April 2020 arXiv papers — page 49

V. V. Flambaum, I. B. Samsonov, H. B. Tran Tan

Experiments with paramagnetic ground or metastable excited states of molecules (ThO, HfF$^+$, YbF, YbOH, BaF, PbO, etc.) provide strong constraints on electron electric dipole moment (EDM) and coupling constant $C_{SP}$ of contact semileptonic interaction. We compute new contributions to $C_{SP}$ arising from the nucleon EDMs due to combined electric and mag

Ying Cao, Bo Sun, Danny H. K. Tsang

We study two canonical online optimization problems under capacity/budget constraints: the fractional one-way trading problem (OTP) and the integral online knapsack problem (OKP) under an infinitesimal assumption. Under the competitive analysis framework, it is well-known that both problems have the same optimal competitive ratio. However, these two problems

Edson Bollis, Helio Pedrini, Sandra Avila

Pests and diseases are relevant factors for production losses in agriculture and, therefore, promote a huge investment in the prevention and detection of its causative agents. In many countries, Integrated Pest Management is the most widely used process to prevent and mitigate the damages caused by pests and diseases in citrus crops. However, its results are

R. Parimala, V. Suresh

Let K be a p-adic field and F the function field of a curve over K. Let G be a connected linear algebraic group over F of classical type. Suppose the prime p is a good prime for G. Then we prove that projective homogeneous spaces under G over F satisfy a local global principle for rational points with respect to discrete valuations of F . If G is a semisimpl

Denis dos Reis, Marcílio de Souto, Elaine de Sousa, Gustavo Batista

Quantification is the research field that studies methods for counting the number of data points that belong to each class in an unlabeled sample. Traditionally, researchers in this field assume the availability of labelled observations for all classes to induce a quantification model. However, we often face situations where the number of classes is large or

Ariel Norambuena, Alejandro Jimenez, Christoph Becher, Jerónimo R. Maze

The unavoidable presence of vibrations in solid-state devices can drastically modify the expected electron spin resonance (ESR) absorption spectrum in magnetically active systems. In this work, we model the effect of phonons and temperature on the ESR signal in molecular systems with strong $E \otimes e$ Jahn-Teller (JT) effect and an electronic spin-$1/2$.

Jon McCormack, Ben Porter, James Wetter

We describe a flexible, script-based system for the procedural generation and animation of 3D geometry. Dynamic triangular meshes are generated through the real-time execution of scripts written in the Lua programming language. Tight integration between the programming environment, runtime engine and graphics visualisation enables a workflow between coding a

Aryaman Arora, Luke Gessler, Nathan Schneider

Hindi grapheme-to-phoneme (G2P) conversion is mostly trivial, with one exception: whether a schwa represented in the orthography is pronounced or unpronounced (deleted). Previous work has attempted to predict schwa deletion in a rule-based fashion using prosodic or phonetic analysis. We present the first statistical schwa deletion classifier for Hindi, which

James Hope, Matthew Goodwin, Frederique Vanholsbeeck

Significance: Imaging neural activity in myelinated tissue using optical coherence tomography (OCT) creates new possibilities for functional imaging in the peripheral and central nervous systems. Aim: To investigate changes in OCT images in response to evoked neural activity in sciatic nerve of rat in vitro. Approach: M-scans were obtained on peripheral nerv

TJ Tsai, Daniel Yang, Mengyi Shan, Thitaree Tanprasert

This article investigates a cross-modal retrieval problem in which a user would like to retrieve a passage of music from a MIDI file by taking a cell phone picture of several lines of sheet music. This problem is challenging for two reasons: it has a significant runtime constraint since it is a user-facing application, and there is very little relevant train

Anand Pillay, Philipp Rothmaler

We ask some questions and make some observations about the (complete) theory T (infinity, V) of free algebras in V on infinitely many generators, where V is a variety in the sense of universal algebra. We focus on the case T(infinity, R) where V is the variety of R-modules (R a ring). Building on work in Kucera-Pillay we characterize when all models of T(inf

Ahmed Al-Taweel, Xiaoshen Wang, Xiu Ye, Shangyou Zhang

The weak Galerkin (WG) finite element method is an effective and flexible general numerical techniques for solving partial differential equations. A simple weak Galerkin finite element method is introduced for second order elliptic problems. First we have proved that stabilizers are no longer needed for this WG element. Then we have proved the supercloseness

Sabah Al-Fedaghi, Dana Al-Qemlas

The Internet s ability to support a wide range of services depends on the network architecture and theoretical and practical innovations necessary for future networks. Network architecture in this context refers to the structure of a computer network system as well as interactions among its physical components, their configuration, and communication protocol

S. M. Kamrul Hasan, Cristian A. Linte

In this work, we implement a fully convolutional segmenter featuring both a learned group structure and a regularized weight-pruner to reduce the high computational cost in volumetric image segmentation. We validated our framework on the ACDC dataset featuring one healthy and four pathology groups imaged throughout the cardiac cycle. Our technique achieved D

Ahmed Sabir, Francesc Moreno-Noguer, Lluís Padró

Text Spotting in the wild consists of detecting and recognizing text appearing in images (e.g. signboards, traffic signals or brands in clothing or objects). This is a challenging problem due to the complexity of the context where texts appear (uneven backgrounds, shading, occlusions, perspective distortions, etc.). Only a few approaches try to exploit the r

Hsu-Chuan Hsu, Tsung-Wei Chen

In the long-range Su-Schriffer-Heeger (SSH) model, in which the next nearest-neighbor hopping is considered, there exhibits a rich topological phase diagram that contains winding numbers $w=0, 1$, and $2$. In the presence of disorder, the change in mean winding number with various disorder strengths is numerically calculated. We find that the disorder drives

Daniel Yang, Thitaree Tanprasert, Teerapat Jenrungrot, Mengyi Shan

This paper investigates a cross-modal retrieval problem in which a user would like to retrieve a passage of music from a MIDI file by taking a cell phone picture of a physical page of sheet music. While audio-sheet music retrieval has been explored by a number of works, this scenario is novel in that the query is a cell phone picture rather than a digital sc

Yu-Hsiang Liu

This paper is a continuation of author's previous work arXiv:1911.07949, where we defined Donaldson-Thomas invariants of quantum Fermat threefolds. In this paper, we study the generic quantum Fermat threefold. We give explicit local models for Hilbert schemes of points as quivers with potential, and compute degree zero Donaldson-Thomas invariants. The result

Thitaree Tanprasert, Teerapat Jenrungrot, Meinard Mueller, T. J. Tsai

MIDI-sheet music alignment is the task of finding correspondences between a MIDI representation of a piece and its corresponding sheet music images. Rather than using optical music recognition to bridge the gap between sheet music and MIDI, we explore an alternative approach: projecting the MIDI data into pixel space and performing alignment in the image dom

Scott E. Smart, David A. Mazziotti

Quantum chemistry provides key applications for near-term quantum computing, but these are greatly complicated by the presence of noise. In this work we present an efficient ansatz for the computation of two-electron atoms and molecules within a hybrid quantum-classical algorithm. The ansatz exploits the fundamental structure of the two-electron system, and

Pratik Das, H. S. Udaykumar

The vaporization rate of aluminum droplets in shocked flows plays a crucial role in determining the energy release rate during the combustion of the aluminized energetic materials. In this paper, the physics of the vaporization of aluminum droplets in shocked flows is numerically investigated. Surrogate models for the temporally averaged Sherwood number and

Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

We consider learning a multi-class classification model in the federated setting, where each user has access to the positive data associated with only a single class. As a result, during each federated learning round, the users need to locally update the classifier without having access to the features and the model parameters for the negative classes. Thus,

Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique

Many convolutional neural network (CNN) accelerators face performance- and energy-efficiency challenges which are crucial for embedded implementations, due to high DRAM access latency and energy. Recently, some DRAM architectures have been proposed to exploit subarray-level parallelism for decreasing the access latency. Towards this, we present a design spac

Sara Beery, Elijah Cole, Arvi Gjoka

Camera traps enable the automatic collection of large quantities of image data. Biologists all over the world use camera traps to monitor animal populations. We have recently been making strides towards automatic species classification in camera trap images. However, as we try to expand the geographic scope of these models we are faced with an interesting qu

E. P. Segarra, F. Hauenstein, A. Schmidt, A. Beck

The Backward Angle Neutron Detector (BAND) of CLAS12 detects neutrons emitted at backward angles of $155^\circ$ to $175^\circ$, with momenta between $200$ and $600$ MeV/c. It is positioned 3 meters upstream of the target, consists of $18$ rows and $5$ layers of $7.2$ cm by $7.2$ cm scintillator bars, and read out on both ends by PMTs to measure time and ener

Giovanni Dietler, Robert Kusner, Wöden Kusner, Eric Rawdon

Chiral objects rotate when placed in a collimated flow or wind. We exploit this hydrodynamic intuition to construct a tensorial chirality measure for rigid filaments and curves. This tensor is trace-free, so if a curve has a right-handed twist about some axis, there is a perpendicular axis about which the twist is left-handed. Our measure places minimal requ

Karush Suri, Rinki Gupta

Advancements in gesture recognition algorithms have led to a significant growth in sign language translation. By making use of efficient intelligent models, signs can be recognized with precision. The proposed work presents a novel one-dimensional Convolutional Neural Network (CNN) array architecture for recognition of signs from the Indian sign language usi

Paul N Zivich, Alexander Breskin

Modern causal inference methods allow machine learning to be used to weaken parametric modeling assumptions. However, the use of machine learning may result in complications for inference. Doubly-robust cross-fit estimators have been proposed to yield better statistical properties. We conducted a simulation study to assess the performance of several differen

Wenjian Liu

Relativistic quantum chemistry has evolved into a fertile and large field and is now becoming an integrated part of mainstream chemistry. Yet, given the much-involved physics and mathematics (as compared with nonrelativistic quantum chemistry), it is still necessary to clean up the essentials underlying the relativistic electronic structure theories and meth

Isidoros Marougkas, Petros Koutras, Nikos Kardaris, Georgios Retsinas

We present a novel multi-attentional convolutional architecture to tackle the problem of real-time RGB-D 6D object pose tracking of single, known objects. Such a problem poses multiple challenges originating both from the objects' nature and their interaction with their environment, which previous approaches have failed to fully address. The proposed framewo

Shaohui Liu, Daniel Adrian Maldonado, Emil M. Constantinescu

In this paper we present a probabilistic analysis framework to estimate behind-the-meter photovoltaic generation in real time. We develop a forward model consisting of a spatiotemporal stochastic process that represents the photovoltaic generation and a stochastic differential equation with jumps that represents the demand. We employ this model to disaggrega

Antenor Ostine

In this paper, using a basic algebraic approach, we demonstrate that, if the integers $x,y$ and $z$ are pairwise relatively prime, and $x^p-my^p=zw$ where $m$ is an integer and $p$ is a prime, then we can write $x,y,m,z$ and $w$ as explicit expressions in 7 integers.

Jean-Marc Azaïs, Federico Dalmao, José R. León

We consider the winding number of planar stationary Gaussian processes defined on the line. Under mild conditions, we obtain the asymptotic variance and the Central Limit Theorem for the winding number as the time horizon tends to infinity. In the asymptotic regime, our discrete approach is equivalent to the continuous one studied previously in the literatur

Ran Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay Vargaftik

Counters are a fundamental building block for networking applications such as load balancing, traffic engineering, and intrusion detection, which require estimating flow sizes and identifying heavy hitter flows. Existing works suggest replacing counters with shorter multiplicative error \emph{estimators} that improve the accuracy by fitting more of them with

Tyler Westenbroek, Fernando Castaneda, Ayush Agrawal, S. Shankar Sastry

This paper introduces a framework for learning a minimum-norm stabilizing controller for a system with unknown dynamics using model-free policy optimization methods. The approach begins by first designing a Control Lyapunov Function (CLF) for a (possibly inaccurate) dynamics model for the system, along with a function which specifies a minimum acceptable rat

Taisa Kushner, Amit Sharma

Recent years have seen a rise in social media platforms that provide peer-to-peer support to individuals suffering from mental distress. Studies on the impact of these platforms have focused on either short-term scales of single-post threads, or long-term changes over arbitrary period of time (months or years). While important, such arbitrary periods do not

Han Gao, Luning Sun, Jian-Xun Wang

Recently, the advent of deep learning has spurred interest in the development of physics-informed neural networks (PINN) for efficiently solving partial differential equations (PDEs), particularly in a parametric setting. Among all different classes of deep neural networks, the convolutional neural network (CNN) has attracted increasing attention in the scie

Maria Bras-Amoros, Marly Gotti

A Puiseux monoid is a submonoid of $(\mathbb{Q},+)$ consisting of nonnegative rational numbers. Although the operation of addition is continuous with respect to the standard topology, the set of irreducibles of a Puiseux monoid is, in general, difficult to describe. In this paper, we use topological density to understand how much a Puiseux monoid, as well as

Tin Sulejmanpasic, Yuya Tanizaki, Mithat Ünsal

We study low-energy dynamics of $[SU(N)]^K$ chiral quiver gauge theories in connection with $\mathcal{N}=1$ super Yang-Mills (SYM) theory, and quantum chromodynamics with bi-fundamental fermions (QCD(BF)). These theories can be obtained by $\mathbb{Z}_K$ orbifold projections of $\mathcal{N}=1$ $SU(NK)$ SYM theory, but the perturbative planar equivalence does

K. G Paulson, Ekta Panwar, Subhashish Banerjee, R. Srikanth

We investigate the dynamics of quantum correlations (QC) under the effects of reservoir memory, as a resource for quantum information and computation tasks. Quantum correlations of two-qubit systems are used for implementing quantum teleportation successfully, and for investigating how teleportation fidelity, violation of Bell-CHSH inequality, quantum steeri

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg

We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Constructing Graph (SCG) module, which makes use of learnable latent variables to self-construct the underlying graphs directly from the input features without relying on manually bu

Hyoshin Kim, Nancy McMillan, Jeffrey Geppert, Laura Aume

Objective: To evaluate differences in major outcomes between Bundled Payments for Care Improvement (BPCI) participating providers and non-participating providers for both Major Joint Replacement of the Lower Extremity (MJRLE) and Acute Myocardial Infarction (AMI) episodes. Methods: A difference-in-differences approach estimated the differential change in out

Yixuan Huang, Pavan Hosur, Hridis K. Pal

We study the single- and many-particle properties of a two-leg ladder model threaded by a flux with the legs coupled by a spatially varying term. Although a priori unrelated to twisted bilayer graphene (TBG), the model is found to have striking similarities: a quasi-flat low-energy band emerges with characteristics similar to that of magic angle TBG. We stud

David Gershon, Alexander Lipton, Hagai Levine

We analyze an approach to managing the COVID-19 pandemic without shutting down the economy while staying within the capacity of the healthcare system. We base our analysis on a detailed heterogeneous epidemiological model, which takes into account different population groups and phases of the disease, including incubation, infection period, hospitalization,

Asmaa Alrushoud, Ning Lu

This paper presents a new method for assessing the amount of photovoltaics that can be accommodated on a distribution feeder before disrupting the normal operational conditions, commonly referred to hosting capacity. An optimal-capacity-based (OCB) PV allocation method is proposed to evaluate PV hosting capacity. We fist use load allocation method to allocat

Tonghe Wang, Yang Lei, Yabo Fu, Walter J. Curran

This paper reviewed the deep learning-based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning-based methods in inter- and intra-modality image synthesis by listing and highlighting the proposed methods, study designs and reported performances with related clinical applicat

Haifa Ben Fredj, Farouk Chérif

In this paper, we propose a new model for the dynamics of COVID-19 infections. Our approach consists of seven phenotypes: the susceptible humans, exposed humans, infectious humans, the recovered humans, the quarantine population, the recovered-exposed and deceased population. We proved first through mathematical approach the positivity, boundness and existen

Yanan Jia, Sony SungChu

Sentiment analysis is crucial for the advancement of artificial intelligence (AI). Sentiment understanding can help AI to replicate human language and discourse. Studying the formation and response of sentiment state from well-trained Customer Service Representatives (CSRs) can help make the interaction between humans and AI more intelligent. In this paper,

Sebastian Forster, Gramoz Goranci, Monika Henzinger

We give the first non-trivial fully dynamic probabilistic tree embedding algorithm for weighted graphs undergoing edge insertions and deletions. We obtain a trade-off between amortized update time and expected stretch against an oblivious adversary. At the two extremes of this trade-off, we can maintain a tree of expected stretch $ O (\log^4 n) $ with update

Wanling Qiu, Simon Rudkin, Pawel Dlotko

Corporate failure resonates widely leaving practitioners searching for understanding of default risk. Managers seek to steer away from trouble, credit providers to avoid risky loans and investors to mitigate losses. Applying Topological Data Analysis tools this paper explores whether failing firms from the United States organise neatly along the five predict

A. Markhotok

A recently proposed technique for improving ignition timing is investigated for real-gas effects. A correction to the model describing the cumulative energy effect in the presence of the shock-discontinuity interaction was done by re-considering the RH-relations and the shock refraction equations. Non-dissociating gas in thermal equilibrium state, with excit

Stefan Ankirchner, Thomas Kruse, Wolfgang Löhr, Mikhail Urusov

We prove several properties of the EMCEL scheme, which is capable of approximating one-dimensional continuous strong Markov processes in distribution on the path space (the scheme is briefly recalled). Special cases include irregular stochastic differential equations and processes with sticky features. In particular, we highlight differences from the Euler s

Daniel LaChapelle, Todd Humphreys, Lakshay Narula, Peter Iannucci

This paper offers a technique for estimating collision risk for automated ground vehicles engaged in cooperative sensing. The technique allows quantification of (i) risk reduced due to cooperation, and (ii) the increased accuracy of risk assessment due to cooperation. If either is significant, cooperation can be viewed as a desirable practice for meeting the

Binping Xiao, M. Blaskiewicz, T. Xin

For the radiofrequency (RF) applications of normal conducting film with large mean free path at high frequency and low temperature, the anomalous skin effect differs considerably from the normal skin effect with field decaying exponentially in the film. Starting from the relationship between the current and the electric field (E field) in the film, the ampli

Jan Sedmidubsky, Pavel Zezula

The popular task of 3D human action recognition is almost exclusively solved by training deep-learning classifiers. To achieve a high recognition accuracy, the input 3D actions are often pre-processed by various normalization or augmentation techniques. However, it is not computationally feasible to train a classifier for each possible variant of training da

Baihan Lin

This paper proposed a new interaction paradigm in the virtual reality (VR) environments, which consists of a virtual mirror or window projected onto a virtual surface, representing the correct perspective geometry of a mirror or window reflecting the real world. This technique can be applied to various videos, live streaming apps, augmented and virtual reali

Xin Sun, Piotr Kulicki, Mirek Sopek

This paper propose a protocol for lottery and a protocol for auction on quantum Blockchain. Our protocol of lottery satisfies randomness, unpredictability, unforgeability, verifiability, decentralization and unconditional security. Our protocol of auction satisfies bid privacy, posterior privacy, bids' binding, decentralization and unconditional security. Ex

Christopher Lane

We present an exact treatment of layered many-body electronic systems in the presence of interlayer coupling within the Schwinger functional derivative approach on the Keldysh contour. Our transparent approach allows us to clarify the definition of interlayer coupling by showing the independent roles hybridization and interactions play in generating new elec

J. Götzfried, A. Döpp, M. Gilljohann, M. Foerster

Laser wakefield acceleration (LWFA) and its particle-driven counterpart, plasma wakefield acceleration (PWFA), are commonly treated as separate, though related branches of high-gradient plasma-based acceleration. However, novel proposed schemes are increasingly residing at the interface of both concepts where the understanding of their interplay becomes cruc

Lucas A. Souza, Rodrigo Negreiros, Mariana Dutra, Débora P. Menezes

Short range correlations (SRC) have been known to be an important aspect of nuclear theory for some time. Recent works have re-ignited interest on this topic, particularly due to the fact that it has recently been demonstrated that SRC may be responsible for breaking pairing gaps in nuclear matter. In this work we revisit the concept of SRC for beta equilibr

Yacov Hel-Or, Gil Ben-Artzi

Wavelet denoising is a classical and effective approach for reducing noise in images and signals. Suggested in 1994, this approach is carried out by rectifying the coefficients of a noisy image in the transform domain, using a set of scalar shrinkage function (SFs). A plethora of papers deals with the optimal shape of the SFs and the transform used, where it

Tim Daubenschuetz, Oksana Kulyk, Stephan Neumann, Isabella Hinterleitner

The global SARS-CoV-2 pandemic is currently putting a massive strain on the world's critical infrastructures. With healthcare systems and internet service providers already struggling to provide reliable service, some operators may, intentionally or unintentionally, lever out privacy-protecting measures to increase their system's efficiency in fighting the v

Kilian Fritsch, Jonathan Brons, Maksim Iandulskii, Ka Fai Mak

For the first time to our knowledge, a dual-comb laser based on thin-disk technology and its application to direct frequency comb spectroscopy are presented. The peak power (0.6 MW) and the average power (12 W) of our Yb:YAG thin-disk dual-comb system are more than one-order-of-magnitude higher than in any previous systems. The scheme allows easy adjustment

Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer

Model-based methods are the dominant paradigm for controlling robotic systems, though their efficacy depends heavily on the accuracy of the model used. Deep neural networks have been used to learn models of robot dynamics from data, but they suffer from data-inefficiency and the difficulty to incorporate prior knowledge. We introduce Structured Mechanical Mo

Ryan Sanford, Siavash Gorji, Luiz G. Hafemann, Bahareh Pourbabaee

Group activity detection in soccer can be done by using either video data or player and ball trajectory data. In current soccer activity datasets, activities are labelled as atomic events without a duration. Given that the state-of-the-art activity detection methods are not well-defined for atomic actions, these methods cannot be used. In this work, we evalu

Benjamin Plotkin-Swing, Anna Wirth, Daniel Gochnauer, Tahiyat Rahman

We demonstrate a method to enhance the atom loading rate of a ytterbium (Yb) magneto-optic trap (MOT) operating on the 556 nm ${^1S}_0 \rightarrow {^3P}_1$ intercombination transition (narrow linewidth $\Gamma_g = 2\pi \times 182$ kHz). Following traditional Zeeman slowing of an atomic beam near the 399 nm ${^1S}_0 \rightarrow {^1P}_1$ transition (broad line

P. Mukherjee, J. A. M. Paddison, C. Xu, Z. Ruff

We present a structural and magnetic study on two batches of polycrystalline LiNi$_{0.8}$Mn$_{0.1}$Co$_{0.1}$O$_2$ (commonly known as Li NMC 811), a Ni-rich Li ion battery cathode material, using elemental analysis, X-ray and neutron diffraction, magnetometry, and polarised neutron scattering measurements. We find that the samples, labelled S1 and S2, have t

S. A. Grebenev, R. A. Sunyaev

We show that Compton scattering by electrons of the hot intergalactic gas in galaxy clusters should lead to peculiar distortions of the cosmic background X-ray and soft gamma-ray radiation - an increase in its brightness at E<60-100 keV and a drop at higher energies. The distortions allow the most important cluster parameters to be measured. The spectral sha

Xavier Romain, Riccardo Degl'Innocenti, Fadi I. Baida, Philippe Boyer

Stacked metasurfaces are being investigated in light of exploring exotic optical effects that cannot be achieved with single-layered metasurfaces. In this Letter, we theoretically demonstrate that stacks of metallic wire-grid metasurfaces possessing specific polarization properties have the ability to induce tunable Fano resonances. The developed original mo

Kyle Morgenstein

Radio interferometry is the current method of choice for deep space astronomy, but in the past few decades optical techniques have become increasingly common. This research seeks to characterize the performance of aperture masking interferometry in the near-infrared at small scales. A mask containing six pairs of apertures at varying diameters and separation

Xu Shen, Ivo Batkovic, Vijay Govindarajan, Paolo Falcone

We investigate the problem of predicting driver behavior in parking lots, an environment which is less structured than typical road networks and features complex, interactive maneuvers in a compact space. Using the CARLA simulator, we develop a parking lot environment and collect a dataset of human parking maneuvers. We then study the impact of model complex

J. H. Chaudhry, A. E. Rappaport, J. N. Shadid

Magnetohydrodynamics (MHD) is a continuum level model for conducting fluids subject to external magnetic fields, e.g. plasmas and liquid metals. The efficient and robust solution of the MHD system poses many challenges due to it's nonlinear, non self-adjoint, and highly coupled nature. In this paper, we develop a robust and accurate a posteriori error estima

Martín H. Félix-Medina

Currently the COVID-19 epidemic is developing in the City of Culiac\'n Sinaloa, Mexico, where up to April 20 of this year there have been 35 deaths associated with this epidemic. The reproduction number $(R_0)$ of an epidemic represents the average number of people infected by an infected person during their period of infection. In this work we use the data

Jianping Lin, Dong Liu, Houqiang Li, Feng Wu

We propose an end-to-end learned video compression scheme for low-latency scenarios. Previous methods are limited in using the previous one frame as reference. Our method introduces the usage of the previous multiple frames as references. In our scheme, the motion vector (MV) field is calculated between the current frame and the previous one. With multiple r

Aysegul Dundar, Karan Sapra, Guilin Liu, Andrew Tao

Conditional image synthesis for generating photorealistic images serves various applications for content editing to content generation. Previous conditional image synthesis algorithms mostly rely on semantic maps, and often fail in complex environments where multiple instances occlude each other. We propose a panoptic aware image synthesis network to generat

Manuel Baltieri

The connections between optimal control and Bayesian inference have long been recognised, with the field of stochastic (optimal) control combining these frameworks for the solution of partially observable control problems. In particular, for the linear case with quadratic functions and Gaussian noise, stochastic control has shown remarkable results in differ

Nassif Ghoussoub, Young-Heon Kim, Hugo Lavenant, Aaron Zeff Palmer

We study compressible and incompressible nonlinear elasticity variational problems in a general context. Our main result gives a sufficient condition for an equilibrium to be a global energy minimizer, in terms of convexity properties of the pressure in the deformed configuration. We also provide a convex relaxation of the problem together with its dual form

Miguel Angel Martin Contreras, Alfredo Vega

In this work, we consider a non-quadratic dilaton $\Phi(z)=(\kappa\,z)^{2-\alpha}$ in the context of the static soft wall model to describe the mass spectrum of a wide range of vector mesons from the light up to the heavy sectors. The effect of this non-quadratic approach is translated into non-linear Regge trajectories with the generic form $M^2=a\,(n+b)^\n

S. Omar, M. Gurram, K. Watanabe, T. Taniguchi

The current generation of spintronic devices, which use electron-spin relies on linear operations for spin-injection, transport and detection processes. The existence of nonlinearity in a spintronic device is indispensable for spin-based complex signal processing operations. Here we for the first time demonstrate the presence of electron-spin dependent nonli

Hermann Karcher

We use ODEs and symmetry arguments to construct closed constant curvature space curves, first on cylinders, next on tori, at last with the Frenet-Serret equations.

Georg Rehm

The annotation of textual information is a fundamental activity in Linguistics and Computational Linguistics. This article presents various observations on annotations. It approaches the topic from several angles including Hypertext, Computational Linguistics and Language Technology, Artificial Intelligence and Open Science. Annotations can be examined along

Malte Hoffmann, Benjamin Billot, Douglas N. Greve, Juan Eugenio Iglesias

We introduce a strategy for learning image registration without acquired imaging data, producing powerful networks agnostic to contrast introduced by magnetic resonance imaging (MRI). While classical registration methods accurately estimate the spatial correspondence between images, they solve an optimization problem for every new image pair. Learning-based

Matthew Wicker, Luca Laurenti, Andrea Patane, Marta Kwiatkowska

We study probabilistic safety for Bayesian Neural Networks (BNNs) under adversarial input perturbations. Given a compact set of input points, $T \subseteq \mathbb{R}^m$, we study the probability w.r.t. the BNN posterior that all the points in $T$ are mapped to the same region $S$ in the output space. In particular, this can be used to evaluate the probabilit

Niklas Friedrich, Pedro Brandimarte, Jingcheng Li, Shohei Saito

Graphene nanoribbons (GNRs), low-dimensional platforms for carbon-based electronics, show the promising perspective to also incorporate spin polarization in their conjugated electron system. However, magnetism in GNRs is generally associated to localized states around zigzag edges, difficult to fabricate and with high reactivity. Here we demonstrate that mag

Vasundhra Iyengar, Azra Bihorac, Parisa Rashidi

Sleep has been shown to be an indispensable and important component of patients recovery process. Nonetheless, sleep quality of patients in the Intensive Care Unit (ICU) is often low, due to factors such as noise, pain, and frequent nursing care activities. Frequent sleep disruptions by the medical staff and/or visitors at certain times might lead to disrupt

Andreas B. Michelsen, Thomas L. Schmidt, Edvin G. Idrisov

We study Cooper pair transport through a quantum point contact between a superconductor and a quantum Hall edge state at integer and fractional filling factors. We calculate the tunnelling current and its finite-frequency noise to the leading order in the tunneling amplitude for dc and ac bias voltage in the limit of low temperatures. At zero temperature and

Yanbin Pan, Jun Xu, Nick Wadleigh, Qi Cheng

Any ideal in a number field can be factored into a product of prime ideals. In this paper we study the prime ideal shortest vector problem (SVP) in the ring $ \Z[x]/(x^{2^n} + 1) $, a popular choice in the design of ideal lattice based cryptosystems. We show that a majority of rational primes lie under prime ideals admitting a polynomial time algorithm for S

D. A. Artemenkov, V. Bradnova, M. M. Chernyavsky, E. Firu

The invariant mass method is used to identify the $^8$Be and $^9$B nuclei and Hoyle state formed in dissociation of relativistic nuclei in a nuclear track emulsion. It is shown that to identify these extremely short-lived states in the case of the isotopes $^9$Be, $^{10}$B, $^{10}$C, $^{11}$C, $^{12}$C, and $^{16}$O, it is sufficient to determine the invaria

Dimitrios Kallergis, Zacharenia Garofalaki, Georgios Katsikogiannis, Christos Douligeris

The microservices architectural approach has important benefits regarding the agile applications' development and the delivery of complex solutions. However, to convey the information and share the data amongst services in a verifiable and stateless way, there is a need to enable appropriate access control methods and authorisations. In this paper, we study

Michael Alan Chang, Domenic Bottini, Lisa Jian, Pranay Kumar

Deep Neural Nets have hit quite a crest, But physical networks are where they must rest, And here we put them all to the test, To see which network optimization is best.

Bálint Mészáros, Hugo Sámano-Sánchez, Jesús Alvarado-Valverde, Jelena Čalyševa

The primary cell surface receptor for SARS-CoV-2 is the angiotensin-converting enzyme 2 (ACE2). Recently it has been noticed that the viral Spike protein has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif resource, ELM, and were presented with candidat

Jorge L. Ramirez Alfonsin, Mariusz Skalba

Let 0 < a < b be two relatively prime integers and let <a,b> be the numerical semigroup generated by a and b with Frobenius number g(a,b)=ab-a-b. In this note, we prove that there exists a prime number p in <a,b> with p < g(a,b) when the product ab is sufficiently large. Two related conjectures are posed and discussed as well.

Ian E. Ochs, Nathaniel J. Fisch

For an electrostatic wave interacting with a single species in a collisionless plasma, momentum conservation implies current conservation. However, when multiple species interact with the wave, they can exchange momentum, leading to current drive. A simple, general formula for this driven current is derived. As examples, we show how currents can be driven fo

Xiaoxiao Sun, Wenxuan Zhong, Ping Ma

Large samples have been generated routinely from various sources. Classic statistical models, such as smoothing spline ANOVA models, are not well equipped to analyze such large samples due to expensive computational costs. In particular, the daunting computational costs of selecting smoothing parameters render smoothing spline ANOVA models impractical. In th

Devansh Mehta, Sebastin Santy, Ramaravind Kommiya Mothilal, Brij Mohan Lal Srivastava

The primary obstacle to developing technologies for low-resource languages is the lack of usable data. In this paper, we report the adoption and deployment of 4 technology-driven methods of data collection for Gondi, a low-resource vulnerable language spoken by around 2.3 million tribal people in south and central India. In the process of data collection, we

Rob Burns

We consider the sum of squares function in the ring $\mathbb{Z}_{n}$. We determine formulae in a number of cases when $n$ is a power of a prime.

A. Denniston, E. P. Segarra, A. Schmidt, A. Beck

A laser calibration system was developed for monitoring and calibrating time of flight (TOF) scintillating detector arrays. The system includes setups for both small- and large-scale scintillator arrays. Following test-bench characterization, the laser system was recently commissioned in experimental Hall B at the Thomas Jefferson National Accelerator Facili

Alexander Hanbo Li, Yaqing Wang, Changyou Chen, Jing Gao

Effective inference for a generative adversarial model remains an important and challenging problem. We propose a novel approach, Decomposed Adversarial Learned Inference (DALI), which explicitly matches prior and conditional distributions in both data and code spaces, and puts a direct constraint on the dependency structure of the generative model. We deriv

Kumar Venkataramani, Shashikiran Ganesh, Kiran S. Baliyan

We carried out observations of a peculiar comet, C/2016 R2 (Pan-STARRS), using a low resolution spectrograph mounted on the 1.2m telescope at Mount Abu Infrared Observatory, India. The comet was observed on two dates in January 2018, when it was at a heliocentric distance of 2.8 AU. Study based on our observations revealed that the optical spectrum of this c

Nicholas Vincent, Brent Hecht

A growing body of work has highlighted the important role that Wikipedia's volunteer-created content plays in helping search engines achieve their core goal of addressing the information needs of millions of people. In this paper, we report the results of an investigation into the incidence of Wikipedia links in search engine results pages (SERPs). Our resul