February 2019 arXiv papers — page 10

Kyu Jung Bae, Howard Baer, Vernon Barger, Dibyashree Sengupta

The supersymmetry preserving mu parameter in SUSY theories is naively expected to be of order the Planck scale while phenomenology requires it to be of order the weak scale. This is the famous SUSY mu problem. Its solution involves two steps: 1. first forbid mu, perhaps via some symmetry, and then 2. re-generate it of order the scale of soft SUSY breaking te

Stephan Stetina

I calculate the rate of electromagnetic scattering in degenerate and partially degenerate plasmas composed of electrons, muons, protons, and neutrons. Correlations with strong interactions, induced by the polarizability of electromagnetically and strongly charged protons, are taken into account. At subnuclear densities induced interactions are shown to cause

Bindita Chaudhuri, Noranart Vesdapunt, Baoyuan Wang

Facial motion retargeting is an important problem in both computer graphics and vision, which involves capturing the performance of a human face and transferring it to another 3D character. Learning 3D morphable model (3DMM) parameters from 2D face images using convolutional neural networks is common in 2D face alignment, 3D face reconstruction etc. However,

Chung Ting Ke, Christian M. Moehle, Folkert K. de Vries, Candice Thomas

Two-dimensional electron gases (2DEGs) coupled to superconductors offer the opportunity to explore a variety of quantum phenomena. These include the study of novel Josephson effects, superconducting correlations in quantum (spin) Hall systems, hybrid superconducting qubits and emergent topological states in semiconductors with spin-orbit interaction (SOI). I

Weizhao Shao, Srinivasan Vijayarangan, Cong Li, George Kantor

Simultaneous Localization and Mapping (SLAM) is a fundamental task to mobile and aerial robotics. LiDAR based systems have proven to be superior compared to vision based systems due to its accuracy and robustness. In spite of its superiority, pure LiDAR based systems fail in certain degenerate cases like traveling through a tunnel. We propose Stereo Visual I

Wenbo Li, Pengchuan Zhang, Lei Zhang, Qiuyuan Huang

In this paper, we propose Object-driven Attentive Generative Adversarial Newtorks (Obj-GANs) that allow object-centered text-to-image synthesis for complex scenes. Following the two-step (layout-image) generation process, a novel object-driven attentive image generator is proposed to synthesize salient objects by paying attention to the most relevant words i

John Leuner

Recent research used machine learning methods to predict a person's sexual orientation from their photograph (Wang and Kosinski, 2017). To verify this result, two of these models are replicated, one based on a deep neural network (DNN) and one on facial morphology (FM). Using a new dataset of 20,910 photographs from dating websites, the ability to predic

Dushan N. Wadduwage, Jong Kang Park, Josiah R. Boivin, Yi Xue

From multi-photon imaging penetrating millimeters deep through scattering biological tissue, to super-resolution imaging conquering the diffraction limit, optical imaging techniques have greatly advanced in recent years. Notwithstanding, a key unmet challenge in all these imaging techniques is to perform rapid wide-field imaging through a turbid medium. Stra

Debabrata Karmakar, Gershon Wolansky

We study the global in time existence of solutions to the parabolic-elliptic Patlak-Keller-Segel system of multi-species populations. We prove that if the initial mass satisfies an appropriate notion of sub-criticality, then the system has a solution defined for all time. We explore the gradient flow structure in the Wasserstein space to study the question o

Carolyn A. Raithel, Feryal Ozel, Dimitrios Psaltis

Observations of isolated neutron stars place constraints on the equation of state (EOS) of cold, neutron-rich matter, while nuclear physics experiments probe the EOS of hot, symmetric matter. Many dynamical phenomena, such as core-collapse supernovae, the formation and cooling of proto-neutron stars, and neutron star mergers, lie between these two regimes an

Amos Beimel, Shay Moran, Kobbi Nissim, Uri Stemmer

We present a private learner for halfspaces over an arbitrary finite domain $X\subset \mathbb{R}^d$ with sample complexity $mathrm{poly}(d,2^{\log^*|X|})$. The building block for this learner is a differentially private algorithm for locating an approximate center point of $m>\mathrm{poly}(d,2^{\log^*|X|})$ points -- a high dimensional generalization of the

Vladislav Borisov, Rafael M. Fernandes, Roser Valentí

Recent experiments reported an unusual nematic behavior of heavily hole-doped pnictides $A$Fe$_{2}$As$_{2}$, with alkali $A$ = Rb, Cs. In contrast to the $B_{2g}$ nematic order of the parent $Ae$Fe$_{2}$As$_{2}$ compounds (with alkaline earth $Ae$ = Sr, Ba), characterized by unequal nearest-neighbor Fe-Fe bonds, in the hole-doped systems nematic order is obs

Yayaati Chachan, David J. Stevenson

The higher order gravitational moments of a differentially rotating planet are greatly affected or even dominated by the near surface differential flow. Unlike the contribution from rigid body rotation, this part of the gravity field can be well estimated by linear theory when the differential rotation is on cylinders and the corresponding gravity field aris

João L. Costa, Pedro M. Girão

We consider smooth solutions of the wave equation, on a fixed black hole region of a subextremal Reissner-Nordström (asymptotically flat, de Sitter or anti-de Sitter) spacetime, whose restrictions to the event horizon have compact support. We provide criteria, in terms of surface gravities, for the waves to remain in $C^l$, $l\geq 1$, up to and including the

Harshil Kamdar, Charlie Conroy, Yuan-Sen Ting, Ana Bonaca

The clustered nature of star formation should produce a high degree of structure in the combined phase and chemical space in the Galactic disk. To date, observed structure of this kind has been mostly limited to bound clusters and moving groups. In this paper we present a new dynamical model of the Galactic disk that takes into account the clustered nature o

Gao-Yuan Zhang, Jonathan D. Slavin, Adam Foster, Randall K. Smith

The mixed morphology class of supernova remnants (MMSNRs) comprises a substantial fraction of observed remnants and yet there is as yet no consensus on their origin. A clue to their nature is the presence of regions that show X-ray evidence of recombining plasmas. Recent calculations of remnant evolution in a cloudy interstellar medium (ISM) that included th

M. Fredslund Andersen, P. Pallé, J. Jessen-Hansen, K. Wang

Context. We present the first high-cadence multi-wavelength radial-velocity observations of the Sun-as-a-star, carried out during 57 consecutive days using the stellar échelle spectrograph at the Hertzsprung SONG Telescope operating at the Teide Observatory. Aims. The aim was to produce a high-quality data set and reference values for the global helioseismic

Gao-Yuan Zhang, Adam Foster, Randall Smith

We describe an improved nonequilibrium ionization (NEI) method that we have developed as an optional module for the FLASH magnetohydrodynamic simulation code. The method employs an eigenvalue approach rather than the earlier iterative ordinary differential equation approach to solve the stiff differential equations involved in NEI calculations. The new code

Aaron B. Pearlman, Walid A. Majid, Thomas A. Prince

The Deep Space Network (DSN) is a worldwide array of radio telescopes that supports NASA's interplanetary spacecraft missions. When the DSN antennas are not communicating with spacecraft, they provide a valuable resource for performing observations of radio magnetars, searches for new pulsars at the Galactic Center, and additional pulsar-related studies.

Maksym Lisogorskyi, Hugh Jones, Fabo Feng

The Alpha Centauri system is the primary target for planet search as it is the closest star system composed of a solar twin Alpha Centauri A, a K-dwarf Alpha Centauri B and an M-dwarf Proxima Centauri, which has a confirmed planet in the temperate zone. Alpha Centauri A & B were monitored intensively with the HARPS spectrograph for over 10 years, providing h

Pawel Korus, Nasir Memon

Forensic analysis of digital photographs relies on intrinsic statistical traces introduced at the time of their acquisition or subsequent editing. Such traces are often removed by post-processing (e.g., down-sampling and re-compression applied upon distribution in the Web) which inhibits reliable provenance analysis. Increasing adoption of computational meth

Yaping Mao, Zhao Wang, Colton Magnant, Ingo Schiermeyer

Given a graph $G$ and a positive integer $k$, define the \emph{Gallai-Ramsey number} to be the minimum number of vertices $n$ such that any $k$-edge coloring of $K_n$ contains either a rainbow (all different colored) triangle or a monochromatic copy of $G$. In this paper, we obtain general upper and lower bounds on the Gallai-Ramsey numbers for fans $F_{m} =

A. A. Andrianov, V. A. Andrianov, D. Espriu, A. V. Iakubovich

The possibility of the formation of a local parity breaking (LPB) in a quark-hadron medium is examined as a result of chiral symmetry violation, i.e, the appearance of difference between the average densities of right- and left-handed quarks in the fireball after heavy-ion collisions (HIC). Using the effective meson Lagrangian motivated by QCD extended to th

Yanzhi Chen, Michael U. Gutmann

Approximate Bayesian computation (ABC) is a set of techniques for Bayesian inference when the likelihood is intractable but sampling from the model is possible. This work presents a simple yet effective ABC algorithm based on the combination of two classical ABC approaches --- regression ABC and sequential ABC. The key idea is that rather than learning the p

Natanael Arndt, Michael Martin

The World Wide Web and the Semantic Web are designed as a network of distributed services and datasets. In this network and its genesis, collaboration played and still plays a crucial role. But currently we only have central collaboration solutions for RDF data, such as SPARQL endpoints and wiki systems, while decentralized solutions can enable applications

Cesare Davini, Antonino Favata, Roberto Paroni

We deduce a non-linear continuum model of graphene for the case of finite out-of-plane displacements and small in-plane deformations. On assuming that the lattice interactions are governed by the Brenner's REBO potential of 2nd generation and that self-stress is present, we introduce discrete strain measures accounting for up-to-the-third neighbor intera

Imon Banerjee, Luis de Sisternes, Joelle Hallak, Theodore Leng

We propose a hybrid sequential deep learning model to predict the risk of AMD progression in non-exudative AMD eyes at multiple timepoints, starting from short-term progression (3-months) up to long-term progression (21-months). Proposed model combines radiomics and deep learning to handle challenges related to imperfect ratio of OCT scan dimension and train

Sayna Firoozi Yeganeh, Ahmadreza Mahmoudzadeh, Mohammad Amin Azizpour, Amir Golroo

Smartphones are equipped with sensors such as accelerometers, gyroscope, and GPS in one cost-effective device with an acceptable level of accuracy. There have been some research studies carried out in terms of using smartphones to measure the pavement roughness. However, a little attention has been paid to investigate the validity of the measured pavement ro

Fadhel Ayed, François Caron

We present a Bayesian nonparametric Poisson factorization model for modeling network data with an unknown and potentially growing number of overlapping communities. The construction is based on completely random measures and allows the number of communities to either increase with the number of nodes at a specified logarithmic or polynomial rate, or be bound

Alexander Kurtenkov, Mirela Napetova

Data from the VSX, SDSS DR12, and Gaia DR2 catalogs were combined in order to explore the observed temperature distribution of known contact binaries. Color-temperature relations were applied to calculate the effective temperatures of approximately 20000 binaries and a temperature distribution was built using the results with a precision better than 160 K. T

Mark L. Lewis

We consider groups where the centers of the irreducible characters form a chain. We obtain two alternate characterizations of these groups, and we obtain some information regarding the structure of these groups. Using our results, we are able to classify those groups where the kernels of the irreducible characters form a chain. We show that a result of Nenci

Grzegorz Szamel

We present a theory for the single-particle dynamics in binary mixtures with particle size swaps. The general structure of the theory follows that of the theory for the collective dynamics in binary mixtures with particle size swaps, which we developed previously [G. Szamel, Phys. Rev. E 98, 050601(R) (2018)]. Particle size swaps open up an additional relaxa

Matthew J. O'Rourke, Nicholas R. Hutzler

Laser cooling is a powerful method to control molecules for applications in precision measurement, as well as quantum information, many-body physics, and fundamental chemistry. However, many optically-active metal centers in valence states which are promising for these applications, especially precision measurement, are difficult to laser cool. In order to e

R. Gohil, D. R. Ballantyne, G. Li

Nuclear starburst discs (NSDs) are very compact star-forming regions in the centers of galaxies that have been studied as a possible origin for the absorbing gas around a central active galactic nucleus. NSDs may be most relevant at $z\sim 1$ when obscured accretion onto supermassive black holes (SMBHs) is common. This paper describes the characteristics of

Jia-Qi Zhou, Qi-Ping Su, Chui-Ping Yang

Implementation of discrete-time quantum walk (DTQW) with superconducting qubits is difficult since on-chip superconducting qubits cannot hop between lattice sites. We propose an efficient protocol for the implementation of DTQW in circuit quantum electrodynamics (QED), in which only $N+1$ qutrits and $N$ assistant cavities are needed for an $N$-step DTQW. Th

Andrea Simonetto, Julien Monteil, Claudio Gambella

In this paper, we propose a novel, computational efficient, dynamic ridesharing algorithm. The beneficial computational properties of the algorithm arise from casting the ridesharing problem as a linear assignment problem between fleet vehicles and customer trip requests within a federated optimization architecture. The resulting algorithm is up to four time

Saif Alabachi, Gita Sukthankar, Rahul Sukthankar

Object detection models based on convolutional neural networks (CNNs) demonstrate impressive performance when trained on large-scale labeled datasets. While a generic object detector trained on such a dataset performs adequately in applications where the input data is similar to user photographs, the detector performs poorly on small objects, particularly on

E. Chiaraluce, G. Bruni, F. Panessa, M. Giroletti

A strong effort has been devoted to understand the physical origin of radio emission from low-luminosity AGN (LLAGN), but a comprehensive picture is still missing. We used high-resolution ($\le$1 arcsec), multi-frequency (1.5, 5.5, 9 and 14 GHz) NSF's Karl G. Jansky Very Large Array (VLA) observations to characterise the state of the nuclear region of te

Yossi Mosbacher, Micha Weiss, Hagar Landsman, Nadav Priel

We identify a number of crystalline structures with promising characteristics to serve as a detection medium for a novel Dark Matter (DM) detector with a low threshold energy. A detector of this kind can be specifically useful in application requiring the detection of nuclear recoils, such as in direct detection of low mass DM, coherent neutrino scattering a

Ramiro D. Camino, Christian A. Hammerschmidt, Radu State

Datasets with missing values are very common on industry applications, and they can have a negative impact on machine learning models. Recent studies introduced solutions to the problem of imputing missing values based on deep generative models. Previous experiments with Generative Adversarial Networks and Variational Autoencoders showed interesting results

David Cushing, Supanat Kamtue, Norbert Peyerimhoff, Leyna Watson May

We give a classification of all connected quartic graphs which are (infinity) curvature sharp in all vertices with respect to Bakry-Émery curvature. The result is based on a computer classification by F. Gurr and L. Watson May and a combinatorial case by case investigation.

Emanuel Rodríguez Cirone

Let l be a commutative ring with unit. Garkusha constructed a functor from the category of l-algebras into a triangulated category D, that is a universal excisive and homotopy invariant homology theory. Later on, he provided different descriptions of D, as an application of his motivic homotopy theory of algebras. Using these, it can be shown that D is trian

Fionn Murtagh

It is demonstrated how linear computational time and storage efficient approaches can be adopted when analyzing very large data sets. More importantly, interpretation is aided and furthermore, basic processing is easily supported. Such basic processing can be the use of supplementary, i.e. contextual, elements, or particular associations. Furthermore pixella

James Damon

We consider geodesic flows between hypersurfaces in $\R^n$. However, rather than consider using geodesics in $\R^n$, which are straight lines, we consider an induced flow using geodesics between the tangent spaces of the hypersurfaces viewed as affine hyperplanes. For naturality, we want the geodesic flow to be invariant under rigid transformations and homot

Xiao Li, Allan H. MacDonald, Hua Chen

Most canted antiferromagnets are also anomalous Hall antiferromagnets (AHE AFMs), i.e. they have an anomalous Hall response and other responses with the same symmetry requirements. We suggest that AHE AFMs are promising materials as hosts for high-temperature quantum anomalous Hall effects. By considering models of two-dimensional (001) perovskite layers wit

Stanislav Peshterliev, Alexander Hsieh, Imre Kiss

Voice-assistants text classification and named-entity recognition (NER) models are trained on millions of example utterances. Because of the large datasets, long training time is one of the bottlenecks for releasing improved models. In this work, we develop F10-SGD, a fast optimizer for text classification and NER elastic-net linear models. On internal datas

Georg Böcherer, Diego Lentner, Alessandro Cirino, Fabian Steiner

Linear layered probabilistic shaping (LLPS) is proposed, an architecture for linear codes to efficiently encode to shaped code words. In the previously proposed probabilistic amplitude shaping (PAS) architecture, a distribution matcher (DM) maps information bits to shaped bits, which are then systematically encoded by appending uniformly distributed parity b

Luca Rossetto, Mahnaz Amiri Parian, Ralph Gasser, Ivan Giangreco

This paper presents an after-the-fact summary of the participation of the vitrivr system to the 2019 Video Browser Showdown. Analogously to last year's report, the focus of this paper lies on additions made since the original publication and the system's performance during the competition.

Kurniawan D. Irianto, Juan A. Cabrera, Giang T. Nguyen, Hani Salah

Well-known error detection and correction solutions in wireless communications are slow or incur high transmission overhead. Recently, notable solutions like PRAC and DAPRAC, implementing partial packet recovery with network coding, could address these problems. However, they perform slowly when there are many errors. We propose S-PRAC, a fast scheme for par

Hervé Le Ferrand

In this article, we are interested in the life and scientific work of the Belgian mathematician Paul Mansion. The year 2019 marks the centenary of his passing. We bring some new insights into Paul Mansion's work thanks to his scientific correspondence at the Royal Library in Brussels.

Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra

Recently,there has been a lot of interest in building compact models for video classification which have a small memory footprint (<1 GB). While these models are compact, they typically operate by repeated application of a small weight matrix to all the frames in a video. E.g. recurrent neural network based methods compute a hidden state for every frame of t

C. Güttler, T. Mannel, A. Rotundi, S. Merouane

Before Rosetta, the space missions Giotto and Stardust shaped our view on cometary dust, supported by plentiful data from Earth based observations and interplanetary dust particles collected in the Earth&#39;s atmosphere. The Rosetta mission at comet 67P/Churyumov-Gerasimenko was equipped with a multitude of instruments designed to study cometary dust. While

Michael Kapralov, Ameya Velingker, Amir Zandieh

The Discrete Fourier Transform (DFT) is a fundamental computational primitive, and the fastest known algorithm for computing the DFT is the FFT (Fast Fourier Transform) algorithm. One remarkable feature of FFT is the fact that its runtime depends only on the size $N$ of the input vector, but not on the dimensionality of the input domain: FFT runs in time $O(

Marco Martins Afonso, Philippe Meliga, Eric Serre

With the aim of providing a first step in the quest for a reduction of the aerodynamic drag on the rear-end of a car, we study the phenomena of separation and reattachment of an incompressible flow focusing on a specific aerodynamic geometry, namely a backward-slanted step at 25 degrees of inclination. The ensuing recirculation bubble provides the basis for

Nicolas Curien, Cyril Marzouk

The infinite discrete stable Boltzmann maps are &#34;heavy-tailed&#34; generalisations of the well-known Uniform Infinite Planar Quadrangulation. Very efficient tools to study these objects are Markovian step-by-step explorations of the lattice called peeling processes. Such a process depends on an algorithm which selects at each step the next edge where the

Yu Li, Zhiping Yin, Zhonghao Liu, Weiyi Wang

We use inelastic neutron scattering to study energy and wave vector dependence of spin fluctuations in SrCo$_2$As$_2$, derived from SrFe$_{2-x}$Co$_x$As$_2$ iron pnictide superconductors. Our data reveals the coexistence of antiferromagnetic (AF) and ferromagnetic (FM) spin fluctuations at wave vectors $\textbf{Q}_{\rm AF}$=(1,0) and $\textbf{Q}_{\rm FM}$=(0

Craig Innes, Alex Lascarides

Methods for learning and planning in sequential decision problems often assume the learner is aware of all possible states and actions in advance. This assumption is sometimes untenable. In this paper, we give a method to learn factored markov decision problems from both domain exploration and expert assistance, which guarantees convergence to near-optimal b

Remi Bonnefoi, Lilian Besson, Julio Manco-Vasquez, Christophe Moy

In this paper, we propose and evaluate different learning strategies based on Multi-Arm Bandit (MAB) algorithms. They allow Internet of Things (IoT) devices to improve their access to the network and their autonomy, while taking into account the impact of encountered radio collisions. For that end, several heuristics employing Upper-Confident Bound (UCB) alg

Florian Besau, Thomas Hack, Peter Pivovarov, Franz E. Schuster

The spherical centroid body of a centrally-symmetric convex body in the Euclidean unit sphere is introduced. Two alternative definitions - one geometric, the other probabilistic in nature - are given and shown to lead to the same objects. The geometric approach is then used to establish a number of basic properties of spherical centroid bodies, while the pro

Leah Comment, Brent A. Coull, Corwin Zigler, Linda Valeri

Bayesian causal inference offers a principled approach to policy evaluation of proposed interventions on mediators or time-varying exposures. We outline a general approach to the estimation of causal quantities for settings with time-varying confounding, such as exposure-induced mediator-outcome confounders. We further extend this approach to propose two Bay

Markus J. Aschwanden

Coronal loops in active regions are often characterized by quasi-circular and helically twisted (sigmoidal) geometries, which are consistent with dipolar potential field models in the former case, and with nonlinear force-free field models with vertical currents in the latter case. Alternatively, Parker-type nanoflare models of the solar corona hypothesize t

A. F. Marino, G. S. Da Costa, A. R. Casey, M. Asplund

We present results from the analysis of high-resolution spectra obtained with the Keck HIRES spectrograph for a sample of 17 candidate extremely metal-poor (EMP) stars originally selected from commissioning data obtained with the SkyMapper telescope. Fourteen of the stars have not been observed previously at high dispersion. Three have [Fe/H]<=-3.0 while the

Sabreen Hammouda, Manuel Angst

We report the controlled growth of single crystals of intercalated layered Lu$ _{1+n} $Fe$ _{2+n} $O$ _{4+3n-δ} $ ($ n $=1,2) with different oxygen stoichiometries $δ$. For the first time crystals sufficiently stoichiometric to exhibit superstructure reflections in X-ray diffraction attributable to charge ordering were obtained. The estimated correlation len

Jun Yin, Salvatore Calabrese, Edoardo Daly, Amilcare Porporato

It is well known that evaporative cooling of Earth&#39;s surface water reduces the amount of radiation that goes into sensible heat, namely the portion of radiation that produces higher temperatures. However, a rigorous use of long-term hydrologic measurements and the related theories of hydrologic partitioning have not yet been fully exploited to quantify t

Barbara Kaltenbacher, Vanja Nikolić

We study the Jordan--Moore--Gibson--Thompson (JMGT) equation, a third order in time wave equation that models nonlinear sound propagation, in the practically relevant setting of Neumann and absorbing boundary conditions. In the analysis, we pay special attention to dependencies on the coefficient $τ$ of the third order time derivative that plays the physical

Peter Zeidman, Amirhossein Jafarian, Mohamed L. Seghier, Vladimir Litvak

This tutorial provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). This involves specifying a hierarchical model with two or more levels. At the first level, state space models (DCMs) are used to infer the effective connec

Paul Breutmann

Moduli spaces of global $\mathbb G$-shtukas play a crucial role in the Langlands program for function fields. We analyze their functoriality properties following a change of the curve and a change of the group scheme $\mathbb G$ under various aspects. In particular, we prove two finiteness results which are of interest in the study of stratifications of thes

Pavel Kornilovitch

A three-fermion problem in a three-dimensional lattice with anisotropic hopping is solved by discretizing the Schroedinger equation in momentum space. Interparticle interaction comprises on-site Hubbard repulsion and in-plane nearest-neighbor attraction. By comparing the energy of three-fermion bound clusters (trions) with the energy of one pair plus one fre

Peter Zeidman, Amirhossein Jafarian, Nadège Corbin, Mohamed L. Seghier

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs of researchers in cognitive and clinical neuroscience. In this tutorial, we step through an exemplar fMR

V. Dotsenko, A. Maciolek, G. Oshanin, O. A. Vasilyev

The basic phenomenology of experimentally observed synchronization (i.e., a stochastic phase locking) of identical, beating flagella of a biflagellate alga is known to be captured well by a minimal model describing the dynamics of coupled, limit-cycle, noisy oscillators (known as the noisy Kuramoto model). As demonstrated experimentally, the amplitudes of th

Kyle C. Augustson, Stéphane Mathis

Gravito-inertial waves can be excited at the interface of convective and radiative regions and by the Reynolds stresses in the bulk of the convection zone. The magnitude of their energy flux will therefore vary with the properties of the convection. To assess how convection changes with rotation, a simplified local monomodal model for rotating convection is

Kyle C. Augustson, Stéphane Mathis

A monomodal model for stellar and planetary convection is derived for the magnitude of the rms velocity, degree of superadiabaticity, and characteristic length scale as a function of rotation rate as well as with thermal and viscous diffusivities. The convection model is used as a boundary condition for a linearization of the equations of motion in the trans

Barton J. Pritzl, Thomas C. Gehrman, Ricardo Salinas, Márcio Catelan

We present new photometry and analysis of the twelve variable stars (nine RR Lyrae, three SX Phoenicis) belonging to the Sagittarius globular cluster Arp 2. Of the nine RR Lyrae stars in the cluster, eight are RRab and one is RRc. From the RRab stars, we determined a mean period of $\langle P_{ab}\rangle=0.581\pm0.047$ days, where the error is the standard e

Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan

We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving. We consider three technology pillars for architecting dependable autonomy, namely diverse redundancy, information fusion, and runtime monitoring. For learning-enabled components, we additionally s

Claus Metzner

In chemotaxis, cells are modulating their migration patterns in response to concentration gradients of a guiding substance. Immune cells are believed to use such chemotactic sensing for remotely detecting and homing in on pathogens. Considering that an immune cells may encounter a multitude of targets with vastly different migration properties, ranging from

Fernando Nobre, Christoffer Heckman

We propose a solution for sensor extrinsic self-calibration with very low time complexity, competitive accuracy and graceful handling of often-avoided corner cases: drift in calibration parameters and unobservable directions in the parameter space. It consists of three main parts: 1) information-theoretic based segment selection for constant-time estimation;

Sima Sharifirad, Stan Matwin

Sexism is very common in social media and makes the boundaries of freedom tighter for feminist and female users. There is still no comprehensive classification of sexism attracting natural language processing techniques. Categorizing sexism in social media in the categories of hostile or benevolent sexism are so general that simply ignores the other types of

Xiaojun Huang, Wanke Yin

We prove equality of the vector field (iterated commutator) type and the regular contact type, which together with the Bloom theorem on equality of the Levi-form type and the regular contact type provides a complete solution of a long standing open problem of Bloom in the case of complex dimension three. For general dimensions, we verify the Bloom conjecture

Ting Zhang, Bang Liu, Di Niu, Kunfeng Lai

A large number of deep learning models have been proposed for the text matching problem, which is at the core of various typical natural language processing (NLP) tasks. However, existing deep models are mainly designed for the semantic matching between a pair of short texts, such as paraphrase identification and question answering, and do not perform well o

Erla Sturludottir, Gudjon Mar Sigurdsson, Gunnar Stefansson

The common fisheries policy aims at eliminating discarding which has been part of fisheries for centuries. It is important to monitor the compliance with the new regulations but estimating the discard rate is a challenging task, especially where the practise is illegal. The aim of this study was to review a length-based method that has been used to estimate

María Eugenia Cejas, Irene Drelichman, Javier C. Martínez-Perales

We obtain improved fractional Poincaré inequalities in John domains of a metric space $(X, d)$ endowed with a doubling measure $μ$ under some mild regularity conditions on the measure $μ$. We also give sufficient conditions on a bounded domain to support fractional Poincaré type inequalities in this setting.

Pavel Zorin-Kranich

The first three results in this thesis are motivated by a far-reaching conjecture on boundedness of singular Brascamp-Lieb forms. Firstly, we improve over the trivial estimate for their truncations, thus excluding potential trivial counterexamples. Secondly, in a dyadic model we give a partial result in the trilinear, 2-dimensional case when one of the funct

Liuyang Lu, Yanxiang Jiang, Mehdi Bennis, Zhiguo Ding

In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated. By considering the unknown spatio-temporal content popularity and user preference, a user request model based on hidden Markov process is proposed to characterize the fluctuant spatio-temporal traffic demands in F-RANs. Then, the Q-learning method based

Michael P. Howard, Arash Nikoubashman, Jeremy C. Palmer

Multiparticle collision dynamics (MPCD) is a flexible and robust mesoscale computational technique for simulating solvent-mediated hydrodynamic interactions in soft materials. Here, we provide a critical overview of the MPCD method and summarize its current strengths and limitations. The capabilities of the method are highlighted by reviewing its recent appl

Gaëlle Loosli

The proposed work aims at proposing a alternative kernel decomposition in the context of kernel machines with indefinite kernels. The original paper of KSVM (SVM in Kreǐn spaces) uses the eigen-decomposition, our proposition avoids this decompostion. We explain how it can help in designing an algorithm that won&#39;t require to compute the full kernel matrix

Ronghua Xu, Seyed Yahya Nikouei, Yu Chen, Erik Blasch

Thanks to rapid technological advances in the Internet of Things (IoT), a smart public safety (SPS) system has become feasible by integrating heterogeneous computing devices to collaboratively provide public protection services. While a service oriented architecture (SOA) has been adopted by IoT and cyber-physical systems (CPS), it is difficult for a monolit

A. Utrobicic, M. Kovacic, F. Erhardt, M. Jercic

This paper presents an investigation of the discharge propagation (DP) to the readout electrode that occurs with a microsecond time delay after a primary discharge that develops inside a GEM foil hole. A single hole THGEM (THick GEM) foil that enables a controlled discharge position and the induction of primary discharge with an over-voltage in the THGEM foi

Younggun Cho, Giseop Kim, Ayoung Kim

Recently, learning-based ego-motion estimation approaches have drawn strong interest from studies mostly focusing on visual perception. These groundbreaking works focus on unsupervised learning for odometry estimation but mostly for visual sensors. Compared to images, a learning-based approach using Light Detection and Ranging (LiDAR) has been reported in a

Priyanka Roy, Geetanjali Panda

In this article, the concept of $μ-$ monotonic property of interval-valued function in higher dimension is introduced. Expansion of interval-valued function in higher dimension is developed using this property. Generalized Hukuhara differentiability is used to derive the theoretical results. Several examples are provided to justify the theoretical developmen

Michael Björklund, Tobias Hartnick, Thierry Stulemeijer

We extend classical density theorems of Borel and Dani--Shalom on lattices in semisimple, respectively solvable algebraic groups over local fields to approximate lattices. Our proofs are based on the observation that Zariski closures of approximate subgroups are close to algebraic subgroups. Our main tools are stationary joinings between the hull dynamical s

Yao Yao, Zixin Luo, Shiwei Li, Tianwei Shen

Deep learning has recently demonstrated its excellent performance for multi-view stereo (MVS). However, one major limitation of current learned MVS approaches is the scalability: the memory-consuming cost volume regularization makes the learned MVS hard to be applied to high-resolution scenes. In this paper, we introduce a scalable multi-view stereo framewor

Zichao Fan, Shili Wei, Zhengbo Zhu, Yan Mo

In this paper, we propose a new approach to automatically retrieve the first-order design of double-sided telecentric zoom systems with high efficiency based on Particle Swarm Optimization (PSO) algorithms. We transform the design problem to realize a zoom lens system with fixed positions of both the front focal point and the rear focal point during zooming.

Kathrin Bringmann, Jonas Kaszian, Antun Milas, Sander Zwegers

In this paper, we study a family of rank two false theta series associated to the root lattice of type $A_2$. We show that these functions appear as Fourier coefficients of a meromorphic Jacobi form of negative definite matrix index. Hypergeometric $q$-series identities are also obtained.

R. Lazauskas, E. Hiyama, J. Carbonell

By solving the 5-body Faddeev-Yakubovsky equations in configuration space with realistic nuclear Hamiltonians we have studied the resonant states of $^5$H isotope. Two different methods, allowing to bypass the exponentially diverging boundary conditions, have been employed providing consistent results. The existence of $^5$H broad J$^π$=1/2$^+$,3/2$^+$,5/2$^

Marcos Cramer, Mathieu Guillaume

In abstract argumentation, multiple argumentation semantics have been proposed that allow to select sets of jointly acceptable arguments from a given argumentation framework, i.e. based only on the attack relation between arguments. The existence of multiple argumentation semantics raises the question which of these semantics predicts best how humans evaluat

Jyotsna Bahl, Pankaj Priyadarshi, Bhaskaran Muralidharan

We propose energy bandpass filtering employed using the idea of anti-reflection heterostructures as a means to reduce the energy requirements of a superlattice phase change memory based on GeTe and Sb$_{2}$Te$_{3}$ heterostructures. Different configurations of GeTe/Sb$_{2}$Te$_{3}$ superlattices are studied using the non-equilibrium Green&#39;s function appr

Daniel de Florian, Gonzalo Agustin Lucero, Rodolfo Sassot, Marco Stratmann

We implement a Monte Carlo sampling strategy to extract helicity parton densities and their uncertainties from a reference set of longitudinally polarized scattering data, chosen to be that used in the DSSV14 global analysis. Instead of adopting the simplest possible functional forms for the helicity parton distributions and imposing certain restrictions on

Alejandro Sanz, Jeppe C. Dyre, Kristine Niss

We report an experimental study documenting the challenge of employing dielectric dilatometry for the study of pressure densification in glass-forming materials. An influence of the dielectric cell geometry on the resulting capacitance of 5-poly-phenyl-ether upon vitrification under different thermobaric pathways is documented. The capacitive response is stu

Shinya Tomizawa, Takashi Mishima

Using the inverse scattering method to solve the five-dimensional vacuum Einstein equations, we construct an asymptotically flat four-soliton solution as a stationary and bi-axisymmetric solution. We impose certain boundary conditions on this solution so that it includes a rotating black hole whose horizon-cross section is topologically a lens space of L(2,1

Noémie Gaudio, Abraham J. Escobar-Gutiérrez, Pierre Casadebaig, Jochem B. Evers

Growing mixtures of annual arable crop species or genotypes is a promising way to improve crop production without increasing agricultural inputs. To design optimal crop mixtures, choices of species, genotypes, sowing proportion, plant arrangement, and sowing date need to be made but field experiments alone are not sufficient to explore such a large range of