May 2020 arXiv papers — page 3

Thomas Drugman, Yannis Stylianou

Maximum Voiced Frequency (MVF) is used in various speech models as the spectral boundary separating periodic and aperiodic components during the production of voiced sounds. Recent studies have shown that its proper estimation and modeling enhance the quality of statistical parametric speech synthesizers. Contrastingly, these same methods of MVF estimation h

M. Makvand Chaharlang, Maria Alessandra Ragusa, Abdolrahman Razani

In this article a nonlocal elliptic problem involving $p$-Laplacian on unbounded domain is considered. Using variational methods and under suitable conditions, the existence of a sequence of radially symmetric weak solutions, in two different cases, is proved.

Thomas Drugman, John Kane, Christer Gobl

This paper investigates the temporal excitation patterns of creaky voice. Creaky voice is a voice quality frequently used as a phrase-boundary marker, but also as a means of portraying attitude, affective states and even social status. Consequently, the automatic detection and modelling of creaky voice may have implications for speech technology applications

Daisuke Hotta, Yoichiro Ota

The ability of ensemble Kalman filter (EnKF) algorithms to extract information from observations is analyzed with the aid of the concept of the degrees of freedom for signal (DFS). A simple mathematical argument shows that DFS for EnKF is bounded from above by the ensemble size, which entails that assimilating much more observations than the ensemble size au

M. Heemskerk, M. Mandjes, B. Mathijsen

Arrival processes to service systems often display (i) larger than anticipated fluctuations, (ii) a time-varying rate, and (iii) temporal correlation. Motivated by this, we introduce a specific non-homogeneous Poisson process that incorporates these three features. The resulting arrival process is fed into an infinite-server system, which is then used as a p

Fedor Ivanov, Eugenii Krouk

McEliece cryptosystem represents a smart open key system based on the hardness of the decoding of an arbitrary linear code, which is believed to be able to resist the advent of quantum computers. But the original McEliece cryptosystem, based on Goppa codes, has just very limited interest in practice, partly because it requires a very large public key. In thi

Rebecca K. Leane

I present a short overview of the latest developments in indirect searches for dark matter using gamma rays, X-rays, charged cosmic rays, micro waves, radio waves, and neutrinos. I briefly outline key past, present, and future experiments and their search strategies. In several searches there are exciting anomalies which could potentially be emerging dark ma

Sebastiaan Scholten, Danny Merkx, Odette Scharenborg

We investigated word recognition in a Visually Grounded Speech model. The model has been trained on pairs of images and spoken captions to create visually grounded embeddings which can be used for speech to image retrieval and vice versa. We investigate whether such a model can be used to recognise words by embedding isolated words and using them to retrieve

Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, Dusit Niyato

In 5G and Beyond networks, Artificial Intelligence applications are expected to be increasingly ubiquitous. This necessitates a paradigm shift from the current cloud-centric model training approach to the Edge Computing based collaborative learning scheme known as edge learning, in which model training is executed at the edge of the network. In this article,

Tianlun Chen, Albert Y. S. Lam, Yue Song, David J. Hill

Widespread utilization of renewable energy sources (RESs) in subtransmission systems causes serious problems on power quality, such as voltage violations, leading to significant curtailment of renewables. This is due to the inherent variability of renewables and the high R/X ratio of the subtransmission system. To achieve full utilization of renewables, batt

Alexander Fuerst, Ahmed Ali-Eldin, Prashant Shenoy, Prateek Sharma

Transient computing has become popular in public cloud environments for running delay-insensitive batch and data processing applications at low cost. Since transient cloud servers can be revoked at any time by the cloud provider, they are considered unsuitable for running interactive application such as web services. In this paper, we present VM deflation as

Tianlun Chen, Albert Y. S. Lam, Yue Song, David J. Hill

This paper proposes a robust transient stability constrained optimal power flow problem that addresses renewable uncertainties by the coordination of generation re-dispatch and power flow router (PFR) tuning.PFR refers to a general type of network-side controller that enlarges the feasible region of the OPF problem. The coordination between network-side and

Guido Falk von Rudorff, Stefan N. Heinen, Marco Bragato, O. Anatole von Lilienfeld

Reaction barriers are a crucial ingredient for first principles based computational retro-synthesis efforts as well as for comprehensive reactivity assessments throughout chemical compound space. While extensive databases of experimental results exist, modern quantum machine learning applications require atomistic details which can only be obtained from quan

Mustafa Aggul

An alternative first step approximation based on subgrid artificial viscosity modeling (SAV) is proposed for defect-deferred correction method (DDC) for incompresible Navier-Stokes equation at high Reynolds number. This new approach not only preserves all qualifications of the conventional artificial viscosity (AV) based DDC, such as unconditional stability,

Willian Tokura, Elismar Batista

In this paper, we show that any compact gradient k-Yamabe soliton must have constant $σ_k$-curvature. Moreover, we provide a certain condition for a compact k-Yamabe soliton to be gradient.

Geraint H. Jones, Heather A. Elliott, David J. McComas, Matthew E. Hill

During March-April 2002, while between the orbits of Jupiter and Saturn, the Cassini spacecraft detected a significant enhancement in pickup proton flux. The most likely explanation for this enhancement was the addition of protons to the solar wind by the ionization of neutral hydrogen in the corona of comet 153P/Ikeya-Zhang. This comet passed relatively clo

Aleksi Pyörälä, Pablo Shmerkin, Ville Suomala, Meng Wu

We show that non-trivial $\times N$-invariant sets in $[0,1]^d$, such as the Sierpiński carpet and the Sierpiński sponge, are tube-null, that is, they can be covered by a union of tubular neighbourhoods of lines of arbitrarily small total volume. This introduces a new class of tube-null sets of dimension strictly between $d-1$ and $d$. We utilize ergodic-the

Mircea Merca

The restricted partitions in which the largest part is less than or equal to $N$ and the number of parts is less than or equal to $k$ were investigated by Andrews in \cite{Andrews76}. These partitions were extended recently by the author to the partitions into parts of two kinds. In this paper, we use a new class of restricted partitions into parts of two ki

Zbigniew Haba

The time-dependent cosmological term arises from the energy-momentum tensor calculated in a state different from the ground state. We discuss the expectation value of the energy-momentum tensor on the rhs of Einstein equations in various (approximate)pure as well as mixed states. We apply the classical slow-roll field evolution as well as the Starobinsky and

G. Aymar, T. Becker, S. Boogert, M. Borghesi

The `Laser-hybrid Accelerator for Radiobiological Applications', LhARA, is conceived as a novel, uniquely-flexible facility dedicated to the study of radiobiology. The technologies demonstrated in LhARA, which have wide application, will be developed to allow particle-beam therapy to be delivered in a completely new regime, combining a variety of ion spe

Marco Falconi, Emanuela L. Giacomelli, Christian Hainzl, Marcello Porta

We study the ground state properties of interacting Fermi gases in the dilute regime, in three dimensions. We compute the ground state energy of the system, for positive interaction potentials. We recover a well-known expression for the ground state energy at second order in the particle density, which depends on the interaction potential only via its scatte

Brenda Salenave Santana, Aline Aver Vanin

2018's Brazilian presidential elections highlighted the influence of alternative media and social networks, such as Twitter. In this work, we perform an analysis covering politically motivated discourses related to the second round in Brazilian elections. In order to verify whether similar discourses reinforce group engagement to personal beliefs, we col

Lu Xia, Martijn Anthonissen, Michiel Hochstenbach, Barry Koren

Due to the limited number of bits in floating-point or fixed-point arithmetic, rounding is a necessary step in many computations. Although rounding methods can be tailored for different applications, round-off errors are generally unavoidable. When a sequence of computations is implemented, round-off errors may be magnified or accumulated. The magnification

Debayan Maity, Takéo Takahashi

The article is devoted to the mathematical analysis of a fluid-structure interaction system where the fluid is compressible and heat conducting and where the structure is deformable and located on a part of the boundary of the fluid domain. The fluid motion is modeled by the compressible Navier-Stokes-Fourier system and the structure displacement is describe

Xiaokang Liu, Xiaomei Cong, Gen Li, Kendra Maas

The so-called gut-brain axis has stimulated extensive research on microbiomes. One focus is to assess the association between certain clinical outcomes and the relative abundances of gut microbes, which can be presented as sub-compositional data in conformity with the taxonomic hierarchy of bacteria. Motivated by a study for identifying the microbes in the g

Patrick R. Whelan, Qian Shen, Binbin Zhou, I. G. Serrano

We demonstrate terahertz time-domain spectroscopy (THz-TDS) to be an accurate, rapid and scalable method to probe the interaction-induced Fermi velocity renormalization νF^* of charge carriers in graphene. This allows the quantitative extraction of all electrical parameters (DC conductivity σDC, carrier density n, and carrier mobility μ) of large-scale graph

Yonatan Mishnayot, Hitesh Rahangdale, Ben Ohayon, Sergey Vaintraub

In this article, we present a measurement of flow rate, yield and effusion time of a $^{23}$Ne production and transport system. We used an accelerator-driven Li(d,n) neutron source to produce neutrons up to 20 MeV. The radioactive atoms were produced by a $^{23}$Na(n,p) reaction at a NaCl target. Later, the atoms were diffused out from the NaCl crystals and

Marcella Contini

We calculate the physical conditions and the N/H and O/H relative abundances for a sample of long GRB (LGRB) host galaxies in the redshift range 1<z<2.1 by modelling recently observed line and continuum spectra. The results are consistent with those previously calculated for LGRB host galaxies throughout a more extended redshift range z<3. We analyse star fo

Fei Xu, Yong Zhang, Fengquan Li

In this paper, the two-component Fornberg-Whitham system is studied. We firstly investigate the well-posedness in classical Sobolev Space and show a blow-up scenario by local-in-time a priori estimates, then we present some sufficient conditions on the initial data to lead to wave breaking. Furthermore, we establish analytically the existence of periodic tra

Dana Weitzner, David Mendlovic, Raja Giryes

Face verification is a fast-growing authentication tool for everyday systems, such as smartphones. While current 2D face recognition methods are very accurate, it has been suggested recently that one may wish to add a 3D sensor to such solutions to make them more reliable and robust to spoofing, e.g., using a 2D print of a person&#39;s face. Yet, this requir

Jingtao Guo, Yi Liu, Zhenzhen Qian, Zuowei Zhou

Image synthesis has witnessed substantial progress due to the increasing power of generative model. This paper we propose a novel generative approach for exemplar based facial editing in the form of the region inpainting. Our method first masks the facial editing region to eliminates the pixel constraints of the original image, then exemplar based facial edi

Dan-Bo Zhang, Guo-Qing Zhang, Zheng-Yuan Xue, Shi-Liang Zhu

Simulation of a quantum many-body system at finite temperatures is crucially important but quite challenging. Here we present an experimentally feasible quantum algorithm assisted with continuous-variable for simulating quantum systems at finite temperatures. Our algorithm has a time complexity scaling polynomially with the inverse temperature and the desire

Yura Zharkovsky, Ovadya Menadeva

Monitoring large areas is presently feasible with high resolution drone cameras, as opposed to time-consuming and expensive ground surveys. In this work we reveal for the first time, the potential of using a state-of-the-art change detection GAN based algorithm with high resolution drone images for infrastructure inspection. We demonstrate this concept on so

Ilya Gorshkov, Timur Nasybullov

A. Smoktunowicz and L. Vendramin conjectured that if $A$ is a finite skew brace with solvable additive group, then the multiplicative group of $A$ is solvable. In this short note we make a step towards positive solution of this conjecture proving that if $A$ is a minimal finite skew brace with solvable additive group and non-solvable multiplicative group, th

Girma Negashe, Adane Mamuye

Recognition of handwritten document aims at transforming document images into a machine understandable format. Handwritten document recognition is the most challenging area in the field of pattern recognition. It becomes more complex when a document was written on vellum before hundreds of years, like older Geez scripts. In this study, we introduced a modifi

Pin Tang, Pinli Yang, Yuang Shi, Yi Zhou

Named entity recognition (NER) plays an essential role in natural language processing systems. Judicial NER is a fundamental component of judicial information retrieval, entity relation extraction, and knowledge map building. However, Chinese judicial NER remains to be more challenging due to the characteristics of Chinese and high accuracy requirements in t

Chaman Kumar, Neelima, Christoph Reisinger, Wolfgang Stockinger

In this paper, we first establish well-posedness of McKean-Vlasov stochastic differential equations (McKean-Vlasov SDEs) with common noise, possibly with coefficients having super-linear growth in the state variable. Second, we present stable time-stepping schemes for this class of McKean-Vlasov SDEs. Specifically, we propose an explicit tamed Euler and tame

Eliav Buchnik, Edith Cohen

Classically, ML models trained with stochastic gradient descent (SGD) are designed to minimize the average loss per example and use a distribution of training examples that remains {\em static} in the course of training. Research in recent years demonstrated, empirically and theoretically, that significant acceleration is possible by methods that dynamically

Hichem Rahab, Abdelhafid Zitouni, Mahieddine Djoudi

It is very current in today life to seek for tracking the people opinion from their interaction with occurring events. A very common way to do that is comments in articles published in newspapers web sites dealing with contemporary events. Sentiment analysis or opinion mining is an emergent field who is the purpose is finding the behind phenomenon masked in

Xueyan Wang, Man Jiang, Zhangcan Yang

One of the key challenges to realize controlled fusion energy is tritium self-sufficiency. The application of hydrogen permeation barrier (HPB) is considered to be necessary for tritium self-sufficiency. α-Al2O3 is currently a candidate material for HPB. However, a crucial issue for α-Al2O3 is that its permeability reduction factor (PRF) will dramatically dr

Weijun Fang, Shu-Tao Xia, Fang-Wei Fu

The parameters of a $q$-ary MDS Euclidean self-dual codes are completely determined by its length and the construction of MDS Euclidean self-dual codes with new length has been widely investigated in recent years. In this paper, we give a further study on the construction of MDS Euclidean self-dual codes via generalized Reed-Solomon (GRS) codes and their ext

N. Wall Wennerdal, A. Ask, P. Holmvall, T. Löfwander

We report results of a microscopic calculation of a second-order phase transition into a state breaking time-reversal and translational invariance along pair-breaking edges of $d$-wave superconductors. By solving a tight-binding model through exact diagonalization with the Bogoliubov-de~Gennes method, we find that such a state with current loops having a dia

Shaobo Gan, Yi Shi, Disheng Xu, Jinhua Zhang

In this paper, we study the centralizer of a partially hyperbolic diffeomorphism on $\mathbb{T}^3$ which is homotopic to an Anosov automorphism, and we show that either its centralizer is virtually trivial or such diffeomorphism is smoothly conjugate to its linear part.

C. Lidman, B. E. Tucker, T. M. Davis, S. A. Uddin

We present a description of the Australian Dark Energy Survey (OzDES) and summarise the results from its six years of operations. Using the 2dF fibre positioner and AAOmega spectrograph on the 3.9-metre Anglo-Australian Telescope, OzDES has monitored 771 AGN, classified hundreds of supernovae, and obtained redshifts for thousands of galaxies that hosted a tr

Ehsan Haghighat, Ali Can Bekar, Erdogan Madenci, Ruben Juanes

The Physics-Informed Neural Network (PINN) framework introduced recently incorporates physics into deep learning, and offers a promising avenue for the solution of partial differential equations (PDEs) as well as identification of the equation parameters. The performance of existing PINN approaches, however, may degrade in the presence of sharp gradients, as

Yuanyuan Chen, Wuhong Zhang, Dongkai Zhang, Xiaodong Qiu

The Bell basis, a set of maximally entangled biphoton state, is a critical prerequisite towards quantum information processing, and many quantum applications have highlighted the requirement for the manipulation of high-dimensional Bell basis. While the Bell states can be created by using ingenious single-photon quantum gates, its implementation complexity i

Siavash Valafar

Molecular testing is rapidly becoming integral to the global tuberculosis (TB) control effort. Uncommon mechanisms of resistance can escape detection by these platforms and lead to the development of Multi-Drug Resistant (MDR) strains. This article is a systematic review of published articles that reported isoniazid (INH) resistance-conferring mutations betw

Qinggang Zhou, Yawen Zhang, Pengcheng Li, Xiaoyong Liu

The state-of-the-art deep learning algorithms rely on distributed training systems to tackle the increasing sizes of models and training data sets. Minibatch stochastic gradient descent (SGD) algorithm requires workers to halt forward/back propagations, to wait for gradients aggregated from all workers, and to receive weight updates before the next batch of

Eiichi Bannai, Manabu Oura, Da Zhao

Nebe, Rains and Sloane studied the polynomial invariants for real and complex Clifford groups and they relate the invariants to the space of complete weight enumerators of certain self-dual codes. The purpose of this paper is to show that very similar results can be obtained for the invariants of the complex Clifford group $\mathcal{X}_m$ acting on the space

Feifan Lv, Bo Liu, Feng Lu

This paper proposes a new light-weight convolutional neural network (5k parameters) for non-uniform illumination image enhancement to handle color, exposure, contrast, noise and artifacts, etc., simultaneously and effectively. More concretely, the input image is first enhanced using Retinex model from dual different aspects (enhancing under-exposure and supp

Zimu Khakhaleva-Li, Craig J. Hogan

Rapid advancement in the observation of cosmic strings has been made in recent years placing increasingly stringent constraints on their properties, with $Gμ\lesssim 10^{-11}$ from Pulsar Timing Array (PTA). Cosmic string loops with low string tension clump in the Galaxy due to slow loop decay and low gravitational recoil, resulting in great enhancement to l

Henrik Parsamyan, Hovhannes Haroyan, Khachatur Nerkararyan

We have shown that a structure composed of a semiconductor hemicylinder and a dielectric waveguide separated by a thin metal layer permits efficient and easy light control. In such a system, it is possible to ensure matching between TE and TM modes of a low refractive index waveguide with the corresponding whispering gallery modes of the hemicylinder of a hi

Abhishek Gupta, Tania De Gasperis

With the push for contact- and proximity-tracing solutions as a means to manage the spread of the pandemic, there is a distrust between the citizens and authorities that are deploying these solutions. The efficacy of the solutions relies on meeting a minimum uptake threshold which is hitting a barrier because of a lack of trust and transparency in how these

Noriko Akutsu

The crossover from a Berezinskii--Kosterlitz--Thouless (BKT) rough surface to a Kardar--Parisi--Zhang (KPZ) rough surface on a vicinal surface is studied using the Monte Carlo method in the non-equilibrium steady state in order to address discrepancies between theoretical results and experiments. The model used is a restricted solid-on-solid (RSOS) model wit

Nikolay M. Babayan, Mamikon S. Ginovyan, Murad S. Taqqu

One of the main problem in prediction theory of discrete-time second-order stationary processes $X(t)$ is to describe the asymptotic behavior of the best linear mean squared prediction error in predicting $X(0)$ given $ X(t),$ $-n\le t\le-1$, as $n$ goes to infinity. This behavior depends on the regularity (deterministic or non-deterministic) of the process

Song-Bo Yang, Tian-li Yu

In recent years, semi-supervised learning (SSL) has shown tremendous success in leveraging unlabeled data to improve the performance of deep learning models, which significantly reduces the demand for large amounts of labeled data. Many SSL techniques have been proposed and have shown promising performance on famous datasets such as ImageNet and CIFAR-10. Ho

Xiufan Yu, Danning Li, Lingzhou Xue

Testing large covariance matrices is of fundamental importance in statistical analysis with high-dimensional data. In the past decade, three types of test statistics have been studied in the literature: quadratic form statistics, maximum form statistics, and their weighted combination. It is known that quadratic form statistics would suffer from low power ag

Jae Sung Park, Dinesh Manocha

We present a novel approach to generate collision-free trajectories for a robot operating in close proximity with a human obstacle in an occluded environment. The self-occlusions of the robot can significantly reduce the accuracy of human motion prediction, and we present a novel deep learning-based prediction algorithm. Our formulation uses CNNs and LSTMs a

Liang Liu, Xiaopeng Luo

In this paper, we propose a novel accelerated stochastic gradient method with momentum, which momentum is the weighted average of previous gradients. The weights decays inverse proportionally with the iteration times. Stochastic gradient descent with momentum (Sgdm) use weights that decays exponentially with the iteration times to generate an momentum term.

Nil-Jana Akpinar, Aaditya Ramdas, Umut Acar

Educational software data promises unique insights into students&#39; study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern mining

Yanjun Cao, Giovanni Beltrame

Monocular cameras coupled with inertial measurements generally give high performance visual inertial odometry. However, drift can be significant with long trajectories, especially when the environment is visually challenging. In this paper, we propose a system that leverages ultra-wideband ranging with one static anchor placed in the environment to correct t

Julia White, Jesse Mu, Noah D. Goodman

A hallmark of human language is the ability to effectively and efficiently convey contextually relevant information. One theory for how humans reason about language is presented in the Rational Speech Acts (RSA) framework, which captures pragmatic phenomena via a process of recursive social reasoning (Goodman & Frank, 2016). However, RSA represents ideal rea

Jeiyoon Park, Chanhee Lee, Kuekyeng Kim, Heuiseok Lim

Despite its notable success in adversarial learning approaches to multi-domain task-oriented dialog system, training the dialog policy via adversarial inverse reinforcement learning often fails to balance the performance of the policy generator and reward estimator. During optimization, the reward estimator often overwhelms the policy generator and produces

Ankit Goel, Abdulazeez Mohammed Salim, Ahmad Ansari, Sai Ravela

This paper develops an adaptive autopilot for quadcopters with unknown dynamics. To do this, the PX4 autopilot architecture is modified so that the feedback and feedforward controllers are replaced by adaptive control laws based on retrospective cost adaptive control (RCAC). The present paper provides a numerical investigation of the performance of the adapt

Brandon S. Zerbe, Phil M. Duxbury

This paper is the first in a series which develops the theory of emittance dynamics based on simple statistical reasoning. Emittance is a central quantity used to characterize the quality of electron microscopes, photon sources and particle beams. Emittance growth in high intensity charged particle beams is a particularly challenging non-equilibrium statisti

Ange Lou, Shuyue Guan, Murray Loew

Recently, deep learning has become much more popular in computer vision area. The Convolution Neural Network (CNN) has brought a breakthrough in images segmentation areas, especially, for medical images. In this regard, U-Net is the predominant approach to medical image segmentation task. The U-Net not only performs well in segmenting multimodal medical imag

Hantao Yao, Shaobo Min, Yongdong Zhang, Changsheng Xu

Transductive Zero-shot learning (ZSL) targets to recognize the unseen categories by aligning the visual and semantic information in a joint embedding space. There exist four kinds of domain biases in Transductive ZSL, i.e., visual bias and semantic bias between two domains and two visual-semantic biases in respective seen and unseen domains, but existing wor

Lixing You

The superconducting nanowire single-photon detector (SNSPD) is a quantum-limit superconducting optical detector based on the Cooper-pair breaking effect by a single photon, which exhibits a higher detection efficiency, lower dark count rate, higher counting rate, and lower timing jitter when compared with those exhibited by its counterparts. SNSPDs have been

Zhu Wang, Anat Lubetzky, Charles Hendee, Marta Gospodarek

We developed a novel assessment platform with untethered virtual reality, 3-dimensional sounds, and pressure sensing floor mat to help assess the walking balance and negotiation of obstacles given diverse sensory load and/or cognitive load. The platform provides an immersive 3D city-like scene with anticipated/unanticipated virtual obstacles. Participants ne

Hongyuan You, Furkan Kocayusufoglu, Ambuj K. Singh

Network regularization is an effective tool for incorporating structural prior knowledge to learn coherent models over networks, and has yielded provably accurate estimates in applications ranging from spatial economics to neuroimaging studies. Recently, there has been an increasing interest in extending network regularization to the spatio-temporal case to

K. Tatar, D. Bisig, P. Pasquier

We present the Latent Timbre Synthesis (LTS), a new audio synthesis method using Deep Learning. The synthesis method allows composers and sound designers to interpolate and extrapolate between the timbre of multiple sounds using the latent space of audio frames. We provide the details of two Variational Autoencoder architectures for LTS, and compare their ad

Christopher Griffin, Justin Semonsen, Andrew Belmonte

We study the network replicator equation and characterize its fixed points on arbitrary graph structures for $2 \times 2$ symmetric games. We show a relationship between the asymptotic behavior of the network replicator and the existence of an independent vertex set in the graph and also show that complex behavior cannot emerge in $2 \times 2$ games. This li

Shanming Ji, Ming Mei

This paper is concerned with the multi-dimensional compressible Euler equations with time-dependent over-damping of the form $-\fracμ{(1+t)^λ}ρ\boldsymbol u$ in $\mathbb R^n$, where $n\ge2$, $μ>0$, and $λ\in[-1,0)$. This continues our previous work dealing with the under-damping case for $λ\in[0,1)$. We show the optimal decay estimates of the solutions such

Shanming Ji, Ming Mei

This paper is concerned with the multi-dimensional compressible Euler equations with time-dependent damping of the form $-\fracμ{(1+t)^λ}ρ\boldsymbol u$ in $\mathbb R^n$, where $n\ge2$, $μ>0$, and $λ\in[0,1)$. When $λ>0$ is bigger, the damping effect time-asymptotically gets weaker, which is called under-damping. We show the optimal decay estimates of the so

Arthur L. B. Yang

The Stern poset $\mathcal{S}$ is a graded infinite poset naturally associated to Stern&#39;s triangle, which was defined by Stanley analogously to Pascal&#39;s triangle. Let $P_n$ denote the interval of $\mathcal{S}$ from the unique element of row $0$ of Stern&#39;s triangle to the $n$-th element of row $r$ for sufficiently large $r$. For $n\geq 1$ let \begi

Benjamin Bode

A geometric braid $B$ can be interpreted as a loop in the space of monic complex polynomials with distinct roots. This loop defines a function $g:\mathbb{C}\times S^1\to\mathbb{C}$ that vanishes on $B$. We define the set of P-fibered braids as those braids that can be represented by loops of polynomials such that the corresponding function $g$ induces a fibr

Jonathan H. Brown, Adam H. Fuller, David R. Pitts, Sarah A. Reznikoff

Let $C^*(E)$ be the graph C$^*$-algebra of a row-finite graph $E$. We give a complete description of the vertex sets of the gauge-invariant regular ideals of $C^*(E)$. It is shown that when $E$ satisfies Condition (L) the regular ideals $C^*(E)$ are a class of gauge-invariant ideals which preserve Condition (L) under quotients. That is, we show that if $E$ s

Francesco Petocchi, Viktor Christiansson, Fredrik Nilsson, Ferdi Aryasetiawan

The recent discovery of superconductivity in hole-doped NdNiO$_2$ thin films has captivated the condensed matter physics community. Such compounds with a formal Ni$^+$ valence have been theoretically proposed as possible analogues of the cuprates, and the exploration of their electronic structure and pairing mechanism may provide important insights into the

Xiaocong He, Xiaobo He

The first Zagreb index $M_{1}$ of a graph is defined as the sum of the square of every vertex degree, and the second Zagreb index $M_{2}$ of a graph is defined as the sum of the product of vertex degrees of each pair of adjacent vertices. In this paper, we study the Zagreb indices of bipartite graphs of order $n$ with $κ(G)=k$ (resp. $κ&#39;(G)=s$) and sharp

Zhifeng Kong, Kamalika Chaudhuri

Normalizing flows have received a great deal of recent attention as they allow flexible generative modeling as well as easy likelihood computation. While a wide variety of flow models have been proposed, there is little formal understanding of the representation power of these models. In this work, we study some basic normalizing flows and rigorously establi

Arjumand Seemab, Jehad Alzabut, Mujeeb ur Rehman, Yacine Adjabi

This paper studies Langevin equation with nonlocal boundary conditions involving a $ψ$--Caputo fractional derivatives operator. By the aide of fixed point techniques of Krasnoselskii and Banach, we derive new results on existence and uniqueness of the problem at hand. Further, the $ψ$-fractional Gronwall inequality and $ψ$--fractional integration by parts ar

Susanne Albers, Maximilian Janke

Makespan minimization on identical machines is a fundamental problem in online scheduling. The goal is to assign a sequence of jobs to $m$ identical parallel machines so as to minimize the maximum completion time of any job. Already in the 1960s, Graham showed that Greedy is $(2-1/m)$-competitive. The best deterministic online algorithm currently known achie

Victor Freguglia, Nancy Lopes Garcia

Markov random fields on two-dimensional lattices are behind many image analysis methodologies. mrf2d provides tools for statistical inference on a class of discrete stationary Markov random field models with pairwise interaction, which includes many of the popular models such as the Potts model and texture image models. The package introduces representations

Santanu Nandi

This article discusses some topological properties of the dynamical plane ($z$-plane) of the holomorphic family of meromorphic maps $λ\tan z^2$ for $ λ\in \mathbb C^*$. In the dynamical plane, I prove that there is no Herman ring and the Julia set is a Cantor set for the maps when the parameter is in the hyperbolic component containing the origin. Julia set

A. S. Dosaev, M. I. Shishina, Yu. I. Troitskaya

We present a numerical study of essentially nonlinear dynamics of surface gravity waves on deep water with constant vorticity using governing equations in conformal coordinates. The dispersion relation of surface gravity waves on shear flow is known to have two branches, one of which is weakly dispersive for long waves. Weakly nonlinear evolution of the wave

Jonas C. Kiemel, Robin Weitemeyer, Pascal Meißner, Torsten Kröger

We present TrueÆdapt, a model-free method to learn online adaptations of robot trajectories based on their effects on the environment. Given sensory feedback and future waypoints of the original trajectory, a neural network is trained to predict joint accelerations at regular intervals. The adapted trajectory is generated by linear interpolation of the predi

Michael Freedman

Classical results of Milnor, Wood, Mather, and Thurston produce flat connections in surprising places. The Milnor-Wood inequality is for circle bundles over surfaces, whereas the Mather-Thurston Theorem is about cobording general manifold bundles to ones admitting a flat connection. The surprise comes from the close encounter with obstructions from Chern-Wey

Yifei Huang

With today&#39;s savvy and empowered customers, sales requires more judgment and becomes more cognitively intense than ever before. We argue that Situation Awareness (SA) is at the center of effective sales and customer engagement in this new era, and Information Fusion (IF) is the key for developing the next generation of decision support systems for digita

Nava Haghighi, Nathalie Vladis, Yuanbo Liu, Arvind Satyanarayan

With the rise of wearables, haptic interfaces are increasingly favored to communicate information in an ambient manner. Despite this expectation, existing guidelines are developed in studies where the participant&#39;s focus is entirely on the haptic task. In this work, we systematically study the cognitive load imposed by properties of a haptic signal. Part

Trevor Hastie

Ridge or more formally $\ell_2$ regularization shows up in many areas of statistics and machine learning. It is one of those essential devices that any good data scientist needs to master for their craft. In this brief ridge fest I have collected together some of the magic and beauty of ridge that my colleagues and I have encountered over the past 40 years i

J. Ricardo G. Mendonça

The longest increasing subsequence (LIS) of a sequence of correlated random variables is a basic quantity with potential applications that has started to receive proper attention only recently. Here we investigate the behavior of the length of the LIS of the so-called symmetric ultra-fat tailed random walk, introduced earlier in an abstract setting in the ma

Niraj Sharma, Riya Jain, Madhumita Mohan, Sachin Patkar

Many engineering and scientific applications require high precision arithmetic. IEEE~754-2008 compliant (floating-point) arithmetic is the de facto standard for performing these computations. Recently, posit arithmetic has been proposed as a drop-in replacement for floating-point arithmetic. The posit\texttrademark data representation and arithmetic claim se

Johannes M. Henn

Tremendous ongoing theory efforts are dedicated to developing new methods for QCD calculations. Qualitative rather than incremental advances are needed to fully exploit data still to be collected at the LHC. The maximally supersymmetric Yang-Mills theory (${\mathcal N}=4$ sYM) shares with QCD the gluon sector, which contains the most complicated Feynman grap

Dian Fan, Ronny Pini, Alberto Striolo

We study many-particle transport in heterogeneous, crowded environments at different particle Péclet numbers ($Pe^*$). We demonstrate that a modified Nakagami-$m$ function describes particle velocity probability distributions when particle deposition occurs. We assess the universality of said function through comparison against new Lagrangian simulations of

Davood Karimi, Simon K. Warfield, Ali Gholipour

Transfer learning is widely used for training machine learning models. Here, we study the role of transfer learning for training fully convolutional networks (FCNs) for medical image segmentation. Our experiments show that although transfer learning reduces the training time on the target task, the improvement in segmentation accuracy is highly task/data-dep

Pantelimon Stanica, Aaron Geary

While the classical differential uniformity ($c=1$) is invariant under the CCZ-equivalence, the newly defined \cite{EFRST20} concept of $c$-differential uniformity, in general is not invariant under EA or CCZ-equivalence, as was observed in \cite{SPRS20}. In this paper, we find an intriguing behavior of the inverse function, namely, that adding some appropri

Andreas Bärtschi, Stephan Eidenbenz

We propose GM-QAOA, a variation of the Quantum Alternating Operator Ansatz (QAOA) that uses Grover-like selective phase shift mixing operators. GM-QAOA works on any NP optimization problem for which it is possible to efficiently prepare an equal superposition of all feasible solutions; it is designed to perform particularly well for constraint optimization p

Eric Swartz, Gabrielle Tauscheck

A partial difference set $S$ in a finite group $G$ satisfying $1 \notin S$ and $S = S^{-1}$ corresponds to an undirected strongly regular Cayley graph ${\rm Cay}(G,S)$. While the case when $G$ is abelian has been thoroughly studied, there are comparatively few results when $G$ is nonabelian. In this paper, we provide restrictions on the parameters of a parti

Tang Ye, Margaret Kocherga, Yi-Yang Sun, Andrei Nesmelov

Organic-inorganic hybrids may offer material properties not available from their inorganic components. However, they are typically less stable and disordered. Long-term stability study of the hybrid materials, over the anticipated lifespan of a real-world electronic device, is practically nonexistent. Disordering, prevalent in most nanostructure assemblies,

Ilya Kachkovskiy, Leonid Parnovski, Roman Shterenberg

We consider a class of unbounded quasiperiodic Schrödinger-type operators on $\ell^2(\mathbb Z^d)$ with monotone potentials (akin to the Maryland model) and show that the Rayleigh--Schrödinger perturbation series for these operators converges in the regime of small kinetic energies, uniformly in the spectrum. As a consequence, we obtain a new proof of Anders