July 2019 arXiv papers — page 120

Mehrdad Hessar, Ali Najafi, Vikram Iyer, Shyamnath Gollakota

Wireless protocol design for IoT networks is an active area of research which has seen significant interest and developments in recent years. The research community is however handicapped by the lack of a flexible, easily deployable platform for prototyping IoT endpoints that would allow for ground up protocol development and investigation of how such protoc

Masaru Hongo, Toshiaki Fujimori, Tatsuhiro Misumi, Muneto Nitta

We exhaustively construct instanton solutions and elucidate their properties in one-dimensional anti-ferromagnetic chiral magnets based on the $O(3)$ nonlinear sigma model description of spin chains with the Dzyaloshinskii-Moriya (DM) interaction. By introducing an easy-axis potential and a staggered magnetic field, we obtain a phase diagram consisting of gr

Bo Yuan, Ilia Khait, Guo-Jiun Shu, F. C. Chou

The discovery of massless Dirac electrons in graphene and topological Dirac-Weyl materials has prompted a broad search for bosonic analogues of such Dirac particles. Recent experiments have found evidence for Dirac magnons above an Ising-like ferromagnetic ground state in a two-dimensional (2D) kagome lattice magnet and in the van der Waals layered honeycomb

Aneeq Zia, Liheng Guo, Linlin Zhou, Irfan Essa

Purpose: Surgical task-based metrics (rather than entire procedure metrics) can be used to improve surgeon training and, ultimately, patient care through focused training interventions. Machine learning models to automatically recognize individual tasks or activities are needed to overcome the otherwise manual effort of video review. Traditionally, these mod

Bin Wu, Hye Jin Park, Lingshan Wu, Da Zhou

Cooperators forgo their interest to benefit others. Thus cooperation should not be favored by natural selection. It challenges the evolutionists, since cooperation is widespread. As one of the resolutions, information spreading has been revealed to play a key role in the emergence of cooperation. Individuals, however, are typically assumed to be passive in t

Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang

Model-based reinforcement learning (MBRL) is widely seen as having the potential to be significantly more sample efficient than model-free RL. However, research in model-based RL has not been very standardized. It is fairly common for authors to experiment with self-designed environments, and there are several separate lines of research, which are sometimes

Henrik Ronellenfitsch, Jörn Dunkel

Mass-spring networks (MSNs) have long been used as approximate descriptions of many biological and engineered systems, from actomyosin networks to mechanical trusses. In the last decade, MSNs have re-attracted theoretical interest as models for phononic metamaterials with exotic properties such as negative Poisson's ratio, negative effective mass, or gap

Lars Gottesbüren, Michael Hamann, Dorothea Wagner

In this paper, we propose HyperFlowCutter, an algorithm for balanced hypergraph bipartitioning. It is based on minimum S-T hyperedge cuts and maximum flows. It computes a sequence of bipartitions that optimize cut size and balance in the Pareto sense, being able to trade one for the other. HyperFlowCutter builds on the FlowCutter algorithm for partitioning g

Arman Hasanzadeh, Nagaraj T. Janakiraman, Vamsi K. Amalladinne, Krishna R. Narayanan

In this work, we leverage advances in sparse coding techniques to reduce the number of trainable parameters in a fully connected neural network. While most of the works in literature impose $\ell_1$ regularization, DropOut or DropConnect techniques to induce sparsity, our scheme considers feature importance as a criterion to allocate the trainable parameters

Sam Wenke, Dan Saunders, Mike Qiu, Jim Fleming

Learning to use tools to solve a variety of tasks is an innate ability of humans and has been observed of animals in the wild. However, the underlying mechanisms that are required to learn to use tools are abstract and widely contested in the literature. In this paper, we study tool use in the context of reinforcement learning and propose a framework for ana

N. C. Hara, G. Boué, J. Laskar, J. B. Delisle

Eccentricity is a parameter of particular interest as it is an informative indicator of the past of planetary systems. It is however not always clear whether the eccentricity fitted on radial velocity data is real or if it is an artefact of an inappropriate modelling. In this work, we address this question in two steps: we first assume that the model used fo

Donghang Pan, Jingling Yuan, Lin Li, Deming Sheng

The growing prosperity of social networks has brought great challenges to the sentimental tendency mining of users. As more and more researchers pay attention to the sentimental tendency of online users, rich research results have been obtained based on the sentiment classification of explicit texts. However, research on the implicit sentiment of users is st

Gustav Nilsson, Giacomo Como

We study a robust control problem for dynamical flow networks. In the considered dynamical models, traffic flows along the links of a transportation network --modeled as a capacited multigraph-- and queues up at the nodes, whereby control policies determine which incoming queues at a node are to be allocated service simultaneously, within some predetermined

Giovanni Abramo, Dag W. Aksnes, Ciriaco Andrea D'Angelo

This is the first ever attempt of application in a country other than Italy of a research efficiency indicator (FSS), to assess and compare the performance of professors and universities, within and between countries. A special attention has been devoted to the presentation of the methodology developed to set up a common field classification scheme of profes

Ellen Bowler, Peter T. Fretwell, Geoffrey French, Michal Mackiewicz

In this paper we test the use of a deep learning approach to automatically count Wandering Albatrosses in Very High Resolution (VHR) satellite imagery. We use a dataset of manually labelled imagery provided by the British Antarctic Survey to train and develop our methods. We employ a U-Net architecture, designed for image segmentation, to simultaneously clas

Yiwei Bao, Yang Chen

The Vela\,X pulsar wind nebula (PWN) is characterized by the extended radio nebula (ERN) and the central X-ray "cocoon". We have interpreted the $γ$-ray spectral properties of the cocoon in the sibling paper (Bao et al.\,2019); here, we account for the broadband photon spectrum of the ERN. Since the diffusive escape of the electrons from the TeV emit

Yiwei Bao, Siming Liu, Yang Chen

High-energy particle transport in pulsar wind nebulae (PWNe) plays an essential role in explaining the characteristics revealed in multiwavelength observations. In this paper, the TeV-gamma-ray-emitting electrons in the Vela X PWN are approximated to be injected impulsively when the cocoon is formed due to the interaction between the SNR reverse shock and th

Fatma Zohra Ouail, Mohamed El-Amine Chergui

The aim of this study is to find the optimum of a linear fractional function over the efficient set of a multi-objective linear fractional integer program without generating all efficient solutions. By its nature, it is a global optimization problem since the efficient set is discrete, hence not convex. For this purpose, a branch and bound based method is de

Niklas Hohmann

Survivorship analysis allows to statistically analyze situations that can be modeled as waiting times to an event. These waiting times are characterized by the cumulative hazard rate, which can be estimated by the Nelson-Aalen estimator or diverse confidence estimators based on asymptotic statistics. To better understand the small sample properties of these

Aleksey Marchenko, Peter Wadhams, Clarence O Collins, Jean Rabault

The results of field work on drift ice during wave propagation are analyzed and presented. The field work was performed in the Barents Sea, and the main focus of the paper is on wave processes in the MIZ. A model of wave damping in broken ice is formulated and applied to interpret the field work results. It is confirmed that waves of higher frequencies are s

Dong Li, Lin Li

The Q&A community has become an important way for people to access knowledge and information from the Internet. However, the existing translation based on models does not consider the query specific semantics when assigning weights to query terms in question retrieval. So we improve the term weighting model based on the traditional topic translation model an

Ben Adler, Giacomo Boscaini-Gilroy

Factchecking has always been a part of the journalistic process. However with newsroom budgets shrinking it is coming under increasing pressure just as the amount of false information circulating is on the rise. We therefore propose a method to increase the efficiency of the factchecking process, using the latest developments in Natural Language Processing (

Martina Pili

LHCb provides unique opportunities to study $W$ and $Z$ boson production at forward rapidities at the LHC. It has recently been suggested that a measurement of the $W$ boson mass by LHCb would complement measurements by ATLAS and CMS. All measurements of the $W$ mass at hadron colliders are subject to PDF uncertainties, but there would be a partial cancellat

Amina Khatun, Sabya Sachi Chatterjee, Tarak Thakore, Sanjib Kumar Agarwalla

The neutral current non-standard interactions (NSI's) of neutrino with matter fermions while propagating through long distances inside the Earth matter can give rise to the extra matter potentials apart from the standard MSW potential due to the $W$-mediated interactions in matter. In this paper, we explore the impact of flavor violating neutral current

Robert Wille, Lukas Burgholzer, Alwin Zulehner

The recent progress in the physical realization of quantum computers (the first publicly available ones--IBM's QX architectures--have been launched in 2017) has motivated research on automatic methods that aid users in running quantum circuits on them. Here, certain physical constraints given by the architectures which restrict the allowed interactions o

Tak Chu Li, Yi-Hsin Liu, Michael Hesse, Ying Zou

The spreading of the X-line out of the reconnection plane under a strong guide field is investigated using large-scale three-dimensional (3D) particle-in-cell (PIC) simulations in asymmetric magnetic reconnection. A simulation with a thick, ion-scale equilibrium current sheet (CS) reveals that the X-line spreads at the ambient ion/electron drift speeds, sign

Ugo Bindini, Luigi De Pascale

We investigate some of the properties of the mapping from wave-functions to single particle densities, partially answering an open question posed by E. H. Lieb in 1983.

Alejandro Tolcachier

This article is concerned with the study of the holonomy group of flat solvmanifolds. It is known that the holonomy group of a flat solvmanifold is abelian; we give an elementary proof of this fact and moreover we prove that any finite abelian group is the holonomy group of a flat solvmanifold. Furthermore, we show that the minimal dimension of a flat solvma

Ana Achucarro, Yvette Welling

The simplicity of the CMB data, so well described by single-field inflation, raises the question whether there might be an equally simple multi-field realization consistent with the observations. We explore the idea that an approximate 'angular' shift symmetry in field space (an isometry) protects the dynamics of coupled inflationary perturbations. T

J. Vanterler da C. Sousa, Leandro S. Tavares, E. Capelas de Oliveira

In this paper, we investigate the existence and uniqueness of mild and strong solutions of fractional semilinear evolution equations in the Hilfer sense, by means of Banach fixed point theorem and the Gronwall inequality.

Horacio Falomir, Enrique Muñoz, Marcelo Loewe, Renato Zamora

In this article, we investigate the temperature and chemical potential dependence of the optical conductivity of graphene, within a field theoretical representation in the continuum approximation, arising from an underlying tight-binding atomistic model, that includes up to next-to-nearest neighbor coupling. Our calculations allow us to obtain the dependence

Jonas Fassbender

This paper introduces libconform v0.1.0, a Python library for the conformal prediction framework, licensed under the MIT-license. libconform is not yet stable. This paper describes the main algorithms implemented and documents the API of libconform. Also some details about the implementation and changes in future versions are described.

Wenhan Zhang, Zheng Ju, Weida Wu

We investigated the electronic superstructure of graphite surface in the vicinity to monoatomic armchair step edges with scanning tunneling microscopy and spectroscopy. Only the ($\sqrt{3}\times\sqrt{3}$)$\textit{R}$30$^{\circ}$ superstructure is visualized near atomically clean armchair edges, while the honeycomb superstructure is absent. The spectroscopic

I. D. Avdeev, A. N. Poddubny, A. V. Poshakinskiy

We predict that illumination by a plane electromagnetic wave of optically resonant membranes, such as graphene or monolayers of transition metal dichalcogenides, directly affects their mechanical tension. The induced optomechanical tension is anisotropic and, depending on the spectral detuning from the resonance, can be both positive and negative. In the lat

E. A. -B. Abd-Elsalam, Mohamed I. Nouh

Lane Emden differential equation of the polytropic gas sphere could be used to construct simple models of stellar structures, star clusters and many configurations in astrophysics. This differential equation suffers from the singularity at the center and has an exact solution only for the polytropic index n=0,1 and 5. In the present paper, we present an anal

Constance Toulouse, Danila Amoroso, Cong Xin, Philippe Veber

BaZrO3 is a perovskite that remains in the simple cubic phase at all temperatures, hence with no first-order Raman-active phonon mode allowed by symmetry. Yet, it exhibits an intense Raman spectrum with sharp and well-defined features. Here, we report the evolution of the Raman spectrum of BaZrO3 single crystals in a broad temperature range (4--1200~K) and d

Jenan Shtayat, Alaa Al-Kateeb

In this paper, we propose a new of coding/decoding algorithm using Padovan Q-matrices. This method is based on blocked message matrices. an advantage of this method is that the encryption of each message matrix will use a different key and that will increase the security of the method.

Samuel N. Cohen, Martin N. A. Tegnér, Johannes Wiesel

Consider the empirical measure, $\hat{\mathbb{P}}_N$, associated to $N$ i.i.d. samples of a given probability distribution $\mathbb{P}$ on the unit interval. For fixed $\mathbb{P}$ the Wasserstein distance between $\hat{\mathbb{P}}_N$ and $\mathbb{P}$ is a random variable on the sample space $[0,1]^N$. Our main result is that its normalised quantiles are asy

Pawel Mlynarski, Hervé Delingette, Hamza Alghamdi, Pierre-Yves Bondiau

Planning of radiotherapy involves accurate segmentation of a large number of organs at risk, i.e. organs for which irradiation doses should be minimized to avoid important side effects of the therapy. We propose a deep learning method for segmentation of organs at risk inside the brain region, from Magnetic Resonance (MR) images. Our system performs segmenta

Yuan Gao, Jian-Guo Liu

In this paper we study the relaxation process of Peierls-Nabarro dislocation model, which is a gradient flow with singular nonlocal energy and double well potential describing how the materials relax to its equilibrium with the presence of a dislocation. We prove the dynamic solution to Peierls-Nabarro model will converge exponentially to a shifted steady pr

Thomas Le Reun, Michael Le Bars

In this chapter, we explore how gravitational interactions drive turbulent flows inside planetary cores and provide an interesting alternative to convection to explain dynamo action and magnetic fields around terrestrial bodies. In the first section, we introduce tidal interactions and their effects on the shape and rotation of astrophysical bodies. A method

Hjalte Frellesvig, Federico Gasparotto, Manoj K. Mandal, Pierpaolo Mastrolia

Feynman integrals obey linear relations governed by intersection numbers, which act as scalar products between vector spaces. We present a general algorithm for constructing multivariate intersection numbers relevant to Feynman integrals, and show for the first time how they can be used to solve the problem of integral reduction to a basis of master integral

Samuel Fromm

We study the defocusing nonlinear Schrödinger equation in the quarter plane with asymptotically periodic boundary values. By studying an associated Riemann-Hilbert problem and employing nonlinear steepest descent arguments, we construct solutions in a sector close to the boundary whose leading behaviour is described by a single exponential plane wave. Furthe

N. Ding, Q. S. Gu, X. F. Geng, Ding-Rong Xiong

The origin of the multi-band activities (outbursts/flares) of blazars is still a heavily debated topic. Shock and magnetic reconnection have long been considered as possible triggers for the multi-band activities. In this paper, we present an exploration of the origin of multi-band activities for a high-redshift (z =1.8385) FSRQ PKS 1502+106. Utilizing multi

Thomas Gittings, Steve Schneider, John Collomosse

We present a novel method for generating robust adversarial image examples building upon the recent `deep image prior' (DIP) that exploits convolutional network architectures to enforce plausible texture in image synthesis. Adversarial images are commonly generated by perturbing images to introduce high frequency noise that induces image misclassificatio

Franco Flandoli, Francesco Grotto, Dejun Luo

After a short review of recent progresses in 2D Euler equations with random initial conditions and noise, some of the recent results are improved by exploiting a priori estimates on the associated infinite dimensional Fokker-Planck equation. The regularity class of solutions investigated here does not allow energy- or enstrophy-type estimates, but only bound

Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl

We describe an approach for incorporating prior knowledge into machine learning algorithms. We aim at applications in physics and signal processing in which we know that certain operations must be embedded into the algorithm. Any operation that allows computation of a gradient or sub-gradient towards its inputs is suited for our framework. We derive a maxima

Juhyun Lee, Nikolay Chirkov, Ekaterina Ignasheva, Yury Pisarchyk

On-device inference of machine learning models for mobile phones is desirable due to its lower latency and increased privacy. Running such a compute-intensive task solely on the mobile CPU, however, can be difficult due to limited computing power, thermal constraints, and energy consumption. App developers and researchers have begun exploiting hardware accel

Hsu-Chieh Hu, Stephen F. Smith, Rick Goldstein

Recent work in decentralized, schedule-driven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in real-time constructs a schedule that minimizes the cum

Sofya Zaytseva, Junping Shi, Leah B Shaw

Smooth cordgrass Spartina alterniflora is a grass species commonly found in tidal marshes. It is an ecosystem engineer, capable of modifying the structure of its surrounding environment through various feedbacks. The scale-dependent feedback between marsh grass and sediment volume is particularly of interest. Locally, the marsh vegetation attenuates hydrodyn

Haim Kaplan, Katharina Klost, Wolfgang Mulzer, Liam Roditty

Let $S \subset \mathbb{R}^2$ be a set of $n$ sites, where each $s \in S$ has an associated radius $r_s > 0$. The disk graph $D(S)$ is the undirected graph with vertex set $S$ and an undirected edge between two sites $s, t \in S$ if and only if $|st| \leq r_s + r_t$, i.e., if the disks with centers $s$ and $t$ and respective radii $r_s$ and $r_t$ intersect. D

Adnan Aijaz, Aleksandar Stanoev, Mahesh Sooriyabandara

The use of mobile platforms (MPs) is particularly attractive for various industrial applications. This demonstration highlights the importance of remote control of MPs and shows its viability over a high-performance wireless solution designed for closed-loop control. Further, it shows the viability of formation control of a network of MPs through a leader-fo

Hsu-Chieh Hu, Stephen F. Smith

Recent work in decentralized, schedule-driven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in real-time constructs a schedule that minimizes the cum

Majid Ali Choudhary

B. Sahin [9] introduced the notion of anti-invariant Riemannian submersions from almost Hermitian manifolds onto Riemannian manifolds. In the present paper we extend the notion of anti-invariant and Lagrangian Riemannian submersions (a special anti-invariant Riemannian submersion) to the case of locally conformal Kaehler manifolds. We discuss the geometry of

Siddhartha Omar, Bettadahalli Nandishaiah Madhushankar, Bart Jan van Wees

We study spin-transport in bilayer-graphene (BLG), spin-orbit coupled to a tungsten di sulfide (WS$_2$) substrate, and measure a record spin lifetime anisotropy ~40-70, i.e. ratio between the out-of-plane $τ_{\perp}$ and in-plane spin relaxation time $τ_{||}$. We control the injection and detection of in-plane and out-of-plane spins via the shape-anisotropy

F. Surot, E. Valenti, S. L. Hidalgo, M. Zoccali

The bulge represents the best compromise between old and massive Galactic component, and as such its study is a valuable opportunity to understand how the bulk of the Milky Way formed and evolved. In addition, being the only bulge in which we can individually resolve stars in all evolutionary sequences, the properties of its stellar content provide crucial i

Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian

While very deep neural networks have shown effectiveness for computer vision and text classification applications, how to increase the network depth of neural machine translation (NMT) models for better translation quality remains a challenging problem. Directly stacking more blocks to the NMT model results in no improvement and even reduces performance. In

L. V. Bogdanov

It was demonstrated recently [Dunajski, Ferapontov and Kruglikov (2014)] that the Manakov-Santini system describes a local form of general Lorentzian Einstein-Weyl geometry. We introduce integrable matrix extension of the Manakov-Santini system and show that it describes (2+1)-dimensional integrable chiral model in Einstein-Weyl space. We develop a dressing

Matthijs Berghuis, Alexei Halpin, Quynh Le-Van, Mohammad Ramezani

We demonstrate experimentally an enhanced delayed fluorescence in tetracene single crystals strongly coupled to optical modes in open cavities formed by arrays of plasmonic nanoparticles. Hybridization of singlet excitons with collective plasmonic resonances in the arrays leads to the splitting of the material dispersion into a lower and an upper polariton b

Saeid Soheily Khah, Yiming Wu

In digital advertising, Click-Through Rate (CTR) and Conversion Rate (CVR) are very important metrics for evaluating ad performance. As a result, ad event prediction systems are vital and widely used for sponsored search and display advertising as well as Real-Time Bidding (RTB). In this work, we introduce an enhanced method for ad event prediction (i.e. cli

Wankai Tang, Ming Zheng Chen, Jun Yan Dai, Yong Zeng

Many emerging technologies, such as ultra-massive multiple-input multiple-output (UM-MIMO), terahertz (THz) communications are under active discussion as promising technologies to support the extremely high access rate and superior network capacity in the future sixth-generation (6G) mobile communication systems. However, such technologies are still facing m

Debmalya Sain

We study the smoothness and the norm attainment of bounded bilinear operators between Banach spaces, using the concepts of Birkhoff-James orthogonality and semi-inner-products. In the finite-dimensional case, we characterize Birkhoff-James orthogonality of bilinear operators in terms of the norm attainment set. This yields a nice characterization of smoothne

Jure Demšar, Grega Repovš, Erik Štrumbelj

Research in psychology generates interesting data sets and unique statistical modelling tasks. However, these tasks, while important, are often very specific, so appropriate statistical models and methods cannot be found in accessible Bayesian tools. As a result, the use of Bayesian methods is limited to those that have the technical and statistical fundamen

William Béthune, Roman R. Rafikov

Measurements of exoplanetary masses and radii have revealed a population of massive super-Earths --- planets sufficiently large that, according to one dimensional models, they should have turned into gas giants. To better understand the origin of these objects, we carry out hydrodynamical simulations of planetary cores embedded in a nascent protoplanetary di

Alireza Fali, Samuel T. White, Thomas G. Folland, Mingze. He

Hyperbolic phonon polaritons (HPhPs) are generated when infrared photons couple to polar optic phonons in anisotropic media, confining long-wavelength light to nanoscale volumes. However, to realize the full potential of HPhPs for infrared optics, it is crucial to understand propagation and loss mechanisms on substrates suitable for applications from wavegui

Michael McGuigan

We revisit the nonsupersymmetric SO(16)x SO(16)' model in light of LHC and Dark Energy data. Recently nonsupersymmetric models have become of great interest because the LHC has not found evidence of supersymmetry. In addition nonsupersymmetric models with a single Higgs-like field and small one loop vacuum energy have been constructed. Also models of dar

Zach Branson, Luke Keele

Instrumental variable (IV) analyses are becoming common in health services research and epidemiology. Most IV analyses use naturally occurring instruments, such as distance to a hospital. In these analyses, investigators must assume the instrument is as-if randomly assigned. This assumption cannot be tested directly, but it can be falsified. Most falsificati

D. J. Haw, S. J. Hogan

We present a complete analysis of the Schelling dynamical system [Haw2018] of two connected neighbourhoods, with or without population reservoirs, for different types of linear and nonlinear tolerance schedules. We show that stable integration is only possible when the minority is small and combined tolerance is large. Unlike the case of the single neighbour

Michał Przykucki, Thomas Shelton

In this paper we fill in a fundamental gap in the extremal bootstrap percolation literature, by providing the first proof of the fact that for all $d \geq 1$, the size of the smallest percolating sets in $d$-neighbour bootstrap percolation on $[n]^d$, the $d$-dimensional grid of size $n$, is $n^{d-1}$. Additionally, we prove that such sets percolate in time

Marcus Märtens, Dario Izzo

The ability to design complex neural network architectures which enable effective training by stochastic gradient descent has been the key for many achievements in the field of deep learning. However, developing such architectures remains a challenging and resourceintensive process full of trial-and-error iterations. All in all, the relation between the netw

Geunsu Choi, Yun Sung Choi, Miguel Martin

We classify several notions of norm attaining Lipschitz maps which were introduced previously, and present the relations among them in order to verify proper inclusions. We also analyze some results for the sets of Lipschitz maps satisfying each of these properties to be dense or not in $\Lip(X,Y)$. For instance, we characterize a Banach space $Y$ with the R

Florentin Wörgötter, Fatemeh Ziaeetabar, Stefan Pfeiffer, Osman Kaya

Efficient action prediction is of central importance for the fluent workflow between humans and equally so for human-robot interaction. To achieve prediction, actions can be encoded by a series of events, where every event corresponds to a change in a (static or dynamic) relation between some of the objects in a scene. Manipulation actions and others can be

Cedric Perret, Emma Hart, Simon T. Powers

Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their personal characteristics, and secondly, as an institutional hierarchy where leaders and followers are explicitly appointed by group decision. Although both forms can reduce the time spent

David Berger

The goal of this paper is twofold. In the first part we will study Lévy white noise in different distributional spaces and solve equations of the type $p(D)s=q(D)\dot{L}$, where $p$ and $q$ are polynomials. Furthermore, we will study measurability of $s$ in Besov spaces. By using this result we will prove that stochastic partial differential equations of the

Mateusz Kluczek, Raphael Stuhlmeier

We provide an in-depth exploration of the mass-transport properties of Pollard's exact solution for a zonally-propagating surface water-wave in infinite depth. Without resorting to approximations we discuss the Eulerian mass transport of this fully nonlinear, Lagrangian solution. We show that it has many commonalities with the linear, Eulerian wave-theor

Justin Edwards, Elaheh Sanoubari

Across several branches of conversational interaction research including interactions with social robots, embodied agents, and conversational assistants, users have identified trust as a critical part of those interactions. Nevertheless, there is little agreement on what trust means within these sort of interactions or how trust can be measured. In this pape

Lihao Liu, Xiaowei Hu, Lei Zhu, Pheng-Ann Heng

Brain image registration transforms a pair of images into one system with the matched imaging contents, which is of essential importance for brain image analysis. This paper presents a novel framework for unsupervised 3D brain image registration by capturing the feature-level transformation relationships between the unaligned image and reference image. To ac

Allison Perrone, Justin Edwards

Chatbots are popular for both task-oriented conversations and unstructured conversations with web users. Several different approaches to creating comedy and art exist across the field of computational creativity. Despite the popularity and ease of use of chatbots, there have not been any attempts by artists or comedians to use these systems for comedy perfor

Oumuamua ISSI Team

The discovery of the first interstellar object passing through the Solar System, 1I/2017 U1 ('Oumuamua), provoked intense and continuing interest from the scientific community and the general public. The faintness of 'Oumuamua, together with the limited time window within which observations were possible, constrained the information available on its

Serdar Altuntas, Christoph Scheven

We consider critical points $u:Ω\to N$ of the bi-energy \[ \int_Ω|Δu|^2\,d x, \] where $Ω\subset\mathbb{R}^m$ is a bounded smooth domain of dimension $m\ge 5$ and $N\subset\mathbb{R}^L$ a compact submanifold without boundary. More precisely, we consider variationally biharmonic maps $u\in W^{2,2}(Ω,N)$, which are defined as critical points of the bi-energy t

Ahsanul Kabir, Simone Santucci, Ngo Van Nong, Maxim Varenik

Some oxygen defective metal oxides, such as cerium and bismuth oxides, have recently shown exceptional electrostrictive properties that are even superior to the best performing lead-based electrostrictors, e.g. lead-magnesium-niobates (PMN). Compared to piezoelectric ceramics, electromechanical mechanisms of such materials do not depend on crystalline symmet

Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig, Richard L. Berg

The widespread digitization of patient data via electronic health records (EHRs) has created an unprecedented opportunity to use machine learning algorithms to better predict disease risk at the patient level. Although predictive models have previously been constructed for a few important diseases, such as breast cancer and myocardial infarction, we currentl

Sihong Shao, Yunfeng Xiong

The stochastic solutions to the Wigner equation, which explain the nonlocal oscillatory integral operator $Θ_V$ with an anti-symmetric kernel as {the generator of two branches of jump processes}, are analyzed. All existing branching random walk solutions are formulated based on the Hahn-Jordan decomposition $Θ_V=Θ^+_V-Θ^-_V$, i.e., treating $Θ_V$ as the diff

M. J. Page, S. R. Oates, M. De Pasquale, A. A. Breeveld

We examine the the emission from optically bright gamma-ray burst (GRB) afterglows as the Ultraviolet and Optical Telescope (UVOT) on the Neil Gehrels Swift Observatory first begins observing, following the slew to target the GRB, while the pointing of the Swift satellite is still settling. We verify the photometric quality of the UVOT settling data using br

Jijiang Sun, Lin Li, Matija Cencelj, Boštjan Gabrovšek

In this paper, we consider the following nonlinear Kirchhoff type problem: \[ \left\{\begin{array}{lcl}-\left(a+b\displaystyle\int_{\mathbb{R}^3}|\nabla u|^2\right)Δu+V(x)u=f(u), & \textrm{in}\,\,\mathbb{R}^3,\\ u\in H^1(\mathbb{R}^3), \end{array}\right. \] where $a,b>0$ are constants, the nonlinearity $f$ is superlinear at infinity with subcritical growth a

Jinghua Liu, Yong-Guo Shi

The conjugacy problem is one of the central questions in iteration theory. As far as we, for discontinuous strictly monotone maps there is no complete result. In this paper, we investigate the conjugacy problem of strictly monotone maps with only one jump discontinuity. We give some sufficient and necessary conditions for the conjugacy relationship. And we p

Matthäus Zloch, Maribel Acosta, Daniel Hienert, Stefan Dietze

As the availability and the inter-connectivity of RDF datasets grow, so does the necessity to understand the structure of the data. Understanding the topology of RDF graphs can guide and inform the development of, e.g. synthetic dataset generators, sampling methods, index structures, or query optimizers. In this work, we propose two resources: (i) a software

Samuel Roth

We construct dendrites with endpoint sets isometric to any totally disconnected compact metric space. This allows us to embed zero-dimensional dynamical systems into dendrites and solve a problem regarding Li-Yorke and distributional chaos.

Abdelkerim Amari, Sebastiaan Goossens, Yunus Can Gultekin, Olga Vassilieva

The performance of enumerative sphere shaping (ESS), constant composition distribution matching (CCDM), and uniform signalling are compared at the same forward error correction rate. ESS is shown to offer a reach increase of approximately 10% and 22% compared to CCDM and uniform signalling, respectively.

A. Abramian, O. Devauchelle, G. Seizilles, E. Lajeunesse

The coupling of sediment transport with the flow that drives it allows rivers to shape their own bed. Cross-stream fluxes of sediment play a crucial, yet poorly understood, role in this process. Here, we track particles in a laboratory flume to relate their statistical behavior to the self organization of the granular bed they make up. As they travel downstr

Christoph Heindl, Sebastian Zambal, Josef Scharinger

This work considers robot keypoint estimation on color images as a supervised machine learning task. We propose the use of probabilistically created renderings to overcome the lack of labeled real images. Rather than sampling from stationary distributions, our approach introduces a feedback mechanism that constantly adapts probability distributions according

V. V. Sargsyan, H. Lenske, G. G. Adamian, N. V. Antonenko

The Darwin instability effect in the binary systems (planets, stars, and galaxies) is analyzed within the model based on the Regge-like laws. New analytical formulas are presented for the relative distance between components of the binary and orbital rotation period of the binary.

Shyuichi Izumiya, Ana Claudia Nabarro, Andrea de Jesus Sacramento

Submanifolds in Lorentz-Minkowski space are investigated from various mathematical viewpoints and are of interest also in relativity theory. We define the hyperbolic surface and the de Sitter surface of a curve in the spacelike hypersurface M in the Minkowski 4-space. These surfaces are respectively located in the hyperbolic 3-space and in the de Sitter 3-sp

Wilhelm Hasselbring, Sören Henning, Björn Latte, Armin Möbius

The visions and ideas of Industry 4.0 require a profound interconnection of machines, plants, and IT systems in industrial production environments. This significantly increases the importance of software, which is coincidentally one of the main obstacles to the introduction of Industry 4.0. Lack of experience and knowledge, high investment and maintenance co

Martin Geier, Samarjit Chakraborty

Over the last two decades, the majority of German universities adopted various characteristics of the prevailing North-American academic system, resulting in significant changes in several key areas that include, e.g., both teaching and research. The universities' internal organizational structures, however, still follow a traditional, decentralized sche

Shekhar Das, Goutam Sheet

We present the construction and performance of a plug-n-play type point contact spectroscopy probe equipped with a piezo-driven coarse approach mechanism for sub-kelvin applications. A modular assembly has been built which can be placed in or taken out from a sub-Kelvin socket mounted inside a He3 cryostat (with a 7 Tesla magnet) using an external manipulato

Juliaana Juurakko, Zenith Purisha, Simo Särkkä

This is the documentation of Computed Tomography (CT) data of a pen-spring. The open data set is available at https://zenodo.org/record/3266936#.XRyMdCZS9oA and can be freely used for scientific purposes with appropriate references to the data and to this document in arxiv.org. The provided data set includes the X-ray sinograms ({\tt finalSino}) of a single

Wilhelm Wimmer, Clair Vandersteen, Nicolas Guevara, Marco Caversaccio

The cochlea, the auditory part of the inner ear, is a spiral-shaped organ with large morphological variability. An individualized assessment of its shape is essential for clinical applications related to tonotopy and cochlear implantation. To unambiguously reference morphological parameters, reliable recognition of the cochlear modiolar axis in computed tomo

Myowin Htwe, Peter Y. H. Pang, Yifu Wang

We are concerned with the Keller--Segel--Navier--Stokes system \begin{equation*} \left\{ \begin{array}{ll} ρ_t+u\cdot\nablaρ=Δρ-\nabla\cdot(ρ\mathcal{S}(x,ρ,c)\nabla c)-ρm, &\!\! (x,t)\in Ω\times (0,T), \\ m_t+u\cdot\nabla m=Δm-ρm, &\!\! (x,t)\in Ω\times (0,T), \\ c_t+u\cdot\nabla c=Δc-c+m, & \!\! (x,t)\in Ω\times (0,T), \\ u_t+ (u\cdot \nabla) u=Δu-\nabla P

Manijeh Bashar, Alister G. Burr, Katsuyuki Haneda, Kanapathippillai Cumanan

A low complexity massive multiple-input multiple-output (MIMO) technique is studied with a geometry-based stochastic channel model, called COST 2100 model. We propose to exploit the discrete-time Fourier transform of the antenna correlation function to perform user scheduling. The proposed algorithm relies on a trade off between the number of occupied bins o