January 2022 arXiv papers — page 61

W. Wilfred Godfrey

Covid-19 has ravaged the entire world and it may not be the last such to ravage the world. COMOKIT [3] is an agent based spatial modeling tool to study the effect of covid -19 in a geographical area by creating heterogenous synthetic agents and their behaviours. This paper presents comokit based case study on Gwalior region with respect to various interventi

Sara Björk, Jonas Nordhaug Myhre, Thomas Haugland Johansen

Full characterization of the spectral behavior of generative models based on neural networks remains an open issue. Recent research has focused heavily on generative adversarial networks and the high-frequency discrepancies between real and generated images. The current solution to avoid this is to either replace transposed convolutions with bilinear up-samp

Toni Karvonen, Fehmi Cirak, Mark Girolami

The recently proposed statistical finite element (statFEM) approach synthesises measurement data with finite element models and allows for making predictions about the unknown true system response. We provide a probabilistic error analysis for a prototypical statFEM setup based on a Gaussian process prior under the assumption that the noisy measurement data

Lukas Müller, Lukas Woike

The classifying spaces of handlebody groups form a modular operad. Algebras over the handlebody operad yield systems of representations of handlebody groups that are compatible with gluing. We prove that algebras over the modular operad of handlebodies with values in an arbitrary symmetric monoidal bicategory $\mathcal{M}$ (we introduce for these the name an

Subhayan Roychoudhury, David Prendergast

Resonant Inelastic X-ray Scattering (RIXS), which probes the occupied and unoccupied electronic subspaces in an interrelated fashion, is one of the most detailed, complex and information-rich experimental techniques employed in the investigation of electronic structure across physics, chemistry and materials science. We introduce an ab-initio, accurate and e

Cailian Yang, Xianghao Liao, Yuhao Wang, Minghui Zhang

Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, scan time, and throughput, it is often clinically challenging to obtain high-quality MR images. In this article, we propose a method of using artificial intelligence to expand the channel to achieve the goal of generating the virtual coils

Camille Gontier, Simone Carlo Surace, Igor Delvendahl, Martin Müller

Bayesian Active Learning (BAL) is an efficient framework for learning the parameters of a model, in which input stimuli are selected to maximize the mutual information between the observations and the unknown parameters. However, the applicability of BAL to experiments is limited as it requires performing high-dimensional integrations and optimizations in re

Max Wolff, Stuart Wolff

Feature preference in Convolutional Neural Network (CNN) image classifiers is integral to their decision making process, and while the topic has been well studied, it is still not understood at a fundamental level. We test a range of task relevant feature attributes (including shape, texture, and color) with varying degrees of signal and noise in highly cont

Alfonso Semeraro, Salvatore Vilella, Giancarlo Ruffo, Massimo Stella

Since their announcement in November 2020, COVID-19 vaccines were largely debated by the press and social media. With most studies focusing on COVID-19 disinformation in social media, little attention has been paid to how mainstream news outlets framed COVID-19 narratives compared to alternative sources. To fill this gap, we use cognitive network science and

Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher

This paper presents a new Android malware detection method based on Graph Neural Networks (GNNs) with Jumping-Knowledge (JK). Android function call graphs (FCGs) consist of a set of program functions and their inter-procedural calls. Thus, this paper proposes a GNN-based method for Android malware detection by capturing meaningful intra-procedural call path

D. N. Voskresensky

S-wave pion-nucleon interactions in the linear sigma model, and in Manohar-Georgi and Gasser-Sainio-Svarc models with finite number of terms in Lagrangians, as well as in a general phenomenological approach are reviewed. Subtleties associated with the current algebra theorems and field redefinitions are discussed. In the first and third models most likely th

Dong Li, Jianchao Xue, Ding Yuan, Zongjun Ning

Small-scale, cyclic, transverse motions of plasma threads are usually seen in solar prominences, which are often interpreted as magnetohydrodynamic (MHD) waves. Here, we observed small-scale decayless transverse oscillations in a quiescent prominence, and they appear to be omnipresent. The oscillatory periods of the emission intensity and a proxy for the lin

Wojciech Kusa, Allan Hanbury, Petr Knoth

In the process of Systematic Literature Review, citation screening is estimated to be one of the most time-consuming steps. Multiple approaches to automate it using various machine learning techniques have been proposed. The first research papers that apply deep neural networks to this problem were published in the last two years. In this work, we conduct a

Rong Liu, Tie Liu, Gang Chen, Hong-Li Liu

To understand the nature of SiO emission, we conducted ACA observations of the SiO (2-1) lines toward 146 massive star-forming regions, as part of the ALMA Three-millimeter Observations of Massive Star-forming regions (ATOMS) survey. We detected SiO emission in 128 (87.7$\%$) sources and identified 171 SiO clumps, 105 of which are spatially separated from 3

Chong Jin Ong, Ilayda Canyakmaz

This work addresses the synchronization/consensus problem of identical multi-agent system (MAS) where the agents' dynamics are linear and the communication network is arbitrarily switching among connected topologies. The approach uses a gain matrix of a special structure in a dynamic compensator for each agent. Under reasonable conditions, the approach ensur

Aemilius A W van Vondelen, Alexandros Iliopoulos, Sachin T Navalkar, Daan C van der Hoek

Operational Modal Analysis (OMA) provides essential insights into the structural dynamics of an Offshore Wind Turbine (OWT). In these dynamics, damping is considered an especially important parameter as it governs the magnitude of the response at the natural frequencies. Violation of the stationary white noise excitation requirement of classical OMA algorith

S. V. Jeffers, R. H. Cameron, S. C. Marsden, S. Boro Saikia

Cool main-sequence stars, such as the Sun, have magnetic fields which are generated by an internal dynamo mechanism. In the Sun, the dynamo mechanism produces a balance between the amounts of magnetic flux generated and lost over the Sun's 11-year activity cycle and it is visible in the Sun's different atmospheric layers using multi-wavelength observations.

Kouichi Takemura

We investigate the symmetry of the linear q-difference equations which are associated with some q-Painlev\'e equations. We apply it for adjustment of the expression of the time evolution on the q-Painlev\'e equations in terms of the Weyl group symmetry.

Imran Allie

In this paper we further our understanding of the structure of class two cubic graphs, or snarks, as they are commonly known. We do this by investigating their 3-critical subgraphs, or as we will call them, minimal conflicting subgraphs. We consider how the minimal conflicting subgraphs of a snark relate to its possible minimal 4-edge-colourings. We fully ch

Antonin Delpeuch

We construct a compact closed category out of any symmetric monoidal category by freely adding adjoints to its objects. The morphisms of the completion are defined as string diagrams annotated by objects and morphisms from the original category. The symmetric monoidal category embeds via a faithful monoidal functor into its completion, but in contrast to the

Marco D'Addezio

We prove that the $p^\infty$-torsion of the transcendental Brauer group of an abelian variety over a finitely generated field of characteristic $p>0$ is bounded. This answers a (variant of a) question asked by Skorobogatov and Zarhin for abelian varieties. To do this, we prove a "flat Tate conjecture" for divisors. In the text, we also study other geometric

Sara Ceschia, Luca Di Gaspero, Andrea Schaerf

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on "standard" formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also reviewed and br

Rajmadan Lakshmanan, Alois Pichler, Daniel Potts

This contribution features an accelerated computation of the Sinkhorn's algorithm, which approximates the Wasserstein transportation distance, by employing nonequispaced fast Fourier transforms (NFFT). The algorithm proposed allows approximations of the Wasserstein distance by involving not more than $\mathcal O(n\log n)$ operations for probability measures

Pierre Monmarché

We consider elliptic diffusion processes on $\mathbb R^d$. Assuming that the drift contracts distances outside a compact set, we prove that, at a sufficiently high temperature, the Markov semi-group associated to the process is a contraction of the $\mathcal W_2$ Wasserstein distance, which implies a Poincar\'e inequality for its invariant measure. The resul

Rita Maji, Julia Contreras-García, Eleonora Luppi, Elena Degoli

The interaction of grain boundaries (GBs) with inherent defects and/or impurity elements in multi-crystalline silicon play a decisive role in their electrical behavior. Strain, depending on the types of GBs and defects, plays an important role in these systems. Herein, the correlation between the structural and electronic properties of {\Sigma} 3{111} Si-GB

Domenico Cotroneo, Luigi De Simone, Roberto Natella

In this work, we present a novel fault injection solution (ThorFI) for virtual networks in cloud computing infrastructures. ThorFI is designed to provide non-intrusive fault injection capabilities for a cloud tenant, and to isolate injections from interfering with other tenants on the infrastructure. We present the solution in the context of the OpenStack cl

Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin

We introduce CM3, a family of causally masked generative models trained over a large corpus of structured multi-modal documents that can contain both text and image tokens. Our new causally masked approach generates tokens left to right while also masking out a small number of long token spans that are generated at the end of the string, instead of their ori

Yuting Zhan, Alex Kyllo, Afra Mashhadi, Hamed Haddadi

As various mobile devices and location-based services are increasingly developed in different smart city scenarios and applications, many unexpected privacy leakages have arisen due to geolocated data collection and sharing. While these geolocated data could provide a rich understanding of human mobility patterns and address various societal research questio

Rita Maji, Julia Contreras-García, Nathalie Capron, Elena Degoli

Grain boundaries (GBs) are defects originating in multi-crystalline silicon during crystal growth for device Si solar cell fabrication. The presence of GBs changes the coordination of Si, making it advantageous for charge carriers to recombine, which brings a significant reduction of carrier lifetimes. Therefore, GBs can be highly detrimental for device perf

Noemie Combe, Philippe Combe, Hanna Nencka

We prove that the information geometry's Frobenius manifold is a symplectic manifold having Poisson structures. By proving this statement, a bridge is created between the theories developed by Vinberg, Souriau and Koszul and the Frobenius manifold approach. Until now these approaches seemed disconnected.

Adam D. Weiss, Prabakaran Rajamanickam, Wilfried Coenen, Antonio L. Sánchez

This paper investigates the steady axisymmetric structure of the cold boundary-layer flow surrounding fire whirls developing over localized fuel sources lying on a horizontal surface. The inviscid swirling motion found outside the boundary layer, driven by the entrainment of the buoyant turbulent plume of hot combustion products that develops above the fire,

Claudio Corianò, Matteo Maria Maglio

Recently, the possibility of evading Lovelock's theorem at $d=4$, via a singular redefinition of the dimensionless coupling of the Gauss-Bonnet term, has been very extensively discussed in the cosmological context. The term is added as a quadratic contribution of the curvature tensor to the Einstein-Hilbert action, originating theories of "Einstein Gauss-Bon

Martin Fatou

We extend the lift application for automorphic induction defined by an identity of characters to all elliptic representations.

Zeyang Sha, Xinlei He, Ning Yu, Michael Backes

Self-supervised representation learning techniques have been developing rapidly to make full use of unlabeled images. They encode images into rich features that are oblivious to downstream tasks. Behind their revolutionary representation power, the requirements for dedicated model designs and a massive amount of computation resources expose image encoders to

Marco Minissale, Yuri Aikawa, Edwin Bergin, M. Bertin

The evolution of star-forming regions and their thermal balance are strongly influenced by their chemical composition, that, in turn, is determined by the physico-chemical processes that govern the transition between the gas phase and the solid state, specifically icy dust grains (e.g., particles adsorption and desorption). Gas-grain and grain-gas transition

Taylan Kabbani, Fatih Enes Usta

Predicting the stock market trend has always been challenging since its movement is affected by many factors. Here, we approach the future trend prediction problem as a machine learning classification problem by creating tomorrow_trend feature as our label to be predicted. Different features are given to help the machine learning model predict the label of a

Max van Haren, Maurice Poot, Dragan Kostić, Robin van Es

Mechatronic systems have increasingly stringent performance requirements for motion control, leading to a situation where many factors, such as position-dependency, cannot be neglected in feedforward control. The aim of this paper is to compensate for position-dependent effects by modeling feedforward parameters as a function of position. A framework to mode

Hongkui Wang, Xinmin Hou

Given an irreducible fraction $\frac{c}{d} \in [0,1]$, a pair $(\mathcal{A},\mathcal{B})$ is called a $\frac{c}{d}$-cross-intersecting pair of $2^{[n]}$ if $\mathcal{A}, \mathcal{B}$ are two families of subsets of $[n]$ such that for every pair $A \in\mathcal{A}$ and $B\in\mathcal{B}$, $|A \cap B|= \frac{c}{d}|B|$. Mathew, Ray, and Srivastava [{\it\small Fra

Adam Kardos, Costas G. Papadopoulos, Alexander V. Smirnov, Nikolaos Syrrakos

Based on the Simplified Differential Equations approach, we present results for the two-loop non-planar hexa-box families of master integrals. We introduce a new approach to obtain the boundary terms and establish a one-dimensional integral representation of the master integrals in terms of Generalised Polylogarithms, when the alphabet contains non-factorisa

Anup Mishra, Yijie Mao, Luca Sanguinetti, Bruno Clerckx

This letter focuses on integrating rate-splitting multiple-access (RSMA) with time-division-duplex Cell-free Massive MIMO (multiple-input multiple-output) for massive machine-type communications. Due to the large number of devices, their sporadic access behaviour and limited coherence interval, we assume a random access strategy with all active devices utili

S. B. Popov

Situation with highly magnetized neutron stars in binary systems is not yet certain. On the one hand, all best studied magnetars seem to be isolated objects. On the other, there are many claims based on model-dependent analysis of spin properties or/and luminosity of neutron stars in X-ray binaries in favour of large fields. In addition, there are a few resu

Lise Morlet-Decarnin, Thibaut Divoux, Sebastien Manneville

Cellulose nanocrystals (CNCs) are rodlike biosourced colloidal particles used as key building blocks in a growing number of materials with innovative mechanical or optical properties. While CNCs form stable suspensions at low volume fractions in pure water, they aggregate in the presence of salt and form colloidal gels with time-dependent properties. Here, w

P. M. Lavrov

New method for construction of gauge-invariant deformed theory from an initial gauge theory proposed in our previous papers [1], [2] for closed/open gauge algebras is extended to the case of reducible gauge algebras. The deformation procedure is explicitly described with the help of generating functions of anticanonical transformations depending on fields of

Stefanos Aivazidis, Maria Loukaki

Given a $p$-group $G$ and a subgroup-closed class $\mathfrak{X}$, we associate with each $\mathfrak{X}$-subgroup $H$ certain quantities which count $\mathfrak{X}$-subgroups containing $H$ subject to further properties. We show in Theorem I that each one of the said quantities is always $\equiv 1 \pmod p$ if and only if the same holds for the others. In Theor

Gianira N. Alfarano, Alberto Ravagnani, Emina Soljanin

We are concerned with linear redundancy storage schemes regarding their ability to provide concurrent (local) recovery of multiple data objects. This paper initiates a study of such systems within the classical coding theory. We show how we can use the structural properties of the generator matrix defining the scheme to obtain a bounding polytope for the set

Uta Pigorsch, Marc Sabek

A network's assortativity is the tendency of vertices to bond with others based on similarities, usually excess vertex degree. In this paper we consider assortativity in weighted networks, both directed and undirected. To this end, we propose to consider excess vertex strength, rather than excess degree, and show, that assortativity in weighted networks can

Lei Yi, Cheng Wang, Thomas van Vuren, Detlef Lohse

By varying the oil volume fraction, the microscopic droplet size and the macroscopic rheology of emulsions are investigated in a Taylor-Couette (TC) turbulent shear flow. Although here oil and water in the emulsions have almost the same physical properties (density and viscosity), unexpectedly, we find that oil-in-water (O/W) and water-in-oil (W/O) emulsions

Pardeep Kaur, Sandeep Gautam, S. K. Adhikari

We study supersolid-like crystalline structures emerging in the stationary states of a quasi-two-dimensional spin-orbit (SO)-coupled spin-2 condensate in the ferromagnetic, cyclic, and antiferro-magnetic phases by solving a mean-field model.Interplay of different strengths of SO coupling and interatomic interactions gives rise to a variety of non-trivial den

Rui J. Costa, Moritz Gerstung

The software package $\texttt{mstate}$, in articulation with the package $\texttt{survival}$, provides not only a well-established multi-state survival analysis framework in R, but also one of the most complete, as it includes point and interval estimation of relative transition hazards, cumulative transition hazards and state occupation probabilities, both

Álvaro López-Raventós, Boris Bellalta

The multi-link operation (MLO) is a new feature proposed to be part of the IEEE 802.11be Extremely High Throughput (EHT) amendment. Such feature represents a paradigm shift towards multi-link communications, as nodes will be allowed to transmit and receive data over multiple radio interfaces concurrently. To make it possible, the 802.11be Task Group has prop

Francesco Sgherzi, Alberto Parravicini, Marco Domenico Santambrogio

Graph analytics techniques based on spectral methods process extremely large sparse matrices with millions or even billions of non-zero values. Behind these algorithms lies the Top-K sparse eigenproblem, the computation of the largest eigenvalues and their associated eigenvectors. In this work, we leverage GPUs to scale the Top-K sparse eigenproblem to bigge

Garima Arora, Jinto Thomas, Hem Chandra Joshi

In this article, we report rather long time emission ($\sim$ 250 $\mu s$) from aluminum neutrals (Al I) in ns laser produced plasma in the presence of ambient argon. The study is carried out with varying laser power density, background pressure, and the distance from the target. Slow and fast peak components in the emission spectra observed at earlier times

Utsav Banerjee, Anantha P. Chandrakasan

We present the first BLS12-381 elliptic curve pairing crypto-processor for Internet-of-Things (IoT) security applications. Efficient finite field arithmetic and algorithm-architecture co-optimizations together enable two orders of magnitude energy savings. We implement several countermeasures against timing and power side-channel attacks. Our crypto-processo

Steve Ahlswede, Nimisha Thekke-Madam, Christian Schulz, Birgit Kleinschmit

The collection of a high number of pixel-based labeled training samples for tree species identification is time consuming and costly in operational forestry applications. To address this problem, in this paper we investigate the effectiveness of explanation methods for deep neural networks in performing weakly supervised semantic segmentation using only imag

Jakub Podgorný, Michal Dovčiak, Frédéric Marin, René Goosmann

X-ray polarimetric missions planned for this decade will significantly enhance our knowledge of compact accreting sources. Observations of the X-ray polarization signal from active galactic nuclei (AGNs) or X-ray binary systems (XRBs) will bring new means to study inner accretion flow in these objects that, together with currently used spectroscopic and timi

Mabel Morales-Otero, Virgilio Gómez-Rubio, Vicente Núñez-Antón

Double hierarchical generalized linear models (DHGLM) are a family of models that are flexible enough as to model hierarchically the mean and scale parameters. In a Bayesian framework, fitting highly parameterized hierarchical models is challenging when this problem is addressed using typical Markov chain Monte Carlo (MCMC) methods due to the potential high

Tsuyoshi Kato, Doman Takata

We compute the equivariant Bauer-Furuta degree, when a finite group acts freely on a spin 4-manifold. In the case when the group is cyclic of order power of two, Bryan gave a formula and its applications. We have treated the case when the group has order of odd degree. In particular we gave a formula of the degree when the order is odd-prime. Our approach is

J. C. Morales, N. Nakhjiri, J. Colomé, I. Ribas

Automatic scheduling techniques are becoming a crucial tool for the efficient planning of large astronomical surveys. A specific scheduling method is being designed and developed for the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (Ariel) mission planning based on a hybrid meta-heuristic algorithm with global optimization capability to ensure

Zuo-Wei Yeh, Chia-Hua Hsu, Alexander White, Chen-Fu Yeh

The inner operations of the human brain as a biological processing system remain largely a mystery. Inspired by the function of the human brain and based on the analysis of simple neural network systems in other species, such as Drosophila, neuromorphic computing systems have attracted considerable interest. In cellular-level connectomics research, we can id

Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identif

Thibault Vieu, Stefano Gabici, Vincent Tatischeff, Sruthiranjani Ravikularaman

We compute the production of cosmic rays in the dynamical superbubble produced by a cluster of massive stars. Stellar winds, supernova remnants and turbulence are found to accelerate particles so efficiently that the nonlinear feedback of the particles must be taken into account in order to ensure that the energy balance is not violated. High energy particle

Qiuyun Zou, Hongwen Yang

High-dimensional signal recovery of standard linear regression is a key challenge in many engineering fields, such as, communications, compressed sensing, and image processing. The approximate message passing (AMP) algorithm proposed by Donoho \textit{et al} is a computational efficient method to such problems, which can attain Bayes-optimal performance in i

Yuanzhan Li, Yuqi Liu, Yujie Lu, Siyu Zhang

In recent years, neural signed distance function (SDF) has become one of the most effective representation methods for 3D models. By learning continuous SDFs in 3D space, neural networks can predict the distance from a given query space point to its closest object surface,whose positive and negative signs denote inside and outside of the object, respectively

A. R. Yeates

The magneto-frictional method is used in solar physics to compute both static and quasi-static models of the Sun's coronal magnetic field. Here, we examine how accurately magneto-friction (without fluid pressure) is able to predict the relaxed state in a one-dimensional test case containing two magnetic null points. Firstly, we show that relaxation under the

Maria Colombo, Riccardo Tione

In this paper we answer Iwaniec and Sbordone's conjecture \cite{IB94} concerning very weak solutions to the $p$-Laplace equation. Namely, on one hand we show that distributional solutions of the $p$-Laplace equation in $W^{1,r}$ for $p \neq 2$ and $r>\max\{ 1,p-1\}$ are classical weak solutions if their weak derivatives belong to certain cones. On the other

Hailing Wang, Di Wu, Changjun Yu

In this paper, we consider a special class of nonlinear optimal control problems, where the control variables are box-constrained and the objective functional is strongly convex corresponding to control variables and separable with respect to the state variables and control variables. We convert solving the original nonlinear problem into solving a sequence

Amandine M. C. Le Brun, Romain Teyssier

We investigate the evolution of the dark matter density profiles of the most massive galaxy clusters in the Universe. Using a `zoom-in' procedure on a large suite of cosmological simulations of total comoving volume of $3\,(h^{-1}\,\rm Gpc)^3$, we study the 25 most massive clusters in four redshift slices from $z\sim 1$ to the present. The minimum mass is $M

Yuki Miyakawa

The gradient flow exact renormalization group (GFERG) is a formulation of the exact renormalization group that keeps exact gauge invariance. GFERG can keep also modified chiral invariance. We will show that this formulation reproduces the correct axial anomaly in four dimensions.

A. F. Lanza

The rotation period of some planet-hosting stars appears to be in close commensurability with the orbital period of their close-by planets. A model is proposed to interpret such a phenomenon based on the excitation of resonant oscillations in the interior magnetic field of the star by a component of the tidal potential with a very low frequency in the refere

Antonio Bueno, Irene Ortiz

Given $a,b\in\mathbb{R}$ and $\Phi\in C^1(\mathbb{S}^2)$, we study immersed oriented surfaces $\Sigma$ in the Euclidean 3-space $\mathbb{R}^3$ whose mean curvature $H$ and Gauss curvature $K$ satisfy $2aH+bK=\Phi(N)$, where $N:\Sigma\rightarrow\mathbb{S}^2$ is the Gauss map. This theory widely generalize some of paramount importance such as the ones constant

David Marín, Jean-François Mattei, Eliane Salem

In this work we use our previous results on the topological classification of generic singular foliation germs on $(\mathbb C^{2},0)$ to construct complete families: after fixing the semi-local topological invariants we prove the existence of a minimal family of foliation germs that contain all the topological classes and such that any equisingular global fa

Nima Chartab, Asantha Cooray, Jingzhe Ma, Hooshang Nayyeri

Despite advances in observational data, theoretical models, and computational techniques to simulate key physical processes in the formation and evolution of galaxies, the stellar mass assembly of galaxies still remains an unsolved problem today. Optical spectroscopic measurements appear to show that the gas-phase metallicities of local ultra-luminous infrar

M. Suganya, K. Ganesan, P. Vijayakumar, Amirdha Sher Gill

We report on Raman and photoluminescence spectroscopic studies on oxygen vacancy induced structural disorder in Gd2Ti2O7-d single crystals grown by optical floating zone technique under argon atmosphere. The oxygen vacancies in Gd2Ti2O7-d wafers decrease with thermal annealing in an air atmosphere. The full width at half maximum of X-ray diffraction rocking

Pedro Sarriguren

The competition between alpha- and beta+/EC-decay modes is studied systematically in nuclei along the alpha-decay chains following the synthesis of superheavy nuclei with Z = 119 and Z = 120. A microscopic approach based on deformed self-consistent Hartree-Fock mean-field calculations with Skyrme forces and pairing correlations is used to describe the beta+

F. Onofri, Isaac Rodríguez-Ruiz, Fabrice Lamadie, Fabrice Onofri

The analysis of nano-and microparticle suspensions with micro systems affords improved space-time yields, selectivity, reaction residence times and conversions capabilities. These capabilities are of primary importance in various fields of research and industry. The few microfluidic lab-on-a-chip approaches that have been developed are essentially designed t

Patrick Cattiaux, Arnaud Guillin

As the title indicates this paper will describe several extensions and applications of the $\Gamma$2 integrated criterion introduced by M. Ledoux following ideas of B. Hellffer. We introduce general weak versions and show that they are equivalent to the weak Poincar{\'e} inequalities introduced by M. R{\"o}ckner and F. Y. Wang. We also discuss special weak v

Albert Benveniste, Jean-Baptiste Raclet

Graphical models in probability and statistics are a core concept in the area of probabilistic reasoning and probabilistic programming-graphical models include Bayesian networks and factor graphs. In this paper we develop a new model of mixed (nondeterministic/probabilistic) automata that subsumes both nondeterministic automata and graphical probabilistic mo

Alain Franc

A tensor is a multi-way array that can represent, in addition to a data set, the expression of a joint law or a multivariate function. As such it contains the description of the interactions between the variables corresponding to each of the entries. The rank of a tensor extends to arrays with more than two entries the notion of rank of a matrix, bearing in

Roshni Chakraborty, Maitry Bhavsar, Sourav Kumar Dandapat, Joydeep Chandra

Identifying user stance related to a political event has several applications, like determination of individual stance, shaping of public opinion, identifying popularity of government measures and many others. The huge volume of political discussions on social media platforms, like, Twitter, provide opportunities in developing automated mechanisms to identif

Hailing Wang, Changjun Yu, Di Wu

This paper is concerned with the optimal control problem governed by a linear parabolic equation and subjected to box constraints on control variables. This type of problem has important applications in heating and cooling systems. By applying the scheme of Fenchel duality, we derive the dual problem explicitly where the control constraints in primal problem

Frédéric Du-Burck, Karim Manamanni, Tatiana Steshchenko, Amine Chaouche

Using the Jones formalism, it is shown that electro-optic modulators used for phase modulation generate a modulation of the output polarization induced by the difference of phase modulation depth along the crystallographic axes of the modulator. We study two consequences of this polarization modulation in the fiber setups, limiting the performance of high se

Jiawei Duan, Qingqing Ye, Haibo Hu

Local differential privacy (LDP), which perturbs the data of each user locally and only sends the noisy version of her information to the aggregator, is a popular privacy-preserving data collection mechanism. In LDP, the data collector could obtain accurate statistics without access to original data, thus guaranteeing privacy. However, a primary drawback of

Karim Manamanni, Tatiana Steshchenko, Fabrice Wiotte, Rodolphe Le Targat

We present an experimental investigation of the stability limits specific to optical frequency standards using a fiber-optic architecture and semiconductor lasers. A compact setup composed of a semiconductor laser frequency-locked onto an acetylene transition detected in saturated absorption has been implemented using only fiber-optic components. Fiber optic

Karim Manamanni, Tatiana Steshchenko, Fabrice Wiotte, Amine Chaouche-Ramdane

In this paper, we present an experimental study of the metrological stabilization of a solid-state frequency comb for embedded metrology applications. The comb is a passively mode-locked laser diode based on InGaAs/InP Quantum-dash structure emitting optical lines into a 9 nm bandwidth centered at 1.55 $\mu$m with a repetition rate of 10.09 GHz. The frequenc

Hamid Basiri, Tadahiro Kin, Naoya Okamoto, Eduardo Cortina Gil

So far, most of the developments in muography (or cosmic-ray muon radiography) have been based on either the scattering or the absorption of cosmic-ray muons produced by the nuclear interactions between primary cosmic-rays and the nuclei of the Earth's atmosphere. Applications of muography are increasing in various disciplines. A new use of this technique to

Léo Morin, Nicolas Raymond, San Vu Ngoc

This article is devoted to the spectral analysis of the electro-magnetic Schr\"odinger operator on the Euclidean plane. In the semiclassical limit, we derive a pseudo-differential effective operator that allows us to describe the spectrum in various situations and appropriate regions of the complex plane. Not only results of the selfadjoint case are proved (

V. A. Golovko

There exist two methods for finding the magnetic moment of the electron. In the first of them employed in quantum electrodynamics, one calculates the energy of the electron placed in a constant magnetic field, the extra energy due to the field being proportional to the magnetic moment. It is also possible to use the second method proceeding from the fact tha

Carlo H. Godoy

Within the past two decades, Augmented Reality (AR) applications have received increased attention. Augmented Reality is now widely used in the education sector at level K to 12. AR is expected to be generally adopted in two to three years in higher education and four to five years in K to 12. Applying AR technology in the education sector especially in STEM

Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller

Unlike the classical linear model, nonlinear generative models have been addressed sparsely in the literature of statistical learning. This work aims to bringing attention to these models and their secrecy potential. To this end, we invoke the replica method to derive the asymptotic normalized cross entropy in an inverse probability problem whose generative

Kazhan Othman Mohammed Salih, Tarik A. Rashid, Dalibor Radovanovic, Nebojsa Bacanin

There is no doubt that new technology has become one of the crucial parts of most people's lives around the world. By and large, in this era, the Internet and the Internet of Things (IoT) have become the most indispensable parts of our lives. Recently, IoT technologies have been regarded as the most broadly used tools among other technologies. The tools and

Daniel Frese, Basudeb Sain, Hongqiang Zhou, Yongtian Wang

Optical metasurfaces are perfect candidates for the phase and amplitude modulation of light, featuring an excellent basis for holographic applications. In this work, we present a dual amplitude holographic scheme based on the photon sieve principle, which is then combined with a phase hologram by utilizing the Pancharatnam-Berry phase. We demonstrate that tw

Francesco La Rosa, Maxence Wynen, Omar Al-Louzi, Erin S Beck

The current multiple sclerosis (MS) diagnostic criteria lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, advanced MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign

Carlo H. Godoy, Jerico C. Torayno, Audrey Rose Abbey C. Magtarayo, Mark Wilson J. Suarez

Monitoring typically supports greater analysis and allows for a lot deeper data collection on a Web browser level. Analysts may usually see the use of web-based monitoring software within an entire client context when it comes to client-side monitoring, on the other hand. In the case of Greatleaf Land Inc., their monitoring is somehow traditional. Traditiona

Yang Su, Damith C. Ranasinghe

Internet of Things devices are widely adopted by the general population. People today are more connected than ever before. The widespread use and low-cost driven construction of these devices in a competitive marketplace render Internet-connected devices an easier and attractive target for malicious actors. This paper demonstrates non-invasive physical attac

M. Loukaki, A. Moretó

It has been conjectured that if the number of distinct irreducible constituents of the product of two faithful irreducible characters of a finite $p$-group, for $p\geq5$, is bigger than $(p+1)/2$, then it is at least $p$. We give a counterexample to this conjecture.

Lidia Stocker, Stefan H. Sack, Michael S. Ferguson, Oded Zilberberg

Quantum impurities exhibit fascinating many-body phenomena when the small interacting impurity changes the physics of a large noninteracting environment. The characterisation of such strongly correlated non-perturbative effects is particularly challenging due to the infinite size of the environment, and the inability of local correlators to capture the build

Neda Hejazi, Sebastien Lepine, Thomas Nordlander

We present a model-fit pipeline to determine the stellar parameters of M-type dwarfs, which is an improvement upon our previous work described in Hejazi et al. 2020. We apply this pipeline to analyze the low-resolution (R~2000) spectra of 3745 M dwarfs/subdwarfs, collected at the MDM Observatory, Lick Observatory, Kitt Peak National Observatory, and Cerro To

John Seon Keun Yi, Minseok Seo, Jongchan Park, Dong-Geol Choi

Labeling a large set of data is expensive. Active learning aims to tackle this problem by asking to annotate only the most informative data from the unlabeled set. We propose a novel active learning approach that utilizes self-supervised pretext tasks and a unique data sampler to select data that are both difficult and representative. We discover that the lo

Alexey V Veryaskin, Thomas J Meyer

The first analytical evaluation of free-hinged-hinged-hinged-free beam, proposed to be used as a primary sensing element for gravity gradiometry, is presented. The results of the evaluation, obtained in quadratures, are applied to the beam's structure such as the locations of hinges that form the beam's boundary conditions allowing only free rotations around

Hwai-Chung Ho

The study of long-horizon returns has received a great deal of attention in recent years (see, for example, Boudoukh, Richardson, and Whitelaw (2008), Neuberger (2012) and Lee (2013), Fama and French (2018)). While most of the discussions are concerned with some practical issues in investment, few have touched the important aspect on risk management. The app