arXiv papers from October 2020

Laurent Desvillettes, Ling-Bing He, Jin-Cheng Jiang

We describe a time-dependent functional involving the relative entropy and the $\dot{H}^1$ seminorm, which decreases along solutions to the spatially homogeneous Landau equation with Coulomb potential. The study of this monotone functionial sheds light on the competition between the dissipation and the nonlinearity for this equation. It enables to obtain new

Dian-Teng Chen, Jia Chen, Xiang-Guo Li, George Christou

This work builds a bridge between density functional theory (DFT) and model interpretations of Anderson's superexchange theory by constructing a $f$-$d$-$p$ model with DFT Wannier functions to enable a direct quantum many-body solution within an embedding approach. When applied to long-range magnetic interactions in a Mn-Ce magnetic molecule, we are able to

Meiyi Ma, John Stankovic, Ezio Bartocci, Lu Feng

Predictive monitoring -- making predictions about future states and monitoring if the predicted states satisfy requirements -- offers a promising paradigm in supporting the decision making of Cyber-Physical Systems (CPS). Existing works of predictive monitoring mostly focus on monitoring individual predictions rather than sequential predictions. We develop a

Zhengyang Zhou, Chaitanya Joshi, Ruoshi Liu, Michael M. Norton

Active nematics are a class of far-from-equilibrium materials characterized by local orientational order of force-generating, anisotropic constitutes. Traditional methods for predicting the dynamics of active nematics rely on hydrodynamic models, which accurately describe idealized flows and many of the steady-state properties, but do not capture certain det

Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun

A fundamental challenge in multiagent reinforcement learning is to learn beneficial behaviors in a shared environment with other simultaneously learning agents. In particular, each agent perceives the environment as effectively non-stationary due to the changing policies of other agents. Moreover, each agent is itself constantly learning, leading to natural

Dongkwan Kim, Pavlo Pylyavskyy

Combinatorics of Kazhdan-Lusztig cells in affine type $A$ was originally developed by Lusztig, Shi, and Xi. Building on their work, Chmutov, Pylyavskyy, and Yudovina introduced the affine matrix-ball construction (abbreviated AMBC) which gives an analog of Robinson-Schensted correspondence for affine symmetric groups. An alternative approach to Kazhdan-Luszt

Shuonan Pei, Mingzhi Zhu

Inrecentyears,ConvolutionalNeuralNet-work(CNN) is quite a popular topic, as it is a powerful andintelligent technique that can be applied in various fields.The YOLO is a technique that uses the algorithms for real-time text detection tasks. However, issues like, photometricdistortion and geometric distortion, could affect the systemYOLO accuracy and cause sy

Jialu Wang, Yang Liu, Caleb Levy

This work examines how to train fair classifiers in settings where training labels are corrupted with random noise, and where the error rates of corruption depend both on the label class and on the membership function for a protected subgroup. Heterogeneous label noise models systematic biases towards particular groups when generating annotations. We begin b

Kevin Heng, Christian L. Althaus

Compartmental transmission models have become an invaluable tool to study the dynamics of infectious diseases. The Susceptible-Infectious-Recovered (SIR) model is known to have an exact semi-analytical solution. In the current study, the approach of Harko et al. (2014) is generalised to obtain an approximate semi-analytical solution of the Susceptible-Expose

Ankita Agarwal, Preetham Salehundam, Swati Padhee, William L. Romine

The recent global outbreak of the coronavirus disease (COVID-19) has spread to all corners of the globe. The international travel ban, panic buying, and the need for self-quarantine are among the many other social challenges brought about in this new era. Twitter platforms have been used in various public health studies to identify public opinion about an ev

Ange Lou, Shuyue Guan, Nada Kamona, Murray Loew

Breast cancer is the second leading cause of death for women in the U.S. Early detection of breast cancer is key to higher survival rates of breast cancer patients. We are investigating infrared (IR) thermography as a noninvasive adjunct to mammography for breast cancer screening. IR imaging is radiation-free, pain-free, and non-contact. Automatic segmentati

Md M. Adnan, Darpan Verma, Zhanbo Xia, Nidhin K. Kalarickal

$\beta-Ga_{2}O_{3}$ is an unusual semiconductor where large electric fields (~1-6 MV/cm) can be applied while still maintaining a dominant excitonic absorption peak below its ultra-wide bandgap. This provides a rare opportunity in the solid-state to examine exciton and carrier self-trapping dynamics in the strong-field limit at steady-state. Under sub-bandga

Sajjad Taravati, George V. Eleftheriades

Static metasurfaces have shown to be prominent compact structures for reciprocal and frequency-invariant transformation of electromagnetic waves in space. However, incorporating temporal variation to static metasurfaces would result in dynamic apparatuses which are capable of four-dimensional tailoring of both the spatial and temporal characteristics of elec

Denis Kojevnikov, Kyungchul Song

This note provides a conditional Berry-Esseen bound for the sum of a martingale difference sequence $\{X_i\}_{i=1}^n$ in $\mathbb{R}^d$, $d\ge 1$, adapted to a filtration $\{\mathcal{F}_i\}_{i=1}^n$. We approximate the conditional distribution of $S=\sum_{i=1}^n X_i$ given some $\sigma$-field $\mathcal{F}_0\subset \mathcal{F}_1$ by that of a mean-zero normal

Michael Pollmann

Many events and policies (treatments) occur at specific spatial locations, with researchers interested in their effects on nearby units. I approach the spatial treatment setting from an experimental perspective: What ideal experiment would we design to estimate the causal effects of spatial treatments? This perspective motivates a comparison between units ne

Jiaming Hu, Hongyi Ling, Priyam Parashar, Aayush Naik

In the robotic industry, specular and textureless metallic components are ubiquitous. The 6D pose estimation of such objects with only a monocular RGB camera is difficult because of the absence of rich texture features. Furthermore, the appearance of specularity heavily depends on the camera viewpoint and environmental light conditions making traditional met

Luigi Accardi, Abdessatar Souissi, El Gheteb Soueidy

In this paper, we study the structure of a family of superposition states on tensor algebras. The correlation functions of the considered states are described through a new kind of positive definite kernels valued in the dual of C$^\ast$-algebras, so-called Schur kernels. Mainly, we show the existence of the limiting state of a net of superposition states ov

David Gundana, Hadas Kress-Gazit

We propose a new specification language and control synthesis technique for single and multi-robot high-level tasks; these tasks include timing constraints and reaction to environmental events. Specifically, we define Event-based Signal Temporal Logic (STL) and use it to encode tasks that are reactive to uncontrolled environment events. Our control synthesis

Andrea Oldofredi, Hans Christian Öttinger

Many attempts have been made to provide Quantum Field Theory with conceptually clear and mathematically rigorous foundations; remarkable examples are the Bohmian and the algebraic perspectives respectively. In this essay we introduce the dissipative approach to QFT, a new alternative formulation of the theory explaining the phenomena of particle creation and

Maryam Dialameh, Ali Hamzeh, Hossein Rahmani

Regularization plays a vital role in the context of deep learning by preventing deep neural networks from the danger of overfitting. This paper proposes a novel deep learning regularization method named as DL-Reg, which carefully reduces the nonlinearity of deep networks to a certain extent by explicitly enforcing the network to behave as much linear as poss

Fabian M. Faulstich, Xiaojie Wu, Lin Lin

Molecular orbitals based on the linear combination of Gaussian type orbitals are arguably the most employed discretization in quantum chemistry simulations, both on quantum and classical devices. To circumvent a potentially dense two-body interaction tensor and obtain lower asymptotic costs for quantum simulations of chemistry, the discontinuous Galerkin (DG

Ambrish Dongre, Karan Singhal, Upasak Das

This paper documents the representation of women in Economics academia in India by analyzing the share of women in faculty positions, and their participation in a prestigious conference held annually. Data from the elite institutions shows that the presence of women as the Economics faculty members remains low. Of the authors of the papers which were in the

Qahhar Muhammad Qadir

This letter studies the performance of a single gateway LoRa system in the presence of different interference considering the imperfect orthogonality effect. It utilizes concepts of stochastic geometry to present a low-complexity approximate closed-form model for computing the success and coverage probabilities under these challenging conditions. Monte Carlo

Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan

The use of min-max optimization in adversarial training of deep neural network classifiers and training of generative adversarial networks has motivated the study of nonconvex-nonconcave optimization objectives, which frequently arise in these applications. Unfortunately, recent results have established that even approximate first-order stationary points of

Cao Vien Phung, Admela Jukan

We analyze whether the THz transmission distance can be extended with systematic linear network coding (sRLNC) and a low-bitrate additional channel. While various coding techniques have been proposed to mitigate issues of channel quality, and other techniques have used auxiliary channels to enable an effective THz transmission system configuration, their com

Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Debapriya Banerjee

Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudo labels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learnin

S. I. Ipatov, E. A. Feoktistova, V. V. Svettsov

We compare the number of lunar craters larger than 15 km across and younger than 1.1 Ga to the estimates of the number of craters that could have been formed for 1.1 Ga if the number of near-Earth objects and their orbital elements during that time were close to the corresponding current values. The comparison was performed for craters over the entire lunar

Yajuan Si

Multilevel regression and poststratification (MRP) is a popular method for addressing selection bias in subgroup estimation, with broad applications across fields from social sciences to public health. In this paper, we examine the inferential validity of MRP in finite populations, exploring the impact of poststratification and model specification. The succe

Wenshan Wang, Yaoyu Hu, Sebastian Scherer

We present the first learning-based visual odometry (VO) model, which generalizes to multiple datasets and real-world scenarios and outperforms geometry-based methods in challenging scenes. We achieve this by leveraging the SLAM dataset TartanAir, which provides a large amount of diverse synthetic data in challenging environments. Furthermore, to make our VO

Christos Mantoulidis

We study the spectrum of phase transitions with prescribed mean curvature in Riemannian manifolds. These phase transitions are solutions to an inhomogeneous semilinear elliptic PDE that give rise to diffuse objects (varifolds) that limit to hypersurfaces, possibly with singularities, whose mean curvature is determined by the "prescribed mean curvature" funct

Amir Shanehsazzadeh, David Belanger, David Dohan

Recently, there has been great interest in learning how to best represent proteins, specifically with fixed-length embeddings. Deep learning has become a popular tool for protein representation learning as a model's hidden layers produce potentially useful vector embeddings. TAPE introduced a number of benchmark tasks and showed that semi-supervised learning

Wei Zhang, Hanhan Sun, Christopher Edwards, Datao Gong

We present the design and test results of a Time-to-Digital-Converter (TDC). The TDC will be a part of the readout ASIC, called ETROC, to read out Low-Gain Avalanche Detectors (LGADs) for the CMS Endcap Timing Layer (ETL) of High-Luminosity LHC upgrade. One of the challenges of the ETROC design is that the TDC is required to consume less than 200 W for each

Jason P. Bell, Peter V. Danchev

We consider applications of a finitary version of the Affine Representability theorem, which follows from recent work of Belov-Kanel, Rowen, and Vishne. Using this result we are able to show that when given a finite set of polynomial identities, there is an algorithm that terminates after a finite number of steps which decides whether these identities force

Valerio Faraoni

Using a suitable rescaling of the independent variable, a Lagrangian is found for the nonlinear Vialov equation ruling the longitudinal profiles of glaciers and ice caps in the shallow ice approximation. This leads to a formal analogy between the (rescaled) Vialov equation and the Friedmann equation of relativistic cosmology, which is explored. This context

Yatong Chen, Jialu Wang, Yang Liu

Machine learning systems are often used in settings where individuals adapt their features to obtain a desired outcome. In such settings, strategic behavior leads to a sharp loss in model performance in deployment. In this work, we aim to address this problem by learning classifiers that encourage decision subjects to change their features in a way that lead

Haonan Zhang

The optimal 2-uniform convexity of Schatten classes $S_p, 1<p\le 2$ was first proved by Ball, Carlen and Lieb \cite{BCL94}. In this note we revisit this result using multiple operator integrals and generalized monotone metrics in quantum information theory.

S. Stanley Young, Warren Kindzierski

The US EPA and the WHO claim that PM2.5 is causal of all-cause deaths. Both support and fund research on air quality and health effects. WHO funded a massive systematic review and meta-analyses of air quality and health-effect papers. 1,632 literature papers were reviewed and 196 were selected for meta-analyses. The standard air components, particulate matte

Maurice Pouzet, Imed Zaguia

The age $\mathcal{A}(G)$ of a graph $G$ (undirected and without loops) is the collection of finite induced subgraphs of $G$, considered up to isomorphy and ordered by embeddability. It is well-quasi-ordered (wqo) for this order if it contains no infinite antichain. A graph is \emph{path-minimal} if it contains finite induced paths of unbounded length and eve

T. Guillet, C. Zucchetti, A. Marty, G. Isella

The structure inversion asymmetry at surfaces and interfaces give rise to the Rashba spin-orbit interaction (SOI), that breaks the spin degeneracy of surface or interface states. Hence, when an electric current runs through a surface or interface, this Rashba effect generates an effective magnetic field acting on the electron spin. This provides an additiona

Christof Kuelske, Daniel Meissner

We consider the Curie-Weiss Potts model in zero external field under independent symmetric spin-flip dynamics. We investigate dynamical Gibbs-non-Gibbs transitions for a range of initial inverse temperatures beta<3, which covers the phase transition point beta=4 log 2 [8]. We show that finitely many types of trajectories of bad empirical measures appear, dep

Dorian Chanfi

Given an adjoint semisimple group $G$ over a local field $k$, we prove that the maximal Satake-Berkovich compactification of the Bruhat-Tits building of $G$ can be identified with the one obtained by embedding the building into the Berkovich analytification of the wonderful compactification of $G$, extending previous results of R\'emy, Thuillier and Werner.

Ron Ruimy, Alexey Gorlach, Chen Mechel, Nicholas Rivera

Free electrons provide a powerful tool to probe material properties at atomic-scale spatial resolution. Recent advances in ultrafast electron microscopy enable the manipulation of free electron wavefunctions using laser pulses. It would be of great importance if one could combine the spatial resolution of electron probes with the ability of laser pulses to p

Eduardo González-Alfonso, Miguel Pereira-Santaella, Jacqueline Fischer, Santiago García-Burillo

Galaxies with nuclear bars are believed to efficiently drive gas inward, generating a nuclear starburst and possibly an active galactic nucleus (AGN). We confirm this scenario for the isolated, double-barred, luminous infrared galaxy ESO 320-G030 based on an analysis of Herschel and ALMA spectroscopic observations. Herschel/PACS and SPIRE observations of ESO

Ahmed Ali, Yasser Hifny

Emotion recognition from speech signal based on deep learning is an active research area. Convolutional neural networks (CNNs) may be the dominant method in this area. In this paper, we implement two neural architectures to address this problem. The first architecture is an attention-based CNN-LSTM-DNN model. In this novel architecture, the convolutional lay

Thomas Kober, Malihe Alikhani, Matthew Stone, Mark Steedman

The interpretation of the lexical aspect of verbs in English plays a crucial role for recognizing textual entailment and learning discourse-level inferences. We show that two elementary dimensions of aspectual class, states vs. events, and telic vs. atelic events, can be modelled effectively with distributional semantics. We find that a verb's local context

Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári

A key problem in the theory of meta-learning is to understand how the task distributions influence transfer risk, the expected error of a meta-learner on a new task drawn from the unknown task distribution. In this paper, focusing on fixed design linear regression with Gaussian noise and a Gaussian task (or parameter) distribution, we give distribution-depen

Gábor Czédli

In addition to the unique cover $M^+$ of the variety of modular lattices, we also deal with those twenty-three known covers of $M^+$ that can be extracted from the literature. For $M^+$ and for each of these twenty-three known varieties covering it, we determine what the pair formed by the number of atoms and that of coatoms of a three-generated lattice belo

Fabrizio Cinque

In this paper we study the joint distributions of the telegraph process and its maximum conditioned on the number of changes of direction and the initial velocity. We prove that in the case of positive starting velocity, a form of the reflection principle holds. We call it the negative reflection principle and we generalize it to the paths of the random moti

Yasin Almalioglu, Angel Santamaria-Navarro, Benjamin Morrell, Ali-akbar Agha-mohammadi

In recent years, unsupervised deep learning approaches have received significant attention to estimate the depth and visual odometry (VO) from unlabelled monocular image sequences. However, their performance is limited in challenging environments due to perceptual degradation, occlusions and rapid motions. Moreover, the existing unsupervised methods suffer f

V. M. S. Carrasco, M. C. Gallego, R. Arlt, J. M. Vaquero

Naked-eye sunspot observations (NESO, hereafter) have been recorded for last two millennia, approximately. This kind of records were made around the world, mainly in Asian civilizations, and they are compiled in several catalogues. In this work, we analyze solar activity in days of the 19th century when NESO were recorded. We found that only more than five s

Samantha Moore

Understanding the structure of indecomposable $n$-dimensional persistence modules is a difficult problem, yet is foundational for studying multipersistence. To this end, Buchet and Escolar showed that any finitely presented rectangular $(n-1)$-dimensional persistence module with finite support is a hyperplane restriction of an $n$-dimensional persistence mod

Mike Behrisch

We study unary parts of centraliser clones on the set $\{0,1,2,3\}$, so-called centralising monoids. We describe and count all centralising monoids on the set $\{0,1,2,3\}$ having majority operations as witnesses, and we list the inclusion maximal proper submonoids of the full transformation monoid among them. This extends previous work by Goldstern, Machida

Michela Gravina, Diego Gragnaniello, Luisa Verdoliva, Giovanni Poggi

Lung ultrasound imaging is reaching growing interest from the scientific community. On one side, thanks to its harmlessness and high descriptive power, this kind of diagnostic imaging has been largely adopted in sensitive applications, like the diagnosis and follow-up of preterm newborns in neonatal intensive care units. On the other side, state-of-the-art i

Neil Yeung, Jonathan Lai, Jiebo Luo

In spite of a growing body of scientific evidence on the effectiveness of individual face mask usage for reducing transmission rates, individual face mask usage has become a highly polarized topic within the United States. A series of policy shifts by various governmental bodies have been speculated to have contributed to the polarization of face masks. A ty

Atreyee Kundu

This paper deals with stability of discrete-time switched linear systems whose all subsystems are unstable. We present sufficient conditions on the subsystems matrices such that a switched system is globally exponentially stable under a set of purely time-dependent switching signals that are allowed to activate all subsystems. The main apparatuses for our an

Trideba Padhi, Astik Biswas, Febe De Wet, Ewald van der Westhuizen

In this work, we explore the benefits of using multilingual bottleneck features (mBNF) in acoustic modelling for the automatic speech recognition of code-switched (CS) speech in African languages. The unavailability of annotated corpora in the languages of interest has always been a primary challenge when developing speech recognition systems for this severe

Daniel Estrada

This paper addresses the ways AI ethics research operates on an ideology of ideal theory, in the sense discussed by Mills (2005) and recently applied to AI ethics by Fazelpour \& Lipton (2020). I address the structural and methodological conditions that attract AI ethics researchers to ideal theorizing, and the consequences this approach has for the quality

Ella Rabinovich, Hila Gonen, Suzanne Stevenson

A large body of research on gender-linked language has established foundations regarding cross-gender differences in lexical, emotional, and topical preferences, along with their sociological underpinnings. We compile a novel, large and diverse corpus of spontaneous linguistic productions annotated with speakers' gender, and perform a first large-scale empir

Jon González-Sánchez, Andoni Zozaya

We prove that the $\mathbb{F}_p[[t]]$-standard Hausdorff spectrum of a compact $\mathbb{F}_p[[t]]$-analytic group contains a real interval and that it coincides with the full unit interval when the group is soluble. Moreover, we show that the $\mathbb{F}_p[[t]]$-standard Hausdorff spectrum of classical Chevalley groups over $\mathbb{F}_p[[t]]$ is not full, s

P. Pfeffer, W. Zawadzki, K. Dybko

Transmission of electrons across a rectangular barrier of IV-VI semiconductor compounds is considered. Conduction electrons arrive at the barrier and are reflected or transmitted through it depending on the relative values of the barrier potential $V_b$ and the electron energy $E$. The theory, in close analogy to the Dirac four component spinors, accounts fo

Lucas das Dores

Consider the scheme parametrizing non-constant morphisms from a fixed projective curve to a projective surface. There is a rational map between this scheme and the Chow variety of $1$-cycles on the surface. We prove that, if the curve is non-singular, then this rational map is a morphism. As a consequence, we obtain that, if the surface is rational and we fi

Lucas das Dores

Let $X$ be a fixed projective scheme which is flat over a base scheme $S$. The association taking a quasi-projective $S$-scheme $Y$ to the scheme parametrizing $S$-morphisms from $X$ to $Y$ is functorial. We prove that this functor preserves limits, and both open and closed immersions. As an application, we determine a partition of schemes parametrizing rati

Ana Fernández-Guillamón, Emilio Gómez-Lázaro, Angel Molina-García

Traditionally, power system's inertia has been estimated according to the rotating masses directly connected to the grid. However, a new generation mix scenario is currently identified, where conventional supply-side is gradually replaced by renewable sources decoupled from the grid by electronic converters (i.e., wind and photovoltaic power plants). Due to

Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael I. Jordan

We study exploration in stochastic multi-armed bandits when we have access to a divisible resource that can be allocated in varying amounts to arm pulls. We focus in particular on the allocation of distributed computing resources, where we may obtain results faster by allocating more resources per pull, but might have reduced throughput due to nonlinear scal

Zona Kostic, Jared Jessup, Jeffrey Baglioni, Nathan Weeks

An innumerable number of individual choices go into discovering a new book. There are unmistakably two groups of booklovers: those who like to search online, follow other people's latest readings, or simply react to a system's recommendations; and those who love to wander between library stacks, lose themselves behind bookstore shelves, or simply hide behind

Michael Kohler, Adam Krzyzak

A regression problem with dependent data is considered. Regularity assumptions on the dependency of the data are introduced, and it is shown that under suitable structural assumptions on the regression function a deep recurrent neural network estimate is able to circumvent the curse of dimensionality.

Sonia Ghayem, Reza Foudazi

In this paper, we propose a conceptual framework to identify the key dimensions affecting behavioral intention to bank umbilical cord blood in Iran. We examine the impact of awareness, reference group, usability, disease history, and price on perceived risk and behavioral intention to use umbilical cord blood banking service. To evaluate the proposed model o

P. N. Bibikov

Using the truncated form factor expansion the low-temperature asymptotics for the transverse dynamical structure factor of the magnetically polarized $XX$ chain is studied. Unlike the previous paper we do not use the representation of structure factor in terms of the corresponding magnetic susceptibility. This enables to obtain correct results at small and n

Khemraj Shukla, Jesse Chan, Maarten V. de Hoop

Wave propagation in real media is affected by various non-trivial physical phenomena, e.g., anisotropy, an-elasticity and dissipation. Assumptions on the stress-strain relationship are an integral part of seismic modeling and determine the deformation and relaxation of the medium. Stress-strain relationships based on simplified rheologies will incorrectly pr

Andrey A. Kurakin, Sergey G. Rubin

We consider the scalar field solitons and their interaction with the fermions in the early Universe. The analytical form of the reflection coefficient is obtained. The fermion mass is a function of the distance between the fermion and the soliton (wall). The function was approximated by the Woods-Saxon potential.

Ping Wang, Jizong Peng, Marco Pedersoli, Yuanfeng Zhou

Deep co-training has recently been proposed as an effective approach for image segmentation when annotated data is scarce. In this paper, we improve existing approaches for semi-supervised segmentation with a self-paced and self-consistent co-training method. To help distillate information from unlabeled images, we first design a self-paced learning strategy

Harsha Blumer, Samar Safi-Harb

Swift J1818.0-1607 is a new radio-loud magnetar discovered by the Swift Burst Alert Telescope on 2020 March 12. It has a magnetic field B~2.5e14 G, spin-down luminosity of 7.2e35 ergs/s, and characteristic age of ~470yr. Here we report on the Chandra observations of Swift J1818.0-1607, which allowed for a high-resolution imaging and spectroscopic study of th

Azadeh Parvaneh, Afshin Parvardeh, Rahul Roy

We study a system of coalescing random walks on the integer lattice $\mathbb{Z}^{d}$ in which the walk is oriented in the $d$-th direction and follows certain specified rules. We first study the geometry of the paths and show that, almost surely, the paths from a graph consisting of just one tree for dimentions $d=2,3$ and infinitely many disjoint trees for

Olivia Jeans, Jozef Širáň

An edge-biregular map arises as a smooth normal quotient of a unique index-two subgroup of a full triangle group acting with two edge-orbits. We give a classification of all finite edge-biregular maps on surfaces of negative prime Euler characteristic.

Fan Yin, Domarin Khago, Rachel W. Martin, Carter T. Butts

Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactio

Jhony Kaesemodel Pontes, James Hays, Simon Lucey

Scene flow is the three-dimensional (3D) motion field of a scene. It provides information about the spatial arrangement and rate of change of objects in dynamic environments. Current learning-based approaches seek to estimate the scene flow directly from point clouds and have achieved state-of-the-art performance. However, supervised learning methods are inh

Amirahmad Chapnevis, Babak Sadeghiyan

Intersection detection between three-dimensional bodies has various applications in computer graphics, video game development, robotics as well as military industries. In some respects, entities do not want to disclose sensitive information about themselves, including their location. In this paper, we present a secure two-party protocol to determine the exis

Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, Ramesh Pathirana

Analyzing the sentiments of legal opinions available in Legal Opinion Texts can facilitate several use cases such as legal judgement prediction, contradictory statements identification and party-based sentiment analysis. However, the task of developing a legal domain specific sentiment annotator is challenging due to resource constraints such as lack of doma

Rebekah Herrman, Peter van Hintum, Stephen G. Z. Smith

In this paper, we consider a variant of the cops and robbers game on a graph, introduced by Kinnersley and Peterson, in which every time the robber uses an edge, it is removed from the graph, known as bridge-burning cops and robbers. In particular, we study the maximum time it takes the cops to capture the robber.

Yen-Hao Chen, Da-Yi Wu, Tsung-Han Wu, Hung-yi Lee

Recently, voice conversion (VC) has been widely studied. Many VC systems use disentangle-based learning techniques to separate the speaker and the linguistic content information from a speech signal. Subsequently, they convert the voice by changing the speaker information to that of the target speaker. To prevent the speaker information from leaking into the

Xinyue Evelyn Zhao, Wenrui Hao, Bei Hu

Free boundary problems deal with systems of partial differential equations, where the domain boundaries are apriori unknown. Due to this special characteristic, it is challenging to solve free boundary problems either theoretically or numerically. In this paper, we develop a novel approach for solving a modified Hele-Shaw problem based on neural network disc

Yûsuke Okuyama

We show that a rational function $f$ of degree $>1$ on the projective line over an algebraically closed field that is complete with respect to a non-trivial and non-archimedean absolute value has no potentially good reductions if and only if the Berkovich Julia set of $f$ is uniformly perfect. As an application, a uniform regularity of the boundary of each B

Nenad Teofanov, Joachim Toft, Patrik Wahlberg

We study the link between pseudo-differential operators and Wick operators via the Bargmann transform. We deduce a formula for the symbol of the Wick operator in terms of the short-time Fourier transform of the Weyl symbol. This gives characterizations of Wick symbols of pseudo-differential operators of Shubin type and of infinite order, and results on compo

Viktor Stojkoski, Trifce Sandev, Lasko Basnarkov, Ljupco Kocarev

Classical option pricing schemes assume that the value of a financial asset follows a geometric Brownian motion (GBM). However, a growing body of studies suggest that a simple GBM trajectory is not an adequate representation for asset dynamics due to irregularities found when comparing its properties with empirical distributions. As a solution, we develop a

Min Guo, Shiqi Xia, Nan Wang, Daohong Song

We study both theoretically and experimentally the effect of nonlinearity on topologically protected linear interface modes in a photonic Su-Schrieffer-Heeger (SSH) lattice. It is shown that under either focusing or defocusing nonlinearity, this linear topological mode of the SSH lattice turns into a family of topological gap solitons. These solitons are sta

S. D. Pogorilyy, A. A. Kramov

Due to the growing role of the SEO technologies, it is necessary to perform an automated analysis of the article's quality. Such approach helps both to return the most intelligible pages for the user's query and to raise the web sites positions to the top of query results. An automated assessment of a coherence is a part of the complex analysis of the text.

Søren Fournais

We give a short proof of Bose Einstein Condensation of dilute Bose gases on length scales much longer than the Gross-Pitaevskii scale.

Niklas Dexheimer, Claudia Strauch, Lukas Trottner

Up to now, the nonparametric analysis of multidimensional continuous-time Markov processes has focussed strongly on specific model choices, mostly related to symmetry of the semigroup. While this approach allows to study the performance of estimators for the characteristics of the process in the minimax sense, it restricts the applicability of results to a r

Liang Liao, Stephen John Maybank

We consider a novel backward-compatible paradigm of general data analytics over a recently-reported semisimple algebra (called t-algebra). We study the abstract algebraic framework over the t-algebra by representing the elements of t-algebra by fix-sized multi-way arrays of complex numbers and the algebraic structure over the t-algebra by a collection of dir

Maria Amarakristi Onyido, Wenxian Shen

This series of two papers is devoted to the study of the principal spectral theory of nonlocal dispersal operators with almost periodic dependence and the study of the asymptotic dynamics of nonlinear nonlocal dispersal equations with almost periodic dependence. In this first part of the series, we investigate the principal spectral theory of nonlocal disper

B. G. Zakharov

We perform an analysis of jet quenching in heavy ion collisions at RHIC and LHC energies with the temperature dependent running QCD coupling. Our results show that the $T$-dependent QCD coupling largely eliminates the difference between the optimal values of $\alpha_s$ for the RHIC and LHC energies. It may be viewed as direct evidence of the increase of the

Salomeh Khoeini-Moghaddam, Farzad Omidi, Chandrima Paul

Recently, it was proposed that a $T\overline{T}$ deformed CFT is dual to a gravity theory in an asymptotically AdS spacetime at finite radial cutoff. Motivated by this proposal, we explore some aspects of Hyperscaling Violating geometries at finite cutoff and zero temperature. We study holographic entanglement entropy, mutual information (HMI) and entangleme

Shuaifeng Li, Liza M. Roger, Lokander Kumar, Nastassja Lewinski

Coral reef ecosystems support significant biological activities and harbor huge diversity, but they are facing a severe crisis driven by anthropogenic activities and climate change. An important behavioral trait of the coral holobiont is coral motion, which may play an essential role in feeding, competition, reproduction, and thus survival and fitness. There

Michael Dowd, Anna Dixon, Benjamin Kinsella

Sustainable Organic Integrated Livelihoods (SOIL) is a research and development organization that aims to increase access to cost-effective household sanitation services in urban communities in Haiti. Each week, SOIL provides over 1,000 households with ecological sanitation toilets, then transports the waste to be transformed into rich compost. However, SOIL

Yanglin Hu, Darya Melnyk, Yuyi Wang, Roger Wattenhofer

Universal quantum computers are the only general purpose quantum computers known that can be implemented as of today. These computers consist of a classical memory component which controls the quantum memory. In this paper, the space complexity of some data stream problems, such as PartialMOD and Equality, is investigated on universal quantum computers. The

Zexi Chen, Jiaxin Guo, Xuecheng Xu, Yunkai Wang

Utilizing the trained model under different conditions without data annotation is attractive for robot applications. Towards this goal, one class of methods is to translate the image style from another environment to the one on which models are trained. In this paper, we propose a weakly-paired setting for the style translation, where the content in the two

Parikha Mehrotra, David Yang, Scott Weigand, Shreyas Sen

The emergence of Human Body Communication (HBC) as an alternative to wireless body area networks (WBAN) has led to the development of small sized, energy efficient and more secure wearable and implantable devices forming a network in and around the body. Previous studies claim that though HBC is comparatively more secure than WBAN, nevertheless, the electrom

Lei Dong, Xiaohui Yuan, Meng Li, Carlo Ratti

Measuring the geographical distribution of economic activity plays a key role in scientific research and policymaking. However, previous studies and data on economic activity either have a coarse spatial resolution or cover a limited time span, and the high-resolution characteristics of socioeconomic dynamics are largely unknown. Here, we construct a dataset

X. Huang, D. Gong, D. Guo, S. Hou

We present a novel design and the test results of a 4-channel driver for an array of Vertical-Cavity Surface-Emitting Lasers (VCSELs). This ASIC, named cpVLAD and fabricated in a 65 nm CMOS technology, has on-chip charge pumps and is for data rates up to 10 Gbps per channel. The charge pumps are implemented to address the issue of voltage margin of the VCSEL

Jantine A. C. Broek, Guillaume Drion

Neuronal excitability is the phenomena that describes action potential generation due to a stimulus input. Commonly, neuronal excitability is divided into two classes: Type I and Type II, both having different properties that affect information processing, such as thresholding and gain scaling. These properties can be mathematically studied using generalised