

No abstract provided.

Stormwater Best Management Practices, Kat Kelleher

UNH Cooperative Extension

No abstract provided.

Nh State Shoreland Water Quality Protection Act (Landscaping For Water Quality Workshop - 2026), Jay Aube

UNH Cooperative Extension

No abstract provided.

Water Resource Protection Principles And Strategies, Julia Peterson

UNH Cooperative Extension

No abstract provided.

Assessing And Understanding Soil Characteristics, Amy Papineau

UNH Cooperative Extension

No abstract provided.

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Multivariate Quantile Autoregression-Mixed Data Sampling (Mvqar-Midas) Modeling Of Cost Of Living And Supply Chain Dynamics In Canada., Patrick Gbolonyo

Theses and Dissertations (Comprehensive)

In recent years, the rising cost of living as a result of persistent inflationary pressures, disruptions in the global supply chains, and changes in the macroeconomic landscape has become a critical topic of discussion. To address this, we move beyond a mean-based framework and employ a quantile regression approach. This allows the persistence of each series and the transmis- sion of shocks between the Consumer Price Index (CPI) (the total CPI which is a percentage change over the past 12 months), the Interest Rate (IR)(the target for the overnight rate), the New Housing Price Index (NHPI), and high-frequency supply chain …

Implementation Of A 3-Dimensional Hydrodynamic Numerical Model On A Large Northern Lake, Kirin Lorente

Theses and Dissertations (Comprehensive)

Climate change is impacting high latitude regions disproportionately more than those at a lower latitude. With polar lakes being highly sensitive to changes in the climate, shifts in lake ice dynamics and hydrodynamics are indicators of such changes in regional and global climates. These changes impact future seasons in a positive feedback loop, where changes in winter ice cover impact open water nutrients levels and lake thermal structure. This highlights the importance for long-term monitoring. Despite the abundance of lakes distributed across Northern Canada, there has been limited research conducted on these sentinels of climate change.

Specifically, Great Bear Lake …

Geovig And Purevig: Geometry-Aware Architectures For Efficient Computer Vision, Omar Ismail

Theses and Dissertations (Comprehensive)

Deploying deep learning models for medical image analysis on mobile devices requires a balance between inference latency, memory footprint, and delineating anatomical boundaries with high accuracy. While Convolutional Neural Networks (CNNs) and mobile Vision Transformers (ViTs) offer efficiency, they often struggle to model the irregular, non-local geometric structures inherent in biological tissues without incurring prohibitive computational costs. In this thesis, we introduce GeoViG (Geometric Vision Graph), an architecture that bridges the gap between efficient grid-based processing and explicit Geometric Deep Learning. GeoViG introduces a novel transition from high-resolution pixel grids to low-resolution dynamic graphs via a SpreadEdgePool operator, a geometry-aware …

Error-Driven Density Control For Compact Gaussian Splatting Under Sparse Supervision, Abdelrhman Elrawy

Theses and Dissertations (Comprehensive)

This thesis studies efficiency and stability challenges in Gaussian-splatting-based reconstruction under sparse supervision. In few-shot novel view synthesis, standard 3D Gaussian Splatting (3DGS) can overfit the limited training views and grow an unnecessarily large number of primitives due to limitations in its Adaptive Density Control (ADC) mechanism. This thesis introduces an error-driven reformulation of ADC that triggers densification using opacity gradients as a lightweight proxy for rendering error, and shows that such aggressive densification must be paired with delayed and conservative pruning to prevent destructive create--destroy cycles. When combined with depth-based geometric regularization, the resulting framework produces substantially more compact …

Assessing Dissolved Organic Matter Sources And Dynamics In Urban Stormwater: Implications For Greenhouse Gases, Harper W. Schmalz

Theses and Dissertations (Comprehensive)

Stormwater management ponds (SWMPs) are important aspects of land-use planning and increasingly recognized as active sites of biogeochemical processing that influence carbon cycling; however, little research has investigated the controls on dissolved organic and dissolved inorganic carbon (DOC and DIC) within these systems. This thesis examined the processing and transformations of dissolved carbon between three compartments to support the development of a greenhouse gas (GHG) box-model for urban stormwater ponds, including SWMP sediment, surface water, and vegetation. The objective of this thesis was to assess the biogeochemical processes that govern the rate and transformation of DOC and DIC between these …

Intelligent Electric Vehicle Routing For Goods Delivery Under Real-Time Traffic Conditions: A Comparative Framework For Modular Battery Swapping And Dynamic Wireless Charging, Ranjit Jakharabhai Odedra

Theses and Dissertations (Comprehensive)

Electric vehicles (EVs) are becoming central to sustainable and intelligent transportation systems, particularly in urban logistics, where reducing emissions, congestion, and operating inefficiencies is increasingly important. Despite their environmental advantages, the large-scale deployment of EVs in delivery operations remains constrained by limited driving range, time-consuming energy replenishment, and the difficulty of making routing decisions under dynamic traffic and load-dependent energy consumption. Addressing these challenges is essential for improving the practicality and reliability of EV-based freight transportation.

This thesis investigates optimization frameworks for EV routing in urban delivery systems by studying two complementary energy replenishment strategies: modular battery segment swapping and …

Impacts Of Burn Severity On The Hydro-Physical, Chemical And Thermal Properties Of Sub-Arctic Peat, Joshua B. Meyer Mr

Theses and Dissertations (Comprehensive)

Under current climate change, summer season in the boreal regions of Canada is becoming increasingly warmer and drier. This shift is driving increases in the frequency and intensity of naturally occurring wildfires and allowing access to areas not normally susceptible to fire such as wetlands. In peatland areas, these increasingly large fires can create complex burn scars, which contain a wide variety of different burn severities across different landcover types. This variety calls for a greater understanding of how varying fire intensity affects the hydro physical, chemical, and thermal characteristics of boreal peat. This study aims to deepen that understanding …

Investigation Of Mercury Bioaccessibility In Subsistence Fishes From The Canadian Subarctic, Kiran Mateo Sharma Mr

Theses and Dissertations (Comprehensive)

Fish consumption is the primary pathway for human exposure to methylmercury (MeHg), a global contaminant of concern known to cause adverse health effects. Fort Albany First Nation, a remote Indigenous community in northern Ontario that relies on fish for both subsistence and cultural practices, has expressed concern regarding the safety of local fish consumption. Community members and leaders have communicated several priorities for scientific research that are the foundation of this thesis. Specifically, consumers of wild-caught fish have asked how traditional cooking methods may affect mercury concentrations in fish, and how mercury concentrations in little-studied organs, such as liver and …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Permafrost Microtopography And Active Layer Hydrology In The Western Canadian Arctic, Tobias L. Leonhard

Theses and Dissertations (Comprehensive)

The growing interest in Arctic regions will likely increase the use of nuclear energy in the Arctic. While this energy source has a high potential to improve economic opportunities in the Arctic, it also increases the release of radioactive material (radionuclides). Radionuclides are already found in the Arctic and are traced back to natural as well as anthropogenic sources. Water is one of the dominant transport vectors for solutes such as radionuclides or other contaminants. Therefore, improving our understanding of Arctic hydrology is important for assessing future environmental risks such as the release of radionuclides. Topographic and microtopographic features are …

Evops: Evolutionary Patch Selection In The Embedding Space Of Whole Slide Images, Saya Hashemian

Theses and Dissertations (Comprehensive)

Computational pathology increasingly relies on the analysis of Whole-Slide Images (WSIs), which capture tissue specimens at gigapixel resolution. Because a single slide is far too large to process directly, the

prevailing paradigm decomposes each WSI into thousands of small patches and encodes them as high- dimensional feature embeddings using deep learning backbones. While effective, this paradigm carries a

substantial cost: the resulting collections of patch embeddings are computationally expensive to store and process, and they are frequently dominated by redundant, homogeneous, or otherwise uninformative tissue regions that dilute the diagnostic signal. Existing patch selection methods largely depend on heuristic or …

The Classical Limit In Geometric Quantization By Group Extension, Paul Bracken

School of Mathematical & Statistical Sciences Faculty Publications

Physical systems as a rule are associated with a symmetry group. The group approach to geometric quantization makes use of this to introduce a quantization by means of group extension. This procedure is discussed and applied to a physical system whose group law has its origin with the Galilean group. The main intention is to investigate the classical limit and its relationship under this approach to geometric quantization. The classical quantization conditions are obtained based on a deeper foundation.

Strong Q-Analogues For Values Of The Dirichlet Beta Function, Ankush Goswami, Tim Huber

School of Mathematical & Statistical Sciences Faculty Publications

An infinite class of relations between modular forms is constructed that generalizes evaluations of the Dirichlet beta function at odd positive integers. The work is motivated by a base case appearing in Ramanujan’s Notebooks and a parallel construction for the Riemann zeta function. The identities are shown to be strong q-analogues by virtue of their reduction to the classical beta evaluations as 𝑞→1− and explicit evaluations at CM points for |𝑞|< 1. We also determine asymptotic formulas for the Fourier coefficients of the associated modular forms.

A Conceptual Framework For Cognitive Engagement And Human Agency In Ai-Mediated Learning, Sam Rhodes, Zuhal Yilmaz, Terrie Galanti, Younggon Bae, Victoria Delaney, Zareen Gul Aga, Stephen Hutt

School of Mathematical & Statistical Sciences Faculty Publications

The purpose of this chapter is to propose a conceptual framework that unpacks AI use in instructional practice across three interrelated dimensions: human agency, cognitive demand, and AI orchestration. We ground this work in historical perspectives on technology's mediating role in education. We then propose the conceptual framework and three characterizations of the use of AI in school instruction: cognitive load reducer, cognitive capacity builder, and cognitive companion. We then illustrate a worked example of each, including a curricular example and sample student prompts, and conclude with questions that educators might ask themselves as they consider if and how to …