subject:(computational modeling)

1. Fox, Neal P. Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach.

Degree: PhD, Cognitive Sciences, 2016, Brown University

URL: https://repository.library.brown.edu/studio/item/bdr:674171/

► During auditory language comprehension, bottom-up acoustic cues in the sensory signal are critical to the recognition of spoken words. However, listeners are also sensitive to… (more)

▼ During auditory language comprehension, bottom-up acoustic cues in the sensory signal are critical to the recognition of spoken words. However, listeners are also sensitive to higher-level processing; in general, identification of ambiguous targets is biased by prior expectations (e.g., words over non-words, contextually consistent words over inconsistent words). Although it is clear that such top-down cues influence word recognition, how they do so is less clear. The present work examines several questions about the computational principles underlying top-down effects on speech perception, focusing primarily on the influence of a preceding sentential context (e.g., Valerie hated the... vs. Brett hated to...) on the identification of phonetically ambiguous targets from voice-onset time continua (e.g., between bay and pay). Chapter 1 considers a longstanding debate: do top-down effects result from interactive modulation of perceptual processing or from entirely autonomous, decision-level processing? Some research has suggested that the time course of top-down effects is incompatible with interactive models. However, two experiments illustrate that, with appropriate controls, the predictions of interactive models are supported. Ultimately, though, two weaknesses of existing spoken word recognition models (whether interactive or autonomous) are that they ignore the role of sentential context and that they ignore the enormous variability in the size of top-down effects. To address these gaps, Chapter 2 introduces BIASES (short for Bayesian Integration of Acoustic and Sentential Evidence in Speech), a newly developed computational model of speech perception. Chapter 3 demonstrates BIASES’ ability to predict and explain fine-grained variability and asymmetries in both novel experimental data and in previously published work. Finally, Chapter 4 employs BIASES to examine top-down processing in patients with aphasia. Model-based analysis of previously published data and new data utilizing stimuli from Chapter 1 suggest that patients experience both bottom-up processing deficits and lexical processing deficits. Importantly, those impairments differ as a function of patients’ clinical diagnoses. In sum, this work offers new insights into the computations occurring at the interface between the perceptual processing of speech and the cognitive and linguistic processing of language. Advisors/Committee Members: Blumstein, Sheila (Director), Frank, Michael (Reader), Morgan, James (Reader).

Subjects/Keywords: computational modeling

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APA (6^th Edition):

Fox, N. P. (2016). Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:674171/

Chicago Manual of Style (16^th Edition):

Fox, Neal P. “Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach.” 2016. Doctoral Dissertation, Brown University. Accessed September 22, 2019. https://repository.library.brown.edu/studio/item/bdr:674171/.

MLA Handbook (7^th Edition):

Fox, Neal P. “Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach.” 2016. Web. 22 Sep 2019.

Vancouver:

Fox NP. Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach. [Internet] [Doctoral dissertation]. Brown University; 2016. [cited 2019 Sep 22]. Available from: https://repository.library.brown.edu/studio/item/bdr:674171/.

Council of Science Editors:

Fox NP. Top-Down Effects on Speech Perception: An Integrated Computational and Behavioral Approach. [Doctoral Dissertation]. Brown University; 2016. Available from: https://repository.library.brown.edu/studio/item/bdr:674171/

Georgia Tech

2. Faraji Mosalman, Mozhdeh Sadat. From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/59881

► Lignin is a natural polymer that is interwoven with cellulose and hemicellulose within plant cell walls. Due to this molecular arrangement, lignin is a major… (more)

Subjects/Keywords: Lignin; Computational modeling

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APA (6^th Edition):

Faraji Mosalman, M. S. (2018). From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59881

Chicago Manual of Style (16^th Edition):

Faraji Mosalman, Mozhdeh Sadat. “From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/59881.

MLA Handbook (7^th Edition):

Faraji Mosalman, Mozhdeh Sadat. “From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights.” 2018. Web. 22 Sep 2019.

Vancouver:

Faraji Mosalman MS. From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/59881.

Council of Science Editors:

Faraji Mosalman MS. From experimental observations to a functional model of the lignin pathway: Computational modeling reveals new insights. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59881

Georgia Tech

3. Tallman, Aaron E. Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support.

Degree: PhD, Materials Science and Engineering, 2018, Georgia Tech

URL: http://hdl.handle.net/1853/61639

► Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support Aaron E. Tallman 222 Pages Directed by Dr. David L. McDowell Computational material models help… (more)

▼ Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support Aaron E. Tallman 222 Pages Directed by Dr. David L. McDowell Computational material models help establish structure-property relationships by simulating properties, and are most effective when physically-based. The length and time scales of each simulation are constrained both by model type and computing power. Significant uncertainty can arise when models attempt to bridge across length and time scales, especially when using different model constructs. Hierarchical multiscale modeling (HMM) links models at different scales by informing parameters and form of higher scale models based on lower scale simulations, which can reduce uncertainty. The combination of diverse information sources in HMMs requires rigorous approaches to evaluate uncertainty propagation. In the pursuit of improved methods for empirical testing and development of model hierarchies, four approaches in which information is coordinated amongst multiple models are presented. (1) In a reconciled top-down and bottom-up approach, a likelihood-based model calibration method is proposed, and bcc Fe crystal plasticity (CP) is used to demonstrate the compatibility of information pathways. (2) A statistical volume element (SVE) ensemble-based homogenization scheme of two models of cartridge brass polycrystal plasticity is used to inform a Bammann-Chiesa-Johnson macroplasticity model with a local variation in parameters. The effects of SVE size and model form on the performance of the homogenization in bridging microstructure variability to macroscale uncertainty are explored. (3) A multiscale model development framework is outlined for the reduced order modeling of mesoscale variability in cartridge brass. The variability in SVE simulations is included with the results of a series of spherical microindentation experiments in a multiscale data collection. An initial study of the modeling involved in connecting the two length scales is performed. (4) In a CP-finite element method (FEM) based Materials Knowledge System model of -Ti, the influence of texture is considered. Texture is parameterized using generalized spherical harmonics. The CP-FEM model is used with polycrystalline SVE-ensembles to calibrate the MKS model across different textures, sampled according to an uncertainty reduction criterion. Results of the work suggest that data collection is an especially critical step in the formulation and deployment of hierarchical multiscale models. The use of bottom-up information in calibrating a multiscale model is shown to be susceptible to bias. A multiscale approach to coarse-grained simulations of polycrystals at the mesoscale is proposed. An approach to automating the data collection for a reduced-order model of microstructure sensitive response is shown to be competitive with manual data selection, prior to full optimization of the automated approach. Advisors/Committee Members: McDowell, David L (advisor), Wang, Yan (advisor), Swiler, Laura P (committee member), Garmestani, Hamid (committee member), Kalidindi, Surya R (committee member).

Subjects/Keywords: Calibration; Computational modeling

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APA (6^th Edition):

Tallman, A. E. (2018). Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61639

Chicago Manual of Style (16^th Edition):

Tallman, Aaron E. “Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2019. http://hdl.handle.net/1853/61639.

MLA Handbook (7^th Edition):

Tallman, Aaron E. “Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support.” 2018. Web. 22 Sep 2019.

Vancouver:

Tallman AE. Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1853/61639.

Council of Science Editors:

Tallman AE. Hierarchical Multiscale Materials Modeling: Calibration, Uncertainty Quantification, and Decision Support. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61639

University of Vermont

4. Stanton, Suzanne Louise. Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R).

Degree: MS, Chemistry, 2016, University of Vermont

URL: https://scholarworks.uvm.edu/graddis/624

► Recent studies have identified the Class B g-protein coupled receptor (GPCR) pituitary adenylate cyclase activating polypeptide type 1 (PAC1R) as a key component in… (more)

▼ Recent studies have identified the Class B g-protein coupled receptor (GPCR) pituitary adenylate cyclase activating polypeptide type 1 (PAC1R) as a key component in physiological stress management. Over-activity of neurological stress response systems due to prolonged or extreme exposure to traumatic events has led researchers to investigate PAC1R inhibition as a possible treatment for anxiety disorders such as post-traumatic stress disorder (PTSD). In 2008, Beebe and coworkers identified two such small molecule hydrazide antagonists and a general pharmacaphore for PAC1R inhibition. However, a relative dearth of information about Class B GPCRs in general, and PAC1R in specific, has significantly hindered progress toward the development of small molecule antagonists of PAC1R. The recent crystallization of the homologically similar glucagon receptor (GCGR) by Siu and coworkers in 2013, also a Class B receptor, has provided an experimentally resolved template from which to base computationally derived models of PAC1R. Initially, this research was focused towards synthesizing small molecule antagonists for PAC1R which were to be biologically screened via a qualitative western blot assay followed by a radioisotope binding assay for those hydrazides exhibiting down-stream signaling inhibitory capabilities. However, the resolution of the GCGR crystal structure shifted research objectives towards developing a homology model of PAC1R and evaluating that computationally created model with Beebe's known small molecule antagonists. Created using academic versions of on-line resources including UniProtKB, Swiss-Model and Maestro, a homology model for PAC1R is presented here. The model is validated and evaluated for the presence of conserved Class B GPCR residues and motifs, including expected disulfide bridges, a conserved tyrosine residue, a GWGxP motif, a conserved glutamic acid residue and the extension of the transmembrane helix 1 (TM1) into the extra-cellular domain. Having determined this virtual PAC1R an acceptable model, ligand docking studies of known antagonists to the receptor were undertaken using AutoDock Vina in conjunction with AutoDock Tools and PyMol. Computational docking results were evaluated via comparison of theoretical binding affinity results to Beebe's experimental data. Based on hydrogen bonding capabilities, several residues possibly key to the ligand-receptor binding complex are identified and include ASN 240, TYR 241 and HIST 365. Although the docking software does not identify non-bonding interactions other than hydrogen-bonding, the roles of additional proposed binding pocket residues are discussed in terms of hydrophobic interactions, π-π interactions and halogen bonding. These residues include TYR 161, PHE 196, VAL 203, PHE 204, ILE 209, LEU 210, VAL 237, TRP 297, PHE 362 and LEU 386. Although theoretical in nature, this reported homology modeling and docking exercise details a proposed binding site that may potentially further the development of drugs designed… Advisors/Committee Members: Matthias Brewer.

Subjects/Keywords: Computational; Homology; Modeling; Chemistry

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APA (6^th Edition):

Stanton, S. L. (2016). Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R). (Thesis). University of Vermont. Retrieved from https://scholarworks.uvm.edu/graddis/624

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Stanton, Suzanne Louise. “Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R).” 2016. Thesis, University of Vermont. Accessed September 22, 2019. https://scholarworks.uvm.edu/graddis/624.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Stanton, Suzanne Louise. “Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R).” 2016. Web. 22 Sep 2019.

Vancouver:

Stanton SL. Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R). [Internet] [Thesis]. University of Vermont; 2016. [cited 2019 Sep 22]. Available from: https://scholarworks.uvm.edu/graddis/624.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Stanton SL. Homology Modeling and Molecular Docking of Antagonists to Class B G-Protein Coupled Receptor Pituitary Adenylate Cyclase Type 1 (PAC1R). [Thesis]. University of Vermont; 2016. Available from: https://scholarworks.uvm.edu/graddis/624

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia State University

5. Aiken, John M. Transforming High School Physics With Modeling And Computation.

Degree: MS, Physics and Astronomy, 2013, Georgia State University

URL: https://scholarworks.gsu.edu/phy_astr_theses/18

► The Engage to Excel (PCAST) report, the National Research Council's Framework for K-12 Science Education, and the Next Generation Science Standards all call for… (more)

Subjects/Keywords: Computational Modeling; Physics; Education

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APA (6^th Edition):

Aiken, J. M. (2013). Transforming High School Physics With Modeling And Computation. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/phy_astr_theses/18

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Aiken, John M. “Transforming High School Physics With Modeling And Computation.” 2013. Thesis, Georgia State University. Accessed September 22, 2019. https://scholarworks.gsu.edu/phy_astr_theses/18.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Aiken, John M. “Transforming High School Physics With Modeling And Computation.” 2013. Web. 22 Sep 2019.

Vancouver:

Aiken JM. Transforming High School Physics With Modeling And Computation. [Internet] [Thesis]. Georgia State University; 2013. [cited 2019 Sep 22]. Available from: https://scholarworks.gsu.edu/phy_astr_theses/18.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Aiken JM. Transforming High School Physics With Modeling And Computation. [Thesis]. Georgia State University; 2013. Available from: https://scholarworks.gsu.edu/phy_astr_theses/18

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

6. Husain, Taha Murtuza. Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns.

Degree: PhD, Energy and Mineral Engineering, 2014, Penn State University

URL: https://etda.libraries.psu.edu/catalog/25682

► Large (1 – 4 x 106 m3) to major (> 4 x 106 m3) dome collapses for andesitic lava domes such as Soufriere Hills Volcano,… (more)

▼ Large (1 – 4 x 106 m3) to major (> 4 x 106 m3) dome collapses for andesitic lava domes such as Soufriere Hills Volcano, Montserrat are observed for elevated magma discharge rates (6 – 13 m3/s). The gas rich magma pulses lead to pressure build up in the lava dome that result in structural failure of the over steepened canyon-like walls which may lead to rockfall or pyroclastic flow. This indicates that dome collapse at Soufriere Hills Volcano, Montserrat is intimately related to magma extrusion rate. Variation in magma extrusion rate for open-system magma chambers is observed to follow alternating periods of high and low activity. Periodic behavior of magma exhibits a rich diversity in the nature of its eruptive history due to variation in magma chamber size, total crystal content, linear crystal growth rate and magma replenishment rate. Distinguished patterns of growth were observed at different magma flow rates ranging from endogenous to exogenous dome growth for magma with varying strengths. Determining the key parameters that control the transition in flow pattern of the magma during its lava dome building eruption is the main focus of this work. This dissertation examines the mechanical effects on the morphology of the evolving lava dome on the extrusion of magma from a central vent using a 2D particle dynamics model. The particle dynamics model is coupled with a conduit flow model that incorporates the kinetics of crystallization and rheological stiffening to investigate important mechanisms during lava dome building eruptions. Chapter I of this dissertation explores lava dome growth and failure mechanics using a two-dimensional particle-dynamics model. The model follows the evolution of fractured lava, with solidification driven by degassing induced crystallization of magma. The particle-dynamics model emulates the natural development of dome growth and rearrangement of the lava dome which is difficult in mesh-based analyses due to mesh entanglement effects. The deformable talus evolves naturally as a frictional carapace that caps a ductile magma core. Extrusion rate and magma rheology together with crystallization temperature and volatile content govern the distribution of strength in the composite structure. This new model is calibrated against existing observational models of lava dome growth. Results show that the shape and extent of the ductile core and the overall structure of the lava dome are strongly controlled by the infusion rate. The effects of extrusion rate on magma rheology are sensitive to material stiffness, which in turn is a function of volatile content and crystallinity. Material stiffness and material strength are key model parameters which govern magma rheology and subsequently the morphological character of the lava dome and in turn stability. Degassing induced crystallization causes material stiffening and enhances material strength reflected in non-Newtonian magma behavior. The increase in stiffness and strength of the injected magma causes a transition in the style of dome growth, from…

Subjects/Keywords: computational modeling; lava domes

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APA (6^th Edition):

Husain, T. M. (2014). Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/25682

Chicago Manual of Style (16^th Edition):

Husain, Taha Murtuza. “Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns.” 2014. Doctoral Dissertation, Penn State University. Accessed September 22, 2019. https://etda.libraries.psu.edu/catalog/25682.

MLA Handbook (7^th Edition):

Husain, Taha Murtuza. “Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns.” 2014. Web. 22 Sep 2019.

Vancouver:

Husain TM. Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns. [Internet] [Doctoral dissertation]. Penn State University; 2014. [cited 2019 Sep 22]. Available from: https://etda.libraries.psu.edu/catalog/25682.

Council of Science Editors:

Husain TM. Computational Modeling of Lava Domes using Particle Dynamics to investigate the effect of conduit flow mechanics on flow patterns. [Doctoral Dissertation]. Penn State University; 2014. Available from: https://etda.libraries.psu.edu/catalog/25682

Virginia Tech

7. Meyer, Kevin Joseph. Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries.

Degree: PhD, Chemical Engineering, 2013, Virginia Tech

URL: http://hdl.handle.net/10919/24762

► This work is concerned with the prediction of short (SGF) and long glass fiber (LGF) orientation in a center-gated disk and end-gated plaque injection molding… (more)

▼ This work is concerned with the prediction of short (SGF) and long glass fiber (LGF) orientation in a center-gated disk and end-gated plaque injection molding test geometry using a simulation method that has not been attempted previously. Previous work has used assumptions to simplify the fiber orientation geometry (assuming a thin cavity) or flow field (neglecting fountain flow and entry regions). LGF orientation is predicted in a center-gated disk injection molding geometry including the advancing front and simulating the sprue and gate region (SGM method) so that no assumption about fiber orientation at the mold entrance has to be made. Using a semi-flexible fiber model and orientation parameters obtained through rheology, increased agreement was found between predicted and experimentally obtained values of orientation using the SGM method and a semi-flexible fiber model than was found using a Hele-Shaw approximation. The SGM method was applied to the end-gated plaque to predict SGF orientation both along and away from the centerline using an objective (reduced strain closure model) and non-objective (strain reduction factor model) orientation model. The predicted values of the strain reduction factor model showed reasonable agreement with experimentally obtained values of orientation throughout the three-dimensional cavity when using orientation parameters fit to experimental orientation data. Furthermore it was found that the objective model predicted results very similar to the non-objective model suggesting that objectivity may not play a role in predicting orientation in more complex geometries such as an end-gated plaque. Finally, the SGM method was applied to the end-gated plaque geometry to predict LGF orientation using a rigid and semi-flexible fiber model. It was found that the SGM method and the semi-flexible fiber model provides orientation predictions that are similar to experimentally obtained values of orientation. Advisors/Committee Members: Baird, Donald G. (committeechair), Achenie, Luke E. (committee member), Wapperom, Peter (committee member), Martin, Stephen Michael (committee member).

Subjects/Keywords: Injection Molding; Composites; Computational Modeling

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APA (6^th Edition):

Meyer, K. J. (2013). Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/24762

Chicago Manual of Style (16^th Edition):

Meyer, Kevin Joseph. “Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries.” 2013. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/24762.

MLA Handbook (7^th Edition):

Meyer, Kevin Joseph. “Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries.” 2013. Web. 22 Sep 2019.

Vancouver:

Meyer KJ. Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/24762.

Council of Science Editors:

Meyer KJ. Improved Prediction of Glass Fiber Orientation in Basic Injection Molding Geometries. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/24762

Mississippi State University

8. Taylor, Benjamin Hugh. Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube.

Degree: MS, Mechanical Engineering, 2016, Mississippi State University

URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-10282016-135510/ ;

► This thesis seeks to investigate the predictive capabilities of Advanced turbulence models in the wake region of a wall-mounted cube. Dynamic Hybrid RANS/LES (DHRL), Hybrid… (more)

Subjects/Keywords: computational fluid dynamics; turbulence modeling

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APA (6^th Edition):

Taylor, B. H. (2016). Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube. (Masters Thesis). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-10282016-135510/ ;

Chicago Manual of Style (16^th Edition):

Taylor, Benjamin Hugh. “Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube.” 2016. Masters Thesis, Mississippi State University. Accessed September 22, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-10282016-135510/ ;.

MLA Handbook (7^th Edition):

Taylor, Benjamin Hugh. “Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube.” 2016. Web. 22 Sep 2019.

Vancouver:

Taylor BH. Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube. [Internet] [Masters thesis]. Mississippi State University; 2016. [cited 2019 Sep 22]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-10282016-135510/ ;.

Council of Science Editors:

Taylor BH. Predictive capabilities of advanced turbulence models in the wake region of a wall mounted cube. [Masters Thesis]. Mississippi State University; 2016. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-10282016-135510/ ;

University of Notre Dame

9. Cameron Wade Harvey. Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>.

Degree: PhD, Physics, 2013, University of Notre Dame

URL: https://curate.nd.edu/show/sx61dj55b1t

► A remarkable example of how patterns of movement and organization in populations of bacterial cells emerge from individual level interactions is seen with Myxobacteria.… (more)

Subjects/Keywords: biophysics; myxobacteria; simulation; computational modeling

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APA (6^th Edition):

Harvey, C. W. (2013). Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/sx61dj55b1t

Chicago Manual of Style (16^th Edition):

Harvey, Cameron Wade. “Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>.” 2013. Doctoral Dissertation, University of Notre Dame. Accessed September 22, 2019. https://curate.nd.edu/show/sx61dj55b1t.

MLA Handbook (7^th Edition):

Harvey, Cameron Wade. “Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>.” 2013. Web. 22 Sep 2019.

Vancouver:

Harvey CW. Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2013. [cited 2019 Sep 22]. Available from: https://curate.nd.edu/show/sx61dj55b1t.

Council of Science Editors:

Harvey CW. Collective Movement in Myxobacteria: Modeling and Experiments with Myxococcus xanthus</h1>. [Doctoral Dissertation]. University of Notre Dame; 2013. Available from: https://curate.nd.edu/show/sx61dj55b1t

University of Manitoba

10. Curtis, Evan. Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia.

Degree: Psychology, 2017, University of Manitoba

URL: http://hdl.handle.net/1993/32111

► By a dominant account, memory is composed of multiple storage systems, each operating according to unique principles. By an alternative account, memory is a single… (more)

Subjects/Keywords: Memory; Dissociation; Amnesia; Computational modeling

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APA (6^th Edition):

Curtis, E. (2017). Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia. (Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/32111

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Curtis, Evan. “Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia.” 2017. Thesis, University of Manitoba. Accessed September 22, 2019. http://hdl.handle.net/1993/32111.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Curtis, Evan. “Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia.” 2017. Web. 22 Sep 2019.

Vancouver:

Curtis E. Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia. [Internet] [Thesis]. University of Manitoba; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1993/32111.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Curtis E. Reinterpreting selective impairments in memory: computational and empirical simulations of dissociations in amnesia. [Thesis]. University of Manitoba; 2017. Available from: http://hdl.handle.net/1993/32111

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Utah

11. DeMille, Robert Curtis. Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail.

Degree: PhD, Chemistry, 2012, University of Utah

URL: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2028/rec/1656

► A theoretical study of a chemical system is focused on representing the systemproperly with a model and using it to accurately represent and predict physical… (more)

Subjects/Keywords: Computational efficiency; DNA; Modeling; Molecular Dynamics

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APA (6^th Edition):

DeMille, R. C. (2012). Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2028/rec/1656

Chicago Manual of Style (16^th Edition):

DeMille, Robert Curtis. “Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail.” 2012. Doctoral Dissertation, University of Utah. Accessed September 22, 2019. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2028/rec/1656.

MLA Handbook (7^th Edition):

DeMille, Robert Curtis. “Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail.” 2012. Web. 22 Sep 2019.

Vancouver:

DeMille RC. Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail. [Internet] [Doctoral dissertation]. University of Utah; 2012. [cited 2019 Sep 22]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2028/rec/1656.

Council of Science Editors:

DeMille RC. Multiple disciplinary modeling and reproduction of physical phenomena with computer simulations at high and low atomic detail. [Doctoral Dissertation]. University of Utah; 2012. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2028/rec/1656

Texas A&M University

12. Martin, Michael. Modeling of Transport in Lithium Ion Battery Electrodes.

Degree: 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11178

► Lithium ion battery systems are promising solutions to current energy storage needs due to their high operating voltage and capacity. Numerous efforts have been conducted… (more)

▼ Lithium ion battery systems are promising solutions to current energy storage needs due to their high operating voltage and capacity. Numerous efforts have been conducted to model these systems in order to aid the design process and avoid expensive and time consuming prototypical experiments. Of the numerous processes occurring in these systems, solid state transport in particular has drawn a large amount of attention from the research community, as it tends to be one of the rate limiting steps in lithium ion battery performance. Recent studies have additionally indicated that purposeful design of battery electrodes using 3D microstructures offers new freedoms in design, better use of available cell area, and increased battery performance. The following study is meant to serve as a first principles investigation into the behaviors of 3D electrode architectures by monitoring concentration and cycle behaviors under realistic operating conditions. This was accomplished using computational tools to model the solid state diffusion behavior in several generated electrode morphologies. Developed computational codes were used to generate targeted structures under prescribed conditions of particle shape, size, and overall morphology. The diffusion processes in these morphologies were simulated under conditions prescribed from literature. Primary results indicate that parameters usually employed to describe electrode geometry, such as volume to surface area ratio, cannot be solely relied upon to predict or characterize performance. Additionally, the interaction between particle shapes implies some design aspects that may be exploited to improve morphology behavior. Of major importance is the degree of particle isolation and overlap in 3D architectures, as these govern gradient development and lithium depletion within the electrode structures. The results of this study indicate that there are optimum levels of these parameters, and so purposeful design must make use of these behaviors. Advisors/Committee Members: Mukherjee, Partha P. (advisor), Ranjan, Devesh (advisor), Annamalai, Kalyan (committee member), Lazarov, Raytcho (committee member).

Subjects/Keywords: Lithium Ion Battery; 3D Electrode; Computational Modeling

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APA (6^th Edition):

Martin, M. (2012). Modeling of Transport in Lithium Ion Battery Electrodes. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11178

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Martin, Michael. “Modeling of Transport in Lithium Ion Battery Electrodes.” 2012. Thesis, Texas A&M University. Accessed September 22, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11178.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Martin, Michael. “Modeling of Transport in Lithium Ion Battery Electrodes.” 2012. Web. 22 Sep 2019.

Vancouver:

Martin M. Modeling of Transport in Lithium Ion Battery Electrodes. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11178.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Martin M. Modeling of Transport in Lithium Ion Battery Electrodes. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11178

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

13. Knight, Jason Matthew. Optimal Model-Based Approaches for Predictive Inference in Biology.

Degree: 2015, Texas A&M University

URL: http://hdl.handle.net/1969.1/155131

► Predictive modeling of the dynamic, multivariate, non-linear, stochastic systems of biology is a difficult enterprise. High throughput measurement techniques are enabling new approaches to computational… (more)

Subjects/Keywords: computational biology; predictive inference; statistical modeling; bioinformatics

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APA (6^th Edition):

Knight, J. M. (2015). Optimal Model-Based Approaches for Predictive Inference in Biology. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155131

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Knight, Jason Matthew. “Optimal Model-Based Approaches for Predictive Inference in Biology.” 2015. Thesis, Texas A&M University. Accessed September 22, 2019. http://hdl.handle.net/1969.1/155131.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Knight, Jason Matthew. “Optimal Model-Based Approaches for Predictive Inference in Biology.” 2015. Web. 22 Sep 2019.

Vancouver:

Knight JM. Optimal Model-Based Approaches for Predictive Inference in Biology. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1969.1/155131.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Knight JM. Optimal Model-Based Approaches for Predictive Inference in Biology. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155131

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Edinburgh

14. Warren, Mariah. Modeling Allophonic Rule Learning with Distributional and Phonetic Factors.

Degree: 2012, University of Edinburgh

URL: http://hdl.handle.net/1842/8496

► A fundamental task faced by infants during language acquisition is acquiring the phonological structure of the native language, including the abstract phonemic categories and the… (more)

Subjects/Keywords: Allophone; Phonological Rules; Statistical Learning; Computational Modeling

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APA (6^th Edition):

Warren, M. (2012). Modeling Allophonic Rule Learning with Distributional and Phonetic Factors. (Thesis). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/8496

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Warren, Mariah. “Modeling Allophonic Rule Learning with Distributional and Phonetic Factors.” 2012. Thesis, University of Edinburgh. Accessed September 22, 2019. http://hdl.handle.net/1842/8496.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Warren, Mariah. “Modeling Allophonic Rule Learning with Distributional and Phonetic Factors.” 2012. Web. 22 Sep 2019.

Vancouver:

Warren M. Modeling Allophonic Rule Learning with Distributional and Phonetic Factors. [Internet] [Thesis]. University of Edinburgh; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1842/8496.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Warren M. Modeling Allophonic Rule Learning with Distributional and Phonetic Factors. [Thesis]. University of Edinburgh; 2012. Available from: http://hdl.handle.net/1842/8496

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Jawaharlal Nehru University

15. Patil, Kiran Suresh. Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -.

Degree: Computer Science, 2007, Jawaharlal Nehru University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/32306

none

References, Tables, Figures vip. 118p.

Advisors/Committee Members: Karmeshu.

Subjects/Keywords: Neurons; computational; modeling

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APA (6^th Edition):

Patil, K. S. (2007). Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -. (Thesis). Jawaharlal Nehru University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/32306

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Patil, Kiran Suresh. “Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -.” 2007. Thesis, Jawaharlal Nehru University. Accessed September 22, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/32306.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Patil, Kiran Suresh. “Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -.” 2007. Web. 22 Sep 2019.

Vancouver:

Patil KS. Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -. [Internet] [Thesis]. Jawaharlal Nehru University; 2007. [cited 2019 Sep 22]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/32306.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Patil KS. Computational modeling and simulation of Neuronal dynamics : effects of Stochastic Perturbations; -. [Thesis]. Jawaharlal Nehru University; 2007. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/32306

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

16. Vedula, Vijay. Image based computational modeling of intracardiac flows.

Degree: 2015, Johns Hopkins University

URL: http://jhir.library.jhu.edu/handle/1774.2/37858

► With continuous advancements in four-dimensional medical imaging technologies, increasing computational speeds, and widespread availability of high performance computing facilities, computational modeling of intracardiac flows is… (more)

▼ With continuous advancements in four-dimensional medical imaging technologies, increasing computational speeds, and widespread availability of high performance computing facilities, computational modeling of intracardiac flows is becoming increasingly viable and has the potential to become a powerful non-invasive diagnostic tool for the diagnosis and treatment of cardiovascular disease. The motive of the current study is to develop a modeling framework that facilitates image-based analysis of intracardiac flows in health as well as disease and to use this framework to gain fundamental insights into intracardiac hemodynamics. A procedure is developed for constructing computational fluid dynamics (CFD) – ready models from in vivo imaging data. The key components of this procedure are the registration and segmentation of the 4D data for several (~20) key frames, template based mapping to ensure surface grid conformality and high-fidelity simulations using a sharp-interface immersed boundary solver. A physiologically representative, kinematic model of the mitral valve is also developed for use in these simulations. As a precursor, a comprehensive quantitative validation of the flow solver is performed using experimental data in a simple model of the left ventricle. A quantitative comparison of the phase-averaged velocity and vorticity fields between the simulation and the experiment shows a reasonable agreement. The detailed assessment of this comparison is used to identify and discuss the key challenges and uncertainties associated in conducting such a validation study. The vast majority of computational investigations of intracardiac flows have focused either on the left or the right ventricles while the corresponding atria were modeled in highly simplistic ways. However, the impact of this simplification on the hemodynamics of the ventricular filling has not been clearly understood. Additionally, the surface of the ventricle has been assumed to be smooth although it is well known that the left ventricle is highly corrugated with surface protrusions or trabeculae and papillary muscles extending deep into the ventricular cavity. Hence, separate studies were conducted to understand the effect of complex atrial flows on the intraventricular flow development and also to understand and quantify the impact of the trabeculae and papillary muscles on ventricular hemodynamics Results indicate that the trabeculae and papillary muscles significantly impact ventricular flow resulting in a deeper penetration of the mitral jet into the ventricle during filling. These anatomical features are also found to produce a “squeezing” effect that enhances apical washout. It is also demonstrated that the complex flow dynamics developed inside the left atrium have minimal influence on the flow inside the left ventricle, which is primarily governed by the mitral valve leaflets configuration. The complex vortical structures inside the left atrium are rapidly dissipated due to the complex interaction of multiple vortex rings leading to breakup,… Advisors/Committee Members: Mittal, Rajat (advisor).

Subjects/Keywords: Cardiac hemodynamics; computational modeling; immersed boundary methods

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APA (6^th Edition):

Vedula, V. (2015). Image based computational modeling of intracardiac flows. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/37858

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Vedula, Vijay. “Image based computational modeling of intracardiac flows.” 2015. Thesis, Johns Hopkins University. Accessed September 22, 2019. http://jhir.library.jhu.edu/handle/1774.2/37858.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Vedula, Vijay. “Image based computational modeling of intracardiac flows.” 2015. Web. 22 Sep 2019.

Vancouver:

Vedula V. Image based computational modeling of intracardiac flows. [Internet] [Thesis]. Johns Hopkins University; 2015. [cited 2019 Sep 22]. Available from: http://jhir.library.jhu.edu/handle/1774.2/37858.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vedula V. Image based computational modeling of intracardiac flows. [Thesis]. Johns Hopkins University; 2015. Available from: http://jhir.library.jhu.edu/handle/1774.2/37858

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Carnegie Mellon University

17. MacLellan, Christopher J. Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing.

Degree: 2017, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/1054

► Intelligent tutoring systems are effective for improving students’ learning outcomes (Bowen et al., 2013; Koedinger & Anderson, 1997; Pane et al., 2013). However, constructing tutoring… (more)

▼ Intelligent tutoring systems are effective for improving students’ learning outcomes (Bowen et al., 2013; Koedinger & Anderson, 1997; Pane et al., 2013). However, constructing tutoring systems that are pedagogically effective has been widely recognized as a challenging problem (Murray, 1999, 2003). In this thesis, I explore the use of computational models of apprentice learning, or computer models that learn interactively from examples and feedback, to support tutor development. In particular, I investigate their use for authoring expert-models via demonstrations and feedback (Matsuda et al., 2014), predicting student behavior within tutors (VanLehn et al., 1994), and for testing alternative learning theories (MacLellan, Harpstead, Patel, & Koedinger, 2016). To support these investigations, I present the Apprentice Learner Architecture, which posits the types of knowledge, performance, and learning components needed for apprentice learning and enables the generation and testing of alternative models. I use this architecture to create two models: the DECISION TREE model, which non- incrementally learns when to apply its skills, and the TRESTLE model, which instead learns incrementally. Both models both draw on the same small set of prior knowledge for all simulations (six operators and three types of relational knowledge). Despite their limited prior knowledge, I demonstrate their use for efficiently authoring a novel experimental design tutor and show that they are capable of achieving human-level performance in seven additional tutoring systems that teach a wide range of knowledge types (associations, categories, and skills) across multiple domains (language, math, engineering, and science). I show that the models are capable of predicting which versions of a fraction arithmetic and box and arrows tutors are more effective for human students’ learning. Further, I use a mixedeffects regression analysis to evaluate the fit of the models to the available human data and show that across all seven domains the TRESTLE model better fits the human data than the DECISION TREE model, supporting the theory that humans learn the conditions under which skills apply incrementally, rather than non-incrementally as prior work has suggested (Li, 2013; Matsuda et al., 2009). This work lays the foundation for the development of a Model Human Learner— similar to Card, Moran, and Newell’s (1986) Model Human Processor—that encapsulates psychological and learning science findings in a format that researchers and instructional designers can use to create effective tutoring systems.

Subjects/Keywords: Computational Modeling; Science of Learning; Educational Technology

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APA (6^th Edition):

MacLellan, C. J. (2017). Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1054

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

MacLellan, Christopher J. “Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing.” 2017. Thesis, Carnegie Mellon University. Accessed September 22, 2019. http://repository.cmu.edu/dissertations/1054.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

MacLellan, Christopher J. “Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing.” 2017. Web. 22 Sep 2019.

Vancouver:

MacLellan CJ. Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing. [Internet] [Thesis]. Carnegie Mellon University; 2017. [cited 2019 Sep 22]. Available from: http://repository.cmu.edu/dissertations/1054.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

MacLellan CJ. Computational Models of Human Learning: Applications for Tutor Development, Behavior Prediction, and Theory Testing. [Thesis]. Carnegie Mellon University; 2017. Available from: http://repository.cmu.edu/dissertations/1054

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Southern California

18. Ivzan, Nadav. A probabilistic model predicting retinal ganglion cell responses to natural stimuli.

Degree: PhD, Biomedical Engineering, 2015, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548002/rec/309

► Developing computational models that predict the spiking responses of neurons is important to understand how the brain functions, and cure neuronal diseases. In the first… (more)

Subjects/Keywords: retina; electophysiology; natural images; vision; computational modeling

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APA (6^th Edition):

Ivzan, N. (2015). A probabilistic model predicting retinal ganglion cell responses to natural stimuli. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548002/rec/309

Chicago Manual of Style (16^th Edition):

Ivzan, Nadav. “A probabilistic model predicting retinal ganglion cell responses to natural stimuli.” 2015. Doctoral Dissertation, University of Southern California. Accessed September 22, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548002/rec/309.

MLA Handbook (7^th Edition):

Ivzan, Nadav. “A probabilistic model predicting retinal ganglion cell responses to natural stimuli.” 2015. Web. 22 Sep 2019.

Vancouver:

Ivzan N. A probabilistic model predicting retinal ganglion cell responses to natural stimuli. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Sep 22]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548002/rec/309.

Council of Science Editors:

Ivzan N. A probabilistic model predicting retinal ganglion cell responses to natural stimuli. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/548002/rec/309

Montana State University

19. Sturlaugson, Liessman Eric. Extensions to modeling and inference in continuous time Bayesian networks.

Degree: College of Engineering, 2014, Montana State University

URL: https://scholarworks.montana.edu/xmlui/handle/1/9368

► The continuous time Bayesian network (CTBN) enables reasoning about complex systems in continuous time by representing a system as a factored, finite-state, continuous-time Markov process.… (more)

▼ The continuous time Bayesian network (CTBN) enables reasoning about complex systems in continuous time by representing a system as a factored, finite-state, continuous-time Markov process. The dynamics of the CTBN are described by each node's conditional intensity matrices, determined by the states of the parents in the network. As the CTBN is a relatively new model, many extensions that have been defined with respect to Bayesian networks (BNs) have not yet been extended to CTBNs. This thesis presents five novel extensions to CTBN modeling and inference. First, we prove several complexity results specific to CTBNs. It is known that exact inference in CTBNs is NP-hard due to the use of a BN for the initial distribution. We prove that exact inference in CTBNs is still NP-hard, even when the initial states are given, and prove that approximate inference in CTBNs, as with BNs, is also NP-hard. Second, we formalize performance functions for the CTBN and show how they can be factored in the same way as the network, even when the performance functions are defined with respect to interaction between multiple nodes. Performance functions extend the model, allowing it to represent complex, user-specified functions of the behaviors of the system. Third, we present a novel method for node marginalization called "node isolation" that approximates a set of conditional intensity matrices with a single unconditional intensity matrix. The method outperforms previous node marginalization techniques in all of our experiments by better describing the long-term behavior of the marginalized nodes. Fourth, using the node isolation method we developed, we show how methods for sensitivity analysis of Markov processes can be applied to the CTBN while exploiting the conditional independence structure of the network. This enables efficient sensitivity analysis to be performed on our CTBN performance functions. Fifth, we formalize both uncertain and negative types of evidence in the context of CTBNs and extend existing inference algorithms to be able to support all combinations of evidence types. We show that these extensions make the CTBN more powerful, versatile, and applicable to real-world domains. Advisors/Committee Members: Chairperson, Graduate Committee: John Sheppard (advisor).

Subjects/Keywords: Markov processes.; Computational complexity.; Graphical modeling (Statistics).

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APA (6^th Edition):

Sturlaugson, L. E. (2014). Extensions to modeling and inference in continuous time Bayesian networks. (Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/9368

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sturlaugson, Liessman Eric. “Extensions to modeling and inference in continuous time Bayesian networks.” 2014. Thesis, Montana State University. Accessed September 22, 2019. https://scholarworks.montana.edu/xmlui/handle/1/9368.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sturlaugson, Liessman Eric. “Extensions to modeling and inference in continuous time Bayesian networks.” 2014. Web. 22 Sep 2019.

Vancouver:

Sturlaugson LE. Extensions to modeling and inference in continuous time Bayesian networks. [Internet] [Thesis]. Montana State University; 2014. [cited 2019 Sep 22]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9368.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sturlaugson LE. Extensions to modeling and inference in continuous time Bayesian networks. [Thesis]. Montana State University; 2014. Available from: https://scholarworks.montana.edu/xmlui/handle/1/9368

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Ottawa

20. Kuebler, Eric Stephen. Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks .

Degree: 2018, University of Ottawa

URL: http://hdl.handle.net/10393/37855

► Neurons and networks of the brain may use various strategies of computation to provide the neural substrate for sensation, perception, or cognition. To simplify the… (more)

Subjects/Keywords: Neuronal variability; Computational modeling; Synchrony; Neural networks

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APA (6^th Edition):

Kuebler, E. S. (2018). Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/37855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kuebler, Eric Stephen. “Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks .” 2018. Thesis, University of Ottawa. Accessed September 22, 2019. http://hdl.handle.net/10393/37855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kuebler, Eric Stephen. “Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks .” 2018. Web. 22 Sep 2019.

Vancouver:

Kuebler ES. Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10393/37855.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kuebler ES. Harnessing the Variability of Neuronal Activity: From Single Neurons to Networks . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/37855

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Virginia Tech

21. Carbo Barrios, Adria. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.

Degree: PhD, Animal and Poultry Sciences, 2014, Virginia Tech

URL: http://hdl.handle.net/10919/64833

► CD4+ T cells mediate and orchestrate a tremendous panoply of lymphoid cell subsets in the human immune system. CD4+ T cells are able to differentiate… (more)

▼ CD4+ T cells mediate and orchestrate a tremendous panoply of lymphoid cell subsets in the human immune system. CD4+ T cells are able to differentiate into either effector pro-inflammatory or regulatory anti-inflammatory subsets depending on the cytokine milieu in their environment. This complex process is mediated through a variety of cytokines and soluble factors. Yet, the mechanisms of action underlying the process of differentiation and plasticity of this interesting immune subset are incompletely understood. To gain a better understanding of the CD4+ T cell differentiation and function, here we present an array of different strategies to model and validate CD4+ T cell differentiation and heterogeneity. The approaches presented here vary from ordinary-differential equation-based to agent-based simulations, from data-driven to theory-based approaches, and from intracellular mathematical to tissue-level or cellular modeling. The knowledge generated throughout this dissertation exemplifies how a combination of computational modeling with experimental immunology can efficiently advance the scene on CD4+ T cell differentiation. In this thesis I present i) an overview on CD4+ T cell differentiation and an introduction to which computational strategies have been adopted in the field to tackle with this problem, ii) ODE-based modeling and predictions on Th17 plasticity modulated by PPARγ, iii) ODE- and ABM-based cellular level modeling of immune responses towards Helicobacter pylori and the role of CD4+ T cell subsets on it, iv) Intracellular strategies to validate a potential therapeutic target within a CD4+ T cell to treat H. pylori infection, and finally v) data-driven strategies to model Th17 differentiation based on sequencing or microarray data to generate novel predictions on specific components. I present both mathematical and computational work as well as experimental work, in vitro and in vivo with animal models, to demonstrate how computational immunology and immunoinformatics can help, not only in understanding this complex process, but also in the development of immune therapeutics for infectious, allergic and immune-mediated diseases. Advisors/Committee Members: Bassaganya-Riera, Josep (committeechair), Hoops, Stefan (committee member), Bevan, David R. (committee member), Hontecillas-Magarzo, Raquel (committee member).

Subjects/Keywords: Immunology; CD4+ T cells; computational modeling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Carbo Barrios, A. (2014). Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64833

Chicago Manual of Style (16^th Edition):

Carbo Barrios, Adria. “Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.” 2014. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/64833.

MLA Handbook (7^th Edition):

Carbo Barrios, Adria. “Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity.” 2014. Web. 22 Sep 2019.

Vancouver:

Carbo Barrios A. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/64833.

Council of Science Editors:

Carbo Barrios A. Transdisciplinary Strategies to Study the Mechanisms of CD4+ T cell Differentiation and Heterogeneity. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64833

Clemson University

22. Harvey, Tyler George. Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology.

Degree: PhD, Bioengineering, 2018, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/2249

► The heart is a complex mechanical and electrical environment and small changes at the cellular and subcellular scale can have profound impacts at the tissue,… (more)

▼ The heart is a complex mechanical and electrical environment and small changes at the cellular and subcellular scale can have profound impacts at the tissue, organ, and organ system levels. The goal of this research is to better understand structure-function relationships at these cellular and subcellular levels of the cardiac environment. This improved understanding may prove increasingly important as medicine begins shifting toward engineered replacement tissues and organs. Specifically, we work towards this goal by presenting a framework to automatically create finite element models of cells based on optical images. This framework can be customized to model the effects of subcellular structure and organization on mechanical and electrophysiological properties at the cellular level and has the potential for extension to the tissue level and beyond. In part one of this work, we present a novel algorithm is presented that can generate physiologically relevant distributions of myofibrils within adult cardiomyocytes from confocal microscopy images. This is achieved by modelling these distributions as directed acyclic graphs, assigning a cost to each node based on observations of cardiac structure and function, and determining to minimum-cost flow through the network. This resulting flow represents the optimal distribution of myofibrils within the cell. In part two, these generated geometries are used as inputs to a finite element model (FEM) to determine the role the myofibrillar organization plays in the axal and transverse mechanics of the whole cell. The cardiomyocytes are modeled as a composite of fiber trusses within an elastic solid matrix. The behavior of the model is validated by comparison to data from combined Atomic Force Microscopy (AFM) and Carbon Fiber manipulation. Recommendations for extending the FEM framework are also explored. A secondary goal, discussed in part three of this work, is to make computational models and simulation tools more accessible to novice learners. Doing so allows active learning of complicated course materials to take place. Working towards this goal, we present CellSpark: a simulation tool developed for teaching cellular electrophysiology and modelling to undergraduate bioengineering students. We discuss the details of its implementation and implications for improved student learning outcomes when used as part of a discovery learning assignment. Advisors/Committee Members: Delphine Dean, Committee Chair, Bruce Z. Gao, Jiro Nagatomi, William Richardson.

Subjects/Keywords: Cardiac mechanics; Computational modeling; Engineering education

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APA (6^th Edition):

Harvey, T. G. (2018). Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/2249

Chicago Manual of Style (16^th Edition):

Harvey, Tyler George. “Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology.” 2018. Doctoral Dissertation, Clemson University. Accessed September 22, 2019. https://tigerprints.clemson.edu/all_dissertations/2249.

MLA Handbook (7^th Edition):

Harvey, Tyler George. “Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology.” 2018. Web. 22 Sep 2019.

Vancouver:

Harvey TG. Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology. [Internet] [Doctoral dissertation]. Clemson University; 2018. [cited 2019 Sep 22]. Available from: https://tigerprints.clemson.edu/all_dissertations/2249.

Council of Science Editors:

Harvey TG. Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology. [Doctoral Dissertation]. Clemson University; 2018. Available from: https://tigerprints.clemson.edu/all_dissertations/2249

Cornell University

23. Boston, Marisa. A Computational Model Of Cognitive Constraints In Syntactic Locality .

Degree: 2012, Cornell University

URL: http://hdl.handle.net/1813/29156

► This dissertation is broadly concerned with the question: how do human cognitive limitations influence difficult sentences? The focus is a class of grammatical restrictions, locality… (more)

Subjects/Keywords: Computational modeling; Syntactic locality; Cognitive constraints

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APA (6^th Edition):

Boston, M. (2012). A Computational Model Of Cognitive Constraints In Syntactic Locality . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/29156

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Boston, Marisa. “A Computational Model Of Cognitive Constraints In Syntactic Locality .” 2012. Thesis, Cornell University. Accessed September 22, 2019. http://hdl.handle.net/1813/29156.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Boston, Marisa. “A Computational Model Of Cognitive Constraints In Syntactic Locality .” 2012. Web. 22 Sep 2019.

Vancouver:

Boston M. A Computational Model Of Cognitive Constraints In Syntactic Locality . [Internet] [Thesis]. Cornell University; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1813/29156.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Boston M. A Computational Model Of Cognitive Constraints In Syntactic Locality . [Thesis]. Cornell University; 2012. Available from: http://hdl.handle.net/1813/29156

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Cornell University

24. Chylek, Lily. Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments .

Degree: 2016, Cornell University

URL: http://hdl.handle.net/1813/44334

► Fc[epsilon]RI is a multi-subunit receptor found on the surface of mast cells and basophils and binds immunoglobulin E (IgE) with high affinity. Stimulation of this… (more)

▼ Fc[epsilon]RI is a multi-subunit receptor found on the surface of mast cells and basophils and binds immunoglobulin E (IgE) with high affinity. Stimulation of this receptor, typically via antigen-mediated crosslinking of IgE, can lead to release of histamine and other mediators that are involved in the allergic immune response. Thus, understanding the workings of Fc[epsilon]RI-mediated signaling brings us closer to understanding one of the most widespread health conditions in the developed world. Fc[epsilon]RI-mediated signaling processes are inherently complex, involving highly interconnected systems in which quantitative factors can play a decisive role. Such systems can be difficult to decipher using intuition alone, but computational models can extend our reasoning abilities and enable us to develop nontrivial hypotheses that generate experimentally testable predictions. To develop a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated to impact cellular decisionmaking, we developed a computational interaction library. The library consists of executable rules for protein-protein and protein-lipid interactions. The library is visualized to facilitate understanding of network circuitry and identification of network motifs. Using this library, we investigated branching pathways from the adaptor protein Lat, which influence production of the phospholipid phosphatidylinositol (3,4,5)trisphosphate (PIP3) at the plasma membrane and the soluble second messenger inositol trisphosphate (IP3). We found that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. Such robustness has been observed experimentally for some readouts. We also developed a model that proposes an explanation for experimentally observed oscillations in Ca2+ concentration, which is an important outcome of Fc[epsilon]RI stimulation. To investigate Fc[epsilon]RI signaling from another angle, we modeled interactions between the receptor and a structurally defined ligand for IgE. We parameterized the model for consistency with kinetic fluorescence data as well as super-resolution imaging measurements of antigen-induced receptor aggregation. To facilitate this study, we developed a specialized tool for fitting biochemical models to experimental data. Finally, we examined how patterns of exposure to stimulatory and non-stimulatory ligands affect mast cells' secretory responses. Through iterative modeling and experimental tests, we learned that a tug-of-war between positive signals from the tyrosine kinase Syk and negative signals from the lipid phosphatase Ship-1 govern the magnitude of responses, with the adaptor protein Shc1 influencing how the balance of positive and negative signals changes with time. Advisors/Committee Members: Cerione,Richard A (committeeMember), Holowka,David Allan (committeeMember), Sondermann,Holger (committeeMember), Hlavacek,William S (committeeMember).

Subjects/Keywords: mast cells; computational modeling; cell signaling

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chylek, L. (2016). Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/44334

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chylek, Lily. “Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments .” 2016. Thesis, Cornell University. Accessed September 22, 2019. http://hdl.handle.net/1813/44334.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chylek, Lily. “Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments .” 2016. Web. 22 Sep 2019.

Vancouver:

Chylek L. Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments . [Internet] [Thesis]. Cornell University; 2016. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1813/44334.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chylek L. Understanding Ige Receptor Signaling Through Computational Modeling And Quantitative Experiments . [Thesis]. Cornell University; 2016. Available from: http://hdl.handle.net/1813/44334

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Uppsala University

25. Holmgren, Hanna. Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH.

Degree: Information Technology, 2012, Uppsala University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179861

► Numerical ice sheet modeling is a rather young discipline: it started in the 1950s. The "first generation" models developed at that time are currently… (more)

▼ Numerical ice sheet modeling is a rather young discipline: it started in the 1950s. The "first generation" models developed at that time are currently being replaced by "new generations" ones, such as e.g. ARCTIC-TARAH. ARCTIC-TARAH is a Bert Bolin Center for Climate Research spin-off from the Pennsylvania State University Ice sheet model (PSUI). When the Bolin Center received PSUI for subsequent independent development and adaption of the code to Arctic settings in 2010, an initial inspection of the source code suggested that PSUI also contained a module that allows for the treatment of glacial hydraulics. A numerical ice sheet model including coupling of ice dynamics and hydraulics is an extremely important tool in testing new hypotheses of former geological events. E.g., based on the recent finding that Arctic Ocean sediments contain a very distinct signature, it has been suggested that ice dammed lakes at the south-eastern margin of the late Weichselian Eurasian ice sheet drained into the Arctic Ocean in a catastrophic event around 55.000 years ago. The aim of this thesis is to perform a reconnaissance analysis of the glacio-hydraulic algorithms in ARCTIC-TARAH, as "inherited" (but never with published record of functionality) from PSUI. The work is carried out in two steps: first the routines and algorithms describing the hydraulics are located and explored, and then these routines are tested and verified by performing experiment simulations. The investigation of the program code reveals the presence of two hydraulics related modules in ARCTIC-TARAH. The main tasks of the module Water are to initiate lakes and oceans and to adjust hydrostatic pressure in each lake. Further, with the module Move Water activated, transportation of water (e.g. in rivers) is possible. Results from idealized experiment simulations verify the functionality of the routines in the module Water. An in-depth analysis of the module Move Water suggests that there is a mismatch in time units when solving the equations describing flow of water. Experiment simulations also support this flaw detected in the flow model. Preliminary adjustments were made to the source code of the module Move Water, which made it possible to simulate the transportation of water both under an ice sheet and in rivers on land. However, these adjustments do not solve the problem of mismatching time scales, and the numerical solutions obtained from the experiments were observed to be unstable and, therefore, possibly incorrect. To be able to perform more advanced simulations in support of the above mentioned hypothesis, the flow model in the module Move Water needs to be improved or replaced. One solution to the problem with mismatching time scales, could be to use a so called multiscale solution in time.

Subjects/Keywords: ice dynamics; ice sheet modeling; computational hydraulics

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APA (6^th Edition):

Holmgren, H. (2012). Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH. (Thesis). Uppsala University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179861

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Holmgren, Hanna. “Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH.” 2012. Thesis, Uppsala University. Accessed September 22, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179861.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Holmgren, Hanna. “Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH.” 2012. Web. 22 Sep 2019.

Vancouver:

Holmgren H. Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH. [Internet] [Thesis]. Uppsala University; 2012. [cited 2019 Sep 22]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179861.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Holmgren H. Computational Ice Dynamics and Hydraulics : Towards a Coupling in the Ice Sheet Code ARCTIC-TARAH. [Thesis]. Uppsala University; 2012. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179861

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Vanderbilt University

26. Kragel, James Edward. The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory.

Degree: PhD, Neuroscience, 2015, Vanderbilt University

URL: http://etd.library.vanderbilt.edu//available/etd-05202015-151428/ ;

► The medial temporal lobe (MTL) is essential to episodic memory through its role in the reactivation of past experience. Cortical networks provide top-down influence on… (more)

▼ The medial temporal lobe (MTL) is essential to episodic memory through its role in the reactivation of past experience. Cortical networks provide top-down influence on the MTL, influencing the manner in which information can be retrieved. While neuroimaging investigations of human memory have characterized the functional correlates of episodic retrieval, the coordination of MTL systems during self-guided memory search is poorly understood. Using functional neuroimaging to estimate neural activation during variants of the free-recall paradigm, this dissertation demonstrates that the posterior MTL is critically involved in internally-directed memory search, through its interactions with distributed cortical systems. First, I characterize the engagement of a cortico-hippocampal network during memory search. I then demonstrate increased functional connectivity between this network and multiple frontoparietal systems, identifying neural mechanisms that may potentially reflect top-down control of memory search. Next, I relate activation of the posterior MTL to the process of episodic recollection through comparison of activity during free recall and source recognition tasks. I additionally demonstrate common activation in dorsal frontoparietal networks during free recall and processing of item familiarity. To characterize the computations mediated by the MTL, I develop a neuro-cognitive model of free recall. Retrieved-context theories propose that temporal context, a slowly integrating representation of the recent past, cues the hippocampus during retrieval. I link activation of the MTL to the process of temporal reinstatement, predicting the temporal organization of recall. Next, I use a variant of the free-recall paradigm in which memory is disrupted prior to retrieval, to test the capacity of large-scale cortical networks to control episodic memory. I show that a frontoparietal control network (FPCN) functionally couples with the MTL when memory is disrupted. Using a neurally informed computational model of recall, I demonstrate that activation of the FPCN and posterior MTL predict when individuals will overcome distraction by reinstating contextual information to guide memory search. Taken together, these findings demonstrate how the MTL supports memory search through the reinstatement of contextual information, a process that is coordinated through top-down signals from frontoparietal networks. Advisors/Committee Members: Sean M. Polyn (committee member), René, Marois (committee member), Thomas J. Palmeri (committee member), Frank Tong (chair).

Subjects/Keywords: computational modeling; fMRI; free recall; episodic memory

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kragel, J. E. (2015). The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu//available/etd-05202015-151428/ ;

Chicago Manual of Style (16^th Edition):

Kragel, James Edward. “The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory.” 2015. Doctoral Dissertation, Vanderbilt University. Accessed September 22, 2019. http://etd.library.vanderbilt.edu//available/etd-05202015-151428/ ;.

MLA Handbook (7^th Edition):

Kragel, James Edward. “The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory.” 2015. Web. 22 Sep 2019.

Vancouver:

Kragel JE. The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory. [Internet] [Doctoral dissertation]. Vanderbilt University; 2015. [cited 2019 Sep 22]. Available from: http://etd.library.vanderbilt.edu//available/etd-05202015-151428/ ;.

Council of Science Editors:

Kragel JE. The functional neuroanatomy of episodic retrieval: using neuroimaging to understand the computational processes underlying human memory. [Doctoral Dissertation]. Vanderbilt University; 2015. Available from: http://etd.library.vanderbilt.edu//available/etd-05202015-151428/ ;

University of Minnesota

27. Hunt, Sarah. Understanding the Glomerular Mesangium through computational modeling.

Degree: PhD, Biomedical Engineering, 2017, University of Minnesota

URL: http://hdl.handle.net/11299/190556

► The mesangium plays a prominent role in maintaining glomerular homeostasis by contributing to hemodynamic regulation, macromolecule clearance, and immune monitoring. However, it is also intimately… (more)

Subjects/Keywords: computational modeling; counter-current; glomerulus; mesangium

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APA (6^th Edition):

Hunt, S. (2017). Understanding the Glomerular Mesangium through computational modeling. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/190556

Chicago Manual of Style (16^th Edition):

Hunt, Sarah. “Understanding the Glomerular Mesangium through computational modeling.” 2017. Doctoral Dissertation, University of Minnesota. Accessed September 22, 2019. http://hdl.handle.net/11299/190556.

MLA Handbook (7^th Edition):

Hunt, Sarah. “Understanding the Glomerular Mesangium through computational modeling.” 2017. Web. 22 Sep 2019.

Vancouver:

Hunt S. Understanding the Glomerular Mesangium through computational modeling. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/11299/190556.

Council of Science Editors:

Hunt S. Understanding the Glomerular Mesangium through computational modeling. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/190556

University of Illinois – Urbana-Champaign

28. Kunal, Kumar. Computational modeling of intrinsic dissipation in nano-structure.

Degree: PhD, Theoretical & Applied Mechans, 2016, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/90707

► In this work, using computational modeling, we study the different mechanisms of intrinsic dissipation in nano-electro mechanical systems (NEMS). We, first, use molecular dynamics (MD)… (more)

▼ In this work, using computational modeling, we study the different mechanisms of intrinsic dissipation in nano-electro mechanical systems (NEMS). We, first, use molecular dynamics (MD) simulation and gain an understanding of the underlying loss mechanisms. Using insights from the MD simulation, a multi-scale method to model intrinsic damping is developed. The high frequency vibration in NEMS have important applications. A few examples include the sensing of atomic mass, detection of biological molecules and observation of quantum effects in macroscopic objects. For all these potential applications, dissipation plays a limiting role. While a number of experimental and theoretical studies have been performed, the individual role of different mechanisms remains unclear. In this work, we attempt to isolate and understand the surface and size effect on some of the intrinsic mechanisms. We, first, consider the case of the Akhiezer damping. The Akhiezer dynamics is expected to play an important role in nano-resonators with frequencies in the GHz range. Using a judiciously devised MD set-up, we isolate Akhiezer dynamics. We show that the surfaces aid in reducing the dissipation rate through increasing the rate of thermalization of the phonons. We, next, study damping under the flexure mode of operation. A comparative analysis with the stretching mode shows that the flexure mode is less dissipative. A reduced order model is considered to understand this novel behavior. We, also, investigate the role of tension on the Q factor, a measure of the inverse of dissipation rate. From these studies, we conclude that Akhiezer dynamics plays a dominant role in nano-resonators. We, then, develop a quasi-harmonic based multi-scale method to model Akhiezer damping. A stress component, that characterizes the non-equilibrium phonon population, is derived. We obtain constitutive relation that governs the time evolution of the non-equilibrium stress. Different methods to parametrize the constitutive relation are discussed. Using the proposed formulation, we compute the dissipation rate for different cases. The results are compared with those obtained using MD. Next, we use the Boltzmann transport equation and investigate the Q factor due to the thermo-elastic dissipation (TED). The Q factor obtained shows deviations from the classical theory of TED. Correction to the classical formula, for the case of longitudinal modes, is provided. We, then, study damping is low dimensional structure. We first consider the case of two dimensional graphene sheet and under in-plane stretching. We show that the coupling between the in-plane and the out-of-plane motions plays an important role in the loss of mechanical energy. Further, a hysteresis behavior in the out-of-plane dynamics is observed. Next, we investigate the stretching motion of graphene nano-ribbon. A normal mode Langevin dynamics is devised to understand the results from the MD simulation. Advisors/Committee Members: Aluru, Narayana R (advisor), Aluru, Narayana R (Committee Chair), Saif, M. Taher (committee member), Sinha, Sanjiv (committee member), Ertekin, Elif (committee member).

Subjects/Keywords: Dissipation; Computational Modeling; Molecular Dynamics; Multi-Scale

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kunal, K. (2016). Computational modeling of intrinsic dissipation in nano-structure. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/90707

Chicago Manual of Style (16^th Edition):

Kunal, Kumar. “Computational modeling of intrinsic dissipation in nano-structure.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed September 22, 2019. http://hdl.handle.net/2142/90707.

MLA Handbook (7^th Edition):

Kunal, Kumar. “Computational modeling of intrinsic dissipation in nano-structure.” 2016. Web. 22 Sep 2019.

Vancouver:

Kunal K. Computational modeling of intrinsic dissipation in nano-structure. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/2142/90707.

Council of Science Editors:

Kunal K. Computational modeling of intrinsic dissipation in nano-structure. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/90707

University of Missouri – Columbia

29. Pendyam, Sandeep. Computational models of neuronal fear and addiction circuits.

Degree: 2011, University of Missouri – Columbia

URL: http://hdl.handle.net/10355/14516

► [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Computational Neuroscience provides tools to abstract and generalize principles of neuronal functions using mathematics, with… (more)

Subjects/Keywords: neuronal functions; subcircuits; computational modeling; anxiety disorder

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APA (6^th Edition):

Pendyam, S. (2011). Computational models of neuronal fear and addiction circuits. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/14516

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pendyam, Sandeep. “Computational models of neuronal fear and addiction circuits.” 2011. Thesis, University of Missouri – Columbia. Accessed September 22, 2019. http://hdl.handle.net/10355/14516.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pendyam, Sandeep. “Computational models of neuronal fear and addiction circuits.” 2011. Web. 22 Sep 2019.

Vancouver:

Pendyam S. Computational models of neuronal fear and addiction circuits. [Internet] [Thesis]. University of Missouri – Columbia; 2011. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10355/14516.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pendyam S. Computational models of neuronal fear and addiction circuits. [Thesis]. University of Missouri – Columbia; 2011. Available from: http://hdl.handle.net/10355/14516

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Rice University

30. Huang, Bin. Decoding biological gene regulatory networks by quantitative modeling.

Degree: PhD, Natural Sciences, 2017, Rice University

URL: http://hdl.handle.net/1911/96072

► Gene regulatory network is essential to regulate the biological functions of cells. With the rapid development of “omics” technologies, the network can be inferred for… (more)

▼ Gene regulatory network is essential to regulate the biological functions of cells. With the rapid development of “omics” technologies, the network can be inferred for a certain biological function. However, it still remains a challenge to understand the complex network at a systematic level. In this thesis, we utilized quantitative modeling approaches to study the nonlinear dynamics and the design principles of these biological gene regulatory networks. We aim to explain the existing experimental observations with the model, and further propose reasonable hypothesis for future experimental designs. More importantly, the understanding of the circuit’s regulatory mechanism would benefit the design of a de novo gene circuit for a new biological function. We first studied the plasticity of cell migration phenotypes during cancer metastasis, which contains two key cellular plasticity mechanisms - epithelial-tomesenchymal transition (EMT) and mesenchymal-to-amoeboid transition (MAT). In this study, we quantitatively modeled the core Rac1/RhoA gene regulatory circuit for MAT and later connected it with the core regulatory circuit for EMT. We found four different stable states, consistent with the amoeboid (A), mesenchymal (M), the hybrid amoeboid/mesenchymal (A/M), and the hybrid epithelial/mesenchymal (E/M) phenotypes that are observed in the experiment. We also explored the effects of microRNAs and EMT-inducing signals like Hepatocyte Growth Factor (HGF), and provided a new insight for the transitions among these phenotypes. To improve the traditional modeling approaches, we developed a new computational modeling method called Random Circuit Perturbation (RACIPE) to explore the dynamic behavior of gene regulatory circuits without the requirement of detailed kinetic parameters. We applied RACIPE on several gene circuits, and found the existence of robust gene expression patterns even though the model parameters are wildly perturbed. We also showed the powerful aspect of RACIPE to decipher the operating principles of the circuits. This kind of quantitative models not only works for gene regulatory network, but also is capable to be extended to study the cell-cell interactions among cancer and immune cells. The results shown the co-occurrence of three cancer states: low risk cancer with intermediate immunity (L), intermediate risk cancer with high immunity (I) and high risk cancer with low immunity state (H). We further used the model to assess the different combinations of cancer therapies. Advisors/Committee Members: Onuchic, Jose (advisor).

Subjects/Keywords: Computational biology; System biology; Gene network; Modeling

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APA (6^th Edition):

Huang, B. (2017). Decoding biological gene regulatory networks by quantitative modeling. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/96072

Chicago Manual of Style (16^th Edition):

Huang, Bin. “Decoding biological gene regulatory networks by quantitative modeling.” 2017. Doctoral Dissertation, Rice University. Accessed September 22, 2019. http://hdl.handle.net/1911/96072.

MLA Handbook (7^th Edition):

Huang, Bin. “Decoding biological gene regulatory networks by quantitative modeling.” 2017. Web. 22 Sep 2019.

Vancouver:

Huang B. Decoding biological gene regulatory networks by quantitative modeling. [Internet] [Doctoral dissertation]. Rice University; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1911/96072.

Council of Science Editors:

Huang B. Decoding biological gene regulatory networks by quantitative modeling. [Doctoral Dissertation]. Rice University; 2017. Available from: http://hdl.handle.net/1911/96072

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