Physical Sciences and Mathematics Commons^™

Metallacycle-Mediated Cross-Coupling As An Enabling Tool For Studies In Carbocycle Synthesis And Functionalization, Adam Barry Millham

Dartmouth College Ph.D Dissertations

Natural products, specifically complex, carbocyclic natural products, have served as the inspiration for novel methods development for decades. Over that time, metallacycle-mediated cross-coupling has arisen as a powerful means for the synthesis of fused carbocycles. This work details three methods for the synthesis and functionalization of carbocyclic motifs that have been enabled by Ti-mediated cross-coupling reactions. The first of these studies include a complementary method to the Pauson–Khand reaction for the synthesis of highly substituted cyclopentenones via Ti-mediated alkyne–β-ketoester coupling. The second project, a modern approach to steroidal tetracycles, will be discussed that features: (1) an alkoxide-directed metallacycle-mediated [2+2+2] annulation …

Development Of Novel Nucleophile-Intercepted Beckmann Fragmentations And Progress Toward The Total Synthesis Of 2(S)-Cathafoline, Evan M. Dunkley

Dartmouth College Master’s Theses

This thesis is comprised of two chapters, the first being the discovery of a novel nucleophile-intercepted Beckmann fragmentation of [2.2.1] indoline systems that resulted in highly stereo- and regioselective reactions. Chapter one details the exploration of this reaction as well as its relevant background information detailing its significance. Chapter two describes the application of the novel nucleophile-intercepted Beckmann fragmentation in the context of a total synthesis of akuammilline alkaloid 2(S)-cathafoline. While the target natural product was never synthesized, unpredicted reactivity resulted in interesting discoveries worthy of discussion.

Efforts Towards The Asymmetric De Novo Synthesis Of Lanostanes And Euphanes, Htoo Tint Wai

Dartmouth College Ph.D Dissertations

Tetracyclic triterpenoids are ubiquitous in nature and biology, with members displaying a wide range of medically relevant properties and occupying rather distinct regions of chemical space. Members of this large class include well-known steroid hormones and sterols as well as structurally interesting subclasses such as lanostanes and euphanes, among others. Comprised of the tetracyclic skeleton with three stereodefined quaternary centers at ring-junction positions, lanostanes and euphanes present synthetic challenges that are different from those encountered in efforts targeting the structurally less complex steroid hormones. Lanostanes, in particular, stand as a historically important class of compounds as significant attention has been …

The Impact Of Contact Geometry On Sea Ice Stress And Fracture At The Scale Of Ice Floes, Michael J. May

Dartmouth College Master’s Theses

Observations of stress and strain at the scale of ice floes are necessary to fill a gap in our understanding of sea ice mechanical behavior. Current climate and ice dynamics models represent ice mechanical properties using stress-strain relationships largely determined at laboratory-scale (<1m) or from regional-scale (10+km) deformation observations. The former scale does not include all mechanisms of deformation operating in the ice pack; the latter aggregates multiple modes of deformation into non-physical fluid analogies. The Sea Ice Dynamics Experiment (SIDEx) was run in Feb-Mar 2021 to fill this gap, observing stress and strain at the scale of sea ice failure processes. Here we present stress sensor observations. Stress gages (N=31) were deployed over a 4.5km² area in the southern Beaufort Sea to observe in-situ stress. These data were analyzed in the context of deformation observations from satellite imagery and local laser and radar interferometers to explain the drivers of sea ice stress variations before and after fracture. Three case studies between 14 March and 24 March, during which fractures propagated through …

Converting Hydrazone-Based Photoswitches Into Functional Materials, Sirun Yang

Dartmouth College Ph.D Dissertations

The development of new classes of molecular switches with enhanced performance and brand-new functionalities enables practitioners to push the frontiers of adaptive materials. In the realm of photoswitches, the bistability of hydrazones (i.e., molecules that incorporate the C=N-NH functional group) allows for the kinetic trapping of polymer and supramolecular assemblies resulting in multistate actuation and emergent phenomena that are not tractable with other photoswitches. This property has transformed hydrazone photoswitches into powerful tools that can be used in understanding fundamental molecular interactions and how to apply them in modulating the physicochemical properties of materials.

Progressing from disordered to …

Geomorphic And Paleoclimatic Implications Of Glacial Extent Records In The Sierra Nevada Del Cocuy, Colombia During Termination 1, Jordan Nickerson Herbert

Dartmouth College Master’s Theses

Reconstructions of past glacial extents using geomorphic mapping and cosmogenic dating provide an opportunity to infer past climates. A record of the past extents of tropical mountain glaciers is particularly useful because there are few other means to reconstruct past temperatures in high-altitude, low-latitude locations. The tropics play an outsized role in mediating global climate, yet there is a lack of understanding of how the tropics may have influenced past climate changes such as the most recent deglaciation (Termination 1, ~18–11.7 ka). Improving reconstructions of tropical mountain glaciers will aid in understanding the role of the tropics in the global …

On The Thom Isomorphism For Groupoid-Equivariant Representable K-Theory, Zachary J. Garvey

Dartmouth College Ph.D Dissertations

This thesis proves a general Thom Isomorphism in groupoid-equivariant KK-theory. Through formalizing a certain pushforward functor, we contextualize the Thom isomorphism to groupoid-equivariant representable K-theory with various support conditions. Additionally, we explicitly verify that a Thom class, determined by pullback of the Bott element via a generalized groupoid homomorphism, coincides with a Thom class defined via equivariant spinor bundles and Clifford multiplication. The tools developed in this thesis are then used to generalize a particularly interesting equivalence of two Thom isomorphisms on TX, for a Riemannian G-manifold X.

A Smartwatch Step-Counting App For Older Adults: Development And Evaluation Study, George Boateng, Curtis L. Petersen, David Kotz, Karen L. Fortuna, Rebecca Masutani, John A. Batsis

Dartmouth Scholarship

Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have …

Space-Efficient Algorithms And Verification Schemes For Graph Streams, Prantar Ghosh

Dartmouth College Ph.D Dissertations

Structured data-sets are often easy to represent using graphs. The prevalence of massive data-sets in the modern world gives rise to big graphs such as web graphs, social networks, biological networks, and citation graphs. Most of these graphs keep growing continuously and pose two major challenges in their processing: (a) it is infeasible to store them entirely in the memory of a regular server, and (b) even if stored entirely, it is incredibly inefficient to reread the whole graph every time a new query appears. Thus, a natural approach for efficiently processing and analyzing such graphs is reading them as …

Determining American Sign Language Joint Trajectory Similarity Using Dynamic Time Warping (Dtw), Rohith Mandavilli

Computer Science Senior Theses

As American Sign Language (ASL), the language used by Deaf/Hard of Hearing (D/HH) Americans has grown in popularity in recent years, an unprecedented number of schools and organizations now offer ASL classes. Many hold misconceptions about ASL, assuming it is easily learned; however due to its rich, complex grammatical construction, it’s not mastered easily beyond a basic level. Therefore, it becomes ever more important to improve upon existing techniques to teach ASL. The Dartmouth Applied Learning Initiative (DALI) at Dartmouth college in coordination with the Robotics and Reality Lab developed an application on the Oculus Quest that helps D/HH individuals …

A Bidirectional Formulation For Walk On Spheres, Yang Qi

Dartmouth College Master’s Theses

Poisson’s equations and Laplace’s equations are important linear partial differential equations (PDEs)
widely used in many applications. Conventional methods for solving PDEs numerically often need to
discretize the space first, making them less efficient for complex shapes. The random walk on spheres
method (WoS) is a grid-free Monte-Carlo method for solving PDEs that does not need to discrete the
space. We draw analogies between WoS and classical rendering algorithms, and find that the WoS
algorithm is conceptually identical to forward path tracing.
We show that solving the Poisson’s equation is equivalent to solving the Green’s function for every
pair of …

Towards A Computational Model Of Narrative On Social Media, Anne Bailey

Dartmouth College Undergraduate Theses

This thesis describes a variety of approaches to developing a computational model of narrative on social media. Our goal is to use such a narrative model to identify efforts to manipulate public opinion on social media platforms like Twitter. We present a model in which narratives in a collection of tweets are represented as a graph. Elements from each tweet that are relevant to potential narratives are made into nodes in the graph; for this thesis, we populate graph nodes with tweets’ authors, hashtags, named entities (people, locations, organizations, etc.,), and moral foundations (central moral values framing the discussion). Two …

Machine Learning And The Network Analysis Of Ethereum Trading Data, Santosh Sivakumar

Dartmouth College Undergraduate Theses

Since their conception, cryptocurrencies have captured the public interest, motivating a growing body of research aimed at exploring blockchain-based transactions. This said, little work has been done to draw conclusions from transaction patterns, particularly in the realm of predicting cryptocurrency price movements. Moreover, research in the cryptocurrency sphere largely focuses on Bitcoin, paying little attention to Ethereum, Bitcoin's second-in-line with respect to market capitalization. In this paper, we construct hourly networks for a year of Ethereum transactions, using computed graph metrics as features in a series of machine learning models. We find that regression-based approaches to predicting Ether prices/price deltas …

Designing Narrative-Based Interfaces For Collective Action: A Case Study Using Amazon, Climate Change, And Consumer Behavior, Catherine Parnell

Dartmouth College Undergraduate Theses

Climate change is the most pressing issue facing future generations. Amongst expanses of the population there is a lack of collective action on environmental issues, as there is a large gap between awareness and behavior change. This study suggests persuasive design that utilizes a narrative framing as a solution to reduce barriers to engaging in issues of collective action. Through extensive need-finding studies to understand target users, this thesis uses online-shopping via Amazon as a context for arguing that narrative can support actionable change in behavior. The technical artifact resulting from this research is a developed chrome extension and web …

Torsh: Obfuscating Consumer Internet-Of-Things Traffic With A Collaborative Smart-Home Router Network, Adam Vandenbussche

Dartmouth College Undergraduate Theses

When consumers install Internet-connected "smart devices" in their homes, metadata arising from the communications between these devices and their cloud-based service providers enables adversaries privy to this traffic to profile users, even when adequate encryption is used. Internet service providers (ISPs) are one potential adversary privy to users’ incom- ing and outgoing Internet traffic and either currently use this insight to assemble and sell consumer advertising profiles or may in the future do so. With existing defenses against such profiling falling short of meeting user preferences and abilities, there is a need for a novel solution that empowers consumers to …

Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston

Computer Science Senior Theses

The ability of patients to understand health-related text is important for optimal health outcomes. A system that can automatically annotate medical entities could help patients better understand health-related text. Such a system would also accelerate manual data annotation for this low-resource domain as well as assist in down- stream medical NLP tasks such as finding textual similarity, identifying conflicting medical advice, and aspect-based sentiment analysis. In this work, we investigate a state-of-the-art entity set expansion model, BootstrapNet, for the task of medical entity classification on a new dataset of medical advice text. We also propose EP SBERT, a simple model …

Symplectically Integrated Symbolic Regression Of Hamiltonian Dynamical Systems, Daniel Dipietro

Computer Science Senior Theses

Here we present Symplectically Integrated Symbolic Regression (SISR), a novel technique for learning physical governing equations from data. SISR employs a deep symbolic regression approach, using a multi-layer LSTMRNN with mutation to probabilistically sample Hamiltonian symbolic expressions. Using symplectic neural networks, we develop a model-agnostic approach for extracting meaningful physical priors from the data that can be imposed on-the-fly into the RNN output, limiting its search space. Hamiltonians generated by the RNN are optimized and assessed using a fourth-order symplectic integration scheme; prediction performance is used to train the LSTM-RNN to generate increasingly better functions via a risk-seeking policy gradients …

Cysteine Metallochemistry And Metal Binding: Quantification Of The Thermodynamic Foundations Of Cellular Homeostasis, Matthew R. Mehlenbacher

Dartmouth College Ph.D Dissertations

Metals are required for life. Many metalloproteins contain cysteine in their metal-binding site (MBS) and cysteines are unique in that they are reactive, and strongly bind certain metals, which aid in metal selectivity and specificity. Using isothermal titration calorimetry (ITC), the thermodynamic foundation for metal binding, cellular protection, and transcriptional regulation, which all utilize cysteines in their MBS, are quantified.

In bacteria there are metalloprotein pathways that actively uptake mercury, which are regulated by the metalloregulatory protein MerR. MerR de-represses the transcription of these mer proteins in a metal-dependent manner. Using ITC, the thermodynamic foundation of the negative allosteric coupling …

Information Provenance For Mobile Health Data, Taylor A. Hardin

Dartmouth College Ph.D Dissertations

Mobile health (mHealth) apps and devices are increasingly popular for health research, clinical treatment and personal wellness, as they offer the ability to continuously monitor aspects of individuals' health as they go about their everyday activities. Many believe that combining the data produced by these mHealth apps and devices may give healthcare-related service providers and researchers a more holistic view of an individual's health, increase the quality of service, and reduce operating costs. For such mHealth data to be considered useful though, data consumers need to be assured that the authenticity and the integrity of the data has remained intact---especially …

Approaching Quantum-Limited Electrometry In The Single-Photon Regime, Sisira Kanhirathingal

Dartmouth College Ph.D Dissertations

Mesoscopic quantum systems currently serve as essential building blocks in many quantum information and metrology devices. This thesis investigates the potential of quantum-limited detection in a mesoscopic electrometer named the cavity-embedded Cooper pair transistor (cCPT). As one application, this charge detector can act as the basis for an optomechanical system in the single-photon strong coupling regime. The realization of this scheme would entail near quantum-limited, ultra-sensitive electrometry at the single-photon level, the feasibility of which is studied at length in this thesis.

On the one hand, we approach this question using a fundamental, first-principles study, where an operator scattering model …

Protecting Systems From Exploits Using Language-Theoretic Security, Prashant Anantharaman

Dartmouth College Ph.D Dissertations

Any computer program processing input from the user or network must validate the input. Input-handling vulnerabilities occur in programs when the software component responsible for filtering malicious input---the parser---does not perform validation adequately. Consequently, parsers are among the most targeted components since they defend the rest of the program from malicious input. This thesis adopts the Language-Theoretic Security (LangSec) principle to understand what tools and research are needed to prevent exploits that target parsers. LangSec proposes specifying the syntactic structure of the input format as a formal grammar. We then build a recognizer for this formal grammar to validate any …

Automated Filament Inking For Multi-Color Fff 3d Printing, Eammon Littler

Dartmouth College Master’s Theses

We propose a novel system for low-cost multi-color Fused Filament Fabrication (FFF) 3D printing, allowing for the creation of customizable colored filament using a pre-processing approach. We developed an open-source device to automatically ink filament using permanent markers. Our device can be built using 3D printed parts and off-the-shelf electronics. An accompanying web-based interface allows users to view GCODE toolpaths for a multi-color print and quickly generate filament color profiles. Taking a pre-processing approach makes this system compatible with the majority of desktop 3D printers on the market, as the processed filament behaves no differently from conventional filaments. Furthermore, inked …

A Machine-Verified Proof Of Linearizability For A Queue Algorithm, Ugur Yavuz

Dartmouth College Master’s Theses

Proofs of linearizability are typically intricate and lengthy, and readers may find it difficult to verify their correctness. We present a unique technique for producing proofs of linearizability that are fully verifiable by a mechanical proof system, thereby eliminating the need for any manual verification. Specifically, we reduce the burden of proving linearizable object implementations correct to the proof of a particular invariant whose correctness can be shown inductively. Noting that the latter is a task that many proof systems (such as the TLA+ Proof System we chose to work with) are well-suited to handle, this technique allows us to …

The Feasibility And Utility Of Harnessing Digital Health To Understand Clinical Trajectories In Medication Treatment For Opioid Use Disorder: D-Tect Study Design And Methodological Considerations, Lisa A. Marsch, Ching-Hua Chen, Sara R. Adams, Asma Asyyed, Monique B. Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C. Jacobson, Heather K. Jones, David Kotz, Chantal A. Lambert-Harris, Zhiguo Li, Bethany Mcleman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Cynthia I. Campbell

Dartmouth Scholarship

Introduction: Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substance use during substance use disorder treatment. However, much of this literature has examined a small set of potential moderators or mediators of outcomes in MOUD treatment and may lead to over-simplified accounts of treatment non-adherence. Digital health methodologies offer great promise for capturing intensive, longitudinal ecologically-valid …

Entity Based Sentiment Analysis For Textual Health Advice, Dae Lim Chung

Computer Science Senior Theses

This work explores entity based sentiment analysis for textual health advice through deep learning. We fine tuned a pretrained BERT model to analyze sentiments across five different predetermined categories which consist of food, medicine, disease, exercise, and vitality for three different sentiments: positive, negative, and neutral. Original set of annotated medical dataset from Dartmouth College’s Persist Lab was used to conduct the experiments. For the aim of tailoring the data for the purpose of entity based sentiment analysis, we explored data transformation techniques to generate optimum training examples. During the experiments, we were able to discover that the wide variety …

The Three-Way Interplay Among Early Life Exposures, The Gut Microbiome, And Outcomes In Infancy, Yuka Moroishi

Dartmouth College Ph.D Dissertations

The bidirectional relationship between the gut microbiome and immune system plays an important role in host immune status: the immune system provides the gut microbiome the optimal environment to thrive in, and the gut microbiome helps regulate the immune system. This relationship is especially important in infants, whose immune system is still premature and rely on innate immunity.

We investigated the three-way interplay among early-life exposures, the developing gut microbiome, and outcomes in infancy from the general population in New Hampshire, US. We used prospective cohort data from the New Hampshire Birth Cohort study to 1) determine whether timing of …

Correlations And Reuse For Fast And Accurate Physically Based Light Transport, Benedikt Bitterli

Dartmouth College Ph.D Dissertations

Light transport is the study of the transfer of light between emitters, surfaces, media and sensors. Fast simulations of light transport play a pivotal role in photo-realistic image synthesis, and find many applications today, including predictive manufacturing, machine learning, scientific visualization and the movie industry. In order to accurately reproduce the appearance of real scenes, light transport must closely approximate the physical laws governing the flow of light. Physically based rendering is a set of principles for codifying these laws into a mathematical model, and is the predominant rendering methodology today.

The representational power of this model is limited to …

Temporally Sliced Photon Primitives For Volumetric Time-Of-Flight Rendering, Yang Liu

Dartmouth College Master’s Theses

Traditional steady-state rendering assumes that the light transport has already reached equilibrium. In contrast, time-of-flight rendering removes this assumption and recovers the pattern of light at extremely high temporal resolutions. This novel rendering modality not only provides a way to visualize the propagation of light, but can also empower the advances in time-of-flight imaging and its corresponding applications.

Building on previous work in steady-state volumetric rendering, this thesis introduces a novel framework for deriving new Monte Carlo estimators for solving the time-of-flight rendering problem in participating media. Conceptually, our method starts with any steady-state photon primitive, like a photon plane …

Detecting The Presence Of Electronic Devices In Smart Homes Using Harmonic Radar, Beatrice Perez, Gregory Mazzaro, Timothy J. Pierson, David Kotz

Dartmouth Scholarship

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things' now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in …

Analyzing Behavioral Adaptation To Covid-19 And Return To Pre-Pandemic Baselines In A Cohort Of College Seniors, Vlado Vojdanovski

Computer Science Senior Theses

As the critical phase of the COVID-19 pandemic seems to be winding down, it is important to analyze the adjustment to COVID-19 and return to normalcy of various populations. In this study we focus on the behavioral adjustments exhibited by a cohort of N=114 college seniors. To infer COVID-19 adjustment we compare the 2021 year (second year of COVID-19) to the 2020 year (first year of COVID-19) and 2019 (prepandemic baseline year). We begin with a broad analysis between the second and first covid year, finding that the second year of COVID-19 shows significant returns to pre-pandemic baselines on multiple …