December 2020 arXiv papers — page 143

Y. J. Li, F. Jin, Z. Y. Mi, J. Guo

We report structural and physical properties of the single crystalline ${\mathrm{Ca}}{\mathrm{Mn}}_{2}{\mathrm{P}}_{2}$. The X-ray diffraction(XRD) results show that ${\mathrm{Ca}}{\mathrm{Mn}}_{2}{\mathrm{P}}_{2}$ adopts the trigonal ${\mathrm{Ca}}{\mathrm{Al}}_{2}{\mathrm{Si}}_{2}$-type structure. Temperature dependent electrical resistivity $ρ(T)$ measure

Manuel Perger, Guillem Anglada-Escudé, Ignasi Ribas, Albert Rosich

Accounting for the effects of stellar magnetic phenomena is indispensable to fully exploit radial velocities (RVs). Correlated time variations are often mitigated by Gaussian processes (GP). They rely on fitting kernel functions that are motivated on mathematical grounds, and whose physical interpretation is often elusive. We aim to establish a connection be

Michael E. Cuffaro, Emerson P. Doyle

This is an extended essay review of Tanya and Jeffrey Bub's Totally Random: Why Nobody Understands Quantum Mechanics: A serious comic on entanglement. Princeton and Oxford: Princeton University Press (2018), ISBN: 9780691176956, 272 pp., 7x10 in., 254 b/w illus., £18.99 / $22.95 (paperback). We review the philosophical aspects of the book, provide sugges

Mi Jiang, George A. Sawatzky, Mona Berciu, Steven Johnston

Bismuth perovskites ABiO$_3$ (A = Sr, Ba) host a variety of peculiar phenomena including bond-disproportionated insulating phases and high-temperature superconductivity upon hole doping. While the mechanisms underlying these phenomena are still debated, off-diagonal electron-phonon ($e$-ph) coupling originating from the modulation of the orbital overlaps has

Krzysztof Ptaszynski

I present an approach to calculate the finite-frequency quantum noise in systems strongly coupled to structured reservoirs based on the Markovian embedding. This technique consists of mapping of the non-Markovian dynamics of the original system onto the Markovian dynamics of the extended supersystem. The applicability of this method is demonstrated on a sing

Youcheng Xi, Jie Ren, Liang Wang, Song Fu

This study performs global stability/receptivity analyses of hypersonic sweep flows around a blunt body with an infinite span. For the first time, we obtain the characteristics of the leading attachment-line mode to the variation of sweep angles from 20 to 70 degrees. The global eigenfunctions exhibit the characteristics of the attachment-line instability at

Ross Drummond, Stephen R. Duncan

Growing demand for fast charging and optimised battery designs is fuelling significant interest in electrochemical models of Li-ion batteries. However, estimating parameter values for these models remains a major challenge. In this paper, a structural identifiability analysis was applied to a pseudo-2D Li-ion electrochemical battery model that can be conside

Grzegorz Plebanek

We present a connected version of the compact $L$-space constructed by Kenneth Kunen under CH. We show that this provides a Corson compact space $K$ such that the Banach space $C(K)$ is isomorphic to no space of continuous function on a zero-dimensional compactum.

Bert Cox, Chesney Buyle, Liesbet Van der Perre, Lieven De Strycker

We present a hybrid signaling approach to position energy-neutral devices. Our method combines the best of two worlds: instant RF signals for both communication and energy transfer, and slower propagating acoustic waves for accurate distance measurements. We introduce advanced energy loading of an 'E-buffer' through beamformed RF signals. The scienti

Linh Anh Nguyen

Like bisimulations, simulations and directed simulations are used for analyzing graph-based structures such as automata, labeled transition systems, linked data networks, Kripke models and interpretations in description logic. Simulations characterize the class of existential modal formulas, whereas directed simulations characterize the class of positive mod

Jorge Mello

We give effective bounds for the set quasi-integral points in orbits of non-isotrivial rational maps over function fields under some conditions, generalizing previous work of Hsia and Silverman (2011) for orbits over function fields of characteristic zero. We then use this to prove finiteness results for algebraic functions whose orbit under a rational funct

Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami

Unsupervised Domain Adaptation (UDA) aims to bridge the gap between a source domain, where labelled data are available, and a target domain only represented with unlabelled data. If domain invariant representations have dramatically improved the adaptability of models, to guarantee their good transferability remains a challenging problem. This paper addresse

K. Ross, J. R. Callingham, N. Hurley-Walker, N. Seymour

Spectral variability of radio sources encodes information about the conditions of intervening media, source structure, and emission processes. With new low-frequency radio interferometers observing over wide fractional bandwidths, studies of spectral variability for a large population of extragalactic radio sources are now possible. Using two epochs of obser

Haotian Shi, Yang Zhou, Keshu Wu, Xin Wang

This paper proposes a cooperative strategy of connected and automated vehicles (CAVs) longitudinal control for partially connected and automated traffic environment based on deep reinforcement learning (DRL) algorithm, which enhances the string stability of mixed traffic, car following efficiency, and energy efficiency. Since the sequences of mixed traffic a

Haohan Guo, Heng Lu, Na Hu, Chunlei Zhang

This paper describes an end-to-end adversarial singing voice conversion (EA-SVC) approach. It can directly generate arbitrary singing waveform by given phonetic posteriorgram (PPG) representing content, F0 representing pitch, and speaker embedding representing timbre, respectively. Proposed system is composed of three modules: generator $G$, the audio genera

Aaron Labdon, John D. Monnier, Stefan Kraus, Jean-Baptiste Le Bouquin

In this contribution we report on our work to increase the spectral range of the Michigan Infrared Combiner-eXeter (MIRC-X) instrument at the CHARA array to allow for dual H and J band interferometric observations. We comment on the key science drivers behind this project and the methods of characterisation and correction of instrumental birefringence and di

Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki, Tatsuaki Hashimoto

In this paper, we present a novel image inpainting technique using frequency domain information. Prior works on image inpainting predict the missing pixels by training neural networks using only the spatial domain information. However, these methods still struggle to reconstruct high-frequency details for real complex scenes, leading to a discrepancy in colo

Ramy Rashad, Federico Califano, Frederic P. Schuller, Stefano Stramigioli

Part I of this paper presented a systematic derivation of the Stokes Dirac structure underlying the port-Hamiltonian model of ideal fluid flow on Riemannian manifolds. Starting from the group of diffeomorphisms as a configuration space for the fluid, the Stokes Dirac structure is derived by Poisson reduction and then augmented by boundary ports and distribut

Jan Strohschein, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke

This paper presents the cognitive module of the cognitive architecture for artificial intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipel

Taras Bodnar, Mathias Lindholm, Vilhelm Niklasson, Erik Thorsén

We study the optimal portfolio allocation problem from a Bayesian perspective using value at risk (VaR) and conditional value at risk (CVaR) as risk measures. By applying the posterior predictive distribution for the future portfolio return, we derive relevant quantiles needed in the computations of VaR and CVaR, and express the optimal portfolio weights in

Ramy Rashad, Federico Califano, Frederic P. Schuller, Stefano Stramigioli

In this two-parts paper, we present a systematic procedure to extend the known Hamiltonian model of ideal inviscid fluid flow on Riemannian manifolds in terms of Lie-Poisson structures to a port-Hamiltonian model in terms of Stokes-Dirac structures. The first novelty of the presented model is the inclusion of non-zero energy exchange through, and within, the

Siu Wun Cheung, Eric Chung, Yalchin Efendiev, Wing Tat Leung

In this paper, we develop an iterative scheme to construct multiscale basis functions within the framework of the Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM) for the mixed formulation. The iterative procedure starts with the construction of an energy minimizing snapshot space that can be used for approximating the s

Sara R. Machado

I estimate the semi-elasticity of blood donations with respect to a monetary benefit, namely the waiver of user fees when using the National Health Service, in Portugal. Using within-county variation over time in the value of the benefitI estimate both the unconditional elasticity, which captures overall response of the market, and the conditional elasticity

Raphael Bialon

The Android operating system runs on the majority of smartphones nowadays. Its success is driven by its availability to a variety of smartphone hardware vendors on the one hand, and the customization possibilities given to its users on the other hand. While other big smartphone operating systems restrict user configuration to a given set of functionality, An

Harold Berjamin, Michel Destrade, William J. Parnell

Originating in the field of biomechanics, Fung's model of quasi-linear viscoelasticity (QLV) is one of the most popular constitutive theories employed to compute the time-dependent relationship between stress and deformation in soft solids. It is one of the simplest models of nonlinear viscoelasticity, based on a time-domain integral formulation. In the

Tolga Altinoluk, Néstor Armesto, Alex Kovner, Michael Lublinsky

Within the dense-dilute Color Glass Condensate approach, and using the Golec-Biernat-Wuesthoff model for the dipole scattering amplitude, we calculate $v_2^2$ as well as the correlations between $v_2^2$ and both the total multiplicity and the mean transverse momentum of produced particles. We find that the correlations are generally very small consistent wit

Eaman Eftekhary

We address the problem of counting periodic orbits of vector fields on smooth closed manifolds. The space of non-constant periodic orbits is enlarged to a complete space by adding the ghost orbits, which are decorations of the zeros of vector fields. Associated with any compact and open subset $Γ$ of the moduli space of periodic and ghost orbits, we define a

Fernando de S. Bastos, Wagner Barreto-Souza, Marc G. Genton

Many proposals have emerged as alternatives to the Heckman selection model, mainly to address the non-robustness of its normal assumption. The 2001 Medical Expenditure Panel Survey data is often used to illustrate this non-robustness of the Heckman model. In this paper, we propose a generalization of the Heckman sample selection model by allowing the sample

Gilles Callebaut, Sara Gunnarsson, Andrea P. Guevara, Fredrik Tufvesson

Low-Power Wide-Area Networks operating in the unlicensed bands are being deployed to connect a rapidly growing number of Internet-of-Things devices. While the unlicensed sub-GHz band offers favorable propagation for long-range connections, measurements show that the energy consumption of the nodes is still mostly dominated by the wireless transmission affect

Zizhen Zhou, Dewei Chu, Claudio Cazorla

Epitaxially grown SrTiO$_{3}$ (STO) thin films are material enablers for a number of critical energy-conversion and information-storage technologies like electrochemical electrode coatings, solid oxide fuel cells and random access memories. Oxygen vacancies (${\rm V_{O}}$), on the other hand, are key defects to understand and tailor many of the unique functi

A. V. Leontyev, D. K. Zharkov, D. P. Pavlov, N. N. Garig'yanov

The effect of green and ultraviolet laser light on Ba$_{0.8}$Sr$_{0.2}$TiO$_3$/LaMnO$_3$ heterostructure electrical resistance was studied. In 80-200 K range illumination induces transient resistance component at ~15% of the steady-state value, the time constant associated with the transient component is ~12 s. The negative photoresistance effect is found un

K. P. Singh, G. Stewart, S. Chandra, G. C. Dewangan

We present observations of four bright stars observed with the AstroSat Soft X-ray Telescope (SXT). Visible light from bright stars like these can leak through the very thin filter in front of the CCD in the focal plane CCD camera of the SXT and thus making the extraction of X-ray events difficult. Here, we show how to extract the X-ray events without contam

Christoffer Lundman, Andrei Beloborodov

We present the first ab initio simulation of a radiation-mediated shock emerging at the photosphere of a relativistic outflow. The simulation is performed using our code radshock that follows fluid dynamics coupled to time-dependent radiative transfer, calculated with the Monte-Carlo method. We use the code to examine the radiative blast wave emerging from n

Erwin Frey, Fridtjof Brauns

These notes are an account of a series of lectures given at the Les Houches Summer School "Active Matter and Non-equilibrium Statistical Physics" during August and September 2018.

Henrik Lundell, Chloé Najac, Marjolein Bulk, Hermien E. Kan

Double diffusion encoding (DDE) magnetic resonance measurements of the water signal offers a unique ability to separate the effect of microscopic anisotropic diffusion in structural units of tissue from the overall macroscopic orientational distribution of cells. However, the specificity in detected microscopic anisotropy is limited as the signal is averaged

Petros Ioannidis, Lina Eklund, Anders Sundnes Løvlie

In this article, we present a lifecycle study of We Dare You, a Substitutional Reality (SR) installation that combines visual and tactile stimuli. The installation is set up in a center for architecture, and invites visitors to explore its facade while playing with vertigo, in a visual Virtual Reality (VR) environment that replicates the surrounding physical

Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser

Federated learning (FL) is one of the most important paradigms addressing privacy and data governance issues in machine learning (ML). Adversarial training has emerged, so far, as the most promising approach against evasion threats on ML models. In this paper, we take the first known steps towards federated adversarial training (FAT) combining both methods t

Niu Wan, Takayuki Myo, Chang Xu, Hiroshi Toki

By using bare Argonne V4' (AV4'), V6' (AV6'), and V8' (AV8') nucleon-nucleon (NN) interactions respectively, the nuclear equations of state (EOSs) for neutron matter are calculated with the unitary correlation operator and high-momentum pair methods. The neutron matter is described under a finite particle number approach with magic nu

Gianluca Tirimbó, Onur Çaylak, Björn Baumeier

We present a Kernel Ridge Regression (KRR) based supervised learning method combined with Genetic Algorithms (GAs) for the calculation of quasiparticle energies within Many-Body Green's Functions Theory. These energies representing electronic excitations of a material are solutions to a set of non-linear equations, containing the electron self-energy (SE

Su Yao, S. Komossa

3C 286 is a well-known calibrator source in radio astronomy. It is also one of very few compact steep-spectrum sources (CSS) detected in $γ$-rays. Here, we perform a detailed spectroscopic and variability analysis and present the first quasi-simultaneous optical to X-ray spectral energy distribution in order to reveal physical mechanisms which dominate its e

John Cai, Bill Cai, Sheng Mei Shen

While many deep learning methods have seen significant success in tackling the problem of domain adaptation and few-shot learning separately, far fewer methods are able to jointly tackle both problems in Cross-Domain Few-Shot Learning (CD-FSL). This problem is exacerbated under sharp domain shifts that typify common computer vision applications. In this pape

Thomas Gessey-Jones, Colm Connaughton, Robin Dunbar, Ralph Kenna

Network science and data analytics are used to quantify static and dynamic structures in George R.R. Martin's epic novels, A Song of Ice and Fire, works noted for their scale and complexity. By tracking the network of character interactions as the story unfolds, it is found that structural properties remain approximately stable and comparable to real-wor

Zheng Yuan, Jie Zhang, Shiguang Shan, Xilin Chen

Recent studies have shown remarkable success in face image generations. However, most of the existing methods only generate face images from random noise, and cannot generate face images according to the specific attributes. In this paper, we focus on the problem of face synthesis from attributes, which aims at generating faces with specific characteristics

Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu

We study a general class of contextual bandits, where each context-action pair is associated with a raw feature vector, but the reward generating function is unknown. We propose a novel learning algorithm that transforms the raw feature vector using the last hidden layer of a deep ReLU neural network (deep representation learning), and uses an upper confiden

Lavinia Ghirardini, Eva A. A. Pogna, Giancarlo Soavi, Andrea Tomadin

Graphene is an ideal material for integrated nonlinear optics thanks to its strong light-matter interaction and large nonlinear optical susceptibility. Graphene has been used in optical modulators, saturable absorbers, nonlinear frequency converters, and broadband light emitters. For the latter application, a key requirement is the ability to control and eng

Michael Fischer, Konstantin Kobs, Andreas Hotho

Fully- or semi-automatic image enhancement software helps users to increase the visual appeal of photos and does not require in-depth knowledge of manual image editing. However, fully-automatic approaches usually enhance the image in a black-box manner that does not give the user any control over the optimization process, possibly leading to edited images th

Toan Duc Bui, Manh Nguyen, Ngan Le, Khoa Luu

Image synthesis from corrupted contrasts increases the diversity of diagnostic information available for many neurological diseases. Recently the image-to-image translation has experienced significant levels of interest within medical research, beginning with the successful use of the Generative Adversarial Network (GAN) to the introduction of cyclic constra

Alexandr Malijevský

Adsorption of liquid on a planar wall decorated by a hydrophilic stripe of width $L$ is considered. Under the condition, that the wall is only partially wet (or dry) while the stripe tends to be wet completely, a liquid drop is formed above the stripe. The maximum height $\ell_m(δμ)$ of the drop depends on the stripe width $L$ and the chemical potential depa

Darshan Gandhi, Rohan Sukumaran, Priyanshi Katiyar, Alex Radunsky

The COVID-19 Pandemic has left a devastating trail all over the world, in terms of loss of lives, economic decline, travel restrictions, trade deficit, and collapsing economy including real-estate, job loss, loss of health benefits, the decline in quality of access to care and services and overall quality of life. Immunization from the anticipated vaccines w

Frédéric Chapoton, Christian Krattenthaler, Jiang Zeng

We explore some connections between moments of rescaled little q-Jacobi polynomials, q-analogues of values at negative integers for some Dirichlet series, and the q-Eulerian polynomials of wreath products of symmetric groups.

Adil Ahmed Chowdhury, Farida Chowdhury, Md Sadek Ferdous

The Government of Bangladesh is aggressively transforming its public service landscape by transforming public services into online services via a number of websites. The motivation is that this would be a catalyst for a transformative change in every aspect of citizen life. Some web services must be protected from any unauthorised usages and passwords remain

David A. Kessler, Eli Barkai, Klaus Ziegler

We solve for the statistics of the first detection of a quantum system in a particular desired state, when the system is subject to a projective measurement at independent identically distributed random time intervals. We present formulas for the probability of detection in the $n$th attempt. We calculate as well the mean and mean square both of the number o

Serge Cantat, Romain Dujardin

We study finite orbits for non-elementary groups of automorphisms of compact projective surfaces. In particular we prove that if the surface and the group are defined over a number field k and the group contains parabolic elements, then the set of finite orbits is not Zariski dense, except in certain very rigid situations, known as Kummer examples. Related r

Elie Aïdékon, Yueyun Hu, Zhan Shi

The classical Ray-Knight theorems for Brownian motion determine the law of its local time process either at the first hitting time of a given value a by the local time at the origin, or at the first hitting time of a given position b by Brownian motion. We extend these results by describing the local time process jointly for all a and all b, by means of stoc

Alain Couret, David Reyes, Marc Thomas, Nicolas Ratel-Ramond

The effects of ageing at 800 $^\circ$C on the properties of the IRIS alloy (Ti$_{49.9}$Al$_{48}$W$_2$B$_{0.1}$) are studied. The initial microstructure of this alloy densified by Spark Plasma Sintering (SPS) is mainly composed of lamellar colonies which are surrounded by $γ$ grains. The evolutions of the alloy strength and creep resistance resulting from thi

Kaixiang Chen, Chufan Zhang, Xiaoxian Zang, Fuyuan Ma

Graphene is an attractive material for broadband photodetection but suffers from weak light absorption. Coating graphene with quantum dots can significantly enhance light absorption and create extraordinarily high photo gain. This high gain is often explained by the classical gain theory which is unfortunately an implicit function and may even be questionabl

Jiajing He, Kaixiang Chen, Chulin Huang, Xiaoming Wang

Photoconductors based on semiconducting thin films, nanowires and 2-dimensional atomic layers have been extensively investigated. But there is no explicit photogain equation that allows for fitting and designing photoresponses of these devices. In this work, we managed to derive explicit photogain equations for silicon nanowire photoconductors based on exper

Prithwiraj Bhattacharjee, Avi Mallick, Md Saiful Islam, Marium-E-Jannat

Abstractive summarization is the process of generating novel sentences based on the information extracted from the original text document while retaining the context. Due to abstractive summarization's underlying complexities, most of the past research work has been done on the extractive summarization approach. Nevertheless, with the triumph of the sequ

Takuya Sakamoto

This study presents the progress of our recent research regarding wireless measurements of the human body. First, we explain radar imaging algorithms for screening passengers at security checkpoints that can process data faster than existing algorithms to generate accurate and high-resolution images of human bodies. Second, we introduce signal processing tec

Jiangtao Nie, Lei Zhang, Wei Wei, Zhiqiang Lang

Despite the great success of deep model on Hyperspectral imagery (HSI) super-resolution(SR) for simulated data, most of them function unsatisfactory when applied to the real data, especially for unsupervised HSI SR methods. One of the main reason comes from the fact that the predefined degeneration models (e.g. blur in spatial domain) utilized by most HSI SR

Kumar Ashutosh, Saurabh Kumar, Subhasis Chaudhuri

We present a classification based approach for the next best view selection and show how we can plausibly obtain a supervisory signal for this task. The proposed approach is end-to-end trainable and aims to get the best possible 3D reconstruction quality with a pair of passively acquired 2D views. The proposed model consists of two stages: a classifier and a

K. Otsuka, N. Fang, D. Yamashita, T. Taniguchi

When continued device scaling reaches the ultimate limit imposed by atoms, technology based on atomically precise structures is expected to emerge. Device fabrication will then require building blocks with identified atomic arrangements and assembly of the components without contamination. Here we report on a versatile dry transfer technique for deterministi

Boya Xie, Sheng Feng

Nonlocality as a fundamental aspect of quantum mechanics is witnessed by violation of Bell inequality or its variants, for which all relevant studies assume some correlations exhibited by local realistic theories. The strategy of Bell's theorem is to establish some criteria to distinguish local realistic theories from quantum mechanics with respect to th

Louis H Kauffman

The purpose of this paper is to give a new basis for examining the relationships of the Affine Index Polynomial and the Sawollek Polynomial. Blake Mellor has written a pioneering paper showing how the Affine Index Polynomial may be extracted from the Sawollek Polynomial. The Affine Index Polynomial is an elementary combinatorial invariant of virtual knots. T

Marcin J. Skwark, Nicolás López Carranza, Thomas Pierrot, Joe Phillips

The SARS-CoV-2 pandemic has created a global race for a cure. One approach focuses on designing a novel variant of the human angiotensin-converting enzyme 2 (ACE2) that binds more tightly to the SARS-CoV-2 spike protein and diverts it from human cells. Here we formulate a novel protein design framework as a reinforcement learning problem. We generate new des

Tomohiro Mori, Akimasa Kataoka

Dust polarization at (sub)millimeter wavelengths has been observed for many protoplanetary disks. Theoretically, multiple origins potentially contribute to the polarized emission but it is still uncertain what mechanism is dominant in disk millimeter polarization. To quantitatively address the origin, we perform radiative transfer calculations of the mixture

Jaime Maldonado, Christoph Zetzsche

In this paper we investigate human-to-robot skill transfer based on the identification of prototypical task executions by clustering a set of examples performed by human demonstrators, where smoothness and kinematic features represent skill and task performance, respectively. We exemplify our skill transfer approach with data from an experimental task in whi

Tongkeun Chang, Minsuk Yang

We study the initial-boundary value problem of the stochastic Navier--Stokes equations in the half space. We prove the existence of weak solutions in the standard Besov space valued random processes when the initial data belong to the critical Besov space.

J. Honolka, S. Krotzky, M. Menzel, T. Herden

The noncollinear magnetic state of epitaxial Mn monolayers on tungsten (110) crystal surfaces is investigated by means of soft x-ray absorption spectroscopy, to complement earlier spin-polarized STM experiments. X-ray absorption spectra (XAS), x-ray linear dichroism (XLD) and x-ray magnetic circular dichroism (XMCD) Mn L23-edge spectra were measured in the t

Li Zhang, Xinyue Chen, Zihao Zhou, Cheng-Xiang Wang

In this paper, a multi-frequency multi-link three-dimensional (3D) non-stationary wideband multiple-input multiple-output (MIMO) channel model is proposed. The spatial consistency and multi-frequency correlation are considered in parameters initialization of every single-link and different frequencies, including large scale parameters (LSPs) and small scale

Yingzhuo Sun, Cheng-Xiang Wang, Jie Huang, Jun Wang

As one of the key technologies for the sixth generation (6G) mobile communications, intelligent reflecting surface IRS) has the advantages of low power consumption, low cost, and simple design methods. But channel modeling is still an open issue in this field currently. In this paper, we propose a three-dimensional (3D) geometry based stochastic model (GBSM)

Satoshi Miyazaki, Yuji Hattori

Neural networks of simple structures are used to construct a turbulence model for large-eddy simulation (LES). Data obtained by direct numerical simulation (DNS) of homogeneous isotropic turbulence are used to train neural networks. It is shown that two methods are effective for improvement of accuracy of the model: weighting data for training and addition o

Anthony Tang, Ravi Sankar Vaddi, Alexander Mamishev, Igor Novosselov

Dielectric Barrier Discharge (DBD) plasma actuators with an asymmetric, straight edge electrode configuration generate a wall-bounded jet without moving parts. Mechanistic description of the interaction between the Coulombic forces and fluid motion as a function of DBD parameters remains unclear. This paper presents an experimental investigation of DBD actua

Mikio Eto, Rui Sakano

We theoretically examine the transport through an Aharonov-Bohm ring with an embedded quantum dot (QD), the so-called QD interferometer, to address two controversial issues regarding the shape of the Coulomb peaks and measurement of the transmission phase shift through a QD. We extend a previous model [B. R. Bulka and P. Stefanski, Phys. Rev. Lett. 86, 5128

Xiaozheng Chen, Xueliang Li

Let $G$ be a graph of order $n$ with an edge-coloring $c$, and let $δ^c(G)$ denote the minimum color-degree of $G$. A subgraph $F$ of $G$ is called rainbow if any two edges of $F$ have distinct colors. There have been a lot results in the existing literature on rainbow triangles in edge-colored complete graphs. Fujita and Magnant showed that for an edge-colo

V. V. Vien, H. N. Long

A multiscalar and nonrenormalizable $B-L$ extension of the standard model (SM) with $S_4$ symmetry which successfully explains the recent observed neutrino oscillation data is proposed. The tiny neutrino masses and their hierarchies are generated via the type-I seesaw mechanism. The model reproduces the recent experiments of neutrino mixing angles and Dirac

Kohji Matsumoto, Ilija Tanackov

In the present series of papers, we study the behavior of the r-fold zeta-function of Euler-Zagier type with identical arguments on the real line. In this first part, we consider the behavior on the interval [0,1]. Our basic tool is an "infinite" version of Newton's classical identities. We carry out numerical computations, and draw graphs for re

Elham J. Barezi, Iacer Calixto, Kyunghyun Cho, Pascale Fung

Extreme classification tasks are multi-label tasks with an extremely large number of labels (tags). These tasks are hard because the label space is usually (i) very large, e.g. thousands or millions of labels, (ii) very sparse, i.e. very few labels apply to each input document, and (iii) highly correlated, meaning that the existence of one label changes the

M. Millea, C. M. Daley, T-L. Chou, E. Anderes

We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg$^2$ of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 $μ$K-arcmin in polarization, which are low enough that

Sadaf Salehkalaibar, Mohammad Hossein Yassaee, Vincent Y. F. Tan, Mehrasa Ahmadipour

We consider fundamental limits for communicating over a compound channel when the state of the channel needs to be masked. Our model is closely related to an area of study known as covert communication that is a setting in which the transmitter wishes to communicate to legitimate receiver(s) while ensuring that the communication is not detected by an adversa

Kush Bhatia, Karthik Sridharan

We study the problem of online learning with dynamics, where a learner interacts with a stateful environment over multiple rounds. In each round of the interaction, the learner selects a policy to deploy and incurs a cost that depends on both the chosen policy and current state of the world. The state-evolution dynamics and the costs are allowed to be time-v

Zhengyuan Liu, Ke Shi, Nancy F. Chen

Text discourse parsing plays an important role in understanding information flow and argumentative structure in natural language. Previous research under the Rhetorical Structure Theory (RST) has mostly focused on inducing and evaluating models from the English treebank. However, the parsing tasks for other languages such as German, Dutch, and Portuguese are

Debasis Bhowmick, Siddhartha Dechoudhury, Vaishali Naik, Alok Chakrabarti

We report here an empirical formalism for predicting the cross-sections of neutron-rich nuclei produced in fragmentation of relativistic \b{eta}-unstable neutron-rich projectiles in the mid-mass region. The formalism is based on the abrasion-ablation picture of the projectile fragmentation reaction. It has been shown that the formalism can accurately reprodu

Han Qiu, Yi Zeng, Tianwei Zhang, Yong Jiang

It is extensively studied that Deep Neural Networks (DNNs) are vulnerable to Adversarial Examples (AEs). With more and more advanced adversarial attack methods have been developed, a quantity of corresponding defense solutions were designed to enhance the robustness of DNN models. It has become a popularity to leverage data augmentation techniques to preproc

Seunghan Yang, Hyoungseob Park, Junyoung Byun, Changick Kim

Federated learning is a paradigm that enables local devices to jointly train a server model while keeping the data decentralized and private. In federated learning, since local data are collected by clients, it is hardly guaranteed that the data are correctly annotated. Although a lot of studies have been conducted to train the networks robust to these noisy

Wei Kang, Qi Gong

As demonstrated in many areas of real-life applications, neural networks have the capability of dealing with high dimensional data. In the fields of optimal control and dynamical systems, the same capability was studied and verified in many published results in recent years. Towards the goal of revealing the underlying reason why neural networks are capable

Gregory Tanyi, Miao Sun, Ranjith Unnithan

We present a plasmonic modulator based on hybrid orthogonal silver junctions using vanadium dioxide as the modulating material on the silicon on insulator. The modulator has an ultra-compact footprint of 1.8μm x 1μm with a 100nm x 100nm modulating section based on the orthogonal geometry. We take advantage of large change in the refractive index of vanadium

Mohit Sharma, Oliver Kroemer

To determine if a skill can be executed in any given environment, a robot needs to learn the preconditions for the skill. As robots begin to operate in dynamic and unstructured environments, precondition models will need to generalize to variable number of objects with different shapes and sizes. In this work, we focus on learning precondition models for man

Sara Ahmadian, Shahrzad Haddadan

Social networks have become an inseparable part of human life and processing them in an efficient manner is a top priority in the study of networks. These networks are highly dynamic and they are growing incessantly. Inspired by the concept of triadic closure, we propose a probabilistic mechanism to model the evolution of these dynamic graphs. Although triad

Genta Indra Winata, Guangsen Wang, Caiming Xiong, Steven Hoi

One crucial challenge of real-world multilingual speech recognition is the long-tailed distribution problem, where some resource-rich languages like English have abundant training data, but a long tail of low-resource languages have varying amounts of limited training data. To overcome the long-tail problem, in this paper, we propose Adapt-and-Adjust (A2), a

Zhen Zeng, Jianzong Wang, Ning Cheng, Jing Xiao

Recent neural vocoders usually use a WaveNet-like network to capture the long-term dependencies of the waveform, but a large number of parameters are required to obtain good modeling capabilities. In this paper, an efficient network, named location-variable convolution, is proposed to model the dependencies of waveforms. Different from the use of unified con

Kai Zhang, Jingwen Wu, Di Li, Chao-Wei Tsai

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) has started the Commensal Radio Astronomy FasT Survey (CRAFTS). In this paper, we use the technical parameters of FAST derived from commissioning observations to simulate the completeness function for extragalactic HI survey of CRAFTS, HI galaxies from two kinds of mock catalogues are selected.

M. Miniya, O. Oubram, A. G. Reynaud Morales, I. Rodriguez-Vargas

Thermoelectric effects have attracted wide attention in recent years from physicists and engineers. In this work, we explore the selfsimilar patterns in the thermoelectric effects of monolayer graphene based structures, by using the quantum relativistic Dirac equation. The transfer matrix method has been used to calculate the transmission coefficient. The La

Tsz Ho Chan, Jared Duker Lichtman, Carl Pomerance

A set of positive integers is primitive (or 1-primitive) if no member divides another. Erdős proved in 1935 that the weighted sum $\sum1/(n \log n)$ for $n$ ranging over a primitive set $A$ is universally bounded over all choices for $A$. In 1988 he asked if this universal bound is attained by the set of prime numbers. One source of difficulty in this conjec

Chuan-Chi Wang, Ying-Chiao Liao, Chia-Heng Tu, Ming-Chang Kao

The rapid advancements of computing technology facilitate the development of diverse deep learning applications. Unfortunately, the efficiency of parallel computing infrastructures varies widely with neural network models, which hinders the exploration of the design space to find high-performance neural network architectures on specific computing platforms f

Zhi-Guo Liu

The Kronecker theta function is a quotient of the Jacobi theta functions, which is also a special case of Ramanujan's $_1ψ_1$ summation. Using the Kronecker theta function as building blocks, we prove a decomposition theorem for theta functions. This decomposition theorem is the common source of a large number of theta function identities. Many striking

Masashige Matsumoto

It is known that the longitudinal and transverse excitation modes can exist in the vicinity of a quantum critical point in the ordered phase of quantum magnetic systems. The total moment sum rule for such systems is derived on the basis of the extended spin-wave theory, where both longitudinal and transverse magnetic excitations are taken into account. The s

Qiaohua Liu, Qian Zhang, Dongmei Shen

A new closed formula for the first order perturbation estimate of the mixed least squares-total least squares (MTLS) solution is presented. It is mathematically equivalent to the one by Zheng and Yang(Numer. Linear Algebra Appl. 2019; 26(4):e2239). With this formula, general and structured normwise, mixed and componentwise condition numbers of the MTLS probl

Othmane Safsafi

We study a new type of random minimum spanning trees. It is built on the complete graph where each vertex is given a weight, which is a positive real number. Then, each edge is given a capacity which is a random variable that only depends on the product of the weights of its endpoints. We then study the minimum spanning tree corresponding to the edge capacit

Gia S. Wulandari, Detlef Plump

We consider Hoare-style verification for the graph programming language GP 2. In previous work, graph properties were specified by so-called E-conditions which extend nested graph conditions. However, this type of assertions is not easy to comprehend by programmers that are used to formal specifications in standard first-order logic. In this paper, we presen