DENALI IN A BOX: ANALOG EXPERIMENTS MODELED AFTER A NATURAL SETTING PROVIDE INSIGHT ON GENTLE RESTRAINING BEND DEFORMATION

The Mount McKinley restraining bend (MMRB) creates an ~18° left-step in the arcuate surface trace of the dextral Denali Fault in south-central Alaska. Despite being a large, crustal-scale fault, little is understood about the controls on deformation within the MMRB. Similarities between previous wet kaolin analog modeling and the MMRB suggest that the first-order deformation patterns may derive from similar mechanisms. We compare uplift patterns, localization of deformation, formation of new faults, and displacement fields from the analog model and the natural setting to assess the influence of different variables on the overall system. Despite strong rheological heterogeneity in the MMRB, this natural setting exhibits the same distribution of deformation across the restraining bend as the homogeneous analog model suggesting this first-order deformation patterns is independent of upper crustal heterogeneity. The active thrust faults of the MMRB are purely dip-slip, whereas the thrust faults formed in the model exhibit oblique slip. Conventional understanding suggests migrating restraining bends cannot produce high topography; we conclude that with a specific combination of geometry, slip rate, and migration rate, high topography is capable of forming within a migrating system

A treatment of stereochemistry in computer aided organic synthesis

This thesis describes the author’s contributions to a new stereochemical processing module constructed for the ARChem retrosynthesis program. The purpose of the module is to add the ability to perform enantioselective and diastereoselective retrosynthetic disconnections and generate appropriate precursor molecules. The module uses evidence based rules generated from a large database of literature reactions. Chapter 1 provides an introduction and critical review of the published body of work for computer aided synthesis design. The role of computer perception of key structural features (rings, functions groups etc.) and the construction and use of reaction transforms for generating precursors is discussed. Emphasis is also given to the application of strategies in retrosynthetic analysis. The availability of large reaction databases has enabled a new generation of retrosynthesis design programs to be developed that use automatically generated transforms assembled from published reactions. A brief description of the transform generation method employed by ARChem is given. Chapter 2 describes the algorithms devised by the author for handling the computer recognition and representation of the stereochemical features found in molecule and reaction scheme diagrams. The approach is generalised and uses flexible recognition patterns to transform information found in chemical diagrams into concise stereo descriptors for computer processing. An algorithm for efficiently comparing and classifying pairs of stereo descriptors is described. This algorithm is central for solving the stereochemical constraints in a variety of substructure matching problems addressed in chapter 3. The concise representation of reactions and transform rules as hyperstructure graphs is described. Chapter 3 is concerned with the efficient and reliable detection of stereochemical symmetry in both molecules, reactions and rules. A novel symmetry perception algorithm, based on a constraints satisfaction problem (CSP) solver, is described. The use of a CSP solver to implement an isomorph‐free matching algorithm for stereochemical substructure matching is detailed. The prime function of this algorithm is to seek out unique retron locations in target molecules and then to generate precursor molecules without duplications due to symmetry. Novel algorithms for classifying asymmetric, pseudo‐asymmetric and symmetric stereocentres; meso, centro, and C2 symmetric molecules; and the stereotopicity of trigonal (sp2) centres are described. Chapter 4 introduces and formalises the annotated structural language used to create both retrosynthetic rules and the patterns used for functional group recognition. A novel functional group recognition package is described along with its use to detect important electronic features such as electron‐withdrawing or donating groups and leaving groups. The functional groups and electronic features are used as constraints in retron rules to improve transform relevance. Chapter 5 details the approach taken to design detailed stereoselective and substrate controlled transforms from organised hierarchies of rules. The rules employ a rich set of constraints annotations that concisely describe the keying retrons. The application of the transforms for collating evidence based scoring parameters from published reaction examples is described. A survey of available reaction databases and the techniques for mining stereoselective reactions is demonstrated. A data mining tool was developed for finding the best reputable stereoselective reaction types for coding as transforms. For various reasons it was not possible during the research period to fully integrate this work with the ARChem program. Instead, Chapter 6 introduces a novel one‐step retrosynthesis module to test the developed transforms. The retrosynthesis algorithms use the organisation of the transform rule hierarchy to efficiently locate the best retron matches using all applicable stereoselective transforms. This module was tested using a small set of selected target molecules and the generated routes were ranked using a series of measured parameters including: stereocentre clearance and bond cleavage; example reputation; estimated stereoselectivity with reliability; and evidence of tolerated functional groups. In addition a method for detecting regioselectivity issues is presented. This work presents a number of algorithms using common set and graph theory operations and notations. Appendix A lists the set theory symbols and meanings. Appendix B summarises and defines the common graph theory terminology used throughout this thesis

Stereovision Combined With Particle Tracking Velocimetry Reveals Advection and Uplift Within a Restraining Bend Simulating the Denali Fault

Scaled physical experiments allow us to directly observe deformational processes that take place on time and length scales that are impossible to observe in the Earth’s crust. Successful evaluation of advection and uplift of material within a restraining bend along a strike-slip fault zone depends on capturing the evolution of strain in three dimensions. Consequently, we require deformation within the horizontal plane as well as vertical motions. While 3D digital image correlation systems can provide this information, their high costs have prompted us to develop techniques that require only two DSLR cameras and a few Matlab® toolboxes, which are available to researchers at many institutions. Matlab® plug-ins can perform particle image velocimetry (PIV), a technique used in many analog modeling studies to map the incremental displacements fields. For tracking material advection throughout experiments more suitable Matlab® plug-ins perform particle tracking velocimetry (PTV), which tracks the complete two-dimensional displacement path of individual particles. To capture uplift the Matlab®Computer Vision ToolboxTM, uses pairs of photos to capture the evolving topography of the experiment. The stereovision approach eliminates the need to stop the experiment to perform 3D laser scans, which can be problematic when working with materials that have time dependent rheology. We demonstrate how the combination of PIV, PTV, and stereovision analysis of experiments that simulate the Mount McKinley restraining bend reveal the evolution of the fault system and three-dimensional advection of material through the bend

Training face perception in developmental prosopagnosia through perceptual learning

Background: Recent work has shown that perceptual learning can improve face discrimination in subjects with acquired prosopagnosia. Objective: In this study, we administered the same program to determine if such training would improve face perception in developmental prosopagnosia.Method: We trained ten subjects with developmental prosopagnosia for several months with a program that required shape discrimination between morphed facial images, using a staircase procedure to keep training near each subject’s perceptual threshold. To promote ecological validity, training progressed from blocks of neutral faces in frontal view through increasing variations in view and expression. Five subjects did 11 weeks of a control television task before training, and the other five were re-assessed for maintenance of benefit 3 months after training. Results: Perceptual sensitivity for faces improved after training but did not improve after the control task. Improvement generalized to untrained expressions and views of these faces, and there was some evidence of transfer to new faces. Benefits were maintained over three months. Training also led to improvements on standard neuropsychological tests of short-term familiarity, and some subjects reported positive effects in daily life.Conclusion: We conclude that perceptual learning can lead to persistent improvements in face discrimination in developmental prosopagnosia. The strong generalization suggests that learning is occurring at the level of three-dimensional representations with some invariance for the dynamic effects of expression

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands