July 2019 arXiv papers — page 45

Ankita Shukla, Sarthak Bhagat, Shagun Uppal, Saket Anand

Learning representations that can disentangle explanatory attributes underlying the data improves interpretabilty as well as provides control on data generation. Various learning frameworks such as VAEs, GANs and auto-encoders have been used in the literature to learn such representations. Most often, the latent space is constrained to a partitioned represen

Jan Troßand Carlos A. Trallero-Herrero

We present an experimental technique using orbital angular momentum (OAM) in a fundamental laser field to drive High Harmonic Generation (HHG). The mixing of beams with different OAM allows to generate two laser foci tightly spaced to study the phase and amplitude of HHG produced in diatomic nitrogen. Nitrogen is used as a well studied system to show the qua

João Alcântara, Samy Sá, Juan Acosta-Guadarrama

Abstract Dialectical Frameworks (ADFs) are argumentation frameworks where each node is associated with an acceptance condition. This allows us to model different types of dependencies as supports and attacks. Previous studies provided a translation from Normal Logic Programs (NLPs) to ADFs and proved the stable models semantics for a normal logic program has

Damek Davis, Dmitriy Drusvyatskiy, Vasileios Charisopoulos

Stochastic (sub)gradient methods require step size schedule tuning to perform well in practice. Classical tuning strategies decay the step size polynomially and lead to optimal sublinear rates on (strongly) convex problems. An alternative schedule, popular in nonconvex optimization, is called \emph{geometric step decay} and proceeds by halving the step size

Michael Ridley, Michael Galperin, Emanuel Gull, Guy Cohen

We use the inchworm Quantum Monte Carlo method to investigate the full counting statistics of particle and energy currents in a strongly correlated quantum dot. Our method is used to extract the heat fluctuations and entropy production of a quantum thermoelectric device, as well as cumulants of the particle and energy currents. The energy--particle current c

Osama Zwaid Alsulami, Amal A. Alahmadi, Sarah O. M. Saeed, Sanaa Hamid Mohamed

Optical wireless communication (OWC) is a promising technology that can provide high data rates while supporting multiple users. The Optical Wireless (OW) physical layer has been researched extensively, however less work was devoted to multiple access and how the OW front end is connected to the network. In this paper, an OWC system which employs a wavelengt

Adrian Albert, Jasleen Kaur, Emanuele Strano, Marta Gonzalez

Accurately forecasting urban development and its environmental and climate impacts critically depends on realistic models of the spatial structure of the built environment, and of its dependence on key factors such as population and economic development. Scenario simulation and sensitivity analysis, i.e., predicting how changes in underlying factors at a giv

Francesco Lovascio, Sijme-Jan Paardekooper

Motivated by the stability of dust laden vortices, in this paper we study the terminal velocity approximation equations for a gas coupled to a pressureless dust fluid and present a numerical solver for the equations embedded in the FARGO3D hydrodynamics code. We show that for protoplanetary discs it is possible to use the baricenter velocity in the viscous s

Ozan Ozdenizci, Barry Oken, Tab Memmott, Melanie Fried-Oken

Across- and within-recording variabilities in electroencephalographic (EEG) activity is a major limitation in EEG-based brain-computer interfaces (BCIs). Specifically, gradual changes in fatigue and vigilance levels during long EEG recording durations and BCI system usage bring along significant fluctuations in BCI performances even when these systems are ca

Zhenwei Dai, Reinhard Heckel

Normalization layers are widely used in deep neural networks to stabilize training. In this paper, we consider the training of convolutional neural networks with gradient descent on a single training example. This optimization problem arises in recent approaches for solving inverse problems such as the deep image prior or the deep decoder. We show that for t

Yikuan Li, Shishir Rao, Jose Roberto Ayala Solares, Abdelaali Hassaine

Today, despite decades of developments in medicine and the growing interest in precision healthcare, vast majority of diagnoses happen once patients begin to show noticeable signs of illness. Early indication and detection of diseases, however, can provide patients and carers with the chance of early intervention, better disease management, and efficient all

Raghunandan M. Rao, Harpeet S. Dhillon, Vuk Marojevic, Jeffrey H. Reed

In this paper, we consider an underlay radar-massive MIMO spectrum sharing scenario in which massive MIMO base stations (BSs) are allowed to operate outside a circular exclusion zone centered at the radar. Modeling the locations of the massive MIMO BSs as a homogeneous Poisson point process (PPP), we derive an analytical expression for a tight upper bound on

Niels Mündler

Association rules express implication formed relations among attributes in databases of itemsets. The apriori algorithm is presented, the basis for most association rule mining algorithms. It works by pruning away rules that need not be evaluated based on the user specified minimum support confidence. Additionally, variations of the algorithm are presented t

Hagai Netzer

The bolometric luminosity of active galactic nuclei (AGN) is difficult to determine and various approximations have been used to calibrate it against different observed properties. Here I combine theoretical calculations of optically thick, geometrically thin accretion disks, and observed X-ray properties of AGN, to provide new bolometric correction factors

Ozan Özdenizci, Timm Meyer, Felix Wichmann, Jan Peters

Stroke-induced disturbances of large-scale cortical networks are known to be associated with the extent of motor deficits. We argue that identifying brain networks representative of motor behavior in the resting brain would provide significant insights for current neurorehabilitation approaches. Particularly, we aim to investigate the global configuration of

David Damanik, Jake Fillman, Mark Helman, Jacob Kesten

We consider disordered Hamiltonians given by the Laplace operator subject to arbitrary random self-adjoint singular perturbations supported on random discrete subsets of the real line. Under minimal assumptions on the type of disorder, we prove the following dichotomy: Either every realization of the random operator has purely absolutely continuous spectrum

Vrindavan Harrison, Lena Reed, Shereen Oraby, Marilyn Walker

Neural generation methods for task-oriented dialogue typically generate from a meaning representation that is populated using a database of domain information, such as a table of data describing a restaurant. While earlier work focused solely on the semantic fidelity of outputs, recent work has started to explore methods for controlling the style of the gene

Raffaele Pascale, James Binney, Carlo Nipoti

We address an issue that arises when self-consistently flattened dynamical stellar systems are constructed by adopting a distribution function (DF) that depends on the action integrals. The velocity distribution at points on the symmetry axis is controlled by the the dependence of the DF on just one action, while at points off the symmetry axis two actions a

Xialu Liu, Ting Zhang

We consider change-point latent factor models for high-dimensional time series, where a structural break may exist in the underlying factor structure. In particular, we propose consistent estimators for factor loading spaces before and after the change point, and the problem of estimating the change-point location is also considered. Compared with existing r

Thomas Johnson

In this short note we shall demonstrate that given a smooth solution $γ$ to the linearised Einstein equations on Schwarzschild which is supported on the $l\geq 2$ spherical harmonics and expressed relative to a transverse and traceless gauge then one can construct from it a smooth solution to the sourced Maxwell equations expressed relative to a generalised

Matteo Rossi, Christian Henriquet, Jeroen Jacobs, Christian Donnerer

Resonant inelastic x-ray scattering (RIXS) is an extremely valuable tool for the study of elementary, including magnetic, excitations in matter. Latest developments of this technique mostly aimed at improving the energy resolution and performing polarization analysis of the scattered radiation, with a great impact on the interpretation and applicability of R

Jeongsik Choi, Yang-Seok Choi, Shilpa Talwar

Given that the accuracy of range-based positioning techniques generally increases with the number of available anchor nodes, it is important to secure more of these nodes. To this end, this paper studies an unsupervised learning technique to obtain the coordinates of unknown nodes that coexist with anchor nodes. As users use the location services in an area

Xu Lan, Xiatian Zhu, Shaogang Gong

Most state-of-the-art person re-identification (re-id) methods depend on supervised model learning with a large set of cross-view identity labelled training data. Even worse, such trained models are limited to only the same-domain deployment with significantly degraded cross-domain generalization capability, i.e. "domain specific". To solve this limi

Lucien Bacharach, Carsten Fritsche, Umut Orguner, Eric Chaumette

In random parameter estimation, Bayesian lower bounds (BLBs) for the mean-square error have been noticed to not be tight in a number of cases, even when the sample size, or the signal-to-noise ratio, grow to infinity. In this paper, we study alternative forms of BLBs obtained from a covariance inequality, where the inner product is based on the \textit{a pos

Johan Mazoyer, Pierre Baudoz, Ruslan Belikov, Brendan Crill

Instrumentation techniques in the field of direct imaging of exoplanets have greatly advanced over the last two decades. Two of the four NASA-commissioned large concept studies involve a high-contrast instrument for the imaging and spectral characterization of exo-Earths from space: LUVOIR and HabEx. This whitepaper describes the status of 8 optical testbeds

Daniel R. Gurevich, Patrick A. K. Reinbold, Roman O. Grigoriev

This paper investigates how models of spatiotemporal dynamics in the form of nonlinear partial differential equations can be identified directly from noisy data using a combination of sparse regression and weak formulation. Using the 4th-order Kuramoto-Sivashinsky equation for illustration, we show how this approach can be optimized in the limits of low and

Eric M. Schlegel, Thomas G. Pannuti, T. Lozinskaya, A. Moiseev

We conducted an observation of the nearby irregular galaxy IC 1613 with the Chandra X-ray Observatory using the S3 chip of the ACIS with an effective exposure time of 49.9 ksec. The observation primarily targeted the extensive bubble and star formation region in the northeast quadrant of the galaxy. The only known supernova remnant (SNR) in IC 1613, S8, is a

Amir Javadpour, Alireza Mohammadi

Background: Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective: This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel al

Fatemeh Hadaeghi

The reservoir computing paradigm is employed to classify heartbeat anomalies online based on electrocardiogram signals. Inspired by the principles of information processing in the brain, reservoir computing provides a framework to design, train, and analyze recurrent neural networks (RNNs) for processing time-dependent information. Due to its computational e

Joshua S. Walker, Jeffrey A. Fagan, Adam J. Biacchi, Valerie A. Kuehl

Over the past decade, substantial progress has been made in the chemical processing (chiral enrichment, length sorting, handedness selectivity, and filling substance) of single-wall carbon nanotubes (SWCNTs). Recently, it was shown that large, horizontally-aligned films can be created out of post-processed SWCNT solutions. Here, we use machine-vision automat

Gourav Khullar, Susanna Kohler, Tarini Konchady, Mike Foley

Support for early career astronomers who are just beginning to explore astronomy research is imperative to increase retention of diverse practitioners in the field. Since 2010, Astrobites has played an instrumental role in engaging members of the community -- particularly undergraduate and graduate students -- in research. In this white paper, the Astrobites

Kevin Sebesta, Liliya L. R. Williams, Jori Liesenborgs, Elinor Medezinski

Abell 2744, a massive Hubble Frontier Fields merging galaxy cluster with many multiple images in the core has been the subject of many lens inversions using different methods. While most existing studies compare various inversion methods, we focus on a comparison of reconstructions that use different input lensing data. Since the quantity and quality of lens

Yoshitaka Hatta, Niklas Mueller, Takahiro Ueda, Feng Yuan

Diffractive dijet production at the electron-ion collider (EIC) has been proposed to study the gluon Wigner distribution at small-$x$. We investigate the soft gluon radiation associated with the final state jets and an all order resummation formula is derived. We show that the soft gluon resummation plays an important role to describe E791 data on $π$-induce

Dominik Kiese, Finn Lasse Buessen, Ciarán Hickey, Simon Trebst

Twisting moiré heterostructures to the flatband regime allows for the formation of strongly correlated quantum states, since the dramatic reduction of the bandwidth can cause the residual electronic interactions to set the principal energy scale. An effective description for such correlated moiré heterostructures, derived in the strong-coupling limit at inte

N. Shipp, T. S. Li, A. B. Pace, D. Erkal

We cross-match high-precision astrometric data from Gaia DR2 with accurate multi-band photometry from the Dark Energy Survey (DES) DR1 to confidently measure proper motions for nine stellar streams in the DES footprint: Aliqa Uma, ATLAS, Chenab, Elqui, Indus, Jhelum, Phoenix, Tucana III, and Turranburra. We determine low-confidence proper motion measurements

Denis Erkal, Vasily A. Belokurov

We study the orbits of ultra-faint dwarf galaxies in the combined presence of the Milky Way and LMC and we find 6 dwarfs which were likely accreted with the LMC (Car 2, Car 3, Hor 1, Hyi 1, Phe 2, Ret 2), in addition to the SMC, representing strong evidence of dwarf galaxy group infall. This procedure depends on the gravitational pull of the LMC, thus allowi

S. Zarattini, J. A. L. Aguerri, A. Biviano, M. Girardi

We want to study how the velocity segregation and the radial profile of the velocity dispersion depend on the prominence of the brightest cluster galaxies (BCGs). We divide a sample of 102 clusters and groups of galaxies into four bins of magnitude gap between the two brightest cluster members. We then compute the velocity segregation in bins of absolute and

Jason D. Eastman, Joseph E. Rodriguez, Eric Agol, Keivan G. Stassun

We present the next generation public exoplanet fitting software, EXOFASTv2. It is capable of fitting an arbitrary number of planets, radial velocity data sets, astrometric data sets, and/or transits observed with any combination of wavelengths. We model the star simultaneously in the fit and provide several state-of-the-art ways to constrain its properties,

N. U. Duronea, L. Bronfman, E. Mendoza, M. Merello

Using APEX-1 and APEX-2 observations, we have detected and studied the rotational lines of the HC$_3$N molecule (cyanoacetylene) in the powerful outflow/hot molecular core G331.512-0.103. We identified thirty-one rotational lines at $J$ levels between 24 and 39; seventeen of them in the ground vibrational state $v$=0 (9 lines corresponding to the main C isot

Muhammad Shaban, Ruqayya Awan, Muhammad Moazam Fraz, Ayesha Azam

Digital histology images are amenable to the application of convolutional neural network (CNN) for analysis due to the sheer size of pixel data present in them. CNNs are generally used for representation learning from small image patches (e.g. 224x224) extracted from digital histology images due to computational and memory constraints. However, this approach

Nan Zou, Stanislav Volgushev, Axel Bücher

Block maxima methods constitute a fundamental part of the statistical toolbox in extreme value analysis. However, most of the corresponding theory is derived under the simplifying assumption that block maxima are independent observations from a genuine extreme value distribution. In practice however, block sizes are finite and observations from different blo

Donatella Romano, Francesca Matteucci, Zhi-Yu Zhang, Rob J. Ivison

Chemical abundances and abundance ratios measured in galaxies provide precious information about the mechanisms, modes and time scales of the assembly of cosmic structures. Yet, the nucleogenesis and chemical evolution of elements heavier than helium are dictated mostly by the physics of the stars and the shape of the stellar mass spectrum. In particular, es

Siqi Liu, Kee Yuan Ngiam, Mengling Feng

Owe to the recent advancements in Artificial Intelligence especially deep learning, many data-driven decision support systems have been implemented to facilitate medical doctors in delivering personalized care. We focus on the deep reinforcement learning (DRL) models in this paper. DRL models have demonstrated human-level or even superior performance in the

J. Brian Pitts

Is change missing in Hamiltonian Einstein-Maxwell theory? Given the most common definition of observables (having weakly vanishing Poisson bracket with each first-class constraint), observables are constants of the motion and nonlocal. Unfortunately this definition also implies that the observables for massive electromagnetism with gauge freedom (Stueckelber

Alexandru Baltag, Soroush Rafiee Rad, Sonja Smets

We propose a new model for forming beliefs and learning about unknown probabilities (such as the probability of picking a red marble from a bag with an unknown distribution of coloured marbles). The most widespread model for such situations of 'radical uncertainty' is in terms of imprecise probabilities, i.e. representing the agent's knowledge as

Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Svore

This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The results show that model interpolation, though simple, achieves the best results on all the open test sets where the test data is very different from the training data. The tree-based b

Paul Balister, Béla Bollobás, Robert Morris, Julian Sahasrabudhe

We show that there exist absolute constants $Δ> δ> 0$ such that, for all $n \geqslant 2$, there exists a polynomial $P$ of degree $n$, with $\pm 1$ coefficients, such that $$δ\sqrt{n} \leqslant |P(z)| \leqslant Δ\sqrt{n}$$ for all $z\in\mathbb{C}$ with $|z|=1$. This confirms a conjecture of Littlewood from 1966.

Hilal A. Ganie, S. Pirzada, A. Alhevaz, M. Baghipur

For a simple connected graph $G$, let $D(G)$, $Tr(G)$, $D^{L}(G)$ and $D^{Q}(G)$, respectively be the distance matrix, the diagonal matrix of the vertex transmissions, distance Laplacian matrix and the distance signless Laplacian matrix of a graph $G$. The convex linear combinations $D_α(G)$ of $Tr(G)$ and $D(G)$ is defined as $D_α(G)=αTr(G)+(1-α)D(G)$, $0\l

Massimo D'Elia, Francesco Negro, Andrea Rucci, Francesco Sanfilippo

We study the dependence of the static quark free energy on the baryon chemical potential for $N_f = 2+1$ QCD with physical quark masses, in a range of temperature spanning from 120~MeV up to 1~GeV and adopting a stout staggered discretization with two different values of the Euclidean temporal extension, $N_t = 6$ and $N_t = 8$. In order to deal with the sig

Chao-Hsiang Sheu, Mikhail Shifman

In this paper two issues are addressed. First, we discuss renormalization properties of a class of gauged linear sigma models (GLSM) which reduce to $\mathbb{WCP}(N,\tilde{N})$ non-linear sigma models (NLSM) in the low-energy limit. Sometimes they are referred to as the Hanany-Tong models. If supersymmetry is ${\cal N} =(2,2)$ the ultraviolet-divergent logar

Hannah V. Bish, Jessica K. Werk, J. Xavier Prochaska, Kate H. R. Rubin

We present a novel absorption line survey using 54 blue horizontal branch stars (BHBs) in the Milky Way halo as background sources for detecting gas flows at the disk-halo interface. Distance measurements to high-latitude ($b$ > 60°) background stars at 3.1-13.4 kpc, combined with unprecedented spatial sampling and spectral resolution, allow us to examine th

Milad Behvandi, Mohammad Azam Khosravi, Amir Abolfazl Suratgar

This article introduces a new algorithm for nonlinear state estimation based on deterministic sigma point and EKF linearized framework for priori mean and covariance respectively. This method reduces the computation cost of UKF about 50% and has better accuracy compared to EKF due to propagating mean and Covariance of state to 3rd order Taylor series. Severa

Suhas S Kowshik, Kirill Andreev, Alexey Frolov, Yury Polyanskiy

We discuss the problem of designing channel access architectures for enabling fast, low-latency, grant-free and uncoordinated uplink for densely packed wireless nodes. Specifically, we study random-access codes, previously introduced for the AWGN multiple-access channel (MAC) by Polyanskiy'2017, in the practically more relevant case of users subject to R

L G Suttle, G C Burdiak, C L Cheung, T Clayson

A supersonic flow of magnetized plasma is produced by the application of a 1 MA-peak, 500 ns current pulse to a cylindrical arrangement of parallel wires, known as an inverse wire array. The plasma flow is produced by the JxB acceleration of the ablated wire material, and a magnetic field of several Tesla is embedded at source by the driving current. This se

Pei-Hong Gu

In the inverse seesaw scenario, several fermion singlets have a small Majorana mass term. We show such Majorana masses can be suppressed by some heavy fermion and/or Higgs singlets after a global symmetry is spontaneously broken. These interactions can also accommodate a leptogenesis mechanism to explain the cosmic baryon asymmetry.

Pei-Hong Gu

A TeV-scale Higgs doublet can acquire a tiny vacuum expectation value via its small mixing with the standard model Higgs doublet. Ones then can realize a testable Dirac neutrino mass generation through the sizable Yukawa couplings among this new Higgs doublet, several right-handed neutrinos and the standard model lepton doublets. We show the small mixing bet

Melanie Schmitz, Francesco Hautmann, Hannes Jung, Sara Taheri Monfared

We present the determination of Transverse Momentum Dependent (TMD) parton distributions from Monte Carlo parton showers. We investigate the effective TMD distributions obtained from the PYTHIA8 and HERWIG6 parton showers and compare them to the TMD distributions determined within the Parton Branching method.

Shao-Yuan Lo, Hsueh-Ming Hang, Sheng-Wei Chan, Jing-Jhih Lin

Lane detection plays an important role in a self-driving vehicle. Several studies leverage a semantic segmentation network to extract robust lane features, but few of them can distinguish different types of lanes. In this paper, we focus on the problem of multi-class lane semantic segmentation. Based on the observation that the lane is a small-size and narro

Alexa Rakoski, Yun Suk Eo, Çağlıyan Kurdak, Boyoun Kang

A well-known feature in transport data of the topological Kondo insulator SmB$_6$ is the sign change in the Hall coefficient at 65 K. Carriers in SmB$_6$ are known to be negative, but above 65 K, the Hall sign suggests that the carriers are positive. Here, we extend Hall measurements up to 400 K and observe that the Hall coefficient changes back to the corre

L. Biasco, L. Chierchia

We show that, in general, averaging at simple resonances a real--analytic, nearly--integrable Hamiltonian, one obtains a one--dimensional system with a cosine--like potential; ``in general'' means for a generic class of holomorphic perturbations and apart from a finite number of simple resonances with small Fourier modes; ``cosine--like'' mea

Giovanni Amendola, Francesco Ricca

In the last years, abstract argumentation has met with great success in AI, since it has served to capture several non-monotonic logics for AI. Relations between argumentation framework (AF) semantics and logic programming ones are investigating more and more. In particular, great attention has been given to the well-known stable extensions of an AF, that ar

Chen Qin, Jo Schlemper, Jinming Duan, Gavin Seegoolam

Dynamic magnetic resonance imaging (MRI) exhibits high correlations in k-space and time. In order to accelerate the dynamic MR imaging and to exploit k-t correlations from highly undersampled data, here we propose a novel deep learning based approach for dynamic MR image reconstruction, termed k-t NEXT (k-t NEtwork with X-f Transform). In particular, inspire

David W. Tam, Hsin-Hua Lai, Jin Hu, Xingye Lu

We use inelastic neutron scattering to show that long-range spin waves arising from the static bicollinear antiferromagnetic (AF) order in FeTe, which have twofold rotational symmetry in a fully detwinned crystal, rapidly dissolve above $E\approx 26$ meV into ridges of scattering with fourfold rotational symmetry and a nearly isotropic magnetic fluctuation s

Jonathan D. Cohen

The truss, a relaxation of the clique based on triangles, serves to identify clusters of actors in a way that is easy to interpret and is computationally attractive. This paper introduces the 4-cycle-based relative to the truss, called the trapeze, presents a weighted extension of both the truss and trapeze, and offers the refinements of strong trusses and t

Justin Curry

In this note we give a self-contained proof of a fundamental statement in the study of cosheaves over a poset. Specifically, if a functor has domain a poset and co-domain a co-complete category, then the left Kan extension of that functor along the embedding of the domain poset into its poset of down-sets is a cosheaf. This proof is meant to replace the mist

Matteo Taffetani, Finn Box, Arthur Neveu, Dominic Vella

The preference of thin flat sheets to bend rather than stretch, combined with results from Geometry, mean that changes in a thin sheet's Gaussian curvature are prohibitively expensive. As a result, an imposed curvature in one principal direction inhibits bending in the other: so-called curvature-induced rigidity. Here, we study the buckling behaviour of

Mikhail V. Bondarko, Sergei V. Vostokov

We prove that certain triangulated categories are (weakly) approximable in the sense of A. Neeman. We prove that a triangulated $C$ that is compactly generated by a single object $G$ is weakly approximable if $C(G,G[i])=0$ for $i>1$ (we say that $G$ is weakly negative if this assumption is fulfilled; the case where the equality $C(G,G[1])=0$ is fulfilled as

V. Flammang

We explain how a slight variant in the use of our recursive algorithm leads to improve the known lower bounds for the absolute trace of a totally positive algebraic integer. We also link the absolute trace of a totally positive algebraic integer and the absolute trace of a totally positive reciprocal integer.

Kelly Lais Wiggers, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich, Laurent Heutte

This paper describes two approaches for content-based image retrieval and pattern spotting in document images using deep learning. The first approach uses a pre-trained CNN model to cope with the lack of training data, which is fine-tuned to achieve a compact yet discriminant representation of queries and image candidates. The second approach uses a Siamese

Giovanni Amendola, Carmine Dodaro, Marco Maratea

Abstract solvers are a method to formally analyze algorithms that have been profitably used for describing, comparing and composing solving techniques in various fields such as Propositional Satisfiability (SAT), Quantified SAT, Satisfiability Modulo Theories, Answer Set Programming (ASP), and Constraint ASP. In this paper, we design, implement and test nove

Hallee E. Wong, Osman Akar, Emmanuel Antonio Cuevas, Iuliana Tabian

Markerless augmented reality can be a challenging computer vision task, especially in live broadcast settings and in the absence of information related to the video capture such as the intrinsic camera parameters. This typically requires the assistance of a skilled artist, along with the use of advanced video editing tools in a post-production environment. W

Kenneth R. O'Neal, Arpita Paul, Amal al-Wahish, Kendall D. Hughey

While 3$d$-containing materials display strong electron correlations, narrow band widths, and robust magnetism, 5$d$ systems are recognized for strong spin-orbit coupling, increased hybridization, and more diffuse orbitals. Combining these properties leads to novel behavior. Sr$_3$NiIrO$_6$, for example, displays complex magnetism and ultra-high coercive fie

Xiaosheng Yan, Yuanlong Yu, Feigege Wang, Wenxi Liu

In this paper, we propose a novel iterative multi-task framework to complete the segmentation mask of an occluded vehicle and recover the appearance of its invisible parts. In particular, to improve the quality of the segmentation completion, we present two coupled discriminators and introduce an auxiliary 3D model pool for sampling authentic silhouettes as

Shervin Minaee, Amirali Abdolrashidi

Iris recognition has been an active research area during last few decades, because of its wide applications in security, from airports to homeland security border control. Different features and algorithms have been proposed for iris recognition in the past. In this paper, we propose an end-to-end deep learning framework for iris recognition based on residua

M. Nizam, B. Satyanarayana, R. R. Shinde, G. Majumder

The Multigap Resistive Plate Chambers (MRPCs) provide excellent timing as well as position resolutions at relatively low cost. Therefore, they can be used in medical imaging applications such as PET where precise timing is a crucial parameter of measurement. We have designed and fabricated several six-gap glass MRPCs and extensively studied their performance

The CUPID Interest Group

CUPID is a proposed future tonne-scale bolometric neutrinoless double beta decay ($0νββ$) experiment to probe the Majorana nature of neutrinos and discover Lepton Number Violation in the so-called inverted hierarchy region of the neutrino mass. CUPID will be built on experience, expertise and lessons learned in CUORE, and will exploit the current CUORE infra

Yifan Wang, Zichun Zhong, Jing Hua

This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visualize high-fidelity 3D / 4D organ geometric models from single-view medical image in real time. Traditional 3D / 4D medical image reconstruction requires near hundreds of projections, which cost insufferable computational time and deliver undesirable high imagin

Armin Seyeditabari, Narges Tabari, Shafie Gholizadeh, Wlodek Zadrozny

In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. In this work, we argue that current methods which are based on conventional machine learning models cannot grasp the intricacy of emotional language by

Argyrios Christodoulou, Ian Short

The Denjoy-Wolff theorem is a foundational result in complex dynamics, which describes the dynamical behaviour of the sequence of iterates of a holomorphic self-map $f$ of the unit disc $\mathbb{D}$. Far less well understood are nonautonomous dynamical systems $F_n=f_n\circ f_{n-1} \circ \dots \circ f_1$ and $G_n=g_1\circ g_{2} \circ \dots \circ g_n$, for $n

Laura de Sousa Oliveira, Neophytos Neophytou

Nanoporous materials are of broad interest for various applications, in particular advanced thermoelectric materials. The introduction of nanoscale porosity, even at modest levels, has been known to drastically reduce a materials thermal conductivity, in some cases even below its amorphous limit, thereby significantly increasing its thermoelectric figure of

M. Afsary, M. Bathaee, F. Bakhshinezhad, A. T. Rezakhani

We provide a physically motivated definition for the binding energy (or bond-dissociation) of a bipartite quantum system. We consider coherently applying an external field to cancel out the interaction between the subsystems, to break their bond and separate them as systems from which no work can be extracted coherently by any cyclic evolution. The minimum d

Luca Egoriti, Marla Cervantes, Thomas Day Goodacre, Alexander Gottberg

A series of irradiation tests have been performed at TRIUMF to investigate different material pairings to act as high-power electron-to-gamma converter for the ARIEL Electron Target East (AETE). The bulk of the converter body will be made out of an aluminum alloy with a sub-millimeter high-Z metal layer bonded to the surface facing the incoming electron beam

Emmanuel Filiot, Shibashis Guha, Nicolas Mazzocchi

Parikh automata extend automata with counters whose values can only be tested at the end of the computation, with respect to membership into a semi-linear set. Parikh automata have found several applications, for instance in transducer theory, as they enjoy decidable emptiness problem. In this paper, we study two-way Parikh automata. We show that emptiness b

Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi

Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an overview over these recent advancements, focusing on neural network based question answering systems over knowledge graphs. We introduce readers to the challenges in the tasks, curre

Luis A. Medina, Matthew G. Parker, Constanza Riera, Pantelimon Stanica

In this paper we define a new transform on (generalized) Boolean functions, which generalizes the Walsh-Hadamard, nega-Hadamard, $2^k$-Hadamard, consta-Hadamard and all $HN$-transforms. We describe the behavior of what we call the root- Hadamard transform for a generalized Boolean function $f$ in terms of the binary components of $f$. Further, we define a no

S. Sakurai, D. Depaoli, R. López-Coto

The Cherenkov Telescope Array (CTA) represents the next generation of very high-energy gamma-ray observatory, which will provide broad coverage of gamma rays from 20 GeV to 300 TeV with unprecedented sensitivity. CTA will employ three different sizes of telescopes, and the Large-Sized Telescopes (LSTs) of 23-m diameter dish will provide the sensitivity in th

José Alves Oliveira, F. E. Brochero Martínez

Let $\mathbb F_q$ denote the finite field with $q$ elements. In this paper we use the relationship between suitable polynomials and number of rational points on algebraic curves to give the exact number of elements $a\in \mathbb F_q$ for which the binomial $x^n(x^{(q-1)/r} + a)$ is a permutation polynomial in the cases $r = 2$ and $r = 3$.

Vyacheslav Saiko, Alexander Karpov

In this work, the charge equilibration process has been analyzed within the Langevin-type dynamical approach. Its duration and energy dependence are discussed. We have analyzed the isotopic distributions of final products obtained in the isospin-asymmetric 58Ni,40Ca + 208Pb reactions. Comparison of 58Ni,64Ni + 208Pb systems have been done in order to analyze

A. K. Lemmens, D. B. Rap, J. M. M. Thunnissen, C. J. Mackie

Aims. In this work we determine the effects of anharmonicity on the mid-infrared spectra of the linear polycyclic aromatic hydrocarbons (PAHs) naphthalene, anthracene, tetracene and pentacene recorded using the free electron laser FELIX. Methods. Comparison of experimental spectra obtained under supersonic jet conditions with theoretically predicted spectra

P. A. Igoshev, I. A. Nekrasov, N. S. Pavlov, T. H. Chinyaev

A comparative study of the magnetocaloric effect (MCE) in metals within the single-band Hubbard model on the face-centered cubic (fcc) lattice using both mean-field (Stoner) approximation (MFA) and dynamical mean-field theory (DMFT) is done. The MCE is investigated in the case of second order magnetic phase transition from ferromagnet to paramagnet. To ensur

Rupesh Kumar, Adrian Wonfor, Richard Penty, Tim Spiller

Advances in highly sensitive detection techniques for classical coherent communication systems have reduced the received signal power requirements to a few photons per bit. At this level one can take advantage of the quantum noise to create secure communication, using continuous variable quantum key distribution (CV-QKD). In this work therefore we embed CV-Q

B. A. van Tiggelen

Abraham forces are defined as electromagnetic forces on neutral objects caused by the presence of slow, time-dependent, homogeneous electromagnetic fields. Only a few experimental observations have been reported, and different formulations exist in literature. The ``standard" Abraham force is usually associated with the full derivative $\partial_t(\mathb

Daniël Boer

This is a brief overview of the spin physics opportunities at a high energy, high luminosity, polarized Electron-Ion Collider (EIC). It covers measurements of electroweak polarized structure functions, quark and gluon PDFs, TMDs, GPDs and GTMDs. Exploiting the many possible final states allows to probe various spin effects. Open and bound heavy quark product

Kokorina E. E., Medvedev M. V., Nekrasov I. A

Here we perform $ab-initio$ study of Curie temperature $T_C$ under hydrostatic pressure for intermetallic compound GdFe$_2$. To calculate $T_C$ for GdFe$_2$ we applied mean-field solution of the Heisenberg model for several magnetic sublattices with DFT/LDA calculated values of necessary exchange interaction integrals and local magnetic moments. To compare w

E. Jourdain, J. P. Roques

We have analyzed 16 years of observations dedicated to the Crab (pulsar + nebula) with the INTEGRAL SPI instrument to investigate its polarization properties. We find that the source presents a substantially polarized emission (PF = 24%) in the hard X-ray domain, with the electric vector aligned with the pulsar spin axis, in agreement with other results at v

Pranava Madhyastha, Josiah Wang, Lucia Specia

We address the task of evaluating image description generation systems. We propose a novel image-aware metric for this task: VIFIDEL. It estimates the faithfulness of a generated caption with respect to the content of the actual image, based on the semantic similarity between labels of objects depicted in images and words in the description. The metric is al

Nobuaki Yagita

In this paper, I correct errors in my paper (Kodai Math. J. (2015)) about gamma filtrations for classifying spaces for abelian p-groups which are not elementary. We also extend Chetard's results for such 2-groups to p-groups for odd prime.

N. N. Avdeev

A point set $M$ in the Euclidean plane is called a planar integral point set if all the distances between the elements of $M$ are integers, and $M$ is not situated on a straight line. A planar integral point set is called to be in semi-general position, if it does not contain collinear triples. The existing lower bound for mininum diameter of planar integral

Anton I. Ovcharenko, Cédric Blanchard, Jean-Paul Hugonin, Christophe Sauvan

We develop a semi-analytical model to describe bound states in the continuum (BICs) in photonic crystal slabs. We model leaky modes supported by photonic crystal slabs as a transverse Fabry-Perot resonance composed of a few propagative Bloch waves bouncing back and forth vertically inside the slab. This multimode Fabry-Perot model accurately predicts the exi

Anubrata Das, Matthew Lease

While search efficacy has been evaluated traditionally on the basis of result relevance, fairness of search has attracted recent attention. In this work, we define a notion of distributional fairness and provide a conceptual framework for evaluating search results based on it. As part of this, we formulate a set of axioms which an ideal evaluation framework