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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Cosmological Inflation In N-Dimensional Gaussian Random Fields With Algorithmic Data Compression, Connor A. Painter
Cosmological Inflation In N-Dimensional Gaussian Random Fields With Algorithmic Data Compression, Connor A. Painter
Honors Theses
The leading modern theories of cosmological inflation are increasingly multi-dimensional. The “inflaton field” φ that has been postulated to drive accelerating expansion in the very early universe has a corresponding potential function V , the details of which, such as the number of dimensions and shape, have yet to be specified. We consider a natural hypothesis that V ought to be maximally random. We realize this idea by defining the V as a Gaussian random field in some number N of dimensions. We repeatedly simulate of the evolution of φ given a set of conditions on the “landscape” of V …
An Introduction To Obstacle Problems, Calvin Reedy
An Introduction To Obstacle Problems, Calvin Reedy
Honors Theses
The obstacle problem can be used to predict the shape of an elastic membrane lying over an obstacle in a domain Ω. In this paper we introduce and motivate a mathematical formulation for this problem, and give an example to demonstrate the need to search for solutions in non-classical settings. We then introduce Sobolev spaces as the proper setting for solutions, and prove that unique solutions exist in W1,2(Ω).
Stereochemical Control In Suzuki Cross Coupling Reactions Of Acyclic (Z)-Beta-Haloacroleins, William Carrick
Stereochemical Control In Suzuki Cross Coupling Reactions Of Acyclic (Z)-Beta-Haloacroleins, William Carrick
Honors Theses
Beta-chloroenals are readily accessible substances and are efficient precursors for a variety of heterocyclic compounds. Suzuki type cross-coupling reactions of such compounds with arylboronic acids yield ��,��-diarylacroleins with control of stereochemistry. The oxidation of these enals to the corresponding acids and subsequent oxidative lactonization leads to formation of the respective coumarins. The chemistry involved in these transformations with special attention to stereochemistry of the Suzuki coupling reaction will be discussed. A full NMR analysis involving 1H, 13C, COSY, NOESY, HSQC, and HMBC was performed to unambiguously confirm the structure and show that the reaction proceeds with retention of stereochemistry.
Overdose Prevention Sites Placement Informed By Simulation, Jing Dong
Overdose Prevention Sites Placement Informed By Simulation, Jing Dong
Honors Theses
In Philadelphia, people are experiencing the greatest opioid crisis in a century. Plac- ing the Overdose Prevention Site (OPS) can alleviate this crisis. However, the journey to the successful launch of the first OPS in the USA is rough. It was first accused of having a collision with federal drug laws. While Safehouse won the lawsuit and the OPS was judged to be legal in 2020, other pressure rose afterward such as the against from the public and the COVID19, which delayed the plan to open the OPS. Without solid research on the effectiveness of OPS, we thought it is …
Understanding Model Reasoning In Automated Speech Systems: Implementing A Prototype Explanation System Using The Lime Method, Vadim Kudlay
Understanding Model Reasoning In Automated Speech Systems: Implementing A Prototype Explanation System Using The Lime Method, Vadim Kudlay
Honors Theses
The field of voice processing has seen great advancements thanks in part to the rise of deep learning. However, the application of these deep learning techniques with an audio input space leads to an interesting result not commonly found when dealing with other input domains. Namely, common techniques for generating auditory adversarial samples using gradient-based optimization have been observed to have extremely low transferability among even the same model structure. This implies an inherent difference in the latent representations of audio samples that may be worth investigating in the pursuit of a more resilient and interpretable voice processing framework. Our …
Adhering Homogeneous Molecular Electrocatalysts Entrapped In Micelles To Electrode Surfaces, Emily Kuhlmann
Adhering Homogeneous Molecular Electrocatalysts Entrapped In Micelles To Electrode Surfaces, Emily Kuhlmann
Honors Theses
Heterogeneous catalysts are important to industrial use; however, mechanistic studies are difficult because they lack the easy tunability of homogeneous catalysts. One solution could be to immobilize homogeneous catalysts using micelles while maintaining catalytic properties and activities.
Fact-Checking Of Claims From The English Wikipedia Using Evidence In The Wild, Aalok Sathe
Fact-Checking Of Claims From The English Wikipedia Using Evidence In The Wild, Aalok Sathe
Honors Theses
Automated fact checking is a task in the domain of Natural Language Processing that deals with the verification of claims using evidence. Fact checking is becoming increasingly important as large amounts of human-generated information accumulate online. In the recent past, our society has witnessed large-scale spread of disinformation via the internet that has time and again led to noticeable disruptions in the fabric of society. Fact-checking would help mitigate the spread of disinformation by allowing large magnitudes of content to be automatically evaluated for disinformation. In this work, we construe and tackle multiple subtasks of fact checking using labeled data …
Bert Argues: How Attention Informs Argument Mining, Ting Chen
Bert Argues: How Attention Informs Argument Mining, Ting Chen
Honors Theses
Argument mining is the automatic identification and extraction of structure from argumentative language. Previous works have constrained the argument structure to forming strictly trees in order to utilize efficient tree-specific techniques. However, arguments in the wild are unlikely to exhibit this constrained structure. Given the recent trend of fine-tuning large pre-trained models to reach state of the art performance on a variety of Natural Language Processing (NLP) tasks, we look to leverage the power of these deep contextualized word embeddings towards the task of non-tree argument mining. In this paper, we introduce a new pipeline which utilizes pre-trained BERT based …