November 2020 arXiv papers — page 5

Rajius Idzalika

This empirical study estimates resilience (adaptive capacity) around the periods of the 2013 heavy flood in Cambodia. We use nearly 1.2 million microfinance institution (MFI) customer data and implement the unsupervised learning method. Our results highlight the opportunity to develop resilience by having a better understanding of which areas are likely to b

Grigori Rozenblum, Eugene Shargorodsky

In a domain $\Omega\subset \mathbb{R}^{\mathbf{N}}$ we consider a selfadjoint operator $\mathbf{T}=\mathfrak{A}^*P\mathfrak{A} ,$ where $\mathfrak{A}$ is a pseudodifferential operator of order $-l=-\mathbf{N}/2$ and $P=V\mu_{\Sigma}$ is a singular signed measure in $\Omega$ concentrated on a Lipschitz surface $\Sigma$ of dimension $d<\mathbf{N}$, absolutely

Kosuke Fukui, Rafael N. Alexander, Peter van Loock

Quantum repeaters are a promising platform for realizing long-distance quantum communication and thus could form the backbone of a secure quantum internet, a scalable quantum network, or a distributed quantum computer. Repeater protocols that encode information in single- or multi-photon states are limited by transmission losses and the cost of implementing

Immanuel Bomze, Markus Gabl

In robust optimization one seeks to make a decision under uncertainty, where the goal is to find the solution with the best worst-case performance. The set of possible realizations of the uncertain data is described by a so-called uncertainty set. In many scenarios, a decision maker may influence the uncertainty regime she is facing, for example, by investin

Yanyang Li, Yingfeng Luo, Ye Lin, Quan Du

Unsupervised Bilingual Dictionary Induction methods based on the initialization and the self-learning have achieved great success in similar language pairs, e.g., English-Spanish. But they still fail and have an accuracy of 0% in many distant language pairs, e.g., English-Japanese. In this work, we show that this failure results from the gap between the actu

Ti Bai, Biling Wang, Dan Nguyen, Bao Wang

Low dose computed tomography (LDCT) is desirable for both diagnostic imaging and image guided interventions. Denoisers are openly used to improve the quality of LDCT. Deep learning (DL)-based denoisers have shown state-of-the-art performance and are becoming one of the mainstream methods. However, there exists two challenges regarding the DL-based denoisers:

Lie Fu, Victoria Hoskins, Simon Pepin Lehalleur

We study the rational Chow motives of certain moduli spaces of vector bundles on a smooth projective curve with additional structure (such as a parabolic structure or Higgs field). In the parabolic case, these moduli spaces depend on a choice of stability condition given by weights; our approach is to use explicit descriptions of variation of this stability

Sahithya Ravi, Samaneh Khoshrou, Mykola Pechenizkiy

In the light of the COVID-19 pandemic, deep learning methods have been widely investigated in detecting COVID-19 from chest X-rays. However, a more pragmatic approach to applying AI methods to a medical diagnosis is designing a framework that facilitates human-machine interaction and expert decision making. Studies have shown that categorization can play an

Luis Felipe M. O. Henriques, Eduardo Morgan, Sergio Colcher, Ruy Luiz Milidiú

Non-Intrusive Load Monitoring (NILM) is a computational technique to estimate the power loads' appliance-by-appliance from the whole consumption measured by a single meter. In this paper, we propose a conditional density estimation model, based on deep neural networks, that joins a Conditional Variational Autoencoder with a Conditional Invertible Normalizing

A. De Riz, J. Hurst, M. Schöbitz, C. Thirion

Two types of domain walls exist in magnetically soft cylindrical nanowires: the transverse-vortex wall (TVW) and the Bloch-point wall (BPW). The latter is expected to prevent the usual Walker breakdown, and thus enable high domain wall speed. We showed recently [M. Sch\"obitz \etal, Phys. Rev. Lett. 123, 217201 (2019)] that the previously overlooked OErsted

Cong Chen, Weikang Wu, Zhi-Ming Yu, Ziyu Chen

Higher-order topological phases and real topological phases are two emerging topics in topological states of matter, which have been attracting considerable research interest. However, it remains a challenge to find realistic materials that can realize these exotic phases. Here, based on first-principles calculations and theoretical analysis, we identify gra

Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan

Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension space while preserving the heterogeneous structures and semantics for downstream tasks (e.g., node/graph classification, node clustering, link prediction)

E. Mossoux, G. Rauw

The study of the X-ray line profiles produced by massive colliding wind binaries is a powerful tool for the characterisation of the stellar winds. We built a self-consistent program for the computation of line profiles named LIFELINE. The resulting theoretical profiles can be compared to the line profile that will be observed with future high-resolution X-ra

Hana Šinkovec, Angelika Geroldinger, Georg Heinze, Rok Blagus

Separation in logistic regression is a common problem causing failure of the iterative estimation process when finding maximum likelihood estimates. Firth's correction (FC) was proposed as a solution, providing estimates also in presence of separation. In this paper we evaluate whether ridge regression (RR) could be considered instead, specifically, if it co

Jose Mario Galicia-Hernandez, Volodymyr Turkowski, Gregorio Hernandez-Cocoletzi, Talat S. Rahman

We provide insights into the atomistic details of the ultrafast spatially-resolved breakdown of the insulating M1 phase in bulk VO2 employing an ab initio technique based on time-dependent density-functional theory and dynamical mean-field theory (DMFT-TDDFT). We find that the system is initially metallized preferentially along the vanadium-dimer chains (CR

Jenny Wong, Christopher J. Davies, Christopher A. Jones

Seismic observations of a slowdown in P wave velocity at the base of Earth's outer core suggest the presence of a stably-stratified region known as the F-layer. This raises an important question: how can light elements that drive the geodynamo pass through the stably-stratified layer without disturbing it? We consider the F-layer as a slurry containing solid

Hans Moritz Günther, Ralf K. Heilmann

Lynx is one of four large-mission concept studies for NASA's 2020 Decadal survey. The design reference mission includes an X-ray grating spectrometer (XGS) based on critical-angle transmission (CAT) gratings. In the past we studied different grating sizes and arrangements using traditional flat CAT gratings with constant bar spacing. However, new technology

AKM Azad, Salem Alyami

Genes/Proteins do not work alone within our body, rather as a group they perform certain activities indicated as pathways. Signalling transduction pathways (STPs) are some of the important pathways that transmit biological signals from protein-to-protein controlling several cellular activities. However, many diseases such as cancer target some of these signa

Marcos A. G. Garcia

A concise summary of out-of-equilibrium dark matter production during post-inflationary reheating is presented. We show that the dark matter relic abundance is in general sensitive to the thermalization rate of the inflaton decay products, and the evolution of the temperature of the subsequently thermalized radiation. We discuss how smoking-gun signals, such

Martin Grohe, Peter Lindner

Probabilistic databases (PDBs) model uncertainty in data in a quantitative way. In the established formal framework, probabilistic (relational) databases are finite probability spaces over relational database instances. This finiteness can clash with intuitive query behavior (Ceylan et al., KR 2016), and with application scenarios that are better modeled by

Derek Lim, René Vidal, Benjamin D. Haeffele

Many state-of-the-art subspace clustering methods follow a two-step process by first constructing an affinity matrix between data points and then applying spectral clustering to this affinity. Most of the research into these methods focuses on the first step of generating the affinity, which often exploits the self-expressive property of linear subspaces, wi

Puranjay Mohan, Aditya Jyoti Paul, Abhay Chirania

The world is going through one of the most dangerous pandemics of all time with the rapid spread of the novel coronavirus (COVID-19). According to the World Health Organisation, the most effective way to thwart the transmission of coronavirus is to wear medical face masks. Monitoring the use of face masks in public places has been a challenge because manual

Hans Moritz Günther, Herman L. Marshall, Alan Garner

X-ray polarimetry is still largely uncharted territory. With the upcoming launch of IXPE, we will learn a lot more about X-ray polarization at energies above 2 keV, but so far no current or accepted mission provides observational capabilities below 2 keV. We present ray-tracing results for a small orbital mission that could be launched within NASA's Pioneer

Olga Martynova, Alexander Okhotin

Graph-walking automata (GWA) traverse graphs by moving between the nodes following the edges, using a finite-state control to decide where to go next. It is known that every GWA can be transformed to a GWA that halts on every input, to a GWA returning to the initial node in order to accept, and to a reversible GWA. This paper establishes lower bounds on the

Ayan Chatterjee, Sundar Gopalakrishnan, Martin Gerdes, Santiago Martinez

With the ongoing heart problems of the population worldwide, the medical requirements of the people are expected to increase. Electrocardiogram (ECG) is one of the proven to capture the heart response signal to assess the electrical and muscular functions of the heart. The ECG setup is expensive and needs proper training, and of course, it is not instant. Fo

Alexander Kupers

In this note we prove that the Fulton-MacPherson compactification of configuration spaces of smooth manifolds can not be extended to topological manifolds in a natural manner, using recent work of Chen and Mann.

Vincenzo Di Gennaro, Davide Franco

Let $X^{2n}\subseteq \mathbb{P} ^N$ be a smooth projective variety. Consider the intersection cohomology complex of the local system $R^{2n-1}\pi{_*}\mathbb{Q}$, where $\pi$ denotes the projection from the universal hyperplane family of $X^{2n}$ to ${(\mathbb{P} ^N)}^{\vee}$. We investigate the cohomology of the intersection cohomology complex $IC(R^{2n-1}\p

Martin Nicholson

A class of log-trigonometric integrals are evaluated in terms of elliptic functions. From this, by using the elliptic integral singular values, one can obtain closed form evaluations of integrals such as \[ \int\limits_0^{{\pi}/{2}}\ln\left(\cosh\frac{x}{\sqrt{3}}+\cos\frac{\ln \left(2\cos x\right)}{\sqrt{3}}\right)dx=\frac{\pi^2}{8\sqrt{3}}-\frac{\pi}{4}\ln

Jun-Qi Guo

We study the dynamics near the central singularity in spherically symmetric collapse of a massless scalar field toward Schwarzschild black hole formation. The equations of motion take different simplified forms in the early and late stages of the singularity curve. We report some fine structures of the analytic solutions and universal features for the metric

Dmitry Dolgopyat, Yeor Hafouta

We obtain asymptotic expansions for local probabilities of partial sums for uniformly bounded independent but not necessarily identically distributed integer-valued random variables. The expansions involve products of polynomials and trigonometric polynomials. Our results do not require any additional assumptions. As an application of our expansions we find

Alexandre Pannier

We consider a family of continuous processes $\{X^\varepsilon\}_{\varepsilon>0}$ which are measurable with respect to a white noise measure, take values in the space of continuous functions $C([0,1]^d:\mathbb{R})$, and have the Wiener chaos expansion \[ X^\varepsilon = \sum_{n=0}^{\infty} \varepsilon^n I_n \big(f_n^{\varepsilon} \big). \] We provide sufficie

Lingxiao Wang, Barry I. Graubard, Hormuzd A. Katki, Yan Li

Most epidemiologic cohorts are composed of volunteers who do not represent the general population. To enable population inference from cohorts, we and others have proposed utilizing probability survey samples as external references to develop a propensity score (PS) for membership in the cohort versus survey. Herein we develop a unified framework for PS-base

Márcia R. Cappelle, Guilherme C. M. Gomes, Vinicius F. dos Santos

A locating-dominating set $D$ of a graph $G$ is a dominating set of $G$ where each vertex not in $D$ has a unique neighborhood in $D$, and the Locating-Dominating Set problem asks if $G$ contains such a dominating set of bounded size. This problem is known to be $\mathsf{NP-hard}$ even on restricted graph classes, such as interval graphs, split graphs, and p

Mahmoud Khaled, Kuize Zhang, Majid Zamani

Symbolic control is an abstraction-based controller synthesis approach that provides, algorithmically, certifiable-by-construction controllers for cyber-physical systems. Symbolic control approaches usually assume that full-state information is available which is not suitable for many real-world applications with partially-observable states or output informa

Kirill Krinkin, Igor Dronnikov

Currently, tens of millions of devices around the world communicate with/ each other via cellular networks. In this paper, we study the stability of network content delivery protocols to the effects of network interference. To conduct the research, a tool was developed that allows testing of protocols, such as TCP, UDP, and QUIC. The analysis and comparison

Nicolò Defenu

An analytically solvable model for quasi-static transformations across quantum critical points featuring Bosonic quasi-particle excitations is presented. The model proves that adiabaticity breakdown is a general feature of universal slow dynamics in these systems. The existence of an "anti-adiabatic" dynamical phase with vanishing ground state fidelity in th

Tatiana Makhalova, Sergei O. Kuznetsov, Amedeo Napoli

Pattern mining is well established in data mining research, especially for mining binary datasets. Surprisingly, there is much less work about numerical pattern mining and this research area remains under-explored. In this paper, we propose Mint, an efficient MDL-based algorithm for mining numerical datasets. The MDL principle is a robust and reliable framew

Wail Mustafa, Christian Kehl, Ulrik Lund Olsen, Søren Kimmer Schou Gregersen

Spectral computed tomography (CT) is an emerging technology capable of providing high chemical specificity, which is crucial for many applications such as detecting threats in luggage. This type of application requires both fast and high-quality image reconstruction and is often based on sparse-view (few) projections. The conventional filtered back projectio

Phillip Martinez, Bart Rosenzweig, Norah M. Hoffmann, Lionel Lacombe

The exact time-dependent potential energy surface driving the nuclear dynamics was recently shown to be a useful tool to understand and interpret the coupling of nuclei, electrons, and photons, in cavity settings. Here we provide a detailed analysis of its structure for exactly-solvable systems that model two phenomena: cavity-induced suppression of proton-c

Alfred Dolich, Chris Miller, Alex Savatovsky, Athipat Thamrongthanyalak

We initiate an investigation of structures on the set of real numbers having the property that path components of definable sets are definable. All o\nobreakdash-\hspace{0pt}minimal structures on $(\mathbb{R},<)$ have the property, as do all expansions of $(\mathbb{R},+,\cdot,\mathbb{N})$. Our main analytic-geometric result is that any such expansion of $(\m

Yasuhiro Suzuki, Jie Huang, Nengchao Wang, Yonghua Ding

This paper deals with the design of the stellarator field with the simple coil set. In order to realize the stellarator field by the simple coil set, the tilted toroidal field coil uses for creating the rotational transform. Sixteen tilted TF coils create the small radial field and large vertical field. With reducing the vertical field of the tilted toroidal

Jiansen He, Bo Cui, Liping Yang, Chuanpeng Hou

Parker Solar Probe (PSP) aims at exploring the nascent solar wind close to the Sun. Meanwhile, PSP is also expected to encounter small objects like comets and asteroids. In this work, we survey the ephemerides to find a chance of recent encounter, and then model the interaction between released dusty plasmas and solar wind plasmas. On 2019 September 2, a com

Peter Albers, Irene Seifert

We consider differential delay equations of the form $\partial_tx(t) = X_{t}(x(t - \tau))$ in $\mathbb{R}^n$, where $(X_t)_{t\in S^1}$ is a time-dependent family of smooth vector fields on $\mathbb{R}^n$ and $\tau$ is a delay parameter. If there is a (suitably non-degenerate) periodic solution $x_0$ of this equation for $\tau=0$, that is without delay, there

Elisabetta Vallarino, Michele Piana, Alberto Sorrentino, Sara Sommariva

The study of functional connectivity from magnetoecenphalographic (MEG) data consists in quantifying the statistical dependencies among time series describing the activity of different neural sources from the magnetic field recorded outside the scalp. This problem can be addressed by utilizing connectivity measures whose computation in the frequency domain o

Yixian Wu

Smartphone overuse has many negative effects on human beings. The function App Limits in our phones, which belongs to behavior reinforcement strategies for overcoming problematic smartphone overuse, constrains users by shutting them completely out of an app after a certain period of time. While it has the effectiveness to some extent, lacking procedural dete

D. V. Bochek, D. A. Yavsin, A. B. Pevtsov, K. B. Samusev

We report the creation of Ge$_2$Sb$_2$Te$_5$ metasurfaces on sapphire substrates by the ablation method and the study of their structural properties by scanning electron microscopy (SEM), atomic force microscopy (AFM), and optical diffraction. The main emphasis is on the optical technique, which boils down to obtaining bright Laue diffraction patterns on a s

Shuangshuang Zhang, Zihe Li, Kun Luo, Julong He

Carbon is likely the most fascinating element of the periodic table because of the diversity of its allotropes stemming from its variable (sp, sp2, and sp3) bonding motifs. Exploration of new forms of carbon has been an eternal theme of contemporary scientific research. Here we report on novel amorphous carbon phases containing high fraction of sp3 bonded at

Ignacio Amores-Sesar, Christian Cachin, Jovana Mićić

The Ripple network is one of the most prominent blockchain platforms and its native XRP token currently has one of the highest cryptocurrency market capitalizations. The Ripple consensus protocol powers this network and is generally considered to a Byzantine fault-tolerant agreement protocol, which can reach consensus in the presence of faulty or malicious n

Eric Canton, Monica Lewis

Let $R$ be a regular ring of prime characteristic $p > 0$, and let $\underline{\mathbf{f}}=f_1,\ldots,f_c$ be a permutable regular sequence of codimension $c\geq 1$. We describe a complex of $R\langle F \rangle$-modules, denoted $\Delta\hspace{-2.65mm}\Delta^\bullet_{\underline{\mathbf{f}}}(R)$, whose terms include $\Delta\hspace{-2.65mm}\Delta^0_{\underline

Gal Lifshitz, Dan Raviv

Steepest descent algorithms, which are commonly used in deep learning, use the gradient as the descent direction, either as-is or after a direction shift using preconditioning. In many scenarios calculating the gradient is numerically hard due to complex or non-differentiable cost functions, specifically next to singular points. In this work we focus on the

Tianyuan Xu, Shanming Ji, Ming Mei, Jingxue Yin

We are concerned with a class of degenerate diffusion equations with time delay describing population dynamics with age structure. In our recent study [{\em Nonlinearity}, 33 (2020), 4013--4029], we established the existence and uniqueness of critical traveling wave for the time-delayed degenerate diffusion equations, and obtained the reducing mechanism of t

Chris Hamilton, Tobias Heinemann

The traditional Chandrasekhar picture of the slow relaxation of stellar systems assumes that stars' orbits are only modified by occasional, uncorrelated, two-body flyby encounters with other stars. However, the long-range nature of gravity means that in reality large numbers of stars can behave collectively. In stable systems this collective behaviour (i) am

Di Zhao, Axel Ringh, Li Qiu, Sei Zhen Khong

In this paper, we propose and solve a low phase-rank approximation problem, which serves as a counterpart to the well-known low-rank approximation problem and the Schmidt-Mirsky theorem. More specifically, a nonzero complex number can be specified by its gain and phase, and while it is generally accepted that the gains of a matrix may be defined by its singu

Qi Wang, Hao-Ran Liu, Roberto Verzicco, Olga Shishkina

Vertical convection is investigated using direct numerical simulations over a wide range of Rayleigh numbers $10^7\le Ra\le10^{14}$ with fixed Prandtl number $Pr=10$, in a two-dimensional convection cell with unit aspect ratio. It is found that the dependence of the mean vertical centre temperature gradient $S$ on $Ra$ shows three different regimes: In regim

Luiz G. A. Alves, Higor Y. D. Sigaki, Matjaz Perc, Haroldo V. Ribeiro

Summarized by the efficient market hypothesis, the idea that stock prices fully reflect all available information is always confronted with the behavior of real-world markets. While there is plenty of evidence indicating and quantifying the efficiency of stock markets, most studies assume this efficiency to be constant over time so that its dynamical and col

Silvan Brauen, Philipp Erpf, Micha Wasem

Based on an axiomatic approach we propose two related novel one-parameter families of indicators of change which put in a relation classical indicators of change such as absolute change, relative change and the log-ratio.

Zakarias Sjöström Dyrefelt

We prove continuity results for new stability thresholds related to uniform K-stability and deduce that uniform K-stability is an open condition in the K\"ahler cone of any compact K\"ahler manifold, thus establishing an algebro-geometric counterpart to a classical result of LeBrun-Simanca for constant scalar curvature (cscK) metrics. This settles a folklore

Miguel Alvarez, Chu Xu, Manuel A. Rodriguez, Abdullah Al-Mamun

This paper examines the degree to which connectivity and automation can potentially reduce the overall fuel consumption of on-road vehicles. The paper begins with a simulation study highlighting the tradeoff between: (i) the fuel that a vehicle can save through speed trajectory shaping, versus (ii) the additional inter-vehicle spacing needed for this traject

Vipin Singh Sehrawat, Foo Yee Yeo, Yvo Desmedt

Secret sharing allows distributing a secret among several parties such that only authorized subsets, specified by an access structure, can reconstruct the secret. Sehrawat and Desmedt (COCOON 2020) introduced hidden access structures, that remain secret until some authorized subset of parties collaborate. However, their scheme assumes semi-honest parties and

Yunfeng Nie, David R. Shafer, Heidi Ottevaere, Hugo Thienpont

Reflective imaging systems form an important part of photonic devices such as spectrometers, telescopes, augmented and virtual reality headsets or lithography platforms. Reflective optics provide unparalleled spectral performance and can be used to reduce overall volume and weight. So far, most reflective designs have focused on two or three reflections, whi

Guilherme C. M. Gomes, Vinicius F. dos Santos

In the Selective Coloring problem, we are given an integer $k$, a graph $G$, and a partition of $V(G)$ into $p$ parts, and the goal is to decide whether or not we can pick exactly one vertex of each part and obtain a $k$-colorable induced subgraph of $G$. This generalization of Vertex Coloring has only recently begun to be studied by Demange et al. [Theoreti

Mikael Beuthe

Dissipation of ocean potential energy is proposed by Tyler (2020) as a new mechanism leading to possible high-power states for Enceladus. I show here that this process actually results from viscoelastic dissipation within the crust. For plausible values of Enceladus's ocean thickness, crustal dissipation can be computed with the standard approach of static d

Jiří Adámek, Chase Ford, Stefan Milius, Lutz Schröder

Finitary monads on $\mathsf{Pos}$ are characterized as the precisely the free-algebra monads of varieties of algebras. These are classes of ordered algebras specified by inequations in context. Analagously, finitary enriched monads on $\mathsf{Pos}$ are characterized: here we work with varieties of coherent algebras which means that their operations are mono

Adam Barker, Martin Swany

Wireless sensor networks (WSN) are characterized by a network of small, battery powered devices, operating remotely with no pre-existing infrastructure. The unique structure of WSN allow for novel approaches to data reduction and energy preservation. This paper presents a modification to the existing Q-routing protocol by providing an alternate action of per

Silvan Weder, Johannes L. Schönberger, Marc Pollefeys, Martin R. Oswald

We present a novel online depth map fusion approach that learns depth map aggregation in a latent feature space. While previous fusion methods use an explicit scene representation like signed distance functions (SDFs), we propose a learned feature representation for the fusion. The key idea is a separation between the scene representation used for the fusion

Jiseon Shin, Youngju Park, Bheema Lingam Chittari, Jeil Jung

Spontaneous orbital magnetism observed in twisted bilayer graphene (tBG) on nearly aligned hexagonal boron nitride (BN) substrate builds on top of the electronic structure resulting from combined G/G and G/BN double moire interfaces. Here we show that tBG/BN commensurate double moire patterns can be classified into two types, each favoring the narrowing of e

Igor Konnov, Marijana Lazić, Ilina Stoilkovska, Josef Widder

Threshold guards are a basic primitive of many fault-tolerant algorithms that solve classical problems in distributed computing, such as reliable broadcast, two-phase commit, and consensus. Moreover, threshold guards can be found in recent blockchain algorithms such as, e.g., Tendermint consensus. In this article, we give an overview of techniques for automa

E. Gügercinoğlu, M. Y. Ge, J. P. Yuan, S. Q. Zhou

We present timing solutions from the Fermi-LAT observations of gamma-ray pulsars PSR J0835$-$4510 (Vela), PSR J1023$-$5746, PSR J2111$+$4606, and PSR J2229$+$6114. Data ranges for each pulsar extend over a decade. From data analysis we have identified a total of 20 glitches, 11 of which are new discoveries. Among them, 15 glitches are large ones with $\Delta

Michal Pándy, Daniel Lenton, Ronald Clark

We demonstrate that challenging shortest path problems can be solved via direct spline regression from a neural network, trained in an unsupervised manner (i.e. without requiring ground truth optimal paths for training). To achieve this, we derive a geometry-dependent optimal cost function whose minima guarantees collision-free solutions. Our method beats st

Kai Benning, Miriam Menzel, Jan Reuter, Markus Axer

In recent years, Independent Component Analysis (ICA) has successfully been applied to remove noise and artifacts in images obtained from Three-dimensional Polarized Light Imaging (3D-PLI) at the mesoscale (i.e., 64 $\mu$m). Here, we present an automatic denoising procedure for gray matter regions that allows to apply the ICA also to microscopic images, with

Yan Yang, Md Zakir Hossain, Tom Gedeon, Shafin Rahman

Interactive facial image manipulation attempts to edit single and multiple face attributes using a photo-realistic face and/or semantic mask as input. In the absence of the photo-realistic image (only sketch/mask available), previous methods only retrieve the original face but ignore the potential of aiding model controllability and diversity in the translat

Taisuke Katayose, Shigeki Matsumoto, Satoshi Shirai

Electroweakly Interacting Massive Particles (EWIMPs), in other words, new massive particles that are charged under the electroweak interaction of the Standard Model (SM), are often predicted in various new physics models. EWIMPs are probed at hadron collider experiments not only by observing their direct productions but also by measuring their quantum effect

Jia Wang, Peter Hannaford, Bryan J Dalton

We present a fully comprehensive multi-mode quantum treatment based on the truncated Wigner approximation (TWA) to study many-body effects and quantum fluctuations on the formation of a discrete time crystal (DTC) in a Bose-Einstein condensate (BEC) bouncing resonantly on an atom mirror, driven at period T. Our theoretical approach avoids the restrictions bo

J. Jacquemin-Ide, G. Lesur, J. Ferreira

Astrophysical disks are likely embedded in an ambient vertical magnetic field. This ambient field is known to drive magneto-rotational turbulence in the disk bulk but is also responsible for the launching of magnetized outflows at the origin of astrophysical jets. The vertical structure and long-term (secular) evolution of such a system lack quantitative pre

Niklas Kühl, Marc Goutier, Lucas Baier, Clemens Wolff

The capabilities of supervised machine learning (SML), especially compared to human abilities, are being discussed in scientific research and in the usage of SML. This study provides an answer to how learning performance differs between humans and machines when there is limited training data. We have designed an experiment in which 44 humans and three differ

Lei Wang, Bin Gao, Xin Liu

We propose a class of multipliers correction methods to minimize a differentiable function over the Stiefel manifold. The proposed methods combine a function value reduction step with a proximal correction step. The former one searches along an arbitrary descent direction in the Euclidean space instead of a vector in the tangent space of the Stiefel manifold

Jean-Baptiste Truong, Pratyush Maini, Robert J. Walls, Nicolas Papernot

Current model extraction attacks assume that the adversary has access to a surrogate dataset with characteristics similar to the proprietary data used to train the victim model. This requirement precludes the use of existing model extraction techniques on valuable models, such as those trained on rare or hard to acquire datasets. In contrast, we propose data

Zhendong Li, Wen Chen, Qingqing Wu, Kunlun Wang

This paper proposes a novel network framework of intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) non-orthogonal multiple access (NOMA) networks, where IRS is used to enhance the NOMA performance and the wireless power transfer (WPT) efficiency of SWIPT. We formulate a problem of minimizing base stati

A. Alia, I. Heckenberger

This work is motivated to study the representation theory of the non-semisimple deformed Fomin-Kirillov algebras $\mathcal{D}_4(\alpha_1, \alpha_2)$. In particular, we consider Gabriel's theorem applications in regard of constructing algebraic presentations.

Muhammad Sadegh Esmaeilian, Marzieh Farhang, Shirin Khodabakhshi

In this work we explore the power of future large-scale surveys to constrain possible deviations from the standard single-field slow-roll inflationary scenario. Specifically, we parametrize possible fluctuations around the almost scale-invariant primordial scalar power spectrum in a model independent way. We then use their imprints on the simulated matter di

Jesús M. Rodríguez-de-Vera, Josefa González-Carrillo, José M. García, Gregorio Bernabé

Left ventricular non-compaction (LVNC) is a rare cardiomyopathy characterized by abnormal trabeculations in the left ventricle cavity. Although traditional computer vision approaches exist for LVNC diagnosis, deep learning-based tools could not be found in the literature. In this paper, a first approach using convolutional neural networks (CNNs) is presented

P. P. Kanevska, S. N. Volkov

The model of the deformation of DNA macromolecule is developed with the accounting of two types of components of deformation: external and internal. External components describe the bend, twist and stretch of the double helix. The internal component - the conformational mobility inside of the double helix. In the work the deformation of DNA macromolecule is

Francisco M. Fernández

We discuss a recent test of the performance of the kinetic energy partition method (KEP) through its application to two separable quantum-mechanical models. We argue that one of the benchmark models is exceedingly simple for testing any realistic approximate method and that almost any reasonable approach yields better results. In the second example our exact

Quentin Giraud, Jérôme Pétri

Context. Pulsars are detected as broadband electromagnetic emitters from the radio wavelength up to high and very high energy in the MeV/GeV and sometimes even in the TeV range. Multi-wavelength phase-resolved spectra and light curves offer an unrivalled opportunity to understand their underlying radiation mechanisms and to localize their emission sites and

Hyun Kyu Kim

In this paper we partially settle Fock-Goncharov's duality conjecture for cluster varieties associated to their moduli spaces of ${\rm G}$-local systems on a punctured surface $\frak{S}$ with boundary data, when ${\rm G}$ is a group of type $A_2$, namely ${\rm SL}_3$ and ${\rm PGL}_3$. Based on Kuperberg's ${\rm SL}_3$-webs, we introduce the notion of ${\rm

Peter Bellmann, Heinke Hihn, Daniel A. Braun, Friedhelm Schwenker

In many real-world pattern recognition scenarios, such as in medical applications, the corresponding classification tasks can be of an imbalanced nature. In the current study, we focus on binary, imbalanced classification tasks, i.e.~binary classification tasks in which one of the two classes is under-represented (minority class) in comparison to the other c

Michael Thorne

$\sigma$-Stable matrices are introduced and it is shown that the real roots of the polynomials comprising the coefficients of the characteristic polynomial indicate the coefficient sign changes. A proof of Obrechkoff is then used to show that the largest real root from the coefficients is the point of stability when the maximal eigenvalue of the $\sigma$-sta

Arvind W. Kiwelekar, Sanil S. Gandhi, Laxaman D. Netak, Shankar B. Deosarkar

Humanitarian Engineers need innovative methods to make technological interventions for solving societal problems. The emerging blockchain technology has the enormous potential to provide effective interventions in various developmental sectors, including Agriculture, Education, Health, and Transportation. In these sectors, mediators have been considered as o

Benjamin Eltzner

Asymptotic theory for M-estimation problems usually focuses on the asymptotic convergence of the sample descriptor, defined as the minimizer of the sample loss function. Here, we explore a related question and formulate asymptotic theory for the minimum value of sample loss, the M-variance. Since the loss function value is always a real number, the asymptoti

Oleg Voynov, Aleksandr Safin, Savva Ignatyev, Evgeny Burnaev

We study the effects of the additional input to deep multi-view stereo methods in the form of low-quality sensor depth. We modify two state-of-the-art deep multi-view stereo methods for using with the input depth. We show that the additional input depth may improve the quality of deep multi-view stereo.

M. Roushan, K. Nozari

Quantum gravitational effects may affect the large scale dynamics of the universe. Phenomenologically, quantum gravitational effect at large distances can be encoded in an extended uncertainty principle that admits a minimal measurable momentum/energy or a maximal length. This maximal length can be considered as the size of the cosmological horizon today. In

Tony Lindeberg

This paper presents a hybrid approach between scale-space theory and deep learning, where a deep learning architecture is constructed by coupling parameterized scale-space operations in cascade. By sharing the learnt parameters between multiple scale channels, and by using the transformation properties of the scale-space primitives under scaling transformati

Mikhail Khovanov, Victor Ostrik, Yakov Kononov

We study generalized Deligne categories and related tensor envelopes for the universal two-dimensional cobordism theories described by rational functions, recently defined by Sazdanovic and one of the authors.

Fei Liu, Zhengdao Yuan, Qinghua Guo, Zhongyong Wang

The orthogonal time frequency space (OTFS) modulation has emerged as a promising modulation scheme for high mobility wireless communications. To enable efficient OTFS detection in the delay-Doppler (DD) domain, the DD domain channels need to be acquired accurately. To achieve the low latency requirement in future wireless communications, the time duration of

Vasily Korovkin, Alexey Makarin

How do severe shocks such as war alter the economy? We study how a country's production network is affected by a devastating but localized conflict. Using unique transaction-level data on Ukrainian railway shipments around the start of the 2014 Russia-Ukraine crisis, we uncover several novel indirect effects of conflict on firms. First, we document substanti

Robert Guirado, Hyoukjun Kwon, Sergi Abadal, Eduard Alarcón

Deep neural network (DNN) models continue to grow in size and complexity, demanding higher computational power to enable real-time inference. To efficiently deliver such computational demands, hardware accelerators are being developed and deployed across scales. This naturally requires an efficient scale-out mechanism for increasing compute density as requir

Sepideh Bazzaz Abkenar, Mostafa Haghi Kashani, Mohammad Akbari, Ebrahim Mahdipour

Nowadays, with the rise of Internet access and mobile devices around the globe, more people are using social networks for collaboration and receiving real-time information. Twitter, the microblogging that is becoming a critical source of communication and news propagation, has grabbed the attention of spammers to distract users. So far, researchers have intr

Vasiliy Stanislavovich Usatyuk

In this Phd thesis discusses modern methods for constructing MET QC-LDPC codes with a given error correction ("waterfall, error-floor") and complexity (parallelism level according circulant size plus scheduler orthogonality of checks) profiles: 1. weight enumerators optimization, protograph construction using Density Evolution, MI (P/Exit-chart) and it appro

Alok Singh, Thoudam Doren Singh, Sivaji Bandyopadhyay

Video description involves the generation of the natural language description of actions, events, and objects in the video. There are various applications of video description by filling the gap between languages and vision for visually impaired people, generating automatic title suggestion based on content, browsing of the video based on the content and vid

Matúš Sulír

To evaluate software maintenance techniques and tools in controlled experiments with human participants, researchers currently use projects and tasks selected on an ad-hoc basis. This can unrealistically favor their tool, and it makes the comparison of results difficult. We suggest a gradual creation of a benchmark repository with projects, tasks, and metada