Physical Sciences and Mathematics Commons^™

Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre

SMU Data Science Review

Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …

From Small Molecules To Infinite Crystals: Probing Noncovalent Interactions Through Vibrational Spectroscopy, Sadisha Nanayakkara

Chemistry Theses and Dissertations

During my four years in the CATCO group supervised by Dr. Kraka, I have been exposed to various topics targeted to address a multitude of chemical problems, broadening our knowledge of modern chemistry research as we know it. In undertaking the age-old problem of understanding the nature of chemical bonding, I could modestly contribute with my work, using in-house tools based on vibrational spectroscopy.

First part of my dissertation is focused on inventing new methods and tools to efficiently investigate chemical bonding, followed by the study of some non-covalent interactions, imperative in catalysis and solid-state chemistry. This includes analysis of …

I. Non-Degradable Polysiloxane Networks For Controlled Release Applications, And Ii. Additive Free, Degradable Silyl-Ether Furyl-Maleimide Networks, Caleb M. Bunton

Chemistry Theses and Dissertations

I. Two different series of non–degradable polysiloxane networks were prepared for the encapsulation and controlled release of a small molecule agent. For the first series, hydrosilylation was utilized to prepare networks of varying crosslink densities, as determined from swelling studies, from vinyl terminated and silylhydride functional poly(dimethyl)siloxanes. For the second series, the thiol-ene reaction was utilized to prepare networks of varying crosslink densities, as determined from swelling studies, from vinyl terminated and mercaptopropyl functional poly(dimethyl)siloxanes. Nile red dye was used as an encapsulated agent and dye release from each series of networks was measured using UV–vis spectroscopy to determine controllability …

Unravel Allostery Mechanism Through Molecular Dynamic Simulations With Machine Learning Approaches, Hongyu Zhou

Chemistry Theses and Dissertations

Allostery is referred to as protein function changes due to external perturbations, and ubiquitous in the living cells. Investigation of the allosteric mechanism is essential for developing drugs or assisting protein engineering. Recently, the population shift model has been proposed to explain the allosteric mechanism. This model emphasizes the importance of conformational distribution in the allostery. In the past several years, I have been continuously working on developing computational methods to explore and quantify protein allostery mechanism. By fully utilizing protein simulation results, several machine learning related methods have been applied to protein systems to investigate the underlying conformational changes …