December 2020 arXiv papers — page 125

Etienne Brangbour, Pierrick Bruneau, Stéphane Marchand-Maillet, Renaud Hostache

In this paper, we investigate the conversion of a Twitter corpus into geo-referenced raster cells holding the probability of the associated geographical areas of being flooded. We describe a baseline approach that combines a density ratio function, aggregation using a spatio-temporal Gaussian kernel function, and TFIDF textual features. The features are tran

Huan Qing, Jingli Wang

Mixed-SCORE is a recent approach for mixed membership community detection proposed by Jin et al. (2017) which is an extension of SCORE (Jin, 2015). In the note Jin et al. (2018), the authors propose SCORE+ as an improvement of SCORE to handle with weak signal networks. In this paper, we propose a method called Mixed-SCORE+ designed based on the Mixed-SCORE a

Leonardo Furtado, Bruno Cartaxo, Christoph Treude, Gustavo Pinto

Are Brazilian developers less likely to have a contribution accepted than their peers from, say, the United Kingdom? In this paper we studied whether the developers' location relates to the outcome of a pull request. We curated the locations of 14k contributors who performed 44k pull requests to 20 open source projects. Our results indeed suggest that de

A. Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal

Does a Variational AutoEncoder (VAE) consistently encode typical samples generated from its decoder? This paper shows that the perhaps surprising answer to this question is `No'; a (nominally trained) VAE does not necessarily amortize inference for typical samples that it is capable of generating. We study the implications of this behaviour on the learne

K. Ziegler

We propose an approach to process data from interferometric measurements on a closed quantum system at random times. For this purpose a time correlation matrix is introduced which enables us to extract dynamical properties of the quantum system. After defining a generalized expectation value we obtain a distribution of time scales, an average transition time

Chiara Aieta, Gianluca Bertaina, Marco Micciarelli, Michele Ceotto

We present in detail and validate an effective Monte Carlo approach for the calculation of the nuclear vibrational densities via integration of molecular eigenfunctions that we have preliminary employed to calculate the densities of the ground and the excited OH stretch vibrational states in protonated glycine molecule [C. Aieta et. al. Nat. Commun. 11, 4348

Verena Krall, Andrew Coates, Kostas D. Kokkotas

Recently, a toy model was introduced to demonstrate that screening mechanisms in alternative theories of gravitation can hide additional effects. In this model a scalar field is charged under a $U(1)$ symmetry. In sufficiently compact objects the scalar field spontaneously grows, i.e. the object scalarizes, spontaneously breaking the $U(1)$ symmetry. Exactly

Jonathan Conejeros

We prove that every distortion element in the group of diffeomorphisms of the 2-sphere which has some recurrent point that is not fixed is an irrational pseudo-rotation. Moreover we prove that the differential of a distortion element in the group of diffeomorphisms of the 2-sphere having at least three fixed points at a fixed point has a unique eigenvalue wh

George Bissias, Rainer Böhme, David Thibodeau, Brian N. Levine

A key component of security in decentralized blockchains is proof of opportunity cost among block producers. In the case of proof-of-work (PoW), currently used by the most prominent systems, the cost is due to spent computation. In this paper, we characterize the security investment of miners in terms of its cost in fiat money. This enables comparison of sec

Svitlana Vakulenko, Vadim Savenkov, Maarten de Rijke

How can we better understand the mechanisms behind multi-turn information seeking dialogues? How can we use these insights to design a dialogue system that does not require explicit query formulation upfront as in question answering? To answer these questions, we collected observations of human participants performing a similar task to obtain inspiration for

Gregor T. Leuthner, Toma Susi, Clemens Mangler, Jannik C. Meyer

Transmission electron microscopy (TEM) and scanning TEM (STEM) are indispensable tools for materials characterization. However, during a typical (S)TEM experiment, the sample is subject to a number of effects that can change its atomic structure. Of these, perhaps the least discussed are chemical modifications due to the non-ideal vacuum around the sample. W

D. Kuridze, H. Socas-Navarro, J. Koza, R. Oliver

We study a solar spicule observed off-limb using high-resolution imaging spectroscopy in the Ca II 8542 Å line obtained with the CRisp Imaging SpectroPolarimeter (CRISP) on the Swedish 1-m Solar Telescope. Using a new version of the non-LTE code NICOLE specifically developed for this problem we invert the spicule single- and double-peak line profiles. This n

Shuhei Maruyama

We construct two kinds of group cocycles on the volume-preserving diffeomorphism group. We show that, for the volume-preserving diffeomorphism group of the sphere, one of the cocycles gives the Euler class of flat sphere bundles.

Moreno Ursino, Lucie Biard, Sylvie Chevret

Dose-finding clinical trials in oncology aim to determine the maximum tolerated dose (MTD) of a new drug, generally defined by the proportion of patients with short-term dose-limiting toxicities (DLTs). Model-based approaches for such phase I oncology trials have been widely designed and are mostly restricted to the DLTs occurring during the first cycle of t

Mengzhen Wang, Yi Jiang, Yinrui Liu, Wenbin Qian

In this article, the importance is demonstrated of a proper choice of reference particles for decay angle definitions, when constructing partial-wave amplitude of multi-body decays using helicity formalism. This issue is often ignored in the standard use case of the helicity formalism. A new technique is proposed to determine the correct particle ordering, a

Kenji Kadota, Joseph Silk

We explore the possibility that the annihilation of dark matter (DM) is boosted due to enhanced substructure in the presence of primordial black holes (PBHs) which constitute a sub-component of DM. The PBHs can generate entropy fluctuations at the small scales which trigger early structure formation, and a large fraction of the whole DM can reside in these c

E. Bachmat, J. Doncel

We investigate the performance of two size-based routing policies: the Size Interval Task Assignment (SITA) and Task Assignment based on Guessing Size (TAGS). We consider a system with two servers and Bounded Pareto distributed job sizes with tail parameter 1 where the difference between the size of the largest and the smallest job is finite. We show that th

Matthew Corsetti, Ernest Fokoué

Nonnegative Matrix Factorization (NMF) is an unsupervised learning algorithm that produces a linear, parts-based approximation of a data matrix. NMF constructs a nonnegative low rank basis matrix and a nonnegative low rank matrix of weights which, when multiplied together, approximate the data matrix of interest using some cost function. The NMF algorithm ca

Ohad Ben-Baruch, Srivatsan Ravi

Linearizability, the traditional correctness condition for concurrent data structures is considered insufficient for the non-volatile shared memory model where processes recover following a crash. For this crash-recovery shared memory model, strict-linearizability is considered appropriate since, unlike linearizability, it ensures operations that crash take

Jin Zhao, Yi-Dong Wang, Li-Zheng Yin, Feng-Yuan Han

Manipulation of spoof surface plasmons (SSPs) has recently intrigued enormous interest due to the capability of guiding waves with subwavelength footsteps. However, most of the previous studies, manifested for a single functionality, are not suitable for multifunctional integrated devices. Herein, a bifunctional Luneburg-fisheye lens is proposed based on a t

Benjamin Rausch, Kevin Mayer, Marie-Louise Arlt, Gunther Gust

While photovoltaic (PV) systems are installed at an unprecedented rate, reliable information on an installation level remains scarce. As a result, automatically created PV registries are a timely contribution to optimize grid planning and operations. This paper demonstrates how aerial imagery and three-dimensional building data can be combined to create an a

Huiyuan Yang, Xiaojun Yuan, Jun Fang, Ying-Chang Liang

By reconfiguring the propagation environment of electromagnetic waves artificially, reconfigurable intelligent surfaces (RISs) have been regarded as a promising and revolutionary hardware technology to improve the energy and spectrum efficiency of wireless networks. In this paper, we study a RIS aided multiuser multiple-input multiple-output (MIMO) wireless

Rajnish Bhusal, Kamesh Subbarao

This paper is concerned with the consensus problem for multi-agent systems subject to communication delays between the neighboring agents. We consider a scenario where each agent is characterized by a general high-order linear system and the communication delays between the agents are non-uniform and time-varying. We design a distributed control protocol for

Daniel Schaden, Elisabeth Ullmann

We study the computational complexity and variance of multilevel best linear unbiased estimators introduced in [D. Schaden and E. Ullmann, SIAM/ASA J. Uncert. Quantif., (2020)]. We specialize the results in this work to PDE-based models that are parameterized by a discretization quantity, e.g., the finite element mesh size. In particular, we investigate the

Yinghan Li, Shengqian Han, Chenyang Yang

In the paper we study a deep learning based method to solve the multicell power control problem for sum rate maximization subject to per-user rate constraints and per-base station (BS) power constraints. The core difficulty of this problem is how to ensure that the learned power control results by the deep neural network (DNN) satisfy the per-user rate const

A. B. T. Penzlin, W. Kley, R. P. Nelson

The Kepler space mission discovered about a dozen planets orbiting around binary stars systems. Most of these circumbinary planets lie near their instability boundaries at about 3 to 5 binary separations. Past attempts to match these final locations through an inward migration process were only successful for the Kepler-16 system. Here, we study 10 circumbin

Eugenio Petrovich

Scholars in science and technology studies and bibliometricians are increasingly revealing the performative nature of bibliometric indicators. Far from being neutral technical measures, indicators such as the Impact Factor and the h-index are deeply transforming the social and epistemic structures of contemporary science. At the same time, scholars have high

E. Busekool, M. A. W. Verheijen, J. M. van der Hulst, R. B. Tully

We determined the HI mass function of galaxies in the Ursa Major association of galaxies using a blind VLA-D array survey, consisting of 54 pointings in a cross pattern, covering the centre as well as the outskirts of the Ursa Major volume. The calculated HI mass function has best-fitting Schechter parameters θ^* = 0.19+/-0.11 Mpc^{-3}, log(M^*_{HI}/M_{\odot

T. Dumont, A. Palacios, C. Charbonnel, O. Richard

Transport processes occurring in the radiative interior of solar-type stars are evidenced by the surface variation of light elements, in particular Li, and the evolution of their rotation rates. For the Sun, inversions of helioseismic data indicate that the radial profile of angular velocity in its radiative zone is nearly uniform, which implies the existenc

Keke Chang, Yong Du

Inspired by the wisdom of metallurgists in designing new alloys, the Integrated Computational Materials Engineering (ICME) based design strategy is proposed for development of Si based anodes for Li-ion batteries (LIBs). The strategy starts with a rational component design of Si-X, where X is the additive component(s) helping to overcome the problems of the

Oded Zilberberg

Topological phases of matter have sparked an immense amount of activity in recent decades. Topological materials are classified by topological invariants that act as a non-local order parameter for any symmetry and condition. As a result, they exhibit quantized bulk and boundary observable phenomena, motivating various applications that are robust to perturb

Jelle Will, Dominik Krug

We present experimental results for spherical particles rising and settling in a still fluid. Imposing a well-controlled center of mass offset enables us to vary the rotational dynamics selectively by introducing an intrinsic rotational timescale to the problem. Results are highly sensitive even to small degrees of offset, rendering this a practically releva

Xiaoyu Wang, Martin Benning

We present a generalisation of Rosenblatt's traditional perceptron learning algorithm to the class of proximal activation functions and demonstrate how this generalisation can be interpreted as an incremental gradient method applied to a novel energy function. This novel energy function is based on a generalised Bregman distance, for which the gradient w

Claudianor O. Alves, Geovany F. Patricio

This paper concerns the existence of a nontrivial solution for the following problem \begin{equation} \left\{\begin{aligned} -Δu + V(x)u & \in \partial_u F(x,u)\;\;\mbox{a.e. in}\;\;\mathbb{R}^{N},\nonumber u \in H^{1}(\mathbb{R}^{N}). \end{aligned} \right.\leqno{(P)} \end{equation} where $F(x,t)=\int_{0}^{t}f(x,s)\,ds$, $f$ is a $\mathbb{Z}^{N}$-periodic Ca

Yael Naze, Eric Gosset, Quentin Marechal

Using XMM-Newton, we undertook a dedicated project to search for X-ray bright wind-wind collisions in 18 WR+OB systems. We complemented these observations with Swift and Chandra datasets, allowing for the study of two additional systems. We also improved the ephemerides, for these systems displaying photometric changes, using TESS, Kepler, and ASAS-SN data.

Byeong-Hoo Lee, Byeong-Hee Kwon, Do-Yeun Lee, Ji-Hoon Jeong

Brain-computer interface uses brain signals to control external devices without actual control behavior. Recently, speech imagery has been studied for direct communication using language. Speech imagery uses brain signals generated when the user imagines speech. Unlike motor imagery, speech imagery still has unknown characteristics. Additionally, electroence

Ji Yoon Han, Ohyun Jo, Juyeop Kim

Proliferation of 5G devices and services has driven the demand for wide-scale enhancements ranging from data rate, reliability, and compatibility to sustain the ever increasing growth of the telecommunication industry. In this regard, this work investigates how machine learning technology can improve the performance of 5G cell and beam index search in practi

Adrián Pérez-Suay, Julia Amorós-López, Luis Gómez-Chova, Valero Laparra

Dealing with land cover classification of the new image sources has also turned to be a complex problem requiring large amount of memory and processing time. In order to cope with these problems, statistical learning has greatly helped in the last years to develop statistical retrieval and classification models that can ingest large amounts of Earth observat

Kolja Them, Frowin Ellermann, Andrey N. Pravdivtsev, Oleg G. Salnikov

The sensitivity of NMR and MRI can be boosted via hyperpolarization of nuclear spins. However, current methods are costly, polarization is relatively low, or applicability is limited. Here, we report a new hyperpolarization method combining the low-cost, high polarization of hydrogenative parahydrogen-induced polarization (PHIP) with the flexibility of polar

Kanggeun Lee, Won-Ki Jeong

With the advent of recent advances in unsupervised learning, efficient training of a deep network for image denoising without pairs of noisy and clean images has become feasible. However, most current unsupervised denoising methods are built on the assumption of zero-mean noise under the signal-independent condition. This assumption causes blind denoising te

Victor R. Kebande, Nickson M. Karie, Richard A. Ikuesan

The phenomenon of network vigilantism is autonomously attributed to how anomalies and obscure activities from adversaries can be tracked in realtime. Needless to say, in today dynamic, virtualized, and complex network environments, it has become undeniably necessary for network administrators, analysts as well as engineers to practice network vigilantism, on

E. Macías-Virgós, M. J. Pereira-Sáez, Ana D. Tarrío-Tobar

We study the Rayleigh quotient of a Hermitian matrix with quaternionic coefficients and prove its main properties. As an application, we give some relationships between left and right eigenvalues of Hermitian and symplectic matrices.

Byoung-Hee Kwon, Byeong-Hoo Lee, Ji-Hoon Jeong

The electroencephalogram, a type of non-invasive-based brain signal that has a user intention-related feature provides an efficient bidirectional pathway between user and computer. In this work, we proposed a deep learning framework based on corresponding frequency empahsize method to decode the motor imagery (MI) data from 2020 International BCI competition

Alex Cole, Matteo Biagetti, Gary Shiu

We present a pipeline for characterizing and constraining initial conditions in cosmology via persistent homology. The cosmological observable of interest is the cosmic web of large scale structure, and the initial conditions in question are non-Gaussianities (NG) of primordial density perturbations. We compute persistence diagrams and derived statistics for

P. Zasche, R. Uhlar, P. Svoboda, P. Cagas

The available minima timings of 14 selected eclipsing binaries (V1297 Cas, HD 24105, KU Aur, GU CMa, GH Mon, AZ Vel, DI Lyn, DK Her, GQ Dra, V624 Her, V1134 Her, KIC 6187893, V1928 Aql, V2486 Cyg) were collected and analyzed. Using the automatic telescopes, surveys, and satellite data, we derived more than 2500 times of eclipses, accompanied with our own gro

Yihui Han, Xiao-Ping Wang, Xiaoping Xie

This paper proposes an interface/boundary-unfitted eXtended hybridizable discontinuous Galerkin (X-HDG) method for Darcy-Stokes-Brinkman interface problems in two and three dimensions. The method uses piecewise linear polynomials for the velocity approximation and piecewise constants for both the velocity gradient and pressure approximations in the interior

Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian

This paper proposes a novel framework of resource allocation in intelligent reflecting surface (IRS) aided multi-cell non-orthogonal multiple access (NOMA) networks, where a sum-rate maximization problem is formulated. To address this challenging mixed-integer non-linear problem, we decompose it into an optimization problem (P1) with continuous variables and

Kostyukova O. I., Tchemisova T.

The paper is devoted to a study of the cone $\cop$ of copositive matrices. Based on the known from semi-infinite optimization concept of immobile indices, we define zero and minimal zero vectors of a subset of the cone $\cop$ and use them to obtain different representations of faces of $\cop$ and the corresponding dual cones. We describe the minimal face of

Paula Nuño Ruano, Charles W. Robson, Marco Ornigotti

We consider the effect of orbital angular momentum (OAM) on localized waves in optical fibers using theory and numerical simulations, focusing on splash pulses and focus wave modes. For splash pulses, our results show that they may carry OAM only up to a certain maximal value. We also examine how one can optically excite these OAM-carrying modes, and discuss

Saeed Nosratabadi, Nesrine Khazami, Marwa Ben Abdallah, Zoltan Lackner

Social capital creates a synergy that benefits all members of a community. This review examines how social capital contributes to the food security of communities. A systematic literature review, based on Prisma, is designed to provide a state-of-the-art review on capacity social capital in this realm. The output of this method led to finding 39 related arti

M. A. Vasquez-Beltran, B. Jayawardhana, R. Peletier

While it is widely used to represent hysteresis phenomena with unidirectional-oriented loops, we study in this paper the use of Preisach operator for describing hysteresis behavior with multidirectional-oriented loops. This complex hysteresis behavior is commonly found in advanced materials, such as, shape-memory alloys or piezoelectric materials, that are u

Gengwei Zhang, Yiming Gao, Hang Xu, Hao Zhang

Panoptic segmentation that unifies instance segmentation and semantic segmentation has recently attracted increasing attention. While most existing methods focus on designing novel architectures, we steer toward a different perspective: performing automated multi-loss adaptation (named Ada-Segment) on the fly to flexibly adjust multiple training losses over

Nicola Gigli, Chiara Rigoni

We study partial derivatives on the product of two metric measure structures, in particular in connection with calculus via modules as proposed by the first named author. Our main results are 1) The extension to this non-smooth framework of Schwarz's theorem about symmetry of mixed second derivatives, 2) a quite complete set of results relating the prope

Sushil Kumar Saroj, Vikas Ratna, Rakesh Kumar, Nagendra Pratap Singh

Retinal blood vessels structure contains information about diseases like obesity, diabetes, hypertension and glaucoma. This information is very useful in identification and treatment of these fatal diseases. To obtain this information, there is need to segment these retinal vessels. Many kernel based methods have been given for segmentation of retinal vessel

Domenico Logoteta, Albino Perego, Ignazio Bombaci

A precise understanding of the equation of state (EOS) of dense and hot matter is key to modeling relativistic astrophysical environments, including core-collapse supernovae (CCSNe), protoneutron star (PNSs) evolution, and compact binary mergers. In this paper, we extend the microscopic zero-temperature BL (Bombaci and Logoteta) %nuclear equation of state nu

Md. Rabiul Islam, Shuji Sakamoto, Yoshihiro Yamada, Andrew Vargo

Reading analysis can give important information about a user's confidence and habits and can be used to construct feedback to improve a user's reading behavior. A lack of labeled data inhibits the effective application of fully-supervised Deep Learning (DL) for automatic reading analysis. In this paper, we propose a self-supervised DL method for read

Carlos A. R. Herdeiro, Eugen Radu

We present a comparative analysis of the self-gravitating solitons arising in the Einstein-Klein-Gordon, Einstein-Dirac and Einstein-Proca models, for the particular case of static, spherically symmetric spacetimes. Differently from the previous study arXiv:1708.05674, the matter fields possess suitable self-interacting terms in the Lagrangians, which allow

Agnieszka Janiuk, Dominika Król

We study the gravitational collapse and formation of the Kerr black hole from the rotating progenitor star. We follow the evolution of black hole spin, coupled with its increasing mass. We study the effect of different level of rotation endowed in the progenitor's envelope, and we out some constraints on the final black hole parameters. Our method is bas

Zsolt Páles, Amr Zakaria

This paper is motivated by an astonishing result of H. Alzer and S. Ruscheweyh published in 2001 in the Proc. Amer. Math. Soc., which states that the intersection of the classes two-variable Gini means and Stolarsky means is equal to the class of two-variable power means. The two-variable Gini and Stolarsky means form two-parameter classes of means expressed

Phillip Manley, Michele Segantini, Doguscan Ahiboz, Martin Hammerschmidt

We present a double-layer dielectric metasurface obtained by stacking a silicon nanodisc array and a silicon photonic crystal slab with equal periodicity on top of each other. We focus on the investigation of electric near-field enhancement effects occurring at resonant excitation of the metasurface and study its optical properties numerically and experiment

Liang Bai, Yi Bi, Bo Yang, Jun-Chao Hong

The continuous observation of the magnetic field by Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) produces numerous image sequences in time and space. These sequences provide data support for predicting the evolution of photospheric magnetic field. Based on the spatiotemporal long short-term memory(LSTM) network, we use the preproce

Olivier Dehaene, Axel Camara, Olivier Moindrot, Axel de Lavergne

One of the biggest challenges for applying machine learning to histopathology is weak supervision: whole-slide images have billions of pixels yet often only one global label. The state of the art therefore relies on strongly-supervised model training using additional local annotations from domain experts. However, in the absence of detailed annotations, most

Vijay V. Vazirani

The Micali-Vazirani (MV) algorithm for maximum cardinality matching in general graphs, which was published in 1980 \cite{MV}, remains to this day the most efficient known algorithm for the problem. This paper gives the first complete and correct proof of this algorithm. Central to our proof are some purely graph-theoretic facts, capturing properties of minim

Chang Liu, Yixing Huang, Joscha Maier, Laura Klein

In computed tomography (CT), automatic exposure control (AEC) is frequently used to reduce radiation dose exposure to patients. For organ-specific AEC, a preliminary CT reconstruction is necessary to estimate organ shapes for dose optimization, where only a few projections are allowed for real-time reconstruction. In this work, we investigate the performance

Taha Y. Posos, Oksana Chubenko, Sergey V. Baryshev

In this work, a pattern recognition algorithm was developed to process and analyze electron emission micrographs. Various examples of dc and rf emission are given that demonstrate this algorithm applicability to determine emitters spatial location and distribution and calculate apparent emission area. The algorithm is fast and only takes $\sim$10 seconds to

Ievgeniia Kuzminykh, Bogdan Ghita, Alexandr Silonosov

Authentication based on keystroke dynamics is a convenient biometric approach, easy in use, transparent, and cheap as it does not require a dedicated sensor. Keystroke authentication, as part of multi factor authentication, can be used in remote display access to guarantee the security of use of remote connectivity systems during the access control phase or

Yan Li, Bo An, Junming Ma, Donggang Cao

Hyper-parameter tuning (HPT) is crucial for many machine learning (ML) algorithms. But due to the large searching space, HPT is usually time-consuming and resource-intensive. Nowadays, many researchers use public cloud resources to train machine learning models, convenient yet expensive. How to speed up the HPT process while at the same time reduce cost is v

Matthias Blohm, Marc Hanussek, Maximilien Kintz

Recently, Automated Machine Learning (AutoML) has registered increasing success with respect to tabular data. However, the question arises whether AutoML can also be applied effectively to text classification tasks. This work compares four AutoML tools on 13 different popular datasets, including Kaggle competitions, and opposes human performance. The results

Xiaofei Li, Laurent Girin, Fabien Badeig, Radu Horaud

This paper addresses the problem of sound-source localization (SSL) with a robot head, which remains a challenge in real-world environments. In particular we are interested in locating speech sources, as they are of high interest for human-robot interaction. The microphone-pair response corresponding to the direct-path sound propagation is a function of the

Bin He, Di Zhou, Jing Xie, Jinghui Xiao

Entities may have complex interactions in a knowledge graph (KG), such as multi-step relationships, which can be viewed as graph contextual information of the entities. Traditional knowledge representation learning (KRL) methods usually treat a single triple as a training unit, and neglect most of the graph contextual information exists in the topological st

Ekaterina Shemetova, Alexander Okhotin, Semyon Grigorev

The rational index of a context-free language $L$ is a function $f(n)$, such that for each regular language $R$ recognized by an automaton with $n$ states, the intersection of $L$ and $R$ is either empty or contains a word shorter than $f(n)$. It is known that the context-free language (CFL-)reachability problem and Datalog query evaluation for context-free

Jiaxin Wang, Jinping Zhou, Liqin Zhao

This paper studies the family of piecewise linear differential systems in the plane with two pieces separated by a switching curve $y=x^{m}$, where $m>1$ is an arbitrary positive. By analysing the first order Melnikov function, we give an upper bound and an lower bound of the maximum number of limit cycles which bifurcate from the period annulus around the o

Jens Lang, Pia Domschke, Elisa Strauch

In this paper, we are concerned with the quantification of uncertainties that arise from intra-day oscillations in the demand for natural gas transported through large-scale networks. The short-term transient dynamics of the gas flow is modelled by a hierarchy of hyperbolic systems of balance laws based on the isentropic Euler equations. We extend a novel ad

Piotr Lebiedowicz, Josef Leutgeb, Otto Nachtmann, Anton Rebhan

The production of $f_{1}$ ($J^{PC} = 1^{++}$) mesons in proton-proton collisions via pomeron-pomeron fusion is discussed. Two ways to construct the pomeron-pomeron-$f_{1}$ coupling are presented. Comparisons with data from the WA102 experiment are made and predictions for RHIC and LHC experiments are given.

Aditya Ajit Khadilkar, Godwyn James William, Hemprasad Yashwant Patil

The feedback of consumers who pass by an advertisement board is crucial for the marketing teams of corporate companies .If the emotions of a consumer are analyzed after exposure to the advertisement, it would help to rate the quality of the advertisement .The state of the art emotion analyzers can do this task seamlessly .However, if the consumer moves away

X. Song, P. Weltevrede, M. J. Keith, S. Johnston

The Thousand Pulsar Array (TPA) project currently monitors about 500 pulsars with the sensitive MeerKAT radio telescope by using subarrays to observe multiple sources simultaneously. Here we define the adopted observing strategy, which guarantees that each target is observed long enough to obtain a high fidelity pulse profile, thereby reaching a sufficient p

Yao Cheng, Yanjie Mei, Hans-Goerg Roos

In this paper we analyze the error as well for the semi-discretization as the full discretization of a time-dependent convection-diffusion problem. We use for the discretization in space the local discontinuous Galerkin (LDG) method on a class of layer-adapted meshes including Shishkin-type and Bakhvalov-type meshes and the implicit $θ$-scheme in time. For p

R. D. Dawson, K. S. Rabinovich, D. Putzky, G. Christiani

The temperature dependence of the superfluid density $ρ_s(T)$ has been measured for a series of ultrathin MBE-grown DyBa$_2$Cu$_3$O$_{7-δ}$ superconducting (SC) films by sub-mm wave interferometry combined with time-domain THz spectroscopy and IR ellipsometry. We find that all films 10 u.c. and thicker show the same universal temperature dependence of $ρ_s(T

Laurent Denis, Anis Matoussi, Jing Zhang

We prove an existence and uniqueness result for two-obstacle problem for quasilinear Stochastic PDEs (DOSPDEs for short). The method is based on the probabilistic interpretation of the solution by using the backward doubly stochastic differential equations (BDSDEs for short).

Marcin Maździarz

An ability of different molecular potentials to reproduce the properties of 2D molybdenum disulphide polymorphs is examined. Structural and mechanical properties, as well as phonon dispersion of the 2H, 1T and 1T' single-layer MoS2 (SL MoS2) phases, were obtained using density functional theory (DFT) and molecular statics calculations (MS) with Stillinge

Andreas D. Meid

In many academic settings, medical students start their scientific work already during their studies. Like at our institution, they often work in interdisciplinary teams with more or less experienced (postgraduate) researchers of pharmaceutical sciences, natural sciences in general, or biostatistics. All of them should be taught good research practices as an

Simon Chatelin, Raoul Pop, Céline Giraudeau, Khalid Ambarki

The invasive measurement of the hepatic venous pressure gradient is still considered as the reference method to assess the severity of portal hypertension. Even though previous studies have shown that the liver stiffness measured by elastography could predict portal hypertension in patients with chronic liver disease, the mechanisms behind remain today poorl

Bin He, Xin Jiang, Jinghui Xiao, Qun Liu

Recent studies on pre-trained language models have demonstrated their ability to capture factual knowledge and applications in knowledge-aware downstream tasks. In this work, we present a language model pre-training framework guided by factual knowledge completion and verification, and use the generative and discriminative approaches cooperatively to learn t

Yurong Su, Xinlu Li, Meng Zhu, Jia Zhang

Multiferroic tunnel junctions (MFTJs) have aroused significant interest due to their functional properties useful for non-volatile memory devices. So far, however, all the existing MFTJs have been based on perovskite-oxide heterostructures limited by a relatively high resistance-area (RA) product unfavorable for practical applications. Here, using first-prin

M. Pietrow, R. Zaleski, A. Wagner, P. Slomski

The excess energy emitted during the positronium (Ps) formation in condensed matter may be released as light. Spectroscopic analysis of this light can be a new method of studying the electronic properties of materials. We report the first experimental attempt, according to our knowledge, to verify the existence of this emission process. As a result, the poss

Philipp Gesner, Christian Gletter, Florian Landenberger, Frank Kirschbaum

Dynamic models of the battery performance are an essential tool throughout the development process of automotive drive trains. The present study introduces a method making a large data set suitable for modeling the electrical impedance. When obtaining data-driven models, a usual assumption is that more observations produce better models. However, real drivin

Rong Zhu, Andreas Pfadler, Ziniu Wu, Yuxing Han

Structure Learning for Bayesian network (BN) is an important problem with extensive research. It plays central roles in a wide variety of applications in Alibaba Group. However, existing structure learning algorithms suffer from considerable limitations in real world applications due to their low efficiency and poor scalability. To resolve this, we propose a

Alexander Okhotin

A classical result by Floyd ("On the non-existence of a phrase structure grammar for ALGOL 60", 1962) states that the complete syntax of any sensible programming language cannot be described by the ordinary kind of formal grammars (Chomsky's ``context-free''). This paper uses grammars extended with conjunction and negation operators, know

David Hertz

The purpose of this letter is to improve Hoeffding&#39;s lemma and consequently Hoeffding&#39;s tail bounds. The improvement pertains to left skewed zero mean random variables $X\in[a,b]$, where $a<0$ and $-a>b$. The proof of Hoeffding&#39;s improved lemma uses Taylor&#39;s expansion, the convexity of $\exp(sx), s\in {\bf R}$ and an unnoticed observation sin

D. Mary, S. Bourguignon, E. Roquain, S. Sulis

We consider several detection situations where, under the alternative hypothesis, the signal admits a low complexity model and, under both the null and the alternative hypotheses, the distribution of the background noise is {unknown}. We present several detection strategies for such cases, whose design relies on exogenous or on endogenous data. These testing

Dong-Kyun Han, Ji-Hoon Jeong

The inter/intra-subject variability of electroencephalography (EEG) makes the practical use of the brain-computer interface (BCI) difficult. In general, the BCI system requires a calibration procedure to acquire subject/session-specific data to tune the model every time the system is used. This problem is recognized as a major obstacle to BCI, and to overcom

Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov

Recent advances in Deep Reinforcement Learning (DRL) have largely focused on improving the performance of agents with the aim of replacing humans in known and well-defined environments. The use of these techniques as a game design tool for video game production, where the aim is instead to create Non-Player Character (NPC) behaviors, has received relatively

Anita de Mello Koch, Ellen de Mello Koch, Robert de Mello Koch

Promising resolutions of the generalization puzzle observe that the actual number of parameters in a deep network is much smaller than naive estimates suggest. The renormalization group is a compelling example of a problem which has very few parameters, despite the fact that naive estimates suggest otherwise. Our central hypothesis is that the mechanisms beh

J. J. F Guo

In this paper, we prove that if $f(x)=\sum_{k=0}^n{n\choose k}a_kx^k$ is a polynomial with real zeros only, then the sequence $\{a_k\}_{k=0}^n$ satisfies the following inequalities $a_{k+1}^2(1-\sqrt{1-c_k})^2/a_k^2 \leq(a_{k+1}^2-a_ka_{k+2})/(a_k^2-a_{k-1}a_{k+1}) \leq a_{k+1}^2(1+\sqrt{1-c_k})^2/a_k^2$, where $c_k=a_ka_{k+2}/a_{k+1}^2$. This inequality hol

Yiwen Guo, Qizhang Li, Hao Chen

The vulnerability of deep neural networks (DNNs) to adversarial examples has drawn great attention from the community. In this paper, we study the transferability of such examples, which lays the foundation of many black-box attacks on DNNs. We revisit a not so new but definitely noteworthy hypothesis of Goodfellow et al.&#39;s and disclose that the transfer

Nikola Anđelić, Sandi Baressi Šegota, Ivan Lorencin, Zlatan Car

In this paper, the publicly available dataset of condition based maintenance of combined diesel-electric and gas (CODLAG) propulsion system for ships has been utilized to obtain symbolic expressions which could estimate gas turbine shaft torque and fuel flow using genetic programming (GP) algorithm. The entire dataset consists of 11934 samples that was divid

Shin-ichi Fujimori, Ikuto Kawasaki, Yukiharu Takeda, Hiroshi Yamagami

The valence state of UTe$_2$ was studied by core-level photoelectron spectroscopy. The main peak position of the U $4f$ core-level spectrum of UTe$_2$ coincides with that of UB$_2$, which is an itinerant compound with a nearly $5f^3$ configuration. However, the main peak of UTe$_2$ is broader than that of UB$_2$, and satellite structures are observed in the

Jun-Jie Huang

The lattice Boltzmann method (LBM) has gained increasing popularity in incompressible viscous flow simulations, but it uses many more variables than necessary. This defect was overcome by a recent approach that solves the more actual macroscopic equations obtained through Taylor series expansion analysis of the lattice Boltzmann equations [Lu et al., J. Comp

Cheuk Yin Lee

We determine the exact Hausdorff measure functions for the range and level sets of a class of Gaussian random fields satisfying sectorial local nondeterminism and other assumptions. We also establish a Chung-type law of the iterated logarithm. The results can be applied to the Brownian sheet, fractional Brownian sheets whose Hurst indices are the same in all

Leonardo Cella, Claudio Gentile, Massimiliano Pontil

Motivated by a natural problem in online model selection with bandit information, we introduce and analyze a best arm identification problem in the rested bandit setting, wherein arm expected losses decrease with the number of times the arm has been played. The shape of the expected loss functions is similar across arms, and is assumed to be available up to