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The path to high-energy electron-positron colliders: from Wideroe's betatron to Touschek's AdA and to LEP
We describe the road which led to the construction and exploitation of electron positron colliders, hightlighting how the young physics student Bruno Touschek met the Norwegian engineer Rolf Wideroe in Germany, during WWII, and collaborated in building the 15 MeV betatron, a secret project directed by Wideroe and fin...
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Lazarsfeld-Mukai Reflexive Sheaves and their Stability
Consider an ample and globally generated line bundle $L$ on a smooth projective variety $X$ of dimension $N\geq 2$ over $\mathbb{C}$. Let $D$ be a smooth divisor in the complete linear system of $L$. We construct reflexive sheaves on $X$ by an elementary transformation of a trivial bundle on $X$ along certain globall...
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Dimensionality reduction for acoustic vehicle classification with spectral embedding
We propose a method for recognizing moving vehicles, using data from roadside audio sensors. This problem has applications ranging widely, from traffic analysis to surveillance. We extract a frequency signature from the audio signal using a short-time Fourier transform, and treat each time window as an individual dat...
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Efficient Estimation of Linear Functionals of Principal Components
We study principal component analysis (PCA) for mean zero i.i.d. Gaussian observations $X_1,\dots, X_n$ in a separable Hilbert space $\mathbb{H}$ with unknown covariance operator $\Sigma.$ The complexity of the problem is characterized by its effective rank ${\bf r}(\Sigma):= \frac{{\rm tr}(\Sigma)}{\|\Sigma\|},$ whe...
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A stroll in the jungle of error bounds
The aim of this paper is to give a short overview on error bounds and to provide the first bricks of a unified theory. Inspired by the works of [8, 15, 13, 16, 10], we show indeed the centrality of the Lojasiewicz gradient inequality. For this, we review some necessary and sufficient conditions for global/local error...
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Variational obstacle avoidance problem on Riemannian manifolds
We introduce variational obstacle avoidance problems on Riemannian manifolds and derive necessary conditions for the existence of their normal extremals. The problem consists of minimizing an energy functional depending on the velocity and covariant acceleration, among a set of admissible curves, and also depending o...
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An Extension of Heron's Formula
This paper introduces an extension of Heron's formula to approximate area of cyclic n-gons where the error never exceeds $\frac{\pi}{e}-1$
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Learning Less-Overlapping Representations
In representation learning (RL), how to make the learned representations easy to interpret and less overfitted to training data are two important but challenging issues. To address these problems, we study a new type of regulariza- tion approach that encourages the supports of weight vectors in RL models to have smal...
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LDPC Code Design for Distributed Storage: Balancing Repair Bandwidth, Reliability and Storage Overhead
Distributed storage systems suffer from significant repair traffic generated due to frequent storage node failures. This paper shows that properly designed low-density parity-check (LDPC) codes can substantially reduce the amount of required block downloads for repair thanks to the sparse nature of their factor graph...
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Structural, magnetic, and electronic properties of GdTiO3 Mott insulator thin films grown by pulsed laser deposition
We report on the optimization process to synthesize epitaxial thin films of GdTiO3 on SrLaGaO4 substrates by pulsed laser deposition. Optimized films are free of impurity phases and are fully strained. They possess a magnetic Curie temperature TC = 31.8 K with a saturation magnetization of 4.2 muB per formula unit at...
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GPU-Based High-Performance Imaging for Mingantu Spectral RadioHeliograph
As a dedicated solar radio interferometer, the MingantU SpEctral RadioHeliograph (MUSER) generates massive observational data in the frequency range of 400 MHz -- 15 GHz. High-performance imaging forms a significantly important aspect of MUSER's massive data processing requirements. In this study, we implement a prac...
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Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning
We present Deep Voice 3, a fully-convolutional attention-based neural text-to-speech (TTS) system. Deep Voice 3 matches state-of-the-art neural speech synthesis systems in naturalness while training ten times faster. We scale Deep Voice 3 to data set sizes unprecedented for TTS, training on more than eight hundred ho...
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Ubenwa: Cry-based Diagnosis of Birth Asphyxia
Every year, 3 million newborns die within the first month of life. Birth asphyxia and other breathing-related conditions are a leading cause of mortality during the neonatal phase. Current diagnostic methods are too sophisticated in terms of equipment, required expertise, and general logistics. Consequently, early de...
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Fluid-Structure Interaction with the Entropic Lattice Boltzmann Method
We propose a novel fluid-structure interaction (FSI) scheme using the entropic multi-relaxation time lattice Boltzmann (KBC) model for the fluid domain in combination with a nonlinear finite element solver for the structural part. We show validity of the proposed scheme for various challenging set-ups by comparison t...
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Two provably consistent divide and conquer clustering algorithms for large networks
In this article, we advance divide-and-conquer strategies for solving the community detection problem in networks. We propose two algorithms which perform clustering on a number of small subgraphs and finally patches the results into a single clustering. The main advantage of these algorithms is that they bring down ...
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Feature-based visual odometry prior for real-time semi-dense stereo SLAM
Robust and fast motion estimation and mapping is a key prerequisite for autonomous operation of mobile robots. The goal of performing this task solely on a stereo pair of video cameras is highly demanding and bears conflicting objectives: on one hand, the motion has to be tracked fast and reliably, on the other hand,...
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Effective Description of Higher-Order Scalar-Tensor Theories
Most existing theories of dark energy and/or modified gravity, involving a scalar degree of freedom, can be conveniently described within the framework of the Effective Theory of Dark Energy, based on the unitary gauge where the scalar field is uniform. We extend this effective approach by allowing the Lagrangian in ...
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Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences
Video analytics requires operating with large amounts of data. Compressive sensing allows to reduce the number of measurements required to represent the video using the prior knowledge of sparsity of the original signal, but it imposes certain conditions on the design matrix. The Bayesian compressive sensing approach...
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Making Neural QA as Simple as Possible but not Simpler
Recent development of large-scale question answering (QA) datasets triggered a substantial amount of research into end-to-end neural architectures for QA. Increasingly complex systems have been conceived without comparison to simpler neural baseline systems that would justify their complexity. In this work, we propos...
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Finite-dimensional Gaussian approximation with linear inequality constraints
Introducing inequality constraints in Gaussian process (GP) models can lead to more realistic uncertainties in learning a great variety of real-world problems. We consider the finite-dimensional Gaussian approach from Maatouk and Bay (2017) which can satisfy inequality conditions everywhere (either boundedness, monot...
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A Generalization of Quasi-twisted Codes: Multi-twisted codes
Cyclic codes and their various generalizations, such as quasi-twisted (QT) codes, have a special place in algebraic coding theory. Among other things, many of the best-known or optimal codes have been obtained from these classes. In this work we introduce a new generalization of QT codes that we call multi-twisted (M...
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On the Successive Cancellation Decoding of Polar Codes with Arbitrary Linear Binary Kernels
A method for efficiently successive cancellation (SC) decoding of polar codes with high-dimensional linear binary kernels (HDLBK) is presented and analyzed. We devise a $l$-expressions method which can obtain simplified recursive formulas of SC decoder in likelihood ratio form for arbitrary linear binary kernels to r...
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OpenML: An R Package to Connect to the Machine Learning Platform OpenML
OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the OpenML platform and illustrate its usage in combination w...
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Discovering Latent Patterns of Urban Cultural Interactions in WeChat for Modern City Planning
Cultural activity is an inherent aspect of urban life and the success of a modern city is largely determined by its capacity to offer generous cultural entertainment to its citizens. To this end, the optimal allocation of cultural establishments and related resources across urban regions becomes of vital importance, ...
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Direct mapping of the temperature and velocity gradients in discs. Imaging the vertical CO snow line around IM Lupi
Accurate measurements of the physical structure of protoplanetary discs are critical inputs for planet formation models. These constraints are traditionally established via complex modelling of continuum and line observations. Instead, we present an empirical framework to locate the CO isotopologue emitting surfaces ...
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Learning Rates for Kernel-Based Expectile Regression
Conditional expectiles are becoming an increasingly important tool in finance as well as in other areas of applications. We analyse a support vector machine type approach for estimating conditional expectiles and establish learning rates that are minimax optimal modulo a logarithmic factor if Gaussian RBF kernels are...
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Critical role of electronic correlations in determining crystal structure of transition metal compounds
The choice that a solid system "makes" when adopting a crystal structure (stable or metastable) is ultimately governed by the interactions between electrons forming chemical bonds. By analyzing 6 prototypical binary transition-metal compounds we demonstrate here that the orbitally-selective strong $d$-electron correl...
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A Machine Learning Alternative to P-values
This paper presents an alternative approach to p-values in regression settings. This approach, whose origins can be traced to machine learning, is based on the leave-one-out bootstrap for prediction error. In machine learning this is called the out-of-bag (OOB) error. To obtain the OOB error for a model, one draws a ...
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Image Registration Techniques: A Survey
Image Registration is the process of aligning two or more images of the same scene with reference to a particular image. The images are captured from various sensors at different times and at multiple view-points. Thus to get a better picture of any change of a scene or object over a considerable period of time image...
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Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes
This work initiates a general study of learning and generalization without the i.i.d. assumption, starting from first principles. While the standard approach to statistical learning theory is based on assumptions chosen largely for their convenience (e.g., i.i.d. or stationary ergodic), in this work we are interested...
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Obstructions for three-coloring and list three-coloring $H$-free graphs
A graph is $H$-free if it has no induced subgraph isomorphic to $H$. We characterize all graphs $H$ for which there are only finitely many minimal non-three-colorable $H$-free graphs. Such a characterization was previously known only in the case when $H$ is connected. This solves a problem posed by Golovach et al. As...
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Hybrid quantum-classical modeling of quantum dot devices
The design of electrically driven quantum dot devices for quantum optical applications asks for modeling approaches combining classical device physics with quantum mechanics. We connect the well-established fields of semi-classical semiconductor transport theory and the theory of open quantum systems to meet this req...
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Efficient exploration with Double Uncertain Value Networks
This paper studies directed exploration for reinforcement learning agents by tracking uncertainty about the value of each available action. We identify two sources of uncertainty that are relevant for exploration. The first originates from limited data (parametric uncertainty), while the second originates from the di...
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Auxiliary Variables for Multi-Dirichlet Priors
Bayesian models that mix multiple Dirichlet prior parameters, called Multi-Dirichlet priors (MD) in this paper, are gaining popularity. Inferring mixing weights and parameters of mixed prior distributions seems tricky, as sums over Dirichlet parameters complicate the joint distribution of model parameters. This paper...
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Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter
We present a new matched filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar Point Spread Function (PSF) is first subtracted using a Karhunen-Loéve Image Processing (KLIP) algorithm with Angular and Spectral Differential Imaging (ADI and SDI). The KLIP-induced...
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Numerical non-LTE 3D radiative transfer using a multigrid method
3D non-LTE radiative transfer problems are computationally demanding, and this sets limits on the size of the problems that can be solved. So far Multilevel Accelerated Lambda Iteration (MALI) has been to the method of choice to perform high-resolution computations in multidimensional problems. The disadvantage of MA...
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Test Case Prioritization Techniques for Model-Based Testing: A Replicated Study
Recently, several Test Case Prioritization (TCP) techniques have been proposed to order test cases for achieving a goal during test execution, particularly, revealing faults sooner. In the Model-Based Testing (MBT) context, such techniques are usually based on heuristics related to structural elements of the model an...
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Magnetic order and interactions in ferrimagnetic Mn3Si2Te6
The magnetism in Mn$_3$Si$_2$Te$_6$ has been investigated using thermodynamic measurements, first principles calculations, neutron diffraction and diffuse neutron scattering on single crystals. These data confirm that Mn$_3$Si$_2$Te$_6$ is a ferrimagnet below a Curie temperature of $T_C$ approximately 78K. The magnet...
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On the Solution of Linear Programming Problems in the Age of Big Data
The Big Data phenomenon has spawned large-scale linear programming problems. In many cases, these problems are non-stationary. In this paper, we describe a new scalable algorithm called NSLP for solving high-dimensional, non-stationary linear programming problems on modern cluster computing systems. The algorithm con...
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Highly accurate acoustic scattering: Isogeometric Analysis coupled with local high order Farfield Expansion ABC
This work is concerned with a unique combination of high order local absorbing boundary conditions (ABC) with a general curvilinear Finite Element Method (FEM) and its implementation in Isogeometric Analysis (IGA) for time-harmonic acoustic waves. The ABC employed were recently devised by Villamizar, Acosta and Dastr...
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Deep Domain Adaptation Based Video Smoke Detection using Synthetic Smoke Images
In this paper, a deep domain adaptation based method for video smoke detection is proposed to extract a powerful feature representation of smoke. Due to the smoke image samples limited in scale and diversity for deep CNN training, we systematically produced adequate synthetic smoke images with a wide variation in the...
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NaCl crystal from salt solution with far below saturated concentration under ambient condition
Under ambient conditions, we directly observed NaCl crystals experimentally in the rGO membranes soaked in the salt solution with concentration below and far below the saturated concentration. Moreover, in most probability, the NaCl crystals show stoichiometries behavior. We attribute this unexpected crystallization ...
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Plasmonic properties of refractory titanium nitride
The development of plasmonic and metamaterial devices requires the research of high-performance materials, alternative to standard noble metals. Renewed as refractory stable compound for durable coatings, titanium nitride has been recently proposed as an efficient plasmonic material. Here, by using a first principles...
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The localization transition in SU(3) gauge theory
We study the Anderson-like localization transition in the spectrum of the Dirac operator of quenched QCD. Above the deconfining transition we determine the temperature dependence of the mobility edge separating localized and delocalized eigenmodes in the spectrum. We show that the temperature where the mobility edge ...
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Conformation Clustering of Long MD Protein Dynamics with an Adversarial Autoencoder
Recent developments in specialized computer hardware have greatly accelerated atomic level Molecular Dynamics (MD) simulations. A single GPU-attached cluster is capable of producing microsecond-length trajectories in reasonable amounts of time. Multiple protein states and a large number of microstates associated with...
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Optimal Low-Rank Dynamic Mode Decomposition
Dynamic Mode Decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of non-linear systems from experimental datasets. Recently, several attempts have extended DMD to the context of low-rank approximations. This extension is of particular interest for reduced-order modeling in various applicativ...
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Improving Community Detection by Mining Social Interactions
Social relationships can be divided into different classes based on the regularity with which they occur and the similarity among them. Thus, rare and somewhat similar relationships are random and cause noise in a social network, thus hiding the actual structure of the network and preventing an accurate analysis of i...
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The set of quantum correlations is not closed
We construct a linear system non-local game which can be played perfectly using a limit of finite-dimensional quantum strategies, but which cannot be played perfectly on any finite-dimensional Hilbert space, or even with any tensor-product strategy. In particular, this shows that the set of (tensor-product) quantum c...
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Correction to the article: Floer homology and splicing knot complements
This note corrects the mistakes in the splicing formulas of the paper "Floer homology and splicing knot complements". The mistakes are the result of the incorrect assumption that for a knot $K$ inside a homology sphere $Y$, the involution on the knot Floer homology of $K$ which corresponds to moving the basepoints by...
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Tree tribes and lower bounds for switching lemmas
We show tight upper and lower bounds for switching lemmas obtained by the action of random $p$-restrictions on boolean functions that can be expressed as decision trees in which every vertex is at a distance of at most $t$ from some leaf, also called $t$-clipped decision trees. More specifically, we show the followin...
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Gyrokinetic ion and drift kinetic electron model for electromagnetic simulation in the toroidal geometry
The kinetic effects of electrons are important to long wavelength magnetohydrodynamic(MHD)instabilities and short wavelength drift-Alfvenic instabilities responsible for turbulence transport in magnetized plasmas, since the non-adiabatic electron can interact with, modify and drive the low frequency instabilities. A ...
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Transferring Agent Behaviors from Videos via Motion GANs
A major bottleneck for developing general reinforcement learning agents is determining rewards that will yield desirable behaviors under various circumstances. We introduce a general mechanism for automatically specifying meaningful behaviors from raw pixels. In particular, we train a generative adversarial network t...
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Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications
Developing an intelligent vehicle which can perform human-like actions requires the ability to learn basic driving skills from a large amount of naturalistic driving data. The algorithms will become efficient if we could decompose the complex driving tasks into motion primitives which represent the elementary composi...
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NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks
"How much energy is consumed for an inference made by a convolutional neural network (CNN)?" With the increased popularity of CNNs deployed on the wide-spectrum of platforms (from mobile devices to workstations), the answer to this question has drawn significant attention. From lengthening battery life of mobile devi...
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The Minor Fall, the Major Lift: Inferring Emotional Valence of Musical Chords through Lyrics
We investigate the association between musical chords and lyrics by analyzing a large dataset of user-contributed guitar tablatures. Motivated by the idea that the emotional content of chords is reflected in the words used in corresponding lyrics, we analyze associations between lyrics and chord categories. We also e...
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Effective computation of $\mathrm{SO}(3)$ and $\mathrm{O}(3)$ linear representations symmetry classes
We propose a general algorithm to compute all the symmetry classes of any $\mathrm{SO}(3)$ or $\mathrm{O}(3)$ linear representation. This method relies on the introduction of a binary operator between sets of conjugacy classes of closed subgroups, called the clips. We compute explicit tables for this operation which ...
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Subextensions for co-induced modules
Using cohomological methods, we prove a criterion for the embedding of a group extension with abelian kernel into the split extension of a co-induced module. This generalises some earlier similar results. We also prove an assertion about the conjugacy of complements in split extensions of co-induced modules. Both res...
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Specht Polytopes and Specht Matroids
The generators of the classical Specht module satisfy intricate relations. We introduce the Specht matroid, which keeps track of these relations, and the Specht polytope, which also keeps track of convexity relations. We establish basic facts about the Specht polytope, for example, that the symmetric group acts trans...
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Existence theorems for the Cauchy problem of 2D nonhomogeneous incompressible non-resistive MHD equations with vacuum
In this paper, we investigate the Cauchy problem of the nonhomogeneous incompressible non-resistive MHD on $\mathbb{R}^2$ with vacuum as far field density and prove that the 2D Cauchy problem has a unique local strong solution provided that the initial density and magnetic field decay not too slow at infinity. Furthe...
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Mass Conservative and Energy Stable Finite Difference Methods for the Quasi-incompressible Navier-Stokes-Cahn-Hilliard system: Primitive Variable and Projection-Type Schemes
In this paper we describe two fully mass conservative, energy stable, finite difference methods on a staggered grid for the quasi-incompressible Navier-Stokes-Cahn-Hilliard (q-NSCH) system governing a binary incompressible fluid flow with variable density and viscosity. Both methods, namely the primitive method (fini...
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Density-equalizing maps for simply-connected open surfaces
In this paper, we are concerned with the problem of creating flattening maps of simply-connected open surfaces in $\mathbb{R}^3$. Using a natural principle of density diffusion in physics, we propose an effective algorithm for computing density-equalizing flattening maps with any prescribed density distribution. By v...
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Measuring the radius and mass of Planet Nine
Batygin and Brown (2016) have suggested the existence of a new Solar System planet supposed to be responsible for the perturbation of eccentric orbits of small outer bodies. The main challenge is now to detect and characterize this putative body. Here we investigate the principles of the determination of its physical...
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Efficient and principled score estimation with Nyström kernel exponential families
We propose a fast method with statistical guarantees for learning an exponential family density model where the natural parameter is in a reproducing kernel Hilbert space, and may be infinite-dimensional. The model is learned by fitting the derivative of the log density, the score, thus avoiding the need to compute a...
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Small presentations of model categories and Vopěnka's principle
We prove existence results for small presentations of model categories generalizing a theorem of D. Dugger from combinatorial model categories to more general model categories. Some of these results are shown under the assumption of Vopěnka's principle. Our main theorem applies in particular to cofibrantly generated ...
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Automatic Trimap Generation for Image Matting
Image matting is a longstanding problem in computational photography. Although, it has been studied for more than two decades, yet there is a challenge of developing an automatic matting algorithm which does not require any human efforts. Most of the state-of-the-art matting algorithms require human intervention in t...
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X-ray spectral properties of seven heavily obscured Seyfert 2 galaxies
We present the combined Chandra and Swift-BAT spectral analysis of seven Seyfert 2 galaxies selected from the Swift-BAT 100-month catalog. We selected nearby (z<=0.03) sources lacking of a ROSAT counterpart and never previously observed with Chandra in the 0.3-10 keV energy range, and targeted these objects with 10 k...
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Towards the LISA Backlink: Experiment design for comparing optical phase reference distribution systems
LISA is a proposed space-based laser interferometer detecting gravitational waves by measuring distances between free-floating test masses housed in three satellites in a triangular constellation with laser links in-between. Each satellite contains two optical benches that are articulated by moving optical subassembl...
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Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
Generative Adversarial Networks (GANs) have shown remarkable success as a framework for training models to produce realistic-looking data. In this work, we propose a Recurrent GAN (RGAN) and Recurrent Conditional GAN (RCGAN) to produce realistic real-valued multi-dimensional time series, with an emphasis on their app...
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Embedded eigenvalues of generalized Schrödinger operators
We provide examples of operators $T(D)+V$ with decaying potentials that have embedded eigenvalues. The decay of the potential depends on the curvature of the Fermi surfaces of constant kinetic energy $T$. We make the connection to counterexamples in Fourier restriction theory.
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Multichannel Robot Speech Recognition Database: MChRSR
In real human robot interaction (HRI) scenarios, speech recognition represents a major challenge due to robot noise, background noise and time-varying acoustic channel. This document describes the procedure used to obtain the Multichannel Robot Speech Recognition Database (MChRSR). It is composed of 12 hours of multi...
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The Algorithmic Inflection of Russian and Generation of Grammatically Correct Text
We present a deterministic algorithm for Russian inflection. This algorithm is implemented in a publicly available web-service www.passare.ru which provides functions for inflection of single words, word matching and synthesis of grammatically correct Russian text. The inflectional functions have been tested against ...
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Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures
Objective: A clinical decision support tool that automatically interprets EEGs can reduce time to diagnosis and enhance real-time applications such as ICU monitoring. Clinicians have indicated that a sensitivity of 95% with a specificity below 5% was the minimum requirement for clinical acceptance. We propose a highp...
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Implementing a Concept Network Model
The same concept can mean different things or be instantiated in different forms depending on context, suggesting a degree of flexibility within the conceptual system. We propose that a compositional network model can be used to capture and predict this flexibility. We modeled individual concepts (e.g., BANANA, BOTTL...
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Two simple observations on representations of metaplectic groups
M. Hanzer and I. Matic have proved that the genuine unitary principal series representations of the metaplectic groups are irreducible. A simple consequence of that paper is a criterion for the irreducibility of the non-unitary principal series representations of the metaplectic groups that we give in this paper.
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Spinors in Spacetime Algebra and Euclidean 4-Space
This article explores the geometric algebra of Minkowski spacetime, and its relationship to the geometric algebra of Euclidean 4-space. Both of these geometric algebras are algebraically isomorphic to the 2x2 matrix algebra over Hamilton's famous quaternions, and provide a rich geometric framework for various importa...
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Near-sphere lattices with constant nonlocal mean curvature
We are concerned with unbounded sets of $\mathbb{R}^N$ whose boundary has constant nonlocal (or fractional) mean curvature, which we call CNMC sets. This is the equation associated to critical points of the fractional perimeter functional under a volume constraint. We construct CNMC sets which are the countable union...
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Stability, convergence, and limit cycles in some human physiological processes
Mathematical models for physiological processes aid qualitative understanding of the impact of various parameters on the underlying process. We analyse two such models for human physiological processes: the Mackey-Glass and the Lasota equations, which model the change in the concentration of blood cells in the human ...
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Poisson multi-Bernoulli mixture filter: direct derivation and implementation
We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multi-target tracking with the standard point target measurements without using probability generating functionals or functional derivatives. We also establish the connection with the \delta-generalised labelled multi-Bernoulli (\delta-G...
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Surface magnetism in a chiral d-wave superconductor with hexagonal symmetry
Surface properties are examined in a chiral d-wave superconductor with hexagonal symmetry, whose one-body Hamiltonian possesses the intrinsic spin-orbit coupling identical to the one characterizing the topological nature of the Kane-Mele honeycomb insulator. In the normal state spin-orbit coupling gives rise to spont...
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Penetrating a Social Network: The Follow-back Problem
Modern threats have emerged from the prevalence of social networks. Hostile actors, such as extremist groups or foreign governments, utilize these networks to run propaganda campaigns with different aims. For extremists, these campaigns are designed for recruiting new members or inciting violence. For foreign governm...
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Universality of density waves in p-doped La2CuO4 and n-doped Nd2CuO4+y
The contribution of $O^{2-}$ ions to antiferromagnetism in $La_{2-x}Ae_xCuO_4$ ($Ae = Sr, Ba)$ is highly sensitive to doped holes. In contrast, the contribution of $Cu^{2+}$ ions to antiferromagnetism in $Nd_{2-x}Ce_xCuO_{4+y}$ is much less sensitive to doped electrons. The difference causes the precarious and, respe...
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The perceived assortativity of social networks: Methodological problems and solutions
Networks describe a range of social, biological and technical phenomena. An important property of a network is its degree correlation or assortativity, describing how nodes in the network associate based on their number of connections. Social networks are typically thought to be distinct from other networks in being ...
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Generalized Sheet Transition Conditions (GSTCs) for a Metascreen -- A Fishnet Metasurface
We used a multiple-scale homogenization method to derive generalized sheet transition conditions (GSTCs) for electromagnetic fields at the surface of a metascreen---a metasurface with a "fishnet" structure. These surfaces are characterized by periodically-spaced arbitrary-shaped apertures in an otherwise relatively i...
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$k^{τ,ε}$-anonymity: Towards Privacy-Preserving Publishing of Spatiotemporal Trajectory Data
Mobile network operators can track subscribers via passive or active monitoring of device locations. The recorded trajectories offer an unprecedented outlook on the activities of large user populations, which enables developing new networking solutions and services, and scaling up studies across research disciplines....
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The Taipan Galaxy Survey: Scientific Goals and Observing Strategy
Taipan is a multi-object spectroscopic galaxy survey starting in 2017 that will cover 2pi steradians over the southern sky, and obtain optical spectra for about two million galaxies out to z<0.4. Taipan will use the newly-refurbished 1.2m UK Schmidt Telescope at Siding Spring Observatory with the new TAIPAN instrumen...
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The Externalities of Exploration and How Data Diversity Helps Exploitation
Online learning algorithms, widely used to power search and content optimization on the web, must balance exploration and exploitation, potentially sacrificing the experience of current users for information that will lead to better decisions in the future. Recently, concerns have been raised about whether the proces...
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Life-span of blowup solutions to semilinear wave equation with space-dependent critical damping
This paper is concerned with the blowup phenomena for initial value problem of semilinear wave equation with critical space-dependent damping term (DW:$V$). The main result of the present paper is to give a solution of the problem and to provide a sharp estimate for lifespan for such a solution when $\frac{N}{N-1}<p\...
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Invariant submanifolds of (LCS)n-Manifolds with respect to quarter symmetric metric connection
The object of the present paper is to study invariant submanifolds of (LCS)n-manifolds with respect to quarter symmetric metric connection. It is shown that the mean curvature of an invariant submanifold of (LCS)n-manifold with respect to quarter symmetric metric connection and Levi-Civita connection are equal. An ex...
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Iterated filtering methods for Markov process epidemic models
Dynamic epidemic models have proven valuable for public health decision makers as they provide useful insights into the understanding and prevention of infectious diseases. However, inference for these types of models can be difficult because the disease spread is typically only partially observed e.g. in form of rep...
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An Algebraic-Combinatorial Proof Technique for the GM-MDS Conjecture
This paper considers the problem of designing maximum distance separable (MDS) codes over small fields with constraints on the support of their generator matrices. For any given $m\times n$ binary matrix $M$, the GM-MDS conjecture, due to Dau et al., states that if $M$ satisfies the so-called MDS condition, then for ...
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The Word Problem of $\mathbb{Z}^n$ Is a Multiple Context-Free Language
The \emph{word problem} of a group $G = \langle \Sigma \rangle$ can be defined as the set of formal words in $\Sigma^*$ that represent the identity in $G$. When viewed as formal languages, this gives a strong connection between classes of groups and classes of formal languages. For example, Anisimov showed that a gro...
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Rigorous proof of the Boltzmann-Gibbs distribution of money on connected graphs
Models in econophysics, i.e., the emerging field of statistical physics that applies the main concepts of traditional physics to economics, typically consist of large systems of economic agents who are characterized by the amount of money they have. In the simplest model, at each time step, one agent gives one dollar...
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Stochastic population dynamics in spatially extended predator-prey systems
Spatially extended population dynamics models that incorporate intrinsic noise serve as case studies for the role of fluctuations and correlations in biological systems. Including spatial structure and stochastic noise in predator-prey competition invalidates the deterministic Lotka-Volterra picture of neutral popula...
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Learning Policies for Markov Decision Processes from Data
We consider the problem of learning a policy for a Markov decision process consistent with data captured on the state-actions pairs followed by the policy. We assume that the policy belongs to a class of parameterized policies which are defined using features associated with the state-action pairs. The features are k...
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Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters
As autonomous vehicles become an every-day reality, high-accuracy pedestrian detection is of paramount practical importance. Pedestrian detection is a highly researched topic with mature methods, but most datasets focus on common scenes of people engaged in typical walking poses on sidewalks. But performance is most ...
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The sequence of open and closed prefixes of a Sturmian word
A finite word is closed if it contains a factor that occurs both as a prefix and as a suffix but does not have internal occurrences, otherwise it is open. We are interested in the {\it oc-sequence} of a word, which is the binary sequence whose $n$-th element is $0$ if the prefix of length $n$ of the word is open, or ...
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Capital Regulation under Price Impacts and Dynamic Financial Contagion
We construct a continuous time model for price-mediated contagion precipitated by a common exogenous stress to the trading book of all firms in the financial system. In this setting, firms are constrained so as to satisfy a risk-weight based capital ratio requirement. We use this model to find analytical bounds on th...
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On seaweed subalgebras and meander graphs in type D
In 2000, Dergachev and Kirillov introduced subalgebras of "seaweed type" in $\mathfrak{gl}_n$ and computed their index using certain graphs, which we call type-${\sf A}$ meander graphs. Then the subalgebras of seaweed type, or just "seaweeds", have been defined by Panyushev (2001) for arbitrary reductive Lie algebras...
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Singular Riemannian flows and characteristic numbers
Let $M$ be an even-dimensional, oriented closed manifold. We show that the restriction of a singular Riemannian flow on $M$ to a small tubular neighborhood of each connected component of its singular stratum is foliated-diffeomorphic to an isometric flow on the same neighborhood. We then prove a formula that computes...
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Transformation Models in High-Dimensions
Transformation models are a very important tool for applied statisticians and econometricians. In many applications, the dependent variable is transformed so that homogeneity or normal distribution of the error holds. In this paper, we analyze transformation models in a high-dimensional setting, where the set of pote...
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