Physical Sciences and Mathematics Commons^™

Marine Sentinels Of The Past: Holocene Trace Element Records From North Pacific Pinnipeds, Aidan M. Pflieger

Honors Theses

Since the Last Glacial Maximum (20,000 years ago), the North Pacific has remained geologically dynamic and biologically diverse. Natural fluctuations in island arc volcanism and climate likely continue to influence the inputs of trace elements (TEs) to the Aleutian Island Archipelago. Bioaccumulation of these TEs in the region’s marine food webs provides a proxy for long-term environmental variability. In this study, 95 tephra-preserved pinniped bone samples from temporally identified archeological Aleut midden sites on Unalaska Island (5500-200 BP; BP=years before present, c. 1950), were analyzed for 20 TEs using inductively coupled plasma mass spectrometry (ICP-MS). Elemental concentrations were compared temporally …

Representations Of Finite Groups And Diagrammatic Algebras, Hudson Yeend

CMC Senior Theses

Representation theory allows mathematicians to study abstract mathematical objects using the powerful and concrete tools of linear algebra. This thesis aims to present some foundational concepts in representation theory and apply these concepts to specific groups and algebras. We begin by examining representations of finite groups, culminating with a proof of Maschke's theorem. We then use the correspondence between a group and its group algebra to segue into a study of representations of diagrammatic algebras, where we introduce analogous notions of decomposition. We end with a study of quiver representations, noting that Gabriel's theorem and the kQ-modular structure transcend …

Federated Data Engineering And Learning For Edge Intelligence Systems, Afsaneh Mahanipour

Theses and Dissertations--Computer Science

The rapid proliferation of Internet of Things (IoT) devices and cyber–physical systems (CPS) in domains such as smart healthcare, intelligent transportation, and industrial automation has led to unprecedented volumes of heterogeneous data. While advances in deep learning and large-scale foundation models have enabled powerful data-driven decision making, their deployment in real-world distributed environments remains fundamentally constrained by limited computation, communication bandwidth, energy resources, and data privacy requirements. This dissertation addresses these challenges by developing novel federated learning frameworks and efficient federated data-processing pipelines that make large-scale artificial intelligence practical, scalable, and trustworthy in resource-constrained settings. This dissertation identifies data preprocessing …

Multi-Objective Optimization Of Energy Costs And Ev Battery Health In V2g Enabled Homes, Dzifa M. Hodey

Theses and Dissertations--Computer Science

Electric vehicles (EVs) and rooftop solar photovoltaic (PV) systems are increasingly being integrated into residential settings, creating new opportunities for vehicle-to-grid (V2G) and vehicle-to-home (V2H) operations. In these systems, the EV battery functions as a controllable energy storage unit that can charge from the grid or PV and discharge energy to supply household load or export to the grid for a profit. By intelligently scheduling this bidirectional power exchange, households can reduce electricity costs and enhance PV utilization. Realizing these benefits requires optimization strategies that balance cost reduction with EV battery health preservation. However, existing V2G/V2H studies largely emphasize cost …

Toward Efficient And Scalable Scientific Data Management Through Quality-Oriented Data Compression, Pu Jiao

Theses and Dissertations--Computer Science

Scientific simulations and instruments now produce data at rates that overwhelm the storage, memory, and network subsystems of modern high-performance computing (HPC) facilities. Error-bounded lossy compression reduces data movement costs while bounding reconstruction error, yet three barriers limit its adoption in mission-critical workflows: existing compressors cannot guarantee the accuracy of domain-specific quantities of interest (QoIs) derived from compressed data; compression-induced artifacts such as posterization, blocking, and interpolation banding erode user confidence in decompressed fields; and significant compressibility in the quantization index arrays of interpolation-based pipelines remains unexploited. This dissertation addresses all three barriers through four contributions, with the artifact barrier …

A Literature Review On Ethics In Medical Diagnostic Ai & Analysis Therein, Connor J. Turetzky

Master's Theses

Artificial Intelligence presents a very promising future in medicine. Being able to diagnose and recommend treatments quickly is vital in ensuring positive patient outcomes. However, the new technology is not without risk. In this narrative literature review, the risks of AI in terms of bias, ethics, and environmental impact will be explored through existing research. This paper will focus on research published between 2019 and 2026, highlighting the major ethical and systematic problems currently facing diagnostic AI. Historical bias in medical data has led to AI that share those biases, and humans inherit that bias creating a potential negative feedback …

Mat 1500 Calculus I Syllabus, Tian Cai

Open Educational Resources

No abstract provided.

Mat 1600 Syllabus Ii Syllabus, Tian Cai

Open Educational Resources

No abstract provided.

Mat 2100 Calculus Iii Syllabus, Mei Xing

Open Educational Resources

No abstract provided.

Part Sm: Statistical Mechanics, Konstantin Likharev

Essential Graduate Physics

Includes: Review of Thermodynamics; Principles of Physical Statistics; Ideal and Not-So-Ideal Gases; Phase Transitions; Fluctuations; Elements of Kinetics

Laser Beam Shaping Using A Neural Network, Azeem A. Hakim

Honors Undergraduate Theses

Multiphoton lithography (MPL) is a method of laser-based 3D-printing for fabricating micron-scale structures point-by-point in a photopolymerizable medium. MPL’s high-resolution capabilities have made it a powerful method for the fabrication of many devices, such as microelectromechanical systems (MEMS) and tissue scaffolds.  The throughput of MPL processes can be increased by using spatially shaped laser beams that expose large areas or volumes simultaneously. A laser beam can be reshaped by passing it through a spatial light modulator (SLM) displaying a pre-designed phase mask. One type of laser beam profile used for this purpose is the Bessel beam, a type of structured …

Alexander Duals Of Symmetric Simplicial Complexes And Stanley-Reisner Ideals, Ayah Almousa, Kaitlin Bruegge, Martina Juhnke-Kubitzke, Uwe Nagel, Alexandra Pevzner

Mathematics Faculty Publications

Given an ascending chain (I_n)_n∈N of Sym-invariant squarefree monomial ideals, we study the corresponding chain of Alexander duals (I_n^∨)_n∈N. Using a novel combinatorial tool, which we call avoidance up to symmetry, we provide an explicit description of the minimal generating set up to symmetry in terms of the original generators. Combining this result with methods from discrete geometry, this enables us to show that the number of orbit generators of I_n^∨ is given by a polynomial in n for sufficiently large n. The same is true for …

Using Ai To Analyze Survey Data, Sara Martucci

Open Educational Resources

This assignment in Methodology in Sociology/Criminology engages students in the full research process by guiding them through variable selection, data analysis, interpretation, and critical reflection on AI-assisted decision-making. Using a class-generated survey dataset (or an existing dataset), students develop a research question, identify independent and dependent variables, and formulate a hypothesis. They then compare their selections with those suggested by an AI tool, analyzing differences in reasoning and variable choice. Through SPSS, students generate frequency tables, charts, and scatterplots to examine relationships between variables, including potential intervening factors. The assignment culminates in a group presentation and reflective analysis on the …

Differences In Biologic Clinical Trials For Chronic Rhinosinusitis With Nasal Polyps—Are We Comparing Apples With Oranges?, Marjolein Cornet, Peter W. Hellings, Martin Desrosiers, Martin Wagenmann, Richard Follows, Laura Walrave, Luz Adriana Jimenez, Lee Tombs, Dawn Edwards, Peter Howarth, Joseph K. Han

Department of Otolaryngology (ENT) Faculty Publications

In recent years, several biologics targeting Type 2 inflammation have been developed for treating chronic rhinosinusitis with nasal polyps (CRSwNP). These have been studied in registrational randomized controlled trials (RCTs), which vary in their patient populations, trial design, endpoints, geography, timing, or data-handling processes. While (in)direct treatment comparisons and meta-analyses have been carried out to compare efficacy results from RCTs, often these fail to properly account for these between-study differences. Here, we summarize the key between-study differences that can influence trial outcomes and highlight the resulting challenges faced when comparing outcomes from different Phase III RCTs of biologics in CRSwNP.

Celebrating Faculty Scholarship 2026, Smith College Libraries

Celebrating Faculty Scholarship: Bibliographies

Bibliography of selected scholarly and creative work produced by Smith College faculty and submitted by faculty for the 2026 celebration in the Neilson Library Skyline Reading Room, Smith College on September 14, 2026.

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

Linking Phytoplankton Physiology And Ecology To Global Biogeochemical Cycles: A Modeling Approach, Margaret Bernish

Open Access Dissertations

Phytoplankton, or microscopic primary producers, contribute to carbon export through the biological transformation of carbon dioxide into organic molecules. Phytoplankton are responsible for approximately half of global net primary production, while only contributing minimally to total photosynthetic biomass. Despite their important role in the global cycling of nutrients, phytoplankton physiology and ecology are often highly simplified in global biogeochemical models. This dissertation elucidates the role of phytoplankton physiology and ecology within biogeochemical cycles, allowing for better characterization of marine microbial distribution and better representation of nutrient cycling for interpretive and predictive models. The development of formulations that link physiological responses …

Ultrafast Vibrational Dynamics In Important Wide-Bandgap Semiconductors, Dielectrics And Energetic Materials, Dinusha Madushanka Senarathna

Open Access Dissertations

This dissertation applies time-resolved coherent anti-Stokes Raman scattering (tr-CARS), to measure ultrafast vibrational dynamics in technologically important solid-state and van der Waals molecular systems. The central goal is to use time-domain Raman methods to resolve mode-specific phonon and vibrational dephasing processes with high temporal precision, high spectral selectivity, and sufficient experimental flexibility to probe materials ranging from wide-bandgap semiconductors and oxide crystals to energetic molecular crystals. Across the work, I show that carefully designed tr-CARS measurements can access vibrational lifetimes from hundreds of femtoseconds to several picoseconds, enabling direct observation of decay pathways, relaxation mechanisms, and dispersion effects that shape …

Volatiles In Mantle Sources At Mid-Ocean Ridge And Intraplate Settings, Rebecca Lippitt

Open Access Dissertations

Volatiles play an integral role in upper mantle processes and the eruptive styles of volcanoes. Although we know the importance of volatiles to volcanic systems, processes like melting, crystallization, and degassing alter the volatile abundances of mantle melts, making it difficult to quantify mantle source compositions and the extent to which volatiles influence melting processes. Additionally, volatile content may be a key factor in setting the oxidation conditions of mantle source rocks and subsequently changing those conditions in a body of magma as it ascends through the crust and is erupted at the Earth’s surface. Recent work, however, has identified …

Impact Of Water Quality And Gear Type On Eastern Oyster (Crassostrea Virginica) Growth In Narragansett Bay, Ri, Jacqueline Rosa

Open Access Master's Theses

Oyster aquaculture is expanding in Rhode Island, yet key farming regions in the lower West Passage of Narragansett Bay (WPNB) lack the in-situ, high-temporal resolution monitoring needed to evaluate emerging stressors and support production. At the same time, the industry is undergoing rapid technological development aimed at improving production while reducing labor and overall costs. In recent years, a low-maintenance, alternative surface gear was introduced in WPNB; however, its impact on oyster performance relative to traditional cultivation methods has not been quantified. This study established a 1.5-year continuous water quality time series in WPNB and paired these observations with …

Assessment Of Local Amplification Causes At Coastal Strong Motion Stations With Elevated Ground Motion Residuals From The 2024 Tewksbury, New Jersey Earthquake, Patrick Daniele

Open Access Master's Theses

Elevated ground motion amplitudes at individual stations are commonly observed in earthquake datasets, yet the physical causes of these residuals are often not explicitly identified. This study investigates two seismic monitoring stations in southeastern New York that recorded amplified motions during the 2024 Mw 4.8 Tewksbury, New Jersey earthquake. A consistent set of established geophysical methods -- including multichannel analysis of surface waves (MASW), passive ambient noise arrays (MAM), stochastic inversion, horizontal-to-vertical spectral ratio (HVSR) analysis, and directional spectral ratio techniques -- was applied to directly characterize site conditions and identify the mechanisms contributing to amplification.

Results show that elevated …

Data Improved Models Applied To Essential Oceanographic Processes In Rhode Island Coastal Waters, Ainsley Fruhwirth

Open Access Master's Theses

The Ocean State Ocean Model (OSOM), funded and developed through the National Science Foundation’s (NSF) Established Program to Stimulate Competitive Research (EPSCoR), was designed to simulate the physical dynamics of Rhode Island’s estuaries and shelf waters. However, the model struggled to capture key features of summer circulation in Rhode Island Sound (RIS), most notably the westward flowing coastal current and vertical stratification profile found in May through September. Significant errors in modeled lateral and vertical density gradients indicated that the thermohaline structure, physical mixing parameters, and forcing inputs required comprehensive revision. Using historical datasets from the National Oceanic and Atmospheric …

Amino Acid Isotope Dynamics And Associated Ecological Metrics Across Accretionary Tissues Of Marine Fishes, Sofia Piccone

Open Access Master's Theses

Compound-specific isotope analysis of amino acids (CSIA-AA) applied to the organic growth layers of accretionary fish tissues, including eye lenses, otoliths, and scales, has made it possible to reconstruct histories of fish physiology, ecology, and environmental conditions. Yet it remains uncertain whether amino acid isotope values, and the ecological information they contain, are conserved across these archival tissues or if differences in tissue composition, growth, protein structure, and metabolic routing produce tissue-specific offsets that alter inferred carbon sources, d¹⁵N_Baseline, and trophic position. We tested this question with individually paired CSIA-AA of eye lenses, otoliths, and scales …

Small Antiperfect Steiner Triple Systems, Justin Z. Schroeder, Joshua Ganschow

Research & Publications

The cycle structure of Steiner triple systems (STS) has been well studied with regard to uniform STS and cycle switching. Of particular interest among uniform STS are perfect STS, in which every cycle graph consists of a single cycle. In this paper, we initiate the study of antiperfect STS, in which every cycle graph consists of a union of at least two cycles. We prove that an antiperfect STS(n) exists for all admissible n ≥ 15 and provide a complete listing of all antiperfect STS(n) for n ≤ 19 and all antiperfect STS(21) with a non-trivial automorphism. Furthermore, it is …

Hydrogeochemical And Redox Controls On Nitrate And Arsenic Co-Occurrence In The Western Kansas High Plains Aquifer (Usa): A Composite Health Risk Assessment And The Case For Risk-Informed Private Well Governance, Jonathan Kuffour Owusu

Master's Theses or Doctor of Nursing Practice

Fifty-one private domestic wells across western Kansas were sampled to quantify nitrate and arsenic occurrence, identify geochemical controls, and evaluate carcinogenic and non-carcinogenic health risks for adult and child receptors in a region where groundwater serves as the primary drinking water source with no routine regulatory oversight. Samples were analyzed for major ions, nutrients, and trace elements by ICP-MS, ion chromatography, and UV-Vis spectrophotometry. Shapiro-Wilk testing confirmed non-normal distributions for both contaminants; inter-county comparisons were therefore conducted using Kruskal-Wallis tests with Dunn's post-hoc correction. Health risk was quantified via chronic daily intake (CDI), hazard quotient (HQ), HQ-based Water Quality Index …

Special Issue: Innovative Numerical Approaches For Problems In Science And Engineering, Xiaoming He, Shuhao Cao, Qiao Zhuang

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

Equilibrium Stability Under Nuclear Confrontation, Martin Bohner, A. A. Martynyuk

Mathematics and Statistics Faculty Research & Creative Works

This article proposes and analyzes mathematical models of confrontation between two and n countries, including countries with nuclear weapons. The proposed models are based on a generalization of Richardson's well-known mathematical model of the arms race. Namely, the factor of hostility is filled with expanded content, including public opinion and the armed forces of the opposing countries. Qualitative analysis of confrontation models is carried out by the method of Lyapunov functions and by applying nonlinear integral inequalities. As a result of the analysis, the conditions for the stability of the equilibrium state of the opposing countries are established, and the …

Effective Deep Learning Architectures For Structured Data Analysis And Generation, Md Atik Ahamed

Theses and Dissertations--Computer Science

The effective utilization of structured data is fundamental to modern machine learning, yet it presents distinct challenges in both predictive analysis and generative modeling. Traditional deep learning architectures, particularly Transformers, often suffer from quadratic computational complexity when processing long sequences. This dissertation addresses these limitations by introducing novel architectures based on State-Space Models (SSMs) and Diffusion Models. In the area of predictive analysis, we focus on overcoming the computational bottlenecks of attention mechanisms for tabular and time-series data. First, we introduce MambaTab, a selective state-space architecture designed for efficient tabular classification. By leveraging the linear complexity of SSMs, MambaTab significantly …

Threshold Asymmetric Conditional Autoregressive Range (Tacarr) Model, Isuru Ratnayake, V. A. Samaranayake

Mathematics and Statistics Faculty Research & Creative Works

This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed to vary across regimes. A self-adjusting threshold component, determined by past values of the series, is used to identify the prevailing market regime. In this way, the model is able to capture asymmetric and heteroscedastic volatility behavior in financial markets. The TACARR model is designed to address several limitations of existing price range models, including …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …