Physical Sciences and Mathematics Commons^™

2024 Spring Term Sls261/Phy206 Syllabus, Gustavo Machado Monteiro

Open Educational Resources

No abstract provided.

Development Of Platinum(Iv)-Gold(I)-Based Anticancer Agents, Javier E. Lopez-Hernandez

Dissertations, Theses, and Capstone Projects

Heterometallic compounds have emerged as prospective multitarget anticancer drugs. These species may display improved efficacy and physicochemical properties compared to the individual metallic fragments, while helping combat drug resistance by exerting effects on multiple pathways. In this thesis we describe the synthesis of new bi- and tri-metallic compounds based on platinum(IV) compounds containing FDA-approved platinum agents, and gold(I) derivatives with known anticancer properties. We demonstrate their toxicity and selectivity against a small panel of renal, bladder, ovarian, and breast cancer cell lines, as well as their synergistic effects. We have selected a trinuclear PtAu₂compound containing the Pt(IV) core …

Listening For Lemurs: Translating Black-And-White Ruffed Lemur (Varecia Variegata) Vocalizations Into Conservation Insights Through Acoustic Monitoring, Carly H. Batist

Dissertations, Theses, and Capstone Projects

The field of bioacoustic monitoring has undergone a significant evolution in recent years, driven by technological innovations that have revolutionized how researchers study animal vocalizations. Traditionally, bioacoustics was rooted in active acoustic monitoring (AAM), involving human observers using recorders in the field to study animal sounds and understand species' vocal communication. However, the emergence of passive acoustic monitoring (PAM) has introduced a new complementary approach, utilizing specialized recorders placed in ecosystems to autonomously capture sounds at wide spatial and temporal scales. My dissertation adopts a translational approach to bioacoustic monitoring, integrating both AAM and PAM techniques to study and survey …

Positron Emission Tomography In Oncology And Environmental Science, Samantha Delaney

Dissertations, Theses, and Capstone Projects

The last half century has played witness to the onset of molecular imaging for the clinical assessment of physiological targets. While several medical imaging modalities allow for the visualization of the functional and anatomical properties of humans and living systems, few offer accurate quantitation and the ability to detect biochemical processes with low-administered drug mass doses. This limits how physicians and scientists may diagnose and treat medical issues, such as cancer, disease, and foreign agents.

A promising alternative to extant invasive procedures and suboptimal imaging modalities to assess the nature of a biological environment is the use of positron emission …

Crime Prediction Using Agent-Based Modeling, Yifei Gong

Dissertations, Theses, and Capstone Projects

Crime risk evaluation and crime prediction using agent-based modeling (ABM) have gained popularity in the field of computational criminology in recent years. Traditionally, researchers rely on statistical methods and machine learning models to predict crimes using historical data. ABM generates macro-level crime patterns in a bottom-up fashion by simulating the daily behaviors of autonomous entities, such as citizens and offenders. ABM takes into consideration the non-linear interactions between agents under complex social contexts. Currently, the comprehensive usage of ABM for criminological theory testing and urban policy evaluations calls for a unified software framework. In this research, we introduce CARESim, an …

Context In Computer Vision: A Taxonomy, Multi-Stage Integration, And A General Framework, Xuan Wang

Dissertations, Theses, and Capstone Projects

Contextual information has been widely used in many computer vision tasks, such as object detection, video action detection, image classification, etc. Recognizing a single object or action out of context could be sometimes very challenging, and context information may help improve the understanding of a scene or an event greatly. However, existing approaches design specific contextual information mechanisms for different detection tasks.

In this research, we first present a comprehensive survey of context understanding in computer vision, with a taxonomy to describe context in different types and levels. Then we proposed MultiCLU, a new multi-stage context learning and utilization framework, …

Modeling And Dynamics Of Capillary Bridges, Moyosore Odunsi

Dissertations, Theses, and Capstone Projects

Capillary bridges are ubiquitous in nature and have important implications in processes like inkjet printing. They are an important area of study not only because of their industrial applications but because many of the questions in capillary bridge research are applicable to other systems. For example, they exhibit pinning and unpinning patterns that are similar to those in sliding droplets. The rules underlying this pinning are essential to predicting liquid shapes and understanding how contact lines move across surfaces. Many previous studies have focused on axisymmetric capillary bridges and neglected to model the tangential forces that arise due to asymmetry. …

Parabolic And Non-Parabolic Surfaces With Small Or Large End Spaces Via Fenchel-Nielsen Parameters, Michael Antony Pandazis

Dissertations, Theses, and Capstone Projects

We consider conditions on the Fenchel-Nielsen parameters of a Riemann surface X that determine whether or not a surface X is parabolic. Fix a geodesic pants decomposition of a surface and call the boundary geodesics in the decomposition cuffs. For a zero or half-twist flute surface, we prove that parabolicity is equivalent to the surface having a covering group of the first kind. Using that result, we give necessary and sufficient conditions on the Fenchel-Nielsen parameters of a half-twist flute surface X with increasing cuff lengths such that X is parabolic. As an application, we determine whether or not each …

Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev

Dissertations, Theses, and Capstone Projects

Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …

Higher Diffeology Theory, Emilio Minichiello

Dissertations, Theses, and Capstone Projects

Finite dimensional smooth manifolds have been studied for hundreds of years, and a massive theory has been built around them. However, modern mathematicians and physicists are commonly dealing with objects outside the purview of classical differential geometry, such as orbifolds and loop spaces. Diffeology is a new framework for dealing with such generalized smooth spaces. This theory (whose development started in earnest in the 1980s) has started to catch on amongst the wider mathematical community, thanks to its simplicity and power, but it is not the only approach to dealing with generalized smooth spaces. Higher topos theory is another such …

Mechanistic, Biochemical, And Theoretical Studies Of Phototoxicity And Photobluing, Lloyd M. Lapoot

Dissertations, Theses, and Capstone Projects

This thesis consists of four chapters as detailed below:

Chapter 1 discusses the photoconversion of heptamethine to pentamethine cyanines and of pentamethine to trimethine cyanines. Here, we report mechanistic studies and initial experimental evidence for a previously unexplored 4-carbon truncation reaction that converts the simplest heptamethine cyanine to the corresponding trimethine cyanine. We propose a DFT-supported model describing a singlet oxygen (¹O₂) mediated formation of an allene hydroperoxide intermediate and subsequent 4-carbon loss through a retro-Diels-Alder process. Fluorescence and mass spectrometry measurements provide evidence for this direct conversion process. This 4-carbon truncation reaction adds to growing …

Bifurcations And Resultants For Rational Maps And Dynatomic Modular Curves In Positive Characteristic, Colette Lapointe

Dissertations, Theses, and Capstone Projects

No abstract provided.

Effect Of Magnetic Draping On Satellite Galaxies In Clusters, Vanessa Brown

Dissertations, Theses, and Capstone Projects

Galaxy evolution has been observed to be influenced by environment. Satellite galaxies orbiting within clusters can experience changes in morphology and composition through various mechanisms such as ram-pressure stripping (RPS), which removes a galaxy’s interstellar medium as it passes through the cluster via direct interaction with the hot intracluster medium gas. An open question is whether intracluster magnetic fields affect galaxy evolution, for example by forming a magnetic layer around infalling galaxies (called magnetic draping) and mitigating gas removal by RPS. Using the code GADGET-3, we compare global properties and mass distributions within identical cluster simulations run with and without …

Development And Application Of Magnus Expansion Based Propagators For Problems In Spectroscopy And Quantum Dynamics, Taner M. Ture

Dissertations, Theses, and Capstone Projects

Stable and accurate numerical propagators of time-evolution equations in quantum mechanics are required to capture correct dynamical behavior, especially in the long time limit. Magnus expansion (ME) provides a general way to expand the real time propagator of a time dependent Hamiltonian within the exponential such that the unitarity is satisfied at any order. Integrators are developed by truncating the ME and using explicit integration of Lagrange interpolation formulas for the time dependent Hamiltonian within each time interval. The derived approximations are studied in a numerical test and compared to other available expressions. The sixth order expression is applied to …

Sigma_N-Correct Forcing Axioms, Benjamin P. Goodman

Dissertations, Theses, and Capstone Projects

I introduce a new family of axioms extending ZFC set theory, the Sigma_n-correct forcing axioms. These assert roughly that whenever a forcing name a' can be forced by a poset in some forcing class Gamma to have some Sigma_n property phi which is provably preserved by all further forcing in Gamma, then a' reflects to some small name such that there is already in V a filter which interprets that small name so that phi holds. Sigma_1-correct forcing axioms turn out to be equivalent to classical forcing axioms, while Sigma_2-correct forcing axioms for Sigma_2-definable forcing classes are consistent relative to …

Speeding Up Coded Distributed Machine Learning, Xian Su

Dissertations, Theses, and Capstone Projects

The advancement of artificial intelligence has facilitated the generation of vast datasets, whose size often exceeds tens of terabytes. Meanwhile, machine learning has become the most important technique for big data analytics, and sophisticated models with thousands or even millions of parameters are designed to leverage big data. However, processing big data and training large models necessitate significant storage and computational resources, which has been a bottleneck in the development of artificial intelligence. Distributed computing, such as MapReduce, has been proposed to surmount the computational bottlenecks associated with single-machine analysis.

Although distributed computing harnesses the collective power of numerous less …

Unconventional Computing With Photonic Oscillator Networks, Mostafa Honari Latifpour

Dissertations, Theses, and Capstone Projects

The ever-increasing demand for data processing and the challenges in scaling traditional computing architectures are driving intensive research into alternative computing paradigms. Optical computing has garnered renewed attention since the 2010s, driven by its potential to accelerate specialized computational tasks such as combinatorial optimization and neural networks.

Coherent light sources including lasers and parametric oscillators have been around for decades and become indispensable tools in modern technology, but these photonic oscillators are also nonlinear dynamical systems that can exhibit emergent, complex phenomena, especially when coupled in arrays. These nonlinear optical systems have recently been shown to be capable of doing …

Assessing Job Vulnerability And Employment Growth In The Era Of Large Language Models (Llms), Prudence P. Brou

Dissertations, Theses, and Capstone Projects

This paper explores the impact of Large Language Models (LLMs) and artificial intelligence (AI) on white-collar occupations in the context of job vulnerability and employment growth. Utilizing the Kaggle dataset "Occupation Salary and Likelihood of Automation," the study employs a data-driven approach to analyze trends across states. Through interactive data visualization, the project aims to provide actionable insights for affected workers, businesses, and policymakers navigating the changing dynamics of the workforce amidst technological advancements.

The Efficacy Of Using Machine Learning Techniques For Identifying And Classifying “Fake News”, Muhammad Islam

Dissertations, Theses, and Capstone Projects

In today's digital world, detecting fake news has emerged as a critical challenge, one that has significant effects on democracy and public discourse at large both regionally and globally. This research studies how diversity of news sources in training datasets affects how well machine learning models can classify fake vs true news. I used the Linear Support Vector Classification (LinearSVC) to create and compare two classification models: one was trained on a dataset that only had real news from a singular source, Reuters (Dataset 1), and the other was trained on a dataset that contained real news from Reuters, The …

Using A Novel Chain Of Chemical, Crystallographic, And Isotopic Analytical Techniques To Examine The Formation Histories Of Features In Chondritic Meteorites And Orbicular Granites, Samuel P. Alpert

Dissertations, Theses, and Capstone Projects

Understanding the chemistry, crystallography, and isotopic variability of minerals allows us to place significant constraints on the formation history of their host rocks. These constraints provide insight into everything from the distribution of water in the solar system to the onset of plate tectonics. Electron beam instruments and ion probes are important tools used by modern geologists to obtain crystallographic, chemical, and isotopic data. Here I present a new workflow, using these instruments, combining wavelength dispersive spectrometry (WDS), backscattered electron (BSE) imaging, machine learning algorithms, electron backscatter diffraction (EBSD), and secondary ion mass spectroscopy (SIMS), to place quantitative constraints on …

Modeling Hydroxide In Classical Proton Hopping Simulations And Amyloid Beta Membrane Pores, Ankita Dutta

Dissertations, Theses, and Capstone Projects

H3O+ and OH- ions display anomalously large diffusion coefficients, a property that is often attributed to their ability to perform structural diffusion which allow these ions to move through aqueous solutions by sequential proton transfers, also known as ‘Grotthuss hopping’. A rearrangement of the local solvation structure is known to be the prerequisite for proton transfer events via these ions. Studying this phenomenon using classical molecular dynamics simulations that do not allow bond rearrangements poses significant obstacles. Here we use a Monte Carlo augmented classical Molecular Dynamics method called the MOBHY algorithm which allows instantaneous changes in protonation states in …

Explicit Composition Identities For Higher Composition Laws In The Quadratic Case, Ajith A. Nair

Dissertations, Theses, and Capstone Projects

The theory of Gauss composition of integer binary quadratic forms provides a very useful way to compute the structure of ideal class groups in quadratic number fields. In addition to that, Gauss composition is also important in the problem of representations of integers by binary quadratic forms. In 2001, Bhargava discovered a new approach to Gauss composition which uses 2x2x2 integer cubes, and he proved a composition law for such cubes. Furthermore, from the higher composition law on cubes, he derived four new higher composition laws on the following spaces - 1) binary cubic forms, 2) pairs of binary quadratic …

Aspects Of Parity Breaking In Classical And Quantum Fluids, Dylan J. Reynolds

Dissertations, Theses, and Capstone Projects

Parity-breaking is ubiquitous across many scales of physics, from the rotation of galaxies at the largest of scales, to the cyclotron orbits of electrons at the microscopic scale. In describing the collective dynamics of many particle systems, parity breaking effects typically originate from some form of chirality, such as angular momentum, at the level of the constituent particles. External forces can also induce chiral motion, with the primary examples being the Lorentz and Coriolis forces.

The effects of parity breaking are perhaps most strikingly seen in active matter, systems of complex particles that tend to convert energy into some directed …

Me And Mathematics: “Doing What You’Re Talking About”: In Dialogue With My Family, Eden Morris

Dissertations, Theses, and Capstone Projects

This paper is a philosophically oriented accompaniment to my audio project (accessible through the following link: https://cuny.manifoldapp.org/projects/me-and-mathematics). Working together, the paper and audio collages form a call to action and a resource. My primary finding is the importance of doing what you’re talking about or exploring and implementing your ideas experientially. Doing what you’re talking about is important for effective teaching/learning and feeling in line with oneself. This working concept came to my attention during my research conversation with my oldest living relative, and then, again, with my youngest (non-baby) relative. This doing what you’re talking about is a way …

Using Gaussian Processes To Measure M-Dwarf Rotation Periods From Ground-Based Light Curves, Ryan J. Lebron

Dissertations, Theses, and Capstone Projects

Stellar rotation is a readily observable characteristic that plays a crucial role in the generation and activity of magnetic fields through a process known as a magnetic dynamo. For low mass main sequence stars, they exhibit fully convective interiors, giving rise to a distinct dynamo mechanism compared to solar-type stars. Examining the rotational speeds of these stars can offer valuable insights into the workings of these mechanisms. To measure these rotation periods, we developed a pipeline to analyze 192 archival light curves of low mass stars observed by the Zwicky Transient Facility (ZTF) by utilizing a combination of Lomb-Scargle and …

Illustris-Tng Simulated Central Black Mass(Mbh) And Galaxy Properties Correlations With A Machine Learning Approach, Imani L. Dindy

Dissertations, Theses, and Capstone Projects

Observationaly it is well established that the masses of central black holes are tightly correlated with galaxy properties, most notably the bulge’s velocity dispersion. Cosmolog- ical hydrodynamical simulations can capture most of these correlations, but it is yet not understood why this occurs. To gain greater insight into central black hole growth we use machine learning algorithms to study the relationship between central black hole mass(MBH) and other galaxy properties at z=0 in the TNG simulations. We find that the central black hole mass can be accurately predicted with just a few galaxy properties only if the central black hole …

Quantics Tensor Trains: The Study Of A Continuous Lattice Model And Beyond, Aleix Bou Comas

Dissertations, Theses, and Capstone Projects

This four-chapter dissertation studies the efficient discretization of continuous variable functions with tensor train representation. The first chapter describes all the methodology used to discretize functions and store them efficiently. In this section, the algorithm tensor renormalization group is explained for self-containment purposes. The second chapter centers around the XY model. Quantics tensor trains are used to describe the transfer matrix of the model and compute one and two-dimensional quantities. The one dimensional magnitudes are compared to analytical results with an agreement close to machine precision. As for two dimensions, the analytical results cannot be computed. However, the critical temperature …

Three Essays Applying Dynamic Models In Economics, Finance, And Machine Learning, Lucas C. Dowiak

Dissertations, Theses, and Capstone Projects

This dissertation is a composition in three parts. Collectively, these essays investigate dynamic methods and their application in the fields of Economics, Finance, and Machine Learning. It pulls liberally from all three. In particular, this dissertation makes repeated use of multi-state modeling frameworks popular in Economics to bring a faceted view to the underlying data and detect its hidden heterogeneity. The challenge of modeling financial assets and estimating their dependence is another focus. For stimulus, concepts in the Machine Learning field are brought in to aid or compete with established econometric techniques.

Econometric Applications of the Hierarchical Mixture-of-Experts

In this …

Engineering Thermodynamics, Paul J. Marchese

Open Educational Resources

This collection of assignments is designed for an introductory thermodynamics class. It includes comprehensive readings that cover the fundamental concepts, problem sets to reinforce learning through practical application, and YouTube videos that provide detailed explanations and visual demonstrations of the material. These resources can be utilized in a regular classroom setting or for independent study, offering flexibility to accommodate different learning environments and preferences.

On A Generalization Of A Theorem Of Ibukiyama To Evaluate Three Imprimitive Character Sums, Brad Isaacson

Publications and Research

In a previous paper, we expressed three families of character sums by certain generalized Bernoulli functions which in turn were expressed by generalized Bernoulli numbers via a complicated and indirect process. In this paper, we generalize a theorem of Ibukiyama to directly express these generalized Bernoulli functions by generalized Bernoulli numbers. As a result, we can express the three families of character sums by generalized Bernoulli numbers in a more elegant fashion than was done before.