College of Science

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2-D and 3-D Layouts to Aid Human Cognition of Local Structure in Multivariate Data
(2008-08-21T19:38:19Z) Sun, Ru; Sun, Ru
This dissertation addresses the development of new 2-D and 3-D layout algorithms for statistical visualization purposes. These layouts serve tasks that include placing near neighbors close together, showing group or cluster membership, allocating space for glyphs and images used to characterize objects (cases), and approximating distances between objects. These tasks serve goals that include conveying structure, facilitating pattern discovery and hypothesis generation, and providing access to detailed information. The layouts are for human use, so they include considerations of human perception, cognition, and organizational regularity. This dissertation targets applications involving the study of cases, variables, clusters, and other multivariate objects. In these applications the notion of distances/dissimilarities between objects is important. However, accurate distances can not be maintained in low dimensional views. Researchers have developed a variety of layout methods to represent multivariate objects (including data summaries) in low dimensions. Common layout algorithms include multidimensional scaling, Kohonen self-organizing maps, Treemaps and spring models. This dissertation compares and contrasts the new layout algorithms with previous methods, develops new star glyphs, and demonstrates the new algorithms using multivariate data produced by AIRS (Atmospheric InfraRed Sounder) and other datasets.
3d Road Surface Meshing with LIDAR
Obert, Nathan; Obert, Nathan; Duric, Zoran
The primary goal of this research is to create 3d maps of George Mason Fairfax roads. These maps will be used in the 3d driving simulator. Towards this goal I have decided to use Google Cartographer, which uses Lidar and Inertial Measurement Unit (IMU) data. The Cartographer has been developed and applied for slam inside buildings. In the original application Lidar and IMU units were worn in a backpack. Because of that Cartographer is adjusted for abundance of vertical features and relatively slow moving speeds. I have collected Lidar, IMU, HD video, and GPS data for the major GMU campus roads and several parking structures and lots over four days. I have used two different Lidars (VLP-16 and VLP-64) mounted on two different vehicles. I have written the needed drivers to integrate GPS data collection with VLP-16 data. I have fabricated mounts for VLP-16 and reconfigured VLP-64 mounts for these collections. I have processed the data using Cartographer in Robot Operating System (ROS). The collected data was archived on GMU servers for future teaching and research uses. In our application the Lidar and units were placed on a moving vehicle which travels at several times the speed of a walking person. In addition, the vertical features were more struct accurate point clouds for some roads and parking lots and structures, while in several cases more parameter tuning may be needed to make it work.
A Behavioral Investigation of the Thermal Solar Niche
(2015-01-29) Boyer, Emma Gerald; Boyer, Emma Gerald; Luther, David A.
The means by which a species survives in different environmental conditions is central to thoroughly understanding its ecology, evolution, and conservation. As we face a warming climate, developing a more comprehensive picture of an animals’ energetic (specifically, thermal) limitations is critical. Although temperature is often considered the primary parameter governing an animal’s thermal state, water availability, wind, and solar energy are also important. The thermal effect of solar energy is often assumed but is rarely measured. Because behavioral adaptation can be a critical tool for survival in changing and highly variable climates, behavioral patterns in relation to environmental conditions such as solar energy serve as a central way to assess animal responses to climate change. To investigate this fundamental yet overlooked aspect of environmental stress on animals, I conducted a shade manipulation experiment to control the amount of solar energy exposure to free ranging house sparrows, Passer domesticus, and better understand the effects of solar energy, particularly at high summer temperatures, on animal behavior. As predicted, bird attendance increased with increasing shade relative to the surrounding exposed areas. In contrast to my predictions bird attendance also increased with increasing temperature. An interaction between temperature and the amount of shade was also an explanatory variable for house sparrow attendance, which demonstrates the complexity of thermal pressures on animals. This study shows that as we continue to assess and predict how animals respond to climate change, we should incorporate behavior and quantify additive thermal pressures such as solar energy.
A Change Vector Method to Study Behavioral Development
(2010-06-15T14:04:02Z) Cooper, David L.; Cooper, David L.; Olds, James L.
Broca‘s Area was the first region in the human cortex to be tied definitively to a specific behavior—language. However, structural, cytological and molecular peculiarities identified in Broca‘s Area are not unique to humans, and thus language appears to have emerged from other traits that were advantageous in the evolution of primates in general, such as fine motor control for gestures and vocalizations, and the so-called mirror system. One potential source of insight into the emergence of language is to study the correlation of brain structures with behavioral function. This work capitalizes on the existence of a unique resource to undertake that study: eight detailed cytological studies of the developing human cortex from birth through six years of age, accomplished by JL Conel from 1939 to 1967. Conel‘s atlases provide a consistent methodology applied to 37 cortical areas at each of the observations ages for neurons and 42 cortical areas for myelinated fibers, which further enables a quantitative comparison of change patterns during human cortical development. The change vector method that was developed to conduct that investigation normalizes measures for the change steps that occur in the seven change intervals that occur in the Conel data, measures the statistical significance of any of those change steps, and permits the direct comparison of change trajectories using k-means cluster analysis. This analysis reveals significantly correlated synchronized changes at different ages, linked to specific ―core‖ area/layer addresses that imply a clock-like coordination mechanism that appears to support sensorimotor developmental functions at the appropriate age. Neither functional cores nor statistically significant change steps emerge when a similar analysis is applied to verbal behavior, where such a clock-like mechanism is unlikely. In general for the cortex, and for language behavior related to Broca‘s Area in particular, the analysis supports innate architectural mechanisms that facilitate specific address level accommodation to external activity, whereas external behavioral evidence, as from language change, merely supports rapid evolution of the behavior itself to accommodate those same cortical mechanisms. That is, language evolves to enable the speaker to speak, just as writing evolves to enable the child to read. This dissertation research has complied with all George Mason University standards for the ethical conduct of research and for the appropriate use of human and animal subjects.

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A Class of Operators with Symbol on the Bloch Space of a Bounded Homogeneous Domain

(2009-06-08T20:14:00Z) Allen, Robert Francis; Allen, Robert Francis

Let X be a Banach space of holomorphic functions on a domain D in C^n. If ψ  is a holomorphic function on D, and ϕ is a holomorphic self-map of D, we defi ne the weighted composition operator on X with symbols ψ and ϕby W ψ,ϕf =  (f о ϕ). This operator is a generalization of the multiplication operator M(ψ) f = ψ f and the composition operator Cϕf = f о ϕ, which are known as degenerate weighted composition operators. The weighted composition operators have been an object of interest since the early 30's with their connection to the isometries of various spaces of analytic functions on the unit disk. The Bloch space has been of interest since the early 70's to function theorists and to operator theorists. However, these two concepts did not meet until 2001. Classical operator theory on spaces of holomorphic functions in several complex variables is typically carried out on the unit ball and the unit polydisk. The respective function theories are very di fferent. In this dissertation, we attempt to unify the operator theory on the Bloch space on these domains and extend it further to bounded homogeneous domains in C^n. In this uni ed manner, we study the fundamental properties of the weighted composition operators: 1. For what symbols ψ  and ϕ is W ψ,ϕ bounded? 2. For what symbols ψ  and ϕ is W ψ,ϕ compact? 3. What is an expression for ||W ψ,ϕ||? 4. For what symbols ψ  and ϕ is Wψ,ϕ an isometry? 5. What is the spectrum of Wψϕ? It is our hope that this work will mark the beginning of a paradigm shift in operator theory research in several complex variables. This will bring in new  fields of study such as diff erential geometry into the study of operators, thus enriching the  field.

A Comparative Analysis of Shallow Water Mapping Tools
(2015-08-26) Cleveland, Geoffrey S
Varied needs have encouraged development of different technologies over time to meet those needs inclusive of technologies to map land, oceans and shorelines. Over the last decade significant effort has been put into fusing the area that joins the land maps to ocean benthic (ecological region at the lowest level of a body of water such as an ocean or a lake) maps so there is a continuous topographic view. There are several methods used to define the topography of underwater regions such as ship based single and multi-beam echo-sounder approaches with the latter providing complete high resolution coverage of the sea floor. (Committee on National Needs for Coastal Mapping and Charting, 2004). The goal of this thesis is to assess a group of common tools for mapping underwater topography, also known as bathymetry, for use in fusing the land topography to the sea floor topography. Data will be collected from web resources and unclassified geospatial databases for this research and key technical areas and weaknesses will be assessed to draw conclusions. The result of this analytic research identifies a recommended tool for shallow water bathymetry collection and provides recommended applications to support wave renewable energies.
A Comparative Assessment of Aquatic Invasive Species Management in Maryland and Virginia
(2011-05-25) Christmas, John Franklin Jr; Christmas, John Franklin Jr; Balint, Peter J.
The objective of this exploratory case study was to comparatively assess State Aquatic Invasive Species (AIS) Management Capacity in Maryland and Virginia. That is, to measure the perceived ability of each of these states to effectively manage AIS. To collect data for the assessment I conducted semi-structured interviews as scripted telephone surveys, which included both open-ended and closed-ended questions. The interviews generated data in the form of categorical responses to a series of perceptual questions relating to the various components of State AIS Management Capacity, including: situational, political, institutional, state, organizational, and evaluation capacities. The respondents surveyed represented a wide spectrum of AIS experts in Maryland (n=20) and Virginia (n=10) ranging from field biologists to senior managers in both the governmental and nongovernmental sectors. Overall, considering all responses to each of the questions relating to the various components of capacity, the majority of responses in both states were “moderately-developed,” (i.e., AIS program needs some improvement) with this response selected for 52.3% of the responses in Maryland and 58.2% of the responses in Virginia. However, there was a greater frequency of “well-developed” (i.e., sufficient AIS program) responses in Maryland (30.3%) than in Virginia (10.9%) and conversely a lower frequency of “poorly-developed” (i.e., AIS program needs considerable improvement) responses in Maryland (17.4%) than in Virginia (31.0%). Categorical data relating to the perceptual responses of the various components of AIS capacity was coded based on a traditional Likert-like scale ranging from 1-5 (poorly-developed=1, moderately-developed=3, well- developed=5). Group means were calculated for each component of capacity assessed by respondents in each state. The group means for the various components of capacity assessed ranged from 2.4–4.2 in Maryland and from 2.0-3.3 in Virginia, on a scale of 1 (poorly-developed)–5 (well-developed). The greatest differences were apparent in the respondent’s perceptions of situational and state capacity, which were both higher in Maryland than in Virginia. An integrative metric—the index of State AIS Management Capacity (IAIS)—was calculated for each state, as a composite measurement incorporating coded values for all responses for all components of capacity evaluated. The overall IAIS for Maryland was 3.3 while the IAIS for Virginia was 2.6. On a relative scale of 1-5, a higher IAIS value indicates an overall perception by respondents of a better-developed State AIS Management Capacity. Permutation analysis was conducted to determine whether the perceptions of the individual components of State AIS Management Capacity differed significantly in Maryland and Virginia. These analyses confirmed the empirical findings, with statistically significant differences found between states in relation to perceptions of situational (p<0.05) and state capacity (p<0.05), with Maryland receiving higher scores. No statistically significant differences were observed between states as far as perceptions of political capacity, institutional capacity, organizational capacity, or evaluation capacity. Seemingly, the AIS programs in Maryland and Virginia are both reasonably effective, with adequate regulations in place to address most AIS concerns. A basic framework for state AIS management has been developed in both Maryland and Virginia. However, the framework for addressing AIS concerns is not codified or formally established in Maryland, unlike Virginia where such an AIS framework is both codified and formally established. Considerable differences were observed in the governance of the executive branch natural resource agencies tasked with AIS program implementation in these states. While both states have an AIS organization, neither has a discrete AIS program. Staff are generally assigned in a collateral fashion on an ad hoc basis to particular AIS issues, while having other primary responsibilities. Both states have a long-standing regional involvement in AIS issues, and both states have had successes in AIS eradication, although AIS issues remain generally a low priority issue in these states.
A Comparative Study of the Utility of Knowledge Bases for the Geospatial Enrichment of Social Media Data
Hunke, Jacqueline; Hunke, Jacqueline; Croitoru, Arie
In the last decade the use of social media has increased substantially. It has become a data-rich source from which to extract meaningful data, as each post that a user makes to social media contains information that can be extracted or derived. Inherent in some of this data is geographic information (e.g. coordinates, location names) and this information, once discovered, can provide useful spatial, temporal, and thematic context. However, deriving such contextual information often requires the use of external knowledge bases. Employing Semantic Web and Linked Data principles have enabled the large-scale mining of such information from social media. As recent studies have shown, using such knowledge bases can disambiguate social media data and enrich its derived analysis products. Motivated by these recent trends, this thesis conducts a meta-analysis of those recent studies and proposes a set of selection criteria that should be considered when selecting a knowledge base for extraction of geographic and other contextual information from social media data. The analysis also explores which knowledge bases, among the ones existing today, are the most commonly-used and evaluates them against the defined criteria set. Based on this, a set of recommendations are put forward for selecting the best suited knowledge bases for the geographical enrichment of social media data.
A Comparative Test of Traveling Salesman Solutions from GIS Software Packages
(2015-08-06) Nies, Brandi; Nies, Brandi; Curtin, Kevin M.
The Traveling Salesman Problem (TSP) has long been studied and remains a challenge in the realm of combinatorial optimization across many disciplines. This research investigates the extent to which heuristic solutions for symmetric TSPs generated within geographic information systems (GIS) applications are sub-optimal, compared to exact solution procedures. The TSP is addressed in this research through multiple real-world street networks and a range of problem instances, for which a path must be generated that visits each city only once, and returns to the original point of departure, while minimizing the distance traveled. Two GIS applications were used to generate heuristic solutions for the symmetric TSP for each network dataset. These results were compared against the optimal solutions generated from an exact solution procedure for the same networks. The cumulative cost of each TSP route for all network problem instances was examined to determine the performance and level of sub-optimality where applicable. This research concludes that the heuristic solutions generated sub-optimal results averaging a combined performance measure of 17.36% above optimal, however the software that employs the tabu search (TS) heuristic significantly outperformed the software that used the genetic algorithm (GA) by consistently producing solutions nearer to the known optimum as generated by the exact solution procedure. Given the wide range in the extent of sub-optimal results from the heuristic-based GIS applications, this research suggests that careful consideration should be made prior to the use of these implementations for spatial analysis. Additionally, GIS packages could benefit from integrating additional, or more efficient heuristic or exact solution procedures within the application, and allowing the user more control of the search parameters to accommodate various network optimization problems. Keywords: network analysis; traveling salesman; TSP, route optimization; GIS; heuristic; genetic algorithm; tabu search
A Comparison of Reclassification Methods to Improve an NDVI Based Flood Map
(2015-08-06) Fayne, Jessica V; Fayne, Jessica V; Fuhrmann, Sven
In Cambodia and Vietnam, low-lying terrain is particularly susceptible to flooding during the monsoon season between May and November. To monitor flooding in the region, a near-real time NDVI percent decrease based Flood Extent Product was developed to be hosted on an online Flood Dashboard by the NASA DEVELOP team. The product was designed to be updated twice per day with 250-meter resolution from MODIS on the Aqua and Terra satellites. To increase the usage and usability of this product, the classification intervals were compared with other commonly used classification schemes to monitor flooding. The use of substantiated flood classification methods is essential to ensure understanding and usefulness of mapped flood products. Classification schemes can influence the usability and usefulness of these products, e.g. inappropriate flood mapping classification intervals and color selections may incorrectly classify flooded areas and distract from the interpretation of the phenomenon of interest. The percent change method proved to be very helpful in delineating flood boundaries compared to standard deviation and differencing methods. However, only the 100% decrease interval class had the highest accuracy ratings compared to three reference data sets, with an average producer’s accuracy of 67.8% and an average user’s accuracy of 74%. The results of the accuracy assessments indicate that only the 100% interval class can be reclassified to into a descriptive ‘flood’ classification. The use of an additional ‘wet’ category with 75% decrease will be useful to support the flooded area description and allow users to monitor changes in regions that are not currently flooded, but are more susceptible to flooding. The use of a descriptive two-class product eliminates confusion from understanding input data while removing extra information from lower interval change classes.
A Comparison of Remote Sensing Change Detection Techniques in East African Montane Forests
(2015-10-12) Cook, Chelsea; Cook, Chelsea; Haack, Barry
Deforestation is a major concern for many countries throughout the world, including those in East Africa. It is essential to accurately keep track of changes in forests over time both for historical reference, as well as for government decision-making purposes. A large variety of change detection algorithms have been developed for remote sensing to detect fluctuations in forests. Yet, it is hard to determine which one of the multitude of techniques available is the best method for a particular study. Therefore, this study focused on using remote sensing to determine which one method out of the five different change detection techniques chosen to perform this project provides the best results for detecting conversions in East African forests. The five change detection techniques compared: 1) image differencing (ID), 2) post-classification comparison (PCC), 3) normalized difference vegetation index differencing (NDVID), 4) principal component analysis (PCA) and 5) visual interpretation (VI). These five methods are compared with the use of two Landsat Thematic Mapper (TM) Surface Reflectance Climate Data Record (CDR) images of subset areas at three separate sites. The sites are Mount Kenya and the Mau Forest Complex in Kenya and Mount Kilimanjaro in Tanzania. These sites were selected due to the large amount of recent deforestation. The results for all five of the change detection methods were compared for each of the three sites and found that the PCC technique yielded the highest overall accuracy at 90%, followed closely by PCA at 89%. The VI technique came in third at 88%, with ID and NDVID having the lowest accuracies at 87% and 83% respectively. The forest loss (FL) user’s and producer’s accuracies were also compared with PCC, PCA and VI receiving the highest accuracies at Mount Kenya. PCA had the highest user’s accuracy of 81.1% and PCC had the highest producer’s accuracy of 98.5%.VI ranked second for both user’s (56.6%) and producer’s (77.4%) accuracies. At the Mau Forest Complex, PCC had the highest user’s accuracy of 96.0% followed by NDVID at 94.7%. ID was the third highest at 92.4%. PCA received the best producer’s accuracy at 99.1%, with PCC in second at 97.8% and VI in third at 90.6%. Finally, at Mount Kilimanjaro, both ID and VI had the same highest user’s accuracies of 85.6%, followed by PCA at 82.1%. However, both ID and VI received low producer’s accuracies of 46.8% and 42.8% respectively. Both PCC and PCA did the best overall with user’s accuracies of 80.1% (PCC) and 82.1% (PCA) and producer’s accuracies of 77.6% (PCC) and 76.0% (PCA). When all three sites were averaged, PCC had the highest overall average for FL accuracy at 83.9%, followed by PCA at 81.4%, then VI at 76.2%, next ID at 68.9% and then finally NDVID at 55.0%. The findings from averaging the FL accuracies support the results of the overall accuracies, which conclude that the most beneficial techniques from this study are as follows: 1) PCC, 2) PCA, 3) VI, 4) ID and 5) NDVID.
A Comparison of Vector Based and Raster Based Analyses of Historic Records for the Identification of Archaeological Sites
(2015-08-19) Keen, Jolene R; Keen, Jolene R; Houser, Paul R.
This thesis compares a vector based analysis and a raster based analysis of observations and photographs from an historic aerial survey to identify Mayan archaeological sites. The first relies on the distance measurements taken during the original survey to select likely points from a comprehensive database of known Mayan sites while the second relies on the structural features of the landscape to identify likely sites. The two analyses indicate that neither method offers definitive results when used exclusively. The distance measurements cannot be relied upon as absolute due to errors in calculations and the accuracy of the site database. Instead, the distances offer a starting point for a landscape based search. The result is a multi-media model that uses a wide variety of overlapping data in order to utilize the unique information available in historic records for archaeological prospection.
A Comprehensive Process for Spatiotemporal Analysis of Network-Based Phenomena
(2011-06-14) Eckley, David C; Eckley, David C; Curtin, Kevin M.
This thesis describes an efficient and effective process for conducting spatiotemporal cluster analysis of network-based phenomena. While various methods are published which describe spatiotemporal analysis of phenomena in continuous space, the literature is lacking for the application of these methods in network space. Through a step by step process, Part 1 of this thesis establishes the validity of a network application for the spatiotemporal clustering method proposed by Knox (1964). Further, it presents an intuitive technique for determining the critical parameters in space and time for the spatiotemporal test, by examination of minimum and average nearest neighbor distances in both dimensions independently. Through examples, Part 2 explores the significance tests used by the described spatiotemporal clustering methodology and expounds upon the critical parameter determination mentioned in Part 1. Part 3 presents a GIS-based toolbox, SCAn (Spatiotemporal Cluster Analysis on a network) designed to perform spatiotemporal cluster analysis of network-based phenomena using the methods presented in Part 1 and Part 2.
A Comprehensive Study of Cavities on the Sun: Structure, Formation, and Evolution
(2016) Karna, Nishu; Karna, Nishu; Zhang, Jie
Coronal cavities are large scale structures in the solar corona that are closely related to the long-term evolution of the magnetic field in the photosphere as well as associated with energetic solar activity such as prominence eruptions and coronal mass ejections (CMEs), which are a primary driver of space weather. Coronal cavities are observed as elliptical-shaped and relatively low density dark regions above the solar limb in extreme ultraviolet (EUV), X-ray, and white-light coronal images. However, the nature of their magnetic field, how they form and their relationship to solar activity are not well understood. In this dissertation, several important questions regarding coronal cavity origin, structure, and relation to the solar cycle are addressed.
A Computational and Statistical Framework for Screening Novel Antimicrobial Peptides
(2015) Veltri, Daniel Paul; Veltri, Daniel Paul; Shehu, Amarda; Solka, Jeff
Bacterial resistance to antibiotics continues to be a serious concern worldwide. This has motivated a strong research focus on naturally-occurring antimicrobial peptides (AMPs) as templates for new drug development. To date, experiments in the wet laboratory have characterized thousands of AMPs while generally concentrating on measures of antibacterial activity for natural sequences or peptides designed using a limited number of site-directed mutations. Based on these findings, the computational AMP research community seeks to better understand how biological signals and features relate to antimicrobial activity through the use of machine learning and statistical approaches. In this dissertation, we advance our understanding of the determinants for antimicrobial activity by carefully constructing a set of descriptive features for use in AMP classification models. In addition to using physicochemical features, we also construct new sequence-based features which capture information about distal patterns within a peptide. Comparative analysis with state-of-the-art methods in AMP recognition reveal our methods to be among the top performers while still providing a transparent summary of relative feature importance. Moreover, this dissertation applies our features in a new setting to demonstrate for the first time a computational model to recognize if an AMP may perform better against a representative Gram-positive or Gram-negative bacteria. Work presented is a step forward for in silico research seeking to help guide AMP design in the wet laboratory. Our predictive models are made accessible via AMP Scanner, a new publicly-available web server at: http://www.ampscanner.com.
A Computational Approach for SNP Discovery
(2014-09-18) Al-Razgan, Othman; Al-Razgan, Othman; Matukumalli, Lakshmi
The advent of the next-generation sequencing has revolutionized the ability of cattle genomics researchers to sequence many animals from a wide diversity of cattle breeds enabling extraction of high resolution genotypic data. Using these data to understand the relationship between the phenotypes and genotypes will enable significant improvements in food production and animal health. However the existing software methods for analyzing the sequence data and SNP discovery are not flawless and pose as a restriction for further research. The general objective of this dissertation is to equip the genomics researchers such as those working in Cattle with advanced computational tools and techniques, to utilize the ever amplifying accessibility of genome sequence in an effective manner.
A Computational Based Approach Linking Spatial and Temporal Pattern Stiffness to Decreased Lung Function in Idiopathic Pulmonary Fibrosis
(2022) Sangobowale, John; Baranova, Ancha; Kinser, Jason M
Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive disease of unknown etiology that is characterized by the histopathological pattern of usual interstitial pneumonia. The pathogenic mechanisms that regulate the activation, differentiation, and proliferation of fibroblast have been at the central stage of efforts to understand the biological pathway that drives the fibrotic process. Despite the extensive knowledge on the pathogenesis of IPF, the mechanical dysfunction associated with the remodeling of the lung tissue is still not fully understood. This study developed a computational based approach to study the pulmonary mechanics of a hexagonal lattice network of alveoli-like structures to improve understand of the mechanical properties of the lung. A dynamic probabilistic representation of a closed two-dimensional elastic model of nodes and springs was constructed from a baseline High Resolution Computed Topography (HRCT) IPF image. The progressive development of fibrosis was reconstructed from early to late-stage representations of IPF images. Given a predefined probability, regional collagen deposition was simulated by increasing random isolated lesions of the alveolar wall, represented by springs in the lattice model. The local onset of fibrosis was initialized by stiffening springs along a strain-dependent random walk to account for excess deposition of extracellular matrix and tissue remodeling as the lung deviates from its normal geometry. The regional deposition of collagen and the local manifestation of fibrosis were represented by increasing the elastic constant of the spring at the site of initiation and springs along a strain dependent random walk of length N, by a factor of 100. The value of N representing the maximum distance the spread of fibrosis was allowed to travel from its initiation site in the network model. After each expansion and contraction, the nodes were allowed to move in the direction of the applied force, while the total spring energy of the network was minimized. The cycle was repeated until all the springs k constants in the network model were increased. This study focused on modeling and analyzing various functions of the lung, and its parameters to construct a novel approach to recreate early to late-stagecross sectional representations of IPF. The model was proven to show that the onset of fibrosis tends not to follow a linear path, but establishes a sharp increase in energy as the lung structure reaches a critical threshold. The shift in slope as the concentration of spring stiffness increased was broken down into three distinct regions, < 25% (early onset), ≥ 25% and ≤ 75% (progressive), and > 75% (late stage) of the disease. This study provided a new approach to examining how pulmonary mechanics and spatial orientation of lung tissue affects the progression of IPF, and developed a framework to model other biological systems.
A COMPUTATIONAL MODEL OF A HUMAN VENTRICULAR CARDIOMYOCYTE: POSSIBLE ROLES IN CARDIOVASCULAR DISEASE AND ARRHYTHMIAS
(2023) Alvarez, Jerome Anthony Efa; Ullah, Aman
Studying cardiac diseases using human tissue is proven difficult and limited, even in optimized clinical conditions. Computer simulation studies have been continuously researched by mimicking electrophysiological protocols which can now be accommodated in the present time due to their high computational load. In that regard, we have developed a stochastic human ventricular cardiomyocyte model for intracellular calcium ([Ca2+]i) handling to include 9 individual L-Type calcium (LCC) and 49 ryanodine receptor (RyR) channels as components of 20,000 Ca2+–release units (CRUs). The model presented here explores the intricacies of calcium-induced calcium-release (CICR) dynamics, with a particular focus on the interplay between LCCs and a cluster of RyRs within CRUs. This framework elucidates the fundamental aspects of excitation-contraction coupling. Various ionic pumps and currents contained in the cell membrane contribute to the overall electrophysiological behavior of the cardiac action potential (AP) morphology. Moreover, cardiac contractility is regulated by fine–tuning multiple fluxes involved in [Ca2+]i concentrations and impacts signaling pathways by spontaneous calcium release from the sarcoplasmic reticulum (SR). However, Ca2+ ions also indicate the presence of abnormalities observed in the behavior of the cardiomyocyte’s AP and intracellular Ca2+ dynamics which may ultimately result to arrhythmogenic disorders. The model presented here captures the spontaneous Ca2+ release events and can be further used to explore both normal and defective mechanisms in ventricular cardiac abnormalities.
A Computational Study of Causation
(2022) Marr, Joseph A.; Griva, Igor
The need to study causal statements is well-motivated; causal statements about the natural world abound in written text and in speech. These statements represent distilled knowledge that can be learned and implemented efficiently, and that are central in mental architecture theories---in particular, Fodor's ``Language of Thought'' (LOT) hypothesis. Investigating causal statement syntax and evaluating its external world processing effects is fundamental to understanding the mental representation of causal statement syntactic design and the external world impact of that design. Current natural language syntax does not, in my opinion, represent causal statements efficiently from the LOT perspective or lead to effective mental representation. A new causal statement syntax is therefore presented proposed. This new syntactic representation is more compact than that found in current linguistic practice, and, I claim, more closely conforms with LOT architecture. The syntax is consistent with current linguistic grammar theories and also implies a parsing speed difference. I construct an agent-based model (ABM) to computationally investigate the external world impact of this theoretical causal syntax proposal and to quantify its benefits in terms of agent survivability in the environment. In so doing I connect a mental representation of causal statement syntax to tangible, external environment impact for the first time.
A Constraint-Based Model for 3D Spatial-Temporal Data Management
(2012-10-05) Li, Jing; Li, Jing; Wong, David
Describing structures of geospatial objects as models is essential for understanding geographic processes. Efforts to develop such models started from decades ago but a model for 3D spatial-temporal (3D space plus 1D time) objects has not been well formulated. This dissertation describes the formalization of a spatial-temporal data model for managing 3D spatial-temporal objects. This model extends the spatial-temporal Object-Oriented model by incorporating a behavioral description to the definition of the spatial-temporal objects to better characterize the dynamics of these objects. Besides, spatial-temporal rules and conditions, which are expressed as constraints, are integrated as important components of the model. These rules and conditions serve as the foundations of maintaining data integrity and enabling complex spatial-temporal queries. A set of constraints related to the spatial-temporal characteristics of 3D spatial-temporal objects were identified and defined. The conceptual model served as the theoretical basis towards the building of a Geographic Information System (GIS) for managing 3D spatial-temporal objects. Based on the conceptual model, a prototype system was developed that provides interactive data management and query functions for 3D spatial-temporal objects. A subset of spatialtemporal constraints identified in the conceptual model were captured and formalized through extended 3D computational geometry algorithms to ensure data integrity and facilitate spatial-temporal queries. Using the dynamic repartitioning of airspace sectors as a case study, this research shows that the proposed framework is effective to solve problems involving 3D spatial-temporal objects.

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