November 2020 arXiv papers — page 33

Sheng Ao, Qingyong Hu, Bo Yang, Andrew Markham

Extracting robust and general 3D local features is key to downstream tasks such as point cloud registration and reconstruction. Existing learning-based local descriptors are either sensitive to rotation transformations, or rely on classical handcrafted features which are neither general nor representative. In this paper, we introduce a new, yet conceptually

Yassir Fathullah, Mark Gales, Andrey Malinin

Ensemble approaches are commonly used techniques to improving a system by combining multiple model predictions. Additionally these schemes allow the uncertainty, as well as the source of the uncertainty, to be derived for the prediction. Unfortunately these benefits come at a computational and memory cost. To address this problem ensemble distillation (EnD)

Shutang You

This paper proposed a new method to locate the source of forced oscillation that involves resonance with natural oscillation modes. The new method is based on comparing the oscillation mode shape of the forced oscillation with that of the natural oscillation that the forced oscillation resonating with. The location that has the largest angle difference betwe

Nasim Katebi, Reza Sameni, Gari D. Clifford

Assessing fetal development is usually carried out by techniques such as ultrasound imaging, which is generally unavailable in rural areas due to the high cost, maintenance, skills and training needed to operate the devices effectively. In this work, we propose a low-cost one-dimensional Doppler-based method for estimating gestational age (GA). Doppler time

Lucas Dahinden, Álvaro del Pino

We define billiards in the context of sub-Finsler Geometry. We provide symplectic and variational (or rather, control theoretical) descriptions of the problem and show that they coincide. We then discuss several phenomena in this setting, including the failure of the reflection law to be well-defined at singular points of the boundary distribution, the appea

A. G. Luchinin, V. A. Malyshev, E. A. Kopelovich, K. F. Burdonov

An up to 15 T pulsed magnetic field generator in a volume of a few cubic centimeters has been created for experiments with magnetized laser plasma. The magnetic field is created by a pair of coils placed in a sealed reservoir with liquid nitrogen, which is installed in a vacuum chamber with a laser target. The bearing body provides the mechanical strength of

Serena Matucci, Pavel Řehák

We establish conditions guaranteeing that all eventually positive increasing solutions of a half-linear delay differential equation are regularly varying and derive precise asymptotic formulae for them. The results here presented are new also in the linear case and some of the observations are original also for non-functional equations. A substantial differe

James M. Scott, Tadele Mengesha

In this note we prove an estimate on the level sets of a function with $(p, q)$ growth that depends on the difference quotient of a bounded weak solution to a nonlocal double phase equation. This estimate is related to a self improving property of these solutions.

Huang Xie, Tuomas Virtanen

In this paper, we study zero-shot learning in audio classification via semantic embeddings extracted from textual labels and sentence descriptions of sound classes. Our goal is to obtain a classifier that is capable of recognizing audio instances of sound classes that have no available training samples, but only semantic side information. We employ a bilinea

Erik Piatti, Alessandro Sola, Dario Daghero, Giovanni A. Ummarino

We perform electric double-layer gating experiments on thin films of niobium nitride. Thanks to a cross-linked polymer electrolyte system of improved efficiency, we induce surface charge densities as high as $\approx 2.8 \times 10^{15}\,\mathrm{cm}^{-2}$ in the active channel of the devices. We report a reversible modulation of the superconducting transition

Luigi C. Berselli, Michael Růžička

In this paper we prove optimal error estimates for {solutions with natural regularity} of the equations describing the unsteady motion of incompressible shear-thinning fluids. We consider a full space-time semi-implicit scheme for the discretization. The main novelty, with respect to previous results, is that we obtain the estimates directly without introduc

Enrique Lizarraga, Walter Herrera

The design and implementation of low-profile antennas has been analyzed in past decades from different perspectives while the purpose is to have a small size in the device, and an adequate electromagnetic behavior. This work pursues a methodology to identify small antennas and consequently presents some similarities. Meanwhile, curved surfaces are considered

Soorena Salari, Nasser Sadati

This paper presents a novel feature fusion-based deep learning model (called CASU2Net) for fault detection in offshore wind turbines. The proposed CASU2Net model benefits of a two-step early fusion to enrich features in the final stage. Moreover, since previous studies did not consider uncertainty while model developing and also predictions, we take advantag

Jens Hemelaer, Morgan Rogers

FitzGerald identified four conditions (RI), (UR), (RI*) and (UR*) that are necessarily satisfied by an algebra, if its monoid of endomorphisms has commuting idempotents. We show that these conditions are not sufficient, by giving an example of an algebra satisfying the four properties, such that its monoid of endomorphisms does not have commuting idempotents

Kyrill A. Bugaev

We develop a novel method to analyze the excluded volume of the multicomponent mixtures of classical hard spheres in the grand canonical ensemble. The method is based on the Laplace-Fourier transform technique and allows one to account for the fluctuations of the particle number density for the induced surface and curvature tensions equation of state. As a r

Ignacio Cirac, David Perez-Garcia, Norbert Schuch, Frank Verstraete

The theory of entanglement provides a fundamentally new language for describing interactions and correlations in many body systems. Its vocabulary consists of qubits and entangled pairs, and the syntax is provided by tensor networks. We review how matrix product states and projected entangled pair states describe many-body wavefunctions in terms of local ten

Quentin Fontaine

Quantum fluids of light are the photonic counterpart of Bose gases. They currently attract increasing interest since they are versatile and highly tunable systems for probing many-body physics quantum phenomena, such as superfluidity. Superfluid flow of light has already been reported in microcavity exciton-polariton condensates but clear observation of this

Sara Johansson Fernstad, Jimmy Johansson

This paper contributes a novel visualization method, Missingness Glyph, for analysis and exploration of missing values in data. Missing values are a common challenge in most data generating domains and may cause a range of analysis issues. Missingness in data may indicate potential problems in data collection and pre-processing, or highlight important data c

C. Ferrigno, V. Savchenko, A. Coleiro, F. Panessa

At the time of defining the science objectives of the INTernational Gamma-Ray Astrophysics Laboratory (INTEGRAL), such a rapid and spectacular development of multi-messenger astronomy could not have been predicted, with new impulsive phenomena becoming accessible through different channels. Neutrino telescopes have routinely detected energetic neutrino event

Johan Bijnens, Nils Hermansson-Truedsson, Laetitia Laub, Antonio Rodriguez-Sanchez

The current $3.7\sigma$ discrepancy between the Standard Model prediction and the experimental value of the muon anomalous magnetic moment could be a hint for the existence of new physics. The hadronic light-by-light contribution is one of the pieces requiring improved precision on the theory side, and an important step is to derive short-distance constraint

Alexandre Toubiana, Stanislav Babak, Enrico Barausse, Luis Lehner

Exotic compact objects can be difficult to distinguish from black holes in the inspiral phase of the binaries observed by gravitational-wave detectors, but significant differences may be present in the merger and post-merger signal. We introduce a toy model capturing the salient features of binaries of exotic compact objects with compactness below $0.2$, whi

Roberta Palacino, Jonathan Keeling

We consider a generalized Dicke model with U(1) symmetry, which can undergo a transition to a superradiant state that spontaneously breaks this symmetry. By exploiting the difference in timescale between atomic and cavity dynamics, one may eliminate the cavity dynamics, providing an atom-only theory. We show that the standard Redfield theory cannot describe

Nina Lukashina, Alisa Alenicheva, Elizaveta Vlasova, Artem Kondiukov

Lipophilicity is one of the factors determining the permeability of the cell membrane to a drug molecule. Hence, accurate lipophilicity prediction is an essential step in the development of new drugs. In this paper, we introduce a novel approach to encoding additional graph information by extracting molecular substructures. By adding a set of generalized ato

Daniel Schäppi

To a homology theory one can associate an additive site and a new homological functor with values in the category of additive sheaves on that site. If this category of sheaves can be shown to be equivalent to a category of comodules of a Hopf algebroid, then we obtain a new homology theory by composing with the underlying module functor. This new homology th

Guangming Wang, Minjian Xin, Wenhua Wu, Zhe Liu

Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manipulator tasks. On the one hand, a sparse-reward setting causes exploration inefficient. On the other hand, exploration using physical robots is of high cost and unsafe. In this pape

Wanquan Feng, Juyong Zhang, Hongrui Cai, Haofei Xu

Learning non-rigid registration in an end-to-end manner is challenging due to the inherent high degrees of freedom and the lack of labeled training data. In this paper, we resolve these two challenges simultaneously. First, we propose to represent the non-rigid transformation with a point-wise combination of several rigid transformations. This representation

O. L. Dors, M. Contini, R. A. Riffel, E. Perez-Montero

We build detailed composite models of photoionization and shock ionization based on the SUMA code to reproduce emission lines emitted from the Narrow Line Regions (NLR) of Seyfert 2 nuclei. The aim of this work is to investigate diagram AGN positions according to shock parameters, shock effects on the gas temperature and ionization structures and derive a se

Qing Gao, Mingtao Pei, Hongyu Shen

A healthy lifestyle is the key to better health and happiness and has a considerable effect on quality of life and disease prevention. Current lifelogging/egocentric datasets are not suitable for lifestyle analysis; consequently, there is no research on lifestyle analysis in the field of computer vision. In this work, we investigate the problem of lifestyle

Francesco Ballarin, Gianluigi Rozza, Maria Strazzullo

In this contribution we propose reduced order methods to fast and reliably solve parametrized optimal control problems governed by time dependent nonlinear partial differential equations. Our goal is to provide a tool to deal with the time evolution of several nonlinear optimality systems in many-query context, where a system must be analysed for various phy

Michael Niemeyer, Andreas Geiger

Deep generative models allow for photorealistic image synthesis at high resolutions. But for many applications, this is not enough: content creation also needs to be controllable. While several recent works investigate how to disentangle underlying factors of variation in the data, most of them operate in 2D and hence ignore that our world is three-dimension

Christian Himpe, Sara Grundel, Peter Benner

To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be simulated ahead of time. This many-query gas network simulation task can be accelerated by model reduction, yet

Thomas Führer, Norbert Heuer

We observe a dramatic lack of robustness of the DPG method when solving problems on large domains and where stability is based on a Poincar\'e-type inequality. We show how robustness can be re-established by using appropriately scaled test norms. As model cases we study the Poisson problem and the Kirchhoff--Love plate bending model, and also include fully d

Shuyang Sun, Liang Chen, Gregory Slabaugh, Philip Torr

Some image restoration tasks like demosaicing require difficult training samples to learn effective models. Existing methods attempt to address this data training problem by manually collecting a new training dataset that contains adequate hard samples, however, there are still hard and simple areas even within one single image. In this paper, we present a d

Diego Kozlowski, Gabriela Lozano, Carla M. Felcher, Fernando Gonzalez

Cultural products are a source to acquire individual values and behaviours. Therefore, the differences in the content of the magazines aimed specifically at women or men are a means to create and reproduce gender stereotypes. In this study, we compare the content of a women-oriented magazine with that of a men-oriented one, both produced by the same editoria

Muhammad Atif Ur Rehman, Rehmat Ullah, Byung-Seo Kim, Boubakr Nour

The promising vision of Information-Centric Networking (ICN) and of its realization, Named Data Networking (NDN), has attracted extensive attention in recent years in the context of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs). However, a comprehensive NDN/ICN-based architectural design for WSNs, including specially tailored naming scheme

Darryl D. Holm, Ruiao Hu

This paper introduces an energy-preserving stochastic model for studying wave effects on currents in the ocean mixing layer. The model is called stochastic forcing by Lie transport (SFLT). The SFLT model is derived here from a stochastic constrained variational principle, so it has a Kelvin circulation theorem. The examples of SFLT given here treat 3D Euler

Camillo De Lellis, Vikram Giri

We give an example of a bounded divergence free autonomous vector field in $\mathbb R^3$ (and of a nonautonomous bounded divergence free vector field in $\mathbb R^2$) and of a bounded initial data for which the Cauchy problem for the corresponding transport equation has $2$ distinct solutions. We then show that both solutions are limits of classical solutio

Venkat Sri Sai Ram, Ashish Panwar, Arkaprava Basu

Large pages are commonly deployed to reduce address translation overheads for big-memory workloads. Modern x86-64 processors from Intel and AMD support two large page sizes -- 1GB and 2MB. However, previous works on large pages have primarily focused on 2MB pages, partly due to lack of substantial evidence on the profitability of 1GB pages to real-world appl

Xirong Li, Fangming Zhou, Chaoxi Xu, Jiaqi Ji

Retrieving unlabeled videos by textual queries, known as Ad-hoc Video Search (AVS), is a core theme in multimedia data management and retrieval. The success of AVS counts on cross-modal representation learning that encodes both query sentences and videos into common spaces for semantic similarity computation. Inspired by the initial success of previously few

Alex Glushkovsky

The periodic table is a fundamental representation of chemical elements that plays essential theoretical and practical roles. The research article discusses the experiences of unsupervised training of neural networks to represent elements on the 2D latent space based on their electron configurations. To emphasize chemical properties of the elements, the orig

Tommy Hofmann, Carlo Sircana

We show that assuming the generalized Riemann hypothesis there are no normal CM-fields with class number one of degree 64 and 96. This is done by constructing complete tables of normal CM-fields using discriminant bounds of Lee--Kwon. This solves the class number one problem for normal CM-fields assuming GRH. Using the same technique to solve the relative cl

Yalei Song, Yann Monceaux, Stefan Bittner, Kimhong Chao

We report on experiments with M\"obius strip microlasers which were fabricated with high optical quality by direct laser writing. A M\"obius strip, i.e., a band with a half twist, exhibits the fascinating property that it has a single nonorientable surface and a single boundary. We provide evidence that, in contrast to conventional ring or disk resonators, a

Hayk Asatryan, Hanno Gottschalk, Marieke Lippert, Matthias Rottmann

In recent years, generative adversarial networks (GANs) have demonstrated impressive experimental results while there are only a few works that foster statistical learning theory for GANs. In this work, we propose an infinite dimensional theoretical framework for generative adversarial learning. We assume that the probability density functions of the underly

Michael A. Lepori

We present a new approach for detecting human-like social biases in word embeddings using representational similarity analysis. Specifically, we probe contextualized and non-contextualized embeddings for evidence of intersectional biases against Black women. We show that these embeddings represent Black women as simultaneously less feminine than White women,

A. D'Jorge, A. L. Anderson, A. Ferramosca, A. H. González

The interest in non-linear impulsive systems (NIS) has been growing due to its impact in application problems such as disease treatments (diabetes, HIV, influenza, among many others), where the control action (drug administration) is given by short-duration pulses followed by time periods of null values. Within this framework the concept of equilibrium needs

Jiongyan Zhang

In order to study the phenomenon of regional economic development and urban expansion from the perspective of night-light remote sensing images, researchers use NOAA-provided night-light remote sensing image data (data from 1992 to 2013) along with ArcGIS software to process image information, obtain the basic pixel information data of specific areas of the

Wadim Zudilin

Using an intrinsic $q$-hypergeometric strategy, we generalise Dwork-type congruences $H(p^{s+1})/H(p^s)\equiv H(p^s)/H(p^{s-1})\pmod{p^3}$ for $s=1,2,\dots$ and $p$ a prime, when $H(N)$ are truncated hypergeometric sums corresponding to the periods of rigid Calabi--Yau threefolds.

Roman Rausch, Cassian Plorin, Matthias Peschke

We solve the quantum-mechanical antiferromagnetic Heisenberg model with spins positioned on vertices of the truncated icosahedron using the density-matrix renormalization group (DMRG). This describes magnetic properties of the undoped C$_{60}$ fullerene at half filling in the limit of strong on-site interaction $U$. We calculate the ground state and correlat

Jing Chen, Chenhui Wang, Kejun Wang, Meichen Liu

In this paper, we propose a computational efficient end-to-end training deep neural network (CEDNN) model and spatial attention maps based on difference images. Firstly, the difference image is generated by image processing. Then five binary images of difference images are obtained using different thresholds, which are used as spatial attention maps. We use

Suk Joon Hong, Brandon Bennett

The Winograd Schema Challenge (WSC) is a common-sense reasoning task that requires background knowledge. In this paper, we contribute to tackling WSC in four ways. Firstly, we suggest a keyword method to define a restricted domain where distinctive high-level semantic patterns can be found. A thanking domain was defined by key-words, and the data set in this

Shiyuan Qiang, Xiaoyan Jing, Minghui Yang

The autocorrelation values of two classes of binary sequences are shown to be good in [6]. We study the 2-adic complexity of these sequences. Our results show that the 2-adic complexity of such sequences is large enough to resist the attack of the rational approximation algorithm.

Hongyuan Wang, Xiang Liu, Wen Kang, Zhiqiang Yan

To eliminate the problems of large dimensional differences, big semantic gap, and mutual interference caused by hybrid features, in this paper, we propose a novel Multi-Features Guidance Network for partial-to-partial point cloud registration(MFG). The proposed network mainly includes four parts: keypoints' feature extraction, correspondences searching, corr

Junyi Xie

Let $k$ be a perfect complete valued field with a nontrivial non-archimedean norm $|\cdot|$ and $\omega\in k$ with $0<|\omega|<1.$ Let $X$ be a reduced and normal $k$-analytic space. Then $O^{\circ}\simeq \lim\limits_{\leftarrow}O^{\circ}/\omega^n.$

Muhammad Zaigham Zaheer, Arif Mahmood, Marcella Astrid, Seung-Ik Lee

Learning to detect real-world anomalous events through video-level labels is a challenging task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we propose a weakly supervised anomaly detection method which has manifold contributions including1) a random batch based training procedure to reduce inter-batch correlation, 2)

Jean-Claude Cuenin, Isroil A. Ikromov

We establish sharp time decay estimates for the the Klein-Gordon equation on the cubic lattice in dimensions $d=2,3,4$. The $\ell^1\to\ell^{\infty}$ dispersive decay rate is $|t|^{-3/4}$ for $d=2$, $|t|^{-7/6}$ for $d=3$ and $|t|^{-3/2}\log|t|$ for $d=4$. These decay rates are faster than conjectured by Kevrekidis and Stefanov (2005). The proof relies on osc

Alejandro Sobrino, Eduardo C. Garrido-Merchan, Cristina Puente

Imagery is frequently used to model, represent and communicate knowledge. In particular, graphs are one of the most powerful tools, being able to represent relations between objects. Causal relations are frequently represented by directed graphs, with nodes denoting causes and links denoting causal influence. A causal graph is a skeletal picture, showing cau

Carlos Arango Duque, Adrien Bartoli

The vast majority of mesh-based modelling applications iteratively transform the mesh vertices under prescribed geometric conditions. This occurs in particular in methods cycling through the constraint set such as Position-Based Dynamics (PBD). A common case is the approximate local area preservation of triangular 2D meshes under external editing constraints

Michael A. Lepori, R. Thomas McCoy

As the name implies, contextualized representations of language are typically motivated by their ability to encode context. Which aspects of context are captured by such representations? We introduce an approach to address this question using Representational Similarity Analysis (RSA). As case studies, we investigate the degree to which a verb embedding enco

T. Mufakharov, A. Mikhailov, Yu. Sotnikova, M. Mingaliev

We report the first detection at 4.7 and 8.2 GHz with the RATAN-600 radio telescope of the source PSO J047.4478+27.2992, which has been announced as a blazar at z=6.1. The average flux density is $12\pm3$ and $8\pm4$ mJy at 4.7 and 8.2 GHz respectively, and an upper limit is estimated as 3 mJy at 11.2 GHz. The light curve at 4.7 GHz, obtained on a time-scale

Dion Häfner, Johannes Gemmrich, Markus Jochum

The occurrence of extreme (rogue) waves in the ocean is for the most part still shrouded in mystery, as the rare nature of these events makes them difficult to analyze with traditional methods. Modern data mining and machine learning methods provide a promising way out, but they typically rely on the availability of massive amounts of well-cleaned data. To f

Itzhak Goldman

Mirror Dark Matter (MDM) has been considered as an elegant framework for a particle theory of Dark Matter (DM). It is supposed that there exists a dark sector which is mirror of the ordinary matter. Some MDM models allow particle interactions mirror and ordinary matter, in addition to the gravitational interaction. The possibility of neutron to mirror neutro

Kun Qian, Yuanyuan Wang, Xiaoxiang Zhu

Existing SAR tomography (TomoSAR) algorithms are mostly based on an inversion of the SAR imaging model, which are often computationally expensive. Previous study showed perspective of using data-driven methods like KPCA to decompose the signal and reduce the computational complexity. This paper gives a preliminary demonstration of a new data-driven method ba

Chuanjie Cui, Rujin Ma, Emilio Martínez-Pañeda

We present a new theoretical and numerical framework for modelling mechanically-assisted corrosion in elastic-plastic solids. Both pitting and stress corrosion cracking (SCC) can be captured, as well as the pit-to-crack transition. Localised corrosion is assumed to be dissolution-driven and a formulation grounded upon the film rupture-dissolution-repassivati

Saeed Aljaberi, Timothy O'Leary, Fulvio Forni

Neuronal circuits internally regulate electrical signaling via a host of homeostatic mechanisms. Two prominent mechanisms, synaptic scaling and structural plasticity, are believed to maintain average activity within an operating range by modifying the strength and spatial extent of network connectivity using negative feedback. However, both mechanisms operat

Naoki Kitazawa

The class of special generic maps contains Morse functions with exactly two singular points, characterizing spheres topologically which are not $4$-dimensional and the $4$-dimensional unit sphere. This class is for higher dimensional versions of such functions. Canonical projections of unit spheres are simplest examples and suitable manifolds diffeomorphic t

Valentino Vito, Denny Riama Silaban

For simple graphs $G$ and $H$, their size Ramsey number $\hat{r}(G,H)$ is the smallest possible size of $F$ such that for any red-blue coloring of its edges, $F$ contains either a red $G$ or a blue $H$. Similarly, we can define the connected size Ramsey number ${\hat{r}}_c(G,H)$ by adding the prerequisite that $F$ must be connected. In this paper, we explore

A. Bauer, J. Eisert, C. Wille

We introduce a systematic mathematical language for describing fixed point models and apply it to the study to topological phases of matter. The framework is reminiscent of state-sum models and lattice topological quantum field theories, but is formalised and unified in terms of tensor networks. In contrast to existing tensor network ansatzes for the study o

Roberto Feola, Filippo Giuliani

We present the recent result [8] concerning the existence of quasi-periodic in time traveling waves for the 2d pure gravity water waves system in infinite depth. We provide the first existence result of quasi-periodic water waves solutions bifurcating from a completely resonant elliptic fixed point. The proof is based on a Nash-Moser scheme, Birkhoff normal

Tzu-hsien Huang, Jheng-hao Lin, Chien-yu Huang, Hung-yi Lee

Voice conversion technologies have been greatly improved in recent years with the help of deep learning, but their capabilities of producing natural sounding utterances in different conditions remain unclear. In this paper, we gave a thorough study of the robustness of known VC models. We also modified these models, such as the replacement of speaker embeddi

Alexander S. Kutsenko, Valentina I. Abramenko, Olga K. Kutsenko

A long-standing problem is to predict the future flare productivity of an active region (AR) when it is on the stage of early emergence. The aim of this study is to probe two parameters of the photospheric magnetic field, both derived during the emergence phase of an AR, and to compare them with the flare productivity of the well-developed AR. The parameters

Zhu Cao

One of the central themes in classical cryptography is multi-party computation, which performs joint computation on multiple participants' data while maintaining data privacy. The extension to the quantum regime was proposed in 2002, but despite two decades of research, the current state-of-the-art multi-party quantum computation protocol for a fixed number

Alexander S. Kutsenko

Using magnetic field maps acquired by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory we measured rotation rates of 864 active and 322 ephemeral regions observed between 2010 and 2016. We found smaller magnetic tracers to show a tendency to rotate faster as compared to larger ones. Thus, ephemeral regions exhibit on average the f

Fan Wang

Infrared search and tracking (IRST) system has been widely concerned and applied in the area of national defence. Small target detection under complex background is a very challenging task in the development of system algorithm. Low signal-to-clutter ratio (SCR) of target and the interference caused by irregular background clutter make it difficult to get an

Manisha Banerjee, Sudipta Das, Abdulla Al Mamon, Subhajit Saha

Recently, a novel equation of state (EoS) parameter for dark energy has been introduced which deals with a special mathematical function, known as the Lambert$W$ function. In this paper, we study the effect on the growth of perturbations for the Lambert$W$ dark energy model. We perform the analysis for two different approaches. In the first case we consider

Dario Sansone, Anna Zhu

Using high-quality nation-wide social security data combined with machine learning tools, we develop predictive models of income support receipt intensities for any payment enrolee in the Australian social security system between 2014 and 2018. We show that off-the-shelf machine learning algorithms can significantly improve predictive accuracy compared to si

K. Kjærnes, I. Hallsteinsen, R. V. Chopdekar, M. Moreau

Antiferromagnetic thin films typically exhibit a multi-domain state, and control of the antiferromagnetic N\'eel vector is challenging as antiferromagnetic materials are robust to magnetic perturbations. By relying on anisotropic in-plane strain engineering of epitaxial thin films of the prototypical antiferromagnetic material LaFeO3, uniaxial N\'eel vector

Filippo Giuliani, Marcel Guardia, Pau Martin, Stefano Pasquali

The aim of this note is to present the recent results in [16] where we provide the existence of solutions of some nonlinear resonant PDEs on the 2-dimensional torus exchanging energy among Fourier modes in a \emph{chaotic-like} way. We say that a transition of energy is \emph{chaotic-like} if either the choice of activated modes or the time spent in each tra

L. Desplat, S. Meyer, J. Bouaziz, P. M. Buhl

We show how a Dzyaloshinskii-Moriya interaction can be generated in an ultrathin metal film from the induced internal electric field created by an ultrashort electromagnetic pulse. This interaction does not require structural inversion-symmetry breaking, and its amplitude can be tuned depending on the amplitude of the field. We perform first-principles calcu

Victor Snaith

In this brief essay a construction of the $2$-variable L-function of Langlands is sketched in terms of monomial resolutions of admissible representations of reductive locally $p$-adic Lie groups.

Kristoffer Rypdal, Filippo Maria Bianchi, Martin Rypdal

As of November 2020, the number of COVID-19 cases is increasing rapidly in many countries. In Europe, the virus spread slowed considerably in the late spring due to strict lockdown, but a second wave of the pandemic grew throughout the fall. In this study, we first reconstruct the time evolution of the effective reproduction numbers ${\cal R}(t)$ for each co

Projjal Gupta

Internet technologies have made a paradigm shift in the fields of computing and data science and one such paradigm defining change is the Internet of Things or IoT. Nowadays, thousands of household appliances use integrated smart devices which allow remote monitoring and control and also allow intensive computational work such as high end AI-integrated smart

Yi Ren, Biwei Jiang, Ming Yang, Tianding Wang

The aim of this paper is to establish a complete sample of red supergiants (RSGs) in M31 and M33. The member stars of the two galaxies are selected from the near-infrared (NIR) point sources after removing the foreground dwarfs from their obvious branch in the $J-H/H-K$ diagram with the archival photometric data taken by the UKIRT/WFCAM. This separation by N

Dario Raimo, Alessandro Sarracino, Lucilla de Arcangelis

Experimental and numerical results suggest that the brain can be viewed as a system acting close to a critical point, as confirmed by scale-free distributions of relevant quantities in a variety of different systems and models. Less attention has received the investigation of the temporal correlation functions in brain activity in different, healthy and path

Hongwei Liu, Jingge Liu

In this paper we introduce the notion of $\lambda$-constacyclic codes over finite rings $R$ for arbitary element $\lambda$ of $R$. We study the non-invertible-element constacyclic codes (NIE-constacyclic codes) over finite principal ideal rings (PIRs). We determine the algebraic structures of all NIE-constacyclic codes over finite chain rings, give the uniqu

Zuzana Došlá, Serena Matucci, Pavel Řehák

A boundary value problem on an unbounded domain, associated to difference equations with the Euclidean mean curvature operator is considered. The existence of solutions which are positive on the whole domain and decaying at infinity is examined by proving new Sturm comparison theorems for linear difference equations and using a fixed point approach based on

Koen Zandberg, Emmanuel Baccelli

Virtual machines (VM) are widely used to host and isolate software modules. However, extremely small memory and low-energy budgets have so far prevented wide use of VMs on typical microcontroller-based IoT devices. In this paper, we explore the potential of two minimal VM approaches on such low-power hardware. We design rBPF, a register-based VM based on ext

Yuhan Wang, Zijian Lei, Liang Lan

Count-sketch is a popular matrix sketching algorithm that can produce a sketch of an input data matrix X in O(nnz(X))time where nnz(X) denotes the number of non-zero entries in X. The sketched matrix will be much smaller than X while preserving most of its properties. Therefore, count-sketch is widely used for addressing high-dimensionality challenge in mach

Ranadip Gangopadhyay, Anjali Shriwastawa, Bankteshwar Tiwari

In this paper we study warped product Finsler metrics and show that the notion of isotropic $E$-curvature and isotropic $S$-curvature are equivalent for this class of metrics.

Alberto Megías, Andrés Santos

Whereas the original Boltzmann's $H$-theorem applies to elastic collisions, its rigorous generalization to the inelastic case is still lacking. Nonetheless, it has been conjectured in the literature that the relative entropy of the velocity distribution function with respect to the homogeneous cooling state (HCS) represents an adequate nonequilibrium entropy

Thi Kim Hue Nguyen, Koen Van den Berge, Monica Chiogna, Davide Risso

The problem of estimating the structure of a graph from observed data is of growing interest in the context of high-throughput genomic data, and single-cell RNA sequencing in particular. These, however, are challenging applications, since the data consist of high-dimensional counts with high variance and over-abundance of zeros. Here, we present a general fr

Lukas Mauch, Stephen Tiedemann, Javier Alonso Garcia, Bac Nguyen Cong

Recently, predictor-based algorithms emerged as a promising approach for neural architecture search (NAS). For NAS, we typically have to calculate the validation accuracy of a large number of Deep Neural Networks (DNNs), what is computationally complex. Predictor-based NAS algorithms address this problem. They train a proxy model that can infer the validatio

Núria Salvador-Rusiñol, Michael. A. Beasley, Alexandre Vazdekis, Francesco La Barbera

Central cluster galaxies are the largest and most massive galaxies in the Universe. Although they host very old stellar populations, several studies found the existence of blue cores in some BCGs indicating ongoing star formation. We analyse VLT/X-Shooter stacked spectra of 6 nearby massive central galaxies with high central velocity dispersions ($\sigma$>30

LHCb collaboration, R. Aaij, C. Abellán Beteta, T. Ackernley

The CKM angle $\gamma$ is measured for the first time from mixing-induced $CP$ violation between $B^0_s \rightarrow D_s^\mp K^\pm \pi^\pm \pi^\mp$ and $\bar{B}^0_s \rightarrow D_s^\pm K^\mp \pi^\mp \pi^\pm$ decays reconstructed in proton-proton collision data corresponding to an integrated luminosity of 9 ${\rm fb}^{-1}$ recorded with the LHCb detector. A ti

A. M. Mironov

A cryptographic protocol (CP) is a distributed algorithm designed to provide a secure communication in an insecure environment. CPs are used, for example, in electronic payments, electronic voting procedures, database access systems, etc. Errors in the CPs can lead to great financial and social damage, therefore it is necessary to use mathematical methods to

H. Duarte, H. T. Dinani, V. Jacques, J. R. Maze

Several efforts have been made to polarize the nearby nuclear environment of nitrogen vacancy (NV) centers for quantum metrology and quantum information applications. Different methods showed different nuclear spin polarization efficiencies and rely on electronic spin polarization associated to the NV center, which in turn crucially depends on the inter-syst

Min Feng, Kaishun Wang, Yuefeng Yang

Using the two way distance, we introduce the concepts of weak metric dimension of a strongly connected digraph $\Gamma$. We first establish lower and upper bounds for the number of arcs in $\Gamma$ by using the diameter and weak metric dimension of $\Gamma$, and characterize all digraphs attaining the lower or upper bound. Then we study a digraph with weak m

Qing Liao, Charly Leblanc, Jiahuan Ren, Feng Li

The geometry of Hamiltonian's eigenstates is encoded in the quantum geometric tensor (QGT). It contains both the Berry curvature, central to the description of topological matter and the quantum metric. So far the full QGT has been measured only in Hermitian systems, where the role of the quantum metric is mostly shown to determine corrections to physical ef

Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo

In this paper, we propose an adaptive smoothing spline (AdaSS) estimator for the function-on-function linear regression model where each value of the response, at any domain point, depends on the full trajectory of the predictor. The AdaSS estimator is obtained by the optimization of an objective function with two spatially adaptive penalties, based on initi

Gabriele Restuccia, Hannes Tschofenig, Emmanuel Baccelli

Similarly to elsewhere on the Internet, practical security in the Internet of Things (IoT) is achieved by combining an array of mechanisms, at work at all layers of the protocol stack, in system software, and in hardware. Standard protocols such as Datagram Transport Layer Security (DTLS 1.2) and Transport Layer Security (TLS 1.2) are often recommended to se

Vaibhav Gadre

We consider the Weil--Petersson (WP) metric on the modular surface. We lift WP geodesics to the universal cover of the modular surface and analyse geometric properties of the lifts as paths in the hyperbolic metric on the universal cover. For any pair of distinct points in the thick part of the universal cover, we prove that the WP and hyperbolic geodesic se