March 2020 arXiv papers — page 60

Claudia Kirch, Christina Stoehr

Sequential change point tests aim at giving an alarm as soon as possible after a structural break occurs while controlling the asymptotic false alarm error. For such tests it is of particular importance to understand how quickly a break is detected. While this is often assessed by simulations only, in this paper, we derive the asymptotic distribution of the

Ta Thi Hoai An, Nguyen Viet Phuong

In this paper, we will give suitable conditions on differential polynomials $Q(f)$ such that they take every finite non-zero value infinitely often, where $f$ is a meromorphic function in complex plane. These results are related to Problem 1.19 and Problem 1.20 in a book of Hayman and Lingham \cite{HL}. As consequences, we give a new proof of the Hayman conj

D. I. Zobnina, A. V. Zasov

A sample of 22 spiral galaxies compiled from published data is studied. The galaxy rotation curves pass through a maximum distance of more than $\sim 1$ kpc from the center with a subsequent decrease in the rotation velocity. The galaxy position in the Tully-Fisher (TF) and baryonic Tully-Fisher (BTF) diagrams show that the values of maximum rotation velocit

Suat Gumussoy

We present a numerical method to analyze the relative stability of closed-loop single-input-single-output (SISO) dead-time systems on a given left complex half-plane for all positive delays. The well-known boundary crossing method for the imaginary axis is extended to a given vertical line stability boundary in the complex plane for these type of systems. Th

Michele Kaufman, Bruce G. Elmegreen, Morten Andersen, Debra Meloy Elmegreen

New ALMA CO, HCO+, and 100 GHz continuum observations and Gemini NIFS K-band spectra are combined with previous radio to X-ray data to study Feature i, a highly luminous starburst clump on an outer arm of the interacting galaxy NGC 2207. This clump has an optically-opaque dust cone extending out of its 170 pc core. The measured CO accounts for the dark cone

Bruno Laurent

We classify almost homogeneous normal varieties of Albanese codimension $1$, defined over an arbitrary field. We prove that such a variety has a unique normal equivariant completion. Over a perfect field, the group scheme of automorphisms of this completion is smooth, except in one case in characteristic $2$, and we determine its (reduced) neutral component.

Gabriella Böhm, Joost Vercruysse

We introduce monoidal categories whose monoidal products of any positive number of factors are lax coherent and whose nullary products are oplax coherent. We call them $\mathsf{Lax}^+\mathsf{Oplax}^0$-monoidal. Dually, we consider $\mathsf{Lax}_0\mathsf{Oplax}_+$-monoidal categories which are oplax coherent for positive numbers of factors and lax coherent fo

Sándor P. Fekete, Linda Kleist, Dominik Krupke

We provide a comprehensive study of a natural geometric optimization problem motivated by questions in the context of satellite communication and astrophysics. In the problem Minimum Scan Cover with Angular Costs (MSC), we are given a graph $G$ that is embedded in Euclidean space. The edges of $G$ need to be scanned, i.e., probed from both of their vertices.

Varghese Babu, Deng Pan, Yuliang Jin, Bulbul Chakraborty

Granular packings display the remarkable phenomenon of dilatancy [1], wherein their volume increases upon shear deformation. Conventional wisdom and previous results suggest that dilatancy, as also the related phenomenon of shear-induced jamming, requires frictional interactions [2, 3]. Here, we investigate the occurrence of dilatancy and shear jamming in fr

Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Liujuan Cao

Referring expression comprehension (REC) and segmentation (RES) are two highly-related tasks, which both aim at identifying the referent according to a natural language expression. In this paper, we propose a novel Multi-task Collaborative Network (MCN) to achieve a joint learning of REC and RES for the first time. In MCN, RES can help REC to achieve better

Amanda Mesquita, Aline Vidotto

M dwarf stars are currently the main targets in searches for potentially habitable planets. However, their winds have been suggested to be harmful to planetary atmospheres. Here, in order to better understand the winds of M dwarfs and also infer their physical properties, we perform a one-dimensional magnetohydrodynamic parametric study of winds of M dwarfs

Vani K, Simone Mellace, Alessandro Antonucci

We present two deep learning approaches to narrative text understanding for character relationship modelling. The temporal evolution of these relations is described by dynamic word embeddings, that are designed to learn semantic changes over time. An empirical analysis of the corresponding character trajectories shows that such approaches are effective in de

Fang Zhu, Qian Zhang, Hao Chen, Guocheng Shi

Introduction: Internet technologies could strengthen data collection and integration and have been used extensively in public health research. It is necessary to apply this technology to further investigate the behaviour and health of biomedical researchers. A browser-based extension was developed by researchers and clinicians to promote the collection and a

Lei Fu, Daqing Wan

We deduce Katz's theorems for $(A,B)$-exponential sums over finite fields using $\ell$-adic cohomology and a theorem of Denef-Loeser, removing the hypothesis that $A+B$ is relatively prime to the characteristic $p$. In some degenerate cases, the Betti number estimate is improved using toric decomposition and Adolphson-Sperber's bound for the degree o

Shinya Fujita, Boram Park

An edge-colored connected graph $G$ is properly connected if between every pair of distinct vertices, there exists a path that no two adjacent edges have a same color. Fujita (2019) introduced the optimal proper connection number ${\mathrm{pc}_{\mathrm{opt}}}(G)$ for a monochromatic connected graph $G$, to make a connected graph properly connected efficientl

Ian D. Morris

One of the fundamental results of ergodic optimisation asserts that for any dynamical system on a compact metric space $X$ and for any Banach space of continuous real-valued functions on $X$ which embeds densely in $C(X)$ there exists a residual set of functions in that Banach space for which the maximising measure is unique. We extend this result by showing

Carlos Junqueira-Junior, João Luiz F. Azevedo, Jairo Panetta, William R. Wolf

Acoustics loads are rocket design constraints which push researches and engineers to invest efforts in the aeroacoustics phenomena which is present on launch vehicles. Therefore, an in-house computational fluid dynamics tool is developed in order to reproduce high-fidelity results of supersonic jet flows for aeroacoustic analogy applications. The solver is w

Konstantin Izyurov

We prove convergence of multiple interfaces in the critical planar q = 2 random cluster model, and provide an explicit description of the scaling limit. Remarkably, the expression for the partition function of the resulting multiple SLE(16/3) coincides with the bulk spin correlation in the critical Ising model in the half-plane, after formally replacing a po

Alberto Torres-Barrán, Carlos Alaíz, José R. Dorronsoro

We propose an improved version of the SMO algorithm for training classification and regression SVMs, based on a Conjugate Descent procedure. This new approach only involves a modest increase on the computational cost of each iteration but, in turn, usually results in a substantial decrease in the number of iterations required to converge to a given precision

V. I. Yukalov, E. P. Yukalova

A method of ultrafast switching of ferroelectric polarization is suggested. The method is based on the interaction of a ferroelectric sample with the feedback field of a resonator in which the sample is inserted. The polarization reversal time can be of order of femtoseconds. The polarization switching produces a coherent electromagnetic pulse.

M. Láska, A. O. Parry, A. Malijevský

We study the competition between local (bridging) and global condensation of fluid in a chemically heterogeneous capillary slit made from two parallel adjacent walls each patterned with a single stripe. Using a mesoscopic modified Kelvin equation, which determines the shape of the menisci pinned at the stripe edges in the bridge phase, we determine the condi

Yurii Belov, Alexander Borichev, Alexander Kuznetsov

We study the upper and the lower densities of complete and minimal Gabor Gaussians systems. In contrast to the classical lattice case when they are both equal to $1$, we prove that the lower density may reach $0$ while the upper density may vary at least from $\frac{1}π$ to $e$. In the case when the upper density exceeds $1$, we establish a sharp inequality

Benjamin Jourdain, Ezéchiel Kahn

The purpose of this paper is to study the existence and uniqueness of solutions to a Stochastic Differential Equation (SDE) coming from the eigenvalues of Wishart processes. The coordinates are non-negative, evolve as Cox-Ingersoll-Ross (CIR) processes and repulse each other according to a Coulombian like interaction force. We show the existence of strong an

V. Cerone, S. M. Fosson, D. Regruto

Boolean quadratic optimization problems occur in a number of applications. Their mixed integer-continuous nature is challenging, since it is inherently NP-hard. For this motivation, semidefinite programming relaxations (SDR's) are proposed in the literature to approximate the solution, which recasts the problem into convex optimization. Nevertheless, SDR

Laura G. Vivas, Rocio Yanes, Dmitry Berkov, Sergey Erokhin

In the quest to image the three-dimensional magnetization structure we show that the technique of magnetic small-angle neutron scattering (SANS) is highly sensitive to the details of the internal spin structure of nanoparticles. By combining SANS with numerical micromagnetic computations we study the transition from single-domain to multi-domain behavior in

Xinfeng Xu, Nahum Arav, Timothy Miller, Gerard A. Kriss

We present the analysis of two outflows (S1 at --5500 km s$^{-1}$ and S2 at --9700 km s$^{-1}$) seen in recent HST/COS observations of quasar SDSS J0755+2306 (z = 0.854). The outflows are detected as absorption troughs from both high-ionization species, including N III, O III, and S IV, and very high-ionization species, including Ar VIII, Ne VIII, and Na IX.

Timothy R. Miller, Nahum Arav, Xinfeng Xu, Gerard A. Kriss

We analyze absorption troughs from two outflows within PKS J0352-0711 (S1 at $-$1950 km s$^{-1}$ and S2 at $-$3150 km s$^{-1}$) from spectra taken with Hubble Space Telescope/Cosmic Origin Spectrograph, which cover the diagnostic-rich 585-900 Angstrom rest frame wavelength range. In S2, for the first time we clearly detect absorption troughs from Ca IV, Ca V

Xinfeng Xu, Nahum Arav, Timothy Miller, Gerard A. Kriss

We present an analysis of the broad absorption line (BAL) velocity shift that appeared in one of the outflow systems in quasar SDSS J1042+1646. Observations were taken by the Hubble Space Telescope/Cosmic Origin Spectrograph in 2011 and 2017 in the 500 -- 1050 $Å$ rest frame. The outflow's velocity centroid shifted by $\sim$ --1550 km s$^{-1}$ from --19,

Timothy R. Miller, Nahum Arav, Xinfeng Xu, Gerard A. Kriss

We detect four very energetic outflows in the Hubble Space Telescope/Cosmic Origin Spectrograph spectra of quasar 2MASS J1051+1247 with a combined kinetic luminosity ($\dot{E_k}$) of 10$^{46}$ erg s$^{-1}$. Remarkable similarities are seen in these outflows: velocity centroids between 4900 and 5700 km s$^{-1}$, distances from the central source ($R$) of a fe

Xinfeng Xu, Nahum Arav, Timothy Miller, Gerard A. Kriss

We present a study of the BAL outflows seen in quasar SDSS J1042+1646 (z = 0.978) in the rest-frame 500 -- 1050 $Å$ (EUV500) region. The results are based on the analysis of recent Hubble Space Telescope/Cosmic Origins Spectrograph observations. Five outflow systems are identified, where in total they include $\sim$70 outflow troughs from ionic transitions.

Nahum Arav, Xinfeng Xu, Timothy R. Miller, Gerard A. Kriss

The Hubble Space Telescope/Cosmic Origins Spectrograph (COS) has opened a new discovery space for studying quasar absorption outflows and their contribution to AGN feedback. Specifically, COS provides high-quality far-ultraviolet (FUV) spectra covering the diagnostic-rich 500-1050 Angstrom rest frame (hereafter, EUV500) of medium redshift objects. The qualit

Giuseppe Dattoli, Emanuele Di Palma, Silvia Licciardi, Elio Sabia

We employ methods largely exploited in Physics, in the analysis of the evolution of dynamical systems, to study the pattern of the Covid-19 infection in Italy. The techniques we employ are based on the use of logistic function and of its derivative, namely the Hubbert function. The latter is exploited to give a prediction on the number of infected per day. W

Tuhtasin Ergashev

Potentials play an important role in solving boundary value problems for elliptic equations. In the middle of the last century, a potential theory was constructed for a two-dimensional elliptic equation with one singular coefficient. In the study of potentials, the properties of the fundamental solutions of the given equation are essentially and fruitfully u

Matthias Lienert, Markus Nöth

Here we consider an integral equation describing a fixed number of scalar particles which interact not through boson exchange but directly along light cones, similarly as in bound state equations such as the Bethe-Salpeter equation. The equation involves a multi-time wave function $ψ(x_1,...,x_N)$ with $x_i=(t_i,\mathbf{x}_i) \in \mathbb{R}^4$ as a crucial c

Viraj Kulkarni, Milind Kulkarni, Aniruddha Pant

Federated learning enables machine learning models to learn from private decentralized data without compromising privacy. The standard formulation of federated learning produces one shared model for all clients. Statistical heterogeneity due to non-IID distribution of data across devices often leads to scenarios where, for some clients, the local models trai

Doru Constantin

In 1993, Nallet, Laversanne and Roux put forward a simplified model for the intensity scattered by lamellar phases, which was nonetheless very successfully used in fitting experimental results, especially those obtained with powder systems. I argue that the success as well as the simple expression of the model result from an approximate integration over samp

Tanjung Krisnanda

Quantum entanglement is a form of correlation between quantum particles that has now become a crucial part in quantum information and communication science. For example, it has been shown to enable or enhance quantum processing tasks such as quantum cryptography, quantum teleportation, and quantum computing. However, quantum entanglement is prone to decohere

F. F. Karpeshin, M. B. Trzhaskovskaya, L. F. Vitushkin

Latest experimental data on the properties of the 229Th nuclide isomer are analyzed. Deduced are the lifetime and the E2-fraction in its electromagnetic deexcitation, based on the latest experimental data concerning the isomer: its energy together with the magnetic and quadrupole moments.

H. C. Manjunatha, K. N. Sridhar

We have constructed new proximity function particularly for interaction between two superheavy nuclei based on the experimental alpha decay half-lives. The new proximity function is used to produce the alpha decay half-lives of superheavy nuclei whose experimental values are known. The new proximity function produces the alpha decay half-lives close to the e

Raffaele Mosca

The Maximum Weight Independent Set Problem (WIS) is a well-known NP-hard problem. A popular way to study WIS is to detect graph classes for which WIS can be solved in polynomial time, with particular reference to hereditary graph classes, i.e., defined by a hereditary graph property or equivalently by forbidding one or more induced subgraphs. Given two graph

Khanh N. Dang, Akram Ben Ahmed, Abderazek Ben Abdallah, Xuan-Tu Tran

By combining Three Dimensional Integrated Circuits with the Network-on-Chip infrastructure to obtain 3D Networks-on-Chip (3D-NoCs), the new on-chip communication paradigm brings several advantages on lower power, smaller footprint and lower latency. However, thermal dissipation is one of the most critical challenges for 3D-ICs where the heat cannot easily tr

Sebastian Meiling, Thomas C. Schmidt

Inter-connected sensors and actuators have scaled down to small embedded devices such as wearables, and at the same time meet a massive deployment at the Internet edge: the Internet of Things (IoT). Many of these IoT devices run on low-power batteries and are forced to operate on very constrained resources, namely slow CPUs, tiny memories, and low-power radi

Akash Kumar, Arnav Bhavsar

With the arrival of several face-swapping applications such as FaceApp, SnapChat, MixBooth, FaceBlender and many more, the authenticity of digital media content is hanging on a very loose thread. On social media platforms, videos are widely circulated often at a high compression factor. In this work, we analyze several deep learning approaches in the context

Marcellin Atemkeng, Patrice M. Okouma, Eric Maina, Roger Ianjamasimanana

In the African continent, South Africa has world-class astronomical facilities for advanced radio astronomy research. With the advent of the Square Kilometre Array project in South Africa (SA SKA), six countries in Africa (SA SKA partner countries) have joined South Africa to contribute towards the African Very Long Baseline Interferometry (VLBI) Networks (A

F. Marin, D. Hutsemékers

Context: Variations in the mass accretion rate appear to be responsible for the rapid transitions in spectral type that are observed in increasingly more active galactic nuclei (AGNs). These objects are now labeled "changing-look" AGNs and are key objects for understanding the physics of accretion onto supermassive black holes. Aims: We aim to comple

Osamu Shouno

Recent advances in deep learning have significantly improved performance of video prediction. However, state-of-the-art methods still suffer from blurriness and distortions in their future predictions, especially when there are large motions between frames. To address these issues, we propose a deep residual network with the hierarchical architecture where e

Erwin Quiring, Konrad Rieck

Backdoors and poisoning attacks are a major threat to the security of machine-learning and vision systems. Often, however, these attacks leave visible artifacts in the images that can be visually detected and weaken the efficacy of the attacks. In this paper, we propose a novel strategy for hiding backdoor and poisoning attacks. Our approach builds on a rece

Stéphane André, Simon Becker, Camille Noûs, Laurent Farge

A study of methodological nature demonstrates the efficiency of a probation test allowing for the intrinsic character of a rheological constitutive law to be assessed. Such a law is considered here for Semi-Crystalline Polymers exhibiting necking and for large deformation. In the framework of a $(\dotσ, σ, \dot\varepsilon, \varepsilon)$ behavior's law, t

An Zhao, Mingyu Ding, Zhiwu Lu, Tao Xiang

Existing few-shot learning (FSL) methods make the implicit assumption that the few target class samples are from the same domain as the source class samples. However, in practice this assumption is often invalid -- the target classes could come from a different domain. This poses an additional challenge of domain adaptation (DA) with few training samples. In

Guantao Chen, Xing Feng, Fuliang Lu, Cláudio L. Lucchesi

An edge cut $C$ of a graph $G$ is {\it tight} if $|C \cap M|=1$ for every perfect matching $M$ of $G$.~Barrier cuts and 2-separation cuts are called {\it ELP-cuts}, which are two important types of tight cuts in matching covered graphs.~Edmonds, Lovász and Pulleyblank proved that if a matching covered graph has a nontrivial tight cut, then it also has a nont

Chanh Minh Tran, Tho Nguyen Duc, Phan Xuan Tan, Eiji Kamioka

HTTP/2 video streaming has caught a lot of attentions in the development of multimedia technologies over the last few years. In HTTP/2, the server push mechanism allows the server to deliver more video segments to the client within a single request in order to deal with the requests explosion problem. As a result, recent research efforts have been focusing o

Hossein S. Ghadikolaei, Hadi Ghauch, Gabor Fodor, Mikael Skoglund

Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inter-operator

Hui Tang, Ke Chen, Kui Jia

Unsupervised domain adaptation (UDA) is to make predictions for unlabeled data on a target domain, given labeled data on a source domain whose distribution shifts from the target one. Mainstream UDA methods learn aligned features between the two domains, such that a classifier trained on the source features can be readily applied to the target ones. However,

Brent A. Kenney, Arslan J. Majid, Hussein Moradi, Behrouz Farhang-Boroujeny

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a promising solution for futuristic 6G ultra-reliable low latency communications (URLLC) and massive machine type communication (mMTC) applications. We propose that in such applications, the CP-DSSS waveform would operate as a secondary network at the same frequencies as the primary network but at mu

Kudaibergen Urinbayev, Yerassyl Orazbek, Yernur Nurambek, Almas Mirzakhmetov

In this work, we present an end-to-end deep learning framework for X-ray image diagnosis. As the first step, our system determines whether a submitted image is an X-ray or not. After it classifies the type of the X-ray, it runs the dedicated abnormality classification network. In this work, we only focus on the chest X-rays for abnormality classification. Ho

Deepak Singla, Soham Chatterjee, Lavanya Ramapantulu, Andres Ussa

Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area. While neuromorphic vision sensors (NVS) may offer advantages over traditional imagers in this domain, the existing NVS systems either do not meet the power constraints or have not demonstrated end-to-end system performance. To address this,

Zhen Zheng, Z. D. Wang

Motivated by recent experimental advances in ultracold atomic gases placed in cavities, we study the influence of the atom-cavity coupling on the Fermi gases trapped in optical lattices. By adiabatic elimination of the cavity photon field, the atom-cavity coupling gives rise to effective long-range interactions. It results in a variety of two-body scattering

Yuhei Iwata, Tomoharu Oka, Masato Tsuboi, Makoto Miyoshi

A radio source at the Galactic center Sgr A* is a prime supermassive black hole candidate and therefore key to developing our understanding of them. Time variations in the 230 GHz band flux of Sgr A* have been found with the Atacama Large Millimeter/submillimeter Array (ALMA) Cycle 5 observations. Measuring the flux density of Sgr A* in 1 min snapshots at 21

Qin Chang, Xiao-Lin Wang, Jie Zhu, Xiao-Nan Li

In this paper, we investigate the tree-dominated $\bar{B}^*_{u,d,s,c} \to V \ell^- \barν_\ell$ ($V=D^*_{u,d}\,,D^*_s\,,J/ψ$ and $\ell=e\,,μ\,,τ$) decays in the Standard Model with the relevant form factors obtained in the light-front quark model. These decays involve much more helicity states relative to the corresponding $\bar{B}^* \to P \ell^- \barν_\ell$

Brent A. Kenney, Stephen N. Jenkins, Arslan J. Majid, Hussein Moradi

Cyclic Prefix Direct Sequence Spread Spectrum (CP-DSSS) is a novel waveform that is proposed as a solution to massive machine type communications (mMTC) for 5G and beyond. This paper analyzes the capacity of CP-DSSS in comparison with Orthogonal Frequency-Division Multiplexing (OFDM). We show that CP-DSSS achieves the same capacity as OFDM and can be optimiz

Zijian Wang, Wen Chen

In this paper, we consider a dual-hop Multiple Input Multiple Output (MIMO) wireless multi-relay network, in which a source-destination pair both equipped with multiple antennas communicates through multiple half-duplex amplify-and-forward (AF) relay terminals which are also with multiple antennas. Since perfect channel state information (CSI) is difficult t

Baha Rababah, Srija Srivastava

With the increasing number of new attacks on ever growing network traffic, it is becoming challenging to alert immediately any malicious activities to avoid loss of sensitive data and money. This is making intrusion detection as one of the major areas of concern in network security. Anomaly based network intrusion detection technique is one of the most commo

Makarov R. V., Nasibullin R. G

This paper is devoted to Hardy type inequalities with remainders for compactly supported smooth functions on open sets in the Euclidean space. We establish new inequalities with weight functions depending on the distance function to the boundary of the domain. One-dimensional $L_1$ and $L_p$ inequalities and their multidimensional analogues are proved. We co

Shubham Agrawal, Anuj Pahuja, Simon Lucey

What's the most accurate 3D model of your face you can obtain while sitting at your desk? We attempt to answer this question in our work. High fidelity face reconstructions have so far been limited to either studio settings or through expensive 3D scanners. On the other hand, unconstrained reconstruction methods are typically limited by low-capacity mode

Xin Chen, Zhen-Qing Chen, Takashi Kumagai, Jian Wang

This paper studies homogenization of symmetric non-local Dirichlet forms with $α$-stable-like jumping kernels in one-parameter stationary ergodic environment. Under suitable conditions, we establish homogenization results and identify the limiting effective Dirichlet forms explicitly. The coefficients of the jumping kernels of Dirichlet forms and symmetrizin

Jungwoon Shin

A variety of real-world systems can be modeled as bipartite networks. One of the most powerful and simple link prediction methods is Linear-Graph Autoencoder(LGAE) which has promising performance on challenging tasks such as link prediction and node clustering. LGAE relies on simple linear model w.r.t. the adjacency matrix of the graph to learn vector space

Yuzo Maruyama, William E. Strawderman

We study admissibility of a subclass of generalized Bayes estimators of a multivariate normal vector when the variance is unknown, under scaled quadratic loss. Minimaxity is also established for certain of these estimators.

Shanwei Ding, Guanghan Li

In this paper, we consider an expanding flow of closed, smooth, uniformly convex hypersurface in Euclidean \mathbb{R}^{n+1} with speed u^αf^β(α, β\in\mathbb{R}^1), where u is support function of the hypersurface, f is a smooth, symmetric, homogenous of degree one, positive function of the principal curvature radii of the hypersurface. If α\leq 0<β\leq 1-α, w

Burt Totaro

We determine the mod p cohomological invariants for several affine group schemes G in chararacteristic p. These are invariants of G-torsors with values in etale motivic cohomology, or equivalently in Kato&#39;s version of Galois cohomology based on differential forms. In particular, we find the mod 2 cohomological invariants for the symmetric groups and the

Zi Cai, Congjun Wu

In this paper, we study the itinerant ferromagnetic phase in multi-component fermionic systems with symplectic (Sp(4), or isomorphically SO(5)) symmetry. Two different microscopic models have been considered and an effective field theory has been proposed to study the critical behavior of the nonmagnetism-magnetism phase transition. It has been shown that su

Wenjin Wang, Yunqing Hu, Yin Zhang

Lifelong learning remains an open problem. One of its main difficulties is catastrophic forgetting. Many dynamic expansion approaches have been proposed to address this problem, but they all use homogeneous models of predefined structure for all tasks. The common original model and expansion structures ignore the requirement of different model structures on

Donghuan Lu, Sujun Zhao, Peng Xie, Kai Ma

Neuron reconstruction is essential to generate exquisite neuron connectivity map for understanding brain function. Despite the significant amount of effect that has been made on automatic reconstruction methods, manual tracing by well-trained human annotators is still necessary. To ensure the quality of reconstructed neurons and provide guidance for annotato

Xuerun Chen

In agent control issues, the idea of combining reinforcement learning and planning has attracted much attention. Two methods focus on micro and macro action respectively. Their advantages would show together if there is a good cooperation between them. An essential for the cooperation is to find an appropriate boundary, assigning different functions to each

Parag Agrawal, Tulasi Menon, Aya Kamel, Michel Naim

Having a bot for seamless conversations is a much-desired feature that products and services today seek for their websites and mobile apps. These bots help reduce traffic received by human support significantly by handling frequent and directly answerable known questions. Many such services have huge reference documents such as FAQ pages, which makes it hard

Hiroyuki Hirashita, Thiem Hoang

Interstellar dust grains can be spun up by radiative torques, and the resulting centrifugal force may be strong enough to disrupt large dust grains. We examine the effect of this rotational disruption on the evolution of grain size distribution in galaxies. To this goal, we modify our previous model by assuming that rotational disruption is the major small-g

Naoyuki Itagaki, Tokuro Fukui, Akihiro Tohsaki

We aim to describe the cluster states of nuclear systems starting with a realistic interaction, which is a challenge of modern nuclear theories. Here, the short-range correlation of realistic interaction is treated by employing the damping factor, and the resultant interaction can be applied to the cluster structure of light nuclei. We start with a realistic

Ken Furukawa, Naoto Kajiwara

In this paper we consider maximal regularity for the vector-valued quasi-steady linear elliptic problems. The equations are the elliptic equation in the domain and the evolution equations on its boundary. We prove the maximal $L_p$-$L_q$ regularity for these problems and give examples that our results are applicable. The Lopatinskii--Shapiro and the asymptot

B. S. M. Barros, E. V. de Souza

In this paper we present in a theoretical, historical and practical way the inclusion of gravitational waves in the teaching of physics. Through the explanation of the theme through debates and experimental practices in the classroom, we discuss the presence of Modern and Contemporary Physics (MCP) in High School, presenting positive points and showing above

Oleg Galkin, Svetlana Galkina

The functions of the Takagi exponential class are similar in construction to the continuous, nowhere differentiable Takagi function described in 1901. They have one real parameter $v\in (-1;1)$ and at points $x\in{\mathbb R}$ are defined by the series $T_v(x) = \sum_{n=0}^\infty v^n T_0(2^nx)$, where $T_0(x)$ is the distance between $x$ and the nearest integ

Tianyi Zhang, Yun Gu, Xiaolin Huang, Enmei Tu

With the popularity of stereo cameras in computer assisted surgery techniques, a second viewpoint would provide additional information in surgery. However, how to effectively access and use stereo information for the super-resolution (SR) purpose is often a challenge. In this paper, we propose a disparity-constrained stereo super-resolution network (DCSSRnet

Shota Ono

Polonium is known as the only simple metal that has the simple cubic (SC) lattice in three dimension. There is a debate about whether the stabilized SC structure is attributed to the scalar relativistic effect or the spin-orbit coupling (SOC). Here, we study another phase, two-dimensional (2D) polonium (poloniumene), by performing density-functional theory c

Hanlin Zhu, Xue Li, Liuyang Sun, Fei He

Across many areas, from neural tracking to database entity resolution, manual assessment of clusters by human experts presents a bottleneck in rapid development of scalable and specialized clustering methods. To solve this problem we develop C-FAR, a novel method for Fast, Automated and Reproducible assessment of multiple hierarchical clustering algorithms s

Michael Chesser, Asangi Jayatilaka, Renuka Visvanathan, Christophe Fumeaux

Falls have serious consequences and are prevalent in acute hospitals and nursing homes caring for older people. Most falls occur in bedrooms and near the bed. Technological interventions to mitigate the risk of falling aim to automatically monitor bed-exit events and subsequently alert healthcare personnel to provide timely supervisions. We observe that freq

Yi-An Lai, Xuan Zhu, Yi Zhang, Mona Diab

Summarizing data samples by quantitative measures has a long history, with descriptive statistics being a case in point. However, as natural language processing methods flourish, there are still insufficient characteristic metrics to describe a collection of texts in terms of the words, sentences, or paragraphs they comprise. In this work, we propose metrics

Helge Ruddat, Ilia Zharkov

This is an announcement of the following construction: given an integral affine manifold $B$ with singularities, we build a topological space $X$ which is a torus fibration over $B$. The main new feature of the fibration $X\to B$ is that it has the discriminant in codimension 2.

Mateusz Krukowski

The primary aim of the paper is the study of Sobolev spaces in the context of Gelfand pairs. The article commences with providing a historical overview and motivation for the researched subject together with a summary of the current state of the literature. What follows is a general outline of harmonic analysis on Gelfand pairs, starting with a concept of po

Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia

Building home assistant robots has long been a pursuit for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable. Existing environments achieve these requirements for robotics simulation with different levels o

Gökhan Yildirim, Debashis Sen, Mohan Kankanhalli, Sabine Süsstrunk

Salient object detection is evaluated using binary ground truth with the labels being salient object class and background. In this paper, we corroborate based on three subjective experiments on a novel image dataset that objects in natural images are inherently perceived to have varying levels of importance. Our dataset, named SalMoN (saliency in multi-objec

Marko Aunedi, Tim Green

A whole-system, investment-optimising model has been used to examine the change in total cost of meeting demand for electricity when Smart Local Energy Systems (SLES) are deployed. Our assumption is that SLES, alongside their other features, enhance the flexibility of electricity consumption through demand-side response (DSR) and facilitate use of local ener

Hoa Van Nguyen, Michael Chesser, Lian Pin Koh, S. Hamid Rezatofighi

Autonomous aerial robots provide new possibilities to study the habitats and behaviors of endangered species through the efficient gathering of location information at temporal and spatial granularities not possible with traditional manual survey methods. We present a novel autonomous aerial vehicle system-TrackerBots-to track and localize multiple radio-tag

Ruigang Wang, Roland Tóth, Patrick J. W. Koelwijn, Ian R. Manchester

This paper presents a systematic approach to nonlinear state-feedback control design that has three main advantages: (i) it ensures exponential stability and $ \mathcal{L}_2 $-gain performance with respect to a user-defined set of reference trajectories, and (ii) it provides constructive conditions based on convex optimization and a path-integral-based contr

Amee Trivedi, Jeremy Gummeson, Prashant Shenoy

Understanding the mobility of humans and their devices is a fundamental problem in mobile computing. While there has been much work on empirical analysis of human mobility using mobile device data, prior work has largely assumed devices to be independent and has not considered the implications of modern Internet users owning multiple mobile devices that exhi

Francesco Capozzi, Eleonora Di Valentino, Eligio Lisi, Antonio Marrone

We revisit our previous work [Phys. Rev. D 95, 096014 (2017)] where neutrino oscillation and nonoscillation data were analyzed in the standard framework with three neutrino families, in order to constrain their absolute masses and to probe their ordering (either normal, NO, or inverted, IO). We include updated oscillation results to discuss best fits and all

D. A. Palken, B. M. Brubaker, M. Malnou, S. Al Kenany

In experiments searching for axionic dark matter, the use of the standard threshold-based data analysis discards valuable information. We present a Bayesian analysis framework that builds on an existing processing protocol to extract more information from the data of coherent axion detectors such as operating haloscopes. The analysis avoids logical subtletie

Zhongxiang Wang, Yi Xing, Jujia Zhang, Konstantina Boutsia

4FGL J0935.3+0901 is a gamma-ray source detected by the Large Area Telescope (LAT) onboard the Fermi Gamma-Ray Space Telescope. We have conducted detailed analysis of the LAT data for this source and multi-wavelength studies of the source field. Its gamma-ray emission can be described with a power law ($\Gamma=2.0\pm0.2$) with an exponential cutoff ($E_c=2.9

Steven I. Reeves, Dongwook Lee, Adam Reyes, Carlo Graziani

We present a new polynomial-free prolongation scheme for Adaptive Mesh Refinement (AMR) simulations of compressible and incompressible computational fluid dynamics. The new method is constructed using a multi-dimensional kernel-based Gaussian Process (GP) prolongation model. The formulation for this scheme was inspired by the GP methods introduced by A. Reye

Danfeng Li, Bai Yang Wang, Kyuho Lee, Shannon P. Harvey

We report the phase diagram of Nd$_{1-x}$Sr$_x$NiO$_2$ infinite layer thin films grown on SrTiO$_3$. A superconducting dome spanning $0.125 < x < 0.25$ is found, remarkably similar to cuprates, albeit over a narrower doping window. However, while cuprate superconductivity is bounded by an insulator for underdoping and a metal for overdoping, here we observe

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods. In this paper, we take a closer look at the field to see if this is actually true. We find flaws in the experimental methodology of numerous metric learning papers, and show that the actual

Susanne C. Brenner, Li-yeng Sung, Winnifried Wollner

We consider a one dimensional elliptic distributed optimal control problem with pointwise constraints on the derivative of the state. By exploiting the variational inequality satisfied by the derivative of the optimal state, we obtain higher regularity for the optimal state under appropriate assumptions on the data. We also solve the optimal control problem

Yakov Pesin, Samuel Senti, Farruh Shahidi

We show that any surface admits an area preserving $C^{1+\beta}$ diffeomorphism with non-zero Lyapunov exponents which is Bernoulli and has polynomial decay of correlations. We establish both upper and lower polynomial bounds on correlations. In addition, we show that this diffeomorphism satisfies the Central Limit Theorem and has the Large Deviation Propert