Data-driven shape analysis and processing

Data-driven methods serve an increasingly important role in discovering geometric, structural, and semantic relationships between shapes. In contrast to traditional approaches that process shapes in isolation of each other, data-driven methods aggregate information from 3D model collections to improve the analysis, modeling and editing of shapes. Through reviewing the literature, we provide an overview of the main concepts and components of these methods, as well as discuss their application to classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing

Evolutionary Inference from Admixed Genomes: Implications of Hybridization for Biodiversity Dynamics and Conservation

Hybridization as a macroevolutionary mechanism has been historically underappreciated among vertebrate biologists. Yet, the advent and subsequent proliferation of next-generation sequencing methods has increasingly shown hybridization to be a pervasive agent influencing evolution in many branches of the Tree of Life (to include ancestral hominids). Despite this, the dynamics of hybridization with regards to speciation and extinction remain poorly understood. To this end, I here examine the role of hybridization in the context of historical divergence and contemporary decline of several threatened and endangered North American taxa, with the goal to illuminate implications of hybridization for promoting—or impeding—population persistence in a shifting adaptive landscape. Chapter I employed population genomic approaches to examine potential effects of habitat modification on species boundary stability in co-occurring endemic fishes of the Colorado River basin (Gila robusta and G. cypha). Results showed how one potential outcome of hybridization might drive species decline: via a breakdown in selection against interspecific heterozygotes and subsequent genetic erosion of parental species. Chapter II explored long-term contributions of hybridization in an evolutionarily recent species complex (Gila) using a combination of phylogenomic and phylogeographic modelling approaches. Massively parallel computational methods were developed (and so deployed) to categorize sources of phylogenetic discordance as drivers of systematic bias among a panel of species tree inference algorithms. Contrary to past evidence, we found that hypotheses of hybrid origin (excluding one notable example) were instead explained by gene-tree discordance driven by a rapid radiation. Chapter III examined patterns of local ancestry in the endangered red wolf genome (Canis rufus) – a controversial taxon of a long-standing debate about the origin of the species. Analyses show how pervasive autosomal introgression served to mask signatures of prior isolation—in turn misleading analyses that led the species to be interpreted as of recent hybrid origin. Analyses also showed how recombination interacts with selection to create a non-random, structured genomic landscape of ancestries with, in the case of the red wolf, the ‘original’ species tree being retained only in low-recombination ‘refugia’ of the X chromosome. The final three chapters present bioinformatic software that I developed for my dissertation research to facilitate molecular approaches and analyses presented in Chapters I–III. Chapter IV details an in-silico method for optimizing similar genomic methods as used herein (RADseq of reduced representation libraries) for other non-model organisms. Chapter V describes a method for parsing genomic datasets for elements of interest, either as a filtering mechanism for downstream analysis, or as a precursor to targeted-enrichment reduced-representation genomic sequencing. Chapter VI presents a rapid algorithm for the definition of a ‘most parsimonious’ set of recombinational breakpoints in genomic datasets, as a method promoting local ancestry analyses as utilized in Chapter III. My three case studies and accompanying software promote three trajectories in modern hybridization research: How does hybridization impact short-term population persistence? How does hybridization drive macroevolutionary trends? and How do outcomes of hybridization vary in the genome? In so doing, my research promotes a deeper understanding of the role that hybridization has and will continue to play in governing the evolutionary fates of lineages at both contemporary and historic timescales

Compressed Sensing Accelerated Magnetic Resonance Spectroscopic Imaging

abstract: Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker. However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

Robust Scalable Sorting

Sortieren ist eines der wichtigsten algorithmischen Grundlagenprobleme. Es ist daher nicht verwunderlich, dass Sortieralgorithmen in einer Vielzahl von Anwendungen benötigt werden. Diese Anwendungen werden auf den unterschiedlichsten Geräten ausgeführt -- angefangen bei Smartphones mit leistungseffizienten Multi-Core-Prozessoren bis hin zu Supercomputern mit Tausenden von Maschinen, die über ein Hochleistungsnetzwerk miteinander verbunden sind. Spätestens seitdem die Single-Core-Leistung nicht mehr signifikant steigt, sind parallele Anwendungen in unserem Alltag nicht mehr wegzudenken. Daher sind effiziente und skalierbare Algorithmen essentiell, um diese immense Verfügbarkeit von (paralleler) Rechenleistung auszunutzen. Diese Arbeit befasst sich damit, wie sequentielle und parallele Sortieralgorithmen auf möglichst robuste Art maximale Leistung erzielen können. Dabei betrachten wir einen großen Parameterbereich von Eingabegrößen, Eingabeverteilungen, Maschinen sowie Datentypen. Im ersten Teil dieser Arbeit untersuchen wir sowohl sequentielles Sortieren als auch paralleles Sortieren auf Shared-Memory-Maschinen. Wir präsentieren In-place Parallel Super Scalar Samplesort (IPS⁴o), einen neuen vergleichsbasierten Algorithmus, der mit beschränkt viel Zusatzspeicher auskommt (die sogenannte „in-place” Eigenschaft). Eine wesentliche Erkenntnis ist, dass unsere in-place-Technik die Sortiergeschwindigkeit von IPS⁴o im Vergleich zu ähnlichen Algorithmen ohne in-place-Eigenschaft verbessert. Bisher wurde die Eigenschaft, mit beschränkt viel Zusatzspeicher auszukommen, eher mit Leistungseinbußen verbunden. IPS⁴o ist außerdem cache-effizient und führt $O(n/t\log n)$ Arbeitsschritte pro Thread aus, um ein Array der Größe $n$ mit $t$ Threads zu sortieren. Zusätzlich berücksichtigt IPS⁴o Speicherlokalität, nutzt einen Entscheidungsbaum ohne Sprungvorhersagen und verwendet spezielle Partitionen für Elemente mit gleichem Schlüssel. Für den Spezialfall, dass ausschließlich ganzzahlige Schlüssel sortiert werden sollen, haben wir das algorithmische Konzept von IPS⁴o wiederverwendet, um In-place Parallel Super Scalar Radix Sort (IPS²Ra) zu implementieren. Wir bestätigen die Performance unserer Algorithmen in einer umfangreichen experimentellen Studie mit 21 State-of-the-Art-Sortieralgorithmen, sechs Datentypen, zehn Eingabeverteilungen, vier Maschinen, vier Speicherzuordnungsstrategien und Eingabegrößen, die über sieben Größenordnungen variieren. Einerseits zeigt die Studie die robuste Leistungsfähigkeit unserer Algorithmen. Andererseits deckt sie auf, dass viele konkurrierende Algorithmen Performance-Probleme haben: Mit IPS⁴o erhalten wir einen robusten vergleichsbasierten Sortieralgorithmus, der andere parallele in-place vergleichsbasierte Sortieralgorithmen fast um den Faktor drei übertrifft. In der überwiegenden Mehrheit der Fälle ist IPS⁴o der schnellste vergleichsbasierte Algorithmus. Dabei ist es nicht von Bedeutung, ob wir IPS⁴o mit Algorithmen vergleichen, die mit beschränkt viel Zusatzspeicher auskommen, Zusatzspeicher in der Größenordnung der Eingabe benötigen, und parallel oder sequentiell ausgeführt werden. IPS⁴o übertrifft in vielen Fällen sogar konkurrierende Implementierungen von Integer-Sortieralgorithmen. Die verbleibenden Fälle umfassen hauptsächlich gleichmäßig verteilte Eingaben und Eingaben mit Schlüsseln, die nur wenige Bits enthalten. Diese Eingaben sind in der Regel „einfach” für Integer-Sortieralgorithmen. Unser Integer-Sorter IPS²Ra übertrifft andere Integer-Sortieralgorithmen für diese Eingaben in der überwiegenden Mehrheit der Fälle. Ausnahmen sind einige sehr kleine Eingaben, für die die meisten Algorithmen sehr ineffizient sind. Allerdings sind Algorithmen, die auf diese Eingabegrößen abzielen, in der Regel für alle anderen Eingaben deutlich langsamer. Im zweiten Teil dieser Arbeit untersuchen wir skalierbare Sortieralgorithmen für verteilte Systeme, welche robust in Hinblick auf die Eingabegröße, häufig vorkommende Sortierschlüssel, die Verteilung der Sortierschlüssel auf die Prozessoren und die Anzahl an Prozessoren sind. Das Resultat unserer Arbeit sind im Wesentlichen vier robuste skalierbare Sortieralgorithmen, mit denen wir den gesamten Bereich an Eingabegrößen abdecken können. Drei dieser vier Algorithmen sind neue, schnelle Algorithmen, welche so implementiert sind, dass sie nur einen geringen Zusatzaufwand benötigen und gleichzeitig unabhängig von „schwierigen” Eingaben robust skalieren. Es handelt sich z.B. um „schwierige” Eingaben, wenn viele gleiche Elemente vorkommen oder die Eingabeelemente in Hinblick auf ihre Sortierschlüssel ungünstig auf die Prozessoren verteilt sind. Bisherige Algorithmen für mittlere und größere Eingabegrößen weisen ein unzumutbar großes Kommunikationsvolumen auf oder tauschen unverhältnismäßig oft Nachrichten aus. Für diese Eingabegrößen beschreiben wir eine robuste, mehrstufige Verallgemeinerung von Samplesort, die einen brauchbaren Kompromiss zwischen dem Kommunikationsvolumen und der Anzahl ausgetauschter Nachrichten darstellt. Wir überwinden diese bisher unvereinbaren Ziele mittels einer skalierbaren approximativen Splitterauswahl sowie eines neuen Datenumverteilungsalgorithmus. Als eine Alternative stellen wir eine Verallgemeinerung von Mergesort vor, welche den Vorteil von perfekt ausbalancierter Ausgabe hat. Für kleine Eingaben entwerfen wir eine Variante von Quicksort. Mit wenig Zusatzaufwand vermeidet sie das Problem ungünstiger Elementverteilungen und häufig vorkommender Sortierschlüssel, indem sie schnell qualitativ hochwertige Splitter auswählt, die Elemente zufällig den Prozessoren zuweist und einer Duplikat-Behandlung unterzieht. Bisherige praktische Ansätze mit polylogarithmischer Latenz haben entweder einen logarithmischen Faktor mehr Kommunikationsvolumen oder berücksichtigen nur gleichverteilte Eingaben ohne mehrfach vorkommende Sortierschlüssel. Für sehr kleine Eingaben schlagen wir einen einfachen sowie schnellen, jedoch arbeitsineffizienten Algorithmus mit logarithmischer Latenzzeit vor. Für diese Eingaben sind bisherige effiziente Ansätze nur theoretische Algorithmen, die meist unverhältnismäßig große konstante Faktoren haben. Für die kleinsten Eingaben empfehlen wir die Daten zu sortieren, während sie an einen einzelnen Prozessor geschickt werden. Ein wichtiger Beitrag dieser Arbeit zu der praktischen Seite von Algorithm Engineering ist die Kommunikationsbibliothek RangeBasedComm (RBC). Mit RBC ermöglichen wir eine effiziente Umsetzung von rekursiven Algorithmen mit sublinearer Laufzeit, indem sie skalierbare und effiziente Kommunikationsfunktionen für Teilmengen von Prozessoren bereitstellt. Zuletzt präsentieren wir eine umfangreiche experimentelle Studie auf zwei Supercomputern mit bis zu 262144 Prozessorkernen, elf Algorithmen, zehn Eingabeverteilungen und Eingabegrößen variierend über neun Größenordnungen. Mit Ausnahme von den größten Eingabegrößen ist diese Arbeit die einzige, die überhaupt Sortierexperimente auf Maschinen dieser Größe durchführt. Die RBC-Bibliothek beschleunigt die Algorithmen teilweise drastisch – einen konkurrierenden Algorithmus sogar um mehr als zwei Größenordnungen. Die Studie legt dar, dass unsere Algorithmen robust sind und gleichzeitig konkurrierende Implementierungen leistungsmäßig deutlich übertreffen. Die Konkurrenten, die man normalerweise betrachtet hätte, stürzen bei „schwierigen” Eingaben sogar ab

New Techniques for Direct Methods in X-Ray Crystallography

The principal aim of this thesis is the further development of the methods of solution of crystal structures using the techniques of direct methods. All the research undertaken has used either a Bayesian approach to the statistics or has used the more specific maximum entropy technique. Much of the work results in an implementation to the MITHRIL program which is then used as part of the testing strategy, and is mentioned throughout this thesis. The first chapter is an introduction to direct methods to give the reader an overview in the techniques which will be expanded upon later in the thesis. In addition to explaining the major techniques used in the field a section on the maximum entropy method is included along with a brief explanation of the function of the maximum entropy program MICE. The second chapter details the maximum entropy method and presents the results from the entropy maximisation of maps produced using phase sets generated from random starting phases by the SAYTAN program. A small protein Avian Pancreatic Polypeptide (App) was used as the test structure. No conventional figure of merit was able to discriminate between the phase sets yet by applying standard maximum entropy procedures using the MICE program and examining the log likelihood gain (LLO) the correct phase sets were identified. The third chapter details a Bayesian method of obtaining temperature factors, scale factors and estimated standard deviations on these figures for use in the normalisation of structure factors to normalised structure factors. A full derivation of the new formula using Bayesian methods and the Wilson statistics is provided along with details of the implementation into the MITHRIL90 program. A full set of test results based on selections of x-ray diffraction data for seventeen test structures is given. The results show that this is a perfectly adequate method that provides reasonable standard deviations of the normalised structure factors. The greatest advantage of this new theory is that it has the ability to be extended to use Bayesian priors to generate better normalisation equations. The fourth chapter details a likelihood based figure of merit, LOGLIK, designed to compare observed and calculated E-magnitudes for the reflections that are not involved in the direct methods phasing procedure. This gives a measure of the internal consistency of the three phase invariants used in phasing. A derivation of the formula that yields the calculated E-magnitudes is given. The results are given for twenty two test structures and correlations between LOGLIK and conventional figures of merit. The results show that while LOGLIK contains new information it has no new advantage over conventional figures of merit, and indeed can only be used for ranking phase sets into a preferred order not the determination of correctness. Also included in the thesis is an appendix that contains the manual for the use of the MITHRIL90 program, that incorporates the new normalisation method and the LOGLIK figure of merit

Inclusion of Geometrically Nonlinear Aeroelastic Effects into Gradient-Based Aircraft Optimization

While aircraft have largely featured flexible wings for decades, more recently, aircraft structures have rapidly become more flexible. The pursuit of longer ranges and higher efficiency through higher aspect ratio wings, as well as the introduction of modern, light-weight materials has yielded moderately and very flexible aircraft configurations. Past accidents, such as the loss of the Helios High Altitude Long Endurance (HALE) aircraft have highlighted the limitations of linear analysis methods and demonstrated the peril of neglecting nonlinear effects when designing such aircraft. In particular, accounting for geometrical nonlinearities in flutter analyses become necessary in aircraft optimization, including transport aircraft, or future aircraft may require costly modifications late in the design process to fulfill certification requirements. As a result, there is a need to account for geometrical nonlinearities earlier in the design process and integrate these analyses directly into the multi-disciplinary design optimization (MDO) problems. This thesis investigates geometrically nonlinear flutter problems and how these should be integrated into aircraft MDO problems. First, flutter problems with and without geometrical nonlinearities are discussed and a unifying interpretation is presented. Furthermore, methods for interpreting nonlinear flutter problems are proposed and differences between linear and nonlinear flutter problem interpretation are discussed. Next, a flutter constraint formulation which accounts for geometrically nonlinear effects using beam-based analyses is presented. The resulting constraint uses a Kreisselmeiser-Steinhauser aggregation function to yield a scalar constraint from flight envelope flutter damping values. While the constraint enforces feasibility over the entire flight envelope, how the flight envelope is sampled largely determines the flutter constraint’s accuracy. To this end, a constrained Maximin approach, which is applicable for non-hypercube spaces, is used to sample the flight envelope and obtain a low-discrepancy sample set. The flutter constraint is then implemented using a beam-based geometrically nonlinear aeroelastic simulation code, UM/NAST. As gradient-based optimization methods are used in MDO due to the large number of design variables in aircraft design problems, the flutter constraint requires the recovery of flutter damping sensitivities. These are obtained by applying algorithmic differentiation (AD) to the UM/NAST code base. This enables the recovery of gradients for any solution type (static, modal, dynamic, and flutter/stability) with respect to any local design variable available within UM/NAST. The performance of the gradient prediction is studied and a hybrid primal-AD scheme is developed to obtain the coupled nonlinear aeroelastic sensitivities. After verifying the accuracy and performance of the gradient evaluation, the flutter constraint was implemented in a sample optimization problem. Finally, a roadmap for including the beam-based flutter constraint within an aircraft design problem is presented using analyses of varying fidelity. To this end, analyses of appropriate fidelity are used depending on the output of interest. While a shell-based FEM model can recover stress distributions, and is therefore well-suited for strength constraints, they are ill-suited for geometrically nonlinear flutter constraints due to their computational cost. Analyses are presented for a high aspect ratio transport aircraft configuration to illustrate the proposed approach and highlight the necessity for the inclusion of a geometrically nonlinear flutter constraint.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163259/1/clupp_1.pd

Phylogenetic Divergence Time, Algorithms for Improved Accuracy and Performance

The inference of species divergence time is a key step in the study of phylogenetics. Methods have been available for the last ten years to perform the inference, but, there are two significant problems with these methods. First, the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. A study of 349 taxa was estimated to require over 9 months of processing time. Second, the accuracy of the inference process is subject to bias and variance in the specification of model parameters that is not completely understood. These parameters include both the topology of the phylogenetic tree and, more importantly for our purposes, the set of fossils used to calibrate the tree. In this work, we present new algorithms and methods to improve the performance of the divergence time process. We demonstrate a new algorithm for the computation of phylogenetic likelihood and experimentally illustrate a 90% improvement in likelihood computation time on the aforementioned dataset of 349 taxa with over 60,000 DNA base pairs. Additionally we show a new algorithm for the computation of the Bayesian prior on node ages that is experimentally shown to reduce the time for this computation on the 349 taxa dataset by 99%. Using our high performance methods, we present a novel new method for assessing the level of support for the ages inferred. This method utilizes a statistical jackknifing technique on the set of fossil calibrations producing a support value similar to the bootstrap used in phylogenetic inference. Finally, we present efficient methods for divergence time inference on sets of trees based on our development of subtree sharing models. We show a 60% improvement in processing times on a dataset of 567 taxa with over 10,000 DNA base pairs