Physical Sciences and Mathematics Commons^™

Generating Species Assemblages For Restoration And Experimentation: A New Method That Can Simultaneously Converge On Average Trait Values And Maximize Functional Diversity, David C. Laughlin, Loïc Chalmandrier, Chaitanya Joshi, Michael Renton, John M. Dwyer, Jennifer L. Funk

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

1.Restoring resilient ecosystems in an era of rapid environmental change requires a flexible framework for selecting assemblages of species based on functional traits. However, current trait‐based models have been limited to algorithms that select species assemblages that only converge on specified average trait values, and could not accommodate the common desire among restoration ecologists to generate functionally diverse assemblages.

2.We have solved this problem by applying a nonlinear optimization algorithm to solve for the species relative abundances that maximize Rao's quadratic entropy (Q) subject to other linear constraints. Rao's Q is a closed‐form algebraic expression of functional diversity …

Going Negative: The Next Horizon In Climate Engineering Law, Tracy Hester, Michael B. Gerrard

Faculty Scholarship

As the global community struggles to turn the Paris Agreement’s commitments into meaningful emission reductions and the United States turbulently reverses its climate policies, the potential role of “negative emissions technologies” and other climate engineering approaches is drawing increasingly serious attention. These technologies are engineering on the grandest scale: climate engineering seeks to offset the effects of anthropogenic climate change by either altering the solar radiation reaching the earth’s surface or changing the composition of the atmosphere itself. Specifically, negative emissions technologies would directly remove greenhouse gases (GHGs) from the ambient air and help to remove accumulated atmospheric carbon dioxide …

The Effects Of Fire On Snow Accumulation, Snowmelt And Ground Thaw On A Peat Plateau In Subarctic Canada, Elyse Mathieu

Theses and Dissertations (Comprehensive)

During the past century, the highest rates of warming have occurred at latitudes above 60^oN, where air temperatures have risen at twice the rate of other regions. In northwestern Canada, this warming has coincided with an increase in the frequency, size and severity of wildfires. The influence of such fires on the trajectory of on-going permafrost thaw is not well understood. As a consequence, the combined impacts of climate warming induced permafrost thaw and possible feedbacks arising from wildfires cannot be properly assessed. This study examines the impact of a 2.7 ha low-severity wildfire (July 2014) on water …

Abelian Subalgebras Of Maximal Dimension In Euclidean Lie Algebras, Mark Curro

Theses and Dissertations (Comprehensive)

In this paper we define, discuss and prove the uniqueness of the abelian subalgebra of maximal dimension of the Euclidean Lie algebra. We also construct a family of maximal abelian subalgebras and prove that they are maximal.

Nonlinear Coupled Effects In Nanomaterials, Sia Bhowmick

Theses and Dissertations (Comprehensive)

Materials at the nanoscale have different chemical, structural, and optoelectrical properties compared to their bulk counterparts. As a result, such materials, called nanomaterials, exhibit observable differences in certain physical phenomena. One such resulting phenomenon called the piezoelectric effect has played a crucial role in miniature self-powering electronic devices called nanogenerators which are fabricated by using nanostructures, such as nanowires, nanorods, and nanofilms. These devices are capable of harvesting electrical energy by inducing mechanical strain on the individual nanostructures. Electrical energy created in this manner does not have environmental limitations. In this thesis, important coupled effects, such as the nonlinear piezoelectric …

Spatial Modelling And Wildlife Health Surveillance: A Case Study Of White Nose Syndrome In Ontario, Lauren Yee

Theses and Dissertations (Comprehensive)

Wildlife data is often limited by survey effort, small sample sizes, and spatial biases associated with collection and missing data. These factors can create unique challenges from a surveillance perspective when trying to extract spatial patterns of habitat suitability and disease distributions for conservation and management purposes. This thesis examined data quality from a wildlife health database in the context of spatial analysis of wildlife disease. Spatial analysis of the data to predict habitat suitability of bats and white nose syndrome afflicted bats was examined by using the MaxEnt modelling method. Methods to reduce spatial bias were examined and specific …

Synthesis, Properties, And Solid-State Structures Of A Series Of 6,13-Dicyanoheteropentacene Analogues: Towards New Liquid Crystalline Materials, L Hiscock, Kenneth E. Maly, Louise N. Dawe

Theses and Dissertations (Comprehensive)

The focus of this thesis is the synthesis of novel heterocyclic pentacene analogs and the investigation of their self-organization for the development of new materials for organic electronics. The thesis consists of two interrelated projects: the first being development of an improved synthesis of a series of liquid crystalline dicyanotetraoxapentacenes (DCTOPs) while the second entails the exploratory synthesis of several novel dicyanoheteropentacene analogues and a preliminary investigation of their photophysical properties and solid-state structures. Both of these projects centre around the use of nucleophilic aromatic substitution reactions on tetrafluoroterephthalonitrile.

Soluble, tetrakis(bis(alkoxy)phenyl)-substituted DCTOPs were originally synthesised via a short synthesis complicated …

Landscape Scale Spectral-Temporal Modelling Of Bamboo-Dominated Forest Succession Within The Atlantic Forest Of Southern Brazil, Clara Greig

Theses and Dissertations (Comprehensive)

Tropical and subtropical ecosystems have become vulnerable to biological invasion (i.e., bamboo) due to human induced forest fragmentation. Bamboo ecological processes have been found to impede forest development, resulting in a state of arrested succession, which has been found to significantly reduce biodiversity, thus contributing to biotic homogenization. In this study we use a semi-empirical approach to develop a community-level spatially explicit ecological process model (hybrid model) using a time-series of Landsat imagery to describe single-landscape scale ecological processes of a pervasive bamboo species (Merostachys skvortzovii) found throughout the Araucaria forest, a critically threatened subtype of Atlantic forest …

Spatial And Temporal Variability Of The Snow Environment In The Western Canadian Arctic, Philip Mann

Theses and Dissertations (Comprehensive)

Snow cover in the Western Canadian Arctic is a significant input to the hydrological mass balance, it produces shelter and habitat for animals and humans, and supports interactions with vegetation and climate. The Arctic-tundra snow cover is greatly impacted by wind erosion, redistribution and deposition of snow during high wind events over the winter months. As a result, the end of winter snow cover is characterised by significant small-scale (on the order of a few meters) spatial variations in snow cover depth, density, and thus snow water equivalent (SWE), and runoff. Future climate related changes to snow cover depth and …

Permafrost Thaw-Induced Forest To Wetland Conversion: Potential Impacts On Snowmelt And Basin Runoff In Northwestern Canada, Emily Haughton

Theses and Dissertations (Comprehensive)

In the discontinuous permafrost zone of northwestern Canada, snow covers the ground surface for over half the year, thus snowmelt constitutes a primary source of ecosystem moisture supply and strongly influences stream hydrographs. The peat landscapes along the southern limit of discontinuous permafrost are dominated by forested permafrost plateaus (“forest”), and treeless, permafrost-free wetlands (“wetland”). Permafrost-thaw induced transformation of this landscape has changed water flow and storage processes and therefore introduced new uncertainties on the region’s water futures. Here, I a) characterize forest and wetland water storage and flow from snowmelt, and b) evaluate how permafrost thaw-induced wetland expansion at …

Effect Of Socioeconomic And Demographic Factors On Kentucky Crashes, Aaron Berry Cambron

Theses and Dissertations--Civil Engineering

The goal of this research was to examine the potential predictive ability of socioeconomic and demographic data for drivers on Kentucky crash occurrence. Identifying unique background characteristics of at-fault drivers that contribute to crash rates and crash severity may lead to improved and more specific interventions to reduce the negative impacts of motor vehicle crashes. The driver-residence zip code was used as a spatial unit to connect five years of Kentucky crash data with socioeconomic factors from the U.S. Census, such as income, employment, education, age, and others, along with terrain and vehicle age. At-fault driver crash counts, normalized over …

Investigation Of Volatile Organic Compounds (Vocs) Detected At Vapor Intrusion Sites, Mohammadyousef Roghani

Theses and Dissertations--Civil Engineering

This dissertation investigates unexplained vapor intrusion field data sets that have been observed at hazardous waste sites, including: 1) non-linear soil gas concentration trends between the VOC source (i.e. contaminated groundwater plume) and the ground surface; and, 2) alternative pathways that serve as entry points for vapors to infiltrate into buildings and serve to increase VOC exposure risks as compared to the classic vapor intrusion model, which primarily considered foundation cracks as the route for vapor entry. The overall hypothesis of this research is that theoretical knowledge of fate and transport processes can be systematically applied to vapor intrusion field …

Introduction To "Probability", Lawrence Leemis

Arts & Sciences Book Chapters

This calculus-based introduction to probability covers all of the traditional topics, along with a secondary emphasis on Monte Carlo simulation. Examples that introduce applications from a wide range of fields help the reader apply probability theory to real-world problems. The text covers all of the topics associated with Exam P given by the Society of Actuaries. Over 100 figures highlight the intuitive and geometric aspects of probability. Over 800 exercises are used to reinforce concepts and make this text appropriate for classroom use.

Investigating Intervention Components And Exploring States Of Receptivity For A Smartphone App To Promote Physical Activity: Study Protocol Of The Ally Micro-Randomized Trial, Jan-Niklas Kramer, Florian Künzler, Varun Mishra, Bastien Presset, David Kotz, Shawna Smith, Urte Scholz, Tobias Kowatsch

Dartmouth Scholarship

Background: Smartphones enable the implementation of just-in-time adaptive interventions (JITAIs) that tailor the delivery of health interventions over time to user- and time-varying context characteristics. Ideally, JITAIs include effective intervention components, and delivery tailoring is based on effective moderators of intervention effects. Using machine learning techniques to infer each user’s context from smartphone sensor data is a promising approach to further enhance tailoring.

Objective: The primary objective of this study is to quantify main effects, interactions, and moderators of 3 intervention components of a smartphone-based intervention for physical activity. The secondary objective is the exploration of participants’ states of receptivity, …

Scalable Feature Selection And Extraction With Applications In Kinase Polypharmacology, Derek Jones

Theses and Dissertations--Computer Science

In order to reduce the time associated with and the costs of drug discovery, machine learning is being used to automate much of the work in this process. However the size and complex nature of molecular data makes the application of machine learning especially challenging. Much work must go into the process of engineering features that are then used to train machine learning models, costing considerable amounts of time and requiring the knowledge of domain experts to be most effective. The purpose of this work is to demonstrate data driven approaches to perform the feature selection and extraction steps in …

Sdn-Based Mechanisms For Provisioning Quality Of Service To Selected Network Flows, Faisal Alharbi

Theses and Dissertations--Computer Science

Despite the huge success and adoption of computer networks in the recent decades, traditional network architecture falls short of some requirements by many applications. One particular shortcoming is the lack of convenient methods for providing quality of service (QoS) guarantee to various network applications. In this dissertation, we explore new Software-Defined Networking (SDN) mechanisms to provision QoS to targeted network flows. Our study contributes to providing QoS support to applications in three aspects. First, we explore using alternative routing paths for selected flows that have QoS requirements. Instead of using the default shortest path used by the current network routing …

Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger

Theses and Dissertations--Computer Science

Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship …

Soil Organic Carbon And Mineralization Rates At The Woolsey Wet Prairie Mitigation Site In Fayetteville, Arkansas, Zachary Tipton, Lisa S. Wood, Mary Savin, Benjamin R. Runkle

Discovery, The Student Journal of Dale Bumpers College of Agricultural, Food and Life Sciences

Atmospheric carbon dioxide (CO₂) levels are rapidly increasing, surpassing 400 ppm in 2013 from a pre-industrial revolution level of around 280 ppm. Researchers have been looking at methods to reduce CO₂ levels in the atmosphere, including promoting carbon sequestration in soils. Carbon sequestration is the process where CO₂ is naturally or artificially transferred out of the atmosphere and stored in the ocean, plant biomass, soils, and geologic formations. Seemingly contradictory to the notion of carbon sequestration is the use of fire as a management treatment for the restoration of native prairie grass ecosystems. Fire combusts plant …

The Participating Mind In The Quantum Universe, Menas Kafatos, Keun-Hang Susan Yang

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Orthodox interpretation of quantum mechanics, which followed the Copenhagen Interpretation but was enhanced by primarily Werner Heisenberg and John von Neumann into a fully developed theory, brought in, among others, the role of measurement, available choices and response of the quantum system. It is, more consistent and clear than other interpretations of quantum mechanics as it provides account of the interactions of observers with the external world. As such, the Orthodox interpretation does a lot more than just account for physical interactions in the atomic world, which was the original goal of quantum mechanics in the early part of …

Multiple C-H Bond Activations Of Aromatic Compounds By Unsaturated Dirhenium Carbonyl Complexes, Poonam Dhull

Theses and Dissertations

The background and importance of aromatic C-H bond activation by metal complexes are discussed in Chapter 1 with the help of various examples from the literature. Synthesis of the dirhenium complex Re2(CO)8(-C6H5)(-H) 1.1 is also discussed in detail. It also includes work done on C-H activation on arenes and heteroarenes by previous members of Dr. Adams’ group. The reactions of Re2(CO)8(-C6H5)(-H) with naphthalene and anthracene yielding the first multiply-CH activated arene products by the multiple oxidative-addition processes are presented in Chapter 2. The reaction of Re2(CO)8(-C6H5)(-H) with itself yielded the doubly-Re2-metalated C6H4 bridged compound Re2(CO)8(µ-H)(µ-1,µ-3- C6H4)Re2(CO)8(µ-H), 2.3. The reaction of …

Implementation Costs Of Spiking Versus Rate-Based Anns, Lacie Renee Stiffler

Theses and Dissertations

Artificial neural networks are an effective machine learning technique for a variety of data sets and domains, but exploiting the inherent parallelism in neural networks requires specialized hardware. Typically, computing the output of each neuron requires many multiplications, evaluation of a transcendental activation function, and transfer of its output to a large number of other neurons. These restrictions become more expensive when internal values are represented with increasingly higher data precision. A spiking neural network eliminates the limitations of typical rate-based neural networks by reducing neuron output and synapse weights to one-bit values, eliminating hardware multipliers, and simplifying the activation …

Inorganic Nanocrystals And Their Applications In Hybrid 0d:2d Material Optoelectronics, Mathew Kelley

Theses and Dissertations

Functional nanomaterials have garnered great interest as candidates for use in next-generational optoelectronics such as solar photovoltaics, light-emitting diodes, and photodetectors. Among these low-dimensional materials, hybrid devices employing both 0D and 2D materials are of interest due to exploitation of the favorable characteristics of each component, and performances superior to standalone counterparts are achievable. This thesis is divided into two parts, as follows. The first two chapters will introduce lowdimensional materials and their favorable characteristics; our work on the formation of ligand-exchanged nanocrystal thin films purified by gel-permeation chromatography will also be discussed. In the second component, the formation and …

Uncertainty Estimation Of Deep Neural Networks, Chao Chen

Theses and Dissertations

Normal neural networks trained with gradient descent and back-propagation have received great success in various applications. On one hand, point estimation of the network weights is prone to over-fitting problems and lacks important uncertainty information associated with the estimation. On the other hand, exact Bayesian neural network methods are intractable and non-applicable for real-world applications. To date, approximate methods have been actively under development for Bayesian neural networks, including but not limited to: stochastic variational methods, Monte Carlo dropouts, and expectation propagation. Though these methods are applicable for current large networks, there are limits to these approaches with either underestimation …

Hierarchical Corannulene-Based Materials, Allison M. Rice

Theses and Dissertations

Merging the intrinsic properties of fullerene (buckyball) and corannulene (buckybowl) derivatives with the inherent properties of crystalline metal- and covalentorganic frameworks (MOFs and COFs), including their modularity, porosity, versatility, high surface area, and structural tunability, opens a pathway to unlock a novel class of fulleretic materials. Despite the great interest in MOFs and COFs, as well as fullerene derivatives, this dissertation is focused on crystalline fullerene- and corannulenecontaining frameworks, highlighting their potential contributions in the fields of optoelectronic devices, electrodes, and photosensitizers. We have revealed a dual role of fullerene- and corannulene-containing building blocks showing their versatility to act as …

Phylogeny, Ancestral Genome, And Disease Diagnoses Models Constructions Using Biological Data, Bing Feng

Theses and Dissertations

Studies of bioinformatics develop methods and software tools to analyze the biological data and provide insight of the mechanisms of biological process. Machine learning techniques have been widely used by researchers for disease prediction, disease diagnosis, and bio-marker identification. Using machine-learning algorithms to diagnose diseases has a couple of advantages. Besides solely relying on the doctors’ experiences and stereotyped formulas, researchers could use learning algorithms to analyze sophisticated, high-dimensional and multimodal biomedical data, and construct prediction/classification models to make decisions even when some information was incomplete, unknown, or contradictory. In this study, first of all, we built an automated computational …

A Rotatable Asymmetric Variable Compensation Mirt Model, Xinchu Zhao

Theses and Dissertations

The purpose of this study is to develop, estimate, and interpret a new variable compensation multidimensional item response theory (MIRT) model, named the Rotatable Asymmetric Variable Compensation Model (RAVCM), that allows for transformation between different correlation structures. Since the model is rotatable like the common compensatory models (CM), it is not necessary to specify or estimate the correlation of abilities to recover the model. Also, it can approximate the existing MIRT models well. In simulation, the RAVCM is shown to estimate the parameters with small error, especially when the non-compensatory model (NCM) is the true model and the correlation of …

Adjusting For Mis-Reporting In Count Data, Gelareh Rahimighazikalayeh

Theses and Dissertations

Any counting system is prone to recording errors including underreporting and overreporting. Ignoring the misreporting pattern in count data can give rise to bias in the estimation of model parameters. Accordingly, Poisson, negative binomial and generalized Poisson regression have been expanded in some instances to capture reporting biases. However, to our knowledge, no program has been developed to allow users to apply all of these models when needed. In the first part of the dissertation, we review the available models for underreported counts and develop a Stata command to estimate Poisson, negative binomial and generalized Poisson regression models for underreported …

Modeling Data Center Co-Tenancy Performance Interference, Wei Kuang

Dissertations, Master's Theses and Master's Reports

A multi-core machine allows executing several applications simultaneously. Those jobs are scheduled on different cores and compete for shared resources such as the last level cache and memory bandwidth. Such competitions might cause performance degradation. Data centers often utilize virtualization to provide a certain level of performance isolation. However, some of the shared resources cannot be divided, even in a virtualized system, to ensure complete isolation. If the performance degradation of co-tenancy is not known to the cloud administrator, a data center often has to dedicate a whole machine for a latency-sensitive application to guarantee its quality of service. Co-run …

Galaxy And Mass Assembly (Gama): The Consistency Of Gama And Wise Derived Mass-To-Light Ratios, T. Kettlety, J. Hesling, S. Phillipps, M. N. Bremer, M. E. Cluver, E. N. Taylor, J. Bland-Hawthorn, S. Brough, R. De Propris, S. P. Driver, Benne W. Holwerda, L. S. Kelvin, W. Sutherland, A. H. Wright

Faculty and Staff Scholarship

Recent work has suggested that mid-IR wavelengths are optimal for estimating the mass-to-light ratios of stellar populations and hence the stellar masses of galaxies. We compare stellar masses deduced from spectral energy distribution (SED) models, fitted to multiwavelength optical-NIR photometry, to luminosities derived from WISE photometry in the W1 and W2 bands at 3.6 and 4.5 μmfor non-star forming galaxies. The SED-derived masses for a carefully selected sample of low-redshift (z≤0.15) passive galaxies agree with the prediction from stellar population synthesis models such that M*/LW1 ≃0.6 for all such galaxies, independent of other stellar population parameters. The small scatter between …

Galaxy And Mass Assembly (Gama): The Mechanisms For Quiescent Galaxy Formation At Z < 1, K. Rowlands, V. Wild, N. Bourne, M. Bremer, S. Brough, S. P. Driver, A. M. Hopkins, M. S. Owers, S. Phillipps, K. Pimbblet, A. E. Sansom, L. Wang, M. Alpaslan, J. Bland-Hawthorn, M. Colless, Benne W. Holwerda, E. N. Taylor

Faculty and Staff Scholarship

One key problem in astrophysics is understanding how and why galaxies switch off their star formation, building the quiescent population that we observe in the local Universe. From the Galaxy And Mass Assembly and VIsible MultiObject Spectrograph Public Extragalactic Redshift surveys, we use spectroscopic indices to select quiescent and candidate transition galaxies. We identify potentially rapidly transitioning post-starburst (PSB) galaxies and slower transitioning green-valley galaxies. Over the last 8Gyr, the quiescent population has grown more slowly in number density at high masses (M* > 1011M⊙) than at intermediate masses (M* > 1010.6M⊙). There is evolution in both the PSB and green-valley stellar …