Physical Sciences and Mathematics Commons^™

Improved Computational Prediction Of Function And Structural Representation Of Self-Cleaving Ribozymes With Enhanced Parameter Selection And Library Design, James D. Beck

Boise State University Theses and Dissertations

Biomolecules could be engineered to solve many societal challenges, including disease diagnosis and treatment, environmental sustainability, and food security. However, our limited understanding of how mutational variants alter molecular structures and functional performance has constrained the potential of important technological advances, such as high-throughput sequencing and gene editing. Ribonuleic Acid (RNA) sequences are thought to play a central role within many of these challenges. Their continual discovery throughout all domains of life is evidence of their significant biological importance (Weinreb et al., 2016). The self-cleaving ribozyme is a class of noncoding Ribonuleic Acid (ncRNA) that has been useful for …

Towards Making Transformer-Based Language Models Learn How Children Learn, Yousra Mahdy

Boise State University Theses and Dissertations

Transformer-based Language Models (LMs), learn contextual meanings for words using a huge amount of unlabeled text data. These models show outstanding performance on various Natural Language Processing (NLP) tasks. However, what the LMs learn is far from what the meaning is for humans, partly due to the fact that humans can differentiate between concrete and abstract words, but language models make no distinction. Concrete words are words that have a physical representation in the world such as “chair”, while abstract words are ideas such as “democracy”. The process of learning word meanings starts from early childhood when children acquire their …

Computational Approaches To Understanding Subduction Zone Geodynamics, Surface Heat Flow, And The Metamorphic Rock Record, Buchanan C. Kerswell

Boise State University Theses and Dissertations

Pressure-temperature (PT) estimates from exhumed high-pressure (HP) metamorphic rocks and global surface heat flow observations evidently encode information about subduction zone thermal structure and the nature of mechanical and chemical processing of subducted materials along the interface between converging plates. Previous work demonstrates the possibility of decoding such geodynamic information by comparing numerical geodynamic models with empirical observations of surface heat flow and the metamorphic rock record. However, ambiguous interpretations can arise from this line of inquiry with respect to thermal gradients, plate coupling, and detachment and recovery of subducted materials. This dissertation applies a variety of computational techniques to …

Modeling Real And Fake News Sharing In Social Networks, Abishai Joy

Boise State University Theses and Dissertations

Online media is changing the traditional news industry and diminishing the role of journalists, newspapers, and even news channels. This in turn is enhancing the ability of fake news to influence public opinion on important topics. The threat of fake news is quite imminent, as it allows malicious users to share their agenda with a larger audience. Major social media platforms like Twitter, Facebook, etc., are making it easy to spread fake news due to the minimal moderation/ fact-checking on these platforms.

This work aims at predicting fake and real news sharing in social media. Specifically, we employ a multi-level …

Modeling And Analyzing Users' Privacy Disclosure Behavior To Generate Personalized Privacy Policies, A.K.M. Nuhil Mehdy

Boise State University Theses and Dissertations

Privacy and its importance to society have been studied for centuries. While our understanding and continued theory building to hypothesize how users make privacy disclosure decisions has increased over time, the struggle to find a one-size solution that satisfies the requirements of each individual remains unsolved. Depending on culture, gender, age, and other situational factors, the concept of privacy and users' expectations of how their privacy should be protected varies from person to person. The goal of this dissertation is to design and develop tools and algorithms to support personal privacy management for end-users. The foundation of this research is …

Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi

Boise State University Theses and Dissertations

Unsupervised Graph Representation Learning methods learn a numerical representation of the nodes in a graph. The generated representations encode meaningful information about the nodes' properties, making them a powerful tool for tasks in many areas of study, such as social sciences, biology or communication networks. These methods are particularly interesting because they facilitate the direct use of standard Machine Learning models on graphs. Graph representation learning methods can be divided into two main categories depending on the information they encode, methods preserving the nodes connectivity information, and methods preserving nodes' structural information. Connectivity-based methods focus on encoding relationships between nodes, …

A 30-Year Agroclimatic Analysis Of The Snake River Valley American Viticultural Area - Descriptive And Predictive Methods, Charles L. Becker

Boise State University Theses and Dissertations

Climate change poses serious threats to global agriculture, however some localities and crops may benefit from increasing temperatures. Grape production in southern Idaho may be a beneficial example as vineyard acreage has increased over 300% since the designation of the Snake River American Viticultural Area (SRVAVA) in 2007. We perform a statistical characterization of agroclimate within the SRVAVA that centers around four primary objectives: utilization of a novel, 30-year high resolution climate dataset to provide insight and agrometrics unavailable at coarser resolutions, climatic implications of the unique topography within the SRVAVA, identification of statistical trends, and correlation of SRVAVA climate …

A Sense Of Scale: Mapping Exotic Annual Grasses With Satellite Imagery Across A Landscape And Quantifying Their Biomass At A Plot Level With Structure-From-Motion In A Semi-Arid Ecosystem, Monica Vermillion

Boise State University Theses and Dissertations

The native vegetation communities in the sagebrush steppe, a semi-arid ecosystem type, are under threat from exotic annual grasses. Exotic annual grasses increase fire severity and frequency, decrease biodiversity, and reduce soil carbon storage amongst other ecosystem services. The invasion of exotic annual grasses is causing detrimental impacts to land use by eliminating forage for livestock and creating a huge economic cost from fire control and post-fire restoration. To combat invasion, land managers need to know what exotic annual grasses are present, where they are invading, and estimates of their biomass. Mapping exotic annual grasses is challenging because many areas …

Improving Spellchecking For Children: Correction And Design, Brody Downs

Boise State University Theses and Dissertations

Children commonly use software applications such as search engines and word processors in the classroom environment. However, a major barrier to using these programs successfully is the ability of children to type and spell effectively. While many programs make use of spellcheckers to provide spelling corrections to their users, they are designed for more traditional users (i.e., adults) and have proven inadequate for children. The aims of this work is twofold: first, to address the types of spelling errors children make by researching, developing, and evaluating algorithms to generate and rank candidate spelling suggestions; and second, to evaluate the impact …

Characterizing Dryland Ecosystems Using Remote Sensing And Dynamic Global Vegetation Modeling, Abdolhamid Dashtiahangar

Boise State University Theses and Dissertations

Drylands include all terrestrial regions where the production of crops, forage, wood and other ecosystem services are limited by water. These ecosystems cover approximately 40% of the earth terrestrial surface and accommodate more than 2 billion people (Millennium Ecosystem Assessment, 2005). Moreover, the interannual variability of the global carbon budget is strongly regulated by vegetation dynamics in drylands. Understanding the dynamics of such ecosystems is significant for assessing the potential for and impacts of natural or anthropogenic disturbances and mitigation planning, and a necessary step toward enhancing the economic and social well-being of dryland communities in a sustainable manner (Global …

Uncovering New Links Through Interaction Duration, Laxmi Amulya Gundala

Boise State University Theses and Dissertations

Link Prediction is the problem of inferring new relationships among nodes in a network that can occur in the near future. Classical approaches mainly consider neighborhood structure similarity when linking nodes. However, we may also want to take into account whether the two nodes we are going to link will benefit from that by having an active interaction over time. For instance, it is better to link two nodes � and � if we know that these two nodes will interact in the social network in the future, rather than suggesting �, who may never interact with �. Thus, the …

Document Classification, Shane K. Panter

Boise State University Theses and Dissertations

We present an overview of the document classification process and present research conducted against the newly constructed SBIR-STTR corpus. Specifically, the current methods in use for annotation, corpus construction, feature construction, feature weighting, and classifier algorithms are surveyed. We introduce a new dataset derived from public data downloaded from sbir.gov and the Text Annotation Toolkit (TAT) ₁ for use in classification research.

TAT is a collection of independent components packaged together into one open source software application. TAT was engineered to support the document classification process and workflow. Tracking of changes in a working corpus, saving data used in the …

On The K-Mer Frequency Spectra Of Organism Genome And Proteome Sequences With A Preliminary Machine Learning Assessment Of Prime Predictability, Nathan O. Schmidt

Boise State University Theses and Dissertations

A regular expression and region-specific filtering system for biological records at the National Center for Biotechnology database is integrated into an object oriented sequence counting application, and a statistical software suite is designed and deployed to interpret the resulting k-mer frequencies|with a priority focus on nullomers. The proteome k-mer frequency spectra of ten model organisms and the genome k-mer frequency spectra of two bacteria and virus strains for the coding and non-coding regions are comparatively scrutinized. We observe that the naturally-evolved (NCBI/organism) and the artificially-biased (randomly-generated) sequences exhibit a clear deviation from the artificially-unbiased (randomly-generated) histogram distributions. …