April 2020 arXiv papers — page 27

Sergei V. Kalinin, Maxim Ziatdinov, Rama K. Vasudevan

Advances in predictive modeling across multiple disciplines have yielded generative models capable of high veracity in predicting macroscopic functional responses of materials. Correspondingly, of interest is the inverse problem of finding the model parameter that will yield desired macroscopic responses, such as stress-strain curves, ferroelectric hysteresi

Mohammad Motamed

Sinkhorn divergence is a measure of dissimilarity between two probability measures. It is obtained through adding an entropic regularization term to Kantorovich's optimal transport problem and can hence be viewed as an entropically regularized Wasserstein distance. Given two discrete probability vectors in the $n$-simplex and supported on two bounded spaces

Clarissa Z. Cooley, Patrick C. McDaniel, Jason P. Stockmann, Sai Abitha Srinivas

Access to and availability of MRI scanners is typically limited by their cost, siting and infrastructure requirements. This precludes MRI diagnostics, the reference standard for neurological assessment, in patients who cannot be transported to specialized scanner suites. This includes patients who are critically ill and unstable, and patients located in low-

Jan-Niklas Voigt-Antons, Tanja Kojić, Danish Ali, Sebastian Möller

With the rising interest in Virtual Reality and the fast development and improvement of available devices, new features of interactions are becoming available. One of them that is becoming very popular is hand tracking, as the idea to replace controllers for interactions in virtual worlds. This experiment aims to compare different interaction types in VR usi

Alpha Mastrano, Kai E. Yang, Michael S. Wheatland

Vector magnetogram data are often used as photospheric boundary conditions for force-free coronal magnetic field extrapolations. In general, however, vector magnetogram data are not consistent with the force-free assumption. In this article, we demonstrate a way to deal with inconsistent boundary data, by generalizing the "self-consistency procedure" of Whea

Andrew J. Steffl, Leslie A. Young, Darrell F. Strobel, Joshua A. Kammer

During the New Horizons spacecraft's encounter with Pluto, the Alice ultraviolet spectrograph conducted a series of observations that detected emissions from both the interplanetary medium (IPM) and Pluto. In the direction of Pluto, the IPM was found to be 133.4$\pm$0.6R at Lyman $\alpha$, 0.24$\pm$0.02R at Lyman $\beta$, and <0.10R at He I 584{\AA}. We anal

Marco Cuturi, Olivier Teboul, Quentin Berthet, Arnaud Doucet

When the infection prevalence of a disease is low, Dorfman showed 80 years ago that testing groups of people can prove more efficient than testing people individually. Our goal in this paper is to propose new group testing algorithms that can operate in a noisy setting (tests can be mistaken) to decide adaptively (looking at past results) which groups to tes

Kaibo Hu, Qian Zhang, Zhimin Zhang

We construct smooth finite element de Rham complexes in two space dimensions. This leads to three families of curl-curl conforming finite elements, two of which contain two existing families. The simplest triangular and rectangular finite elements have only 6 and 8 degrees of freedom, respectively. Numerical experiments for each family demonstrate the conver

Wei-Jen Ko, Junyi Jessy Li

Recent advances in NLP have been attributed to the emergence of large-scale pre-trained language models. GPT-2, in particular, is suited for generation tasks given its left-to-right language modeling objective, yet the linguistic quality of its generated text has largely remain unexplored. Our work takes a step in understanding GPT-2's outputs in terms of di

Giorgio Laguzzi, Ram Sewak Dubey

We study the topological and set-theoretical nature of Paretian social welfare relations in a setting with infinite time horizon. Specifically, we answer questions posed in \citet{mathias2020} about the interplay between total welfare relations satisfying Pareto and anonymity principles with subsets of real numbers not satisfying the Baire property.

Mostaan Lotfalian Saremi, Razieh Saremi, Denisse Martinez-Mejorado

It is reported that task monetary prize is one of the most important motivating factors to attract crowd workers. While using expert-based methods to price Crowdsourcing tasks is a common practice, the challenge of validating the associated prices across different tasks is a constant issue. To address this issue, three different classifications of multiple l

Arturo Sanchez-Lorenzo, Javier Vaquero-Martínez, Josep Calbó, Martin Wild

The current pandemic caused by the coronavirus SARS-CoV-2 is having negative health, social and economic consequences worldwide. In Europe, the pandemic started to develop strongly at the end of February and beginning of March 2020. It has subsequently spread over the continent, with special virulence in northern Italy and inland Spain. In this study we show

Paulo Almeida, Manuel Marques-Pita, Joana Gonçalves-Sá

In a representative democracy, some decide in the name of the rest, and these elected officials are commonly gathered in public assemblies, such as parliaments, where they discuss policies, legislate, and vote on fundamental initiatives. A core aspect of such democratic processes are the plenary debates, where important public discussions take place. Many pa

Razieh Saremi, Mostaan Lotfalian Saremi, Prasad Desai, Robert Anzalone

Existed studies have shown that crowd workers are more interested in taking similar tasks in terms of context, field, and required technology, rather than tasks from the same project. Therefore, it is important for task owners to not only be able to plan 'when the new task should arrive?' but also, to justify 'what the strategic task arrival plan should be?'

Chandra Mouli Madhav Kotteti, Xishuang Dong, Lijun Qian

Social media is a popular platform for timely information sharing. One of the important challenges for social media platforms like Twitter is whether to trust news shared on them when there is no systematic news verification process. On the other hand, timely detection of rumors is a non-trivial task, given the fast-paced social media environment. In this wo

Valentin D. Ivanov, Jean-Louis Lizon

Observing at the VLT Coude focus can boost the collecting area by combining light from multiple VLT unit telescopes (UTs; albeit with some losses in the light train). An instrument at the Coude enjoys significant operational flexibility advantage: it can be attached to any available UT and the "extra" instrument can help to match better the observing constra

Haiyan Wang, Xuejian Rong, Liang Yang, Jinglun Feng

The deficiency of 3D segmentation labels is one of the main obstacles to effective point cloud segmentation, especially for scenes in the wild with varieties of different objects. To alleviate this issue, we propose a novel deep graph convolutional network-based framework for large-scale semantic scene segmentation in point clouds with sole 2D supervision. D

Dan Reznik, Ronaldo Garcia, Jair Koiller

We introduce several-dozen experimentally-found invariants of Poncelet N-periodics in the confocal ellipse pair (Elliptic Billiard). Recall this family is fully defined by two integrals of motion (linear and angular momentum), so any "new" invariants are dependent upon them. Nevertheless, proving them may require sophisticated methods. We reference some two-

Xi Chen, Rajesh Jayaram, Amit Levi, Erik Waingarten

We study the problems of learning and testing junta distributions on $\{-1,1\}^n$ with respect to the uniform distribution, where a distribution $p$ is a $k$-junta if its probability mass function $p(x)$ depends on a subset of at most $k$ variables. The main contribution is an algorithm for finding relevant coordinates in a $k$-junta distribution with subcub

C. -L. Ho

It is pointed out that, for the fractional Fokker-Planck equation for subdiffusion proposed by Metzler, Barkai, and Klafter [Phys. Rev. Lett. 82 (1999) 3563], there are four types of infinitely many exact solutions associated with the newly discovered exceptional orthogonal polynomials. They represent fractionally deformed versions of the Rayleigh process an

Ilshat Gibadullin, Aidar Valeev

In this paper, we experiment with Large Vocabulary Trick and Feature-rich encoding applied to the Transformer model for Text Summarization. We could not achieve better results, than the analogous RNN-based sequence-to-sequence model, so we tried more models to find out, what improves the results and what deteriorates them.

Li-ya Xu, Bin Liao, Hao Zhang, Peng Xiao

In the ocean environment, reverberation is a common and strong interference which significantly degrades the performance of target bearing estimation. Meanwhile, sensor failure is inevitable in actual sonar deployment as the underwater scene is complicated. Therefore, it is a challenge for target detection in the ocean reverberation with sensor failure. To a

S. I. Kruglov

A new model of nonlinear electrodynamics with dimensional parameters $\beta$ and $\gamma$ is proposed. The principles of causality and unitarity are studied. We show that a singularity of the electric field at the origin of charges is absent and the maximum of the electric field in the center is $E(0)=1/\sqrt{\beta}$. The dual symmetry is broken in our model

A. Philip Dawid

We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic statistical causality (DT), which is a straightforward way of representing and addressing causal questions. DT reframes causal inference as "assisted decision-making", and aims to understand when, and how, I can make use of external data, typically observational,

Kang Liu, Benjamin Tan, Gaurav Rajavendra Reddy, Siddharth Garg

Deep learning (DL) offers potential improvements throughout the CAD tool-flow, one promising application being lithographic hotspot detection. However, DL techniques have been shown to be especially vulnerable to inference and training time adversarial attacks. Recent work has demonstrated that a small fraction of malicious physical designers can stealthily

R. Vila, L. Ferreira, H. Saulo, F. Prataviera

In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regressio

Lynnelle Ye

We generalize bounds of Liu-Wan-Xiao for slopes in eigencurves for definite unitary groups of rank $2$ to slopes in eigenvarieties for definite unitary groups of any rank. We show that for a definite unitary group of rank $n$, the Newton polygon of the characteristic power series of the $U_p$ Hecke operator has exact growth rate $x^{1+\frac2{n(n-1)}}$, times

David Holtz, Ruben Lobel, Inessa Liskovich, Sinan Aral

Online marketplace designers frequently run A/B tests to measure the impact of proposed product changes. However, given that marketplaces are inherently connected, total average treatment effect estimates obtained through Bernoulli randomized experiments are often biased due to violations of the stable unit treatment value assumption. This can be particularl

Daniel Bakkelund

Partial orders and directed acyclic graphs are commonly recurring data structures that arise naturally in numerous domains and applications and are used to represent ordered relations between entities in the domains. Examples are task dependencies in a project plan, transaction order in distributed ledgers and execution sequences of tasks in computer program

Delyan Z. Kalchev, Thomas A. Manteuffel, Steffen Münzenmaier

In this paper, a few dual least-squares finite element methods and their application to scalar linear hyperbolic problems are studied. The purpose is to obtain $L^2$-norm approximations on finite element spaces of the exact solutions to hyperbolic partial differential equations of interest. This is approached by approximating the generally infeasible quadrat

Luca Fabbri, Rodolfo José Bueno Rogerio

In this paper, we perform the polar analysis of the spinorial fields, starting from the regular cases and up to the singular cases: we will give for the first time the polar form of the spinorial field equations for the singular cases constituted by the flag-dipole spinor fields. Comments on the role of further spinor sub-classes containing Majorana and Weyl

K. L. Chong, R. Yang, Q. Wang, R. Verzicco

In the preparation of Caf\'e Latte, spectacular layer formation can occur between the expresso shot in a glass of milk and the milk itself. Xue et al. (Nat. Commun., vol. 8, 2017, pp. 1-6) showed that the injection velocity of expresso determines the depth of coffee-milk mixture. After a while when a stable stratification forms in the mixture, the layering p

Xiu Ye, Shangyou Zhang

The weak Galerkin (WG) finite element method is an effective and flexible general numerical technique for solving partial differential equations. It is a natural extension of the classic conforming finite element method for discontinuous approximations, which maintains simple finite element formulation. Stabilizer free weak Galerkin methods further simplify

Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak

Over the last decade, there has been significant progress in the field of machine learning for de novo drug design, particularly in deep generative models. However, current generative approaches exhibit a significant challenge as they do not ensure that the proposed molecular structures can be feasibly synthesized nor do they provide the synthesis routes of

Sheng-Chun Yang, Bin Li, You-Liang Zhu, Aatto Laaksonen

Computer simulations of model systems are widely used to explore striking phenomena in promising applications spanning from physics, chemistry, biology, to materials science and engineering. The long range electrostatic interactions between charged particles constitute a prominent factor in determining structures and states of model systems. How to efficient

Xiu Ye, Shangyou Zhang

The weak Galerkin (WG) finite element method is an effective and flexible general numerical technique for solving partial differential equations. The novel idea of weak Galerkin finite element methods is on the use of weak functions and their weak derivatives defined as distributions. Weak functions and weak derivatives can be approximated by polynomials wit

Christoffer Riis, Damian Konrad Kowalczyk, Lars Kai Hansen

Our global population contributes visual content on platforms like Instagram, attempting to express themselves and engage their audiences, at an unprecedented and increasing rate. In this paper, we revisit the popularity prediction on Instagram. We present a robust, efficient, and explainable baseline for population-based popularity prediction, achieving str

Andrew Wood, Ali Sydney, Peter Chin, Bishal Thapa

Over the past decades, progress in deployable autonomous flight systems has slowly stagnated. This is reflected in today's production air-crafts, where pilots only enable simple physics-based systems such as autopilot for takeoff, landing, navigation, and terrain/traffic avoidance. Evidently, autonomy has not gained the trust of the community where higher pr

Najma Mathema, Michael A. Goodrich, Jacob W. Crandall

Artificial intelligence (AI) agents will need to interact with both other AI agents and humans. Creating models of associates help to predict the modeled agents' actions, plans, and intentions. This work introduces algorithms that predict actions, plans and intentions in repeated play games, with providing an exploration of algorithms. We form a generative B

Vadim N. Biktashev, Ian Melbourne

It is known that quasiperiodic hypermeander of spiral waves almost certainly produces a bounded trajectory for the spiral tip. We analyse the size of this trajectory. We show that this deterministic question does not have a physically sensible deterministic answer and requires probabilistic treatment. In probabilistic terms, the size of the hypermeander traj

Edward J. Hu, Adith Swaminathan, Hadi Salman, Greg Yang

Robustness against image perturbations bounded by a $\ell_p$ ball have been well-studied in recent literature. Perturbations in the real-world, however, rarely exhibit the pixel independence that $\ell_p$ threat models assume. A recently proposed Wasserstein distance-bounded threat model is a promising alternative that limits the perturbation to pixel mass m

José Carlos Olvera

The absorption section of black holes surrounded by scalar fields is studied with the sinc approximation in the eikonal limit. The effects of the scalar field on the nonlinear Euler-Heisenberg, the magnetic Bardeen and Reissner-Nordstrom BHs are studied in order to obtain information about how the scalar field affects different BHs.

Karim Benakli, Carlo Branchina, Gaëtan Lafforgue-Marmet

We revisit the Scalar Weak Gravity Conjecture and investigate the possibility to impose that scalar interactions dominate over gravitational ones. More precisely, we look for consequences of assuming that, for leading scalar interactions, the corresponding gravitational contribution is sub-dominant in the non-relativistic limit. For a single massive scalar p

J. Chouqar, Z. Benkhaldoun, A. Jabiri, J. Lustig-Yaeger

We investigate the potential for the James Webb Space Telescope (JWST) to detect and characterize the atmospheres of the sub-Neptunian exoplanets in the TOI-270 system. Sub-Neptunes are considered more likely to be water worlds than gas dwarfs. We model their atmospheres using three atmospheric compositions - two examples of hydrogen-dominated atmospheres an

Seungmo Kim, Imtiaz Nasim

The fifth-generation wireless (5G) has already started showing its capability to achieve extremely fast data transfer, which makes itself considered to be a promising mobile technology. However, concerns have been raised on adverse health impacts that human users can experience in a 5G system by being exposed to electromagnetic fields (EMFs). This article in

Ruixuan Yan, Agung Julius

In this paper, we develop a distributed monitoring framework for robot swarms so that the agents can monitor whether the executions of robot swarms satisfy Swarm Signal Temporal Logic (SwarmSTL) formulas. We define generalized moments (GMs) to represent swarm features. A dynamic generalized moments consensus algorithm (GMCA) with Kalman filter (KF) is propos

Bing Liu

Biological systems are often modeled as a system of ordinary differential equations (ODEs) with time-invariant parameters. However, cell signaling events or pharmacological interventions may alter the cellular state and induce multi-mode dynamics of the system. Such systems are naturally modeled as hybrid automata, which possess multiple operational modes wi

Bharath H S, Dileep Bonthu, Pavana Prabhakar, Mrityunjay Doddamani

The goal of this paper is to enable 3D printed lightweight composite foams by blending hollow glass micro balloons (GMB) with high density polyethylene (HDPE). To that end, lightweight feedstock for printing syntactic foam composites is developed. The blend for this is prepared by varying GMB content (20, 40, and 60 volume %) in HDPE for filament extrusion,

Alan Anwer Abdulla, Sabah A. Jassim, Harin Sellahewa

This paper is concerned with secret hiding in multiple image bitplanes for increased security without undermining capacity. A secure steganographic algorithm based on bitplanes index manipulation is proposed. The index manipulation is confined to the first two Least Significant Bits of the cover image. The proposed algorithm has the property of un-detectabil

Z. Y. Ou, Xiaoying Li

A new type of quantum entangled interferometer was recently realized that employs parametric amplifiers as the wave splitting and recombination elements. The quantum entanglement stems from the parametric amplifiers, which produce quantum correlated fields for probing the phase change signal in the interferometer. This type of quantum entangled interferomete

Anton Molina, Pranav Vyas, Nikita Khlystov, Shailabh Kumar

The COVID-19 pandemic has caused a global shortage of personal protective equipment. While existing supply chains are struggling to meet the surge in demand, the limited supply of N95 filtering facepiece respirators (FFRs) has placed healthcare workers at risk. This paper presents a method for scalable and distributed manufacturing of FFR filter material bas

Qiqin Xie, Shijie Xie, Xiaofan Yuan, Xingxing Yu

As a natural extension of the Four Color Theorem, Haj\'{o}s conjectured that graphs containing no $K_5$-subdivision are 4-colorable. Any possible counterexample to this conjecture with minimum number of vertices is called a {\it Haj\'{o}s graph}. Previous results show that Haj\'{o}s graphs are 4-connected but not 5-connected. A $k$-separation in a graph $G$

Alan A. Abdulla, Harin Sellahewa, Sabah A. Jassim

An efficient 2-step steganography technique is proposed to enhance stego image quality and secret message un-detectability. The first step is a preprocessing algorithm that reduces the size of secret images without losing information. This results in improved stego image quality compared to other existing image steganography methods. The proposed secret imag

Fan Qin

Dual canonical bases are expected to satisfy a certain (double) triangularity property by Leclerc's conjecture. We propose an analogous conjecture for common triangular bases of quantum cluster algebras. We show that a weaker form of the analogous conjecture is true. Our result applies to the dual canonical bases of quantum unipotent subgroups. It also appli

Mingmou Liu, Yitong Yin, Huacheng Yu

The membership problem asks to maintain a set $S\subseteq[u]$, supporting insertions and membership queries, i.e., testing if a given element is in the set. A data structure that computes exact answers is called a dictionary. When a (small) false positive rate $\epsilon$ is allowed, the data structure is called a filter. The space usages of the standard dict

Nima Anari, Thuy-Duong Vuong

Given a matrix $A$ and $k\geq 0$, we study the problem of finding the $k\times k$ submatrix of $A$ with the maximum determinant in absolute value. This problem is motivated by the question of computing the determinant-based lower bound of [LSV86] on hereditary discrepancy, which was later shown to be an approximate upper bound as well [Mat13]. The special ca

Yuteng Zhu

Previously, a method has been developed to find the best colour filter for a given camera which results in the new effective camera sensitivities that best meet the Luther condition. That is, the new sensitivities are approximately linearly related to the XYZ colour matching functions. However, with no constraint, the filter derived from this Luther-conditio

Muhammad Lawan Jibril, Usman Sani Sharif

Novel coronavirus-19 (2019-nCoV or COVID-19) is by far the most dangerous coronavirus ever identified for the third time in the three decades capable of infecting not only the animals but also the humans across the globe. Nearly 6000 deaths have been recorded due mainly to COVID-19 outbreak worldwide and more than 50% of these deaths appeared to have evolved

L C G Rogers

Social distancing and lockdown are the two main non-pharmaceutical interventions being used by the UK government to contain and control the COVID-19 epidemic; these are being applied uniformly across the entire country, even though the results of the Imperial College report by Ferguson et al show that the impact of the infection increases sharply with age. T

Berna Bulut

This paper presents a reliable and efficient high quality video streaming solution for use in challenging outdoor environments over Wi-Fi. An application layer forward error correction based on RaptorQ codes was implemented in a practical Wi-Fi based server and client system to enhance reliability. Thus, this paper presents the first detailed analysis on the

Kathrin Egberts

Multi-messenger astronomy has experienced an explosive development in the past few years. While not being a particularly young field, it has recently attracted a lot of attention by several major discoveries and unprecedented observation campaigns covering the entity of the electromagnetic spectrum as well as observations of cosmic rays, neutrinos, and gravi

M. Salazar-Ramírez, D. Ojeda-Guillén, R. D. Mota, J. A. Martínez-Nuño

We introduce an $SU(1,1)$ algebraic approach to study the $(2+1)$-Dirac oscillator in the presence of the Aharonov-Casher effect coupled to an external electromagnetic field in the Minkowski spacetime and the cosmic string spacetime. This approach is based on a quantum mechanics factorization method that allows us to obtain the $su(1,1)$ algebra generators,

Ziwen Huang, Pranav S. Mundada, András Gyenis, David I. Schuster

Protecting superconducting qubits from low-frequency noise is essential for advancing superconducting quantum computation. Based on the application of a periodic drive field, we develop a protocol for engineering dynamical sweet spots which reduce the susceptibility of a qubit to low-frequency noise. Using the framework of Floquet theory, we prove rigorously

Gena Hahn, Maurice Pouzet, Robert Woodrow

We show that every countable cograph has either one or infinitely many siblings. This answers, very partially, a conjecture of Thomass\'e. The main tools are the notion of well quasi ordering and the correspondence between cographs and some labelled ordered trees.

Mohamed Shaat

Nonreciprocity has been introduced to various fields to realize asymmetric, nonlinear, and/or time non-revisal physical systems. By virtue of the Maxwell-Betti reciprocal theorem, breaking the time-reversal symmetry of dynamic mechanical systems is only possible using nonlinear materials. Nonetheless, nonlinear materials should be accompanied by geometrical

Begoña Mula, Silvia N. Santalla, Javier Rodríguez-Laguna

We characterize the Casimir forces for the Dirac vacuum on free-fermionic chains with smoothly varying hopping amplitudes, which correspond to (1+1)D curved spacetimes with a static metric in the continuum limit. The first-order energy potential for an obstacle on that lattice corresponds to the Newtonian potential associated to the metric, while the finite-

Víctor González-Aguilera, Alvaro Liendo, Pedro Montero

Let $X$ be a smooth hypersurface of dimension $n\geq 1$ and degree $d\geq 3$ in the projective space given as the zero set of a homogeneous form $F$. If $(n,d)\neq (1,3), (2,4)$ it is well known that every automorphism of $X$ extends to an automorphism of the projective space, i.e., $\operatorname{Aut}(X)\subseteq \operatorname{PGL}(n+2,\mathbb{C})$. We say

Sushanth Kini Manjeshwar, Karim Elkhouly, Jamie M. Fitzgerald, Martin Ekman

We present high-reflectivity mechanical resonators fabricated from AlGaAs heterostructures for use in free-space optical cavities operating in the telecom wavelength regime. The mechanical resonators are fabricated in slabs of GaAs and patterned with a photonic crystal to increase their out-of-plane reflectivity. Characterization of the mechanical modes reve

Alan Eric Akil, Robert Rosenbaum, Krešimir Josić

The dynamics of local cortical networks are irregular, but correlated. Dynamic excitatory--inhibitory balance is a plausible mechanism that generates such irregular activity, but it remains unclear how balance is achieved and maintained in plastic neural networks. In particular, it is not fully understood how plasticity induced changes in the network affect

Sitao Xiang, Yuming Gu, Pengda Xiang, Mingming He

We present a deep learning-based framework for portrait reenactment from a single picture of a target (one-shot) and a video of a driving subject. Existing facial reenactment methods suffer from identity mismatch and produce inconsistent identities when a target and a driving subject are different (cross-subject), especially in one-shot settings. In this wor

Pablo Amster, Julián Epstein, Arturo Sanjuán

Motivated by Lazer-Leach type results, we study the existence of periodic solutions for systems of functional-differential equations at resonance with an arbitrary even-dimensional kernel and linear deviating terms involving a general delay of the form $\int_0^{2\pi}u(t+s)\,d\lambda(s)$, where $\lambda$ is a finite regular signed measure. Our main technique

Piotr Rybak, Alina Wróblewska

This paper describes the ICS PAS system which took part in CoNLL 2018 shared task on Multilingual Parsing from Raw Text to Universal Dependencies. The system consists of jointly trained tagger, lemmatizer, and dependency parser which are based on features extracted by a biLSTM network. The system uses both fully connected and dilated convolutional neural arc

Alexei Kulik, Ilya Pavlyukevich

In this paper we show that if large jumps of an It\^o-semimartingale $X$ have a finite $p$-moment, $p>0$, the radial part of its drift is dominated by $-|X|^\kappa$ for some $\kappa\geq -1$, and the balance condition $p+\kappa>1$ holds true, then under some further natural technical assumptions $\sup_{t\geq 0} \mathbf{E} |X_t|^{p_X}<\infty$ for each $p_X\in(

Andria C. Schwortz, Andrea C. Burrows

Background: Dataset skills are used in STEM fields from healthcare work to astronomy research. Few fields explicitly teach students the skills to analyze datasets, and yet the increasing push for authentic science implies these skills should be taught. Purpose: The overarching motivation is to understand learning of dataset skills within an astronomy context

Ling Qiu, Mahabubul Alam, Abdullah Ash-Saki, Swaroop Ghosh

Variational algorithm using Quantum Approximate Optimization Algorithm (QAOA) can solve the prime factorization problem in near-term noisy quantum computers. Conventional Variational Quantum Factoring (VQF) requires a large number of 2-qubit gates (especially for factoring a large number) resulting in deep circuits. The output quality of the deep quantum cir

Julie Rowlett, Carl-Joar Karlsson

In numerous contexts, individuals may decide whether they take actions to mitigate the spread of disease, or not. Mitigating the spread of disease requires an individual to change their routine behaviours to benefit others, resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma. In the classical prisoner's dilemma, evolutionary game dynam

Anna Mikusheva, Liyang Sun

We develop a concept of weak identification in linear IV models in which the number of instruments can grow at the same rate or slower than the sample size. We propose a jackknifed version of the classical weak identification-robust Anderson-Rubin (AR) test statistic. Large-sample inference based on the jackknifed AR is valid under heteroscedasticity and wea

Shashank Bhatnagar, Eshete Gebrehana

In this work we study the radiative decays of heavy-light quarkonia through M1 and E1 transitions, that involve quark-triangle diagrams with two hadron vertices, and are difficult to evaluate in BSE-CIA. We have expressed the transition amplitude, $M_{fi}$ as a linear superposition of terms involving all possible combinations of $++$, and $--$ components of

Xingjian Li, Haoyi Xiong, Haozhe An, Dejing Dou

Softening labels of training datasets with respect to data representations has been frequently used to improve the training of deep neural networks (DNNs). While such a practice has been studied as a way to leverage privileged information about the distribution of the data, a well-trained learner with soft classification outputs should be first obtained as a

Sourav Das, Samuel Wedaj, Kolin Paul, Umesh Bellur

The proliferation of application specific cyber-physical systems coupled with the emergence of a variety of attacks on such systems (malware such as Mirai and Hajime) underlines the need to secure such networks. Most existing security efforts have focused on only detection of the presence of malware. However given the ability of most attacks to spread throug

J. Dgheim, R. Al Maarawi, M. Abdallah, N. Nasr

Heat and mass transfers of the evaporation of rotating hydrocarbons liquid droplet of ternary components, in forced convection are studied numerically. Comparison between our numerical results and those obtained in the literature shows qualitative and quantitative satisfactory agreements, in rotatory forced convection. Optimal values of the wind and rotation

János Horváth, Daniel Mas Montserrat, Hanxiang Hao, Edward J. Delp

Satellite images are more accessible with the increase of commercial satellites being orbited. These images are used in a wide range of applications including agricultural management, meteorological prediction, damage assessment from natural disasters, and cartography. Image manipulation tools including both manual editing tools and automated techniques can

Qianhui Wu, Zijia Lin, Börje F. Karlsson, Jian-Guang Lou

To better tackle the named entity recognition (NER) problem on languages with little/no labeled data, cross-lingual NER must effectively leverage knowledge learned from source languages with rich labeled data. Previous works on cross-lingual NER are mostly based on label projection with pairwise texts or direct model transfer. However, such methods either ar

James Reeves, Valentina Braito, George Chartas, Fred Hamann

Past X-ray observations of the nearby luminous quasar PDS 456 (at $z=0.184$) have revealed a wide angle accretion disk wind (Nardini et al. 2015), with an outflow velocity of $\sim-0.25c$, as observed through observations of its blue-shifted iron K-shell absorption line profile. Here we present three new XMM-Newton observations of PDS 456; one in September 2

Steven Platt, Miquel Oliver-Riera

Distributed consensus mechanisms have been widely researched and made popular with a number of blockchain-based token applications, such as Bitcoin, and Ethereum. Although these general-purpose platforms have matured for scale and security, they are designed for human incentive and continue to require currency reward and contract functions that are not requi

Yuta Taniguchi

K. Cho and S. Nelson introduced the notion of a quandle coloring quiver, which is a quiver-valued link invariant, and a quandle cocycle quiver which is an enhancement of the quandle coloring quiver by assigning to each vertex a weight computed using a quandle 2-cocycle. In this paper, we study quandle coloring quivers using dihedral quandles and introduce th

Meng Cao, Yuexian Zou

Deep learning-based scene text detection methods have progressed substantially over the past years. However, there remain several problems to be solved. Generally, long curve text instances tend to be fragmented because of the limited receptive field size of CNN. Besides, simple representations using rectangle or quadrangle bounding boxes fall short when dea

Steven Platt, Miquel Oliver-Riera

While direct allocation of spectrum and evolved medium access protocols provide a base for ubiquitous wireless connectivity, the existing TCP/IP and OSI models were designed for wired networks and do not address open interconnection of air interfaces. Without an interconnection model for the air interface, existing network designs continue to tie wireless me

Mirjana Pović

In this paper we summarise the research that is currently going on in Ethiopia and East-Africa in extragalactic astronomy and physics of active galaxies and active galactic nuclei (AGN). The study is focused on some of the still open questions such as: what are the stellar ages and populations of ultra hard X-ray detected AGN and connection between AGN and t

Jingyuan Wang, Xin Lin, Yuxi Liu, Qilegeri

Since December 2019, A novel coronavirus (2019-nCoV) has been breaking out in China, which can cause respiratory diseases and severe pneumonia. Mathematical and empirical models relying on the epidemic situation scale for forecasting disease outbreaks have received increasing attention. Given its successful application in the evaluation of infectious disease

Yukang Chen, Peizhen Zhang, Zeming Li, Yanwei Li

We propose a Dynamic Scale Training paradigm (abbreviated as DST) to mitigate scale variation challenge in object detection. Previous strategies like image pyramid, multi-scale training, and their variants are aiming at preparing scale-invariant data for model optimization. However, the preparation procedure is unaware of the following optimization process t

Katja Biswas, Helmut G. Katzgraber

Disconnectivity graphs are used to visualize the minima and the lowest energy barriers between the minima of complex systems. They give an easy and intuitive understanding of the underlying energy landscape and, as such, are excellent tools for understanding the complexity involved in finding low-lying or global minima of such systems. We have developed a cl

Manolis C. Tsakiris

Despite the popularity of low-rank matrix completion, the majority of its theory has been developed under the assumption of random observation patterns, whereas very little is known about the practically relevant case of non-random patterns. Specifically, a fundamental yet largely open question is to describe patterns that allow for unique or finitely many c

Zeyang Lei, Zekang Li, Jinchao Zhang, Fandong Meng

Recently, variational auto-encoder (VAE) based approaches have made impressive progress on improving the diversity of generated responses. However, these methods usually suffer the cost of decreased relevance accompanied by diversity improvements. In this paper, we propose a novel multimodal response generation framework with exemplar augmentation and curric

Giuseppe Maria Coclite, Helge Holden, Nils Henrik Risebro

In this paper we develop an existence theory for the nonlinear initial-boundary value problem with singular diffusion $\partial_t u = \text{div}(k(x)\nabla G(u))$, $u|_{t=0}=u_0$ with Neumann boundary conditions $k(x)\nabla G(u)\cdot \nu = 0$. Here $x\in B\subset \mathbb{R}^d$, a bounded open set with locally Lipchitz boundary, and with $\nu$ as the unit out

Qian Wang, Toby P. Breckon

Heterogeneous Domain Adaptation (HDA) addresses the transfer learning problems where data from the source and target domains are of different modalities (e.g., texts and images) or feature dimensions (e.g., features extracted with different methods). It is useful for multi-modal data analysis. Traditional domain adaptation algorithms assume that the represen

Victor Ukleev, Yuichi Yamasaki, Oleg Utesov, Kiyou Shibata

The tensile strain is a promising tool for creation and manipulation of magnetic solitonic textures in the chiral helimagnets via tunable control of magnetic anisotropy and Dzyaloshinskii-Moriya interaction. Here, by using the in-situ resonant small-angle x-ray scattering we demonstrate that the skyrmion and chiral soliton lattices can be achieved as metasta

Archana Dixit, Chanchal Chawla, Anirudh Pradhan

In the present work, a new form of the logarithmic shape function is proposed for the linear $f(R,T)$ gravity, $f(R,T)=R+2\lambda T$ where $\lambda$ is an arbitrary coupling constant, in wormhole geometry. The desired logarithmic shape function accomplishes all necessary conditions for traversable and asymptotically flat wormholes. The obtained wormhole solu

Yajun Yang, Hang Zhang, Hong Gao, Qinghua Hu

Smart city has been consider the wave of the future and the route recommendation in networks is a fundamental problem in it. Most existing approaches for the shortest route problem consider that there is only one kind of cost in networks. However, there always are several kinds of cost in networks and users prefer to select an optimal route under the global

Jimmy Devillet, Pierre Mathonet

We study the class of symmetric $n$-ary bands. These are $n$-ary semigroups $(X,F)$ such that $F$ is invariant under the action of permutations and idempotent, i.e., satisfies $F(x,\ldots,x)=x$ for all $x\in X$. We first provide a structure theorem for these symmetric $n$-ary bands that extends the classical (strong) semilattice decomposition of certain clas