November 2019 arXiv papers — page 71

André Artelt, Barbara Hammer

Due to the increasing use of machine learning in practice it becomes more and more important to be able to explain the prediction and behavior of machine learning models. An instance of explanations are counterfactual explanations which provide an intuitive and useful explanations of machine learning models. In this survey we review model-specific methods fo

Jaroslav Nesetril, Patrice Ossona de Mendez, Roman Rabinovich, Sebastian Siebertz

Classes with bounded rankwidth are MSO-transductions of trees and classes with bounded linear rankwidth are MSO-transductions of paths. These results show a strong link between the properties of these graph classes considered from the point of view of structural graph theory and from the point of view of finite model theory. We take both views on classes wit

Qun Liu, Saikat Basu, Sangram Ganguly, Supratik Mukhopadhyay

Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent in satellite data, most of the current object classification approaches are not suitable for handling satellite datasets. The progress of satellite image analytics has also been inh

Minjia Shi, Tor Helleseth, Patrick Sole

Let $p$ be a prime number. Irreducible cyclic codes of length $p^2-1$ and dimension $2$ over the integers modulo $p^h$ are shown to have exactly two nonzero Hamming weights. The construction uses the Galois ring of characteristic $p^h$ and order $p^{2h}.$ When the check polynomial is primitive, the code meets the Griesmer bound of (Shiromoto, Storme) (2012).

Xiangzhu Meng, Huibing Wang, Lin Feng

During the last decades, learning a low-dimensional space with discriminative information for dimension reduction (DR) has gained a surge of interest. However, it's not accessible for these DR methods to achieve satisfactory performance when facing the features from multiple views. In multi-view learning problems, one instance can be represented by multi

Alena Harley

Determining the primary site of origin for metastatic tumors is one of the open problems in cancer care because the efficacy of treatment often depends on the cancer tissue of origin. Classification methods that can leverage tumor genomic data and predict the site of origin are therefore of great value. Because tumor DNA point mutation data is very sparse, o

Xianfu Chen, Tao Chen, Zhifeng Zhao, Honggang Zhang

This paper investigates an unmanned aerial vehicle (UAV)-assisted mobile-edge computing (MEC) system, in which the UAV provides complementary computation resource to the terrestrial MEC system. The UAV processes the received computation tasks from the mobile users (MUs) by creating the corresponding virtual machines. Due to finite shared I/O resource of the

Linara Adilova, Julia Rosenzweig, Michael Kamp

An approach to distributed machine learning is to train models on local datasets and aggregate these models into a single, stronger model. A popular instance of this form of parallelization is federated learning, where the nodes periodically send their local models to a coordinator that aggregates them and redistributes the aggregation back to continue train

Yan Zhang, Steve Farrell, Michael Crowley, Lee Makowski

An image dataset of 10 different size molecules, where each molecule has 2,000 structural variants, is generated from the 2D cross-sectional projection of Molecular Dynamics trajectories. The purpose of this dataset is to provide a benchmark dataset for the increasing need of machine learning, deep learning and image processing on the study of scattering, im

D. T. Tran, S. Terashima, H. J. Ong, K. Hirakawa

We have constructed and tested a novel plastic-scintillator-based solid-state active proton target for use in nuclear spectroscopic studies with nuclear reactions induced by an ion beam in inverse kinematics. The active target system, named Stack Structure Solid organic Scintillator Active Target (S4AT), consists of five layers of plastic scintillators, each

Atul Sahay, Smita Gholkar, Kavi Arya

e-Yantra Robotics Competition (eYRC) is a unique Robotics Competition hosted by IIT Bombay that is actually an Embedded Systems and Robotics MOOC. Registrations have been growing exponentially in each year from 4500 in 2012 to over 34000 in 2019. In this 5-month long competition students learn complex skills under severe time pressure and have access to a di

Achyudh Ram, Ji Xin, Meiyappan Nagappan, Yaoliang Yu

Public vulnerability databases such as CVE and NVD account for only 60% of security vulnerabilities present in open-source projects, and are known to suffer from inconsistent quality. Over the last two years, there has been considerable growth in the number of known vulnerabilities across projects available in various repositories such as NPM and Maven Centr

Aisha Khatun, Anisur Rahman, Hemayet Ahmed Chowdhury, Md. Saiful Islam

Language models are at the core of natural language processing. The ability to represent natural language gives rise to its applications in numerous NLP tasks including text classification, summarization, and translation. Research in this area is very limited in Bangla due to the scarcity of resources, except for some count-based models and very recent neura

James Enouen

When shuffling a deck of cards, one probably wants to make sure it is thoroughly shuffled. A way to do this is by sifting through the cards to ensure that no adjacent cards are the same number, because surely this is a poorly shuffled deck. Unfortunately, human intuition for probability tends to lead us astray. For a standard 52-card deck of playing cards, t

Jung-Woo Chang, Saehyun Ahn, Keon-Woo Kang, Suk-Ju Kang

Generative adversarial networks (GANs) have shown excellent performance in image and speech applications. GANs create impressive data primarily through a new type of operator called deconvolution (DeConv) or transposed convolution (Conv). To implement the DeConv layer in hardware, the state-of-the-art accelerator reduces the high computational complexity via

Rubin Abrams, Sunhi Choi

We study a parabolic free boundary problem, arising from a model for the propagation of equi-diffusional premixed flames with high activation energy. If an initial data is compactly supported, then the solution vanishes in a finite time, called the extinction time. In this paper, we give a quantitative estimate on the flatness of the free boundary and prove

Ilya Valmianski, Caleb Goodwin, Ian M. Finn, Naqi Khan

Automated classification of chief complaints from patient-generated text is a critical first step in developing scalable platforms to triage patients without human intervention. In this work, we evaluate several approaches to chief complaint classification using a novel Chief Complaint (CC) Dataset that contains ~200,000 patient-generated reasons-for-visit e

Andres Contreras, Robert L. Jerrard

A central focus of Ginzburg-Landau theory is the understanding and characterization of vortex configurations. On a bounded domain $Ω\subseteq \mathbb{R}^2,$ global minimizers, and critical states in general, of the corresponding energy functional have been studied thoroughly in the limit $ε\to 0,$ where $ε>0$ is the inverse of the Ginzburg-Landau parameter.

Dhruva Kartik, Ashutosh Nayyar, Urbashi Mitra

Two active hypothesis testing problems are formulated. In these problems, the agent can perform a fixed number of experiments and then decide on one of the hypotheses. The agent is also allowed to declare its experiments inconclusive if needed. The first problem is an asymmetric formulation in which the the objective is to minimize the probability of incorre

Sunhi Choi, Inwon Kim

We consider a nonlinear Neumann problem, with periodic oscillation in the elliptic operator and on the boundary condition. Our focus is on problems posed in half-spaces, but with general normal directions that may not be parallel to the directions of periodicity. As the frequency of the oscillation grows, quantitative homogenization results are derived. When

Daniela D. Doneva, Stoytcho S. Yazadjiev

In the present paper we demonstrate that there exists a new type of neutron stars in the tensor-multi-scalar theories of gravity. We call this new type of neutron stars topological neutron stars. In addition to the standard characteristics of the usual neutron stars the topological neutron stars are also characterized by a topological charge. We numerical co

Greg Bodwin, Ofer Grossman

In many combinatorial games, one can prove that the first player wins under best play using a simple but non-constructive argument called strategy-stealing. This work is about the complexity behind these proofs: how hard is it to actually find a winning move in a game, when you know by strategy-stealing that one exists? We prove that this problem is PSPACE-h

Kinga Kruppa

Special curves in the Minkowski space such as Minkowski Pythagorean hodographs play an important role in Computer Aided Geometric Design, and their usages have been thoroughly studied in the recent years. Also, several papers have been published which describe methods for interpolating Hermite data in R2,1 by MPH curves. Bizzarri et al.introduced the class o

Kuang Xu

We study the query complexity of Bayesian Private Learning: a learner wishes to locate a random target within an interval by submitting queries, in the presence of an adversary who observes all of her queries but not the responses. How many queries are necessary and sufficient in order for the learner to accurately estimate the target, while simultaneously c

Martin Sundermann

Strongly correlated materials are characterized by the presence of electron-electron interactions in their electronic structure. They often have remarkable properties and transitions between competing phases of very different electronic and magnetic order. This thesis focuses on strongly correlated $f$-electron compounds containing Ce, Sm, and U. These mater

Dafang Zhao, Tianqing An, Guoju Ye, Delfim F. M. Torres

We introduce and investigate the concept of harmonical $h$-convexity for interval-valued functions. Under this new concept, we prove some new Hermite-Hadamard type inequalities for the interval Riemann integral.

Sahin Buyukdagli

The electrostatic Schwinger-Dyson equations are derived and solved for an electrolyte mixture composed of mono- and multivalent ions confined to a negatively charged nanoslit. The closure of these equations is based on an asymmetric treatment of the ionic species with respect to their electrostatic coupling strength; the weakly coupled monovalent ions are tr

Morteza Derakhti, James T. Kirby, Michael L. Banner, Stephan T. Grilli

We investigate the validity and robustness of the Barthelemy et al. (2018) breaking wave onset prediction framework for surface gravity water waves in arbitrary water depth, including shallow water breaking over varying bathymetry. We show that the Barthelemy et al. (2018) breaking onset criterion, which they validated for deep and intermediate water depths,

Andrei Graur, Tristan Pollner, Vidhya Ramaswamy, S. Matthew Weinberg

We consider submodular function minimization in the oracle model: given black-box access to a submodular set function $f:2^{[n]}\rightarrow \mathbb{R}$, find an element of $\arg\min_S \{f(S)\}$ using as few queries to $f(\cdot)$ as possible. State-of-the-art algorithms succeed with $\tilde{O}(n^2)$ queries [LeeSW15], yet the best-known lower bound has never

M. V. Gavich, V. T. Gavich

This article assesses the use of a new type of electron accelerator, the Multirhodotron, for four new purposes that cannot be implemented using Rhodotrons and linacs. This study awards some arguments about possible replacement of nuclear reactors by electron accelerators in process of producing of medical isotopes on a global scale, about new possible electr

Ji Li, Yue Liu, Qiliang Wu

The Degasperis-Procesi equation is an approximating model of shallow-water wave propagating mainly in one direction to the Euler equations. Such a model equation is analogous to the Camassa-Holm approximation of the two-dimensional incompressible and irrotational Euler equations with the same asymptotic accuracy, and is integrable with the bi-Hamiltonian str

George Leckie, Lucy Prior, Harvey Goldstein

In England, Progress 8 is the Conservative government's headline secondary school performance and accountability measure. Progress 8 attempts to measure the average academic progress pupils make in each school between their KS2 tests and their GCSE Attainment 8 examinations. The Labour opposition recently announced they would scrap the KS2 tests were the

Jihn E. Kim

In this historic Lomonosov conference on the occasion of 150 year anniversary of the Mendeleev's periodic table, I present the history of neutrino magnetic moment. It was first thought by Wolfgang Pauli and its magnitude was calculated during the gauge theory era.

Yanlin Zhou, Fan Lu, George Pu, Xiyao Ma

We propose a deep reinforcement learning (DRL) methodology for the tracking, obstacle avoidance, and formation control of nonholonomic robots. By separating vision-based control into a perception module and a controller module, we can train a DRL agent without sophisticated physics or 3D modeling. In addition, the modular framework averts daunting retrains o

P. Frick, D. Sokoloff, R. Stepanov, V. Pipin

Numerous analyses suggest the existence of various quasi-periodicities in solar activity. The power spectrum of solar activity recorded in sunspot data is dominated by the $\sim$11-year quasi-periodicity, known as the Schwabe cycle. In the mid-term range (1 month -- 11 years) a pronounced variability known as a quasi-biennial oscillation (QBO) is widely disc

Zhenyi He, Karl Rosenberg, Ken Perlin

Virtual Reality (VR) enables users to collaborate while exploring scenarios not realizable in the physical world. We propose CollabVR, a distributed multi-user collaboration environment, to explore how digital content improves expression and understanding of ideas among groups. To achieve this, we designed and examined three possible configurations for parti

Lawrence Phillips, Garrett Goh, Nathan Hodas

Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been trained for its specific purpose. In this work, we develop a method to produce explanation masks for pre-trained networks. The mask localizes the most important aspects of each in

Arthur Ishteev, Ross Haroldson, Dmitry Gets, Alexey Tsapenko

Perovskite light-emitting diodes (PeLEDs) have recently attracted great research luminescence at room temperature in interest for their narrow emissions and solution processability. Remarkable progress has been achieved PeLEDs in recent years. Here we present the new configuration of ambipolar transparent perovskite light emitting device. The combination of

Chiara Lastoria

The Deep Underground Neutrino Experiment (DUNE) Far Detector (FD) will be formed by four 10-kton Liquid Argon (LAr) Time Projection Chambers (TPC) using both single and dual-phase technology. The dual-phase technology foreseen the charge amplification in the gas phase before the signal collection and is following a staged approach to demonstrate its feasibil

E. Martynov, G. Tersimonov

The ratios $ρ^{pp}_{\bar pp}(s)$ of the real to the imaginary part of forward elastic $pp$ and $\bar pp$ scattering amplitudes at very high energies are considered in the models with rising total cross-sections and its difference. It is shown from the dispersion relations for $pp$ and $\bar pp$ scattering amplitudes that in the Froissaron and Maximal Odderon

Boris Tsirelson

If the hazard rate $ \frac{ F'(x) }{ 1-F(x) } $ is increasing (in $x$), then $ \mathbb E\, ( X_{n:n} - X_{n-1:n} ) $ is decreasing (in $n$), and moreover, completely monotone.

Haodi Liang, Cecilia Cotton

Propensity score methods are increasingly being used to reduce estimation bias of treatment effects for observational studies. Previous research has shown that propensity score methods consistently estimate the marginal hazard ratio for time to event data. However, recurrent data frequently arise in the biomedical literature and there is a paucity of researc

Jevgenijs Ivanovs

We consider two bivariate models with two-way interactions in context of risk and queueing theory. The two entities interact with each other by providing assistance but otherwise evolve independently. We focus on certain random quantities underlying the joint survival probability and the joint stationary workload, and show that these admit stochastic decompo

Lijun Zhang, Srinath Nizampatnam, Ahana Gangopadhyay, Marcos V. Conde

Temporal localization remains an important challenge in video understanding. In this work, we present our solution to the 3rd YouTube-8M Video Understanding Challenge organized by Google Research. Participants were required to build a segment-level classifier using a large-scale training data set with noisy video-level labels and a relatively small-scale val

Felix J. Lockman, Enrico M. Di Teodoro, N. M. McClure-Griffiths

The ~200 HI clouds observed to be entrained in the Fermi Bubble wind show a trend of increasing maximum |VLSR| with Galactic latitude. We analyze previous observations and present new data from the Green Bank Telescope that rule out systematic effects as the source of this phenomenon. Instead, it is likely evidence for acceleration of the clouds. The data su

Cristina Flaut, Diana Savin, Gianina Zaharia

In this paper, we provide new applications of Fibonacci and Lucas numbers. In some circumstances, we find algebraic structures on some sets defined with these numbers, we generalize Fibonacci and Lucas numbers by using an arbitrary binary relation over the real fields instead of addition of the real numbers and we give properties of the new obtained sequence

Alexander Panchenko, Dmitry Babaev, Sergei Obiedkov

A profile matching algorithm takes as input a user profile of one social network and returns, if existing, the profile of the same person in another social network. Such methods have immediate applications in Internet marketing, search, security, and a number of other domains, which is why this topic saw a recent surge in popularity. In this paper, we presen

M. Riener, J. Kainulainen, H. Beuther, J. D. Henshaw

The analysis of large molecular line surveys of the Galactic plane is essential for our understanding of the gas kinematics on Galactic scales, in particular its link with the formation and evolution of dense structures in the interstellar medium. An approximation of the emission peaks with Gaussian functions allows for an efficient and straightforward extra

Bongjoon Hyun, Youngeun Kwon, Yujeong Choi, John Kim

To satisfy the compute and memory demands of deep neural networks, neural processing units (NPUs) are widely being utilized for accelerating deep learning algorithms. Similar to how GPUs have evolved from a slave device into a mainstream processor architecture, it is likely that NPUs will become first class citizens in this fast-evolving heterogeneous archit

Soheil Rostami, Walid Saad, Choong Seon Hong

Orbital angular momentum (OAM)-encoding has recently emerged as an effective approach for increasing the channel capacity of free-space optical communications. In this paper, OAM-based decoding is formulated as a supervised classification problem. To maintain lower error rate in presence of severe atmospheric turbulence, a new approach that combines effectiv

Samuele Centorrino, Aman Ullah, Jing Xue

We study a linear random coefficient model where slope parameters may be correlated with some continuous covariates. Such a model specification may occur in empirical research, for instance, when quantifying the effect of a continuous treatment observed at two time periods. We show one can carry identification and estimation without instruments. We propose a

Sugata Gangopadhyay, Vishvendra Singh Poonia, Daattavya Aggarwal, Rhea Parekh

We explicitly derive a connection between quantum circuits utilising IBM's quantum gate set and multivariate quadratic polynomials over integers modulo 8. We demonstrate that the action of a quantum circuit over input qubits can be written as generalized Walsh-Hadamard transform. Here, we derive the polynomials corresponding to implementations of the Swa

Simone Di Marino, Augusto Gerolin

This paper exploit the equivalence between the Schrödinger Bridge problem and the entropy penalized optimal transport in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a priori estimates which are consistent in the limit when the regularization parameter goes to zero. In particular, we find a n

Han-Chin Shing, Guoli Wang, Philip Resnik

The vast majority of research in computer assisted medical coding focuses on coding at the document level, but a substantial proportion of medical coding in the real world involves coding at the level of clinical encounters, each of which is typically represented by a potentially large set of documents. We introduce encounter-level document attention network

Benoit Van Troeye, Aurélien Lherbier, Simon M. -M. Dubois, Jean-Christophe Charlier

The emergence of superconductivity in slightly-misaligned graphene bilayer [1] and moiré excitons in MoSe$_2$-WSe$_2$ van der Waals (vdW) heterostructures [2] is intimately related to the formation of a 2D superlattice in those systems. At variance, perfect primitive lattice matching of the constituent layers has also been reported in some vdW-heterostructur

Eyob Gebretinsae Beyene

Researches have been done on Ethiopic scripts. However studies excluded the Geez numbers from the studies because of different reasons. This paper presents offline handwritten and machine printed Geez number recognition using feed forward back propagation artificial neural network. On this study, different Geez image characters were collected from google ima

Antonio Dobado, Domènec Espriu

This article presents a number of technical tools and results that may be instrumental to discern the nature of the Higgs particle. In scenarios where an additional strongly interacting sector is present in the electroweak theory resulting in a composite Higgs and longitudinal components of the massive gauge bosons, unitarity, analyticity and related techniq

P. Moskal, D. Kisielewska, Z. Bura, C. Chhokar

In living organisms the positron-electron annihilation (occurring during the PET imaging) proceeds in about 30% via creation of a metastable ortho-positronium atom. In the tissue, due to the pick-off and conversion processes, over 98% of ortho-positronia annihilate into two 511~keV photons. In this article we assess the feasibility for reconstruction of the

Andrew N. Jordan, Cyril Elouard, Alexia Auffèves

This article presents recent progress in the theory of quantum measurement engines and discusses the implications of them for quantum interpretations and philosophical implications of the theory. Several new measurement engine designs are introduced and analyzed: We discuss a feedback based atom-and-piston engine that sharply associates all work with success

Joshua Williams, J. Zico Kolter

Recent studies on fairness in automated decision making systems have both investigated the potential future impact of these decisions on the population at large, and emphasized that imposing ''typical'' fairness constraints such as demographic parity or equality of opportunity does not guarantee a benefit to disadvantaged groups. However, the

Mathieu Laurière, Ludovic Tangpi

This paper develops a theory of propagation of chaos for a system of weakly interacting particles whose terminal configuration is fixed as opposed to the initial configuration as customary. Such systems are modeled by backward stochastic differential equations. Under standard assumptions on the coefficients of the equations, we prove propagation of chaos res

Kevin Sebastian Luck, Mel Vecerik, Simon Stepputtis, Heni Ben Amor

Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of deterministic nature. This work evaluates the use of model-based trajectory optimization methods used for exploration in Deep Deterministic Policy Gradient when trained on a latent image

Kevin Sebastian Luck, Heni Ben Amor, Roberto Calandra

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturi

Sergio Giardino

After a review on recent results on quaternic quantum mechanics ($\mathbb{H}$QM), we present further consistency tests that reinforce its compatibility with the usual complex quantum mechanics ($\mathbb{C}$QM). The novel results comprises the Virial theorem, the quantum quaternic Lorentz force, the existence of a quaternic magnetic monopole and the redefinit

Sydney Sherman, Shardha Jogee, Jonathan Florez, Matthew L. Stevans

We present the high-mass end of the galaxy stellar mass function using the largest sample to date (5,352) of star-forming galaxies with $M_{\star} > 10^{11} M_{\odot}$ at cosmic noon, $1.5 < z < 3.5$. This sample is uniformly selected across 17.2 deg$^2$ ($\sim$0.44 Gpc$^3$ comoving volume from $1.5 < z < 3.5$), mitigating the effects of cosmic variance and

Almog Yalinewich, Andrey Remorov

We present a mathematical model for the propagation of the shock waves that occur during planetary collisions. Such collisions are thought to occur during the formation of terrestrial planets, and they have the potential to erode the planet&#39;s atmosphere. We show that under certain assumptions, this evolution of the shock wave can be determined using the

Itamar Reis, Michael Rotman, Dovi Poznanski, J. Xavier Prochaska

In recent years many works have shown that unsupervised Machine Learning (ML) can help detect unusual objects and uncover trends in large astronomical datasets, but a few challenges remain. We show here, for example, that different methods, or even small variations of the same method, can produce significantly different outcomes. While intuitively somewhat s

Joachim Brod, Martin Gorbahn, Emmanuel Stamou

The parameter $ε_K$ describes CP violation in the neutral kaon system and is one of the most sensitive probes of new physics. The large uncertainties related to the charm-quark contribution to $ε_K$ have so far prevented a reliable standard-model prediction. We show that CKM unitarity enforces a unique form of the $|ΔS = 2|$ weak effective Lagrangian in whic

Tomáš Husek

We briefly summarize current experimental and theoretical results on the $π^0$ Dalitz decay, including the new value for the ratio $R={Γ(π^0\to e^+e^-γ(γ))}/{Γ(π^0\toγγ)}=11.978(6)\times10^{-3}$, which is by two orders of magnitude more precise than the current PDG average. Furthermore, we discuss radiative corrections for the Dalitz decays $η^{(\prime)}\to\

Zahra Riahi Samani, Jacob Antony Alappatt, Drew Parker, Abdol Aziz Ould Ismail

Quality assessment of diffusion MRI (dMRI) data is essential prior to any analysis, so that appropriate pre-processing can be used to improve data quality and ensure that the presence of MRI artifacts do not affect the results of subsequent image analysis. Manual quality assessment of the data is subjective, possibly error-prone, and infeasible, especially c

Seunghak Yu, Giovanni Da San Martino, Preslav Nakov

Many recent political events, like the 2016 US Presidential elections or the 2018 Brazilian elections have raised the attention of institutions and of the general public on the role of Internet and social media in influencing the outcome of these events. We argue that a safe democracy is one in which citizens have tools to make them aware of propaganda campa

Noga Agmon

The Internet of things (IoT) has become an integral part of our life at both work and home. However, these IoT devices are prone to vulnerability exploits due to their low cost, low resources, the diversity of vendors, and proprietary firmware. Moreover, short range communication protocols (e.g., Bluetooth or ZigBee) open additional opportunities for the lat

Domenico Di Sante, Johanna Erdmenger, Martin Greiter, Ioannis Matthaiakakis

A current challenge in condensed matter physics is the realization of strongly correlated, viscous electron fluids. These fluids are not amenable to the perturbative methods of Fermi liquid theory, but can be described by holography, that is, by mapping them onto a weakly curved gravitational theory via gauge/gravity duality. The canonical system considered

Xiao Zhang, Michael D. Graham

This work investigates the orbital dynamics of a fluid-filled deformable prolate capsule in unbounded shear flow. The motion of the capsule is simulated using a model that incorporates shear elasticity, area dilatation, and bending resistance. Here the deformability of the capsule is characterized by capillary number Ca, which represents the ratio of viscous

Jeroen van Gorsel

We introduce continuous rank functions for field theories with linear quivers, and demonstrate they describe infinitely long quivers. In the context of AdS/CFT, these &#39;continuous quivers&#39; have well-defined supergravity dual descriptions with an infinite number of smeared NS5 and D-branes. These continuous rank functions generalise the supergravity so

Hubert L. Bray, Daniel L. Stern

For a homotopically energy-minimizing map $u: N^3\to S^1$ on a compact, oriented $3$-manifold $N$ with boundary, we establish an identity relating the average Euler characteristic of the level sets $u^{-1}\{θ\}$ to the scalar curvature of $N$ and the mean curvature of the boundary $\partial N$. As an application, we obtain some natural geometric estimates fo

M. Magri, G. Lemoine, L. Adam, J. Segurado

A continuum theory based on thermodynamics has been developed for modeling diffusional creep of polycrystalline solids. It consists of a coupled problem of vacancy diffusion and mechanics where the vacancy generation/absorption at grain boundaries is driven by grain boundary dislocations climb. The model is stated in terms of general balance laws and complet

Levent Kargın, Mümün Can

In this paper, we take advantage of the Mellin type derivative to produce some new families of polynomials whose coefficients involve r-Lah numbers. One of these polynomials leads to rediscover many of the identities of r-Lah numbers. We show that some of these polynomials and hyperharmonic numbers are closely related. Taking into account of these connection

Jacques P Vallee

The density wave theory predicted some physical offsets among different tracers of star formation. To test this prediction, here we compiled data on 40 galaxies searched observationally for a physical offset between spiral arm tracers, and found that 24 of them have a positive offset. In a spiral arm, an arm tracer in a region with a given temperature may be

Antti Vepsäläinen, Sergey Danilin, Gheorghe Sorin Paraoanu

Adiabatic manipulation of the quantum state is an essential tool in modern quantum information processing. Here we demonstrate the speed-up of the adiabatic population transfer in a three-level superconducting transmon circuit by suppressing the spurious non-adiabatic excitations with an additional two-photon microwave pulse. We apply this superadiabatic met

Claire Stines-Chaumeil, Francois Mavré, Brice Kauffmann, Nicolas Mano

The ability to switch on the activity of an enzyme through its spontaneous reconstitution has proven to be a valuable tool in fundamental studies of enzyme structure/reactivity relationships or in the design of artificial signal transduction systems in bioelectronics, synthetic biology, or bioanalytical applications. In particular, those based on the spontan

Viktoriia Kornich, Maxim G. Vavilov, Mark Friesen, M. A. Eriksson

We study how the shape of a periodic magnetic field affects the presence of Majorana bound states (MBS) in a nanowire-superconductor system. Motivated by the field configurations that can be produced by an array of nanomagnets, we consider spiral fields with an elliptic cross-section and fields with two sinusoidal components. We show that MBS are robust to i

Mohammad Hassan Ameri, Jeremiah Blocki, Samson Zhou

Memory hard functions (MHFs) are an important cryptographic primitive that are used to design egalitarian proofs of work and in the construction of moderately expensive key-derivation functions resistant to brute-force attacks. Broadly speaking, MHFs can be divided into two categories: data-dependent memory hard functions (dMHFs) and data-independent memory

Xuefeng Jiang, Lan Yang

Optical whispering-gallery-mode microresonators with ultrahigh quality factors and small mode volumes have played an important role in modern physics. They have been demonstrated as a diverse platform for a wide range of photonics applications, such as nonlinear optics, optomechanics, quantum optics, and information processing. Thermal behaviors induced by p

Jamie Webster, Martyn Amos

The realism and believability of crowd simulations underpins computational studies of human collective behaviour, with implications for urban design, policing, security and many other areas. Realism concerns the closeness of the fit between a simulation and observed data, and believability concerns the human perception of plausibility. In this paper, we ask

T. J. Mertzimekis, A. Khaliel, D. Papaioannou, G. Zagoraios

Mid-heavy nuclei offer unique opportunities to study the collective and single-particle aspects of nuclear structure. This mass regime is a dynamic area where protons and neutrons generally occupy different orbitals, giving rise to complex structures with a wide variety of shapes, shape evolution and shape coexistence. To that end, measurements of nuclear li

Galin Valchev, Peter Djondjorov, Vassil Vassilev, Daniel Dantchev

We study the behaviour of the non-retarded van der Waals force between a planar substrate and a single-walled carbon nanotube, assuming that the system is immersed in a liquid medium which exerts hydrostatic pressure on the tube&#39;s surface, thereby altering its cross-section profile. The shape of the latter is described as a continual structure characteri

A. Logachev, A. Mogulskii, A. Yambartsev

Here we obtain the exact asymptotics for large and moderate deviations, strong law of large numbers and central limit theorem for chains with unbounded variable length memory.

Ali Jahanshahi

In recent years, Convolutional Neural Network (CNN) based methods have achieved great success in a large number of applications and have been among the most powerful and widely used techniques in computer vision. However, CNN-based methods are computational-intensive and resource-consuming, and thus are hard to be integrated into embedded systems such as sma

Rich Pang

We present a novel way to encode compositional information in high-dimensional (HD) vectors. Inspired by chromosomal crossover, random HD vectors are recursively interwoven, with a fraction of one vector&#39;s components masked out and replaced by those from another using a context-dependent mask. Unlike many HD computing schemes, &#34;crossover&#34; codes h

O. S. Latcham, Y. I. Gusieva, A. V. Shytov, O. Y. Gorobets

We propose a class of metamaterials in which propagation of acoustic waves is controlled magnetically through magnetoelastic coupling. The metamaterials are formed by a periodic array of thin magnetic layers (&#39;resonators&#39;) embedded in a non-magnetic matrix. Acoustic waves carrying energy through the structure hybridize with the magnetic modes of the

C. E. Starrett, R. Perriot, N. R. Shaffer, T. Nelson

A new Sesame-type table for the electrical conductivity of aluminum is described. The table is based on density functional theory calculations and ranges from 0.001 to 1 times solid density (2.7 g/cm^3 ), and from 0.01 to 1000 eV in temperature. The table is compared to other simulations and to experiments and is generally in good agreement. The high tempera

Konrad Banaszek, Wojciech Zwoliński, Ludwig Kunz, Marcin Jarzyna

We identify theoretical limits on the photon information efficiency (PIE) of a deep-space optical communication link constrained by the average signal power and operated in the presence of background noise. The ability to implement a scalable modulation format, Geiger-type direct photon counting detection, and complete decoding of detection events are assume

Michael G. Raymer, Ian A. Walmsley

We review the concepts of temporal modes (TMs) in quantum optics, highlighting Roy Glauber&#39;s crucial and historic contributions to their development, and their growing importance in quantum information science. TMs are orthogonal sets of wave packets that can be used to represent a multimode light field. They are temporal counterparts to transverse spati

A. Logachov, O. Logachova, A. Yambartsev

The large deviation principle on phase space is proved for a class of Markov processes known as random population dynamics with catastrophes. In the paper we study the process which corresponds to the random population dynamics with linear growth and uniform catastrophes, where an eliminating portion of the population is chosen uniformly. The large deviation

Y. Saito, R. Rösslhuber, A. Löhle, M. Sanz Alonso

The electronic properties of molecular conductors can be readily varied via physical or chemical pressure as it increases the bandwidth W; this enables crossing the Mott insulator-to-metal phase transition by reducing electronic correlations U/W. Here we introduce an alternative path by increasing the molecular orbitals when partially replacing sulfur by sel

Rangeet Mitra, Paschalis. C. Sofotasios, Vimal Bhatia, Sami Muhaidat

The ever-increasing demand for high data-rate applications and the proliferation of connected devices pose several theoretical and technological challenges for the fifth generation (5G) networks and beyond. Among others, this includes the spectrum scarcity and massive connectivity of devices, particularly in the context of the Internet of Things (IoT) ecosys

Balbeer Singh, Hiranmaya Mishra

We study the effect of shear and bulk viscosities on the heavy quark transport coefficient within the matrix model of semi QGP. Dissipative effects are incorporated through the first-order viscous correction in the quark/antiquark and gluon distribution function. It is observed that while the shear viscosity effects reduces the drag of heavy quark the bulk v

Rene Bellwied, Szabolcs Borsanyi, Zoltan Fodor, Jana N. Guenther

We present cross-correlators of QCD conserved charges at $μ_B=0$ from lattice simulations and perform a Hadron Resonance Gas (HRG) model analysis to break down the hadronic contributions to these correlators. We construct a suitable hadronic proxy for the ratio $-χ_{11}^{BS}/χ_2^S$ and discuss the dependence on the chemical potential and experimental cuts. W

L. A. Yung, K. S. Denisov, I. V. Rozhansky, N. S. Averkiev

The theoretical study considers chiral spin texture induced in a 2D electron gas (2DEG) by magnetic skyrmions. We calculate the electron gas spin density as a linear response to the exchange interaction between the 2DEG and the magnetization field of a magnetic skyrmion. Two physically distinct regimes occur. When the size of the skyrmion is larger than the