November 2019 arXiv papers — page 50

Laura Bishop, Carlos Cancino-Chacón, Werner Goebl

Skilled ensemble musicians coordinate with high precision, even when improvising or interpreting loosely-defined notation. Successful coordination is supported primarily through shared attention to the musical output; however, musicians also interact visually, particularly when the musical timing is irregular. This study investigated the performance conditio

Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang

This paper proposes a set of criteria to evaluate the objectiveness of explanation methods of neural networks, which is crucial for the development of explainable AI, but it also presents significant challenges. The core challenge is that people usually cannot obtain ground-truth explanations of the neural network. To this end, we design four metrics to eval

Michael P. B. Gallaugher, Paul D. McNicholas

Over the years, data have become increasingly higher dimensional, which has prompted an increased need for dimension reduction techniques. This is perhaps especially true for clustering (unsupervised classification) as well as semi-supervised and supervised classification. Many methods have been proposed in the literature for two-way (multivariate) data and

Soma Yokoi, Issei Sato

The current interpretation of stochastic gradient descent (SGD) as a stochastic process lacks generality in that its numerical scheme restricts continuous-time dynamics as well as the loss function and the distribution of gradient noise. We introduce a simplified scheme with milder conditions that flexibly interprets SGD as a discrete-time approximation of a

Ganesh Samarth C. A., Neelanjan Bhowmik, Toby P. Breckon

In this work we explore different Convolutional Neural Network (CNN) architectures and their variants for non-temporal binary fire detection and localization in video or still imagery. We consider the performance of experimentally defined, reduced complexity deep CNN architectures for this task and evaluate the effects of different optimization and normaliza

Geoffroy Dubourg-Felonneau, Yasmeen Kussad, Dominic Kirkham, John W Cassidy

Analysis of somatic mutation profiles from cancer patients is essential in the development of cancer research. However, the low frequency of most mutations and the varying rates of mutations across patients makes the data extremely challenging to statistically analyze as well as difficult to use in classification problems, for clustering, visualization or fo

Abdulkadir Çelikkanat, Fragkiskos D. Malliaros

Representing networks in a low dimensional latent space is a crucial task with many interesting applications in graph learning problems, such as link prediction and node classification. A widely applied network representation learning paradigm is based on the combination of random walks for sampling context nodes and the traditional \textit{Skip-Gram} model

Gilles Kratzer, Fraser Iain Lewis, Arianna Comin, Marta Pittavino

The R package abn is designed to fit additive Bayesian models to observational datasets. It contains routines to score Bayesian networks based on Bayesian or information theoretic formulations of generalized linear models. It is equipped with exact search and greedy search algorithms to select the best network. It supports a possible blend of continuous, dis

Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz

As AI systems become prevalent in high stakes domains such as surveillance and healthcare, researchers now examine how to design and implement them in a safe manner. However, the potential harms caused by systems to stakeholders in complex social contexts and how to address these remains unclear. In this paper, we explain the inherent normative uncertainty i

Arttu Nieminen, Andrea marini, Marco Ornigotti

We investigate the reflection of a Gaussian beam impinging upon the surface of an epsilon-near-zero (ENZ) medium. In particular, we discuss the occurrence of Goos-Hänchen and Imbert-Fedorov shifts. Our calculations reveal that spatial shifts are significantly enhanced owing to the ENZ nature of the medium, and that their value and angular position can be tun

Takumi Bessho, Kohei Kawabata, Masatoshi Sato

We provide classification of gapless phases in non-Hermitian systems according to two types of complex-energy gaps: point gap and line gap. We show that exceptional points, at which not only eigenenergies but also eigenstates coalesce, are characterized by gap closing of point gaps with nontrivial topological charges. Moreover, we find that bulk Fermi arcs a

Carlos Pinto, Michael Gill, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Elizabeth A. Heron

Genome-wide association studies (GWAS) provide a means of examining the common genetic variation underlying a range of traits and disorders. In addition, it is hoped that GWAS may provide a means of differentiating affected from unaffected individuals. This has potential applications in the area of risk prediction. Current attempts to address this problem fo

Yinglong Feng, Shuncheng Wu, Okan Köpüklü, Xueyang Kang

This paper studies unsupervised monocular depth prediction problem. Most of existing unsupervised depth prediction algorithms are developed for outdoor scenarios, while the depth prediction work in the indoor environment is still very scarce to our knowledge. Therefore, this work focuses on narrowing the gap by firstly evaluating existing approaches in the i

Eleonora Bianchi, Cecilia Ceccarelli, Claudio Codella, Juan Enrique-Romero

The latest developments in astrochemistry have shown how some molecular species can be used as a tool to study the early stages of the solar-type star formation process. Among them, the more relevant species are the interstellar complex organic molecules (iCOMs) and the deuterated molecules. Their analysis give us information on the present and past history

María Gómez-Rocha, Enrique Ruiz Arriola

The scattering phase-shifts are invariant under unitary transformations of the Hamiltonian. However, the numerical solution of the scattering problem that requires to discretize the continuum violates this phase-shift invariance among unitarily equivalent Hamiltonians. We extend a newly found prescription for the calculation of phase shifts which relies only

G. Hernandez-Duenas, S. Pérez-Esteva, A. Uribe, C. Villegas-Blas

We consider the asymptotic behavior of the spectrum of the Landau Hamiltonian plus a rapidly decaying potential, as the magnetic field strength, $B$, tends to infinity. After a suitable rescaling, this becomes a semiclassical problem where the role of Planck's constant is played by $1/B$. The spectrum of the operator forms eigenvalue clusters. We obtain

Alessandro Chieffi, Marco Limongi

We present a fine grid of solar metallicity models of massive stars (320 in the range 12$\leq$M(\msun)$\leq$27.95), extending from the Main Sequence up to the onset of the collapse, in order to quantitatively determine how their compactness $ξ_{2.5}$ (as defined by O'Connor $\&$ Ott, 2011, ApJ 730, 70) scales with the Carbon Oxygen core mass at the begin

Alexis Askitopoulos, Lucy Pickup, Sergey Alyatkin, Anton Zasedatelev

Coherent bosonic ensembles offer the promise of harnessing quantum effects in photonic and quantum circuits. In the dynamic equilibrium regime, the application of polariton condensates is hindered by exciton-polariton scattering induced de-coherence in the presence of a dark exciton reservoir. By spatially separating the condensate from the reservoir, we dri

J. Braine, A. Hughes, E. Rosolowsky, P. Gratier

The grand-design spiral galaxy M~51 was observed at 40pc resolution in CO(1--0) by the PAWS project. A large number of molecular clouds were identified and we search for velocity gradients in two high signal-to-noise subsamples, containing 682 and 376 clouds. The velocity gradients are found to be systematically prograde oriented, as was previously found for

Yew Ken Chia, Sam Witteveen, Martin Andrews

The TextGraphs-13 Shared Task on Explanation Regeneration asked participants to develop methods to reconstruct gold explanations for elementary science questions. Red Dragon AI's entries used the language of the questions and explanation text directly, rather than a constructing a separate graph-like representation. Our leaderboard submission placed us 3

Cheng Cheng, Wei Dai

Dictionary learning aims to find a dictionary that can sparsely represent the training data. Methods in the literature typically formulate the dictionary learning problem as an optimisation with respect to two variables, i.e., dictionary and sparse coefficients, and solve it by alternating between two stages: sparse coding and dictionary update. The key cont

Victor Arnaiz, Ángel Castro

We study the formation of singularities for the Euler-Alignment system with influence function $ψ=\frac{k_α}{|x|^α}$ in 1D. As in [20] the problem is reduced to the analysis of a nonlocal 1D equation. We show the existence of singularities in finite time for any $α$ in the range $0<α<2$ in both the real line and the periodic case.

Henry Edison, Xiaofeng Wang, Pekka Abrahamsson

Product innovation is a risky activity, but when successful, it enables large software companies accrue high profits and leapfrog the competition. Internal startups have been promoted as one way to foster product innovation in large companies, which allows them to innovate as startups do. However, internal startups in large companies are challenging endeavou

Diego Arroyuelo, Guillermo de Bernardo, Travis Gagie, Gonzalo Navarro

The $k^2$-tree is a successful compact representation of binary relations that exhibit sparseness and/or clustering properties. It can be extended to $d$ dimensions, where it is called a $k^d$-tree. The representation boils down to a long bitvector. We show that interpreting the $k^d$-tree as a dynamic trie on the Morton codes of the points, instead of as a

Lars Thorge Jensen, Leonardo Patimo

We study cells with respect to the $p$-canonical basis of the Hecke algebra of a crystallographic Coxeter system (see arXiv:1510.01556, arXiv:1901.02323) and their compatibility with standard parabolic subgroups. We show that after induction to the surrounding bigger Coxeter group the cell module of a right $p$-cell in a standard parabolic subgroup decompose

Fuzhen Zhuang, Keyu Duan, Tongjia Guo, Yongchun Zhu

The transfer learning toolkit wraps the codes of 17 transfer learning models and provides integrated interfaces, allowing users to use those models by calling a simple function. It is easy for primary researchers to use this toolkit and to choose proper models for real-world applications. The toolkit is written in Python and distributed under MIT open source

Yona Falinie A. Gaus, Neelanjan Bhowmik, Samet Akcay, Toby P. Breckon

X-ray imagery security screening is essential to maintaining transport security against a varying profile of threat or prohibited items. Particular interest lies in the automatic detection and classification of weapons such as firearms and knives within complex and cluttered X-ray security imagery. Here, we address this problem by exploring various end-to-en

S. S. Kubakaddi

Transport of electrons at high electric fields is investigated in an intrinsic three-dimensional Dirac semimetal cadmium arsenide, considering the scattering of electrons from acoustic and optical phonons. Screening and hot phonon effect are taken in to account. Expressions for the hot electron mobility $μ$ and power loss $P$ are obtained as a function of el

Gregorio Quintana-Ortí, Fernando Hernando, Francisco D. Igual

The minimum distance of a linear code is a key concept in information theory. Therefore, the time required by its computation is very important to many problems in this area. In this paper, we introduce a family of implementations of the Brouwer-Zimmermann algorithm for distributed-memory architectures for computing the minimum distance of a random linear co

H. Abdalla R. Adam F. Aharonian F. Ait Benkhali E. O. Anguener M. Arakawa, C. Arcaro, C. Armand, H. Ashkar

Gamma-ray bursts (GRBs) are brief flashes of gamma rays, considered to be the most energetic explosive phenomena in the Universe. The emission from GRBs comprises a short (typically tens of seconds) and bright prompt emission, followed by a much longer afterglow phase. During the afterglow phase, the shocked outflow -- produced by the interaction between the

Etienne Savonnet, Cédric Le Coz, Etienne Grau, Stéphane Grelier

New bio-based diamines were successfully synthesized from vanillin and fully characterized. These amines, methylated divanillylamine (MDVA) and 3,4-dimethoxydianiline (DMAN), were then used as curing agent with epoxy monomers. Epoxy thermosets obtained from these new bio-based amines exhibited promising thermomechanical properties in terms of glass transitio

Ben Hermans, Roel Leus, Jannik Matuschke

Suppose a target is hidden in one of the vertices of an edge-weighted graph according to a known probability distribution. The expanding search problem asks for a search sequence of the vertices so as to minimize the expected time for finding the target, where the time for reaching the next vertex is determined by its distance to the region that was already

Igor Denisenko

The $J/ψ$ production is a powerful probe of hadron structure, which is complementary to other parts of the SPD physics program. In this work, the current experimental status and modern theoretical approaches to $J/ψ$ and charmonia production are reviewed. In this context, the SPD performance and feasibility of key measurements are discussed.

Yuan-Hang Su, Wan-Tong Li, Yuan Lou, Fei-Ying Yang

This paper is mainly concerned with the generalised principal eigenvalue for time-periodic nonlocal dispersal operators. We first establish the equivalence between two different characterisations of the generalised principal eigenvalue. We further investigate the dependence of the generalised principal eigenvalue on the frequency, the dispersal rate and the

Lander Guerrero Sánchez

This thesis aims to serve as an introduction to the theory of quasitilings for amenable groups. In order to showcase the power of this theory, we focus on the study of the Sofic Lück Approximation Conjecture, which can be proven for amenable groups by making use of quasitilings. The first four chapters of the thesis are an exposition of the aforementioned to

Zikri Bayraktar

This paper presents the application of a newly developed nature-inspired metaheuristic optimization method, namely the Adaptive Wind Driven Optimization (AWDO), to the training of feedforward artificial neural networks (NN) and presents a discussion into the future research of AWDO implementation in Deep Learning (DL). Application example of digit classifica

Claudio Gallicchio, Alessio Micheli

We address the efficiency issue for the construction of a deep graph neural network (GNN). The approach exploits the idea of representing each input graph as a fixed point of a dynamical system (implemented through a recurrent neural network), and leverages a deep architectural organization of the recurrent units. Efficiency is gained by many aspects, includ

Mehrija Hasicic, Harun Siljak

Solar exposure of streets and parking spaces in dense urban areas varies significantly due to the infrastructure: buildings, parks, tunnels, multistorey car parks. This variability leaves space for both real-time and offline route and parking optimization for solar-powered vehicles. In this chapter we present Solar Car Optimized Route Estimation (SCORE), our

Anthony Przybylski, Kathrin Klamroth, Renaud Lacour

We present a simple and at the same time fficient algorithm to compute all nondominated extreme points in the outcome set of multi-objective mixed integer linear programmes in any dimension. The method generalizes the well-known dichotomic scheme to compute the set of nondominated extreme points in the outcome set of a bi-objective programme based on the ite

Zequn Sun, Chengming Wang, Wei Hu, Muhao Chen

Graph neural networks (GNNs) have emerged as a powerful paradigm for embedding-based entity alignment due to their capability of identifying isomorphic subgraphs. However, in real knowledge graphs (KGs), the counterpart entities usually have non-isomorphic neighborhood structures, which easily causes GNNs to yield different representations for them. To tackl

M. L. Shcherbatenko, M. S. Elezov, D. V. Sych, G. N. Goltsman

We experimentally demonstrate a quantum receiver based on Kennedy scheme for discrimination between two phase-modulated weak coherent states. The receiver is assembled entirely from the standard fiber-optic elements and operates at the conventional telecom wavelength 1.55 microns. The local oscillator and the signal are transmitted through different optical

Pietro Falco, Matteo Saveriano, Eka Gibran Hasany, Nicholas H. Kirk

In this paper, we present a descriptor for human whole-body actions based on motion coordination. We exploit the principle, well known in neuromechanics, that humans move their joints in a coordinated fashion. Our coordination-based descriptor (CODE) is computed by two main steps. The first step is to identify the most informative joints which characterize t

Pietro Falco, Abdallah Attawia, Matteo Saveriano, Dongheui Lee

In this letter, we present an approach for learning in-hand manipulation skills with a low-cost, underactuated prosthetic hand in the presence of irreversible events. Our approach combines reinforcement learning based on visual perception with low-level reactive control based on tactile perception, which aims to avoid slipping. The objective of the reinforce

Alec Wright, Vesa Välimäki

This work investigates alternate pre-emphasis filters used as part of the loss function during neural network training for nonlinear audio processing. In our previous work, the error-to-signal ratio loss function was used during network training, with a first-order highpass pre-emphasis filter applied to both the target signal and neural network output. This

Ricardo Pérez-Marco

We define the simplest log-euclidean geometry. This geometry exposes a difficulty hidden in Hilbert&#39;s list of axioms presented in his &#34;Grundlagen der Geometrie&#34;. The list of axioms appears to be incomplete if the foundations of geometry are to be independent of set theory, as Hilbert intended. In that case we need to add a missing axiom. Log-eucl

Arieh Iserles, Marcus Webb

In this paper we explore orthogonal systems in $\mathrm{L}_2(\mathbb{R})$ which give rise to a skew-Hermitian, tridiagonal differentiation matrix. Surprisingly, allowing the differentiation matrix to be complex leads to a particular family of rational orthogonal functions with favourable properties: they form an orthonormal basis for $\mathrm{L}_2(\mathbb{R}

Sylwia Dworakowska, Cédric Le Coz, Guillaume Chollet, Etienne Grau

This paper aimed at obtaining cross-linked polymeric materials of biomass origin. For this purpose one-pot polyesterification of methyl ricinoleate and methyl 12-hydroxystearate using titanium isopropoxide as a catalyst has been performed leading to polyesters known as estolides. The obtained estolides were successfully cross-linked using dicumyl peroxide or

Marcus Bluhm, Marlene Nahrgang

We investigate the role of a finite surface tension during the time-evolution of fluctuations in the net-baryon density. The systems in this study undergo a temperature evolution across the phase transition in the critical region of the QCD phase diagram. The occuring non-equilibrium effects are discussed.

P. B. Isakova, A. G. Zhilkin, D. V. Bisikalo

The structures of plasma flows in close binary systems whose accretors have strong intrinsic magnetic fields are studied. A close binary system with the parameters of a typical polar is considered. The results of three dimensional numerical simulations of the material flow from the donor into the accretor Roche lobe are presented. Special attention is given

Lea Bonnot, Christophe Len, Etienne Grau, Henri Cramail

In the context of the development of bio-refineries, glycerol and its derivatives are co-products of the oleochemistry for which new valorization routes must be found. In this study, the polymerizability of divinylglycol (DVG), a symmetrical C-6 glycerol derivative which bears a vicinal diol and two vinyl functions was studied. The reactivity of the hydroxyl

Mingchao Liu, Peng Jin, Zhiping Xu, Dorian A. H. Hanaor

Self-limiting oxidation of nanowires has been previously described as a reaction- or diffusion-controlled process. In this letter, the concept of finite reactive region is introduced into a diffusion-controlled model, based upon which a two-dimensional cylindrical kinetics model is developed for the oxidation of silicon nanowires and is extended for tungsten

Yun Yen, Guang-Yu Guo

The ZrSiS-type compounds are Dirac semimetals and have been attracting considerable interest in recent years due to their topological electronic properties and possible applications. In particular, gapped Dirac nodes can possess large spin Berry curvatures and thus give rise to large spin Hall effect (SHE) and spin Nernst effect (SNE), which may be used to g

Roberta Campesato, Carsten Baur, Mario Carta, Mariacristina Casale

Triple junction (InGaP/GaAs/Ge) and single junction (SJ) solar cells were irradiated with electrons, protons and neutrons. The degradation of remaining factors was analyzed as function of the induced Displacement Damage Dose (DDD) calculated by means of the SR-NIEL (Screened Relativistic Non Ionizing\ Energy Loss) approach. In particular, the aim of this wor

Jian Xie

In this paper, we present Shift Convolution Network (ShiftConvNet) to provide matching capability between two feature maps for stereo estimation. The proposed method can speedily produce a highly accurate disparity map from stereo images. A module called shift convolution layer is proposed to replace the traditional correlation layer to perform patch compari

Ting-En Lin, Hua Xu, Hanlei Zhang

Identifying new user intents is an essential task in the dialogue system. However, it is hard to get satisfying clustering results since the definition of intents is strongly guided by prior knowledge. Existing methods incorporate prior knowledge by intensive feature engineering, which not only leads to overfitting but also makes it sensitive to the number o

Csilla Bujtás, Vesna Iršič, Sandi Klavžar

The Z-domination game is a variant of the domination game in which each newly selected vertex $u$ in the game must have a not yet dominated neighbor, but after the move all vertices from the closed neighborhood of $u$ are declared to be dominated. The Z-domination game is the fastest among the five natural domination games. The corresponding game Z-dominatio

Parnia Bahar, Albert Zeyer, Ralf Schlüter, Hermann Ney

Attention-based sequence-to-sequence models have shown promising results in automatic speech recognition. Using these architectures, one-dimensional input and output sequences are related by an attention approach, thereby replacing more explicit alignment processes, like in classical HMM-based modeling. In contrast, here we apply a novel two-dimensional long

Deepak Kumar, Ashwin A. Tulapurkar, C. V. Tomy

We report a comprehensive investigation of La0.2Pr0.4Ca0.4MnO3 to clarify the micrometre scale phase separation phenomenon in the mixed valent manganite (La,Pr,Ca)MnO3. The compound shows multiple magnetic transitions, in which the charge-ordered state is converted into a ferromagnetic state in steps with the application of a magnetic field. The ac susceptib

Parnia Bahar, Albert Zeyer, Ralf Schlüter, Hermann Ney

This work investigates a simple data augmentation technique, SpecAugment, for end-to-end speech translation. SpecAugment is a low-cost implementation method applied directly to the audio input features and it consists of masking blocks of frequency channels, and/or time steps. We apply SpecAugment on end-to-end speech translation tasks and achieve up to +2.2

Parnia Bahar, Tobias Bieschke, Hermann Ney

Recent advances in deep learning show that end-to-end speech to text translation model is a promising approach to direct the speech translation field. In this work, we provide an overview of different end-to-end architectures, as well as the usage of an auxiliary connectionist temporal classification (CTC) loss for better convergence. We also investigate on

Christian Huber, Santiago Cano, Iulian Teliban, Stephan Schuschnigg

In this publication we describe the extrusion process and the properties of polymer-bonded anisotropic SrFe$_\text{12}$O$_\text{19}$ filaments for fused filament fabrication (FFF). Highly filled polyamide 12 filaments with a filling fraction from 40 vol.% to 55 vol.% are mixed and extruded into filaments with a diameter of 1.75 mm. Such filaments are process

Hatem A. Alharbi, Taisir E. H. Elgorashi, Jaafar M. H. Elmirghani

Network neutrality (net neutrality) is the principle of treating equally all Internet traffic regardless of its source, destination, content, application or other related distinguishing metrics. Under net neutrality, ISPs are compelled to charge all content providers (CPs) the same per Gbps rate despite the growing profit achieved by CPs. In this paper, we s

Jens Chluba, Andrea Ravenni, Boris Bolliet

Electron-ion Bremsstrahlung (free-free) emission and absorption occur in many astrophysical plasmas for a wide range of physical conditions. This classical problem has been studied multiple times, and many analytical and numerical approximations exist. However, accurate calculations of the transition from the non-relativistic to the relativistic regime remai

Asa F. L. Bluck, Roberto Maiolino, Sebastian Sanchez, Sara L. Ellison

We present an analysis of star formation and quenching in the SDSS-IV MaNGA-DR15, utilising over 5 million spaxels from $\sim$3500 local galaxies. We estimate star formation rate surface densities ($Σ_{\rm SFR}$) via dust corrected $Hα$ flux where possible, and via an empirical relationship between specific star formation rate (sSFR) and the strength of the

Redouane Lguensat, Julien Le Sommer, Sammy Metref, Emmanuel Cosme

We introduce a new strategy designed to help physicists discover hidden laws governing dynamical systems. We propose to use machine learning automatic differentiation libraries to develop hybrid numerical models that combine components based on prior physical knowledge with components based on neural networks. In these architectures, named Deep Neural Numeri

Agnieszka A. Tomaka, Leszek Luchowski, Dariusz Pojda, Michał Tarnawski

The purpose of this chapter is to discuss methods of acquisition, visualization and analysis of the dynamics of a complex biomedical system, illustrated by the human stomatognathic system. The stomatognathic system consists of the teeth and the skull bones with the maxilla and the mandible. Its dynamics can be described by the change of mutual position of th

Xuekai Ma, Yaroslav Y. Kartashov, Tingge Gao, Stefan Schumacher

Parity-time (PT) symmetry gives rise to unusual phenomena in many physical systems, presently attracting a lot of attention. One essential and non-trivial task is the fabrication and design of the PT-symmetric lattices in different systems. Here we introduce a method to realize such a lattice in an exciton-polariton condensate in a planar semiconductor micro

D. Rodgers-Lee, A. M. Taylor, T. P. Downes, T. P. Ray

We assess the ionising effect of low energy protostellar cosmic rays in protoplanetary disks around a young solar mass star for a wide range of disk parameters. We assume a source of low energy cosmic rays located close to the young star which travel diffusively through the protoplanetary disk. We use observationally inferred values from nearby star-forming

Hiroharu Kato, Tatsuya Harada

We present a method to learn single-view reconstruction of the 3D shape, pose, and texture of objects from categorized natural images in a self-supervised manner. Since this is a severely ill-posed problem, carefully designing a training method and introducing constraints are essential. To avoid the difficulty of training all elements at the same time, we pr

Yakov Babichenko, Oren Dean, Moshe Tennenholtz

We investigate the possibility of an incentive-compatible (IC, a.k.a. strategy-proof) mechanism for the classification of agents in a network according to their reviews of each other. In the $ α$-classification problem we are interested in selecting the top $ α$ fraction of users. We give upper bounds (impossibilities) and lower bounds (mechanisms) on the wo

Laura Midgley, Luc J. Bourhis, Oleg Dolomanov, Norbert Peyerimhoff

We have implemented a procedure that allows the use of non-spherical atomic form factors in a standard crystallographic X-Ray refinement. We outline the procedure for their use, alongside a mathematical justification of their viability.

Álvaro de la Cruz-Dombriz, Francisco José Maldonado Torralba, Anupam Mazumdar

In this manuscript we will present the theoretical framework of the recently proposed infinite derivative theory of gravity with a non-symmetric connection. We will explicitly derive the field equations at the linear level and obtain new solutions with a non-trivial form of the torsion tensor in the presence of a fermionic source, and show that these solutio

Jonathan Hoseana, Franco Vivaldi

The transit time of mean-median orbits ---the time it takes for an orbit to become stationary--- has been conjectured to be finite but unbounded over the rationals. Through a study of some near-regular structures in these orbits, we construct two non-trivial sequences of initial sets of increasing size for which the transit time grows linearly and quadratica

L. S. Dreissen, C. Roth, E. L. Gründeman, J. J. Krauth

High-harmonic generation (HHG) is widely used for up-conversion of amplified (near) infrared ultrafast laser pulses to short wavelengths. We demonstrate that Ramsey-comb spectroscopy, based on two such pulses derived from a frequency-comb laser, enables us to observe phase effects in this process with a few mrad precision. As a result, we could perform the m

Sanket Shah, Meghna Lowalekar, Pradeep Varakantham

On-demand ride-pooling (e.g., UberPool) has recently become popular because of its ability to lower costs for passengers while simultaneously increasing revenue for drivers and aggregation companies. Unlike in Taxi on Demand (ToD) services -- where a vehicle is only assigned one passenger at a time -- in on-demand ride-pooling, each (possibly partially fille

K. Z. Najiya, Munnu Sonkar, C. S. Sastry

Prior support constrained compressed sensing, achieved via the weighted norm minimization, has of late become popular due to its potential for applications. For the weighted norm minimization problem, $$ min \|x\|_{p,w} \text{ subject to } y=Ax, \; p=0,1, \text{ and } w \in [0,1], $$ uniqueness results are known when $w=0,1$. Here, $\|x\|_{p,w}=w\|x_T\|_p+\|

Mateen Ashraf, Zijian Wang, Luc Vandendorpe

In this paper, we propose an online power allocation scheme to maximize the time averaged sum rate for multiple downlink receivers with energy harvesting transmitter. The transmitter employs non-orthogonal multiple access (NOMA) and/or orthogonal multiple access (OMA) to transmit data to multiple users. Additionally, we consider the scenario where each indiv

Hélène de Maleprade, Frédéric Moisy, Takuji Ishikawa, Raymond E. Goldstein

Green algae of the $Volvocine$ lineage, spanning from unicellular $Chlamydomonas$ to vastly larger $Volvox$, are models for the study of the evolution of multicellularity, flagellar dynamics, and developmental processes. Phototactic steering in these organisms occurs without a central nervous system, driven solely by the response of individual cells. All suc

Najah-Imane Bentabet, Rémi Juge, Sira Ferradans

The generation of precise and detailed Table-Of-Contents (TOC) from a document is a problem of major importance for document understanding and information extraction. Despite its importance, it is still a challenging task, especially for non-standardized documents with rich layout information such as commercial documents. In this paper, we present a new neur

Shivali Kaundal, Aakriti Bagai, Gulsheen Ahuja, Manmohan Gupta

We have carried out an extensive analysis of all possible minimal texture quark mass matrices implying 169 texture 6 zero combinations. One finds that all these combinations are ruled out, a good number of these analytically, the other possibilities are excluded by the present quark mixing data. Interestingly, even if in future, there are changes in the rang

Arpita Patra, Pratik Sarkar, Ajith Suresh

Oblivious Transfer (OT) is one of the most fundamental cryptographic primitives with wide-spread application in general secure multi-party computation (MPC) as well as in a number of tailored and special-purpose problems of interest such as private set intersection (PSI), private information retrieval (PIR), contract signing to name a few. Often the instanti

Ruiqi Liu, Ben Boukai, Zuofeng Shang

A new statistical procedure, based on a modified spline basis, is proposed to identify the linear components in the panel data model with fixed effects. Under some mild assumptions, the proposed procedure is shown to consistently estimate the underlying regression function, correctly select the linear components, and effectively conduct the statistical infer

Hessel Haagsma, Malvina Nissim, Johan Bos

Idiomatic expressions like `out of the woods&#39; and `up the ante&#39; present a range of difficulties for natural language processing applications. We present work on the annotation and extraction of what we term potentially idiomatic expressions (PIEs), a subclass of multiword expressions covering both literal and non-literal uses of idiomatic expressions

Ofer Givoli, Roi Reichart

We consider a zero-shot semantic parsing task: parsing instructions into compositional logical forms, in domains that were not seen during training. We present a new dataset with 1,390 examples from 7 application domains (e.g. a calendar or a file manager), each example consisting of a triplet: (a) the application&#39;s initial state, (b) an instruction, to

Akshay Dharmavaram, Matthew Riemer, Shalabh Bhatnagar

Option-critic learning is a general-purpose reinforcement learning (RL) framework that aims to address the issue of long term credit assignment by leveraging temporal abstractions. However, when dealing with extended timescales, discounting future rewards can lead to incorrect credit assignments. In this work, we address this issue by extending the hierarchi

Raúl Oset Sinha, Kentaro Saji

For singular corank 1 surfaces in $\mathbb R^3$ we introduce a distinguished normal vector called the axial vector. Using this vector and the curvature parabola we define a new type of curvature called the axial curvature, which generalizes the singular curvature for frontal type singularities. We then study contact properties of the surface with respect to

J. M. Almira, A. Romero

As an application of the Bochner formula, we prove that if a $2$-dimensional Riemannian manifold admits a non-trivial smooth tangent vector field $X$ then its Gauss curvature is the divergence of a tangent vector field, constructed from $X$, defined on the open subset out the zeroes of $X$. Thanks to the Whitney embedding theorem and a standard approximation

Daniel Chao Zhou, Zhongming Jin, Tong Zhang

As an adaptive, interpretable, robust, and accurate meta-algorithm for arbitrary differentiable loss functions, gradient tree boosting is one of the most popular machine learning techniques, though the computational expensiveness severely limits its usage. Stochastic gradient boosting could be adopted to accelerates gradient boosting by uniformly sampling tr

Mian Wei, Anup V. Sanchela, Bin Feng, Yuichi Ikuhara

La-doped SrSnO3 (LSSO) is known as one of deep-ultraviolet (DUV)-transparent conducting oxides with an energy bandgap of ~4.6 eV. Since LSSO can be grown heteroepitaxially on more wide bandgap substrates such as MgO (Eg ~7.8 eV), LSSO is considered to be a good candidate as a DUV-transparent electrode. However, the electrical conductivity of LSSO films are b

Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux, Roberto Interdonato

European satellite missions Sentinel-1 (S1) and Sentinel-2 (S2) provide at highspatial resolution and high revisit time, respectively, radar and optical imagesthat support a wide range of Earth surface monitoring tasks such as LandUse/Land Cover mapping. A long-standing challenge in the remote sensingcommunity is about how to efficiently exploit multiple sou

Takehiro Kawasaki, Nathanael Barrot, Seiji Takanashi, Taiki Todo

Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naive ones. In this paper, w

A. Tiene, J. Levinsen, M. M. Parish, A. H. MacDonald

We investigate the phases of two-dimensional electron-hole systems strongly coupled to a microcavity photon field in the limit of extreme charge imbalance. Using variational wave functions, we examine the competition between different electron-hole paired states for the specific cases of semiconducting III-V single quantum wells, electron-hole bilayers, and

Shifeng Ding, Kevin X. Pan, Sanjay K. Bose, Qiong Zhang

In communication networks, network virtualization can usually provide better capacity utilization and quality of service (QoS) than what can be achieved otherwise. However, conventional resource allocation for virtualized networks would still follow a fixed pattern based on the predicted capacity needs of the users, even though, in reality, the actual traffi

Masataka Gohda, Naonori Kakimura

This paper studies spectral approximation for a positive semidefinite matrix in the online setting. It is known in [Cohen et al. APPROX 2016] that we can construct a spectral approximation of a given $n \times d$ matrix in the online setting if an additive error is allowed. In this paper, we propose an online algorithm that avoids an additive error with the

Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault

Large-scale screening for potential threats with limited resources and capacity for screening is a problem of interest at airports, seaports, and other ports of entry. Adversaries can observe screening procedures and arrive at a time when there will be gaps in screening due to limited resource capacities. To capture this game between ports and adversaries, t

Johanna Kerler-Back, Tatjana Stykel

We consider linear magneto-quasistatic field equations which arise in simulation of low-frequency electromagnetic devices coupled to electrical circuits. A finite element discretization of such equations on 3D domains leads to a singular system of differential-algebraic equations. First, we study the structural properties of such a system and present a new r

Chi Thang Duong, Thanh Dat Hoang, Ha The Hien Dang, Quoc Viet Hung Nguyen

Graph neural network (GNN) is a deep model for graph representation learning. One advantage of graph neural network is its ability to incorporate node features into the learning process. However, this prevents graph neural network from being applied into featureless graphs. In this paper, we first analyze the effects of node features on the performance of gr

Ehud Reiter

Good quality explanations of artificial intelligence (XAI) reasoning must be written (and evaluated) for an explanatory purpose, targeted towards their readers, have a good narrative and causal structure, and highlight where uncertainty and data quality affect the AI output. I discuss these challenges from a Natural Language Generation (NLG) perspective, and

Neema Davis, Gaurav Raina, Krishna Jagannathan

We develop an end-to-end deep learning-based anomaly detection model for temporal data in transportation networks. The proposed EVT-LSTM model is derived from the popular LSTM (Long Short-Term Memory) network and adopts an objective function that is based on fundamental results from EVT (Extreme Value Theory). We compare the EVT-LSTM model with some establis

Andrea Gabrio

Statistical modelling of sports data has become more and more popular in the recent years and different types of models have been proposed to achieve a variety of objectives: from identifying the key characteristics which lead a team to win or lose to predicting the outcome of a game or the team rankings in national leagues. Although not as popular as footba