April 2020 arXiv papers — page 16

Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert

Code completion is one of the most widely used features of modern integrated development environments (IDEs). While deep learning has made significant progress in the statistical prediction of source code, state-of-the-art neural network models consume hundreds of megabytes of memory, bloating the development environment. We address this in two steps: first

Jakob Jonnerby, Philip Lazos, Edwin Lock, Francisco Marmolejo-Cossío

We propose a novel testing and containment strategy in order to contain the spread of SARS-CoV2 while permitting large parts of the population to resume social and economic activity. Our approach recognises the fact that testing capacities are severely constrained in many countries. In this setting, we show that finding the best way to utilise this limited n

Ilya Kostrikov, Denis Yarats, Rob Fergus

We propose a simple data augmentation technique that can be applied to standard model-free reinforcement learning algorithms, enabling robust learning directly from pixels without the need for auxiliary losses or pre-training. The approach leverages input perturbations commonly used in computer vision tasks to regularize the value function. Existing model-fr

Edelcio G. de Souza, Alexandre Costa-Leite, Diogo H. B. Dias

This paper shows how to transform explosive many-valued systems into paraconsistent logics. We investigate especially the case of three-valued systems showing how paraconsistent three-valued logics can be obtained from them.

Carolina Negrelli, Lucila Kraiselburd, Susana J. Landau, Claudia Scóccola

We analyse the MOdified Gravity (MOG) theory, proposed by Moffat, in a cosmological context. We use data from Type Ia Supernovae (SNe Ia), Baryon Acoustic Oscillations (BAO) and Cosmic Chronometers (CC) to test MOG predictions. For this, we perform $\chi^2$ tests considering fixed values of $H_0$ and $V_G$, the self-interaction potential of one of the scalar

Dan Cristofaro-Gardiner

A striking result of McDuff and Schlenk asserts that in determining when a four-dimensional symplectic ellipsoid can be symplectically embedded into a four-dimensional symplectic ball, the answer is governed by an "infinite staircase" determined by the odd-index Fibonacci numbers and the Golden Mean. Here we study embeddings of one four-dimensional symplecti

Daniel Mikkola, Paul. J McMillan, David Hobbs

We study the radial migration of stars as a function of orbital action as well as the structural properties of a large suite of N-body simulations of isolated disc galaxies. Our goal is to establish a relationship between the radial migration efficiency of stars and their vertical action. We aim to describe how that relationship depends on the relative gravi

Alana Marzoev, Samuel Madden, M. Frans Kaashoek, Michael Cafarella

Large, human-annotated datasets are central to the development of natural language processing models. Collecting these datasets can be the most challenging part of the development process. We address this problem by introducing a general purpose technique for ``simulation-to-real'' transfer in language understanding problems with a delimited set of target be

Mark van Hoeij, Hanson Smith

We give a formula for divisors of modular units on $X_1(N)$ and use it to prove that the $\mathbb{Q}$-gonality of the modular curve $X_1(N)$ is bounded above by $\left[\frac{11N^2}{840}\right]$, where $[\bullet]$ denotes the nearest integer.

Angel Garcia-Chung

We show the explicit expression of the geometric phase for $n$-partite Gaussian states. In our analysis, the covariance matrix can be obtained as a boundary term of the geometric phase.

Wiesław Kubiś, Boriša Kuzeljević

We discuss some finite homogeneous structures, addressing the question of universality of their automorphism groups. We also study the existence of so-called Kat\v{e}tov functors in finite categories of embeddings or homomorphisms.

V. K. Maurya, Manju Mishra Patidar, Anita Dhaka, R. Rawat

We report large magnetoresistance (MR) and Shubnikov-de Haas (SdH) oscillations in single crystals of magnetically (M= Ni and Fe) doped M$_x$Bi$_{0.97-x}$Sb$_{0.03}$ ($x=$ 0, 0.02) topological insulators. The R$\bar{3}$m symmetry and phase have been confirmed by the Rietveld refinement of x-ray diffraction data. Interestingly, a magnetic field induced phase

Emroj Hossain, Satyanu Bhadra, Harsh Jain, Soumen Das

N95 respirators comprise a critical part of the personal protective equipment used by frontline health-care workers, and are typically meant for one-time usage. However, the recent COVID-19 pandemic has resulted in a serious shortage of these masks leading to a worldwide effort to develop decontamination and re-use procedures. A major factor contributing to

Zihan Wang, Karthikeyan K, Stephen Mayhew, Dan Roth

Multilingual BERT (M-BERT) has been a huge success in both supervised and zero-shot cross-lingual transfer learning. However, this success has focused only on the top 104 languages in Wikipedia that it was trained on. In this paper, we propose a simple but effective approach to extend M-BERT (E-BERT) so that it can benefit any new language, and show that our

Si Sun, Zhenghao Liu, Chenyan Xiong, Zhiyuan Liu

Open-domain KeyPhrase Extraction (KPE) aims to extract keyphrases from documents without domain or quality restrictions, e.g., web pages with variant domains and qualities. Recently, neural methods have shown promising results in many KPE tasks due to their powerful capacity for modeling contextual semantics of the given documents. However, we empirically sh

Alessandro Audrito, Enrico Serra, Paolo Tilli

We study the existence of segregated solutions to a class of reaction-diffusion systems with strong interactions, arising in many physical applications. These special solutions are obtained as weak limits of minimizers of a family of perturbed functionals. We prove some a priori estimates through a minimization procedure which is nonstandard in the parabolic

Stephen Roller, Emily Dinan, Naman Goyal, Da Ju

Building open-domain chatbots is a challenging area for machine learning research. While prior work has shown that scaling neural models in the number of parameters and the size of the data they are trained on gives improved results, we show that other ingredients are important for a high-performing chatbot. Good conversation requires a number of skills that

Carles Batlle, Joaquim Gomis

We study the space-time symmetries of the actions obtained by expanding the action for a massive free relativistic particle around the Galilean action. We obtain all the point space-time symmetries of the post-Galilean actions by working in canonical space. We also construct an infinite collection of generalized Schr\"odinger algebras parameterized by an int

Lijia Ding, Junmei Fan

Bergman-type integral operators are classical operators in complex analysis and operator theory. Recently, the first author and his collaborator \cite{DiW} completely characterized the $L^p$-$L^q$ boundedness of Bergman-type integral operators $K_\alpha,K_\alpha^+$ and the $L^p$-$L^q$ compactness of $K_\alpha$ on the unit ball. In this paper, we will use a s

Jason F. Parisi, Felix I. Parra, Colin M. Roach, Carine Giroud

Local linear gyrokinetic simulations show that electron temperature gradient (ETG) instabilities are the fastest growing modes for $k_y \rho_i \gtrsim 0.1$ in the steep gradient region for a JET pedestal discharge (92174) where the electron temperature gradient is steeper than the ion temperature gradient. Here, $k_y$ is the wavenumber in the direction perpe

Alberto Cazzaniga, Andrea T. Ricolfi

We prove that, given integers $m\geq 3$, $r\geq 1$ and $n\geq 0$, the moduli space of torsion free sheaves on $\mathbb P^m$ with Chern character $(r,0,\ldots,0,-n)$ that are trivial along a hyperplane $D \subset \mathbb P^m$ is isomorphic to the Quot scheme $\mathrm{Quot}_{\mathbb A^m}(\mathscr O^{\oplus r},n)$ of $0$-dimensional length $n$ quotients of the

Chinmay Patwardhan

SARS-COV-2 has stopped the world in its footsteps and a third of the population has been forced to stay at home. Here we present a comparative study of the performance of states of India, in curbing the spread of the disease, that are most affected by the pandemic. We have done so based on the data collected between 14th March, 2020 to 17th April, 2020. We d

Jie Zhou, Shengding Hu, Xin Lv, Cheng Yang

A comprehensive knowledge graph (KG) contains an instance-level entity graph and an ontology-level concept graph. The two-view KG provides a testbed for models to "simulate" human's abilities on knowledge abstraction, concretization, and completion (KACC), which are crucial for human to recognize the world and manage learned knowledge. Existing studies mainl

Jacob Szeftel, Nicolas Sandeau, Michel Abou Ghantous, Muhammad El-Saba

A stability criterion is worked out for the superconducting phase. The validity of a prerequisite, established previously for persistent currents, is thereby confirmed. Temperature dependence is given for the specific heat and concentration of superconducting electrons in the vicinity of the critical temperature $T_c$. The isotope effect, mediated by electro

S. Hudan, R. T. deSouza, A. S. Umar, Z. Lin

Above-barrier fusion cross-sections for an isotopic chain of oxygen isotopes with A=16-19 incident on a $^{12}$C target are presented. Experimental data are compared with both static and dynamical microscopic calculations. These calculations are unable to explain the $\sim$37\% increase in the average above-barrier fusion cross-section observed for $^{19}$O

Zhengyang Bai, Charles S. Adams, Guoxiang Huang, Weibin Li

We study dispersive optical nonlinearities of short pulses propagating in high number density, warm atomic vapors where the laser resonantly excites atoms to Rydberg $P$-states via a single-photon transition. Three different regimes of the light-atom interaction, dominated by either Doppler broadening, Rydberg atom interactions, or decay due to thermal colli

Xinya Du, Claire Cardie

The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments. Existing work in event argument extraction typically relies heavily on entity recognition as a preprocessing/concurrent step, causing the well-known problem of error propagation. To avoid this issue, we introduce a new paradigm for event extractio

Pascal S. Raux, Anthony Troger, Pierre Jop, Alban Sauret

The fragmentation of liquid sheets produces a collection of droplets. The size distribution of the droplets has a considerable impact on the coating efficiency of sprays and the transport of contaminants. Although many processes commonly used particulate suspensions, the influence of the particles on the spreading dynamics of the sheet and its subsequent fra

Mariusz Tarnopolski

In order to explain the origin of skewness in the gamma-ray burst (GRB) duration distribution, a statistical model, based on the cosmological time dilation and taking into account the GRB formation rate and instrumental effects, is examined. It is concluded that the considered effects are able to account for only a small fraction of the observed skewness. Th

Jiayin Gu, Pierre Gaspard

Multivariate fluctuation relations are established in three stochastic models of transistors, which are electronic devices with three ports and thus two coupled currents. In the first model, the transistor has no internal state variable and particle exchanges between the ports is described as a Markov jump process with constant rates. In the second model, th

Carlos Handrey Araujo Ferraz

Studies on random packing of bidispersive particles have shown that such systems can capture the underlying behavior of more complex phenomena found in physics and materials engineering. In industry, bidispersive particles are used to allow the increase of density and fluidity of the formed compounds. The understanding of the dynamics of these processes is t

Hengshuang Zhao, Jiaya Jia, Vladlen Koltun

Recent work has shown that self-attention can serve as a basic building block for image recognition models. We explore variations of self-attention and assess their effectiveness for image recognition. We consider two forms of self-attention. One is pairwise self-attention, which generalizes standard dot-product attention and is fundamentally a set operator.

G. Dimarco, L. Pareschi, G. Toscani, M. Zanella

We develop a mathematical framework to study the economic impact of infectious diseases by integrating epidemiological dynamics with a kinetic model of wealth exchange. The multi-agent description leads to study the evolution over time of a system of kinetic equations for the wealth densities of susceptible, infectious and recovered individuals, whose propor

Farhad Gh. Khodaei

In design of new power transformers, reliable and efficient tools are required to expedite research and development processes. Some of these tools are used to interpret the data obtained from the transformer tests for better judgement about the response of the transformer. In this paper a clear procedure is proposed to estimate the nonlinear relation between

Hiroyoshi Mitake, Hung V. Tran, Truong-Son Van

We study the large time behavior of the sublinear viscosity solution to a singular Hamilton-Jacobi equation that appears in a critical Coagulation-Fragmentation model with multiplicative coagulation and constant fragmentation kernels. Our results include complete characterizations of stationary solutions and optimal conditions to guarantee large time converg

Petros S. Bithas, Viktor Nikolaidis, Athanasios G. Kanatas, George K. Karagiannidis

Unmanned aerial vehicle (UAV)-enabled communications have been proposed as a critical part of the beyond fifth-generation (5G) cellular networks. This type of communications is frequently characterized by line-of-sight (LoS) and dynamic propagation conditions. However, in various scenarios, the presence of large obstacles in the LoS path is unavoidable, resu

Pranjal Awasthi, Natalie Frank, Mehryar Mohri

Adversarial or test time robustness measures the susceptibility of a classifier to perturbations to the test input. While there has been a flurry of recent work on designing defenses against such perturbations, the theory of adversarial robustness is not well understood. In order to make progress on this, we focus on the problem of understanding generalizati

Chen-Fatt Lim, Chian-Chou Chen, Ian Smail, Wei-Hao Wang

We analyze an extremely deep 450-$\mu$m image ($1\sigma=0.56$\,mJy\,beam$^{-1}$) of a $\simeq 300$\,arcmin$^{2}$ area in the CANDELS/COSMOS field as part of the SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). We select a robust (signal-to-noise ratio $\geqslant 4$) and flux-limited ($\geqslant 4$\,mJy) sample of 164 sub-millimeter galaxies (SMGs) at 450-$\m

J. P. Saraiva, A. Blanco, J. A. Garzón, D. García-Castro

In 2018-2019 a cosmic-ray latitude survey at sea level was performed by the TRISTAN detector, an autonomous system composed by three planes of RPCs (120 x 150 cm$^{2}$). The detector made a two-way journey on board of the Spanish vessel Sarmiento de Gamboa between Vigo (Spain) and Punta Arenas (Chile), measuring continuously the cosmic-ray rate throughout th

Zhu Liu, Philippe Ciais, Zhu Deng, Ruixue Lei

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when compared with the period last year. In addition other emerging esti

Matteo Baggioli, Mikhail Vasin, Vadim Brazhkin, Kostya Trachenko

We develop a field theory with dissipation based on a finite range of wave propagation and associated gapped momentum states in the wave spectrum. We analyze the properties of the Lagrangian and the Hamiltonian with two scalar fields in different representations and show how the new properties of the two-field Lagrangian are related to Keldysh-Schwinger form

Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen

The robust PCA of covariance matrices plays an essential role when isolating key explanatory features. The currently available methods for performing such a low-rank plus sparse decomposition are matrix specific, meaning, those algorithms must re-run for every new matrix. Since these algorithms are computationally expensive, it is preferable to learn and sto

Devan V. Mehrotra, Rachel Marceau West

Randomized clinical trials are often designed to assess whether a test treatment prolongs survival relative to a control treatment. Increased patient heterogeneity, while desirable for generalizability of results, can weaken the ability of common statistical approaches to detect treatment differences, potentially hampering the regulatory approval of safe and

Alexei V. Nikitin, Ruslan L. Davidchack

We outline an approach to physical-layer steganography where the transmitted low-power stego messages are statistically indistinguishable from the Gaussian component of the channel noise (e.g. the thermal noise) observed in the same spectral band, and thus the channel noise itself serves as an effective cover signal. We also demonstrate how the apparent spec

Jonathan P. Chang, Justin Cheng, Cristian Danescu-Niculescu-Mizil

Discourse involves two perspectives: a person's intention in making an utterance and others' perception of that utterance. The misalignment between these perspectives can lead to undesirable outcomes, such as misunderstandings, low productivity and even overt strife. In this work, we present a computational framework for exploring and comparing both perspect

Namkyoung Lee, Michael H. Azarian, Michael G. Pecht

This paper develops an explainable deep learning model that estimates the remaining useful lives of rotating machinery. The model extracts high-level features from Fourier transform using an autoencoder. The features are used as input to a feedforward neural network to estimate the remaining useful lives. The paper explains the model's behavior by analyzing

Li Lei, Hong-Wei Xu

In this survey, we will focus on the mean curvature flow theory with sphere theorems, and discuss the recent developments on the convergence theorems for the mean curvature flow of arbitrary codimension inspired by the Yau rigidity theory of submanifolds. Several new differentiable sphere theorems for submanifolds are obtained as consequences of the converge

Xiang Zhou, Yixin Nie, Hao Tan, Mohit Bansal

We find that the performance of state-of-the-art models on Natural Language Inference (NLI) and Reading Comprehension (RC) analysis/stress sets can be highly unstable. This raises three questions: (1) How will the instability affect the reliability of the conclusions drawn based on these analysis sets? (2) Where does this instability come from? (3) How shoul

Yaolong Zhang, Sheng Ye, Jinxiao Zhang, Ce Hu

Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models targeting tensorial properties, which are rotationally covariant. Here, we propose tensorial neural network (NN) models to learn both tensorial response and transition properties, in whi

D. Behera, S. K. Tripathy, T. R. Routray, B. Behera

We use a finite range simple effective interaction to construct nuclear equations of state for the study of the density dependence of the nuclear symmetry energy. The EoSs provide good descriptions of the nuclear symmetry energy at a subsaturation density $\rho_c=0.11$ fm$^{-3}$ and at a density around two times the saturation density $\rho_0$. We obtain a c

Tjark Heitmann, Jonas Richter, Thomas Dahm, Robin Steinigeweg

We consider two mutually interacting fermionic particle species on a one-dimensional lattice and study how the mass ratio $\eta$ between the two species affects the (equilibration) dynamics of the particles. Focussing on the regime of strong interactions and high temperatures, two well-studied points of reference are given by (i) the case of equal masses ${\

Shai M. Chester, Rohit R. Kalloor, Adar Sharon

The partition function of a 3d $\mathcal{N}=4$ gauge theory with rank $N$ can be computed using supersymmetric localization in terms of a matrix model, which often can be formulated as an ideal Fermi gas with a non-trivial one-particle Hamiltonian. We show how OPE coefficients of protected operators correspond in this formalism to averages of $n$-body operat

Peter Grandits, Maike Klein

We consider two insurance companies with endowment processes given by Brownian motions with drift. The firms can collaborate by transfer payments in order to maximize the probability that none of them goes bankrupt. We show that pushing maximally the company with less endowment is the optimal strategy for the collaboration if the Brownian motions are correla

Maxim Barkov, Yonggang Luo, Maxim Lyutikov

We develop a model of early X-ray afterglows of gamma-ray bursts originating from the reverse shock (RS) propagating through ultra-relativistic, highly magnetized pulsar-like winds produced by long-lasting central engines. We first perform fluid and MHD numerical simulations of relativistic double explosions. We demonstrate that even for constant properties

Felipe Oviedo, Zekun Ren, Xue Hansong, Siyu Isaac Parker Tian

Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost. So far, solar cell R&D has mostly focused on achieving record efficiencies, a process that often results in small batches, large variance, and limited understanding of the physical causes of under

Amit Chaulwar

With increasing usage of deep learning algorithms in many application, new research questions related to privacy and adversarial attacks are emerging. However, the deep learning algorithm improvement needs more and more data to be shared within research community. Methodologies like federated learning, differential privacy, additive secret sharing provides a

A. T. Bajkova, G. Carraro, V. I. Korchagin, N. O. Budanova

We employ Gaia DR2 proper motions for 151 Milky Way globular clusters from Vasiliev (2019) in tandem with distances and line-of-sight velocities to derive their kinematical properties. To assign clusters to the Milky Way thick disk, bulge, and halo we follow the approach of Posti et al. (2018) who distinguished among different Galactic stellar components usi

I. C. Niţu, H. T. J. Bevins, J. D. Bray, A. M. M. Scaife

We present an updated estimate of the cosmic radio background (CRB) and the corresponding attenuation lengths for ultra-high energy photons. This new estimate provides associated uncertainties as a function of frequency derived from observational constraints on key physical parameters. We also present the expected variation in the spectrum of the CRB as a fu

Shan Yang, Yuxuan Wang, Lei Xie

Attention-based sequence-to-sequence (seq2seq) speech synthesis has achieved extraordinary performance. But a studio-quality corpus with manual transcription is necessary to train such seq2seq systems. In this paper, we propose an approach to build high-quality and stable seq2seq based speech synthesis system using challenging found data, where training spee

Melissa Munoz, Gregg Wade, Daniel Faes, Alex Carciofi

Massive star winds are important contributors to the energy, momentum and chemical enrichment of the interstellar medium. Strong, organized and predominantly dipolar magnetic fields have been firmly detected in a small subset of massive O-type stars. Magnetic massive stars are known to exhibit phase-locked variability of numerous observable quantities that i

K. Chen, C. Luo, B. B. Chen, R. M. Abrudan

Charge transfer induced interfacial ferromagnetism and its impact on the exchange bias effect in La$_{0.7}$Sr$_{0.3}$MnO$_3$/NdNiO$_3$ correlated oxide heterostructures were investigated by soft x-ray absorption and x-ray magnetic circular dichroism spectra in a temperature range from 10 to 300 K. Besides the antiferromagnetic Ni$_3^+$ cations which are natu

Che-Hung Huang

Let $\pi:\mathcal{X}\to S$ be a holomorphic family of canonically polarized manifolds over a complex manifold $S$, and $f:\mathcal{X}\to N$ a smooth map into a Riemannian manifold $N$. Consider the energy function $E: S\to \mathbb{R}$ that assigns $z\in S$ to the Dirichlet energy of the map $f|_{\mathcal{X}_z}:\mathcal{X}_z\to N$, where $\mathcal{X}_z=\pi^{-

George F R Ellis

There has been much controversy over weak and strong emergence in physics and biology. As pointed out by Phil Anderson in many papers, the existence of broken symmetries is the key to emergence of properties in much of solid state physics. By carefully distinguishing between dfferent types of symmetry breaking and tracing the relation between broken symmetri

Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang

Event detection (ED), which means identifying event trigger words and classifying event types, is the first and most fundamental step for extracting event knowledge from plain text. Most existing datasets exhibit the following issues that limit further development of ED: (1) Data scarcity. Existing small-scale datasets are not sufficient for training and sta

L. Fernández-Menchero, C. S. Jeffery, C. A. Ramsbottom, C. P. Ballance

Heavy-metal hot subdwarfs (sdB and sdO) represent a small group of stars with unusually high concentrations of trans-iron elements in their atmospheres, having abundances ~ 10000 times solar. One example is LS IV-14$^{\circ}$ 116, where a number of heavy-metal absorption lines of Sr II, Y III and Zr IV have been observed in the optical band 4000 - 5000 A. We

Jin Lei, Pierre Descouvemont

The Lagrange-mesh $R$-matrix method is generalized to inhomogeneous equations. This method is numerically stable and efficient. It can be directly used for transfer reactions with the formalism discussed by Ascuitto and Glendenning [Phys. Rev. 181,1396 (1969)] and for inclusive breakup reactions modeled by Ichimura, Austern, and Vincent [Phys. Rev. C 32, 431

Zhongchao Qian, Tyler L. Hayes, Kushal Kafle, Christopher Kanan

Traditionally, deep convolutional neural networks consist of a series of convolutional and pooling layers followed by one or more fully connected (FC) layers to perform the final classification. While this design has been successful, for datasets with a large number of categories, the fully connected layers often account for a large percentage of the network

Jun-Yi Wu, Mio Murao

We have developed a theory for accessing quantum coherences in mutually unbiased bases associated with generalized Pauli operators in multiphoton multimode linear optics networks (LONs). We show a way to construct complementary Pauli measurements in multiphoton LONs and establish a theory for evaluation of their photonic measurement statistics without dealin

Ian Runnels

We show that given a collection $X=\{f_1$, \ldots , $f_m\}$ of pure mapping classes on a surface $S$, there is an explicit constant N, depending only on $X$, such that their Nth powers $\{f_1^N$, \ldots , $f_m^N\}$ generate the expected right-angled Artin subgroup of MCG($S$). Moreover, we show that these subgroups are undistorted.

Ankush Saxena, Poonam Rani, S. Patnaik, Vipin Nagpal

Here we report successful single crystal growth of new possible magnetic topological insulator (MTI) FeBi2Te4 by self-flux method via vacuum encapsulation process. The detailed Rietveld analysis of Powder XRD data shows the as grown MTI crystal to be mainly dominated by FeBi2Te4 phase along with minority phases of Bi2Te3 and FeTe. Scanning electron microscop

Stéphan Tulkens, Andreas van Cranenburgh

We present a simple but effective method for aspect identification in sentiment analysis. Our unsupervised method only requires word embeddings and a POS tagger, and is therefore straightforward to apply to new domains and languages. We introduce Contrastive Attention (CAt), a novel single-head attention mechanism based on an RBF kernel, which gives a consid

Niall Moroney, Leonardo Del Bino, Michael T. M. Woodley, George N. Ghalanos

Optical logic has the potential to replace electronics with photonic circuits in applications for which optic-to-electronic conversion is impractical and for integrated all-optical circuits. Nonlinear optics in whispering gallery mode resonators provides low power, scalable methods to achieve optical logic. We demonstrate, for the first time, an all-optical,

Zhongyi Han, Benzheng Wei, Yilong Yin, Shuo Li

Automated medical report generation in spine radiology, i.e., given spinal medical images and directly create radiologist-level diagnosis reports to support clinical decision making, is a novel yet fundamental study in the domain of artificial intelligence in healthcare. However, it is incredibly challenging because it is an extremely complicated task that i

Giuseppe Di Benedetto, Vito Bellini, Giovanni Zappella

Contextual bandit algorithms are extremely popular and widely used in recommendation systems to provide online personalised recommendations. A recurrent assumption is the stationarity of the reward function, which is rather unrealistic in most of the real-world applications. In the music recommendation scenario for instance, people's music taste can abruptly

Jayri Bagchi, Tapas Si

Regression analysis is an important machine learning task used for predictive analytic in business, sports analysis, etc. In regression analysis, optimization algorithms play a significant role in search the coefficients in the regression model. In this paper, nonlinear regression analysis using a recently developed meta-heuristic Multi-Verse Optimizer (MVO)

Xilin Zhang, S. R. Stroberg, P. Navrátil, Chan Gwak

A recently modified method to enable low-energy nuclear scattering results to be extracted from the discrete energy levels of the target-projectile clusters confined by harmonic potential traps is tested. We report encouraging results for neutron--$\alpha$ and neutron--$^{24}\mathrm{O}$ elastic scattering from analyzing the trapped levels computed using two

Qingyao Ai, Tao Yang, Huazheng Wang, Jiaxin Mao

How to obtain an unbiased ranking model by learning to rank with biased user feedback is an important research question for IR. Existing work on unbiased learning to rank (ULTR) can be broadly categorized into two groups -- the studies on unbiased learning algorithms with logged data, namely the \textit{offline} unbiased learning, and the studies on unbiased

Emilio Bagan, Janos A. Bergou, Mark Hillery

We present wave-particle duality relations involving the relative entropy coherence measure, which plays a prominent role in the resource theory of coherence. The main input in these relations is an entropic bound for the which-way information, which we derive in this letter. We show that this latter crucially depends on the choice of the measurement strateg

Matthew Kahle, Andrew Newman

A hypertree, or $\mathbb{Q}$-acyclic complex, is a higher-dimensional analogue of a tree. We study random $2$-dimensional hypertrees according to the determinantal measure suggested by Lyons. We are especially interested in their topological and geometric properties. We show that with high probability, a random $2$-dimensional hypertree $T$ is apsherical, i.

Ewan Fong, Sadik L. Omairey, Peter D. Dunning

This paper explores the use of optimization to design multifunctional metamaterials, and proposes a methodology for constructing a design envelope of potential properties. A thermal-mechanical metamaterial, proposed by Ai and Gao (2017), is used as the subject of the study. The properties of the metamaterial are computed using finite element-based periodic h

Juhan Aru, Titus Lupu, Avelio Sepúlveda

Consider CLE$_4$ in the unit disk and let $\ell$ be the loop of the CLE$_4$ surrounding the origin. Schramm, Sheffield and Wilson determined the law of the conformal radius seen from the origin of the domain surrounded by $\ell$. We complement their result by determining the law of the extremal distance between $\ell$ and the boundary of the unit disk. More

Thomas Favale, Francesca Soro, Martino Trevisan, Idilio Drago

The COVID-19 pandemic led to the adoption of severe measures to counteract the spread of the infection. Social distancing and lockdown measures modifies people's habits, while the Internet gains a major role to support remote working, e-teaching, online collaboration, gaming, video streaming, etc. All these sudden changes put unprecedented stress on the netw

Simon N. Wood, Ernst C. Wit, Matteo Fasiolo, Peter J. Green

Knowing the infection fatality ratio (IFR) is of crucial importance for evidence-based epidemic management: for immediate planning; for balancing the life years saved against the life years lost due to the consequences of management; and for evaluating the ethical issues associated with the tacit willingness to pay substantially more for life years lost to t

Wei Liang, Qi-Fang Lü

Inspired by the newly observed $\Lambda_b(6072)$ structure, we investigate its strong decay behaviors under various assignments within the $^3P_0$ model. Compared with the mass and total decay width, our results suggest that the $\Lambda_b(6072)$ can be regarded as the lowest $\rho-$mode excitation in $\Lambda_b$ family. Then, the strong decays of $\rho-$mod

Xin Yang, Xu Wang, Yi Wang, Haoran Dou

Background and Objective: Biometric measurements of fetal head are important indicators for maternal and fetal health monitoring during pregnancy. 3D ultrasound (US) has unique advantages over 2D scan in covering the whole fetal head and may promote the diagnoses. However, automatically segmenting the whole fetal head in US volumes still pends as an emerging

Fabrice Gamboa, Jan Nagel, Alain Rouault

A sum rule is an identity connecting the entropy of a measure with coefficients involved in the construction of its orthogonal polynomials (Jacobi coefficients). Our paper is an extension of Gamboa, Nagel and Rouault (2016), where we have showed sum rules by using only probabilistic tools (namely the large deviations theory). Here, we prove large deviation p

I. Mohelsky, A. Dubroka, J. Wyzula, A. Slobodeniuk

Here we report on Landau level spectroscopy in magnetic fields up to 34 T performed on a thin film of topological insulator Bi$_2$Te$_3$ epitaxially grown on a BaF$_2$ substrate. The observed response is consistent with the picture of a direct-gap semiconductor in which charge carriers closely resemble massive Dirac particles. The fundamental band gap reache

Meryem Benelajla, Elena Kammann, Bernhard Urbaszek, Khaled Karrai

Confocal microscopy is an essential imaging tool for biological systems, in solid-state physics and nano-photonics. Using confocal microscopes allows performing resonant fluorescence experiments, where the emitted light has the same wavelength as the excitation laser. Theses challenging experiments are carried out under linear cross-polarization conditions,

K. Makki, B. Borotikar, M. Garetier, S. Brochard

The log Euclidean polyrigid registration framework provides a way to smoothly estimate and interpolate poly-rigid/affine transformations for which the invertibility is guaranteed. This powerful and flexible mathematical framework is currently being used to track the human joint dynamics by first imposing bone rigidity constraints in order to synthetize the s

Eduard I. Vorobyov, Ryoki Matsukoba, Kazuyuki Omukai, Manuel Guedel

Aims: We explore the long-term evolution of young protoplanetary disks with different approaches to computing the thermal structure determined by various cooling and heating processes in the disk and its surroundings. Methods: Numerical hydrodynamics simulations in the thin-disk limit were complemented with three thermal evolution schemes: a simplified $\bet

Jonathan Donier

A recent study of skipping behaviour on music streaming platforms has shown that the skip profile for a given song -- i.e. the measure of the skipping rate as a function of the time in the song -- can be seen as some intrinsic characteristic of the song, in the sense that it is both very specific and highly stable over time and geographical regions. In this

Neslihan Suzen, Evgeny M. Mirkes, Alexander N. Gorban

In Natural Language Processing, automatic extracting the meaning of texts constitutes an important problem. Our focus is the computational analysis of meaning of short scientific texts (abstracts or brief reports). In this paper, a vector space model is developed for quantifying the meaning of words and texts. We introduce the Meaning Space, in which the mea

Sushovan Mondal, Saif Ali, Shanima S, Narayan Banerjee

The present work investigates some exact solutions of the gravitational wave equation in some widely used cosmological spacetimes. The examples are taken from spatially flat and closed isotropic models as well as Kasner metric which is anisotropic. Various matter distributions are considered, from the standard dust or radiation distribution to exotic matters

D. J. Yu, V. M. Nakariakov

Negative energy wave phenomena may appear in shear flows in the presence of a wave decay mechanism and external energy supply. We study the appearance of negative energy surface waves in a plasma cylinder in the incompressible limit. The cylinder is surrounded by an axial magnetic field and by a plasma of different density. Considering flow inside and viscos

Sierk E. van Terwisga, Ewine F. van Dishoeck, Rita K. Mann, James Di Francesco

Protoplanetary disks in dense, massive star-forming regions are strongly affected by their environment. How this environmental impact changes over time is an important constraint on disk evolution and external photoevaporation models. We characterize the dust emission from 179 disks in the core of the young (0.5 Myr) NGC 2024 cluster. By studying how the dis

Durgesh Samariya, Sunil Aryal, Kai Ming Ting

Outlying Aspect Mining (OAM) aims to find the subspaces (a.k.a. aspects) in which a given query is an outlier with respect to a given dataset. Existing OAM algorithms use traditional distance/density-based outlier scores to rank subspaces. Because these distance/density-based scores depend on the dimensionality of subspaces, they cannot be compared directly

Michael F. Herbst, Antoine Levitt, Eric Cancès

We address the problem of bounding rigorously the errors in the numerical solution of the Kohn-Sham equations due to (i) the finiteness of the basis set, (ii) the convergence thresholds in iterative procedures, (iii) the propagation of rounding errors in floating-point arithmetic. In this contribution, we compute fully-guaranteed bounds on the solution of th

J. Schou, A. C. Birch

As the amount of asteroseismic data available continues to grow, the inability to accurately model observed oscillation frequencies is becoming a critical problem for interpreting these frequencies. A major component of this problem is the modeling of the near-surface layers. Our aim is to develop a method to estimate the effect of the near-surface layers on

Satya N. Majumdar, Baruch Meerson

We study the position distribution of a single active Brownian particle (ABP) on the plane. We show that this distribution has a compact support, the boundary of which is an expanding circle. We focus on a short-time regime and employ the optimal fluctuation method (OFM) to study large deviations of the particle position coordinates $x$ and $y$. We determine

Lubomir Kovachev

For a long time transverse and longitudinal optical forces are used for non-contact and noninvasive manipulation of small individual particles. The following question arises: What is the impact of these forces on the ensemble of thousand particles in continuous media? The aim of this work is to find analytical expression of the radiation force and potential