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A two-dimensional hexagonal sheet of TiO$_2$
We report on the ab initio discovery of a novel putative ground state for quasi two-dimensional TiO$_2$ through a structural search using the minima hopping method with an artificial neural network potential. The structure is based on a honeycomb lattice and is energetically lower than the experimentally reported lep...
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Fast Markov Chain Monte Carlo Algorithms via Lie Groups
From basic considerations of the Lie group that preserves a target probability measure, we derive the Barker, Metropolis, and ensemble Markov chain Monte Carlo (MCMC) algorithms, as well as two new MCMC algorithms. The convergence properties of these new algorithms successively improve on the state of the art. We ill...
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On the (parameterized) complexity of recognizing well-covered (r,l)-graphs
An $(r, \ell)$-partition of a graph $G$ is a partition of its vertex set into $r$ independent sets and $\ell$ cliques. A graph is $(r, \ell)$ if it admits an $(r, \ell)$-partition. A graph is well-covered if every maximal independent set is also maximum. A graph is $(r,\ell)$-well-covered if it is both $(r,\ell)$ and...
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Comments on avalanche flow models based on the concept of random kinetic energy
In a series of papers, Bartelt and co-workers developed novel snow-avalanche models in which \emph{random kinetic energy} $R_K$ (a.k.a.\ granular temperature) is a key concept. The earliest models were for a single, constant density layer, using a Voellmy model but with $R_K$-dependent friction parameters. This was t...
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Continuous Implicit Authentication for Mobile Devices based on Adaptive Neuro-Fuzzy Inference System
As mobile devices have become indispensable in modern life, mobile security is becoming much more important. Traditional password or PIN-like point-of-entry security measures score low on usability and are vulnerable to brute force and other types of attacks. In order to improve mobile security, an adaptive neuro-fuz...
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Ultracold heteronuclear three-body systems: How diabaticity limits the universality of recombination into shallow dimers
The mass-imbalanced three-body recombination process that forms a shallow dimer is shown to possess a rich Efimov-Stückelberg landscape, with corresponding spectra that differ fundamentally from the homonuclear case. A semi-analytical treatment of the three-body recombination predicts an unusual spectra with intertwi...
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Variational Inference for Data-Efficient Model Learning in POMDPs
Partially observable Markov decision processes (POMDPs) are a powerful abstraction for tasks that require decision making under uncertainty, and capture a wide range of real world tasks. Today, effective planning approaches exist that generate effective strategies given black-box models of a POMDP task. Yet, an open ...
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The ANAIS-112 experiment at the Canfranc Underground Laboratory
The ANAIS experiment aims at the confirmation of the DAMA/LIBRA signal at the Canfranc Underground Laboratory (LSC). Several 12.5 kg NaI(Tl) modules produced by Alpha Spectra Inc. have been operated there during the last years in various set-ups; an outstanding light collection at the level of 15 photoelectrons per k...
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A non-ellipticity result, or the impossible taming of the logarithmic strain measure
The logarithmic strain measures $\lVert\log U\rVert^2$, where $\log U$ is the principal matrix logarithm of the stretch tensor $U=\sqrt{F^TF}$ corresponding to the deformation gradient $F$ and $\lVert\,.\,\rVert$ denotes the Frobenius matrix norm, arises naturally via the geodesic distance of $F$ to the special ortho...
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Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records
We present an interpretable neural network for predicting an important clinical outcome (1-year mortality) from multi-modal Electronic Health Record (EHR) data. Our approach builds on prior multi-modal machine learning models by now enabling visualization of how individual factors contribute to the overall outcome ri...
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Automatic Temperature Setpoint Tuning of a Thermoforming Machine using Fuzzy Terminal Iterative Learning Control
This paper presents a new way to design a Fuzzy Terminal Iterative Learning Control (TILC) to control the heater temperature setpoints of a thermoforming machine. This fuzzy TILC is based on the inverse of a fuzzy model of this machine, and is built from experimental (or simulation) data with kriging interpolation. T...
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A New Class of Integrals Involving Extended Hypergeometric Function
Our purpose in this present paper is to investigate generalized integration formulas containing the extended generalized hypergeometric function and obtained results are expressed in terms of extended hypergeometric function. Certain special cases of the main results presented here are also pointed out for the extend...
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The Special Theory of Relativity as Applied to the Born-Oppenheimer-Huang Approach
In two recent publications ( Int. J. Quant. Chem. 114, 1645 (2014) and Molec. Phys. 114, 227 (2016)) it was shown that the Born -Hwang (BH) treatment of a molecular system perturbed by an external field yields a set of decoupled vectorial Wave Equations, just like in Electromagnetism. This finding led us to declare o...
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An efficient algorithm for finding all possible input nodes for controlling complex networks
Understanding structural controllability of a complex network requires to identify a Minimum Input nodes Set (MIS) of the network. It has been suggested that finding an MIS is equivalent to computing a maximum matching of the network, where the unmatched nodes constitute an MIS. However, maximum matching of a network...
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Transformation thermal convection: Cloaking, concentrating, and camouflage
Heat can generally transfer via thermal conduction, thermal radiation, and thermal convection. All the existing theories of transformation thermotics and optics can treat thermal conduction and thermal radiation, respectively. Unfortunately, thermal convection has never been touched in transformation theories due to ...
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Tunable terahertz reflection of graphene via ionic liquid gating
We report a highly efficient tunable THz reflector in graphene. By applying a small gate voltage (up to 3 V), the reflectance of graphene is modulated from a minimum of 0.79% to a maximum of 33.4% using graphene/ionic liquid structures at room temperature, and the reflection tuning is uniform within a wide spectral r...
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Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Kernel online convex optimization (KOCO) is a framework combining the expressiveness of non-parametric kernel models with the regret guarantees of online learning. First-order KOCO methods such as functional gradient descent require only $\mathcal{O}(t)$ time and space per iteration, and, when the only information on...
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On Corecursive Algebras for Functors Preserving Coproducts
For an endofunctor $H$ on a hyper-extensive category preserving countable coproducts we describe the free corecursive algebra on $Y$ as the coproduct of the final coalgebra for $H$ and the free $H$-algebra on $Y$. As a consequence, we derive that $H$ is a cia functor, i.e., its corecursive algebras are precisely the ...
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Semisimple characters for inner froms I: GL_n(D)
The article is about the representation theory of an inner form~$G$ of a general linear group over a non-archimedean local field. We introduce semisimple characters for~$G$ whose intertwining classes describe conjecturally via Local Langlands correspondence the behavior on wild inertia. These characters also play a p...
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Quantum Memristors in Quantum Photonics
We propose a method to build quantum memristors in quantum photonic platforms. We firstly design an effective beam splitter, which is tunable in real-time, by means of a Mach-Zehnder-type array with two equal 50:50 beam splitters and a tunable retarder, which allows us to control its reflectivity. Then, we show that ...
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Spin dynamics and magnetic-field-induced polarization of excitons in ultrathin GaAs/AlAs quantum wells with indirect band gap and type-II band alignment
The exciton spin dynamics are investigated both experimentally and theoretically in two-monolayer-thick GaAs/AlAs quantum wells with an indirect band gap and a type-II band alignment. The magnetic-field-induced circular polarization of photoluminescence, $P_c$, is studied as function of the magnetic field strength an...
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Resonant inelastic x-ray scattering probes the electron-phonon coupling in the spin-liquid kappa-(BEDT-TTF)2Cu2(CN)3
Resonant inelastic x-ray scattering at the N K edge reveals clearly resolved harmonics of the anion plane vibrations in the kappa-(BEDT-TTF)2Cu2(CN)3 spin-liquid insulator. Tuning the incoming light energy at the K edge of two distinct N sites permits to excite different sets of phonon modes. Cyanide CN stretching mo...
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Thermodynamic and kinetic fragility of Freon113: the most fragile plastic crystal
We present a dynamic and thermodynamic study of the orientational glass former Freon113 (CCl2F-CClF2) in order to analyze its kinetic and thermodynamic fragilities. Freon113 displays internal molecular degrees of freedom which promote a complex energy landscape. Experimental specific heat and its microscopic origin, ...
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Semi-supervised Feature Learning For Improving Writer Identification
Data augmentation is usually used by supervised learning approaches for offline writer identification, but such approaches require extra training data and potentially lead to overfitting errors. In this study, a semi-supervised feature learning pipeline was proposed to improve the performance of writer identification...
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Error Bounds for Piecewise Smooth and Switching Regression
The paper deals with regression problems, in which the nonsmooth target is assumed to switch between different operating modes. Specifically, piecewise smooth (PWS) regression considers target functions switching deterministically via a partition of the input space, while switching regression considers arbitrary swit...
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Civil Asset Forfeiture: A Judicial Perspective
Civil Asset Forfeiture (CAF) is a longstanding and controversial legal process viewed on the one hand as a powerful tool for combating drug crimes and on the other hand as a violation of the rights of US citizens. Data used to support both sides of the controversy to date has come from government sources representing...
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Covariance-Insured Screening
Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors far greater than the sample size. In order to identify more novel biomarkers and understand biological mechanisms, it is vital to detect signals weakly associated with outcomes among ultrahigh-dimensional predict...
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Amari Functors and Dynamics in Gauge Structures
We deal with finite dimensional differentiable manifolds. All items are concerned with are differentiable as well. The class of differentiability is $C^\infty$. A metric structure in a vector bundle $E$ is a constant rank symmetric bilinear vector bundle homomorphism of $E\times E$ in the trivial bundle line bundle. ...
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An Experimental Analysis of the Power Consumption of Convolutional Neural Networks for Keyword Spotting
Nearly all previous work on small-footprint keyword spotting with neural networks quantify model footprint in terms of the number of parameters and multiply operations for a feedforward inference pass. These values are, however, proxy measures since empirical performance in actual deployments is determined by many fa...
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Formal Geometric Quantization III, Functoriality in the spin-c setting
In this paper, we prove a functorial aspect of the formal geometric quantization procedure of non-compact spin-c manifolds.
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Infinitesimal perturbation analysis for risk measures based on the Smith max-stable random field
When using risk or dependence measures based on a given underlying model, it is essential to be able to quantify the sensitivity or robustness of these measures with respect to the model parameters. In this paper, we consider an underlying model which is very popular in spatial extremes, the Smith max-stable random f...
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Modeling and Analysis of Two-Way Relay Non-Orthogonal Multiple Access Systems
A two-way relay non-orthogonal multiple access (TWR-NOMA) system is investigated, where two groups of NOMA users exchange messages with the aid of one half-duplex (HD) decode-and-forward (DF) relay. Since the signal-plus-interference-to-noise ratios (SINRs) of NOMA signals mainly depend on effective successive interf...
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Totally positive matrices and dilogarithm identities
We show that two involutions on the variety $N_n^+$ of upper triangular totally positive matrices are related, on the one hand, to the tetrahedron equation and, on the other hand, to the action of the symmetric group $S_3$ on some subvariety of $N_n^+$ and on the set of certain functions on $N_n^+$. Using these invol...
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On the zeros of random harmonic polynomials: the Weyl model
Li and Wei (2009) studied the density of zeros of Gaussian harmonic polynomials with independent Gaussian coefficients. They derived a formula for the expected number of zeros of random harmonic polynomials as well as asymptotics for the case that the polynomials are drawn from the Kostlan ensemble. In this paper we ...
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Online deforestation detection
Deforestation detection using satellite images can make an important contribution to forest management. Current approaches can be broadly divided into those that compare two images taken at similar periods of the year and those that monitor changes by using multiple images taken during the growing season. The CMFDA a...
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Analysis of Different Approaches of Parallel Block Processing for K-Means Clustering Algorithm
Distributed Computation has been a recent trend in engineering research. Parallel Computation is widely used in different areas of Data Mining, Image Processing, Simulating Models, Aerodynamics and so forth. One of the major usage of Parallel Processing is widely implemented for clustering the satellite images of siz...
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Preserving Order of Data When Validating Defect Prediction Models
[Context] The use of defect prediction models, such as classifiers, can support testing resource allocations by using data of the previous releases of the same project for predicting which software components are likely to be defective. A validation technique, hereinafter technique defines a specific way to split ava...
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Graphettes: Constant-time determination of graphlet and orbit identity including (possibly disconnected) graphlets up to size 8
Graphlets are small connected induced subgraphs of a larger graph $G$. Graphlets are now commonly used to quantify local and global topology of networks in the field. Methods exist to exhaustively enumerate all graphlets (and their orbits) in large networks as efficiently as possible using orbit counting equations. H...
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The toric sections: a simple introduction
We review, from a didactic point of view, the definition of a toric section and the different shapes it can take. We'll then discuss some properties of this curve, investigate its analogies and differences with the most renowned conic section and show how to build its general quartic equation. A curious and unexpecte...
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Quantum Field Theory, Quantum Geometry, and Quantum Algebras
We demonstrate how one can see quantization of geometry, and quantum algebraic structure in supersymmetric gauge theory.
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Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware. However, neuromorphic implementations of embedded learning at large scales that are both flexible and efficient have been hindered by a lack of a suitable algorithmic framework. As a result, the most neuro...
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Discrete Wavelet Transform Based Algorithm for Recognition of QRS Complexes
This paper proposes the application of Discrete Wavelet Transform (DWT) to detect the QRS (ECG is characterized by a recurrent wave sequence of P, QRS and T-wave) of an electrocardiogram (ECG) signal. Wavelet Transform provides localization in both time and frequency. In preprocessing stage, DWT is used to remove the...
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Multipolar moments of weak lensing signal around clusters. Weighing filaments in harmonic space
Context. Upcoming weak lensing surveys such as Euclid will provide an unprecedented opportunity to quantify the geometry and topology of the cosmic web, in particular in the vicinity of lensing clusters. Aims. Understanding the connectivity of the cosmic web with unbiased mass tracers, such as weak lensing, is of pri...
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Charge and spin transport on graphene grain boundaries in a quantizing magnetic field
We study charge and spin transport along grain boundaries in single layer graphene in the presence of a quantizing magnetic field. Transport states in a grain boundary are produced by hybridization of Landau zero modes with interfacial states. In selected energy regimes quantum Hall edge states can be deflected eithe...
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Point Cloud Movement For Fully Lagrangian Meshfree Methods
In Lagrangian meshfree methods, the underlying spatial discretization, referred to as a point cloud or a particle cloud, moves with the flow velocity. In this paper, we consider different numerical methods of performing this movement of points or particles. The movement is most commonly done by a first order method, ...
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A fast ILP-based Heuristic for the robust design of Body Wireless Sensor Networks
We consider the problem of optimally designing a body wireless sensor network, while taking into account the uncertainty of data generation of biosensors. Since the related min-max robustness Integer Linear Programming (ILP) problem can be difficult to solve even for state-of-the-art commercial optimization solvers, ...
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Strain broadening of the 1042-nm zero-phonon line of the NV- center in diamond: a promising spectroscopic tool for defect tomography
The negatively charged nitrogen-vacancy (NV-) center in diamond is a promising candidate for many quantum applications. Here, we examine the splitting and broadening of the center's infrared (IR) zero-phonon line (ZPL). We develop a model for these effects that accounts for the strain induced by photo-dependent micro...
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Learning Depthwise Separable Graph Convolution from Data Manifold
Convolution Neural Network (CNN) has gained tremendous success in computer vision tasks with its outstanding ability to capture the local latent features. Recently, there has been an increasing interest in extending convolution operations to the non-Euclidean geometry. Although various types of convolution operations...
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Candidate Hα emission and absorption line sources in the Galactic Bulge Survey
We present a catalogue of candidate H{\alpha} emission and absorption line sources and blue objects in the Galactic Bulge Survey (GBS) region. We use a point source catalogue of the GBS fields (two strips of (l x b) = (6 x 1) degrees centred at b = 1.5 above and below the Galactic centre), covering the magnitude rang...
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Timely Updates over an Erasure Channel
Using an age of information (AoI) metric, we examine the transmission of coded updates through a binary erasure channel to a monitor/receiver. We start by deriving the average status update age of an infinite incremental redundancy (IIR) system in which the transmission of a k-symbol update continuesuntil k symbols a...
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Stellar Absorption Line Analysis of Local Star-Forming Galaxies: The Relation Between Stellar Mass, Metallicity, Dust Attenuation and Star Formation Rate
We analyze the optical continuum of star-forming galaxies in SDSS by fitting stacked spectra with stellar population synthesis models to investigate the relation between stellar mass, stellar metallicity, dust attenuation and star formation rate. We fit models calculated with star formation and chemical evolution his...
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Stratification as a general variance reduction method for Markov chain Monte Carlo
The Eigenvector Method for Umbrella Sampling (EMUS) belongs to a popular class of methods in statistical mechanics which adapt the principle of stratified survey sampling to the computation of free energies. By theoretical analysis and numerical experiments, we demonstrate that EMUS is an efficient general method for...
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Adaptive MCMC via Combining Local Samplers
Markov chain Monte Carlo (MCMC) methods are widely used in machine learning. One of the major problems with MCMC is the question of how to design chains that mix fast over the whole space; in particular, how to select the parameters of an MCMC algorithm. Here we take a different approach and, similarly to parallel MC...
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GAMBIT: The Global and Modular Beyond-the-Standard-Model Inference Tool
We describe the open-source global fitting package GAMBIT: the Global And Modular Beyond-the-Standard-Model Inference Tool. GAMBIT combines extensive calculations of observables and likelihoods in particle and astroparticle physics with a hierarchical model database, advanced tools for automatically building analyses...
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Odd holes in bull-free graphs
The complexity of testing whether a graph contains an induced odd cycle of length at least five is currently unknown. In this paper we show that this can be done in polynomial time if the input graph has no induced subgraph isomorphic to the bull (a triangle with two disjoint pendant edges).
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Magnetic-Field-Induced Superconductivity in Ultrathin Pb Films with Magnetic Impurities
It is well known that external magnetic fields and magnetic moments of impurities both suppress superconductivity. Here, we demonstrate that their combined effect enhances the superconductivity of a few atomic layer thick Pb films grown on a cleaved GaAs(110) surface. A Ce-doped film, where superconductivity is total...
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Unimodal Category and the Monotonicity Conjecture
We completely characterize the unimodal category for functions $f:\mathbb R\to[0,\infty)$ using a decomposition theorem obtained by generalizing the sweeping algorithm of Baryshnikov and Ghrist. We also give a characterization of the unimodal category for functions $f:S^1\to[0,\infty)$ and provide an algorithm to com...
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Holomorphic primary fields in free CFT4 and Calabi-Yau orbifolds
Counting formulae for general primary fields in free four dimensional conformal field theories of scalars, vectors and matrices are derived. These are specialised to count primaries which obey extremality conditions defined in terms of the dimensions and left or right spins (i.e. in terms of relations between the cha...
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A Deep Generative Framework for Paraphrase Generation
Paraphrase generation is an important problem in NLP, especially in question answering, information retrieval, information extraction, conversation systems, to name a few. In this paper, we address the problem of generating paraphrases automatically. Our proposed method is based on a combination of deep generative mo...
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Stiff-response-induced instability for chemotactic bacteria and flux-limited Keller-Segel equation
Collective motion of chemotactic bacteria as E. Coli relies, at the individual level, on a continuous reorientation by runs and tumbles. It has been established that the length of run is decided by a stiff response to a temporal sensingof chemical cues along the pathway.We describe a novel mechanism for pattern forma...
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The Pfaffian state in an electron gas with small Landau level gaps
Landau level mixing plays an important role in the Pfaffian (or anti-Pfaffian) states. In ZnO the Landau level gap is essentially an order of magnitude smaller than that in a GaAs quantum well. We introduce the screened Coulomb interaction in a single Landau level to tackle that situation. Here we study the overlap o...
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Three-Dimensional Numerical Modeling of Shear Stimulation of Naturally Fractured Reservoirs
Shear dilation based hydraulic stimulations enable exploitation of geothermal energy from reservoirs with inadequate initial permeability. While contributing to enhancing the reservoir's permeability, hydraulic stimulation processes may lead to undesired seismic activity. Here, we present a three dimensional numerica...
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Decentralized DC MicroGrid Monitoring and Optimization via Primary Control Perturbations
We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to el...
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AI4AI: Quantitative Methods for Classifying Host Species from Avian Influenza DNA Sequence
Avian Influenza breakouts cause millions of dollars in damage each year globally, especially in Asian countries such as China and South Korea. The impact magnitude of a breakout directly correlates to time required to fully understand the influenza virus, particularly the interspecies pathogenicity. The procedure req...
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Constructing tame supercuspidal representations
A new approach to Jiu-Kang Yu's construction of tame supercuspidal representations of $p$-adic reductive groups is presented. Connections with the theory of cuspidal Deligne-Lusztig representations of finite groups of Lie type are also discussed.
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Cohomologies on hypercomplex manifolds
We review some cohomological aspects of complex and hypercomplex manifolds and underline the differences between both realms. Furthermore, we try to highlight the similarities between compact complex surfaces on one hand and compact hypercomplex manifolds of real dimension 8 with holonomy of the Obata connection in S...
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Automorphism groups of quandles and related groups
In this paper we study different questions concerning automorphisms of quandles. For a conjugation quandle $Q={\rm Conj}(G)$ of a group $G$ we determine several subgroups of ${\rm Aut}(Q)$ and find necessary and sufficient conditions when these subgroups coincide with the whole group ${\rm Aut}(Q)$. In particular, we...
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Forward Amortized Inference for Likelihood-Free Variational Marginalization
In this paper, we introduce a new form of amortized variational inference by using the forward KL divergence in a joint-contrastive variational loss. The resulting forward amortized variational inference is a likelihood-free method as its gradient can be sampled without bias and without requiring any evaluation of ei...
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Beyond-CMOS Device Benchmarking for Boolean and Non-Boolean Logic Applications
The latest results of benchmarking research are presented for a variety of beyond-CMOS charge- and spin-based devices. In addition to improving the device-level models, several new device proposals and a few majorly modified devices are investigated. Deep pipelining circuits are employed to boost the throughput of lo...
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Cosmology and Convention
I argue that some important elements of the current cosmological model are "conventionalist" in the sense defined by Karl Popper. These elements include dark matter and dark energy; both are auxiliary hypotheses that were invoked in response to observations that falsified the standard model as it existed at the time....
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Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering
Standard clustering algorithms usually find regular-structured clusters such as ellipsoidally- or spherically-dispersed groups, but are more challenged with groups lacking formal structure or definition. Syncytial clustering is the name that we introduce for methods that merge groups obtained from standard clustering...
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Goal-oriented Trajectories for Efficient Exploration
Exploration is a difficult challenge in reinforcement learning and even recent state-of-the art curiosity-based methods rely on the simple epsilon-greedy strategy to generate novelty. We argue that pure random walks do not succeed to properly expand the exploration area in most environments and propose to replace sin...
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Adaptive Sampling Strategies for Stochastic Optimization
In this paper, we propose a stochastic optimization method that adaptively controls the sample size used in the computation of gradient approximations. Unlike other variance reduction techniques that either require additional storage or the regular computation of full gradients, the proposed method reduces variance b...
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Explicit estimates for the distribution of numbers free of large prime factors
There is a large literature on the asymptotic distribution of numbers free of large prime factors, so-called $\textit{smooth}$ or $\textit{friable}$ numbers. But there is very little known about this distribution that is numerically explicit. In this paper we follow the general plan for the saddle point argument of H...
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Completely integrally closed Prufer $v$-multiplication domains
We study the effects on $D$ of assuming that the power series ring $D[[X]]$ is a $v$-domain or a PVMD. We show that a PVMD $D$ is completely integrally closed if and only if $\bigcap_{n=1}^{\infty }(I^{n})_{v}=(0)$ for every proper $t$-invertible $t$-ideal $I$ of $D$. Using this, we show that if $D$ is an AGCD domain...
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Masked Autoregressive Flow for Density Estimation
Autoregressive models are among the best performing neural density estimators. We describe an approach for increasing the flexibility of an autoregressive model, based on modelling the random numbers that the model uses internally when generating data. By constructing a stack of autoregressive models, each modelling ...
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Temperature-dependent optical properties of plasmonic titanium nitride thin films
Due to their exceptional plasmonic properties, noble metals such as gold and silver have been the materials of choice for the demonstration of various plasmonic and nanophotonic phenomena. However, noble metals' softness, lack of tailorability and low melting point along with challenges in thin film fabrication and d...
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Succinct Partial Sums and Fenwick Trees
We consider the well-studied partial sums problem in succint space where one is to maintain an array of n k-bit integers subject to updates such that partial sums queries can be efficiently answered. We present two succint versions of the Fenwick Tree - which is known for its simplicity and practicality. Our results ...
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Deep Morphing: Detecting bone structures in fluoroscopic X-ray images with prior knowledge
We propose approaches based on deep learning to localize objects in images when only a small training dataset is available and the images have low quality. That applies to many problems in medical image processing, and in particular to the analysis of fluoroscopic (low-dose) X-ray images, where the images have low co...
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Persistence Flamelets: multiscale Persistent Homology for kernel density exploration
In recent years there has been noticeable interest in the study of the "shape of data". Among the many ways a "shape" could be defined, topology is the most general one, as it describes an object in terms of its connectivity structure: connected components (topological features of dimension 0), cycles (features of di...
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Effective modeling of ground penetrating radar in fractured media using analytic solutions for propagation, thin-bed interaction and dipolar scattering
We propose a new approach to model ground penetrating radar signals that propagate through a homogeneous and isotropic medium, and are scattered at thin planar fractures of arbitrary dip, azimuth, thickness and material filling. We use analytical expressions for the Maxwell equations in a homogeneous space to describ...
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Crystallites in Color Glass Beads of the 19th Century and Their Influence on Fatal Deterioration of Glass
Glass corrosion is a crucial problem in keeping and conservation of beadworks in museums. All kinds of glass beads undergo deterioration but blue-green lead-potassium glass beads of the 19th century are subjected to the destruction to the greatest extent. Blue-green lead-potassium glass beads of the 19th century obta...
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CO2 infrared emission as a diagnostic of planet-forming regions of disks
[Abridged] The infrared ro-vibrational emission lines from organic molecules in the inner regions of protoplanetary disks are unique probes of the physical and chemical structure of planet forming regions and the processes that shape them. The non-LTE excitation effects of carbon dioxide (CO2) are studied in a full d...
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Public Evidence from Secret Ballots
Elections seem simple---aren't they just counting? But they have a unique, challenging combination of security and privacy requirements. The stakes are high; the context is adversarial; the electorate needs to be convinced that the results are correct; and the secrecy of the ballot must be ensured. And they have prac...
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Imprints of Zero-Age Velocity Dispersions and Dynamical Heating on the Age-Velocity dispersion Relation
Observations of stars in the the solar vicinity show a clear tendency for old stars to have larger velocity dispersions. This relation is called the age-velocity dispersion relation (AVR) and it is believed to provide insight into the heating history of the Milky Way galaxy. Here, in order to investigate the origin o...
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Spatial Random Sampling: A Structure-Preserving Data Sketching Tool
Random column sampling is not guaranteed to yield data sketches that preserve the underlying structures of the data and may not sample sufficiently from less-populated data clusters. Also, adaptive sampling can often provide accurate low rank approximations, yet may fall short of producing descriptive data sketches, ...
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Adiponitrile-LiTFSI solution as alkylcarbonate free electrolyte for LTO/NMC Li-ion batteries
Recently, dinitriles (NC(CH2)nCN) and especially adiponitrile (ADN, n=4) have attracted the attention as secure electrolyte solvents due to their chemical stability, high boiling points, high flash points and low vapor pressure. The good solvating properties of ADN toward lithium salts and its high electrochemical st...
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Sea of Lights: Practical Device-to-Device Security Bootstrapping in the Dark
Practical solutions to bootstrap security in today's information and communication systems critically depend on centralized services for authentication as well as key and trust management. This is particularly true for mobile users. Identity providers such as Google or Facebook have active user bases of two billion e...
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On the correlation between a level of structure order and properties of composites. In Memory of Yu.L. Klimontovich
Proposed the computerized method for calculating the relative level of order composites. Correlation between a level of structure order and properties of solids is shown. Discussed the possibility of clarifying the terminology used in describing the structure.
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Schmidt's subspace theorem for moving hypersurface targets
It was discovered that there is a formal analogy between Nevanlinna theory and Diophantine approximation. Via Vojta's dictionary, the Second Main Theorem in Nevanlinna theory corresponds to Schmidt's Subspace Theorem in Diophantine approximation. Recently, Cherry, Dethloff, and Tan (arXiv:1503.08801v2 [math.CV]) obta...
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HoNVis: Visualizing and Exploring Higher-Order Networks
Unlike the conventional first-order network (FoN), the higher-order network (HoN) provides a more accurate description of transitions by creating additional nodes to encode higher-order dependencies. However, there exists no visualization and exploration tool for the HoN. For applications such as the development of s...
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Direct observation of coupled geochemical and geomechanical impacts on chalk microstructural evolution under elevated CO2 pressure. Part I
The dissolution of porous media in a geologic formation induced by the injection of massive amounts of CO2 can undermine the mechanical stability of the formation structure before carbon mineralization takes place. The geomechanical impact of geologic carbon storage is therefore closely related to the structural sust...
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Symplectic resolutions for Higgs moduli spaces
In this paper, we study the algebraic symplectic geometry of the singular moduli spaces of Higgs bundles of degree $0$ and rank $n$ on a compact Riemann surface $X$ of genus $g$. In particular, we prove that such moduli spaces are symplectic singularities, in the sense of Beauville [Bea00], and admit a projective sym...
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Investigation of Defect Modes of Chiral Photonic Crystals
Some properties of defect modes of cholesteric liquid crystals (CLC) are presented. It is shown that when the CLC layer is thin the density of states and emission intensity are maximum for the defect mode, whereas when the CLC layer is thick, these peaks are observed at the edges of the photonic band gap. Similarly, ...
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Crystal Growth of Cu6(Ge,Si)6O18.6H2O and Assignment of UV-VIS Spectra in Comparison to Dehydrated Dioptase and Selected Cu(II) Oxo-Compounds Including Cuprates
It is reported on growth of mm-sized single-crystals of the low-dimensional S = 1/2 spin compound Cu6(Ge,Si)6O18.6H2O by a diffusion technique in aqueous solution. A route to form Si-rich crystals down to possibly dioptase, the pure silicate, is discussed. Further, the assignment of dd excitations from UV-VIS spectra...
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Optical reconfiguration and polarization control in semi-continuous gold films close to the percolation threshold
Controlling and confining light by exciting plasmons in resonant metallic nanostructures is an essential aspect of many new emerging optical technologies. Here we explore the possibility of controllably reconfiguring the intrinsic optical properties of semi-continuous gold films, by inducing permanent morphological c...
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Some Repeated-Root Constacyclic Codes over Galois Rings
Codes over Galois rings have been studied extensively during the last three decades. Negacyclic codes over $GR(2^a,m)$ of length $2^s$ have been characterized: the ring $\mathcal{R}_2(a,m,-1)= \frac{GR(2^a,m)[x]}{\langle x^{2^s}+1\rangle}$ is a chain ring. Furthermore, these results have been generalized to $\lambda$...
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Statistical solutions and Onsager's conjecture
We prove a version of Onsager's conjecture on the conservation of energy for the incompressible Euler equations in the context of statistical solutions, as introduced recently by Fjordholm et al. As a byproduct, we also obtain a new proof for the conservative direction of Onsager's conjecture for weak solutions. Dedi...
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The sum of log-normal variates in geometric Brownian motion
Geometric Brownian motion (GBM) is a key model for representing self-reproducing entities. Self-reproduction may be considered the definition of life [5], and the dynamics it induces are of interest to those concerned with living systems from biology to economics. Trajectories of GBM are distributed according to the ...
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Slow Spin Dynamics and Self-Sustained Clusters in Sparsely Connected Systems
To identify emerging microscopic structures in low temperature spin glasses, we study self-sustained clusters (SSC) in spin models defined on sparse random graphs. A message-passing algorithm is developed to determine the probability of individual spins to belong to SSC. Results for specific instances, which compare ...
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