November 2020 arXiv papers — page 26

Ben Pisanty, Erdal C. Oguz, Cristiano Nisoli, Yair Shokef

Mechanical metamaterials present a promising platform for seemingly impossible mechanics. They often require incompatibility of their elementary building blocks, yet a comprehensive understanding of its role remains elusive. Relying on an analogy to ferromagnetic and antiferromagnetic binary spin interactions, we present a universal approach to identify and

Yue Li, Marc Habermann, Bernhard Thomaszewski, Stelian Coros

Recent monocular human performance capture approaches have shown compelling dense tracking results of the full body from a single RGB camera. However, existing methods either do not estimate clothing at all or model cloth deformation with simple geometric priors instead of taking into account the underlying physical principles. This leads to noticeable artif

Christian Schiffer, Katrin Amunts, Stefan Harmeling, Timo Dickscheid

Cytoarchitectonic maps provide microstructural reference parcellations of the brain, describing its organization in terms of the spatial arrangement of neuronal cell bodies as measured from histological tissue sections. Recent work provided the first automatic segmentations of cytoarchitectonic areas in the visual system using Convolutional Neural Networks.

Sihao Zhao, Xiao-Ping Zhang, Xiaowei Cui, Mingquan Lu

In a time-of-arrival (TOA) or pseudorange based positioning system, user location is obtained by observing multiple anchor nodes (AN) at known positions. Utilizing more than one positioning systems, e.g., combining Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS), brings better positioning accuracy. However, ANs from two systems a

Francesca Foffano, Teresa Scantamburlo, Atia Cortés, Chiara Bissolo

Artificial intelligence (AI) is already part of our daily lives and is playing a key role in defining the economic and social shape of the future. In 2018, the European Commission introduced its AI strategy able to compete in the next years with world powers such as China and US, but relying on the respect of European values and fundamental rights. As a resu

Jana Koehler, Joseph Bürgler, Urs Fontana, Etienne Fux

Cable trees are used in industrial products to transmit energy and information between different product parts. To this date, they are mostly assembled by humans and only few automated manufacturing solutions exist using complex robotic machines. For these machines, the wiring plan has to be translated into a wiring sequence of cable plugging operations to b

Bruno Duchesne

We exhibit a topological group $G$ with property (T) acting non-elementarily and continuously on the circle. This group is an uncountable totally disconnected closed subgroup of $\operatorname{Homeo}^+(\mathbf{S}^1)$. It has a large unitary dual since it separates points. It comes from homeomorphisms of dendrites and a kaleidoscopic construction. Alternative

Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan, Manfred Eppe

Safe human-robot interactions require robots to be able to learn how to behave appropriately in \sout{humans' world} \rev{spaces populated by people} and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to

Omkar Kumbhar, Elena Sizikova, Najib Majaj, Denis G. Pelli

Neural networks today often recognize objects as well as people do, and thus might serve as models of the human recognition process. However, most such networks provide their answer after a fixed computational effort, whereas human reaction time varies, e.g. from 0.2 to 10 s, depending on the properties of stimulus and task. To model the effect of difficulty

Emil Aas Stoltenberg

In this paper we introduce a mixture cure model with a linear hazard rate regression model for the event times. Cure models are statistical models for event times that take into account that a fraction of the population might never experience the event of interest, this fraction is said to be {`}cured{'}. The population survival function in a mixture cure mo

Christian Schiffer, Hannah Spitzer, Kai Kiwitz, Nina Unger

Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the microstructural organization of the brain, as regional differences in the arrangement and composition of neuronal cells are indicators of changes in connectivity and f

Aoife Bharucha, Diogo Boito, Cédric Méaux

In this paper we consider the decay $D^+\to\pi^+\ell^+\ell^-$, addressing in particular the resonance contributions as well as the relatively large contributions from the weak annihilation diagrams. For the weak annihilation diagrams we include known results from QCD factorisation at low $q^2$ and at high $q^2$, adapting the existing calculation for $B$ deca

Quentin Bonnefoy, Emanuele Gendy, Christophe Grojean

From general analyticity and unitarity requirements on the UV theory, positivity bounds on the Wilson coefficients of the dimension-8 operators composed of 4 fermions and two derivatives appearing in the Standard Model Effective Field Theory have been derived recently. We explore the fate of these bounds in the context of models endowed with a Minimal Flavor

Wolfgang Stammer, Patrick Schramowski, Kristian Kersting

Most explanation methods in deep learning map importance estimates for a model's prediction back to the original input space. These "visual" explanations are often insufficient, as the model's actual concept remains elusive. Moreover, without insights into the model's semantic concept, it is difficult -- if not impossible -- to intervene on the model's behav

Dilshad Surroop, Pascal Combes, Philippe Martin

We propose a procedure to demodulate analog signals encoded by a multicarrier modulator, with slowly-varying carrier shapes. We prove that the asymptotic demodulation error can be made arbitrarily small. The intended application is the "sensorless" control of AC electric motors at or near standstill, through the decoding of the PWM-induced current ripple.

Leo Dostal, Marten Hollm, Andrei V. Metrikine, Apostolos Tsouvalas

This paper aims at investigating the existence of localized stationary waves in the shallow subsurface whose constitutive behaviour is governed by the hyperbolic model, implying non-polynomial nonlinearity and strain-dependent shear modulus. To this end, we derive a novel equation of motion for a nonlinear gradient elasticity model, where the higher-order gr

Georg Wilding, Keimpe Nevenzeel, Rien van de Weygaert, Gert Vegter

Using a set of $\Lambda$CDM simulations of cosmic structure formation, we study the evolving connectivity and changing topological structure of the cosmic web using state-of-the-art tools of multiscale topological data analysis (TDA). We follow the development of the cosmic web topology in terms of the evolution of Betti number curves and feature persistence

Giorgio Kaniadakis, Mauro M. Baldi, Thomas S. Deisboeck, Giulia Grisolia

A great variety of complex physical, natural and artificial systems are governed by statistical distributions, which often follow a standard exponential function in the bulk, while their tail obeys the Pareto power law. The recently introduced $\kappa$-statistics framework predicts distribution functions with this feature. A growing number of applications in

Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos

Autonomous systems need to localize and track surrounding objects in 3D space for safe motion planning. As a result, 3D multi-object tracking (MOT) plays a vital role in autonomous navigation. Most MOT methods use a tracking-by-detection pipeline, which includes object detection and data association processing. However, many approaches detect objects in 2D R

Stefanie Kieninger, Bettina G. Keller

Path reweighting is a principally exact method to estimate dynamic properties from biased simulations - provided that the path probability ratio matches the stochastic integrator used in the simulation. Previously reported path probability ratios match the Euler-Maruyama scheme for overdamped Langevin dynamics. Since MD simulations use Langevin dynamics rath

Kun Wang, Jingya Zhu, Quanlin Jie

In this work, we study the direct-detection constraints of light dark matter in the next-to minimal supersymmetric standard model (NMSSM) with non-universal Higgs masses (NUHM), especially the correlation between higgsino asymmetry and spin-dependent cross section. Finally, we get the following conclusions: (i) The spin-dependent cross section is proportiona

Qianwei Cheng, AKM Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem

Rapid globalization and the interdependence of humanity that engender tremendous in-flow of human migration towards the urban spaces. With advent of high definition satellite images, high resolution data, computational methods such as deep neural network, capable hardware; urban planning is seeing a paradigm shift. Legacy data on urban environments are now b

Giacomo Cacciapaglia, Corentin Cot, Francesco Sannino

Pandemics, like the 1918 Spanish Influenza and COVID-19, spread through regions of the World in subsequent waves. There is, however, no consensus on the origin of this pattern, which may originate from human behaviour rather than from the virus diffusion itself. Time-honoured models of the SIR type or others based on complex networks describe well the expone

Łukasz Dębowski

Inspired by Hilberg's hypothesis, which states that mutual information between blocks for natural language grows like a power law, we seek for links between power-law growth rate of algorithmic mutual information and of some estimator of the unifilar order, i.e., the number of hidden states in the generating stationary ergodic source in its minimal unifilar

Rudolf L. M. van Herten, Amedeo Chiribiri, Marcel Breeuwer, Mitko Veta

Tracer-kinetic models allow for the quantification of kinetic parameters such as blood flow from dynamic contrast-enhanced magnetic resonance (MR) images. Fitting the observed data with multi-compartment exchange models is desirable, as they are physiologically plausible and resolve directly for blood flow and microvascular function. However, the reliability

Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset, Markus Mobius

Although it is under-studied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world. Recently, YouTube's scale has fueled concerns that YouTube users are being radicalized via a combination of biased recommendations and ostensibly apolitical anti-woke channels, both of which

Tadayuki Haraguchi, Kazuhisa Shimakawa

We construct on the category of diffeological spaces a Quillen model structure having smooth weak homotopy equivalences as the class of weak equivalences.

R. V. Maluf, Juliano C. S. Neves

In this work, we present black hole solutions with a cosmological constant in bumblebee gravity, which provides a mechanism for the Lorentz symmetry violation by assuming a nonzero vacuum expectation value for the bumblebee field. From the gravitational point of view, such solutions are spherically symmetric black holes with an effective cosmological constan

Pietro Corvaja, Julian Lawrence Demeio, Ariyan Javanpeykar, Davide Lombardo

We prove new results on the distribution of rational points on ramified covers of abelian varieties over finitely generated fields $k$ of characteristic zero. For example, given a ramified cover $\pi : X \to A$, where $A$ is an abelian variety over $k$ with a dense set of $k$-rational points, we prove that there is a finite-index coset $C \subset A(k)$ such

Nick Iliev, Amit Ranjan Trivedi

We present a novel low latency CMOS hardware accelerator for fully connected (FC) layers in deep neural networks (DNNs). The FC accelerator, FC-ACCL, is based on 128 8x8 or 16x16 processing elements (PEs) for matrix-vector multiplication, and 128 multiply-accumulate (MAC) units integrated with 128 High Bandwidth Memory (HBM) units for storing the pretrained

Bitang Kwrung Tripura, Sonu Kumar, K. Anki Reddy, Julian Talbot

We use numerical simulation to investigate the effect an intruder's shape has on the drag and lift forces that it experiences while moving through a granular medium composed of polydisperse disks of mean diameter d. The intruder velocity,v, was varied from 0.1 \sqrt(dg) to 20 \sqrt(dg). For frictionless particles (\mu= 0.0)there is a gradual increase in drag

Sabah Al-Fedaghi, Manar AlSaraf

Architectural Description (AD) is the backbone that facilitates the implementation and validation of robotic systems. In general, current high-level ADs reflect great variation and lead to various difficulties, including mixing ADs with implementation issues. They lack the qualities of being systematic and coherent, as well as lacking technical-related forms

Yu Zeng, Zhe Lin, Huchuan Lu, Vishal M. Patel

Recent deep generative inpainting methods use attention layers to allow the generator to explicitly borrow feature patches from the known region to complete a missing region. Due to the lack of supervision signals for the correspondence between missing regions and known regions, it may fail to find proper reference features, which often leads to artifacts in

Bach Ngoc Kim, Jose Dolz, Christian Desrosiers, Pierre-Marc Jodoin

We propose a client-server system which allows for the analysis of multi-centric medical images while preserving patient identity. In our approach, the client protects the patient identity by applying a pseudo-random non-linear deformation to the input image. This results into a proxy image which is sent to the server for processing. The server then returns

Lourenço Beirão da Veiga, Lorenzo Mascotto

We analyse the interpolation properties of 2D and 3D low order virtual element face and edge spaces, which generalize N\'ed\'elec and Raviart-Thomas polynomials to polygonal-polyhedral meshes. Moreover, we investigate the stability properties of the associated $L^2$ discrete bilinear forms, which typically appear in the virtual element discretization of prob

Wonwoong Cho, Inyeop Lee, David Inouye

While facial attribute manipulation of 2D images via Generative Adversarial Networks (GANs) has become common in computer vision and graphics due to its many practical uses, research on 3D attribute manipulation is relatively undeveloped. Existing 3D attribute manipulation methods are limited because the same semantic changes are applied to every 3D face. Th

Emad Arasteh Emamzadeh-Hashemi, Ailar Mahdizadeh

Interaction of electromagnetic (EM) waves with human tissue has been a longstanding research topic for electrical and biomedical engineers. However, few numbers of publications discuss the impacts of external EM-waves on neural stimulation and communication through the nervous system. In fact, complex biological neural channels are a main barrier for intact

Clément Dorffer, Thomas Paviet-Salomon, Gilles Le Chenadec, Angélique Drémeau

In underwater acoustics, shallow water environments act as modal dispersive waveguides when considering low-frequency sources. In this context, propagating signals can be described as a sum of few modal components, each of them propagating according to its own wavenumber. Estimating these wavenumbers is of key interest to understand the propagating environme

Mateusz Łącki

Using an optical potential with subwavelength resolution in the form of sharp $\delta$-like peaks, new potential landscapes are created with increased anharmonicity in placement of lattice band energies and more favorable energy scales. In particular, this makes the ultracold atom p-band gas more stable. The article outlines the details of the construction a

Ba-Hien Tran, Simone Rossi, Dimitrios Milios, Maurizio Filippone

The Bayesian treatment of neural networks dictates that a prior distribution is specified over their weight and bias parameters. This poses a challenge because modern neural networks are characterized by a large number of parameters, and the choice of these priors has an uncontrolled effect on the induced functional prior, which is the distribution of the fu

Sylvie Corteel, Jehanne Dousse, Ali K. Uncu

We study the generating functions for cylindric partitions with profile $(c_1,c_2,c_3)$ for all $c_1,c_2,c_3$ such that $c_1+c_2+c_3=5$. This allows us to discover and prove seven new $A_2$ Rogers-Ramanujan identities modulo $8$ with quadruple sums, related with work of Andrews, Schilling, and Warnaar.

Rafał Kucharski, Oded Cats

Two-sided mobility platforms, such as Uber and Lyft, widely emerged in the urban mobility landscape, bringing disruptive changes to transportation systems worldwide. This calls for a simulation framework where researchers from various and across disciplines may introduce models aimed at representing the dynamics of platform-driven urban mobility systems. In

Takahiro Wada

The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to describe the effect of the predictability of dynamics or the pattern of motion stimuli on motion sickness. In the proposed mo

Changjie Fang, Ruirui Zhang, Shenglan Chen

In this paper, we introduce an inertial Tseng's extragradient method for solving multi-valued variational inequalits, in which only one projection is needed at each iterate. We also obtain the strong convergence results of the proposed algorithm, provided that the multi-valued mapping is continuous and pseudomonotone with nonempty compact convex values. More

Wei Ren, Dimos V. Dimarogonas

This paper studies the construction of symbolic abstractions for nonlinear control systems via feedback refinement relation. Both the delay-free and time-delay cases are addressed. For the delay-free case, to reduce the computational complexity, we propose a new approximation approach for the state and input sets based on a static quantizer, and then a novel

Joran van Apeldoorn, Sander Gribling, Yinan Li, Harold Nieuwboer

Matrix scaling and matrix balancing are two basic linear-algebraic problems with a wide variety of applications, such as approximating the permanent, and pre-conditioning linear systems to make them more numerically stable. We study the power and limitations of quantum algorithms for these problems. We provide quantum implementations of two classical (in bot

Jarosław Grytczuk, Szymon Stankiewicz

A \emph{square} is a finite non-empty word consisting of two identical adjacent blocks. A word is \emph{square-free} if it does not contain a square as a factor. In any finite word one may delete the repeated block of a square, obtaining thereby a shorter word. By repeating this process, a square-free word is eventually reached, which we call a \emph{reduct}

Saeed Mahdisoltani, Ramin Golestanian

We study the stochastic dynamics of an electrolyte driven by a uniform external electric field and show that it exhibits generic scale invariance despite the presence of Debye screening. The resulting long-range correlations give rise to a Casimir-like fluctuation-induced force between neutral boundaries that confine the ions; this force is controlled by the

Kangway V. Chuang, Michael J. Keiser

The three-dimensional shape and conformation of small-molecule ligands are critical for biomolecular recognition, yet encoding 3D geometry has not improved ligand-based virtual screening approaches. We describe an end-to-end deep learning approach that operates directly on small-molecule conformational ensembles and identifies key conformational poses of sma

Rodrigo Nemmen, Roberta Duarte, Joao Paulo Navarro

We report the results from our ongoing pilot investigation of the use of deep learning techniques for forecasting the state of turbulent flows onto black holes. Deep neural networks seem to learn well black hole accretion physics and evolve the accretion flow orders of magnitude faster than traditional numerical solvers, while maintaining a reasonable accura

Pierre-Hugo Vial, Paul Magron, Thomas Oberlin, Cédric Févotte

Phase retrieval aims to recover a signal from magnitude or power spectra measurements. It is often addressed by considering a minimization problem involving a quadratic cost function. We propose a different formulation based on Bregman divergences, which encompass divergences that are appropriate for audio signal processing applications. We derive a fast gra

Curtis Atkisson, Kelly Finn

Specialization is a hallmark of humans. Specialization in the real world (with imperfectly sorted partners, imperfectly calibrated supply and demand, and high failure risk) requires redundancy in relationships, which prevents specialists from going hungry when some of their partners fail to capture highly variable food items and derive the most value when di

Wei Ren, Dimos V. Dimarogonas

This paper studies the construction of dynamic symbolic abstractions for nonlinear control systems via dynamic quantization. Since computational complexity is a fundamental problem in the use of discrete abstractions, a dynamic quantizer with a time-varying quantization parameter is first applied to deal with this problem. Due to the dynamic quantizer, a dyn

Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanić

Convolutional neural networks (CNNs) have been tremendously successful in solving imaging inverse problems. To understand their success, an effective strategy is to construct simpler and mathematically more tractable convolutional sparse coding (CSC) models that share essential ingredients with CNNs. Existing CSC methods, however, underperform leading CNNs i

John A. Armstrong, Lyndsay Fletcher

Current post-processing techniques for the correction of atmospheric seeing in solar observations -- such as Speckle interferometry and Phase Diversity methods -- have limitations when it comes to their reconstructive capabilities of solar flare observations. This, combined with the sporadic nature of flares meaning observers cannot wait until seeing conditi

Adrien Devolder, Michèle Desouter-Lecomte, Osman Atabek, Eliane Luc-Koenig

We have studied the formation of ultracold RbSr molecules with laser pulses. After discussing the advantages of the Mott insulator phase for the control with pulses, we present two classes of strategies. The first class involves two electronic states. Two extensions of stimulated Raman adiabatic passage (STIRAP) for multi-level transitions are used : alterna

Benjamin Landon, Christian Noack, Philippe Sosoe

We consider systems of $N$ diffusions in equilibrium interacting through a potential $V$. We study a "height function" which for the special choice $V(x) = \e^{-x}$, coincides with the partition function of a stationary semidiscrete polymer, also known as the (stationary) O'Connell-Yor polymer. For a general class of smooth convex potentials (generalizing th

Wei Ren, Dimos V. Dimarogonas

This paper studies symbolic abstractions for nonlinear control systems using logarithmic quantization. With a logarithmic quantizer, we approximate the state and input sets, and then construct a novel discrete abstraction for nonlinear control systems. A feedback refinement relation between the constructed discrete abstraction and the original system is esta

Nilanjana Kumar

Hints of flavor violation at both charged and neutral current decays of mesons have been observed in experiments such as LHCb, Belle, and BaBar. The anomalies in the result can be addressed in the effective field theory (EFT) framework. The effective operators predict different beyond standard model (BSM) signatures and the four point interaction vertices ca

Mostafa Behtouei, Bruno Spataro, Franco Di Paolo, Alberto Leggieri

In the framework of the Compact Light XLS project, a short ultra-high gradient linearizer working on the third harmonic of the main LINAC frequency is requested. Increasing gradients and reducing dimensions are requirements for XLS and all next generation linear accelerators. Actually, ultra-compact normal conducting accelerating structures, operating in the

Rodrigo A. Vargas-Hernández, Ricky T. Q. Chen, Kenneth A. Jung, Paul Brumer

Inverse design of a property that depends on the steady-state of an open quantum system is commonly done by grid-search type of methods. In this paper we present a new methodology that allows us to compute the gradient of the steady-state of an open quantum system with respect to any parameter of the Hamiltonian using the implicit differentiation theorem. As

Thibault Maho, Teddy Furon, Erwan Le Merrer

Machine learning classifiers are critically prone to evasion attacks. Adversarial examples are slightly modified inputs that are then misclassified, while remaining perceptively close to their originals. Last couple of years have witnessed a striking decrease in the amount of queries a black box attack submits to the target classifier, in order to forge adve

Eduardo de Souza Böer, Olímpio H. Miyagaki

In the present work we investigate the existence and multiplicity of nontrivial solutions for the Choquard Logarithmic equation $(-\Delta)^{\frac{1}{2}} u + au + \lambda (\ln|\cdot|\ast |u|^{2})u = f(u) \textrm{ in } \mathbb{R}$, for $ a>0 $, $ \lambda >0 $ and a nonlinearity $f$ with exponential critical growth. We prove the existence of a nontrivial soluti

Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco

Object segmentation is a key component in the visual system of a robot that performs tasks like grasping and object manipulation, especially in presence of occlusions. Like many other computer vision tasks, the adoption of deep architectures has made available algorithms that perform this task with remarkable performance. However, adoption of such algorithms

Anastasia S. Naumova, Sergey V. Lepeshkin, Pavel V. Bushlanov, Artem R. Oganov

C-H-N-O system is central for organic chemistry and biochemistry, and plays a major role in planetary science (dominating the composition of "ice giants" Uranus and Neptune). The inexhaustible chemical diversity of this system at normal conditions explains it as the basis of all known life, but the chemistry of this system at high pressures and temperatures

Christine Breiner, Chikako Mese

Let $S$ be a surface with a metric $d$ satisfying an upper curvature bound in the sense of Alexandrov (i.e. via triangle comparison). We show that an almost conformal harmonic map from a surface into $(S,d)$ is a branched covering. As a consequence, if $(S,d)$ is homeomorphically equivalent to the 2-sphere $\mathbb S^2$, then it is conformally equivalent to

Thibault Cordier, Tanguy Urvoy, Lina M. Rojas-Barahona, Fabrice Lefèvre

A learning dialogue agent can infer its behaviour from interactions with the users. These interactions can be taken from either human-to-human or human-machine conversations. However, human interactions are scarce and costly, making learning from few interactions essential. One solution to speedup the learning process is to guide the agent's exploration with

Zongze Wu, Dani Lischinski, Eli Shechtman

We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture for image generation, using models pretrained on several different datasets. We first show that StyleSpace, the space of channel-wise style parameters, is significantly more disentangled than the other intermediate latent spaces explored by previous works. Next, we de

Jannik T. Lüthje, Jan C. Schulze, Adrian Caspari, Adel Mhamdi

Nonlinear model predictive control (NMPC) requires accurate and computationally efficient plant models. Our previous work has shown that the classical compartmentalization model reduction approach for distillation columns can be enhanced by replacing parts of the system of equations by artificial neural networks (ANNs) trained on offline solved solutions to

Ivan Chajda, Davide Fazio, Helmut Länger, Antonio Ledda

Paraorthomodular posets are bounded partially ordered set with an antitone involution induced by quantum structures arising from the logico-algebraic approach to quantum mechanics. The aim of the present work is starting a systematic inquiry into paraorthomodular posets theory both from an algebraic and order-theoretic perspective. On the one hand, we show t

Federico Ceola, Elisa Maiettini, Giulia Pasquale, Lorenzo Rosasco

Object detection is a fundamental task for robots to operate in unstructured environments. Today, there are several deep learning algorithms that solve this task with remarkable performance. Unfortunately, training such systems requires several hours of GPU time. For robots, to successfully adapt to changes in the environment or learning new objects, it is a

Kavan Adeshara, Vinayak Elangovan

Face Recognition is most used for biometric user authentication that identifies a user based on his or her facial features. The system is in high demand, as it is used by many businesses and employed in many devices such as smartphones and surveillance cameras. However, one frequent problem that is still observed in this user-verification method is its accur

C. Helman, A. M. Llois, M. Tortarolo

We analyze the influence of the Fermi surface (FS) shape on magnetotransport properties, particularly on the Hall effect in the MnAs compound. It has been observed in MnAs films evidence of opposite conduction polarities for different crystal direction (goniopolarity) and a strong dependence of the carrier type with applied magnetic field. In order to unders

Andrea Tosatto, Georgios Misyris, Adrià Junyent-Ferré, Fei Teng

With Europe dedicated to limiting climate change and greenhouse gas emissions, large shares of Renewable Energy Sources (RES) are being integrated in the national grids, phasing out conventional generation. The new challenges arising from the energy transition will require a better coordination between neighboring system operators to maintain system security

Won-Ki Seo

Functional principal component analysis (FPCA) has played an important role in the development of functional time series analysis. This note investigates how FPCA can be used to analyze cointegrated functional time series and proposes a modification of FPCA as a novel statistical tool. Our modified FPCA not only provides an asymptotically more efficient esti

Julian Neñer, María Fabiana Laguna

In this work we study the individual strategies carried out by agents undergoing transactions in wealth exchange models. We analyze the role of risk propensity in the behavior of the agents and find a critical risk, such that agents with risk above that value always end up losing everything when the system approaches equilibrium. Moreover, we find that the w

Lars Lindemann, Dimos V. Dimarogonas

We study the problem of controlling multi-agent systems under a set of signal temporal logic tasks. Signal temporal logic is a formalism that is used to express time and space constraints for dynamical systems. Recent methods to solve the control synthesis problem for single-agent systems under signal temporal logic tasks are, however, subject to a high comp

Cornelia Spee

Hidden nonlocality is the phenomenon that entangled states can be local in the standard Bell scenario but display nonlocality after local filtering. However, there exist entangled states for which all measurement statistics can be described via a local hidden variable model even after local filtering. In this work we consider the scenario that measurement ou

Lars Lindemann, Dipankar Maity, John S. Baras, Dimos V. Dimarogonas

A framework for the event-triggered control synthesis under signal temporal logic (STL) tasks is proposed. In our previous work, a continuous-time feedback control law was designed, using the prescribed performance control technique, to satisfy STL tasks. We replace this continuous-time feedback control law by an event-triggered controller. The event-trigger

Haojie Pan, Cen Chen, Chengyu Wang, Minghui Qiu

Information-seeking conversation systems are increasingly popular in real-world applications, especially for e-commerce companies. To retrieve appropriate responses for users, it is necessary to compute the matching degrees between candidate responses and users' queries with historical dialogue utterances. As the contexts are usually much longer than respons

Rafał Kucharski, Oded Cats, Julian Sienkiewicz

Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion. Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems. Yet, the potential of ride-pooling rides to serve as

Esteban Roulet, Francesco Vissani

We study the distribution of the energy of the protons that can produce an astrophysical neutrino with a given observed energy, in the TeV--PeV range, both through $pp$ or $p\gamma$ interactions. Due to the increasing multiplicity of the pion production at high center of mass energies, the resulting average proton energies can be much larger than the often u

A. Eugene DePrince

Quantum electrodynamics coupled-cluster (QED-CC) theory is used to model vacuum-field-induced changes to ground-state properties of a series of sodium halide compounds (NaX, X = F, Cl, Br, I) strongly coupled to an optical cavity. Ionization potentials (IPs) and electron affinities (EAs) are presented, and it is demonstrated that EAs are easily modulated by

Bappaditya Bhowmik, Nilanjan Das

We explore the Bohr inequality involving the Fourier transforms of complex valued integrable and square integrable functions defined on a second countable compact topological group. We also investigate the connection of the Bohr phenomenon with a modulus of convexity of the space of bounded linear operators defined on a complex Hilbert space.

Anna Miglio, Véronique Brousseau-Couture, Emile Godbout, Gabriel Antonius

Electronic and optical properties of materials are affected by atomic motion through the electron-phonon interaction: not only band gaps change with temperature, but even at absolute zero temperature, zero-point motion causes band-gap renormalization. We present a large-scale first-principles evaluation of the zero-point renormalization of band edges beyond

Thomas Ratz, Jean-Yves Raty, Guy Brammertz, Bart Vermang

In this work, first principle calculations of Cu$_2$ZnSnS$_4$ (CZTS), Cu$_2$ZnGeS$_4$ (CZGS) and Cu$_2$ZnSiS$_4$ (CZSS) are performed to highlight the impact of the cationic substitution on the structural, electronic and optical properties of kesterite compounds. Direct bandgaps are reported with values of 1.32, 1.89 and 3.06 eV respectively for CZTS, CZGS a

Nat Gopalswamy, Sachiko Akiyama, Pertti Mäkelä, Seiji Yashiro

We present a clear case of a Diffuse Interplanetary Radio Emission (DIRE) event observed during 2002 March 11-12 in association with a fast coronal mass ejection (CME). In the previous event reported [1], there were two CMEs, and a detailed analysis was required to pin down the underlying CME. In the event presented here, the CME association is unambiguous,

Samuel Rivera, Olga Mendoza-Schrock, Ashley Diehl

Aided target recognition (AiTR), the problem of classifying objects from sensor data, is an important problem with applications across industry and defense. While classification algorithms continue to improve, they often require more training data than is available or they do not transfer well to settings not represented in the training set. These problems a

Murad Alim

A difference equation is proved for the Gromov-Witten potential of the resolved conifold. Using the Gopakumar-Vafa resummation of the Gromov-Witten invariants of any Calabi-Yau threefold, it is further shown that similar difference equations are satisfied by the part of the resummed potential containing the contribution of the genus zero GV invariants.

Emily Saltz, Claire Leibowicz, Claire Wardle

Since 2016, the amount of academic research with the keyword "misinformation" has more than doubled [2]. This research often focuses on article headlines shown in artificial testing environments, yet misinformation largely spreads through images and video posts shared in highly-personalized platform contexts. A foundation of qualitative research is necessary

Woongsup Lee, Robert Schober

In this paper, a deep learning (DL) framework for the optimization of the resource allocation in multi-channel cellular systems with device-to-device (D2D) communication is proposed. Thereby, the channel assignment and discrete transmit power levels of the D2D users, which are both integer variables, are optimized to maximize the overall spectral efficiency

Stefania Scheurer, Aline Schäfer Rodrigues Silva, Farid Mohammadi, Johannes Hommel

Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex biogeochemical process in subsurface reservoirs that currently contains strong conceptual uncertainty. This means, several modeling approaches describing the biogeochemical process are plausible and modelers face the

L. Riney, C. Bunker, S. -K. Bac, J. Wang

SrxBi2Se3 is a candidate topological superconductor but its superconductivity requires the intercalation of Sr by into the van-der-Waals gaps of Bi2Se3. We report the synthesis of SrxBi2Se3 thin films by molecular beam epitaxy, and we characterize their structural, vibrational and electrical properties. X-ray diffraction and Raman spectroscopy show evidence

Xiaoyu Zhu, Hefeng Dong, Pierluigi Salvo Rossi, Martin Landrø

In this paper, we propose an interpretable feature selection method based on principal component analysis (PCA) and principal component regression (PCR), which can extract important features for underwater source localization by only introducing the source location without other prior information. This feature selection method is combined with a two-step fra

Georgina Onuma Kalu, Chinemerem Dennis Ikpe, Benjamin Ifeanyichukwu Oruh, Samuel Asante Gyamerah

Life expectancy have been increasing over the past years due to better health care, feeding and conducive environment. To manage future uncertainty related to life expectancy, various insurance institutions have resolved to come up with financial instruments that are indexed-linked to the longevity of the population. These new instrument is known as longevit

Constantin Babenko, Frank Göhmann, Karol K. Kozlowski, Junji Suzuki

We consider the longitudinal dynamical two-point function of the XXZ quantum spin chain in the antiferromagnetic massive regime. It has a series representation based on the form factors of the quantum transfer matrix of the model. The $n$th summand of the series is a multiple integral accounting for all $n$-particle $n$-hole excitations of the quantum transf

Xiang Zhou

Causal mediation analysis concerns the pathways through which a treatment affects an outcome. While most of the mediation literature focuses on settings with a single mediator, a flourishing line of research has examined settings involving multiple mediators, under which path-specific effects (PSEs) are often of interest. We consider estimation of PSEs when

Thilo Hagendorff

Several seminal ethics initiatives have stipulated sets of principles and standards for good technology development in the AI sector. However, widespread criticism has pointed out a lack of practical realization of these principles. Following that, AI ethics underwent a practical turn, but without deviating from the principled approach and the many shortcomi

Norbert Bodendorfer, Fabian Haneder

A coarse graining operation of spatially homogeneous quantum states based on an SU(1,1) Lie group structure has recently been proposed in [1] and used in [2] to compute an explicit renormalisation group flow in the context of loop quantum cosmology. In this note, we explain the group theoretical origin of this procedure and generalise previous results based

Yuji Odaka

For any degenerating Calabi-Yau family, we introduce new limit space which we call galaxy, whose dense subspace is the disjoint union of countably infinite open Calabi-Yau varieties, parametrized by the rational points of the Kontsevich-Soibelman's essential skeleton, while dominated by the Huber adification over the Puiseux series field. Other topics includ