April 2020 arXiv papers — page 17

Andrew Knight

The possibility of algorithmic consciousness depends on the assumption that conscious states can be copied or repeated by sufficiently duplicating their underlying physical states, leading to a variety of paradoxes, including the problems of duplication, teleportation, simulation, self-location, the Boltzmann brain, and Wigner's Friend. In an effort to furth

Fabian Küppers, Jan Kronenberger, Amirhossein Shantia, Anselm Haselhoff

Unbiased confidence estimates of neural networks are crucial especially for safety-critical applications. Many methods have been developed to calibrate biased confidence estimates. Though there is a variety of methods for classification, the field of object detection has not been addressed yet. Therefore, we present a novel framework to measure and calibrate

Sushant G. Ghosh, Sunil D. Maharaj

Low energy limits of string theory indicated that the standard gravity action should be modified to include higher-order curvature terms, in the form of dimensionally continued Gauss-Bonnet densities. If one includes only quadratic curvature terms then the resulting theory is Einstein-Gauss-Bonnet (EGB) gravity valid only in $D>4$ dimensions. Recently there

Anna Velyka, Marco Guerzoni

This paper is about the possible negative impact of excessive collaboration on the performance of top employees. With the rise of participatory culture and developments in communications technology, management practices require greater conceptual awareness about possible outcomes of increased organizational interconnectivity. While there exists a sound theor

Gabriel Rainisch, Eduardo A. Undurraga, Gerardo Chowell

Objectives. Public health officials need tools to assist with anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We built a modeling tool to aid practicing public health officials with estimating healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impacts of population-wide social-distanci

Gregory Kopnov, Alexander Gerber

Absence of an efficient technology of GaAs passivation limits the use of III-V semiconductors in modern electronics. The effect reported here can possibly lead to a solution of this long standing problem. We found that an electrically conducting interfacial channel is formed when insulating metal oxide dielectrics are deposited on untreated semi-insulating G

V. Zobac, R. Robles, N. Lorente

We report on a theoretical study of adsorption of 4-Acetylbiphenyl molecule and its diffusion properties in the main directions of the Au(111) surface. Structural changes of the molecule, which are induced by adsorption lead to stronger conjugation of the $\pi$-system. The molecule is adsorbed in a flat configuration on the surface with roughly the same bind

Yuta Kusakabe

We establish Thom's jet transversality theorem for regular maps from an affine algebraic manifold to an algebraic manifold satisfying a suitable flexibility condition. It can be considered as the algebraic version of Forstneri\v{c}'s jet transversality theorem for holomorphic maps from a Stein manifold to an Oka manifold. Our jet transversality theorem impli

Miklos Z. Racz, Anirudh Sridhar

We introduce a new model of correlated randomly growing graphs and study the fundamental questions of detecting correlation and estimating aspects of the correlated structure. The model is simple and starts with any model of randomly growing graphs, such as uniform attachment (UA) or preferential attachment (PA). Given such a model, a pair of graphs $(G_1, G

Jamshid Ardalankia, Jafar Askari, Somaye Sheykhali, Emmanuel Haven

In order to extract hidden joint information from two possibly uncorrelated time-series, we explored the measures of network science. Alongside common methods in time-series analysis of the economic markets, mapping the joint structure of two time-series onto a network provides insight into hidden aspects embedded in the couplings. We discretize the amplitud

Jan Masell, Karin Everschor-Sitte

Magnetic textures can be manipulated by electric currents via the mechanisms of spin-transfer and spin-orbit-torques. We review how these torques can be exploited to create chiral magnetic textures in magnets with broken inversion symmetries, including domain walls and skyrmions. These chiral textures can also be moved by (electric) currents and obey very ri

Simon Müller, Ravit Helled, Andrew Cumming

Recent structure models of Jupiter that match Juno gravity data suggest that the planet harbours an extended region in its deep interior that is enriched in heavy elements, a so-called dilute/fuzzy core. This finding raises the question of what possible formation pathways would lead to such a structure. We model Jupiter's formation and long-term evolution, s

Stefan Floerchinger, Tobias Haas

Thermodynamics is usually developed starting from entropy and the maximum entropy principle. We investigate here to what extent one can replace entropy with relative entropy which has several advantages, for example in the context of local quantum field theory. We find that the principle of maximum entropy can be replaced by a principle of minimum expected r

Richard C. Gerum, Achim Schilling

Up to now, modern Machine Learning is mainly based on fitting high dimensional functions to enormous data sets, taking advantage of huge hardware resources. We show that biologically inspired neuron models such as the Leaky-Integrate-and-Fire (LIF) neurons provide novel and efficient ways of information encoding. They can be integrated in Machine Learning mo

V. I. Mokeev, V. D. Burkert, D. S. Carman, L. Elouadrhiri

The analysis of the nine 1-fold differential cross sections for the $\gamma_{r,v} p \to \pi^+\pi^-p$ photo- and electroproduction reactions obtained with the CLAS detector at Jefferson Laboratory was carried out with the goal to establish the contributing resonances in the mass range from 1.6~GeV to 1.8~GeV. In order to describe the photo- and electroproduct

Luca Benedetto, Andrea Cappelli, Roberto Turrin, Paolo Cremonesi

Statistical models such as those derived from Item Response Theory (IRT) enable the assessment of students on a specific subject, which can be useful for several purposes (e.g., learning path customization, drop-out prediction). However, the questions have to be assessed as well and, although it is possible to estimate with IRT the characteristics of questio

Juarez Monteiro, Nathan Gavenski, Roger Granada, Felipe Meneguzzi

Imitation from observation is a computational technique that teaches an agent on how to mimic the behavior of an expert by observing only the sequence of states from the expert demonstrations. Recent approaches learn the inverse dynamics of the environment and an imitation policy by interleaving epochs of both models while changing the demonstration data. Ho

George Savvidy

The Kolmogorov entropy allows to split the dynamical systems that have equivalent continuous spectrum into non-isomorphic subclasses. In this paper we make an attempt to generalise the concept of entropy that will allow to split the systems with equivalent continuous spectrum and equal Kolmogorov entropies into finer non-isomorphic subclasses. We will define

O. M. Sotnikov, V. V. Mazurenko, J. Colbois, F. Mila

In magnetism, skyrmions correspond to classical three-dimensional spin textures characterized by a topological invariant that keeps track of the winding of the magnetization in real space, a property that cannot be easily generalized to the quantum case since the orientation of a quantum spin is in general ill-defined. Moreover, as we show, the quantum skyrm

Ralf Raumanns, Elif K Contar, Gerard Schouten, Veronika Cheplygina

Machine learning has a recognised need for large amounts of annotated data. Due to the high cost of expert annotations, crowdsourcing, where non-experts are asked to label or outline images, has been proposed as an alternative. Although many promising results are reported, the quality of diagnostic crowdsourced labels is still unclear. We propose to address

Philippe Burlina, Neil Joshi, William Paul, Katia D. Pacheco

This study evaluated generative methods to potentially mitigate AI bias when diagnosing diabetic retinopathy (DR) resulting from training data imbalance, or domain generalization which occurs when deep learning systems (DLS) face concepts at test/inference time they were not initially trained on. The public domain Kaggle-EyePACS dataset (88,692 fundi and 44,

Konstantin Klemm

Decompositions of networks are useful not only for structural exploration. They also have implications and use in analysis and computational solution of processes (such as the Ising model, percolation, SIR model) running on a given network. Tree and branch decompositions considered here directly represent network structure as trees for recursive computation

Arthur Douillard, Matthieu Cord, Charles Ollion, Thomas Robert

Lifelong learning has attracted much attention, but existing works still struggle to fight catastrophic forgetting and accumulate knowledge over long stretches of incremental learning. In this work, we propose PODNet, a model inspired by representation learning. By carefully balancing the compromise between remembering the old classes and learning new ones,

Ronaldo Garcia, Dan Reznik

Discovered by William Chapple in 1746, the Poristic family is a set of variable-perimeter triangles with common Incircle and Circumcircle. By definition, the family has constant Inradius-to-Circumradius ratio. Interestingly, this invariance also holds for the family of 3-periodics in the Elliptic Billiard, though here Inradius and Circumradius are variable a

Dominic Samra, Christiane Helling, Michiel Min

Exoplanet atmosphere characterisation has become an important tool in understanding exoplanet formation, evolution. However, clouds remain a key challenge for characterisation: upcoming space telescopes (e.g. JWST, ARIEL) and ground-based high-resolution spectrographs (e.g. CRIRES+) will produce data requiring detailed understanding of cloud formation and cl

O. R. Sayed, N. H. Sayed

The present paper is devoted to study some completeness properties of transitive binary relational set, i.e., a set together with a transitive binary relation (so called t-set).

Igor Danilkin, Daniel A. S. Molnar, Marc Vanderhaeghen

In this work, we provide a simultaneous and accurate description of the $\pi^+\pi^-$ and $\pi^{\pm} J/\psi$ invariant mass distributions of the recent BESIII data on $e^+ e^- \to J/\psi \; \pi^+ \pi^-$ together with the $e^+ e^- \to J/\psi \; K^+K^-$ cross sections at $e^+e^-$ center-of-mass energies $q=4.23$ GeV and $q=4.26$ GeV. The rescattering effects be

M. Pavana, A. Raj, T. Bohlsen, G. C. Anupama

The optical spectroscopic observations of ASASSN-18fv observed from 2018 March 24 to 2019 Jan 26 are presented. The optical spectra are obtained from Mirranook, Vainu Bappu and South African Astronomical observatories. The spectra are dominated by hydrogen Balmer, Fe II and O I lines with P-Cygni profiles in the early phase, typical of an Fe II class nova. T

Tim Kuipers, Eugeni L. Doubrovski, Jun Wu, Charlie C. L. Wang

3D printing techniques such as Fused Deposition Modeling (FDM) have enabled the fabrication of complex geometry quickly and cheaply. High stiffness parts are produced by filling the 2D polygons of consecutive layers with contour-parallel extrusion toolpaths. Uniform width toolpaths consisting of inward offsets from the outline polygons produce over- and unde

Ana Nunes Alonso, João Abreu, David Nunes, André Vieira

Low-code application development as proposed by the OutSystems Platform enables fast mobile and desktop application development and deployment. It hinges on visual development of the interface and business logic but also on easy integration with data stores and services while delivering robust applications that scale. Data integration increasingly means acce

Tania Massignan, Alberto Boldrini, Luca Terruzzi, Giovanni Spagnolli

The steep climbing of victims caused by the new coronavirus disease 2019 (COVID-19) throughout the planet is sparking an unprecedented effort to identify effective therapeutic regimens to tackle the pandemic. The SARS-CoV-2 virus is known to gain entry into various cell types through the binding of one of its surface proteins (spike) to the host Angiotensin-

Till Fluschnik, Hendrik Molter, Rolf Niedermeier, Malte Renken

Treewidth is arguably the most important structural graph parameter leading to algorithmically beneficial graph decompositions. Triggered by a strongly growing interest in temporal networks (graphs where edge sets change over time), we discuss fresh algorithmic views on temporal tree decompositions and temporal treewidth. We review and explain some of the re

Abhijit Gadde

We discover a modular property of supersymmetric partition functions of supersymmetric theories with R-symmetry in four dimensions. This modular property is, in a sense, the generalization of the modular invariance of the supersymmetric partition function of two-dimensional supersymmetric theories on a torus i.e. of the elliptic genus. The partition function

Emine Yilmaz, Nick Craswell, Bhaskar Mitra, Daniel Campos

As deep learning based models are increasingly being used for information retrieval (IR), a major challenge is to ensure the availability of test collections for measuring their quality. Test collections are generated based on pooling results of various retrieval systems, but until recently this did not include deep learning systems. This raises a major chal

M. M. Glazov

Strong Coulomb interaction in atomically-thin transition metal dichalcogenides makes these systems particularly promising for studies of excitonic physics. Of special interest are the manifestations of the charged excitons, also known as trions, in the optical properties of two-dimensional semiconductors. In order to describe the optical response of such a s

Genya Kobayashi, Shonosuke Sugasawa, Hiromasa Tamae, Takayuki Ozu

The number of confirmed cases of the coronavirus disease (COVID-19) in Japan has been increasing day by day and has had a serious impact on the society especially after the declaration of the state of emergency on April 7, 2020. This study analyzes the real time data from March 1 to April 22, 2020 by adopting a sophisticated statistical modeling tool based o

Roger Granada, Ramon Fraga Pereira, Juarez Monteiro, Leonardo Amado

Computer-based assistants have recently attracted much interest due to its applicability to ambient assisted living. Such assistants have to detect and recognize the high-level activities and goals performed by the assisted human beings. In this work, we demonstrate activity recognition in an indoor environment in order to identify the goal towards which the

Rajesh Kumar Yadav, Suman Banerjee, Nisha Kumari, Avinash Khare

We start from a given one dimensional rationally extended potential associated with $X_m$ exceptional orthogonal polynomials and using the idea of supersymmetry in quantum mechanics, we obtain one continuous parameter ($\lambda$) family of rationally extended strictly isospectral potentials whose solutions are also associated with Xm exceptional orthogonal p

Peng Fu, Kohei Kishida, Peter Selinger

Modern quantum programming languages integrate quantum resources and classical control. They must, on the one hand, be linearly typed to reflect the no-cloning property of quantum resources. On the other hand, high-level and practical languages should also support quantum circuits as first-class citizens, as well as families of circuits that are indexed by s

Hideo Kozono, Yutaka Terasawa, Yuta Wakasugi

We study the asymptotic behavior of axisymmetric solutions with no swirl to the steady Navier-Stokes equations in the outside of the cylinder. We prove an a priori decay estimate of the vorticity under the assumption that the velocity has generalized finite Dirichlet integral. As an application, we obtain a Liouville-type theorem.

Mina Jafari, Ruizhe Li, Yue Xing, Dorothee Auer

In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model, known as U-net. U-net is firstly modified by adding widely used batch normalization and residual block (named as BRU-net) to improve the efficiency of model training. Based on BRU

Milad Hajebrahimi, Kourosh Nozari

In the language of black hole physics, Hawking radiation is one of the most controversial subjects about which there exist lots of puzzles, including the information loss problem and the question of whether this radiation is thermal or not. In this situation, a possible way to face these problems is to bring quantum effects into play, also taking into accoun

S. Martin-Martínez, A. Vigueras-Rodríguez, E. Gómez-Lázaro, A. Molina-García

Examples of the different events affecting wind power fluctuations are shown.The behaviors and the responses of the Spanish power system and wind power plants experiencing such events were analyzed. Examples presented in this chapter show that some of the wind power integration issues are related to low-voltage ride-through. They are solved through strict gr

Hideo Kozono, Yutaka Terasawa, Yuta Wakasugi

We study an asymptotic behavior of solutions to elliptic equations of the second order in a two dimensional exterior domain. Under the assumption that the solution belongs to $L^q$ with $q \in [2,\infty)$, we prove a pointwise asymptotic estimate of the solution at the spatial infinity in terms of the behavior of the coefficients. As a corollary, we obtain t

Magdalena Skurzok

In this paper the search for eta-mesic nuclei with particular focus on light $\eta$-He bound states is reviewed. A brief description of recent theoretical studies and experimental results is presented.

Bo Xue, Guanghui Wang, Yimu Wang, Lijun Zhang

In this paper, we study the problem of stochastic linear bandits with finite action sets. Most of existing work assume the payoffs are bounded or sub-Gaussian, which may be violated in some scenarios such as financial markets. To settle this issue, we analyze the linear bandits with heavy-tailed payoffs, where the payoffs admit finite $1+\epsilon$ moments fo

Konstantina Chalkou, Ewout Steyerberg, Matthias Egger, Andrea Manca

Treatment effects vary across different patients and estimation of this variability is important for clinical decisions. The aim is to develop a model to estimate the benefit of alternative treatment options for individual patients. Hence, we developed a two-stage prediction model for heterogeneous treatment effects, by combining prognosis research and netwo

Menghan Sun, Jichang Zhao

Negative reviews on e-commerce platforms, mainly in the form of texts, are posted by online consumers to express complaints about unsatisfactory experiences, providing a proxy of big data for sellers to consider improvements. However, the exact knowledge that lies beyond the negative reviewing still remains unknown. Aimed at a systemic understanding of how o

Charles Hudin, Vincent Hayward

Hearing is often believed to be more sensitive than touch. This assertion is based on a comparison of sensitivities to weak stimuli. The respective stimuli, however, are not easily comparable since hearing is gauged using acoustic pressure and touch using skin displacement. We show that under reasonable assumptions the auditory and tactile detection threshol

Erik Gengel, Arkady Pikovsky

We present a study dealing with a novel phase reconstruction method based on iterated Hilbert transform embeddings. We show results for the Stuart-Landau oscillator observed by generic observables. The benefits for reconstruction of the phase response curve a presented and the method is applied in a setting where the observed system is pertubred by noise.

Claus Heussinger

We present simulation results on the properties of packings of frictionless spherocylindrical particles. Starting from a random distribution of particles in space, a packing is produced by minimizing the potential energy of inter-particle contacts until a force-equilibrated state is reached. For different particle aspect ratios $\alpha=10\ldots 40$, we calcu

Z. Yousaf, M. Z. Bhatti, T. Naseer, I. Ahmad

In this paper, we investigate irregularities in a cylindrical self-gravitating system which contains the properties of an imperfect matter and electromagnetic field. For $f(R,T,Q)$ theory, in which $R$ represents the Ricci scalar and $T$ shows the trace of matter stress-energy tensor while $Q\equiv R_{\gamma\delta}T^{\gamma\delta}$, the field equations conta

L. J. Townsend, P. A. Charles

We present evidence for a simple linear relationship between the orbital period and super-orbital period in ultra-luminous X-ray (ULX) pulsars, akin to what is seen in the population of disc-fed neutron star super-giant X-ray binary and Be/X-ray binary systems. We argue that the most likely cause of this relationship is the modulation of precessing hot spots

Laura Forastiere, Davide Del Prete, Valerio Leone Sciabolazza

This paper investigates the case of interference, when a unit's treatment also affects other units' outcome. When interference is at work, policy evaluation mostly relies on the use of randomized experiments under cluster interference and binary treatment. Instead, we consider a non-experimental setting under continuous treatment and network interference. In

Timo Milbich, Karsten Roth, Homanga Bharadhwaj, Samarth Sinha

Visual Similarity plays an important role in many computer vision applications. Deep metric learning (DML) is a powerful framework for learning such similarities which not only generalize from training data to identically distributed test distributions, but in particular also translate to unknown test classes. However, its prevailing learning paradigm is cla

Nicola Melluso, Silvia Fareri, Gualtiero Fantoni, Andrea Bonaccorsi

Scientific discoveries and technologies played a significant role in the digital revolution that occurred over the last years. But what is their role in the turmoil brought by the current pandemic? The aim of this paper is to show how digital technologies are operating during this first phase of the spreading of COVID-19. The study analyses and debates the c

Tushar Kanti Bhowmik, Tripurari Prasad Sinha

In this paper, a theoretical journey from electronic to magneto-caloric effect has been shown through the magnetic properties of aluminium induced yttrium chromate. The ground state electronic band structure and density of states have been studied using first principle calculations under GGA+U schemes. From the energy minimization, the ferromagnetic structur

Lianwei Wu, Yuan Rao, Yongqiang Zhao, Hao Liang

Recently, many methods discover effective evidence from reliable sources by appropriate neural networks for explainable claim verification, which has been widely recognized. However, in these methods, the discovery process of evidence is nontransparent and unexplained. Simultaneously, the discovered evidence only roughly aims at the interpretability of the w

Xiang Dai, Sarvnaz Karimi, Ben Hachey, Cecile Paris

Unlike widely used Named Entity Recognition (NER) data sets in generic domains, biomedical NER data sets often contain mentions consisting of discontinuous spans. Conventional sequence tagging techniques encode Markov assumptions that are efficient but preclude recovery of these mentions. We propose a simple, effective transition-based model with generic neu

Mina Jafari, Dorothee Auer, Susan Francis, Jonathan Garibaldi

Residual network (ResNet) and densely connected network (DenseNet) have significantly improved the training efficiency and performance of deep convolutional neural networks (DCNNs) mainly for object classification tasks. In this paper, we propose an efficient network architecture by considering advantages of both networks. The proposed method is integrated i

Sebastian Contreras, H. Andres Villavicencio, David Medina-Ortiz, Juan Pablo Biron-Lattes

The outbreak and propagation of COVID-19 have posed a considerable challenge to modern society. In particular, the different restrictive actions taken by governments to prevent the spread of the virus have changed the way humans interact and conceive interaction. Due to geographical, behavioral, or economic factors, different sub-groups among a population ar

Vadim Lebedev, Taro Yoshikawa, Christoph Schreyvogel, Lutz Kirste

Multiply twinned particles, MTPs, are fascinating crystallographic entities with a number of controllable properties originating from their symmetry and cyclic structure. In the focus of our studies are diamond MTPs hosting optically active defects, objects demonstrating a high application potential for emerging optoelectronic and quantum devices. In this wo

Marc Wenskat, Jakub Cizek, Maciej Oskar Liedke, Maik Butterling

A recently discovered modified low-temperature baking leads to reduced surface losses and an increase of the accelerating gradient of superconducting TESLA shape cavities. We will show that the dynamics of vacancy-hydrogen complexes at low-temperature baking lead to a suppression of lossy nanohydrides at 2\,K and thus a significant enhancement of accelerator

Yana Hasson, Bugra Tekin, Federica Bogo, Ivan Laptev

Modeling hand-object manipulations is essential for understanding how humans interact with their environment. While of practical importance, estimating the pose of hands and objects during interactions is challenging due to the large mutual occlusions that occur during manipulation. Recent efforts have been directed towards fully-supervised methods that requ

Huimin Qiao, Owoong Kwon, Yunseok Kim

Piezoresponse force microscopy (PFM) has been extensively utilized as a versatile and an indispensable tool to understand and analyze nanoscale ferro- /piezoelectric properties by detecting the local electromechanical response on a sample surface. However, it has been discovered that the electromechanical response not only originates from piezoelectricity bu

ATLAS Collaboration

The performance of the ATLAS muon trigger system is evaluated with proton-proton ($pp$) and heavy-ion (HI) collision data collected in Run 2 during 2015-2018 at the Large Hadron Collider. It is primarily evaluated using events containing a pair of muons from the decay of $Z$ bosons to cover the intermediate momentum range between 25 GeV and 100 GeV. Overall,

Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee

Causal inference (CI) in observational studies has received a lot of attention in healthcare, education, ad attribution, policy evaluation, etc. Confounding is a typical hazard, where the context affects both, the treatment assignment and response. In a multiple treatment scenario, we propose the neural network based MultiMBNN, where we overcome confounding

Ali Golmakani, Comlan Edmond Koudjinan, Stefano Luzzatto, Paweł Pilarczyk

We develop algorithms and techniques to compute rigorous bounds for finite pieces of orbits of the critical points, for intervals of parameter values, in the quadratic family of one-dimensional maps $f_a (x) = a - x^2$. We illustrate the effectiveness of our approach by constructing a dynamically defined partition $\mathcal P$ of the parameter interval $\Ome

Ari Patrick, Adán Cabello

We address the problem of detecting bipartite Bell nonlocality whenever the only experimental information are the intensities produced in each run of the experiment by an unknown number of particles. We point out that this scenario naturally occurs in Bell experiments with parametric down-conversion when the crystal is pumped by strong pulses, in Bell tests

Andreas Galanis, Leslie Ann Goldberg, James Stewart

A spin system is a framework in which the vertices of a graph are assigned spins from a finite set. The interactions between neighbouring spins give rise to weights, so a spin assignment can also be viewed as a weighted graph homomorphism. The problem of approximating the partition function (the aggregate weight of spin assignments) or of sampling from the r

Clemens Albrecht, Serena Barbanotti, Heiko Hintz, Kai Jensch

At DESY the ALPS II experiment is being installed in the HERA tunnel to search for axion like particles (ALPs). A laser beam will be injected into a string of superconducting HERA dipole magnets, to produce ALPs. After passing a light tight wall, the ALPs can reconvert into photons in a second string of HERA dipoles.The sensitivity of the experiment will be

Hongyan Sun, Hua-Ming Wang

Let $A_kA_{k-1}\cdots A_1$ be product of some nonnegative 2-by-2 matrices. In general, its elements are hard to evaluate. Under some conditions, we show that $\forall i,j\in\{1,2\},$ $(A_kA_{k-1}\cdots A_1)_{i,j}\sim c\varrho(A_k)\varrho(A_{k-1})\cdots \varrho(A_1)$ as $k\rightarrow\infty,$ where $\varrho(A_n)$ is the spectral radius of the matrix $A_n$ and

Dano Roost, Ralph Meier, Stephan Huschauer, Erik Nygren

We present preliminary results from our sixth placed entry to the Flatland international competition for train rescheduling, including two improvements for optimized reinforcement learning (RL) training efficiency, and two hypotheses with respect to the prospect of deep RL for complex real-world control tasks: first, that current state of the art policy grad

Maher Alharby, Aad van Moorsel

Both in the design and deployment of blockchain solutions many performance-impacting configuration choices need to be made. We introduce BlockSim, a framework and software tool to build and simulate discrete-event dynamic systems models for blockchain systems. BlockSim is designed to support the analysis of a large variety of blockchains and blockchain deplo

Francesca Angrisani, Giacomo Ascione, Gianluigi Manzo

Recently there has been interest in pairs of Banach spaces $(E_0,E)$ in an $o-O$ relation and with $E_0^{**}=E$. It is known that this can be done for Lipschitz spaces on suitable metric spaces. In this paper we consider the case of a compact subset $K$ of $\mathbb{R}^n$ with the euclidean metric, which does not give an $o-O$ structure, but we use part of th

Ginevra Favole, Benjamin R. Granett, Javier Silva Lafaurie, Domenico Sapone

The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the

Conor M. O'Riordan, Stephen J. Warren, Daniel J. Mortlock

We present a systematic analysis of the constraints $\sigma_\gamma$ on the mass profile slope $\gamma$ obtainable when fitting a singular power-law ellipsoid model to a typical strong lensing observation of an extended source. These results extend our previous analysis of circular systems, Paper I. We draw our results from 676 mock observations covering a ra

Philip A. Thomas, Wai Jue Tan, Henry A. Fernandez, William L. Barnes

Light-matter interactions can occur when an ensemble of molecular resonators is placed in a confined electromagnetic field. In the strong coupling regime the rapid exchange of energy between the molecules and the electromagnetic field results in the emergence of hybrid light-matter states called polaritons. Multiple criteria exist to define the strong coupli

Fredrik Schalling, Sebastian Ljungberg, Naveen Mohan

Environment perception and representation are some of the most critical tasks in automated driving. To meet the stringent needs of safety standards such as ISO 26262 there is a need for efficient quantitative evaluation of the perceived information. However, to use typical methods of evaluation, such as comparing using annotated data, is not scalable due to

Wenliang Dai, Tiezheng Yu, Zihan Liu, Pascale Fung

Nowadays, offensive content in social media has become a serious problem, and automatically detecting offensive language is an essential task. In this paper, we build an offensive language detection system, which combines multi-task learning with BERT-based models. Using a pre-trained language model such as BERT, we can effectively learn the representations

Yiming Hu, Yuding Liang, Zichao Guo, Ruosi Wan

In this work, we present a simple and general search space shrinking method, called Angle-Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach progressively simplifies the original search space by dropping unpromising candidates, thus can reduce difficulties for existing NAS methods to find superior architectures. In particu

Jorge Amaya, Romain Dupuis, Maria Elena Innocenti, Giovanni Lapenta

One of the goals of machine learning is to eliminate tedious and arduous repetitive work. The manual and semi-automatic classification of millions of hours of solar wind data from multiple missions can be replaced by automatic algorithms that can discover, in mountains of multi-dimensional data, the real differences in the solar wind properties. In this pape

Tobias Dornheim, Jan Vorberger

We systematically investigate finite-size effects in the dynamic structure factor $S(q,\omega)$ of the uniform electron gas obtained via the analytic continuation of \textit{ab initio} path integral Monte-Carlo (PIMC) data for the imaginary-time density--density correlation function $F(q,\tau)$. Using the recent scheme by Dornheim \textit{et al.}~[PRL \textb

Robin Heveling, Lars Knipschild, Jochen Gemmer

Evidently, some relaxation dynamics, e.g. exponential decays, are much more common in nature than others. Recently there have been attempts to explain this observation on the basis of ``typicality of perturbations'' with respect to their impact on expectation value dynamics. These theories suggest that a majority of the very numerous, possible Hamiltonian pe

Johannes Schumacher, Marius Hauglin, Rasmus Astrup, Johannes Breidenbach

The age of forest stands is critical information for many aspects of forest management and conservation but area-wide information about forest stand age often does not exist. In this study, we developed regression models for large-scale area-wide prediction of age in Norwegian forests. For model development we used more than 4800 plots of the Norwegian Natio

Min He, Hong Wu, Wei Du, He-yang Liu

Low-surface-brightness galaxies(LSBGs) are defined as galaxies that are fainter than dark night sky and are important for studying our universe. Particularly, edge-on galaxies are useful for the study of rotational velocity and dynamical properties of galaxies. Hence here we focus on searching for edge-on LSBGs. In order to find these edge-on dim galaxies, a

Emanuel Florentin Olariu, Cristian Frasinaru, Albert Abel Policiuc

We give a column generation based branch and bound algorithm for coalition structure generation over graphs problem using valuation functions for which this problem is proven to be NP-complete. For a given graph G = (V;E) and a valuation function w : 2^V -> R, the problem is to find the most valuable coalition structure (or partition) of V. We consider two c

Timo Betcke, Erik Burman, Matthew W. Scroggs

We consider boundary element methods where the Calder\'on projector is used for the system matrix and boundary conditions are weakly imposed using a particular variational boundary operator designed using techniques from augmented Lagrangian methods. Regardless of the boundary conditions, both the primal trace variable and the flux are approximated. We focus

István Juhász, Lajos Soukup, Zoltán Szentmiklóssy

For a topological space $X$ we propose to call a subset $S \subset X$ "free in $X$" if it admits a well-ordering that turns it into a free sequence in $X$. The well-known cardinal function $F(X)$ is then definable as $\sup\{|S| : S \text{ is free in } X\}$ and will be called the free set number of $X$. We prove several new inequalities involving $F(X)$ and $

Emanuel Florentin Olariu, Cristian Frasinaru

The Multiple-Depot Vehicle Scheduling Problem (MDVSP) is very important in the planning process of transport systems. It consists in assigning a set of trips to a set of vehicles in order to minimize a certain total cost. We introduce three fast and reliable heuristics for MDVSP based on a classical integer linear programming formulation and on graph theoret

David A. Velasco-Romero, Frédéric S. Masset

Recent work has suggested that the net gravitational force acting on a massive and luminous perturber travelling through a gaseous and opaque medium can have same direction as the perturber's motion (an effect sometimes called negative dynamical friction). Analytic results were obtained using a linear analysis and were later confirmed by means of non-linear

Daniel López-Angulo, Ana Mônica Q. B. Bittante, Carla G. Luciano, German Ayala-Valencia

The effect of Laponite (a synthetic clay) on the structure, thermal and water vapor barrier properties of nanocomposite gelatin films produced by casting with 0, 4.5 and 15% w Lap/w gelatin, was studied. X-ray diffraction, differential scanning calorimetry, thermogravimetric analysis and Fourier transform infrared spectroscopy measurements were reported. The

Kerui Li, Siew-Chong Tan, Ron Shu Yuen Hui

Two-stage wireless power receivers, which typically include an AC-DC diode rectifier and a DC-DC regulator, are popular solutions in low-power wireless power transfer applications. However, the interaction between the rectifier and the regulator may introduce beat frequency oscillation on both the DC-link and output capacitors. In this paper, the cause of th

Andrea Amorese, Martin Sundermann, Brett Leedahl, Andrea Marino

Using inelastic x-ray scattering beyond the dipole limit and hard x-ray photoelectron spectroscopy we establish the dual nature of the U $5f$ electrons in UM$_2$Si$_2$ (M = Pd, Ni, Ru, Fe), regardless of their degree of delocalization. We have observed that the compounds have in common a local atomic-like state that is well described by the U $5f^2$ configur

L. Yalyalieva, G. Carraro, R. Vazquez, L. Rizzo

We present and discuss photometric optical data in the area of the OB association Sco OB1 covering about 1 squared degree. UBVI photometry is employed in tandem with Gaia DR2 data to investigate the 3 dimensional structure and the star formation history of the region. By combining parallaxes and proper motions we identify 7 physical groups located between th

Angelia Nedich, Tatiana Tatarenko

We consider an optimization problem with strongly convex objective and linear inequalities constraints. To be able to deal with a large number of constraints we provide a penalty reformulation of the problem. As penalty functions we use a version of the one-sided Huber losses. The smoothness properties of these functions allow us to choose time-varying penal

Reema Joshi

This paper introduces a new method to find the next prime number after a given prime ${P}$. The proposed method is used to derive a system of inequalities, that serve as constraints which should be satisfied by all primes whose successor is a twin prime. Twin primes are primes having a prime gap of ${2}$. The pairs ${(5,7),(11,13),(41,43)}$, etcetera are all

Pablo G. Ortega

Thunderstorms and lightnings are natural particle accelerator systems. Terrestrial gamma-ray flashes, caused by relativistic runaway electron avalanches, produce bursts of $X$ and $\gamma$ rays, energetic enough to produce photo-nuclear reactions within the atmosphere. Such reactions cause the generation of new isotopes, which modify the air composition loca

Mahid M. Mangontarum

In this paper, we derive formulas for the translated Whitney-Lah numbers and show that they are generalizations of already-existing identities of the classical Lah numbers. q-analogues of the said formulas are also obtained for the case of the translated q-Whitney numbers.

Bhasker Sri Harsha Suri, Kalidas Yeturu

Deep Neural networks forget previously learnt tasks when they are faced with learning new tasks. This is called catastrophic forgetting. Rehearsing the neural network with the training data of the previous task can protect the network from catastrophic forgetting. Since rehearsing requires the storage of entire previous data, Pseudo rehearsal was proposed, w