April 2020 arXiv papers — page 54

Shuntaro Sakai, Feng-Kun Guo, Bastian Kubis

The isovector and isoscalar $ND$ $s$-wave scattering lengths are extracted by fitting to the LHCb data of the $pD^0$ invariant-mass distribution in the decay $\Lambda_b\rightarrow\pi^-pD^0$, making use of the cusp effect at the $nD^+$ threshold. The analysis is based on a coupled-channel nonrelativistic effective field theory. We find that the real part of t

Debjyoti Basua, Masaru Nakajimaa, A. V. Melnikov, David McColl

A pulsed oscillating power amplifier has been developed for high frequency biasing\cite{kn:deb1} and real time turbulent feedback experiment in STOR-M tokamak. It is capable to provide output peak to peak oscillating voltage of around $\pm60$V and current around 30A within frequency band 1kHz-50kHz without any distortion of any waveform signal. Overall outpu

Yang Sun, Fajie Yuan, Min Yang, Guoao Wei

Sequential recommender systems (SRS) have become the key technology in capturing user's dynamic interests and generating high-quality recommendations. Current state-of-the-art sequential recommender models are typically based on a sandwich-structured deep neural network, where one or more middle (hidden) layers are placed between the input embedding layer an

Théophile Chirac, Jean-Yves Chauleau, Pascal Thibaudeau, Olena Gomonay

NiO is a prototypical antiferromagnet with a characteristic resonance frequency in the THz range. From atomistic spin dynamics simulations that take into account the crystallographic structure of NiO, and in particular a magnetic anisotropy respecting its symmetry, we describe antiferromagnetic switching at THz frequency by a spin transfer torque mechanism.

E. I. Khukhro, P. Shumyatsky

A right Engel sink of an element $g$ of a group $G$ is a set ${\mathscr R}(g)$ such that for every $x\in G$ all sufficiently long commutators $[...[[g,x],x],\dots ,x]$ belong to ${\mathscr R}(g)$. (Thus, $g$ is a right Engel element precisely when we can choose ${\mathscr R}(g)=\{ 1\}$.) It is proved that if every element of a compact (Hausdorff) group $G$ h

Jing Xu, Sai Li, Tao Chen, Zheng-Yuan Xue

Quantum gates, which are the essential building blocks of quantum computers, are very fragile. Thus, to realize robust quantum gates with high fidelity is the ultimate goal of quantum manipulation. Here, we propose a nonadiabatic geometric quantum computation scheme on superconducting circuits to engineer arbitrary quantum gates, which share both the robust

Long Chen, Martin Strauch, Dorit Merhof

Automatic instance segmentation is a problem that occurs in many biomedical applications. State-of-the-art approaches either perform semantic segmentation or refine object bounding boxes obtained from detection methods. Both suffer from crowded objects to varying degrees, merging adjacent objects or suppressing a valid object. In this work, we assign an embe

Liwei Jiang, Dan Li, Qisheng Wang, Shuai Wang

Positive Unlabeled (PU) learning is widely used in many applications, where a binary classifier is trained on the datasets consisting of only positive and unlabeled samples. In this paper, we improve PU learning over state-of-the-art from two aspects. Firstly, existing model evaluation methods for PU learning requires ground truth of unlabeled samples, which

Ricardo Fernández-Blanco, Juan Miguel Morales, Salvador Pineda

This paper focuses on the day-ahead forecasting of the aggregate power of a pool of smart buildings equipped with thermostatically-controlled loads. We first propose the modeling of the aggregate behavior of its power trajectory by using a geometric approach. Specifically, we assume that the aggregate power is a homothet of a prototype building, whose physic

Arianna Dolfi, Duncan A. Forbes, Warrick J. Couch, Anna Ferre-Mateu

Using new and archival data, we study the kinematic properties of the nearest field S0 galaxy, NGC 3115, out to $\sim6.5$ half-light radii ($R_\mathrm{e}$) from its stars (integrated starlight), globular clusters (GCs) and planetary nebulae (PNe). We find evidence of three kinematic regions with an inner transition at $\sim0.2\ R_\mathrm{e}$ from a dispersio

Sohei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto

Federated learning (FL) enables a neural network (NN) to be trained using privacy-sensitive data on mobile devices while retaining all the data on their local storages. However, FL asks the mobile devices to perform heavy communication and computation tasks, i.e., devices are requested to upload and download large-volume NN models and train them. This paper

Hai-Chao Zhang

A matter-coupled scalar field model is presented in obtaining a scalar fifth force when the constraint of the current cosmological constant is satisfied. The interaction potential energy density between the scalar field and matter has a symmetry-breaking form with two potential wells. The cosmological constant is proven to be a value of the scalar-field's se

I. F. Barna, Mátyás László

We investigate a one dimensional flow described with the non-compressible coupled Euler and non-compressible Navier-Stokes equations in Cartesian coordinate systems. We couple the two fluids through the continuity equation where different void fractions can be considered. The well-known self-similar Ansatz was applied and analytic solutions were derived for

Christopher T. Nelson, Rama K. Vasudevan, Xiaohang Zhang, Maxim Ziatdinov

The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the correspond

Nils Reimers, Iryna Gurevych

We present an easy and efficient method to extend existing sentence embedding models to new languages. This allows to create multilingual versions from previously monolingual models. The training is based on the idea that a translated sentence should be mapped to the same location in the vector space as the original sentence. We use the original (monolingual

Reyhaneh Khasseh, Angelo Russomanno, Markus Schmitt, Markus Heyl

By means of the discrete truncated Wigner approximation we study dynamical phase transitions arising in the steady state of transverse-field Ising models after a quantum quench. Starting from a fully polarized ferromagnetic initial condition these transitions separate a phase with nonvanishing magnetization along the ordering direction from a symmetric phase

Bai Zhu, Yuanxin Ye, Chao Yang, Liang Zhou

Co-Registration of aerial imagery and Light Detection and Ranging (LiDAR) data is quilt challenging because the different imaging mechanism causes significant geometric and radiometric distortions between such data. To tackle the problem, this paper proposes an automatic registration method based on structural features and three-dimension (3D) phase correlat

Zuling Chang, Martianus Frederic Ezerman, Adamas Aqsa Fahreza, Qiang Wang

Using greedy algorithms to generate de Bruijn sequences is a classical approach that has produced numerous interesting theoretical results. This paper investigates an algorithm which we call the Generalized Prefer-Opposite (GPO). It includes all prior greedy algorithms, with the exception of the Fleury Algorithm applied on the de Bruijn graph, as specific in

Aleksander Głuszek, Francisco Senna Vieira, Arkadiusz Hudzikowski, Adam Wąż

We report the design and characteristics of a simple and compact mode-locked Er-doped fiber laser and its application to broadband cavity-enhanced spectroscopy. The graphene mode-locked polarization maintaining oscillator is thermally stabilized and equipped with three actuators that control the repetition rate: fast and slow fiber stretchers, and metal-coat

Chaojie Ji, Ruxin Wang, Hongyan Wu

While graph neural networks (GNNs) have shown a great potential in various tasks on graph, the lack of transparency has hindered understanding how GNNs arrived at its predictions. Although few explainers for GNNs are explored, the consideration of local fidelity, indicating how the model behaves around an instance should be predicted, is neglected. In this p

Fahreddin Abdullayev, Stanislav Chaichenko, Andrii Shidlich

In Musilak-Orlicz type spaces ${\mathcal S}_{\bf M}$, direct and inverse approximation theorems are obtained in terms of the best approximations of functions and generalized moduli of smoothness. The question of the exact constants in Jackson-type inequalities is studied.

Florian Bridoux, Maximilien Gadouleau, Guillaume Theyssier

Automata networks are mappings of the form f : Q Z $\rightarrow$ Q Z , where Q is a finite alphabet and Z is a set of entities; they generalise Cellular Automata and Boolean networks. An update schedule dictates when each entity updates its state according to its local function fi : Q Z $\rightarrow$ Q. One major question is to study the behaviour of a given

Hongjun Choi, Anirudh Som, Pavan Turaga

Deep-learning architectures for classification problems involve the cross-entropy loss sometimes assisted with auxiliary loss functions like center loss, contrastive loss and triplet loss. These auxiliary loss functions facilitate better discrimination between the different classes of interest. However, recent studies hint at the fact that these loss functio

Yiming Liu, Erwu Liu, Rui Wang

Recently, as explosive growth of mobile data traffic, the performance of wireless communication systems requires to be enhanced significantly in future. Intelligent reflecting surface (IRS) can be used as a promising way to improve the energy efficiency of wireless communications with less complexity and hardware cost. Most existing studies consider the case

Arpan Mangal, Surya Kalia, Harish Rajgopal, Krithika Rangarajan

The exponential increase in COVID-19 patients is overwhelming healthcare systems across the world. With limited testing kits, it is impossible for every patient with respiratory illness to be tested using conventional techniques (RT-PCR). The tests also have long turn-around time, and limited sensitivity. Detecting possible COVID-19 infections on Chest X-Ray

Qi Li, Hanlin Mo, Jinghan Zhao, Hongxiang Hao

The dynamics of human skeletons have significant information for the task of action recognition. The similarity between trajectories of corresponding joints is an indicating feature of the same action, while this similarity may subject to some distortions that can be modeled as the combination of spatial and temporal affine transformations. In this work, we

Benjamin Besga, Alfred Bovon, Artyom Petrosyan, Satya N. Majumdar

We study experimentally and theoretically the optimal mean time needed by a free diffusing Brownian particle to reach a target at a distance L from an initial position in the presence of resetting. Both the initial position and the resetting position are Gaussian distributed with width $\sigma$. We derived and tested two resetting protocols, one with a perio

Filip Chudy, Paweł Woźny

Dual Bernstein polynomials find many applications in approximation theory, computational mathematics, numerical analysis and computer-aided geometric design. In this context, one of the main problems is fast and accurate evaluation both of these polynomials and their linear combinations. New simple recurrence relations of low order satisfied by dual Bernstei

Shizhe Diao, Yan Song, Tong Zhang

Keyphrase generation aims to produce a set of phrases summarizing the essentials of a given document. Conventional methods normally apply an encoder-decoder architecture to generate the output keyphrases for an input document, where they are designed to focus on each current document so they inevitably omit crucial corpus-level information carried by other s

Giuliano Giacalone, Fernando G. Gardim, Jacquelyn Noronha-Hostler, Jean-Yves Ollitrault

We propose the skewness of mean transverse momentum, $\langle p_t \rangle$, fluctuations as a fine probe of hydrodynamic behavior in relativistic nuclear collisions. We describe how the skewness of the $\langle p_t \rangle$ distribution can be analyzed experimentally, and we use hydrodynamic simulations to predict its value. We predict in particular that $\l

Alexandre Dély, Adrien Merlini, Simon B. Adrian, Francesco P. Andriulli

Fast and accurate resolution of electromagnetic problems via the \ac{BEM} is oftentimes challenged by conditioning issues occurring in three distinct regimes: (i) when the frequency decreases and the discretization density remains constant, (ii) when the frequency is kept constant while the discretization is refined and (iii) when the frequency increases alo

Emese Kővári, Bálint Érdi

In the studied axisymmetric case of the central four-body problem, the axis of symmetry is defined by two unequal-mass bodies, while the other two bodies are situated symmetrically with respect to this axis and have equal masses. Here, we consider a special case of the problem and assume that three of the masses are equal. Using a recently found analytical s

Long Chen, Martin Strauch, Matthias Daub, Xiaochen Jiang

Plant parasitic nematodes cause damage to crop plants on a global scale. Robust detection on image data is a prerequisite for monitoring such nematodes, as well as for many biological studies involving the nematode C. elegans, a common model organism. Here, we propose a framework for detecting worm-shaped objects in microscopic images that is based on convol

Sabine Bögli, František Štampach

We study to what extent Lieb--Thirring inequalities are extendable from self-adjoint to general (possibly non-self-adjoint) Jacobi and Schr\"{o}dinger operators. Namely, we prove the conjecture of Hansmann and Katriel from [Complex Anal. Oper. Theory 5, No. 1 (2011), 197-218] and answer another open question raised therein. The results are obtained by means

Lidia Aceto, Paolo Novati

In this paper we consider some rational approximations to the fractional powers of self-adjoint positive operators, arising from the Gauss-Laguerre rules. We derive practical error estimates that can be used to select a priori the number of Laguerre points necessary to achieve a given accuracy. We also present some numerical experiments to show the effective

Akira Koyama, David A. Nicholson, Marat Andreev, Gregory C. Rutledge

The Wiener-Khinchin theorem for the Fourier-Laplace transformation (WKT-FLT) provides a robust method to calculate numerically single-side Fourier transforms of arbitrary autocorrelation functions from molecular simulations. However, the existing WKT-FLT equation produces two artifacts in the output of the frequency-domain relaxation function. In addition, t

Chunheng Jiang, Jianxi Gao, Malik Magdon-Ismail

Inferring topological characteristics of complex networks from observed data is critical to understand the dynamical behavior of networked systems, ranging from the Internet and the World Wide Web to biological networks and social networks. Prior studies usually focus on the structure-based estimation to infer network sizes, degree distributions, average deg

Michel Mollard

The Fibonacci cube of dimension n, denoted as $\Gamma$ n , is the subgraph of the n-cube 5 Q n induced by vertices with no consecutive 1's. Ashrafi and his co-authors proved the non-existence of perfect codes in $\Gamma$ n for n $\ge$ 4. As an open problem the authors suggest to consider the existence of perfect codes in generalizations of Fibonacci cubes. T

Young-Jin Park, Han-Lim Choi

With the advent of NASA's lunar reconnaissance orbiter (LRO), a large amount of high-resolution digital elevation maps (DEMs) have been constructed by using narrow-angle cameras (NACs) to characterize the Moon's surface. However, NAC DEMs commonly contain no-data gaps (voids), which makes the map less reliable. To resolve the issue, this paper provides a dee

M. Ahsan Zeb, Peter G. Kirton, Jonathan Keeling

We study how polariton condensation modifies charge transport in organic materials. In typical organic materials, charge transport proceeds via incoherent hopping. We therefore provide an approach to determine how the rate and final state of this hopping process is affected by strong matter-light coupling and polariton condensation. We show how the hopping p

Suhail Paliath, Mohammad Abu Qbeitah, Monther Aldwairi

Phishing emails are the first step for many of today's attacks. They come with a simple hyperlink, request for action or a full replica of an existing service or website. The goal is generally to trick the user to voluntarily give away his sensitive information such as login credentials. Many approaches and applications have been proposed and developed to ca

Jinyoung Kim, Remi Patriat, Jordan Kaplan, Oren Solomon

Deep cerebellar nuclei are a key structure of the cerebellum that are involved in processing motor and sensory information. It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of the cerebellum system and its utility in deep brain stimulation treatment. However, it is challenging to clearly visualize such small nuclei

Shao-xiong Wu, Chang-shui Yu

The classical version of Mandelstam-Tamm speed limit based on the Wigner function in phase space is reported by B. Shanahan et al. [Phys. Rev. Lett. 120, 070401 (2018)]. In this paper, the Margolus-Levitin speed limit across the quantum-to-classical transition is given in phase space based on the trace distance. The Margolus-Levitin speed limit is set by the

Miikka Kuutila, Mika Mäntylä, Maëlick Claes

Recent works have proposed that software developers' positive emotion has a positive impact on software developers' productivity. In this paper we investigate two data sources: developers chat messages (from Slack and Hipchat) and source code commits of a single co-located Agile team over 200 working days. Our regression analysis shows that the number of cha

Marilena Mierla, Jan Janssens, Elke D'Huys, Laurence Wauters

We use The Sun Watcher with Active Pixel System detector and Image Processing (SWAP) imager onboard the Project for Onboard Autonomy 2 (PROBA2) mission to study the evolution of large-scale EUV structures in the solar corona observed throughout Solar Cycle 24 (from 2010 to 2019). We discuss the evolution of the on-disk coronal features and at different heigh

Paul Dütting, Thomas Kesselheim, Brendan Lucier

Prophet inequalities compare the expected performance of an online algorithm for a stochastic optimization problem to the expected optimal solution in hindsight. They are a major alternative to classic worst-case competitive analysis, of particular importance in the design and analysis of simple (posted-price) incentive compatible mechanisms with provable ap

Juan Chen, Zhiwen Xiao, Huanlai Xing, Penglin Dai

Dynamic routing in software-defined networking (SDN) can be viewed as a centralized decision-making problem. Most of the existing deep reinforcement learning (DRL) agents can address it, thanks to the deep neural network (DNN)incorporated. However, fully-connected feed-forward neural network (FFNN) is usually adopted, where spatial correlation and temporal v

. A. F. M. ter Elst, El Maati Ouhabaz

Let $\Omega$ be a bounded domain in R d with Lipschitz boundary $\Gamma$. We define the Dirichlet-to-Neumann operator N on L 2 ($\Gamma$) associated with a second order elliptic operator A = -- d k,j=1 $\partial$ k (c kl $\partial$ l) + d k=1 b k $\partial$ k -- $\partial$ k (c k $\times$) + a 0. We prove a criterion for invariance of a closed convex set und

Pierre-Etienne Druet

After the pioneering work by Giovangigli on mathematics of multicomponent flows, several attempts were made to introduce global weak solutions for the PDEs describing the dynamics of fluid mixtures. While the incompressible case with constant density was enlighted well enough due to results by Chen and J\"ungel (isothermal case), or Marion and Temam, some op

Shaofeng Deng, Shuyang Ling, Thomas Strohmer

Spectral clustering has become one of the most popular algorithms in data clustering and community detection. We study the performance of classical two-step spectral clustering via the graph Laplacian to learn the stochastic block model. Our aim is to answer the following question: when is spectral clustering via the graph Laplacian able to achieve strong co

Tian-Wei Wu, Ming-Zhu Liu, Li-Sheng Geng, Emiko Hiyama

Both unitary chiral theories and lattice QCD simulations show that the $DK$ interaction is attractive and can form a bound state, namely, $D^*_{s0}(2317)$. Assuming the validity of the heavy antiquark-diquark symmetry (HADS), the $\Xi_{cc}\bar{K}$ interaction is the same as the $DK$ interaction, which implies the existence of a $\Xi_{cc}\bar{K}$ bound state

Anquan Liu, Tao Li, Yu Gu, Haohui Dai

We study platoon control of vehicles with linear third-order longitudinal dynamics under the constant time headway policy. The controller of each follower vehicle is only based on its own velocity, acceleration, inter-vehicle distance and velocity difference with respect to its immediate predecessor, which are all obtained by on-board sensors. We develop dis

Bruno Courcelle

We construct a monadic second-order sentence that characterizes the ternary relations that are the betweenness relations of finite or infinite partial orders. We prove that no first-order sentence can do that. We characterize the partial orders that can be reconstructed from their betweenness relations. We propose a polynomial time algorithm that tests if a

Moritz Einfalt, Rainer Lienhart

In this paper we address the problem of motion event detection in athlete recordings from individual sports. In contrast to recent end-to-end approaches, we propose to use 2D human pose sequences as an intermediate representation that decouples human motion from the raw video information. Combined with domain-adapted athlete tracking, we describe two approac

Pengbo Xu, Tian Zhou, Ralf Metzler, Weihua Deng

L\'evy walks (LWs) are spatiotemporally coupled random-walk processes describing superdiffusive heat conduction in solids, propagation of light in disordered optical materials, motion of molecular motors in living cells, or motion of animals, humans, robots, and viruses. We here investigate a key feature of LWs, their response to an external harmonic potenti

T. A. Kustitskaya, A. A. Kytmanov, M. V. Noskov

The present article is focused on the problem of prediction of student failures with the purpose of their possible prevention by timely introducing supportive measures. We propose a concept for building a predictive model based on Bayesian networks for an academic course or module taught in a blended learning format. Our empirical studies confirm that the pr

Gerd Röpke

The composition of hot and dense nuclear matter is calculated including the $1p$-shell nuclei $4 \le A \le 16$. In-medium shifts, in particular Pauli blocking, are determined by the intrinsic wave function of the nuclei. Results are given within a shell-model approach for the nucleon wave function. Light nuclei are not always well described by the shell mode

Nissim Fraija, Edilberto Aguilar-Ruiz, Antonio Galván-Gámez

The detection of a long flaring activity from blazar TXS 0506+056 in temporal and spatial coincidence with the energetic neutrino IceCube-170922A provided evidence about the photo-hadronic interactions in this source. However, analysis of the archival neutrino and multi-wavelength data from the direction of this blazar between September 2014 and March 2015 r

Lorenzo Spina, Thomas Nordlander, Andrew R. Casey, Megan Bedell

Magnetic fields and stellar spots can alter the equivalent widths of absorption lines in stellar spectra, varying during the activity cycle. This also influences the information that we derive through spectroscopic analysis. In this study we analyse high-resolution spectra of 211 Sun-like stars observed at different phases of their activity cycles, in order

Yeonwoo Rho, Yun Liu, Hie Joo Ahn

This paper proposes a new linearized mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The linearized MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We show that the proposed clustering algorithm successfully recovers true m

Junshu Tang, Zhiwen Shao, Lizhuang Ma

Fine-grained facial expression manipulation is a challenging problem, as fine-grained expression details are difficult to be captured. Most existing expression manipulation methods resort to discrete expression labels, which mainly edit global expressions and ignore the manipulation of fine details. To tackle this limitation, we propose an end-to-end express

Stefan Schwabe, Robert Niemann, Anja Backen, Daniel Wolf

Martensitic materials show a complex, hierarchical microstructure containing structural domains separated by various types of twin boundaries. Several concepts exist to describe this microstructure on each length scale, however, there is no comprehensive approach bridging the whole range from the nano- up to the macroscopic scale. Here, we describe for a Ni-

M. Yoneda, M. Niwa, M. Motohashi

The duality between coherent quantum phase slip and Josephson junction in nanosheets was investigated using the dual Hamiltonian method. This is equivalent to the duality between superconductivity and superinsulator in the 2 + 1 dimension at zero temperature. This method proved to be reliable within the Villain approximation. The possibility of the dual Ginz

Leigh S. Martin

The standard quantum formalism introduced at the undergraduate level treats measurement as an instantaneous collapse. In reality however, no physical process can occur over a truly infinitesimal time interval. A more subtle investigation of open quantum systems lead to the theory of continuous measurement and quantum trajectories, in which wave function coll

Dave Platt, Tim Trudgian

We verify numerically, in a rigorous way using interval arithmetic, that the Riemann hypothesis is true up to height $3\cdot10^{12}$. That is, all zeroes $\beta + i\gamma$ of the Riemann zeta-function with $0<\gamma\leq 3\cdot 10^{12}$ have $\beta = 1/2$.

Xianghong Fang, Haoli Bai, Zenglin Xu, Michael Lyu

Variational autoencoders have been widely applied for natural language generation, however, there are two long-standing problems: information under-representation and posterior collapse. The former arises from the fact that only the last hidden state from the encoder is transformed to the latent space, which is insufficient to summarize data. The latter come

Chihiro Kamijima, Yuta Yoshimoto, Yutaro Abe, Shu Takagi

We investigate the relationship between the thermal properties of a micro pulsating heat pipe (MPHP) and the internal flow characteristics. The MPHP consists of an eleven-turn closed-loop of a meandering square microchannel with a hydraulic diameter of $350\ {}{\mu}{\rm m}$ engraved on a silicon substrate. The MPHP charged with Fluorinert FC-72 tends to exhi

Lami Kim, Yoshihiro Tonegawa

Given a closed countably $1$-rectifiable set in $\mathbb R^2$ with locally finite $1$-dimensional Hausdorff measure, we prove that there exists a Brakke flow starting from the given set with the following regularity property. For almost all time, the flow locally consists of a finite number of embedded curves of class $W^{2,2}$ whose endpoints meet at juncti

Shaosai Huang, Bing Wang

The Colding-Gromov gap theorem asserts that an almost non-negatively Ricci curved manifold with unit diameter and maximal first Betti number is homeomorphic to the flat torus. In this paper, we prove a parametrized version of this theorem, in the context of collapsing Riemannian manifolds with Ricci curvature bounded below: if a closed manifold with Ricci cu

Yiming Liu, Erwu Liu, Rui Wang, Yuanzhe Geng

Large reflecting surface (LRS) has emerged as a new solution to improve the energy and spectrum efficiency of wireless communication system. Most existing studies were conducted with an assumption of ideal hardware, and the impact of hardware impairments receives little attention. However, the non-negligible hardware impairments should be taken into consider

Hao Xue, Du. Q. Huynh, Mark Reynolds

Pedestrian trajectory prediction is a challenging task as there are three properties of human movement behaviors which need to be addressed, namely, the social influence from other pedestrians, the scene constraints, and the multimodal (multiroute) nature of predictions. Although existing methods have explored these key properties, the prediction process of

Akhila Sri Manasa Venigalla, Dheeraj Vagavolu, Sridhar Chimalakonda

Covid-19 has been causing severe loss to the human race. Considering the mode of spread and severity, it is essential to make it a habit to follow various safety precautions such as using sanitizers and masks and maintaining social distancing to prevent the spread of Covid-19. Individuals are widely educated about the safety measures against the disease thro

M. Veselsky, V. Petousis, J. Leja

We present a hypothesis that the anomaly in the folding angle distribution of electron-positron pairs, emitted in the decay of the excited levels of nucleus $^{8}$Be and $^{4}$He can be related to the cluster structure of the decaying state. Furthermore, we present a hypothesis that the potentially observed boson with re st mass $m_{X}$=17 MeV can mediate th

Motohiko Ezawa

Quantum computation may well be performed with the use of electric circuits. Especially, the Schr\"{o}dinger equation can be simulated by the lumped-element model of transmission lines, which is applicable to low-frequency electric circuits. In this paper, we show that the Dirac equation is simulated by the distributed-element model, which is applicable to h

Xin Wang, SeyedMehdi Abtahi, Mahmood Chahari, Tianyu Zhao

In recent decades, one of the scientists' main concerns has been to improve the accuracy of satellite attitude, regardless of the expense. The obvious result is that a large number of control strategies have been used to address this problem. In this study, an adaptive neuro-fuzzy integrated (ANFIS) satellite attitude estimation and control system was develo

Qi Chen, Di Wu, Zhifei Zhang

In this paper, we prove the $L^\infty\cap L^2$ stability of Prandtl expansions of shear flow type as $\big(U(y/\sqrt{\nu}),0\big)$ for the initial perturbation in the Gevrey class, where $U(y)$ is a monotone and concave function and $\nu$ is the viscosity coefficient. To this end, we develop the direct resolvent estimate method for the linearized Orr-Sommerf

Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer Hobbs

The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset. Around 57 participating teams from various countries compete to achieve state-of-the-art in aerial agricult

SeyedMehdi Abtahi, Mojtaba Sharifi

Cancer is one of the most common diseases worldwide, posing a serious threat to human health and leading to the deaths of a large number of people. It was observed during the drug administration in chemotherapy that immune cells, cancer cells and normal cells are killed or at least seriously injured and also in order to keep dosage of the drug at specific le

Vineeth Chandran Suja, Alex Hadidi, Aadithya Kannan, Gerald G Fuller

Understanding the dynamics of liquid films that make up bubbles is of practical and fundamental importance. Practically, this understanding is crucial for tuning bubble stability, while fundamentally, thin films are an excellent platform to study 2D flows. Here we study the spatiotemporal film thickness dynamics of bubbles subjected to evaporation driven Mar

SeyedMehdi Abtahi, Mojtaba Sharifi

Hepatitis type B is one of the most common infectious disease worldwide that can pose severe threats to human health up to the point that may contribute to severe liver damage or cancer. Over the past two decades a large number of dynamic models have been presented based on experimental data to predict the HBV infection behavior. Besides, several kinds of co

Yu Qiu, Yun Liu, Shijie Li, Jing Xu

The rapid spread of the new pandemic, i.e., COVID-19, has severely threatened global health. Deep-learning-based computer-aided screening, e.g., COVID-19 infected CT area segmentation, has attracted much attention. However, the publicly available COVID-19 training data are limited, easily causing overfitting for traditional deep learning methods that are usu

Vo Nguyen Le Duy, Ichiro Takeuchi

Selective Inference (SI) has been actively studied in the past few years for conducting inference on the features of linear models that are adaptively selected by feature selection methods such as Lasso. The basic idea of SI is to make inference conditional on the selection event. Unfortunately, the main limitation of the original SI approach for Lasso is th

Timothy L. Molloy

The problem of quickly diagnosing an unknown change in a stochastic process is studied. We establish novel bounds on the performance of misspecified diagnosis algorithms designed for changes that differ from those of the process, and pose and solve a new robust quickest change diagnosis problem in the asymptotic regime of few false alarms and false isolation

Xuanyu Yin, Yoko Sasaki, Weimin Wang, Kentaro Shimizu

Lidar based 3D object detection and classification tasks are essential for autonomous driving(AD). A lidar sensor can provide the 3D point cloud data reconstruction of the surrounding environment. However, real time detection in 3D point clouds still needs a strong algorithmic. This paper proposes a 3D object detection method based on point cloud and image w

Shoichi Hasegawa, Norihisa Ikoma, Tatsuki Kawakami

This paper and [17] treat the existence and nonexistence of stable (resp. outside stable) weak solutions to a fractional Hardy--H\'enon equation $(-\Delta)^s u = |x|^\ell |u|^{p-1} u$ in $\mathbb{R}^N$ where $0 < s < 1$, $\ell > -2s$, $p>1$, $N \geq 1$ and $N > 2s$. In this paper, the nonexistence part is proved for the Joseph--Lundgren subcritical case.

Majid Arezoomand, Mohsen Ghasemi

A graph $\Gamma$ is said to be a semi-Cayley graph over a group $G$ if it admits $G$ as a semiregular automorphism group with two orbits of equal size. We say that $\Gamma$ is normal if $G$ is a normal subgroup of ${\rm Aut}(\Gamma)$. We prove that every connected intransitive one-matching semi-Cayley graph, with maximum degree three, over a finite abelian g

Or Levi, Sardar Hamidian, Pedram Hosseini

The reports of Russian interference in the 2016 United States elections brought into the center of public attention concerns related to the ability of foreign actors to increase social discord and take advantage of personal user data for political purposes. It has raised questions regarding the ways and the extent to which data can be used to create psychogr

Timothy L. Molloy, Tristan Perez, Brendan P. Williams

This paper presents a novel collision avoidance strategy for unmanned aircraft detect and avoid that requires only information about the relative bearing angle between an aircraft and hazard. It is shown that this bearing-only strategy can be conceived as the solution to a novel differential game formulation of collision avoidance, and has several intuitive

Yijun Zhang, Shashin Sharan, Oscar Lopez, Felix J. Herrmann

Modern-day seismic imaging and monitoring technology increasingly rely on dense full-azimuth sampling. Unfortunately, the costs of acquiring densely sampled data rapidly become prohibitive and we need to look for ways to sparsely collect data, e.g. from sparsely distributed ocean bottom nodes, from which we then derive densely sampled surveys through the met

Zijie Qu, Kenneth S. Breuer

The behavior of flagellated bacteria swimming in non-Newtonian media remains an area with contradictory and conflicting results. We report on the behavior of wild-type and smooth-swimming E. coli in Newtonian, shear thinning and viscoelastic media, measuring their trajectories and swimming speed using a three dimensional real-time tracking microscope. We con

Z. Z. Du, C. M. Wang, Hai-Peng Sun, Hai-Zhou Lu

The nonlinear Hall effect is an unconventional response, in which a voltage can be driven by two perpendicular currents in the Hall-bar measurement. Unprecedented in the family of the Hall effects, it can survive time-reversal symmetry but is sensitive to the breaking of discrete and crystal symmetries. It is a quantum transport phenomenon that has deep conn

Erica Mourão, João Felipe Pimentel, Leonardo Murta, Marcos Kalinowski

Context: When conducting a Systematic Literature Review (SLR), researchers usually face the challenge of designing a search strategy that appropriately balances result quality and review effort. Using digital library (or database) searches or snowballing alone may not be enough to achieve high-quality results. On the other hand, using both digital library se

Wenjie Li, Zhaoyang Zhang, Xinjiang Wang, Ping Luo

Although adaptive optimization algorithms such as Adam show fast convergence in many machine learning tasks, this paper identifies a problem of Adam by analyzing its performance in a simple non-convex synthetic problem, showing that Adam's fast convergence would possibly lead the algorithm to local minimums. To address this problem, we improve Adam by propos

Tanya Chowdhury, Sachin Kumar, Tanmoy Chakraborty

Attentional, RNN-based encoder-decoder architectures have achieved impressive performance on abstractive summarization of news articles. However, these methods fail to account for long term dependencies within the sentences of a document. This problem is exacerbated in multi-document summarization tasks such as summarizing the popular opinion in threads pres

Anindya Dey

Mirror symmetry, a three dimensional $\mathcal{N}=4$ IR duality, has been studied in detail for quiver gauge theories of the $ADE$-type (as well as their affine versions) with unitary gauge groups. The $A$-type quivers (also known as linear quivers) and the associated mirror dualities have a particularly simple realization in terms of a Type IIB system of D3

Michael Roysdon, Sudan Xing

In 2011 Lutwak, Yang and Zhang extended the definition of the $L_p$-Minkowski convex combination ($p \geq 1$) introduced by Firey in the 1960s from convex bodies containing the origin in their interiors to all measurable subsets in $\mathbb{R}^n$, and as a consequence, extended the $L_p$-Brunn-Minkowski inequality ($L_p$-BMI) to the setting of all measurable

Chen Qian, Ya-Dong Wu, Jia-Wei Ji, Yunlong Xiao

The uncertainty principle, first introduced by Heisenberg in inertial frames, clearly distinguishes quantum theories from classical mechanics. In non-inertial frames, its information-theoretic expressions, namely entropic uncertainty relations, have been extensively studied through delocalized quantum fields, and localization of the quantum fields were discu

Avraham A. Melkman, Sini Guo, Wai-Ki Ching, Pengyu Liu

An autoencoder is a layered neural network whose structure can be viewed as consisting of an encoder, which compresses an input vector of dimension $D$ to a vector of low dimension $d$, and a decoder which transforms the low-dimensional vector back to the original input vector (or one that is very similar). In this paper we explore the compressive power of a

Lasitha Wijayarathne, Qie Sima, Ziyi Zhou, Ye Zhao

Force modulation of robotic manipulators has been extensively studied for several decades but is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction forces. This study presents a high-level framework f

Yuxian Gu, Zhengyan Zhang, Xiaozhi Wang, Zhiyuan Liu

Recently, pre-trained language models mostly follow the pre-train-then-fine-tuning paradigm and have achieved great performance on various downstream tasks. However, since the pre-training stage is typically task-agnostic and the fine-tuning stage usually suffers from insufficient supervised data, the models cannot always well capture the domain-specific and