arXiv papers from August 2019

Bryan, Xia, Yuan Gong, Yizhe Zhang

Recent efforts have shown promising results for person re-identification by designing part-based architectures to allow a neural network to learn discriminative representations from semantically coherent parts. Some efforts use soft attention to reallocate distant outliers to their most similar parts, while others adjust part granularity to incorporate more

Yuya Sasaki, Yulong Wang

We develop a new extreme value theory for repeated cross-sectional and panel data to construct asymptotically valid confidence intervals (CIs) for conditional extremal quantiles from a fixed number $k$ of nearest-neighbor tail observations. As a by-product, we also construct CIs for extremal quantiles of coefficients in linear random coefficient models. For

Xianda Deng, Kyle Thomas, Huiying Huang, Scott P Adams

Transformers are critical assets in power systems and transformer failures can cause asset damage, customer outages, and safety concerns. Dominion Energy has a sophisticated monitoring process for the transformers. One of the most cost-efficient, convenient and practical transformer monitoring methods in industry is Dissolved Gas Analysis(DGA). Leveraging ne

Stanislav Budzinskiy

The paper is devoted to (combinations of) Bessel cross-products that arise from oblique derivative boundary value problems for the Laplacian in a circular annulus. We show that like their Neumann-Laplacian counterpart (and unlike the Dirichlet-Laplacian), they possess two kinds of zeros: those that can be derived by McMahon series and diverge to infinity in

Murari Mandal, Manal Shah, Prashant Meena, Santosh Kumar Vipparthi

Detection of small-sized targets is of paramount importance in many aerial vision-based applications. The commonly deployed low cost unmanned aerial vehicles (UAVs) for aerial scene analysis are highly resource constrained in nature. In this paper we propose a simple short and shallow network (SSSDet) to robustly detect and classify small-sized vehicles in a

Tom Banks, Bingnan Zhang

We investigate the low density limit of the Homogeneous Electron system, often called the {\it Strictly Correlated} regime. We begin with a systematic presentation of the expansion around infinite $r_S$, based on the first quantized treatments suggested in the existing literature. We show that the expansion is asymptotic in the parameter $r_S^{1/4}$ and that

Hovhannes Khudaverdian, Theodore Voronov

"Thick" or "microformal" morphisms of supermanifolds generalize ordinary maps. They were discovered as a tool for homotopy algebras. Namely, the corresponding pullbacks provide $L_{\infty}$-morphisms for $S_{\infty}$ or Batalin--Vilkovisky algebras. It was clear from the start that constructions used for thick morphisms closely resemble some fundamental noti

Michał Cieśla

Random sequential adsorption algorithm is a popular tool for modelling structure of monolayers built in irreversible adsorption experiments. However, this algorithm becomes very inefficient when the density of molecules in a layer rises. This problem has already been solved for a very limited range of basic shapes. This study presents a solution that can be

Teerthal Patel, Hiroyuki Tashiro, Yuko Urakawa

We investigate the generation of seed magnetic field through the Chern-Simons coupling between the U(1) gauge field and an axion field that commences to oscillate at various epoch, depending on the mass scale. We address axions which begin oscillation during inflation, reheating, and also the radiation dominated era after the thermalization of the Universe.

Raushan Buzyakova

Given an autohomeomorphism on an ordered topological space or its subspace, we show that it is sometimes possible to introduce a new topology-compatible order on that space so that the same map is monotonic with respect to the new ordering. We note that the existence of such a re-ordering for a given map is equivalent to the map being conjugate (topologicall

Rob van Glabbeek

This paper poses that transition systems constitute a good model of distributed systems only in combination with a criterion telling which paths model complete runs of the represented systems. Among such criteria, progress is too weak to capture relevant liveness properties, and fairness is often too strong; for typical applications we advocate the intermedi

Yuhito Shibaike, Chris W. Ormel, Shigeru Ida, Satoshi Okuzumi

It is generally accepted that the four major (Galilean) satellites formed out of the gas disk that accompanied Jupiter's formation. However, understanding the specifics of the formation process is challenging as both small particles (pebbles) as well as the satellites are subject to fast migration processes. Here, we hypothesize a new scenario for the origin

Erik W. Lentz

This paper examines the structure of electric fields and space-times created by extended finite distributions of irrotational static and spherically-symmetric charge. The resulting electric fields are found to source features in space-time commonly associated with the presence of fields with locally positive and negative mass densities, with the sign of the

Richard E. Zeebe, Lucas J. Lourens

Astronomical calculations reveal the solar system's dynamical evolution, including its chaoticity, and represent the backbone of cyclostratigraphy and astrochronology. An absolute, fully calibrated astronomical time scale has hitherto been hampered beyond $\sim$50 Ma, because orbital calculations disagree before that age. Here we present geologic data and a

Adrian Ioana

We study the notion of permutation stability (or P-stability) for countable groups. Our main result provides a wide class of non-amenable product groups which are not P-stable. This class includes the product group $\Sigma\times\Lambda$, whenever $\Sigma$ admits a non-abelian free quotient and $\Lambda$ admits an infinite cyclic quotient. In particular, we o

Ming Tan, Yang Yu, Haoyu Wang, Dakuo Wang

Out-of-domain (OOD) detection for low-resource text classification is a realistic but understudied task. The goal is to detect the OOD cases with limited in-domain (ID) training data, since we observe that training data is often insufficient in machine learning applications. In this work, we propose an OOD-resistant Prototypical Network to tackle this zero-s

Abdulla Rakhimov, Asliddin Khudoyberdiev, Luxmi Rani, B. Tanatar

We study the thermodynamic properties of dimerized spin-gapped quantum magnets with and without exchange anisotropy (EA) and Dzyaloshinsky and Moriya (DM) anisotropies within the mean-field approximation (MFA). For this purpose we obtain the thermodynamic potential $\Omega$ of a triplon gas taking into account the strength of DM interaction up to second orde

Xihui Chen, Sjouke Mauw, Yunior Ramírez-Cruz

We present a novel method for publishing differentially private synthetic attributed graphs. Unlike preceding approaches, our method is able to preserve the community structure of the original graph without sacrificing the ability to capture global structural properties. Our proposal relies on C-AGM, a new community-preserving generative model for attributed

Zhichao Yang, Pengshan Cai, Yansong Feng, Fei Li

Classical Chinese poetry is a jewel in the treasure house of Chinese culture. Previous poem generation models only allow users to employ keywords to interfere the meaning of generated poems, leaving the dominion of generation to the model. In this paper, we propose a novel task of generating classical Chinese poems from vernacular, which allows users to have

Jakub Cimerman, Boris Tomášik, Christopher Plumberg

The correlation function measured in ultrarelativistic nuclear collisions is non-Gaussian. By making use of models we discuss and assess how much various effects can influence its shape. In particular, we focus on the parametrisations expressed with the help of L\'evy-stable distributions. We show that the L\'evy index may deviate substantially from 2 due to

Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi

Understanding narratives requires reading between the lines, which in turn, requires interpreting the likely causes and effects of events, even when they are not mentioned explicitly. In this paper, we introduce Cosmos QA, a large-scale dataset of 35,600 problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. I

Robert Holland, Uday Patel, Phillip Lung, Elisa Chotzoglou

Crohn's disease, one of two inflammatory bowel diseases (IBD), affects 200,000 people in the UK alone, or roughly one in every 500. We explore the feasibility of deep learning algorithms for identification of terminal ileal Crohn's disease in Magnetic Resonance Enterography images on a small dataset. We show that they provide comparable performance to the cu

Andy Chong, Chenhao Wan, Jian Chen, Qiwen Zhan

Today, it is well known that light possesses a linear momentum which is along the propagation direction. Besides, scientists also discovered that light can possess an angular momentum (AM), a spin angular momentum (SAM) associated with circular polarization and an orbital angular momentum (OAM) owing to the azimuthally dependent phase. Even though such angul

Alejandro Ayala, David de la Cruz, S. Hernández-Ortíz, L. A. Hernández

We compute the relaxation time for quark/antiquark spin and thermal vorticity alignment in a quark-gluon plasma at finite temperature and quark chemical potential. We model the interaction of quark/antiquark spin with thermal vorticity as driven by a phenomenological modification of the elementary quark interaction with gluons. We find that in a scenario whe

Zahra Sobhaninia, Shima Rafiei, Ali Emami, Nader Karimi

Ultrasound imaging is a standard examination during pregnancy that can be used for measuring specific biometric parameters towards prenatal diagnosis and estimating gestational age. Fetal head circumference (HC) is one of the significant factors to determine the fetus growth and health. In this paper, a multi-task deep convolutional neural network is propose

Lei Chen

In this paper, we show that an infinite 2-group of bounded exponent cannot act faithfully and smoothly on compact manifolds.

Maria Luiza Mondelli, A. Townsend Peterson, Luiz M. R. Gadelha

Reproducibility is a fundamental requirement of the scientific process since it enables outcomes to be replicated and verified. Computational scientific experiments can benefit from improved reproducibility for many reasons, including validation of results and reuse by other scientists. However, designing reproducible experiments remains a challenge and henc

Safiyeh Rezaei, Ali Emami, Hamidreza Zarrabi, Shima Rafiei

Histopathology images contain essential information for medical diagnosis and prognosis of cancerous disease. Segmentation of glands in histopathology images is a primary step for analysis and diagnosis of an unhealthy patient. Due to the widespread application and the great success of deep neural networks in intelligent medical diagnosis and histopathology,

Joseph D. Romano

These lecture notes provide a brief introduction to methods used to search for a stochastic background of gravitational radiation -- a superposition of gravitational-wave signals that are either too weak or too numerous to individually detect. The focus of these notes is on relevant data analysis techniques, not on the particular astrophysical or cosmologica

Ankit Gangwal, Samuele Giuliano Piazzetta, Gianluca Lain, Mauro Conti

Cybercriminals have been exploiting cryptocurrencies to commit various unique financial frauds. Covert cryptomining - which is defined as an unauthorized harnessing of victims' computational resources to mine cryptocurrencies - is one of the prevalent ways nowadays used by cybercriminals to earn financial benefits. Such exploitation of resources causes finan

Andrei Khrennikov

We analyze interrelation of quantum and classical entanglement. The latter notion is widely used in classical optic simulation of some quantum-like features of light. We criticize the common interpretation that "quantum nonlocality" is the basic factor differing quantum and classical realizations of entanglement. Instead, we point to the breakthrough Grangie

Jayson G. Cosme, Jim Skulte, Ludwig Mathey

We demonstrate the emergence of a time crystal of atoms in a high-finesse optical cavity driven by a phase-modulated transverse pump field, resulting in a shaken lattice. This shaken system exhibits macroscopic oscillations in the number of cavity photons and order parameters at noninteger multiples of the driving period, which signals the appearance of an i

Jorge I. Poveda, Na Li

We study novel robust zero-order algorithms with acceleration for the solution of real-time optimization problems. In particular, we propose a family of extremum seeking dynamics that can be universally modeled as singularly perturbed hybrid dynamical systems with restarting mechanisms. From this family of dynamics, we synthesize four fast algorithms for the

Sergei Kalmykov, Béla Nagy, Olivier Sète

We establish the existence and uniqueness of rational conformal maps of minimal degree $n+1$ for opening up $n$ arcs. In earlier results, the degree was exponential in $n$. We also discuss two related problems. (a) We establish existence of rational functions of minimal degree with prescribed critical values, and show that the number of (suitably normalized)

Sergey Avvakumov, Gabriel Nivasch

We define and study a discrete process that generalizes the convex-layer decomposition of a planar point set. Our process, which we call "homotopic curve shortening" (HCS), starts with a closed curve (which might self-intersect) in the presence of a set $P\subset \mathbb R^2$ of point obstacles, and evolves in discrete steps, where each step consists of (1)

Neslihan Gügümcü, Sam Nelson, Natsumi Oyamaguchi

Biquandle brackets are a type of quantum enhancement of the biquandle counting invariant for oriented knots and links, defined by a set of skein relations with coefficients which are functions of biquandle colors at a crossing. In this paper we use biquandle brackets to enhance the biquandle counting matrix invariant defined by the first two authors in arXiv

Jörg P. Rachen, Björn Eichmann

Many attempts have been made to provide catalogs of potential sources of ultra-high energy cosmic ray (UHECR) particles based on various astronomical tracers, such as observed radio or gamma-ray emission. A closer look reveals, however, that they all suffer from significant bias and selection effects. We present here a demo-version of a catalog for one often

JJ Garcia-Luna-Aceves, A. Varma

This document describes the work completed at the University of California, Santa Cruz under the project Scalable Internetworking sponsored by ARPA under Contract No. F19628-93-C-0175. This report covers work performed from 1 April 1993 to 31 December 1995. Results on routing and multicasting for large-scale internets are summarized. The technical material d

Hiroyuki Shindo, Yuji Matsumoto

Molecule property prediction is a fundamental problem for computer-aided drug discovery and materials science. Quantum-chemical simulations such as density functional theory (DFT) have been widely used for calculating the molecule properties, however, because of the heavy computational cost, it is difficult to search a huge number of potential chemical compo

J. L. Lado, R. Ortiz, J. Fernandez-Rossier

In this book chapter, we introduce different schemes to create quantum states of matter in engineered graphene nanoribbons. We will focus on the emergence of controllable magnetic interactions, topological quantum magnets, and the interplay of magnetism and superconductivity. We comment on the experimental signatures of those states stemming from their elect

Emerson G. Escolar, Yasuaki Hiraoka, Mitsuru Igami, Yasin Ozcan

Where do firms innovate? Mapping their locations and directions in technological space is challenging due to its high dimensionality. We propose a new method to characterize firms' inventive activities via topological data analysis (TDA) that represents high-dimensional data in a shape graph. Applying this method to 333 major firms' patents in 1976--2005 rev

Johann Davidov

Motivated by generalized geometry (\`a la Hitchin), we discuss the integrability conditions for four natural almost complex structures on the product bundle ${\mathcal Z}\times {\mathcal Z}\to M$, where ${\mathcal Z}$ is the twistor space of a Riemannian 4-manifold $M$ endowed with a metric connection $D$ with skew-symmetric torsion. These structures are def

Geza Kovacs, Joel D. Hartman, Gaspar A. Bakos

We revisit the issue of period variation of the recently claimed red nova precursor candidate KIC 9832227. By using the data gathered during the main mission of the Kepler satellite, those collected by ground-based wide-field surveys and other monitoring programs (such as ASAS-SN), we find that the currently available timing data strongly support a model con

Jiarong Hong, Aliza Abraham

This paper provides a review of the general experimental methodology of snow-powered flow visualization and super-large-scale particle imaging velocimetry (SLPIV), the corresponding field deployments and major scientific findings from our work on a 2.5 MW utility-scale wind turbine at the Eolos field station. The field measurements were conducted to investig

Seth Gannon, Hamid Kulosman

In the 2017 paper by Dougherty, Kim, Ozkaya, Sok, and Sol\'e about the linear programming bound for LCD codes the notion $\mathrm{LCD}[n,k]$ was defined for binary LCD $[n,k]$-codes. We find the formula for $\mathrm{LCD}[n,2]$.

Orion Weller, Kevin Seppi

Much previous work has been done in attempting to identify humor in text. In this paper we extend that capability by proposing a new task: assessing whether or not a joke is humorous. We present a novel way of approaching this problem by building a model that learns to identify humorous jokes based on ratings gleaned from Reddit pages, consisting of almost 1

David Polletta

Mark and Paupert devised a general method for obtaining presentations for arithmetic non-cocompact lattices, $\Gamma$, in isometry groups of negatively curved symmetric spaces. The method involves a classical theorem of Macbeath applied to a $\Gamma$-invariant covering by horoballs of the negatively curved symmetric space upon which $\Gamma$ acts. In this pa

Yunpeng Zhao

We prove a new Bernstein-type inequality for the log-likelihood function of Bernoulli variables. In contrast to classical Bernstein's inequality and Hoeffding's inequality when applied to the log-likelihood, the new bound is independent of the parameters of the Bernoulli variables and therefore does not blow up as the parameters approach 0 or 1. The new ineq

Mengjie Yu, Yoshitomo Okawachi, Rebecca Cheng, Cheng Wang

The recent advancement in lithium niobate on insulator (LNOI) technology is revolutionizing the optoelectronic industry as devices of higher performance, lower power consumption, and smaller footprint can be realized due to the high optical confinement in the structures. The LNOI platform offers both large \c{hi}(2) and \c{hi}(3) nonlinearities along with th

M. Puppin, S. Polishchuk, N. Colonna, A. Crepaldi

Lead-halide perovskite (LHP) semiconductors are emergent optoelectronic materials with outstanding transport properties which are not yet fully understood. We find signatures of large polaron formation in the electronic structure of the inorganic LHP CsPbBr$_3$ by means of angle-resolved photoelectron spectroscopy. The experimental valence band dispersion sh

Alankar Jain, Bhargavi Paranjape, Zachary C. Lipton

Although over 100 languages are supported by strong off-the-shelf machine translation systems, only a subset of them possess large annotated corpora for named entity recognition. Motivated by this fact, we leverage machine translation to improve annotation-projection approaches to cross-lingual named entity recognition. We propose a system that improves over

Georgia Papacharalampous, Hristos Tyralis, Demetris Koutsoyiannis, Alberto Montanari

Predictive hydrological uncertainty can be quantified by using ensemble methods. If properly formulated, these methods can offer improved predictive performance by combining multiple predictions. In this work, we use 50-year-long monthly time series observed in 270 catchments in the United States to explore the performances provided by an ensemble learning p

Kauê Cardoso, Vilmar Trevisan

In this paper we define signless Laplacian matrix of a hypergraph and obtain structural properties from its eigenvalues. We generalize several known results for graphs, relating the spectrum of this matrix with structural parameters of the hypergraph such as the maximum degree, diameter and the chromatic number. In addition, we characterize the complete sign

Yumei Jing, Shaoyun Huang, Jinxiong Wu, Mengmeng Meng

Quantum confined devices of three-dimensional topological insulators have been proposed to be promising and of great importance for studies of confined topological states and for applications in low energy-dissipative spintronics and quantum information processing. The absence of energy gap on the TI surface limits the experimental realization of a quantum c

Katherine Elkins, Jon Chun

Modernist novels are thought to break with traditional plot structure. In this paper, we test this theory by applying Sentiment Analysis to one of the most famous modernist novels, To the Lighthouse by Virginia Woolf. We first assess Sentiment Analysis in light of the critique that it cannot adequately account for literary language: we use a unique statistic

Georgia Papacharalampous, Demetris Koutsoyiannis, Alberto Montanari

We introduce an ensemble learning post-processing methodology for probabilistic hydrological modelling. This methodology generates numerous point predictions by applying a single hydrological model, yet with different parameter values drawn from the respective simulated posterior distribution. We call these predictions "sister predictions". Each sister predi

F. Valizadeh, H. Rahimi, R. A. Kamyabi Gol, F. Esmaeelzadeh

In this note, we fix a real invertible $d\times d$ matrix $\mathcal{A}$ and consider $\mathcal{A}\mathbb{Z}^d$ as an index set. For $f\in L^2(\mathbb{R}^d)$, let $\Phi^{\mathcal{A}}_{f}:=\frac{1}{|\det \mathcal{A}|}\sum_{k\in \mathbb{Z}^d}|\hat{f}(\mathcal{A}^T)^{-1}(\cdot+k)|^2$ be the periodization of $|\hat{f}|^2$. By using $\Phi^{\mathcal{A}}_{f}$, among

P. Kowalewska, K. Szałowski

The paper presents a theoretical study of magnetocaloric properties of polyoxovanadate molecular magnet V6 containing 6 vanadium ions carrying quantum spins $S = 1/2$. The characteristic property of such structure is the presence of two weakly interacting spin triangles with all-antiferromagnetic couplings. The properties of the system are described using th

M. M. Sadeghi, H. Nadgaran

We report the design of a new electromagnetic device with a new mapping function to have simultaneous electromagnetic concentration and rotation using a singular radial mapping. We implement such a device only by using alternating structure of zero index metamaterials and perfect electric conductors. Numerical simulations are performed to verify its function

Ashkan Mohammadi, Boris S. Mordukhovich, M. Ebrahim Sarabi

The paper is mainly devoted to systematic developments and applications of geometric aspects of second-order variational analysis that are revolved around the concept of parabolic regularity of sets. This concept has been known in variational analysis for more than two decades while being largely underinvestigated. We discover here that parabolic regularity

Muhammad Usman Ghani, W. Clem Karl

Computed Tomography (CT) is a non-invasive imaging modality with applications ranging from healthcare to security. It reconstructs cross-sectional images of an object using a collection of projection data collected at different angles. Conventional methods, such as FBP, require that the projection data be uniformly acquired over the complete angular range. I

Mingfei Gao, Larry S. Davis, Richard Socher, Caiming Xiong

We propose weakly supervised language localization networks (WSLLN) to detect events in long, untrimmed videos given language queries. To learn the correspondence between visual segments and texts, most previous methods require temporal coordinates (start and end times) of events for training, which leads to high costs of annotation. WSLLN relieves the annot

Kauê Cardoso, Vilmar Trevisan

In this paper we obtain bounds for the extreme entries of the principal eigenvector of hypergraphs; these bounds are computed using the spectral radius and some classical parameters such as maximum and minimum degrees. We also study inequalities involving the ratio and difference between the two extreme entries of this vector.

Shubhankar Mohapatra, Moumita Sarkar, Anjali Mohapatra, Bhawani Sankar Biswal

Microarray data analysis is one of the major area of research in the field computational biology. Numerous techniques like clustering, biclustering are often applied to microarray data to extract meaningful outcomes which play key roles in practical healthcare affairs like disease identification, drug discovery etc. But these techniques become obsolete when

H. Ramezani-Aval

We investigate detection of Dirac quanta in a uniformly eccentric rotating frame both with canonical and detector approaches by employing relativistic rotational transformations. First we consider a relativistic uniformly eccentric rotating detector that is coupled to the scalar density of a massless Dirac field, and show that this detector has a nonzero res

Nathann T. Rodrigues, Tiago J. Oliveira

We study binary mixtures of hard particles, which exclude up to their $k$th nearest neighbors ($k$NN) on the simple cubic lattice and have activities $z_k$. In the first model analyzed, point particles (0NN) are mixed with 1NN ones. The grand-canonical solution of this model on a Husimi lattice built with cubes unveils a phase diagram with a fluid and a soli

Kauê Cardoso, Carlos Hoppen, Vilmar Trevisan

A generalized power hypergraph $\mathcal{H}^k_s$ is obtained from a base hypergraph $\mathcal{H}$ by means of some simple edge-expansion operations. Kang, Liu, Qi and Yuan [8] proved that the nonzero eigenvalues of $\mathcal{H}$ give rise to nonzero eigenvalues of $\mathcal{H}^k_s$. In this paper we show that all nonzero eigenvalues of $\mathcal{H}^k_s$ may

Andriana Martinou, Dennis Bonatsos

In nuclear physics a magic number is defined as the nucleon number, which is separated by a significantly large single-particle energy gap from the next nucleon. Magic numbers define the nuclear shells, which are considered to be active, only if they are partially occupied by nucleons. As a consequence the single particle interactions of the valence nucleons

Aretha L Teckentrup

This work is concerned with the convergence of Gaussian process regression. A particular focus is on hierarchical Gaussian process regression, where hyper-parameters appearing in the mean and covariance structure of the Gaussian process emulator are a-priori unknown, and are learnt from the data, along with the posterior mean and covariance. We work in the f

Yuzhi Zhang, Chang Gao, Linfeng Zhang, Han Wang

Simulating warm dense matter that undergoes a wide range of temperatures and densities is challenging. Predictive theoretical models, such as quantum-mechanics-based first-principles molecular dynamics (FPMD), require a huge amount of computational resources. Herein, we propose a deep learning based scheme, called electron temperature dependent deep potentia

Cong Fu, Tong Chen, Meng Qu, Woojeong Jin

In recent years, there has been a surge of interests in interpretable graph reasoning methods. However, these models often suffer from limited performance when working on sparse and incomplete graphs, due to the lack of evidential paths that can reach target entities. Here we study open knowledge graph reasoning---a task that aims to reason for missing facts

Huan Qi, Sally Collins, J. Alison Noble

Semantic contour detection is a challenging problem that is often met in medical imaging, of which placental image analysis is a particular example. In this paper, we investigate utero-placental interface (UPI) detection in 2D placental ultrasound images by formulating it as a semantic contour detection problem. As opposed to natural images, placental ultras

Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou

Document-level relation extraction is a complex human process that requires logical inference to extract relationships between named entities in text. Existing approaches use graph-based neural models with words as nodes and edges as relations between them, to encode relations across sentences. These models are node-based, i.e., they form pair representation

Anton F. Faedo, David Mateos, Christiana Pantelidou, Javier Tarrio

We have recently shown that the ground state of ${\cal N} = 4$, SU($N_{\rm{\tiny c}}$) super Yang--Mills coupled to $N_{\rm{\tiny f}} \ll N_{\rm{\tiny c}}$ flavors, in the presence of non-zero isospin and R-symmetry charges, is a supersymmetric, superfluid, color superconductor. The holographic description consists of $N_{\rm{\tiny f}}$ D7-brane probes in Ad

Marian Boguna, Dmitri Krioukov, Pedro Almagro, M. Angeles Serrano

Networks with underlying metric spaces attract increasing research attention in network science, statistical physics, applied mathematics, computer science, sociology, and other fields. This attention is further amplified by the current surge of activity in graph embedding. In the vast realm of spatial network models, only a few reproduce even the most basic

Hanshen Xiao, Nan Du, Zhikang T. Wang, Guoqiang Xiao

Generalized Chinese Remainder Theorem (CRT) is a well-known approach to solve ambiguity resolution related problems. In this paper, we study the robust CRT reconstruction for multiple numbers from a view of statistics. To the best of our knowledge, it is the first rigorous analysis on the underlying statistical model of CRT-based multiple parameter estimatio

Xi-Jing Wang, Hai-Shan Liu, Wei-Jia Li

In this paper, we investigate the AC charge transport in the holographic Horndeski gravity and identify a metal-semiconductor like transition that is driven by the Horndeski coupling. Moreover, we fit our numeric data by the Drude formula in slow relaxation cases.

Patrizio Angelini, Michael A. Bekos, Franz J. Brandenburg, Giordano Da Lozzo

A simple topological graph is $k$-quasiplanar ($k\geq 2$) if it contains no $k$ pairwise crossing edges, and $k$-planar if no edge is crossed more than $k$ times. In this paper, we explore the relationship between $k$-planarity and $k$-quasiplanarity to show that, for $k \geq 2$, every $k$-planar simple topological graph can be transformed into a $(k+1)$-qua

Daniele Ninci, Tomohiro Inada, Javier Rico, Daniel Kerszberg

MAGIC is a system of two Cherenkov telescopes located in the Canary island of La Palma. A key part of MAGIC Fundamental Physics program is the search for indirect signals of Dark Matter (DM) from different sources. In the Milky Way, DM forms an almost spherically symmetric halo, with a density peaked towards the center of the Galaxy and decreasing toward the

Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis

Accurate forecasts are vital for supporting the decisions of modern companies. Forecasters typically select the most appropriate statistical model for each time series. However, statistical models usually presume some data generation process while making strong assumptions about the errors. In this paper, we present a novel data-centric approach -- `forecast

Anestis Fotiadis, Effie Papageorgiou

Let $X$ be a non-compact symmetric space of dimension $n$. We prove that if $f\in L^{p}(X)$, $1\leq p\leq 2$, then the Riesz means $S_{R}^{z}\left( f\right)$ converge to $f$ almost everywhere as $R\rightarrow \infty $, whenever $\operatorname{Re}z>\left( n-\frac{1}{2}\right) \left( \frac{2}{p}-1\right) $.

Raúl Ures, Marcelo Viana, Jiagang Yang

We characterize the maximal entropy measures of partially hyperbolic C^2 diffeomorphisms whose center foliations form circle bundles, by means of suitable finite sets of saddle points, that we call skeletons. In the special case of 3-dimensional nilmanifolds other than the torus, this entails the following dichotomy: either the diffeomorphism is a rotation e

Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier

Various strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for which its current prediction is maximally uncertain. The predictions as well as the measures used to quantify the degree of

Arghya Majee, Markus Bier, Ralf Blossey, Rudolf Podgornik

Motivated by biological membrane-containing organelles in plants and photosynthetic bacteria, we study charge regulation in a model membrane stack. Considering (de)protonation as the simplest mechanism of charge equilibration between the membranes and with the bathing environment, we uncover a symmetry-broken charge state in the stack with a quasiperiodic ef

Francesco Giannini, Marco Maggini

A main property of support vector machines consists in the fact that only a small portion of the training data is significant to determine the maximum margin separating hyperplane in the feature space, the so called support vectors. In a similar way, in the general scheme of learning from constraints, where possibly several constraints are considered, some o

Yi-Ting Yeh, Yun-Nung Chen

Standard accuracy metrics indicate that modern reading comprehension systems have achieved strong performance in many question answering datasets. However, the extent these systems truly understand language remains unknown, and existing systems are not good at distinguishing distractor sentences, which look related but do not actually answer the question. To

József Balogh, Andrzej Dudek, Lina Li

Recently, variants of many classical extremal theorems have been proved in the random environment. We, complementing existing results, extend the Erd\H{o}s-Gallai Theorem in random graphs. In particular, we determine, up to a constant factor, the maximum number of edges in a $P_n$-free subgraph of $G(N,p)$, practically for all values of $N,n$ and $p$. Our wo

Robert Tremblay

We demonstrate that the number of cycles for two problems of the family of generalized 3x+1 mappings is possible finite.

Artur Aleksanyan, Svetlana Shmavonyan, Emil Gazazyan, Aleksandr Khanbekyan

We have studied modification of the fluorescence spectra of a room-temperature atomic rubidium vapor in the region of $^{85}$Rb and $^{87}$Rb D$_2$ line while changing the temporal rate of linear (triangular) scanning of laser radiation frequency. Increase of the ramping speed over certain value ($\approx$ 10$^6$ MHz/s) results in essential modification of m

Vikas Ahuja, Vijay Kumar Neeluru

The life time of electronic circuits board are impacted by the voids present in soldering balls. The quality inspection of solder balls by detecting and measuring the void is important to improve the board yield issues in electronic circuits. In general, the inspection is carried out manually, based on 2D or 3D X-ray images. For high quality inspection, it i

Yunqi Luo, Suxia Yan, Huanhao Li, Puxiang Lai

Optical focusing at depths in tissue is the Holy Grail of biomedical optics that may bring revolutionary advancement to the field. Wavefront shaping is a widely accepted approach to solve this problem, but most implementations thus far have only operated with stationary media which, however, are scarcely existent in practice. In this article, we propose to a

S. Feng, P. Caselli, K. Wang, Y. Lin

The chemical structure of high-mass star nurseries is important for a general understanding of star formation. Deuteration is a key chemical process in the earliest stages of star formation because its efficiency is sensitive to the environment. Using the IRAM-30 m telescope at 1.3--4.3 mm wavelengths, we have imaged two parsec-scale high-mass protostellar c

Meng Yang

We construct \emph{intrinsic} metrics on the Strichartz hexacarpet using weight functions and show that these metrics do \emph{not} satisfy the chain condition. We give uniform Harnack inequality on the approximating graphs of the Strichartz hexacarpet with respect to the intrinsic metrics instead of graph metrics.

Daniele Bartoli, Alexander A. Davydov, Stefano Marcugini, Fernanda Pambianco

Let $\mathrm{PG}(3,q)$ be the projective space of dimension three over the finite field with $q$ elements. Consider a twisted cubic in $\mathrm{PG}(3,q)$. The structure of the point-plane incidence matrix in $\mathrm{PG}(3,q)$ with respect to the orbits of points and planes under the action of the stabilizer group of the twisted cubic is described. This info

Yunqiang Li, Wenjie Pei, Yufei zha, Jan van Gemert

Current massive datasets demand light-weight access for analysis. Discrete hashing methods are thus beneficial because they map high-dimensional data to compact binary codes that are efficient to store and process, while preserving semantic similarity. To optimize powerful deep learning methods for image hashing, gradient-based methods are required. Binary c

Lukas Mennel, Joanna Symonowicz, Stefan Wachter, Dmitry K. Polyushkin

In recent years, machine vision has taken huge leaps and is now becoming an integral part of various intelligent systems, including autonomous vehicles, robotics, and many others. Usually, visual information is captured by a frame-based camera, converted into a digital format, and processed afterwards using a machine learning algorithm such as an artificial

Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang

The pre-trained language models have achieved great successes in various natural language understanding (NLU) tasks due to its capacity to capture the deep contextualized information in text by pre-training on large-scale corpora. In this technical report, we present our practice of pre-training language models named NEZHA (NEural contextualiZed representati

Dmitry K. Polyushkin, Stefan Wachter, Lukas Mennel, Maksym Paliy

While digital electronics has become entirely ubiquitous in today's world and appears in the limelight, analogue electronics is still playing a crucial role in many devices and applications. Current analogue circuits are mostly manufactured using silicon as active material, but the ever present demand for improved performance, new devices and flexible integr

Jérôme Michon, Mohammed Benzaouia, Wenjie Yao, Owen D. Miller

The low efficiency of Raman spectroscopy can be overcome by placing the active molecules in the vicinity of scatterers, typically rough surfaces or nanostructures with various shapes. This surface-enhanced Raman scattering (SERS) leads to substantial enhancement that depends on the scatterer that is used. In this work, we find fundamental upper bounds on the

Lionel Nkenyereye, Lewis Nkenyereye, S M Riazul Islam, Yoon Ho Choi

There is a strong devotion in the automotive industry to be part of a wider progression towards the Fifth Generation (5G) era. In-vehicle integration costs between cellular and vehicle-to-vehicle networks using Dedicated Short Range Communication could be avoided by adopting Cellular Vehicle-to-Everything (C-V2X) technology with the possibility to re-use the