March 2020 arXiv papers — page 17

Guoxing Ji

Let $\mathfrak A$ be a type 1 subdiagonal algebra in a $\sigma$-finite von Neumann algebra $\mathcal M$ with respect to a faithful normal conditional expectation $\Phi$. We give necessary and sufficient conditions for which $\mathfrak A$ is maximal among the $\sigma$-weakly closed subalgebras of $\mathcal M$. In addition, we show that a type 1 subdiagonal al

Emmanuel Kowalski, Kannan Soundararajan

We prove the equidistribution of subsets of $(\Rr/\Zz)^n$ defined by fractional parts of subsets of~$(\Zz/q\Zz)^n$ that are constructed using the Chinese Remainder Theorem.

A. Deb Ray, Atanu Mondal

In this article, we continue our study of the ring of Baire one functions on a topological space $(X,\tau)$, denoted by $B_1(X)$ and extend the well known M. H. Stones's theorem from $C(X)$ to $B_1(X)$. Introducing the structure space of $B_1(X)$, an analogue of Gelfand Kolmogoroff theorem is established. It is observed that $(X,\tau)$ may not be embedded in

Akhlesh Lakhtakia, Tom G. Mackay

The Lorenz--Mie formulation of electromagnetic scattering by a homogeneous, isotropic, dielectric-magnetic sphere was extended to incorporate topologically insulating surface states characterized by a surface admittance $\gamma$. Closed-form expressions were derived for the expansion coefficients of the scattered field phasors in terms of those of the incide

Xin Lin, Changxing Ding, Jinquan Zeng, Dacheng Tao

Scene graph generation (SGG) aims to detect objects in an image along with their pairwise relationships. There are three key properties of scene graph that have been underexplored in recent works: namely, the edge direction information, the difference in priority between nodes, and the long-tailed distribution of relationships. Accordingly, in this paper, we

Abinash Pujahari, Dilip Singh Sisodia

Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempted visitors to click on a particular link either to monetize the landing page or to spread the false news for sensationalization. The presence of clickbaits on any news aggregator portal may l

Jaehoon Kim, Sang-il Oum

We prove that for every integer $k$, there exists $\varepsilon > 0$ such that for every n-vertex graph $G$ with no pivot-minor isomorphic to $C_k$, there exist disjoint sets $A,B \subseteq V(G)$ such that $|A|,|B| \geq \varepsilon n$, and $A$ is either complete or anticomplete to $B$. This proves the analog of the Erd\H{o}s-Hajnal conjecture for the class of

Sandi Klavžar, Gregor Rus

The general position number ${\rm gp}(G)$ of a connected graph $G$ is the cardinality of a largest set $S$ of vertices such that no three pairwise distinct vertices from $S$ lie on a common geodesic. The $n$-dimensional grid graph $\pn$ is the Cartesian product of $n$ copies of the two-way infinite path $P_\infty$. It is proved that if $n\in {\mathbb N}$, th

Markus Stocker, Louise Darroch, Rolf Krahl, Ted Habermann

Instruments play an essential role in creating research data. Given the importance of instruments and associated metadata to the assessment of data quality and data reuse, globally unique, persistent and resolvable identification of instruments is crucial. The Research Data Alliance Working Group Persistent Identification of Instruments (PIDINST) developed a

Rangrang Zhang

In this paper, we establish the Freidlin-Wentzell type large deviation principles for porous medium-type equations perturbed by small multiplicative noise. The porous medium operator $\Delta (|u|^{m-1}u)$ is allowed. Our proof is based on weak convergence approach.

Xianfang Zeng, Yusu Pan, Mengmeng Wang, Jiangning Zhang

Recent works have shown how realistic talking face images can be obtained under the supervision of geometry guidance, e.g., facial landmark or boundary. To alleviate the demand for manual annotations, in this paper, we propose a novel self-supervised hybrid model (DAE-GAN) that learns how to reenact face naturally given large amounts of unlabeled videos. Our

X. Gratens, Yunbo Ou, J. Moodera, P. H. O. Rappl

We find that in the ferromagnetic semiconductor EuS, near its Curie temperature, a single band-edge photon generates a spin polaron (SP), whose magnetic moment approaches 20,000 Bohr magnetons. This is much larger than the supergiant photoinduced SPs in antiferromagnetic europium chalcogenides, reported previously. The larger SP in ferromagnetic EuS, and sti

Rohit Sarma Sarkar, Amrita Mandal, Bibhas Adhikari

In this paper we extend the study of three state lively quantum walks on cycles by considering the coin operator as a linear sum of permutation matrices, which is a generalization of the Grover matrix. First we provide a complete characterization of orthogonal matrices of order $3\times 3$ which are linear sum of permutation matrices. Consequently, we determ

Eric W. Jones, Parker Shankin-Clarke, Jean M. Carlson

The generalized Lotka-Volterra (gLV) equations model the microbiome as a collection of interacting ecological species. Here we use a particular experimentally-derived gLV model of C. difficile infection (CDI) as a case study to generate methods that are applicable to generic gLV models. We examine how to transition gLV systems between multiple steady states

Yan Wang

Sub-Gaussian and subexponential distributions are introduced and applied to study the fluctuation-response relation out of equilibrium. A bound on the difference in expected values of an arbitrary sub-Gaussian or subexponential physical quantity is established in terms of its sub-Gaussian or subexponential norm. Based on that, we find that the entropy differ

R. G. Hamish Robertson, Vedantha Venkatapathy

The isotope $^{83}$Kr$^m$, a 1.8-hr isomer of stable $^{83}$Kr, has become a standard for the calibration of tritium beta decay experiments to determine neutrino mass. It is also widely used as a low-energy electron source for the calibration of dark-matter experiments. The nominally monoenergetic internal conversion lines are accompanied by shakeup and shak

Zhenguo Liang, Jiawen Luo

We build a new estimate relative with Hermite functions based upon oscillatory integrals and Langer's turning point theory. From it we show that the equation $$ i \partial_t u =-\partial_x^2 u+x^2 u+\epsilon \langle x\rangle^{\mu} W(\nu x,\omega t)u,\quad u=u(t,x),~x\in\mathbb R,~ 0\leq \mu<\frac13,$$ can be reduced in $\mathcal H^1(\mathbb R)$ to an autonom

Pankaj K. Sharma, Budharam Yogesh, Deepika Gupta, Dong In Kim

In this paper, we consider an overlay satellite-terrestrial network (OSTN) where an opportunistically selected terrestrial internet-of-things (IoT) network assists the primary satellite communications as well as accesses the spectrum for its own communications under hybrid interference received from extra-terrestrial sources (ETSs) and terrestrial sources (T

Samuel L. Krushkal

Recently the author has presented a new approach to solving extremal problems of geometric function theory. It involves the Bers isomorphism theorem for Teichmuller spaces of punctured Riemann surfaces. We show here that this approach, combined with quasiconformal theory, can be also applied to nonvanishing holomorphic functions from $H^\infty$. In particula

Yiming Li, Changhong Fu, Fangqiang Ding, Ziyuan Huang

Most existing trackers based on discriminative correlation filters (DCF) try to introduce predefined regularization term to improve the learning of target objects, e.g., by suppressing background learning or by restricting change rate of correlation filters. However, predefined parameters introduce much effort in tuning them and they still fail to adapt to n

Chongzhen Zhang, Jianrui Wang, Gary G. Yen, Chaoqiang Zhao

With widespread applications of artificial intelligence (AI), the capabilities of the perception, understanding, decision-making and control for autonomous systems have improved significantly in the past years. When autonomous systems consider the performance of accuracy and transferability, several AI methods, like adversarial learning, reinforcement learni

Rui Dong, Changyang She, Wibowo Hardjawana, Yonghui Li

To accommodate diverse Quality-of-Service (QoS) requirements in the 5th generation cellular networks, base stations need real-time optimization of radio resources in time-varying network conditions. This brings high computing overheads and long processing delays. In this work, we develop a deep learning framework to approximate the optimal resource allocatio

Yavuz Yaman, Predrag Spasojevic

Beamforming for mmWave communications is well-studied in the PHY based on the channel parameters to develop optimum receiver processing techniques. However, even before signal processing, antenna structure and radiation parameters affect the beamforming performance primarily. For example, in contrast to common belief, narrow beamwidth (bmW) may result in deg

Robert Goldblatt

A topological space is \emph{hereditarily $k$-irresolvable} if none of its subspaces can be partitioned into $k$ dense subsets, We use this notion to provide a topological semantics for a sequence of modal logics whose $n$-th member K4$\mathbb{C}_n$ is characterised by validity in transitive Kripke frames of circumference at most $n$. We show that under the

Hao Shen, Jian Song, Rongfeng Sun, Lihu Xu

We consider a directed polymer model in dimension $1+1$, where the disorder is given by the occupation field of a Poisson system of independent random walks on $\mathbb Z$. In a suitable continuum and weak disorder limit, we show that the family of quenched partition functions of the directed polymer converges to the Stratonovich solution of a multiplicative

Zhenpeng Li, Zhen Zhao, Yuhong Guo, Haifeng Shen

Early Unsupervised Domain Adaptation (UDA) methods have mostly assumed the setting of a single source domain, where all the labeled source data come from the same distribution. However, in practice the labeled data can come from multiple source domains with different distributions. In such scenarios, the single source domain adaptation methods can fail due t

Zhen Zhao, Yuhong Guo, Haifeng Shen, Jieping Ye

In this paper, we propose a novel end-to-end unsupervised deep domain adaptation model for adaptive object detection by exploiting multi-label object recognition as a dual auxiliary task. The model exploits multi-label prediction to reveal the object category information in each image and then uses the prediction results to perform conditional adversarial gl

Ke Wang, Zhiqiang Wang, Wancong Yao

In this paper, we study the boundary feedback stabilization of a quasilinear hyperbolic system with partially dissipative structure. Thanks to this structure, we construct a suitable Lyapunov function which leads to the exponential stability to the equilibrium of the $H^2$ solution. As an application, we also obtain the feedback stabilization for the Saint-V

Himadri S. Samanta, Sumit Sinha, D. Thirumalai

By embedding inert tracer particles (TPs) in a growing multicellular spheroid the local stresses on the cancer cells (CCs) can be measured. In order for this technique to be effective the unknown effect of the dynamics of the TPs on the CCs has to be elucidated to ensure that the TPs do not greatly alter the local stresses on the CCs. We show, using theory a

Ciro Javier Diaz Penedo, Lucas Leonardo Silveira Costa

In this work we deal with the problem of grouping in headlines of the newspaper ABC (Australian Bro-adcasting Corporation) using unsupervised machine learning techniques. We present and discuss the results on the clusters found

E. Gaidos, T. Hirano, A. W. Mann, D. A. Owens

We obtained high-resolution infrared spectroscopy and short-cadence photometry of the 600-800 Myr Praesepe star K2-100 during transits of its 1.67-day planet. This Neptune-size object, discovered by the NASA K2 mission, is an interloper in the "desert" of planets with similar radii on short period orbits. Our observations can be used to understand its origin

Xiequan Fan, Ion Grama, Quansheng Liu, Qi-Man Shao

Let $(X _i)_{i\geq1}$ be a stationary sequence. Denote $m=\lfloor n^\alpha \rfloor, 0< \alpha < 1,$ and $ k=\lfloor n/m \rfloor,$ where $\lfloor a \rfloor$ stands for the integer part of $a.$ Set $S_{j}^\circ = \sum_{i=1}^m X_{m(j-1)+i}, 1\leq j \leq k,$ and $ (V_k^\circ)^2 = \sum_{j=1}^k (S_{j}^\circ)^2.$ We prove a Cram\'er type moderate deviation expansio

Mrinal Kumar, Ben Lee Volk

We show that there is a defining equation of degree at most $\mathsf{poly}(n)$ for the (Zariski closure of the) set of the non-rigid matrices: that is, we show that for every large enough field $\mathbb{F}$, there is a non-zero $n^2$-variate polynomial $P \in \mathbb{F}[x_{1, 1}, \ldots, x_{n, n}]$ of degree at most $\mathsf{poly}(n)$ such that every matrix

Xiequan Fan, Haijuan Hu, Xiaohui Ma

We establish some limit theorems for one-dimensional elephant random walk, including Berry-Esseen bounds, Cram\'{e}r moderate deviations and local limit theorems. These limit theorems can be regarded as refinements of the central limit theorems for the elephant random walk. Moreover, by these limit theorems, we conclude that the domain of attraction of norma

Evgenia Chunikhina, Paul Logan, Yevgeniy Kovchegov, Anatoly Yambartsev

Omics technologies are powerful tools for analyzing patterns in gene expression data for thousands of genes. Due to a number of systematic variations in experiments, the raw gene expression data is often obfuscated by undesirable technical noises. Various normalization techniques were designed in an attempt to remove these non-biological errors prior to any

Anatoli Juditsky, Arkadi Nemirovski, Liyan Xie, Yao Xie

We introduce a new general modeling approach for multivariate discrete event data with categorical interacting marks, which we refer to as marked Bernoulli processes. In the proposed model, the probability of an event of a specific category to occur in a location may be influenced by past events at this and other locations. We do not restrict interactions to

Hongshan Li, Zhongyi Huang

In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation (PDE). We take the European option as an example and conduct numerical experiments using different boundary conditions.

Shanchi Wu, Chen Gong, Chengjie Zuo, Shangbin Li

We propose a novel radio-frequency (RF) receiving architecture based on micro-electro-mechanical system (MEMS) and optical coherent detection module. The architecture converts the received electrical signal into mechanical vibration through the piezoelectric effect and adopts an optical detection module to detect the mechanical vibration. We analyze the resp

Ankit Kumar, Piyush Makhija, Anuj Gupta

Owing to the phenomenal success of BERT on various NLP tasks and benchmark datasets, industry practitioners are actively experimenting with fine-tuning BERT to build NLP applications for solving industry use cases. For most datasets that are used by practitioners to build industrial NLP applications, it is hard to guarantee absence of any noise in the data.

Wenjun Zhou, Yuheng Deng, Bo Peng, Dong Liang

Background initialization is an important step in many high-level applications of video processing,ranging from video surveillance to video inpainting.However,this process is often affected by practical challenges such as illumination changes,background motion,camera jitter and intermittent movement,etc.In this paper,we develop a co-occurrence background mod

Ilya Dumanski, Evgeny Feigin, Michael Finkelberg

We compute the spaces of sections of powers of the determinant line bundle on the spherical Schubert subvarieties of the Beilinson- Drinfeld affine Grassmannians. The answer is given in terms of global Demazure modules over the current Lie algebra.

Fengting Yang, Qian Sun, Hailin Jin, Zihan Zhou

In computer vision, superpixels have been widely used as an effective way to reduce the number of image primitives for subsequent processing. But only a few attempts have been made to incorporate them into deep neural networks. One main reason is that the standard convolution operation is defined on regular grids and becomes inefficient when applied to super

Bingchuan Liu, Xinyi Yan, Xiaogang Chen, Yijun Wang

There has become of increasing interest in transcranial alternating current stimulation (tACS) since its inception nearly a decade ago. tACS in modulating brain state is an active area of research and has been demonstrated effective in various neuropsychological and clinical domains. In the visual domain, much effort has been dedicated to brain rhythms and r

Chongying Dong, Feng Xu, Nina Yu

Let $V$ be a vertex operator algebra and $g=\left(1\ 2\ \cdots k\right)$ be a $k$-cycle which is viewed as an automorphism of the vertex operator algebra $V^{\otimes k}$. It is proved that Dong-Li-Mason's associated associative algebra $A_{g}\left(V^{\otimes k}\right)$ is isomorphic to Zhu's algebra $A\left(V\right)$ explicitly. This result recovers a previo

Takao Komatsu

Poly-Cauchy numbers with level $2$ are defined by inverse sine hyperbolic functions with the inverse relation from sine hyperbolic functions. In this paper, we show several convolution identities of poly-Cauchy numbers with level $2$. In particular, that of three poly-Cauchy numbers with level $2$ can be expressed as a simple form. In the sequel, we introduc

Maciej Dendzik, R. Patrick Xian, Enrico Perfetto, Davide Sangalli

Time-resolved soft-X-ray photoemission spectroscopy is used to simultaneously measure the ultrafast dynamics of core-level spectral functions and excited states upon excitation of excitons in WSe$_2$. We present a many-body approximation for the Green's function, which excellently describes the transient core-hole spectral function. The relative dynamics of

Vithya Yogarajan, Jacob Montiel, Tony Smith, Bernhard Pfahringer

Machine learning-based multi-label medical text classifications can be used to enhance the understanding of the human body and aid the need for patient care. We present a broad study on clinical natural language processing techniques to maximise a feature representing text when predicting medical codes on patients with multi-morbidity. We present results of

Christian Henkel, Marc Toussaint

We present a novel approach called Optimized Directed Roadmap Graph (ODRM). It is a method to build a directed roadmap graph that allows for collision avoidance in multi-robot navigation. This is a highly relevant problem, for example for industrial autonomous guided vehicles. The core idea of ODRM is, that a directed roadmap can encode inherent properties o

Rachel Clune, Jacqueline A. R. Shea, Eric Neuscamman

We show that by working in a basis similar to that of the natural transition orbitals and using a modified zeroth order Hamiltonian, the cost of a recently-introduced perturbative correction to excited state mean field theory can be reduced from seventh to fifth order in the system size. The (occupied)$^2$(virtual)$^3$ asymptotic scaling matches that of grou

Ciro Javier Diaz Penedo

In this work we address the problem of predicting the model of a camera based on the content of their photographs. We use two set of features, one set consist in properties extracted from a Discrete Wavelet Domain (DWD) obtained by applying a 4 level Fast Wavelet Decomposition of the images, and a second set are Local Binary Patterns (LBP) features from the

Zeling Shao, Chunjin Ren, Zhiguo Li

A book embedding of a graph consists of an embedding of its vertices along the spine of a book, and an embedding of its edges on the pages such that edges embedded on the same page do not intersect. The pagenumber is the minimum number of pages in which the graph $G$ can be embedded. The main purpose of this paper is to study the book embedding of the comple

Huijuan Feng, Rui Peng, Shixi Zang, Jiayao Ma

Rigid foldability allows an origami pattern to fold about crease lines without twisting or stretching component panels. It enables folding of rigid materials, facilitating the design of foldable structures. Recent study shows that rigid foldability is affected by the mountain-valley crease (M-V) assignment of an origami pattern. In this paper, we investigate

Shajulin Benedict, Rumaize P., Jaspreet Kaur

IoT cloud enabled societal applications have dramatically increased in the recent past due to the thrust for innovations, notably through startup initiatives, in various sectors such as agriculture, healthcare, industry, and so forth. The existing IoT cloud solutions have led practitioners or researchers to a haphazard clutter of serious security hazards and

Gennady Gorin, Lior Pachter

We explore a Markov model used in the analysis of gene expression, involving the bursty production of pre-mRNA, its conversion to mature mRNA, and its consequent degradation. We demonstrate that the integration used to compute the solution of the stochastic system can be approximated by the evaluation of special functions. Furthermore, the form of the specia

Yuanyuan Dong, Yulan Bai, Eli V. Olinick, Andrew Junfang Yu

We present a compact mixed integer program (MIP) for the backhaul profit maximization problem in which a freight carrier seeks to generate profit from an empty delivery vehicle's backhaul trip from its last scheduled delivery to its depot by allowing it to deviate from the least expensive (or fastest) route to accept delivery requests between various points

Amirarsalan Rajabi, Seyyedmilad Talebzadehhosseini, Ivan Garibay

The spread of disinformation is considered a big threat to societies and has recently received unprecedented attention. In this paper we propose an agent-based model to simulate dissemination of a conspiracy in a population. The model is able to compare the resistance of different network structures against the activity of conspirators. Results show that con

József Balogh, Felix Christian Clemen

Mantel's theorem states that every $n$-vertex graph with $\lfloor \frac{n^2}{4} \rfloor +t$ edges, where $t>0$, contains a triangle. The problem of determining the minimum number of triangles in such a graph is usually referred to as the Erd\H{o}s-Rademacher problem. Lov\'asz and Simonovits proved that there are at least $t\lfloor n/2 \rfloor$ triangles in e

Ciro Javier Diaz Penedo, Lucas Leonardo Silveira Costa

We present a study of possible predictors based on four supervised machine learning models for the prediction of four mechanical properties of the main industrially used steels. The results were obtained from an experimental database available in the literature which were used as input to train and evaluate the models.

Rosemary C. She, Dongyu Chen, Pil Pak, Deniz K. Armani

Significant research has shown that UV-C exposure is an effective disinfectant for a range of bacteria and viruses, including coronaviruses. As such, a UV-C treatment in combination with a chemical wipe, such as EPA hydrogen peroxide, is a common cleaning protocol in a medical setting, and such disinfection protocols have gained in importance during the curr

Hongjie Dong, Xinghong Pan

We prove the time analyticity for weak solutions of inhomogeneous parabolic equations with measurable coefficients in the half space with either the Dirichlet boundary condition or the conormal boundary condition under the assumption that the solution and the source term have the exponential growth of order $2$ with respect to the space variables. We also ob

Yi-Bo Yang, Jian Liang, Zhaofeng Liu, Peng Sun

We investigated the origin of the RI'/MOM quark mass under the Landau gauge at the non-perturbative scale, using the chiral fermion with different quark masses and lattice spacings. Our result confirms that such a mass is non-vanishing based on the linear extrapolation to the chiral and continuum limit, and shows that such a mass comes from the spontaneous c

Syed Hashim Ali Shah, Sarankumar Balakrishnan, Liangxiao Xin, Mohamed Abouelseoud

Millimeter wave wireless systems rely heavily on directional communication in narrow steerable beams. Tools to measure the spatial and temporal nature of the channel are necessary to evaluate beamforming and related algorithms. This paper presents a novel 60~GHz phased-array based directional channel sounder and data analysis procedure that can accurately ex

Lu Lu, Xiaomin Yang, Rongzhu Zhang

In this paper, we present a diffusion multi-rate least-mean-square (LMS) algorithm, named DMLMS, which is an effective solution for distributed estimation when two or more observation sequences are available with different sampling rates. Then, we focus on a more practical application in the wireless acoustic sensor networks (ASN). The filtered-x LMS (FxLMS)

Jordan Henkel, Christian Bird, Shuvendu K. Lahiri, Thomas Reps

Dockerfiles are one of the most prevalent kinds of DevOps artifacts used in industry. Despite their prevalence, there is a lack of sophisticated semantics-aware static analysis of Dockerfiles. In this paper, we introduce a dataset of approximately 178,000 unique Dockerfiles collected from GitHub. To enhance the usability of this data, we describe five repres

Negin Karisani, Payam Karisani

World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on January 27th, while the majority of the infection cases were still reported in China and a few cruise ships, we began crawling social media user postings using the Twitter search API. O

Qiang Liu, Tao Han, Ephraim Moges

5G and edge computing will serve various emerging use cases that have diverse requirements of multiple resources, e.g., radio, transportation, and computing. Network slicing is a promising technology for creating virtual networks that can be customized according to the requirements of different use cases. Provisioning network slices requires end-to-end resou

José Alejandro Lara Rodríguez, Dinesh S. Thakur

We prove or conjecture several relations between the multizeta values for positive genus function fields of class number one, focusing on the zeta-like values, namely those whose ratio with the zeta value of the same weight is rational (or conjecturally equivalently algebraic). These are the first known relations between multizetas, which are not with prime

Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu

We study a security threat to reinforcement learning where an attacker poisons the learning environment to force the agent into executing a target policy chosen by the attacker. As a victim, we consider RL agents whose objective is to find a policy that maximizes average reward in undiscounted infinite-horizon problem settings. The attacker can manipulate th

Andrew Warrington, Saeid Naderiparizi, Frank Wood

Deterministic models are approximations of reality that are easy to interpret and often easier to build than stochastic alternatives. Unfortunately, as nature is capricious, observational data can never be fully explained by deterministic models in practice. Observation and process noise need to be added to adapt deterministic models to behave stochastically

C. G. Giménez de Castro, J. -P. Raulin, A. Valio, G. Alaia

The almost unexplored frequency window from submillimeter to mid-infrared (mid-IR) may bring new clues about the particle acceleration and transport processes and the atmospheric thermal response during solar flares. Because of its technical complexity and the special atmospheric environment needed, observations at these frequencies are very sparse. The High

Marta Bílková, Sabine Frittella, Ondrej Majer, Sajad Nazari

A recent line of research has developed around logics of belief based on evidence. The approach of B\'ilkov\'a et al understands belief as based on information confirmed by a reliable source. We propose a finer analysis of how belief can be based on information, where the confirmation comes from multiple possibly conflicting sources and is of a probabilistic

Michael Soltys

This paper re-examines the content of a standard advanced course in Cybersecurity from the perspective of Cloud Computing. More precisely, we review the core concepts of Cybersecurity, as presented in a senior undergraduate or graduate class, in light of the Amazon Web Services (AWS) cloud.

Md Mahadi Rajib, Walid Al Misba, Dhritiman Bhattacharya, Felipe Garcia-Sanchez

One method of creating and annihilating skyrmions in confined geometries is to use Voltage-Controlled Magnetic Anisotropy (VCMA) [1, 2, 3]. Previous study shows that robust voltage controlled ferromagnetic reversal from up to down state in the soft layer of a perpendicular Magnetic Tunnel Junction (p-MTJ) can be achieved by creating and subsequently annihila

Joachim Stöhr

Today, the nature of light is accounted for by one of the jewels of physics, quantum electrodynamics (QED), the fundamental theory of light and matter. Yet owing to its infinite complexity, scientists still debate how its central concept, the photon, can be reconciled with the perceived existence of light waves, emerging 200 years ago in the wake of Young's

Walid Al Misba, Md. Mahadi Rajib, Dhritiman Bhattacharya, Jayasimha Atulasimha

We have investigated Surface Acoustic Wave (SAW) induced ferromagnetic resonance (FMR) assisted Spin Transfer Torque (STT) switching of perpendicular MTJ (p-MTJ) with inhomogeneities using micromagnetic simulations that include the effect of thermal noise. With suitable frequency excitation, the SAW can induce ferromagnetic resonance in magnetostrictive mate

Christopher Leon, Misak M. Sargsian, Frank Vera

Examining the evolution of the maximum of valence quark distribution weighted by Bjorken x, $h(x,t)\equiv xq_V(x,t)$, we observe that $h(x,t)$ at the peak should become a one parameter function; $h(x_p,t)=\Phi(x_p(t))$, where $x_p$ is the position of the peak and $t= \log{Q^2}$. This observation is used to derive a new model independent relation which connec

Julian Schütte, Dennis Titze

Although iOS is the second most popular mobile operating system and is often considered the more secure one, approaches to automatically analyze iOS applications are scarce and generic app analysis frameworks do not exist. This is on the one hand due to the closed ecosystem putting obstacles in the way of reverse engineers and on the other hand due to the co

Julián Moreno-Schneider, Georg Rehm, Elena Montiel-Ponsoda, Víctor Rodriguez-Doncel

Legal technology is currently receiving a lot of attention from various angles. In this contribution we describe the main technical components of a system that is currently under development in the European innovation project Lynx, which includes partners from industry and research. The key contribution of this paper is a workflow manager that enables the fl

Dang Van Cuong, Boris Mordukhovich, Nguyen Mau Nam

In this paper we introduce and study the concept of set extremality for systems of convex sets in vector spaces without topological structures. Characterizations of the extremal systems of sets are obtained in the form of the convex extremal principle, which is shown to be equivalent to convex separation under certain qualification conditions expressed via a

Z. Osmanov, Z. Yoshida, V. I. Berezhiani

In this paper we study the generation of high energy emission from normal pulsars. For this purpose we consider the particles accelerated in the outer magnetosphere sliding along the closed magnetic field lines. It has been shown that in due course of motion the initial small pitch angle increases and at a certain distance from the neutron star the synchrotr

Raghwinder Singh Grewal, Gour Pati, Renu Tripathi

We report on experimental and theoretical investigations of the polarization dependence of magnetic resonance generated by synchronous optical pumping. Magnetic resonances with narrow linewidth are generated experimentally using a rubidium vapor cell with octade-cyltrichlorosilane (OTS) antirelaxation coating on inner walls. We studied the effect of light el

Fan Feng, Xiangxin Dang, Richard D. James, Paul Plucinsky

Rigidly and flat-foldable quadrilateral mesh origami is the class of quadrilateral mesh crease patterns with one fundamental property: the patterns can be folded from flat to fully-folded flat by a continuous one-parameter family of piecewise affine deformations that do not stretch or bend the mesh-panels. In this work, we explicitly characterize the designs

Amit Daniely

We prove that a single step of gradient decent over depth two network, with $q$ hidden neurons, starting from orthogonal initialization, can memorize $\Omega\left(\frac{dq}{\log^4(d)}\right)$ independent and randomly labeled Gaussians in $\mathbb{R}^d$. The result is valid for a large class of activation functions, which includes the absolute value.

Fritz Gesztesy, Lance L. Littlejohn, Isaac Michael, Michael M. H. Pang

The principal aim of this paper is to extend Birman's sequence of integral inequalities originally obtained in 1961, and containing Hardy's and Rellich's inequality as special cases, to a sequence of inequalities that incorporates power weights on either side and logarithmic refinements on the right-hand side of the inequality as well. Our new technique of p

Michely P. Rosseto, Jonathan V. Selinger

Recent experiments have reported a novel splay nematic phase, which has alternating domains of positive and negative splay. To model this phase, previous studies have considered a 1D splay modulation of the director field, accompanied by a 1D modulation of polar order. When the flexoelectric coupling between splay and polar order becomes sufficiently strong,

Guilherme Silva Salomão, Fabio Armando Tal

We prove that, if $f$ is a homeomorphism of the two torus isotopic to the identity whose rotation set is a non-degenerate segment and $f$ has a periodic point, then it has uniformly bounded deviations in the direction perpendicular to the segment.

Michael L. Palumbo, Sheila J. Kannappan, Elaine M. Frazer, Kathleen D. Eckert

We identify and characterize compact dwarf starburst (CDS) galaxies in the RESOLVE survey, a volume-limited census of galaxies in the local universe, to probe whether this population contains any residual ``blue nuggets,'' a class of intensely star-forming compact galaxies first identified at high redshift $z$. Our 50 low-$z$ CDS galaxies are defined by dwar

Vojtech Kejzlar, Tapabrata Maiti

With the advancements of computer architectures, the use of computational models proliferates to solve complex problems in many scientific applications such as nuclear physics and climate research. However, the potential of such models is often hindered because they tend to be computationally expensive and consequently ill-fitting for uncertainty quantificat

Yu. T. Tsap, V. A. Perebeynos, A. V. Borisenko, N. I. Lozitska

The comparative analysis for 1324 measurements of the corresponding sunspot magnetic fields with B > 2.5 kG (according to Crimean data) obtained at Crimean and Mt. Wilson observatories from 2010 to 2017 has been carried out. It has been shown that the difference between measurements can exceed 1 kG in some cases. The averaged values of the magnetic field are

Joerg F. Schneider

In this contribution it is shown that various aspects of the concept of residual migration can be utilized for the case that a prestack time or depth migration has been performed for a seismic survey and a new depth is available: The concept of residual migration is introduced by determining travel times of reflected events for individual traces from aplanat

Donato Bini, Andrea Geralico, Jan Steinhoff

We compute the first-order self-force contribution to Detweiler's redshift invariant for extended bodies endowed with both dipolar and quadrupolar structure (with spin-induced quadrupole moment) moving along circular orbits on a Schwarzschild background. Our analysis includes effects which are second order in spin, generalizing previous results for purely sp

Yinon M. Bar-On, Avi I. Flamholz, Rob Phillips, Ron Milo

The current SARS-CoV-2 pandemic is a harsh reminder of the fact that, whether in a single human host or a wave of infection across continents, viral dynamics is often a story about the numbers. In this snapshot, our aim is to provide a one-stop, curated graphical source for the key numbers that help us understand the virus driving our current global crisis.

Kevin Spahr, Jonathan Graveline, Chrustian Lupien, Marco Aprili

We have probed the switching dynamics of the Josephson critical current of a superconducting weak link by measuring its voltage/current characteristics while applying an ac current bias in the range 1-200 MHz. The weak link between two Nb reservoirs is formed by an mesoscopic Al wire above its critical temperature. We observe a dynamical phase transition as

Hossein Ghaffarnejad, Hoda Gholipour

By using Bianchi I type of homogenous and anisotropic background metric having cylindrical symmetry in $x$ direction of a local cartesian coordinates system, we solve metric field equations for a non-minimally coupled Einstein-Maxwell gravity. To do so we choose long wavelength EM waves where spatial dependence of the waves are negligible at the expansion du

S. Beetham, J. Capecelatro

A data-driven framework for formulation of closures of the Reynolds-Average Navier--Stokes (RANS) equations is presented. In recent years, the scientific community has turned to machine learning techniques to distill a wealth of highly resolved data into improved RANS closures. While the body of work in this area has primarily leveraged Neural Networks (NNs)

M. Bonesini, R. Benocci, R. Bertoni, A. Falcone

The ICARUS T600 LAr TPC is the far detector of the Short Baseline Program at FNAL. As it will have to work at shallow depth in the Booster Neutrino Beam, a large cosmic rays background ($\sim 11$ kHz) will be present. To reduce it, precise timing information is needed from the new light detection system, based on 360 large area photomultipliers. For precise

Michael Larsen, Aner Shalev, Pham Huu Tiep

In recent years there has been significant progress in the study of products of subsets of finite groups and of finite simple groups in particular. In this paper we consider which families of finite simple groups $G$ have the property that for each $\epsilon > 0$ there exists $N > 0$ such that, if $|G| \ge N$ and $S, T$ are normal subsets of $G$ with at leas

Vidyasagar Sadhu, Xueyuan Zhao, Dario Pompili

The research challenge of current Wireless Sensor Networks (WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such as environmental monitoring. Traditional WSNs consist of low density, power-hungry digital motes that are expensive and cannot remain functional for long periods on a single power c

Marianne Menictas, Sabina Tomkins, Susan A Murphy

To effect behavior change a successful algorithm must make high-quality decisions in real-time. For example, a mobile health (mHealth) application designed to increase physical activity must make contextually relevant suggestions to motivate users. While machine learning offers solutions for certain stylized settings, such as when batch data can be processed

Alekh Agarwal, John Langford, Chen-Yu Wei

We study a new form of federated learning where the clients train personalized local models and make predictions jointly with the server-side shared model. Using this new federated learning framework, the complexity of the central shared model can be minimized while still gaining all the performance benefits that joint training provides. Our framework is rob