November 2018 arXiv papers — page 60

I. L. Drichko, I. Yu. Smirnov, A. V. Suslov, M. O. Nestoklon

Oscillations of the real component of AC conductivity $σ_1$ in a magnetic field were measured in the n-AlGaAs/GaAs structure with a wide (75 nm) quantum well by contactless acoustic methods at $T$=(20-500)~mK. In a wide quantum well, the electronic band structure is associated with the two-subband electron spectrum, namely the symmetric (S) and antisymmetric

Abigail Polin, Peter Nugent, Daniel Kasen

We present a numerical parameter survey of sub-Chandrasekhar mass white dwarf (WD) explosions. Carbon-oxygen WDs accreting a helium shell have the potential to explode in the sub-Chandrasekhar mass regime. Previous studies have shown how the ignition of a helium shell can either directly ignite the WD at the core-shell interface or propagate a shock wave int

Xue Yang, Jirui Yang, Junchi Yan, Yue Zhang

Object detection has been a building block in computer vision. Though considerable progress has been made, there still exist challenges for objects with small size, arbitrary direction, and dense distribution. Apart from natural images, such issues are especially pronounced for aerial images of great importance. This paper presents a novel multi-category rot

Clemens-Alexander Brust, Joachim Denzler

One of the most prominent problems in machine learning in the age of deep learning is the availability of sufficiently large annotated datasets. For specific domains, e.g. animal species, a long-tail distribution means that some classes are observed and annotated insufficiently. Additional labels can be prohibitively expensive, e.g. because domain experts ne

Xiao Sun, Chuankang Li, Stephen Lin

We present a method for human pose tracking that is based on learning spatiotemporal relationships among joints. Beyond generating the heatmap of a joint in a given frame, our system also learns to predict the offset of the joint from a neighboring joint in the frame. Additionally, it is trained to predict the displacement of the joint from its position in t

Clemens-Alexander Brust, Joachim Denzler

Knowledge transfer, zero-shot learning and semantic image retrieval are methods that aim at improving accuracy by utilizing semantic information, e.g. from WordNet. It is assumed that this information can augment or replace missing visual data in the form of labeled training images because semantic similarity correlates with visual similarity. This assumptio

B. U. Felderhof, R. B. Jones

The swimming of a deformable uniform sphere is studied in second order perturbation theory in the amplitude of the stroke. The effect of the first order reaction force on the first order center of mass velocity is calculated in linear response theory by use of Newton's equation of motion. The response is characterized by a dipolar admittance, which is shown

Jin Fang, Dingfu Zhou, Feilong Yan, Tongtong Zhao

In Autonomous Driving (AD), detection and tracking of obstacles on the roads is a critical task. Deep-learning based methods using annotated LiDAR data have been the most widely adopted approach for this. Unfortunately, annotating 3D point cloud is a very challenging, time- and money-consuming task. In this paper, we propose a novel LiDAR simulator that augm

D. Ebert, D. Blaschke

We investigate the thermodynamics at finite density of a generalized $(2 + 1)$-dimensional Gross-Neveu model of $N$ fermion species with various types of four-fermion interactions. The motivation for considering such a generalized schematic model arises from taking the Fierz-transformation of an effective Coulomb current-current interaction and certain symme

Ery Arias-Castro, Rong Huang, Nicolas Verzelen

In a bivariate setting, we consider the problem of detecting a sparse contamination or mixture component, where the effect manifests itself as a positive dependence between the variables, which are otherwise independent in the main component. We first look at this problem in the context of a normal mixture model. In essence, the situation reduces to a univar

Sandipan Banerjee, Walter J. Scheirer, Kevin W. Bowyer, Patrick J. Flynn

We propose a multi-scale GAN model to hallucinate realistic context (forehead, hair, neck, clothes) and background pixels automatically from a single input face mask. Instead of swapping a face on to an existing picture, our model directly generates realistic context and background pixels based on the features of the provided face mask. Unlike face inpaintin

Leanne Dong

In this paper we prove that the stochastic Navier-Stokes equations with stable L\'evy noise generates a random dynamical systems. Then we prove the existence of random attractor for the Navier-Stokes equations on 2D spheres under stable L\'evy noise (finite dimensional). We also deduce the existence of Feller Markov invariant measure.

Leanne Dong

In this paper we prove the existence and uniqueness of a strong solution (in PDE sense) to the stochastic Navier-Stokes equations on the rotating 2-dimensional unit sphere perturbed by stable Lévy noise. This strong solution turns out to exist globally in time.

Dai Taguchi, Akihiro Tanaka

In this paper, we first prove that the existence of a solution of SDEs under the assumptions that the drift coefficient is of linear growth and path--dependent, and diffusion coefficient is bounded, uniformly elliptic and H\"older continuous. We apply Gaussian upper bound for a probability density function of a solution of SDE without drift coefficient and l

Xueting Zhang, Yuting Qiang, Flood Sung, Yongxin Yang

Few-shot deep learning is a topical challenge area for scaling visual recognition to open ended growth of unseen new classes with limited labeled examples. A promising approach is based on metric learning, which trains a deep embedding to support image similarity matching. Our insight is that effective general purpose matching requires non-linear comparison

Ndapa Nakashole

Often missing in existing knowledge bases of facts, are relationships that encode common sense knowledge about unnamed entities. In this paper, we propose to extract novel, common sense relationships pertaining to sense perception concepts such as sound and smell.

Pieter C. Allaart, Andrew Allen

In Robbins' problem of minimizing the expected rank, a finite sequence of $n$ independent, identically distributed random variables are observed sequentially and the objective is to stop at such a time that the expected rank of the selected variable (among the sequence of all $n$ variables) is as small as possible. In this paper we consider an analogous prob

Ndapa Nakashole

We consider the problem of recognizing mentions of human senses in text. Our contribution is a method for acquiring labeled data, and a learning method that is trained on this data. Experiments show the effectiveness of our proposed data labeling approach and our learning model on the task of sense recognition in text.

Ruisheng Shi, Lina Lan, Peng Liu, Di Ao

Although many scalable event matching algorithms have been proposed to achieve scalability for large-scale content-based networks, content-based publish/subscribe networks (especially for large-scale real time systems) still suffer performance deterioration when subscription scale increases. While subscription aggregation techniques can be useful to reduce t

Ahmed Ebied, Eli Kinney-Lang, Javier Escudero

Muscle synergies have recently been utilised in myoelectric control systems. Thus far, all proposed synergy-based systems rely on matrix factorisation methods. However, this is limited in terms of task-dimensionality. Here, the potential application of higher-order tensor decomposition as a framework for proportional myoelectric control is demonstrated. A no

Clément Dell'Aiera, Rufus Willett

We introduce a notion of topological property (T) for \'etale groupoids. This simultaneously generalizes Kazhdan's property (T) for groups and geometric property (T) for coarse spaces. One main goal is to use this property (T) to prove the existence of so-called Kazhdan projections in both maximal and reduced groupoid $C^*$-algebras, and explore applications

Urs Hartl, Ambrus Pal

Using the Tannakian formalism, we formulate conjectural analogs of Chebotar\"ev's Density Theorem for $F$-isocrystals over a smooth geometrically irreducible variety defined over a finite field. We prove these analogs for several large classes, including (a) constant $F$-isocrystals, (b) direct sums of isoclinic convergent $F$-isocrystals, (c) semi-simple ov

Marcel Nassar

Recently, graph neural networks have been adopted in a wide variety of applications ranging from relational representations to modeling irregular data domains such as point clouds and social graphs. However, the space of graph neural network architectures remains highly fragmented impeding the development of optimized implementations similar to what is avail

Chenyang Li, Xin Zhang, Lufan Liao, Lianwen Jin

The skeleton based gesture recognition is gaining more popularity due to its wide possible applications. The key issues are how to extract discriminative features and how to design the classification model. In this paper, we first leverage a robust feature descriptor, path signature (PS), and propose three PS features to explicitly represent the spatial and

Ndapa Nakashole

We present a method for learning bilingual translation dictionaries between English and Bantu languages. We show that exploiting the grammatical structure common to Bantu languages enables bilingual dictionary induction for languages where training data is unavailable.

Damian J. Christian, David Kuridze, David B. Jess, Menoa Yousefi

We present multi-wavelength observations of an M-class flare (M3.9) that occurred on 2014 June 11. Our observations were conducted with the Dunn Solar Telescope (DST), adaptive optics, the multi-camera system ROSA (Rapid Oscillations in Solar Atmosphere) and new HARDcam (Hydrogen-Alpha Rapid Dynamics) camera in various wavelengths, such as Ca~II~K, Mg~I~b$_2

Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar, William G. Macready

Building a large image dataset with high-quality object masks for semantic segmentation is costly and time consuming. In this paper, we introduce a principled semi-supervised framework that only uses a small set of fully supervised images (having semantic segmentation labels and box labels) and a set of images with only object bounding box labels (we call it

Yong-Liang Ma, Mannque Rho

The sound velocity $v_s$ and dimensionless tidal deformability $\Lambda$ are analyzed using the pseudo-conformal model we developed before. In contrast to the conclusion obtained in the previous works in the literature, our model with the upper bound of the sound velocity $v_s = 1/\sqrt{3}$, the so-called conformal sound velocity, set in at a { density relev

Paden Tomasello, Sammy Sidhu, Anting Shen, Matthew W. Moskewicz

Convolutional neural networks (CNNs) have become increasingly popular for solving a variety of computer vision tasks, ranging from image classification to image segmentation. Recently, autonomous vehicles have created a demand for depth information, which is often obtained using hardware sensors such as Light detection and ranging (LIDAR). Although it can pr

Börge Göbel, Alexander Mook, Jürgen Henk, Ingrid Mertig

A magnetic bimeron is a pair of two merons and can be understood as the in-plane magnetized version of a skyrmion. Here we theoretically predict the existence of single magnetic bimerons as well as bimeron crystals, and compare the emergent electrodynamics of bimerons with their skyrmion analogues. We show that bimeron crystals can be stabilized in frustrate

Seunghyun Yoon, Kunwoo Park, Joongbo Shin, Hongjun Lim

Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume. This research introduces million-scale pairs of news headline and body text dataset with incongruity label, which can uniquely be utilized for detecting news stories with misleading he

Anadi Chaman, Yu-Jeh Liu, Jonah Casebeer, Ivan Dokmanić

We address the problem of privately communicating audio messages to multiple listeners in a reverberant room using a set of loudspeakers. We propose two methods based on emitting noise. In the first method, the loudspeakers emit noise signals that are appropriately filtered so that after echoing along multiple paths in the room, they sum up and descramble to

I. H. Umirzakov

The equations for Widom lines for the supercritical van der Waals fluid were considered in the paper J. Chem. Phys. 135, 084503 (2011). But the equations for the speed of sound and its special Widom line were incorrect. The correct equations are obtained.

Christian Jilek, Jessica Chwalek, Sven Schwarz, Markus Schröder

Knowledge workers face an ever increasing flood of information in their daily lives. To counter this and provide better support for information management and knowledge work in general, we have been investigating solutions inspired by human forgetting since 2013. These solutions are based on Semantic Desktop (SD) and Managed Forgetting (MF) technology. A key

Christian Jilek, Yannick Runge, Claudia Niederée, Heiko Maus

Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years

Tianlin Liu, João Sedoc, Lyle Ungar

Distributed representations of words, better known as word embeddings, have become important building blocks for natural language processing tasks. Numerous studies are devoted to transferring the success of unsupervised word embeddings to sentence embeddings. In this paper, we introduce a simple representation of sentences in which a sentence embedding is r

Y. M. Cho, Franklin H. Cho

We show how to calculate the effective potential of SU(3) QCD which tells that the true minimum is given by the monopole condensation. To do this we make the gauge independent Weyl symmetric Abelian decomposition of the SU(3) QCD which decomposes the gluons to the color neutral neurons and the colored chromons. In the perturbative regime this decomposes the

Farzad Eskandari, Soroush Pakniat

Considering the creation of persistence landscape on a parametrized curve and structure of sampling, there exists a random process for which a finite mixture model of persistence landscape (FMMPL) can provide a better description for a given dataset. In this paper, a nonparametric approach for computing integrated mean of square error (IMSE) in persistence l

Travis Desell

This paper examines three generic strategies for improving the performance of neuro-evolution techniques aimed at evolving convolutional neural networks (CNNs). These were implemented as part of the Evolutionary eXploration of Augmenting Convolutional Topologies (EXACT) algorithm. EXACT evolves arbitrary convolutional neural networks (CNNs) with goals of bet

Behzad Ghazanfari, Fatemeh Afghah, Matthew E. Taylor

Reinforcement learning (RL) techniques, while often powerful, can suffer from slow learning speeds, particularly in high dimensional spaces. Decomposition of tasks into a hierarchical structure holds the potential to significantly speed up learning, generalization, and transfer learning. However, the current task decomposition techniques often rely on high-l

Amine Marrakchi

Let $M$ be an arbitrary factor and $σ: Γ\curvearrowright M$ an action of a discrete group. In this paper, we study the fullness of the crossed product $M \rtimes_σΓ$. When $Γ$ is amenable, we obtain a complete characterization: the crossed product factor $M \rtimes_σΓ$ is full if and only if $M$ is full and the quotient map $\overlineσ : Γ\rightarrow \mathrm

J. Calatayud, J. -C. Cortés, M. Jornet

The objective of this paper is to complete certain issues from our recent contribution [J. Calatayud, J.-C. Cortés, M. Jornet, L. Villafuerte, Random non-autonomous second order linear differential equations: mean square analytic solutions and their statistical properties, Advances in Difference Equations, 2018:392, 1--29 (2018)]. We restate the main theorem

Jing Lim, Joshua Wong, Minn Xuan Wong, Lee Han Eric Tan

Chemical structure elucidation is a serious bottleneck in analytical chemistry today. We address the problem of identifying an unknown chemical threat given its mass spectrum and its chemical formula, a task which might take well trained chemists several days to complete. Given a chemical formula, there could be over a million possible candidate structures.

Allison Arnold-Roksandich, Kevin James, Rodney Keaton

It is known that all modular forms on $SL_2(Z)$ can be expressed as a rational function in $η(z)$, $η(2z)$ and $η(4z)$. By using a theorem by Gordon, Hughes, and Newman, and calculating the order of vanishing, we can compute the $η$-quotients for a given level. Using this count, knowing how many $η$-quotients are linearly independent and using the dimension

Udit Bhatia, Lina Sela Perelman, Auroop Ratan Ganguly

Designing effective recovery strategies for damaged networked systems is critical to the resilience of built, human and natural systems. However, progress has been limited by the inability to bring together distinct philosophies, such as complex network topology through centrality measures and network flow optimization through entropy measures. Network centr

Qingtang Su, Zehua Zhao

In this paper, we study the dynamics of subcritical threshold solutions for focusing energy critical NLS on $\mathbb{R}^d$ ($d\geq 5$) with nonradial data. This problem with radial assumption was studied by T. Duyckaerts and F. Merle in \cite{DM} for $d=3,4,5$ and later by D. Li and X. Zhang in \cite{LZ} for $d \geq 6$. We generalize the conclusion for the s

Vicky Zayats, Mari Ostendorf

In this paper we introduce a novel pattern match neural network architecture that uses neighbor similarity scores as features, eliminating the need for feature engineering in a disfluency detection task. We evaluate the approach in disfluency detection for four different speech genres, showing that the approach is as effective as hand-engineered pattern matc

Jaehoon Lee

We study the $Λ$-module structure of the ordinary parts of the arithmetic cohomology groups of modular Jacobians made out of various towers of modular curves. We prove that the ordinary parts of $Λ$-adic Selmer groups coming from two different towers have "almost same" $Λ$-module structures. We also prove the cotorsionness of $Λ$-adic Tate-Shafarevic

Yao Wan, Zhou Zhao, Min Yang, Guandong Xu

Code summarization provides a high level natural language description of the function performed by code, as it can benefit the software maintenance, code categorization and retrieval. To the best of our knowledge, most state-of-the-art approaches follow an encoder-decoder framework which encodes the code into a hidden space and then decode it into natural la

A. Brudnyi, Yu. Brudnyi

We introduce and study spaces of multivariate functions of bounded variation generalizing the classical Jordan and Wiener spaces. Multivariate generalizations of the Jordan space were given by several prominent researchers but each of them preserved only some special properties of the space used further in few selected applications. Unlike this the multivari

Blai Bonet, Guillem Francès, Hector Geffner

Generalized planning is concerned with the computation of plans that solve not one but multiple instances of a planning domain. Recently, it has been shown that generalized plans can be expressed as mappings of feature values into actions, and that they can often be computed with fully observable non-deterministic (FOND) planners. The actions in such plans,

Yanett Contreras, David Rebolledo, Shari L. Breen, Anne J. Green

Using the Mopra telescope, we have targeted 61 regions in the Carina Nebula, covering an area of 1.5 square degrees, of bright and compact 870 $μ$m dust continuum emission for molecular line emission from a host of 16 spectral lines at 3mm, including several dense gas tracers. We found that the clumps detected in Carina in general have in average higher temp

Kazumasa Kuwada, Xiang-Dong Li

By means of a space-time Wasserstein control, we show the monotonicity of the W-entropy functional in time along heat flows on possibly singular metric measure spaces with non-negative Ricci curvature and a finite upper bound of dimension in an appropriate sense. The associated rigidity result on the rate of dissipation of the W-entropy is also proved. These

Debashree Sen, T. K. Jha

We explore the possibility of formation of $Δ$ baryons (1232 MeV) in neutron star matter in an effective chiral model within the relativistic mean-field framework. With variation in delta-meson couplings, consistent with the constraints imposed on them, the resulting equation of state is obtained and the neutron star properties are calculated for static and

Nagma Parveen, Pritam Kumar Jana, Monika Schoenhoff

Polyelectrolyte multilayers (PEM) in combination with good electrolyte solvents, e.g., ionic liquids (ILs) are potential candidates for the new generation of electrochemical separators. Swelling PEM with aqueous IL solutions is one way to incorporate IL in PEM. In addition to quantifying the IL uptake in PEM, physical characterization of the swollen PEM is e

Kateryna Tatarko, Elisabeth M. Werner

We prove an analogue of the classical Steiner formula for the $L_p$ affine surface area of a Minkowski outer parallel body for any real parameters $p$. We show that the classical Steiner formula and the Steiner formula of Lutwak's dual Brunn Minkowski theory are special cases of this new Steiner formula. This new Steiner formula and its localized version

Binny Mathew, Ritam Dutt, Suman Kalyan Maity, Pawan Goyal

Anonymity forms an integral and important part of our digital life. It enables us to express our true selves without the fear of judgment. In this paper, we investigate the different aspects of anonymity in the social Q&A site Quora. The choice of Quora is motivated by the fact that this is one of the rare social Q&A sites that allow users to explicitly post

Yair Caro, Raphael Yuster

Erdős, Fajtlowicz and Staton asked for the least integer $f(k)$ such that every graph with more than $f(k)$ vertices has an induced regular subgraph with at least $k$ vertices. Here we consider the following relaxed notions. Let $g(k)$ be the least integer such that every graph with more than $g(k)$ vertices has an induced subgraph with at least $k$ repeated

Mourad E. H. Ismail, Erik Koelink, Pablo Román

A general family of matrix valued Hermite type orthogonal polynomials is introduced and studied in detail by deriving Pearson equations for the weight and matrix valued differential equations for these matrix polynomials. This is used to derive Rodrigues formulas, explicit formulas for the squared norm and to give an explicit expression of the matrix entries

Rami Katz, Yoel Shkolnisky

We present an approximation scheme for functions in three dimensions, that requires only their samples on the Cartesian grid, under the assumption that the functions are sufficiently concentrated in both space and frequency. The scheme is based on expanding the given function in the basis of generalized prolate spheroidal wavefunctions, with the expansion co

Alberto Portone, Luigi Romano, Vito Fasano, Riccardo Di Corato

Molybdenum disulfide (MoS2) has been attracting extraordinary attention for its intriguing optical, electronic and mechanical properties. Here we demonstrate hybrid, organic-inorganic light-emitting nanofibers based on MoS2 nanoparticle dopants obtained through a simple and inexpensive sonication process in N-methyl-2-pyrrolidone and successfully encapsulate

Meha Kaushik, Phaniteja S, K. Madhava Krishna

Multi-agent learning provides a potential framework for learning and simulating traffic behaviors. This paper proposes a novel architecture to learn multiple driving behaviors in a traffic scenario. The proposed architecture can learn multiple behaviors independently as well as simultaneously. We take advantage of the homogeneity of agents and learn in a par

Yuriy Golovaty

One-dimensional Schrödinger operators with singular perturbed magnetic and electric potentials are considered. We study the strong resolvent convergence of two families of the operators with potentials shrinking to a point. Localized $δ$-like magnetic fields are combined with $δ\,'$-like perturbations of the electric potentials as well as localized rank-

Dorota Lipowska, Adam Lipowski

Recently, emergence of signaling conventions, among which language is a prime example, draws a considerable interdisciplinary interest ranging from game theory, to robotics to evolutionary linguistics. Such a wide spectrum of research is based on much different assumptions and methodologies, but complexity of the problem precludes formulation of a unifying a

Travis Hamilton, Hooman Mohseni

Maxwell equations generally explain the propagation of light through an arbitrary medium by using wave mechanics. However, scientific evidence since Newton suggest a discrete interpretation of light more generally explains its nature. This interpretation lends itself well to the discrete form of computer simulation. While current simulations attempt to discr

Neha Baranwal

Humanoid robots have apparently similar body structure like human beings. Due to their technical design, they are sharing the same workspace with humans. They are placed to clean things, to assist old age people, to entertain us and most importantly to serve us. To be acceptable in the household, they must have higher level of intelligence than industrial ro

John Martin, Brendan Englot

The class of Gaussian Process (GP) methods for Temporal Difference learning has shown promise for data-efficient model-free Reinforcement Learning. In this paper, we consider a recent variant of the GP-SARSA algorithm, called Sparse Pseudo-input Gaussian Process SARSA (SPGP-SARSA), and derive recursive formulas for its predictive moments. This extension prom

Cameron Okoth, Andrea Cavanna, Nicolas Joly, Maria Chekhova

Spontaneous parametric down conversion (SPDC) has been one of the foremost tools in quantum optics for over five decades. Over that time it has been used to demonstrate some of the curious features that arise from quantum mechanics. Despite the success of SPDC, its higher-order analogues have never been observed, even though it has been suggested that they g

Víctor Nopal-Coello, Mónica Moreno Rocha

Consider a rational map $R$ of degree $d\geq 2$ with coefficients over the non-archimedean field $\mathbb{C}_p$, with $p$ a fixed prime number. If $R$ has a cycle of Siegel disks and has good reduction, then it was shown by Rivera-Letelier in his PhD dissertation that a new rational map $Q$ can be constructed from $R$, in such a way that $Q$ will exhibit a c

Nolan R. Wallach

The main result asserts: Let $G$ be a reductive, affine algebraic group and let $(ρ,V)$ be a regular representation of $G$. Let $X$ be an irreducible $\mathbb{C}^{ \times } G$ invariant Zariski closed subset such that $G$ has a closed orbit that has maximal dimension among all orbits (this is equivalent to: generic orbits are closed). Then there exists an op

Yichuan Zhang

Approximate inference algorithm is one of the fundamental research fields in machine learning. The two dominant theoretical inference frameworks in machine learning are variational inference (VI) and Markov chain Monte Carlo (MCMC). However, because of the fundamental limitation in the theory, it is very challenging to improve existing VI and MCMC methods on

Eugeny Babichev, Vyacheslav Dokuchaev, Yury Eroshenko

We study a black hole in an expanding Universe during the radiation-dominated stage. In the case when the black hole radius is much smaller than the cosmological horizon, we present a solution of the Einstein equations for the metric, the matter density and velocity distributions. At distances much smaller than the cosmological horizon the solution features

Prateek Jaiswal, Harsha Honnappa, Raghu Pasupathy

We consider a single stage stochastic program without recourse with a strictly convex loss function. We assume a compact decision space and grid it with a finite set of points. In addition, we assume that the decision maker can generate samples of the stochastic variable independently at each grid point and form a sample average approximation (SAA) of the st

Andrei Borodin, Paavo Salminen

We derive a Ray-Knight type theorem for the local time process (in the space variable) of a skew Brownian motion up to an independent exponential time. It is known that the local time seen as a density of the occupation measure and taken with respect to the Lebesgue measure has a discontinuity at the skew point (in our case at zero), but the local time taken

Y. Le Gonidec, M. Rosas-Carbajal, J. de Bremond d'Ars, B. Carlus

The recent 2014 eruption of the Ontake volcano in Japan recalled that hydrothermal fields of moderately active volcanoes have an unpredictable and hazardous behavior that may endanger human beings. Steam blasts can expel devastating ejecta and create craters of several tens of meters. The management of such hydrothermal hazards in populated areas is problema

Michael Ruzhansky, Bolys Sabitbek, Durvudkhan Suragan

In this paper, we present the geometric Hardy inequality for the sub-Laplacian in the half-spaces on the stratified groups. As a consequence, we obtain the following geometric Hardy inequality in a half-space on the Heisenberg group with a sharp constant \begin{equation*} \int_{\mathbb{H}^+} |\nabla_{H}u|^p dξ\geq \left(\frac{p-1}{p}\right)^p \int_{\mathbb{H

David Jewitt, Jessica Agarwal, Man-To Hui, Jing Li

Distant long-period comet C/2017 K2 has been outside the planetary region of the solar system for 3 Myr, negating the possibility that heat retained from the previous perihelion could be responsible for its activity. This inbound comet is also too cold for water ice to sublimate and too cold for amorphous water ice, if present, to crystallize. C/2017 K2 thus

Sophia K. Wright, Jim Q. Smith

Now that Bayesian Networks (BNs) have become widely used, an appreciation is developing of just how critical an awareness of the sensitivity and robustness of certain target variables are to changes in the model. When time resources are limited, such issues impact directly on the chosen level of complexity of the BN as well as the quantity of missing probabi

Oleg Zatsarinny, Henry Parker, Klaus Bartschat

We present a comprehensive study of electron collisions with calcium atoms by using the convergent \emph{B}-spline \emph{R}-matrix method. Elastic, excitation, and ionization cross sections were obtained for all transitions between the lowest 39 physical states of calcium (except for $3p^6 4s5g\ ^{3,1}G$) up to the $3p^6 4s8s\ ^1S$ state, for incident electr

Samuel G. Fadel, Ricardo da S. Torres

Recent advances in employing neural networks on graph domains helped push the state of the art in link prediction tasks, particularly in recommendation services. However, the use of temporal contextual information, often modeled as dynamic graphs that encode the evolution of user-item relationships over time, has been overlooked in link prediction problems.

Eric P. Astor, Denis R. Hirschfeldt, Carl G. Jockusch

This paper concerns algorithms that give correct answers with (asymptotic) density $1$. A dense description of a function $g : ω\to ω$ is a partial function $f$ on $ω$ such that $\left\{n : f(n) = g(n)\right\}$ has density $1$. We define $g$ to be densely computable if it has a partial computable dense description $f$. Several previous authors have studied t

Kirill Boguslavski

In recent years, there have been important advances in understanding the far-from-equilibrium dynamics in different physical systems. In ultra-relativistic heavy-ion collisions, the combination of different methods led to the development of a weak-coupling description of the early-time dynamics. The numerical observation of a classical universal attractor pl

Gregory Schröder, Tobias Senst, Erik Bochinski, Thomas Sikora

The performance of optical flow algorithms greatly depends on the specifics of the content and the application for which it is used. Existing and well established optical flow datasets are limited to rather particular contents from which none is close to crowd behavior analysis; whereas such applications heavily utilize optical flow. We introduce a new optic

Xun-Wang Yan, Zhongbing Huang, Miao Gao, Chunfang Zhang

The potassium-doped p-terphenyl compounds were synthesized in recent experiments and the superconductivity with high transition temperatures were reported, but the atomic structure of potassium-doped p-terphenyl is unclear. In this paper, we studied the structural and electronic properties of potassium-doped p-terphenyl with various doping levels by the firs

Srgei I. Adian, Varujan S. Atabekyan

It is proved that any countable abelian group $D$ can be embedded as a centre into a $m$-generated group $A$ such that the quotient group $A/D$ is isomorphic to the free Burnside group $B(m,n)$ of rank $m>1$ and of odd period $n\ge665$. The proof is based on some modification of the method which was used by S.I.Adian in his monograph in 1975 for a positive s

Jing Yu, Zhenchun Chang, Chuangbai Xiao

Blind image deconvolution is the problem of recovering the latent image from the only observed blurry image when the blur kernel is unknown. In this paper, we propose an edge-based blur kernel estimation method for blind motion deconvolution. In our previous work, we incorporate both sparse representation and self-similarity of image patches as priors into o

José-Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michał Woźniak

Currently, knowledge discovery in databases is an essential step to identify valid, novel and useful patterns for decision making. There are many real-world scenarios, such as bankruptcy prediction, option pricing or medical diagnosis, where the classification models to be learned need to fulfil restrictions of monotonicity (i.e. the target class label shoul

Genki Hosono

We consider the subharmonicity property of the logarithm of Azukawa pseudometrics of pseudoconvex domains under pseudoconvex variations. We prove that such a property holds for the variation of balanced domains. We also give a non-balanced example. The relation of the volume of Azukawa indicatrix and the estimate in the Ohsawa-Takegoshi $L^2$-extension theor

Luisa Fiorot, Teresa Monteiro Fernandes

We introduce the notion of strong regular holonomic ${\mathcal{D}}_{{X\times S}/S}$-module and we prove that the functor ${\mathrm{RH}}^S$ introduced by T. Monteiro Fernandes and C. Sabbah in [14] takes image in ${\mathsf{D}}^{\mathrm{b}}_{\mathrm{srhol}}({\mathcal{D}}_{{X\times S}/S})$ (complexes of ${\mathcal{D}}_{{X\times S}/S}$-module whose cohomologies

Anya Samadi Gh., Patricia Lampens, Davood M. Jassur

We present a new asteroseismic analysis of KIC~6048106, a \textit{Kepler} Algol-type eclipsing binary star in a circularized orbit with $P_\rm{orb}$=1.559361$\pm$0.000036~d. Based on a physical model for the binary and its corresponding set of fundamental parameters, ($T_\rm{eff}=7033\pm187~K, ~M_\rm{1}=1.55\pm0.11M_{\odot}$ and $T_\rm{eff}=4522\pm103~K,~M_\

Giuseppe Greco, Peter Jipsen, Krishna Manoorkar, Alessandra Palmigiano

Taking an algebraic perspective on the basic structures of Rough Concept Analysis as the starting point, in this paper we introduce some varieties of lattices expanded with normal modal operators which can be regarded as the natural rough algebra counterparts of certain subclasses of rough formal contexts, and introduce proper display calculi for the logics

Ali Zamani

We investigate the representation of the so-called orthogonally $a$-Jensen mappings acting on $C^*$-modules. More precisely, let $\mathfrak{A}$ be a unital $C^*$-algebra with the unit $1$, let $a \in \mathfrak{A}$ be fixed such that $a, 1-a$ are invertible and let $\mathscr{E}, \mathscr{F}, \mathscr{G}$ be inner product $\mathfrak{A}$-modules. We prove that

Michaël Cadilhac, Guillermo A. Pérez, Marie van den Bogaard

Discounted-sum games provide a formal model for the study of reinforcement learning, where the agent is enticed to get rewards early since later rewards are discounted. When the agent interacts with the environment, she may regret her actions, realizing that a previous choice was suboptimal given the behavior of the environment. The main contribution of this

Iddo Drori, Isht Dwivedi, Pranav Shrestha, Jeffrey Wan

We tackle the problem of protein secondary structure prediction using a common task framework. This lead to the introduction of multiple ideas for neural architectures based on state of the art building blocks, used in this task for the first time. We take a principled machine learning approach, which provides genuine, unbiased performance measures, correcti

Chang Liu, Yajun Zhu, Kun Xu

The unified gas-kinetic scheme (UGKS) provides a framework for simulating multiscale transport with the updates of both gas distribution function and macroscopic flow variables on the cell size and time step scales. The multiscale dynamics in UGKS is achieved through the coupled particle transport and collision in the particle evolution process within a time

X. Han, L. Zhang, K. Zhou, X. Wang

Protein solubility plays a critical role in improving production yield of recombinant proteins in biocatalyst and pharmaceutical field. To some extent, protein solubility can represent the function and activity of biocatalysts which are mainly composed of recombinant proteins. Highly soluble proteins are more effective in biocatalytic processes and can reduc

Martin Weiß

A common task in robotics is unloading identical goods from a tray with rectangular grid structure. This naturally leads to the idea of programming the process at one grid position only and translating the motion to the other grid points, saving teaching time. However this approach usually fails because of joint limits or singularities of the robot. If the t

Pengjie Zhang

We point out a new possibility to determine the average redshift distribution of a large sample of gravitational wave standard sirens, without spectroscopic follow-ups. It is based on the cross correlation between the luminosity-distance space large scale structure (LSS) traced by standard sirens, and the redshift space LSS traced by galaxies in preexisting

László Györfi, Norbert Henze, Harro Walk

Let $X_1, \ldots, X_n$ be independent random points drawn from an absolutely continuous probability measure with density $f$ in $\mathbb{R}^d$. Under mild conditions on $f$, we derive a Poisson limit theorem for the number of large probability nearest neighbor balls. Denoting by $P_n$ the maximum probability measure of nearest neighbor balls, this limit theo

R. C. McPhedran, B. Stout

We consider integrals of products of Bessel functions and of spherical Bessel functions, combined with a Gaussian factor guaranteeing convergence at infinity. Explicit representations are obtained for the integrals, building on those in the 1992 paper by McPhedran, Dawes and Scott. Attention is paid to those sums with a distributive part arising as the Gauss