Human-chimpanzee alignment: Ortholog Exponentials and Paralog Power Laws

Genomic subsequences conserved between closely related species such as human and chimpanzee exhibit an exponential length distribution, in contrast to the algebraic length distribution observed for sequences shared between distantly related genomes. We find that the former exponential can be further decomposed into an exponential component primarily composed of orthologous sequences, and a truncated algebraic component primarily composed of paralogous sequences.Comment: Main text: 31 pages, 13 figures, 1 table; Supplementary materials: 9 pages, 9 figures, 1 tabl

Highly Mismatched GaAs(1-x)N(x) and Ge(1-x)Sn(x) Alloys Prepared by Ion Implantation and Ultrashort Annealing

Doping allows us to modify semiconductor materials for desired properties such as conductivity, bandgap, and / or lattice parameter. A small portion replacement of the highly mismatched isoelectronic dopants with the host atoms of a semiconductor can result in drastic variation of its structural, optical, and / or electronic properties. Here, the term "mismatch" describes the properties of atom size, ionicity, and / or electronegativity. This thesis presents the fabrication of two kinds of highly mismatched semiconductor alloys, i.e., Ge(1-x)Sn(x) and GaAs(1-x)N(x). The structural and optical properties of the prepared Ge(1-x)Sn(x) and GaAs(1-x)N(x) have been investigated. The results suggest an efficient above-solubility doping induced by non-equilibrium methods of ion implantation and ultrashort annealing. Pulsed laser melting promotes the regrowth of monocrystalline Ge(1-x)Sn(x), whereas flash lamp annealing brings about the formation of high quality GaAs(1-x)N(x) with room temperature photoluminescence. The bandgap modification of Ge(1-x)Sn(x) and GaAs(1-x)N(x) has been verified by optical measurements of spectroscopic ellipsometry and photoluminescence, respectively. In addition, effective defect engineering in GaAs has been achieved by flash lamp annealing, by which a quasi-temperature-stable photoluminescence at 1.3 µm has been obtained.Dotierung ermöglicht es, die Eigenschaften von Halbleitermaterialien, wie Leitfähigkeit, aber auch Bandabstand und / oder Gitterkonstanten gezielt zu verändern. Wenn ein Halbleiter mit einer kleinen Menge unterschiedliche Fremdatome dotiert wird, kann dies in einer drastischen Modifikation der strukturellen, optischen und / oder elektronischen Eigenschaften resultieren. Der Begriff "unterschiedlich" bedeutet hier die Eigenschaften von Atomgröße, Ioniztät und / oder Elektronegativität. Diese Doktorarbeit beschreibt die Herstellung von zwei Arten von stark fehlangepassten Halbleiterlegierungen: Ge(1-x)Sn(x) und GaAs(1-x)N(x). Die strukturellen und optischen Eigenschaften von Ge(1-x)Sn(x) und GaAs(1-x)N(x) wurden untersucht. Die Ergebnisse deuten auf eine effiziente Dotierung oberhalb der Löslichkeit, induziert durch die Nicht-Gleichgewichtsverfahren Ionenimplantation und Ultrakurzzeit-Ausheilung. Gepulstes Laserschmelzen ermöglicht das Nachwachsen von monokristallinem Ge(1-x)Sn(x), während die Blitzlampenausheilung in der Bildung von GaAs(1-x)N(x) hoher Qualität mit Photolumineszenz bei Raumtemperatur resultiert. Die Änderung der Bandlücke von Ge(1-x)Sn(x) und GaAs(1-x)N(x) wurde durch die optischen Methoden der spektroskopischen Ellipsometrie und Photolumineszenz verifiziert. Darüber hinaus konnte in ausgeheiltem GaAs eine quasi-temperaturstabile Photolumineszenz bei 1,3 µm beobachtet werden

THEORETICAL SOLUTION OF PILING COMPACTION AND THE INFLUENCE OF PILE-SOIL-BOUNDARY CURVE HYPOTHESIS

Research is ongoing to find theoretical solution to three-dimensional piling compaction. Considering the spacial-axis-symmetric characteristics, the boundary surface of pile-soil interaction is expressed by polynomials of different orders. First, the curve family parameter is introduced to construct the displacement and integral function. Then, the solution of pile-soil interaction is derived by combining the constitutive relation model of Duncan-Chang and the variational theory. Results of engineering computing show that the theoretical solution converges to the classical CEM and the limit equilibrium theory well at the corresponding computing area. Moreover, the effects of polynomial of different orders on the calculation results are not obvious. The conclusion in this paper can be used for reference in the derivation and application for other interaction of structure and soil problems

Variational Autoencoders for Deforming 3D Mesh Models

3D geometric contents are becoming increasingly popular. In this paper, we study the problem of analyzing deforming 3D meshes using deep neural networks. Deforming 3D meshes are flexible to represent 3D animation sequences as well as collections of objects of the same category, allowing diverse shapes with large-scale non-linear deformations. We propose a novel framework which we call mesh variational autoencoders (mesh VAE), to explore the probabilistic latent space of 3D surfaces. The framework is easy to train, and requires very few training examples. We also propose an extended model which allows flexibly adjusting the significance of different latent variables by altering the prior distribution. Extensive experiments demonstrate that our general framework is able to learn a reasonable representation for a collection of deformable shapes, and produce competitive results for a variety of applications, including shape generation, shape interpolation, shape space embedding and shape exploration, outperforming state-of-the-art methods.Comment: CVPR 201

E-BLOW: E-Beam Lithography Overlapping aware Stencil Planning for MCC System

Electron beam lithography (EBL) is a promising maskless solution for the technology beyond 14nm logic node. To overcome its throughput limitation, recently the traditional EBL system is extended into MCC system. %to further improve the throughput. In this paper, we present E-BLOW, a tool to solve the overlapping aware stencil planning (OSP) problems in MCC system. E-BLOW is integrated with several novel speedup techniques, i.e., successive relaxation, dynamic programming and KD-Tree based clustering, to achieve a good performance in terms of runtime and solution quality. Experimental results show that, compared with previous works, E-BLOW demonstrates better performance for both conventional EBL system and MCC system

Mesh-based Autoencoders for Localized Deformation Component Analysis

Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing. Several methods have recently been developed, with an aim to extract intuitive and interpretable deformation components. However, these techniques suffer from fundamental limitations especially for meshes with noise or large-scale deformations, and may not always be able to identify important deformation components. In this paper we propose a novel mesh-based autoencoder architecture that is able to cope with meshes with irregular topology. We introduce sparse regularization in this framework, which along with convolutional operations, helps localize deformations. Our framework is capable of extracting localized deformation components from mesh data sets with large-scale deformations and is robust to noise. It also provides a nonlinear approach to reconstruction of meshes using the extracted basis, which is more effective than the current linear combination approach. Extensive experiments show that our method outperforms state-of-the-art methods in both qualitative and quantitative evaluations