April 2020 arXiv papers — page 28

Hongyan Sun, Hua-Ming Wang

Consider a nearest-neighbor random walk with certain asymptotically zero drift on the positive half line. Let $M$ be the maximum of an excursion starting from $1$ and ending at $0.$ We study the distribution of $M$ and characterize its asymptotics, which is quite different from those of simple random walks.

Víctor M. Pérez-García, O. León-Triana, M. Rosa, A. Pérez-Martínez

Immunotherapy has the potential to change the way all cancer types are treated and cured. Cancer immunotherapies use elements of the patient immune system to attack tumor cells. One of the most successful types of immunotherapy is CAR-T cells. This treatment works by extracting patient's T-cells and adding to them an antigen receptor allowing tumor cells to

Hai-Tian Wang, Peng-Cheng Li, Jin-Liang Jiang, Guan-Wen Yuan

Testing black hole's charged property is a fascinating topic in modified gravity and black hole astrophysics. In the first Gravitational-Wave Transient Catalog (GWTC-1), ten binary black hole merger events have been formally reported, and these gravitational wave signals have significantly enhanced our understanding of the black hole. In this paper, we try t

Sepideh Sadegh, Julian Matschinske, David B. Blumenthal, Gihanna Galindez

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. It was first identified in Wuhan, China, and has since spread causing a global pandemic. Various studies have been performed to understand the molecular mechanisms of viral infection for predicting drug repurposing candidates. However, such information is spread acro

Asmita Bhandare, Rolf Kuiper, Thomas Henning, Christian Fendt

Stars form as an end product of the gravitational collapse of cold, dense gas in magnetized molecular clouds. This multi-scale scenario occurs via the formation of two quasi-hydrostatic cores and involves complex physical processes, which require a robust, self-consistent numerical treatment. The aim of this study is to understand the formation and evolution

Kannabiran Seshasayanan, Vassilios Dallas, Stephan Fauve

We study the primary bifurcations of a two-dimensional Kolmogorov flow in a channel subject to boundary conditions chosen to mimic a parallel flow, i.e. periodic and free-slip boundary conditions in the streamwise and spanwise directions, respectively. The control parameter is the Reynolds number based on the friction coefficient, denoted as $Rh$. We find th

Hongwei Tang, Jean Rabault, Alexander Kuhnle, Yan Wang

This paper focuses on the active flow control of a computational fluid dynamics simulation over a range of Reynolds numbers using deep reinforcement learning (DRL). More precisely, the proximal policy optimization (PPO) method is used to control the mass flow rate of four synthetic jets symmetrically located on the upper and lower sides of a cylinder immerse

Ahmet Emir, Ferdi Kara, Hakan Kaya

Non-Orthogonal Multiple Access (NOMA) has higher spectral efficiency than orthogonal multiple access (OMA) techniques. In uplink communication systems that the channel is not known at the receiver, pilot signals sent from each user in different time intervals have reduced the spectral efficiency of NOMA. In this study, in the uplink communication system, DL-

Cheng-Jian Xiao, Yu-Bing Dong, Thomas Gutsche, Valery E. Lyubovitskij

Recent lattice QCD calculations showed that a $d_{N\Omega}$ dibaryon state similar to the deuteron with small binding energy may exist. In this work we propose a hadronic molecular approach to study the dynamical properties of this exotic state. We use a phenomenological Lagrangian approach to describe the coupling of the $d_{N\Omega}$ state to its constitue

Yanmeng Shi, Shuigang Xu, Mohammed M. Al Ezzi, Nilanthy Balakrishnan

Understanding and tuning correlated states is of great interest and significance to modern condensed matter physics. The recent discovery of unconventional superconductivity and Mott-like insulating states in magic-angle twisted bilayer graphene (tBLG) presents a unique platform to study correlation phenomena, in which the Coulomb energy dominates over the q

Camille Noûs, Urko Reinosa, Julien Serreau, Rodrigo Carmo Terin

We investigate the generation of a gluon screening mass in Yang-Mills theory in the Landau gauge. We propose a gauge-fixing procedure where the Gribov ambiguity is overcome by summing over all Gribov copies with some weight function. This can be formulated in terms of a local field theory involving constrained, nonlinear sigma model fields. We show that a ph

Ziyou Song, Fanny Pinto Delgado, Jun Hou, Heath Hofmann

Fault diagnosis is extremely important to the safe operation of Lithium-ion batteries. To avoid severe safety issues (e.g., thermal runaway), initial faults should be timely detected and resolved. In this paper, we consider parallel-connected battery cells with only one voltage and one current sensor. The lack of independent current sensors makes it difficul

Yazeed Alharbi, Peter Wonka

We explore different design choices for injecting noise into generative adversarial networks (GANs) with the goal of disentangling the latent space. Instead of traditional approaches, we propose feeding multiple noise codes through separate fully-connected layers respectively. The aim is restricting the influence of each noise code to specific parts of the g

Enrique Andjel, Inés Armendáriz, Milton Jara

We provide two methods to construct zero-range processes with superlinear rates on ${\mathbb Z}^d$. In the first method these rates can grow very fast, if either the dynamics and the initial distribution are translation invariant or if only nearest neigbour translation invariant jumps are permitted, in the one-dimensional lattice. In the second method the ra

Akihiko Ikeda, Yasuhiro H. Matsuda, Xuguang Zhou, Takeshi Yajima

Single shot x-ray diffraction (XRD) experiments have been performed with a x-ray free electron laser (XFEL) under pulsed high magnetic fields up to 16 T generated with a nondestructive minicoil. The antiferromagnetic insulator phase in a perovskite manganaite, Pr$_{0.6}$Ca$_{0.4}$MnO$_{3}$, is collapsed at a magnetic field of $\approx 8$ T with an emergence

Alexey Ananyevskiy

We show that a triangulated motivic category admits categorical Thom isomorphisms for vector bundles with an additional structure if and only if the generalized motivic cohomology theory represented by the tensor unit object admits Thom classes. We also show that the stable $\mathbb{A}^1$-derived category does not admit Thom isomorphisms for oriented vector

Daomin Cao, Weilin Yu, Changjun Zou

We study the 2D Euler equation in a bounded simply-connected domain, and establish the local uniqueness of flow whose stream function $\psi_\varepsilon$ satisfies \begin{equation*} \begin{cases} -\varepsilon^2\Delta \psi_\varepsilon=\sum\limits_{i=1}^k \mathbf1_{B_\delta(z_{0,i})}(\psi_\varepsilon-\mu_{\varepsilon,i})_+^\gamma,\ \ \ & \text{in} \ \Omega, \ps

Ferdi Kara, Hakan Kaya

Non-orthogonal multiple access (NOMA) has attracted great recent attention due to its high spectral efficiency. Besides, NOMA can be easily implemented in physical layer, thus its interplays with other psychical layer techniques have been analyzed widely by researches. Cooperative NOMA schemes are the most investigated among these interplays. However, these

Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi

We present an efficient method of utilizing pretrained language models, where we learn selective binary masks for pretrained weights in lieu of modifying them through finetuning. Extensive evaluations of masking BERT and RoBERTa on a series of NLP tasks show that our masking scheme yields performance comparable to finetuning, yet has a much smaller memory fo

C. P. Vyasarayani, Anindya Chatterjee

We take up a recently proposed compartmental SEIQR model with delays, ignore loss of immunity in the context of a fast pandemic, extend the model to a network structured on infectivity, and consider the continuum limit of the same with a simple separable interaction model for the infectivities $\beta$. Numerical simulations show that the evolving dynamics of

Debasish Koner, Max Schwilk, Sarbani Patra, Evan J. Bieske

The fundamentals and higher vibrationally excited states for the N$_3^+$ ion in its electronic ground state have been determined from quantum bound state calculations on 3-dimensional potential energy surfaces (PESs) at the CCSD(T)-F12 and MRCI+Q levels of theory. The vibrational fundamentals are at 1130 cm$^{-1}$ ($\nu_1$, symmetric stretch), 807 cm$^{-1}$

Ansgar Fehnker, Hubert Garavel

This volume contains the proceedings of MARS 2020, the fourth workshop on Models for Formal Analysis of Real Systems held as part of ETAPS 2020, the European Joint Conferences on Theory and Practice of Software. The MARS workshop brings together researchers from different communities who are developing formal models of real systems in areas where complex mod

Ferdi Kara, Hakan Kaya

Non-orthogonal multiple access (NOMA) is very promising for future wireless systems thanks to its spectral efficiency. In NOMA schemes, the effect of imperfect successive interference canceler (SIC) has dominant effect on the error performances. In addition to this imperfect SIC effect, the error performance will get worse with the channel estimation errors

Li Huang, Haiyan Lu

Ce$_{3}$Al is an archetypal heavy-fermion compound with multiple crystalline phases. Here, we try to investigate its electronic structures in the hexagonal phase ($\alpha$-Ce$_{3}$Al) and cubic phase ($\beta$-Ce$_{3}$Al) by means of a combination of density functional theory and single-site dynamical mean-field theory. We confirm that the 4$f$ valence electr

Fabrizio Cipollini, Giampiero M. Gallo, Alessandro Palandri

We build the time series of optimal realized portfolio weights from high-frequency data and we suggest a novel Dynamic Conditional Weights (DCW) model for their dynamics. DCW is benchmarked against popular model-based and model-free specifications in terms of weights forecasts and portfolio allocations. Next to portfolio variance, certainty equivalent and tu

Jerry Zikun Chen

Generalization remains a challenging problem for deep reinforcement learning algorithms, which are often trained and tested on the same set of deterministic game environments. When test environments are unseen and perturbed but the nature of the task remains the same, generalization gaps can arise. In this work, we propose and evaluate a surprise minimizing

Evagoras Xydas, Konstantinos Kostas

Researchers have shown that even simple empirical models stemming from biological growth modeling have the potential to provide useful information on the development and severity of ongoing epidemics since they can be employed as tools for carrying out projections on the size of the affected population, timing of turning points, as well as best- and worst-ca

Yuta Kusakabe

We solve fundamental problems in Oka theory by establishing an implicit function theorem for sprays. As the first application of our implicit function theorem, we obtain an elementary proof of the fact that approximation yields interpolation. This proof and L\'{a}russon's elementary proof of the converse give an elementary proof of the equivalence between ap

Sera Markoff, David M. Russell, Jason Dexter, Oliver Pfuhl

Infrared interferometry is a new frontier for precision ground based observing, with new instrumentation achieving milliarcsecond (mas) spatial resolutions for faint sources, along with astrometry on the order of 10 microarcseconds. This technique has already led to breakthroughs in the observations of the supermassive black hole at the Galactic centre and i

Akihiko Ikeda, Yasuhiro H. Matsuda, Keisuke Sato

We report a magnetostriction study of a perovskite $\rm{LaCoO}_{3}$ above 100 T using our state-of-the-art strain gauge to investigate an interplay between electron correlations and spin crossover. There has been a controversy regarding whether two novel phases in $\rm{LaCoO}_{3}$ at high magnetic fields result from crystallizations or Bose-Einstein condensa

Thomas Krabichler, Josef Teichmann

This article introduces a new mathematical concept of illiquidity that goes hand in hand with credit risk. The concept is not volume- but constraint-based, i.e., certain assets cannot be shorted and are ineligible as num\'eraire. If those assets are still chosen as num\'eraire, we arrive at a two-price economy. We utilise Jarrow & Turnbull's foreign exchange

Karl J. Friston, Thomas Parr, Peter Zeidman, Adeel Razi

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several of these (epidemic) models to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity--and the exchange of people between regions--and how mortality rates can be

Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu

As a crucial step in extractive document summarization, learning cross-sentence relations has been explored by a plethora of approaches. An intuitive way is to put them in the graph-based neural network, which has a more complex structure for capturing inter-sentence relationships. In this paper, we present a heterogeneous graph-based neural network for extr

Thomas Krabichler, Josef Teichmann

We consider a financial market with zero-coupon bonds that are exposed to credit and liquidity risk. We revisit the famous Jarrow & Turnbull setting in order to account for these two intricately intertwined risk types. We utilise the foreign exchange analogy that interprets defaultable zero-coupon bonds as a conversion of non-defaultable foreign counterparts

Guo-yuan Huang, Newton Nath

The T2K collaboration has recently reported their results, which gives the best-fit values of the atmospheric mixing angle $\sin^2 \theta_{23} = 0.53$ and the Dirac CP-violating phase $\delta = -1.89$ for normal neutrino mass ordering. We give a possible theoretical origin of such values based on the $\mu$-$\tau$ reflection symmetry. It has been found that t

Nikolaos Panagiotis Souris

Riemannian geodesic orbit spaces (G/H,g) are natural generalizations of symmetric spaces, defined by the property that their geodesics are orbits of one-parameter subgroups of G. We study the geodesic orbit spaces of the form (G/S,g), where G is a compact, connected, semisimple Lie group and S is abelian. We give a simple geometric characterization of those

Keyu Yang, Yunjun Gao, Lei Liang, Song Bian

Sentiment classification is a fundamental task in content analysis. Although deep learning has demonstrated promising performance in text classification compared with shallow models, it is still not able to train a satisfying classifier for text sentiment. Human beings are more sophisticated than machine learning models in terms of understanding and capturin

Po-Ming Law, Sana Malik, Fan Du, Moumita Sinha

While decision makers have begun to employ machine learning, machine learning models may make predictions that bias against certain demographic groups. Semi-automated bias detection tools often present reports of automatically-detected biases using a recommendation list or visual cues. However, there is a lack of guidance concerning which presentation style

Zoé-Lise Deck-Léger, Xuezhi Zheng, Christophe Caloz

This paper extends current knowledge on electromagnetic wave scattering from bounded moving media in several regards. First, it complements the usual dispersion relation of moving media, $\omega(\theta_\mathbf{k})$ ($\theta_\mathbf{k}$: phase velocity direction, associated with the wave vector, $\mathbf{k}$), with the equally important impedance relation, $\

Goro Akagi, Christian Kuehn, Ken-Ichi Nakamura

Constrained gradient flows are studied in fracture mechanics to describe strongly irreversible (or unidirectional) evolution of cracks. The present paper is devoted to a study on the long-time behavior of non-compact orbits of such constrained gradient flows. More precisely, traveling wave dynamics for a one-dimensional fully nonlinear Allen-Cahn type equati

Qiuling Xu, Guanhong Tao, Siyuan Cheng, Xiangyu Zhang

We propose a new adversarial attack to Deep Neural Networks for image classification. Different from most existing attacks that directly perturb input pixels, our attack focuses on perturbing abstract features, more specifically, features that denote styles, including interpretable styles such as vivid colors and sharp outlines, and uninterpretable ones. It

Dunzhao Wei, Pengcheng Chen, Xiaopeng Hu, Yipeng Zhang

Laguerre-Gaussian (LG) modes, carrying orbital angular momentum of light, are critical for important applications such as high-capacity optical communications, super-resolution imaging, and multi-dimensional quantum entanglement. Advanced developments in these applications strongly demand reliable and tunable LG mode laser sources, which, however, do not yet

Sergio Albeverio, Hiroshi Kawabi, Stefan-Radu Mihalache, Michael Roeckner

We consider space-time quantum fields with exponential/trigonometric interactions. In the context of Euclidean quantum field theory, the former and the latter are called the Hoegh-Krohn model and the Sine-Gordon model, respectively. The main objective of the present paper is to construct infinite dimensional diffusion processes which solve modified stochasti

Roman Korolev, Francisco S. N. Lobo, Sergey V. Sushkov

In this work, we consider the full Horndeski Lagrangian applied to wormhole geometries and present the full gravitational field equations. We analyse the general constraints imposed by the flaring-out conditions at the wormhole throat and consider a plethora of specific subclasses of the Horndeski Lagrangian, namely, quintessence/phantom fields, $k$-essence,

Xiangdong Zhang, Tengjun Wang, Yun Yang

Because hyperspectral remote sensing images contain a lot of redundant information and the data structure is highly non-linear, leading to low classification accuracy of traditional machine learning methods. The latest research shows that hyperspectral image classification based on deep convolutional neural network has high accuracy. However, when a small am

Torsten Schenkel, Ian Halliday

We present a continuum scale particle transport model for red blood cells following collision arguments in a diffusive flux formulation. The model is implemented in FOAM, in a framework for haemodynamics simulations. Modern mechanistic rheology models are implemented and tested. The model is verified against a known analytical solution and shows excellent ag

Tomasz Beberok

The purpose of this paper is to study a Markov type inequality for algebraic polynomials in $L^p$ norm on two-dimensional cuspidal domains.

Sheik Mohammad Mostakim Fattah, Athman Bouguettaya, Sajib Mistry

We propose a novel approach to select IaaS cloud services for a long-term period where the service providers offer limited QoS information. The proposed approach leverages free short-term trials to obtain the previously undisclosed QoS information. A new significance-based trial scheme is proposed using frequency distribution analysis to test a consumer's lo

Maurizio Giacomin, Paolo Ricci

The results of flux-driven, two-fluid simulations in single-null configurations are used to investigate the processes determining the turbulent transport in the tokamak edge. Three turbulent transport regimes are identified: (i) a developed transport regime with turbulence driven by an interchange instability, which shares a number of features with the stand

Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan, Sunayana Sitaram

Code-switching is the use of more than one language in the same conversation or utterance. Recently, multilingual contextual embedding models, trained on multiple monolingual corpora, have shown promising results on cross-lingual and multilingual tasks. We present an evaluation benchmark, GLUECoS, for code-switched languages, that spans several NLP tasks in

Santosh K. Das, Jan-e Alam, Salvatore Plumari, Vincenzo Greco

The spread of COVID19 through droplets ejected by infected individuals during sneezing and coughing has been considered as a matter of key concern. Therefore, a quantitative understanding of the propagation of droplets containing virus assumes immense importance. Here we investigate the evolution of droplets in space and time under varying external condition

Sergey I. Agafonov

We present a geometric interpretation of integrability of geodesic flow by quadratic integrals in terms of the web theory and construct integrable billiards on surfaces admitting such integrals.

Sameera Horawalavithana, John Skvoretz, Adriana Iamnitchi

Predicting the flow of information in dynamic social environments is relevant to many areas of the contemporary society, from disseminating health care messages to meme tracking. While predicting the growth of information cascades has been successfully addressed in diverse social platforms, predicting the temporal and topological structure of information cas

Jayashree Roy, P. C. Agrawal, B. Singari, R. Misra

Results on timing and spectral properties of the Be/X-ray binary pulsar 3A 0726-260 (4U 0728-25) are presented. The binary was observed on 2016 May 6-7 with the Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) instruments onboard the AstroSat satellite. During this observation the source was in non-flaring persistent state at a fl

Matthew Hague, Anthony Widjaja Lin, Philipp Rümmer, Zhilin Wu

Monadic decomposability is a notion of variable independence, which asks whether a given formula in a first-order theory is expressible as a Boolean combination of monadic predicates in the theory. Recently, Veanes et al. showed the usefulness of monadic decomposability in the context of SMT (i.e. the input formula is quantifier-free), and found various inte

Yong Xiao, Guangming Shi, Marwan Krunz

With 5G cellular systems being actively deployed worldwide, the research community has started to explore novel technological advances for the subsequent generation, i.e., 6G. It is commonly believed that 6G will be built on a new vision of ubiquitous AI, an hyper-flexible architecture that brings human-like intelligence into every aspect of networking syste

Michael Ruderman

A novel modeling approach for viscoelastic hydraulic cylinders, with negligible inertial forces, is proposed, based on the extended fractional-order Jeffreys model. Analysis and physical reasoning for the parameter constraints and order of the fractional derivatives are provided. Comparison between the measured and computed frequency response functions and t

Samuele Centorrino, María Pérez-Urdiales

We propose and study a maximum likelihood estimator of stochastic frontier models with endogeneity in cross-section data when the composite error term may be correlated with inputs and environmental variables. Our framework is a generalization of the normal half-normal stochastic frontier model with endogeneity. We derive the likelihood function in closed fo

Julio C. Valencia-Guevara

This work considers a chemotaxis system for multi-species that includes birth or death rate terms, which implies no mass preservation of the populations. We aim to show the convergence to a $L^{\infty}\ -\ $weak solutions, that is local in time, of the JKO - scheme arising from the Optimal Transport Theory, in the spirit of [35,14]. Currently, $L^{\infty}$ s

Morihiko Saito

We prove a descent theorem of nearby cycle formula for Newton non-degenerate functions at the origin as well as its motivic version (without assuming the convenience condition). This is used in some papers without any proof although its proof is quite nontrivial because of the existence of coordinate hyperplanes which is completely neglected in the literatur

Beomkyu Kim, Jeongsu Bok, Jaeyoon Cho, Jiyeon Cho

Several types of detectors are used to detect charged particles in particle and nuclear physics experiments. Since the semiconductor detector has superior spatial and kinematic resolutions as well as good response time than other types of detectors, it has become one of the most important detectors recently. When charged particles pass through the semiconduc

Laurent Duchemin, Christophe Josserand

Thin liquid or gas films are everywhere in nature, from foams to submillimetric bubbles at a free surface, and their rupture leaves a collection of small drops and bubbles. However, the mechanisms at play responsible for the bursting of these films is still in debate. The present study thus aims at understanding the drainage dynamics of the thin air film squ

Holger Dette, Kevin Kokot

We study the problem of testing the equivalence of functional parameters (such as the mean or variance function) in the two sample functional data problem. In contrast to previous work, which reduces the functional problem to a multiple testing problem for the equivalence of scalar data by comparing the functions at each point, our approach is based on an es

Kai Wang, Junfeng Tian, Rui Wang, Xiaojun Quan

Generating fluent and informative responses is of critical importance for task-oriented dialogue systems. Existing pipeline approaches generally predict multiple dialogue acts first and use them to assist response generation. There are at least two shortcomings with such approaches. First, the inherent structures of multi-domain dialogue acts are neglected.

Kai Wang, Weizhou Shen, Yunyi Yang, Xiaojun Quan

Aspect-based sentiment analysis aims to determine the sentiment polarity towards a specific aspect in online reviews. Most recent efforts adopt attention-based neural network models to implicitly connect aspects with opinion words. However, due to the complexity of language and the existence of multiple aspects in a single sentence, these models often confus

Congcong Ge, Yunjun Gao, Honghui Weng, Chong Zhang

The quality assurance of the knowledge graph is a prerequisite for various knowledge-driven applications. We propose KGClean, a novel cleaning framework powered by knowledge graph embedding, to detect and repair the heterogeneous dirty data. In contrast to previous approaches that either focus on filling missing data or clean errors violated limited rules, K

Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf

We present two new metrics for evaluating generative models in the class-conditional image generation setting. These metrics are obtained by generalizing the two most popular unconditional metrics: the Inception Score (IS) and the Fre'chet Inception Distance (FID). A theoretical analysis shows the motivation behind each proposed metric and links the novel me

Khalid S. Aloufi, Omar H. Alhazmi

IoT applications are promising for future daily activities; therefore, the number of IoT connected devices is expected to reach billions in the coming few years. However, IoT has different application frameworks. Furthermore, IoT applications require higher security standards. In this work, an IoT application framework is presented with a security embedded s

Martin Kolář, Francine Meylan

We classify polynomial models for real hypersurfaces in $\mathbb C^N$, which admit nonlinearizable infinitesimal CR automorphisms. As a consequence, this provides an optimal 1-jet determination result in the general case. Further we prove that such automorphisms arise from one common source, by pulling back via a holomorphic mapping a suitable symmetry of a

Sun-Ting Tsai, En-Jui Kuo, Pratyush Tiwary

Recurrent neural networks (RNNs) have led to breakthroughs in natural language processing and speech recognition, wherein hundreds of millions of people use such tools on a daily basis through smartphones, email servers and other avenues. In this work, we show such RNNs, specifically Long Short-Term Memory (LSTM) neural networks can also be applied to captur

Décio Krause, Jonas R. B. Arenhart

The so-called Received View (RV) on quantum non-individuality states, basically, that quantum particles are not individuals. It has received an amount of criticism in the recent literature, most of it concerning the relation between the RV and the relation of identity. In this chapter we carefully characterise a family of concepts involved in clarifying the

Vinícius D. Mayrink, João Daniel N. Duarte, Fábio N. Demarqui

In this study, we present a new module built for users interested in a programming language similar to BUGS to fit a Bayesian model based on the piecewise exponential (PE) distribution. The module is an extension to the open-source program JAGS by which a Gibbs sampler can be applied without requiring the derivation of complete conditionals and the subsequen

Luigi Casella, Matteo Baggioli, Tatsuya Mori, Alessio Zaccone

The nature of bosonic excitations in disordered materials has remained elusive due to the difficulties in defining key concepts such as quasi-particles in the presence of disorder. We report on the experimental observation of phonon-polaritons in glasses, including a boson peak (BP), i.e. excess of THz modes over the Debye law. A theoretical framework based

Hui Wang, Mike Preuss, Aske Plaat

Recently, AlphaZero has achieved landmark results in deep reinforcement learning, by providing a single self-play architecture that learned three different games at super human level. AlphaZero is a large and complicated system with many parameters, and success requires much compute power and fine-tuning. Reproducing results in other games is a challenge, an

Yohei Ito

The subject of this paper is an algebraic version of the irregular Riemann-Hilbert correspondence which was mentioned in [arXiv:1910.09954] by the author. In particular, we prove an equivalence of categories between the triangulated category of algebraic holonomic D-modules on a smooth algebraic variety and the one of algebraic C-constructible enhanced ind-s

Bhaskar Ghawri, Phanibhusan S. Mahapatra, Shinjan Mandal, Aditya Jayaraman

In moir\'{e} systems with twisted bilayer graphene (tBLG), the amplification of Coulomb correlation effects at low twist angles ($\theta$) is a result of nearly flat low-energy electronic bands and divergent density of states (DOS) at van Hove singularities (vHS). This not only causes superconductivity, Mott insulating states, and quantum anomalous Hall effe

Adam Jakubowski, Zbigniew S. Szewczak

We consider a class of perpetuities which admit direct characterization of asymptotics of the key truncated moment. The class contains perpetuities without polynomial decay of tail probabilities and thus not satisfying Kesten's theorem. We show how to apply this result in deriving a new weak law of large numbers for solutions to stochastic recurrence equatio

V. A. Bovdi, O. Yu. Dashkova, M. A. Salim

Let FL_s(K) be the finitary linear group of degree s over an associative ring K with unity. We prove that the torsion subgroups of FL_s(K) are locally finite for certain classes of rings K. A description of some f.g. solvable subgroups of FL_s(K) are given.

Ferdi Kara, Hakan Kaya

Non-orthogonal multiple access (NOMA) is one of the key technologies to serve in ultra-dense networks with massive connections which is crucial for Internet of Things (IoT) applications. Besides, NOMA provides better spectral efficiency compared to orthogonal multiple access (OMA) schemes. However, in NOMA, successive interference canceler (SIC) should be im

Michal Heker, Hayit Greenspan

Transfer learning and joint learning approaches are extensively used to improve the performance of Convolutional Neural Networks (CNNs). In medical imaging applications in which the target dataset is typically very small, transfer learning improves feature learning while joint learning has shown effectiveness in improving the network's generalization and rob

Haidong Liu

We study very basic slc-trivial fibrations. We show that restricting on any lc center of a very basic slc-trivial fibration, its moduli part is numerically trivial if and only if it is $\mathbb Q$-linearly trivial. We then prove that abundance conjecture for very basic slc-trivial fibrations holds true in dimension two when the moduli part is $\mathbb Q$-Car

Mahid M. Mangontarum, Norlailah M. Madid

In this paper, we establish some formulas for the noncentral Tanny-Dowling polynomials including sums of products and explicit formulas which are shown to be generalizations of known identities. Other important results and consequences are also discussed and presented.

Pavle V. M. Blagojević, Frederick R. Cohen, Michael C. Crabb, Wolfgang Lück

The equivariant cohomology of the classical configuration space $F(\mathbb{R}^d,n)$ has been been of great interest and has been studied intensively starting with the classical papers by Artin (1925/1947) on the theory of braids, by Fox and Neuwirth (1962), Fadell and Neuwirth (1962), and Arnol'd (1969). We give a brief treatment of the subject from the begi

Ali Caglayan, Nevrez Imamoglu, Ahmet Burak Can, Ryosuke Nakamura

Recognizing objects and scenes are two challenging but essential tasks in image understanding. In particular, the use of RGB-D sensors in handling these tasks has emerged as an important area of focus for better visual understanding. Meanwhile, deep neural networks, specifically convolutional neural networks (CNNs), have become widespread and have been appli

Theodorus Jonathan Wijaya, Daigo Oue, Mamoru Matsuo, Yasutoshi Ito

Surface plasmon polariton (SPP) is an electromagnetic wave which is tightly localised beyond the diffraction limit at metallic surfaces. Recently, it is theoretically proposed that the angular momentum conversion between the SPP and electrons. In this work, we have successfully measured SPP induced spin currents, which proves the fact that the angular moment

Lorenzo Bastianello, José Heleno Faro, Ana Santos

A group of experts, for instance climate scientists, is to choose among two policies $f$ and $g$. Consider the following decision rule. If all experts agree that the expected utility of $f$ is higher than the expected utility of $g$, the unanimity rule applies, and $f$ is chosen. Otherwise the precautionary principle is implemented and the policy yielding th

Gopikrishnan Chirappurathu Remesan

A uniform bounded variation estimate for finite volume approximations of the nonlinear scalar conservation law $\partial_t \alpha + \mathrm{div}(\boldsymbol{u}f(\alpha)) = 0$ in two and three spatial dimensions with an initial data of bounded variation is established. We assume that the divergence of the velocity $\mathrm{div}(\boldsymbol{u})$ is of bounded

Yuntian Chen, Dongxiao Zhang

This study proposes a supervised learning method that does not rely on labels. We use variables associated with the label as indirect labels, and construct an indirect physics-constrained loss based on the physical mechanism to train the model. In the training process, the model prediction is mapped to the space of value that conforms to the physical mechani

Yitian Qian, Shaohua Pan

This paper is concerned with the unconstrained binary polynomial program (UBPP), which has a host of applications in many science and engineering fields. By leveraging the global exact penalty for its DC constrained SDP reformulation, we achieve an equivalent DC penalized SDP, and propose a continuous relaxation approach by seeking the critical point of the

Ruchit Rawal, Prabhu Pradhan

The utility of aerial imagery (Satellite, Drones) has become an invaluable information source for cross-disciplinary applications, especially for crisis management. Most of the mapping and tracking efforts are manual which is resource-intensive and often lead to delivery delays. Deep Learning methods have boosted the capacity of relief efforts via recognitio

Daniel J. F. Fox

A commutative algebra is exact if its multiplication endomorphisms are trace-free and is Killing metrized if its Killing type trace-form is nondegenerate and invariant. A Killing metrized exact commutative algebra is necessarily neither unital nor associative. Such algebras can be viewed as commutative analogues of semisimple Lie algebras or, alternatively,

Sourav Sen

Informal transliteration from other languages to English is prevalent in social media threads, instant messaging, and discussion forums. Without identifying the language of such transliterated text, users who do not speak that language cannot understand its content using translation tools. We propose a Language Identification (LID) system, with an approach f

Hiroaki Kurihara

In this paper we study isotopy classes of closed connected orientable surfaces in the standard $3$-sphere. Such a surface splits the $3$-sphere into two compact connected submanifolds, and by using their Heegaard splittings, we obtain a $2$-component handlebody-link. In this paper, we first show that the equivalence class of such a 2-component handlebody-lin

T. Chacon Rebollo, D. Franco Coronil

In this article, we develop a data assimilation procedure to predict the evolution of epidemics with data uncertainty, with application to the Covid-19 pandemic. We construct a vademecum of solutions by solving the SIR epidemic model for a set of data neighboring the estimated real (or official) ones. A reduced basis is constructed from this vademecum throug

Xinwei Chai, Xian Guo, Jihua Xiao, Jie Jiang

During the epidemics of COVID-19, the whole world is experiencing a serious crisis on public health and economy. Understanding human mobility during the pandemic helps one to design intervention strategies and resilience measures. The widely used Bike Sharing System (BSS) can characterize the activities of urban dwellers over time & space in big cities but i

E. Estrecho, M. Pieczarka, M. Wurdack, M. Steger

We report the observation of low-energy, low-momenta collective oscillations of an excitonpolariton condensate in a round "box" trap. The oscillations are dominated by the dipole and breathing modes, and the ratio of the frequencies of the two modes is consistent with that of a weakly interacting two-dimensional trapped Bose gas. The speed of sound extracted

Giorgio Guzzetta, Flavia Riccardo, Valentina Marziano, Piero Poletti

On March 10, 2020, Italy imposed a national lockdown to curtail the spread of COVID-19. Here we estimate that, fourteen days after the implementation of the strategy, the net reproduction number has dropped below the epidemic threshold - estimated range 0.4-0.7. Our findings provide a timeline of the effectiveness of the implemented lockdown, which is releva

Mateusz Żarski, Bartosz Wójcik, Jarosław Adam Miszczak

Monitoring the technical condition of infrastructure is a crucial element to its maintenance. Currently applied methods are outdated, labour-intensive and inaccurate. At the same time, the latest methods using Artificial Intelligence techniques are severely limited in their application due to two main factors -- labour-intensive gathering of new datasets and

Anton J. Heckens, Sebastian M. Krause, Thomas Guhr

The measured correlations of financial time series in subsequent epochs change considerably as a function of time. When studying the whole correlation matrices, quasi-stationary patterns, referred to as market states, are seen by applying clustering methods. They emerge, disappear or reemerge, but they are dominated by the collective motion of all stocks. In

Leila Ismail, Huned Materwala

Data centers are large scale, energy-hungry infrastructure serving the increasing computational demands as the world is becoming more connected in smart cities. The emergence of advanced technologies such as cloud-based services, internet of things (IoT) and big data analytics has augmented the growth of global data centers, leading to high energy consumptio