June 2019 arXiv papers — page 4

Dimitrios Rafailidis, Gerhard Weiss

Social-based recommendation systems exploit the selections of friends to combat the data sparsity on user preferences, and improve the recommendation accuracy of the collaborative filtering strategy. The main challenge is to capture and weigh friends' preferences, as in practice they do necessarily match. In this paper, we propose a Neural Attention mechanis

Antonio De Rosa, Luca Lussardi

We extend to the anisotropic setting the existence of solutions for the Kirchhoff-Plateau problem and its dimensional reduction.

Christopher Lynch, Andrew M. Marshall, Catherine Meadows, Paliath Narendran

Asymmetric unification, or unification with irreducibility constraints, is a newly developed paradigm that arose out of the automated analysis of cryptographic protocols. However, there are still relatively few asymmetric unification algorithms. In this paper we address this lack by exploring the application of automata-based unification methods. We examine

V. E. Minakova, A. M. Nikitina, S. V. Zaitsev-Zotov

Diminishing in the concentration of quenching defects during thermocycling of orthorhombic TaS$_3$ samples in the temperature range below the Peierls transition temperature $T <T_P$ is observed. It makes it possible to study the character of pinning of the charge density wave (CDW) by these defects. A number of fundamental differences from pinning by ordinar

Jesse Bluem, Philip Kaaret, Andrea Prestwich, Matthew Brorby

X-ray binaries may have helped reionize the early Universe by enabling Lyman continuum escape. We analyzed a set of 8 local galaxies that are potential Lyman leaking galaxies, identified by a blue color and weak emission lines, using Chandra X-ray observations. Five of the galaxies feature X-ray sources, while three galaxies are not significantly detected in

Guanxiong Chen, Ryan Freeman, Andrei Zholud, Sergei Urazhdin

Sufficiently large electric current applied to metallic nanostructures can bring them far out-of-equilibrium, resulting in non-Ohmic behaviors characterized by current-dependent resistance. We experimentally demonstrate a linear dependence of resistance on current in microscopic thin-film metallic wires at cryogenic temperatures, and show that our results ar

Igor Omelyan

The superior Fisher-Kopeliovich closure is applied to the hierarchy of master equations for spatial moments of population dynamics for the first time. As a consequence, the population density, pair and triplet distribution functions are calculated within this closure for a birth-death model with nonlocal dispersal and competition in continuous space. The new

Nicolas Apfel

Many economic studies use shift-share instruments to estimate causal effects. Often, all shares need to fulfil an exclusion restriction, making the identifying assumption strict. This paper proposes to use methods that relax the exclusion restriction by selecting invalid shares. I apply the methods in two empirical examples: the effect of immigration on wage

Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser

Classical causal and statistical inference methods typically assume the observed data consists of independent realizations. However, in many applications this assumption is inappropriate due to a network of dependences between units in the data. Methods for estimating causal effects have been developed in the setting where the structure of dependence between

Qingkai Yang, Hao Fang, Jie Chen, Zhong-Ping Jiang

This published paper investigates the distributed tracking control problem for a class of Euler-Lagrange multi-agent systems when the agents can only measure the positions. In this case, the lack of the separation principle and the strong nonlinearity in unmeasurable states pose severe technical challenges to global output-feedback control design. To overcom

Michael A. Kouritzin, Anne MacKay

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and volatility, especially for purposes of path-dependent option pricing. The resulting simulation algorithm is an analog to

Liwen Zhang, Kewei Tu, Yue Zhang

Neural models have been investigated for sentiment classification over constituent trees. They learn phrase composition automatically by encoding tree structures but do not explicitly model sentiment composition, which requires to encode sentiment class labels. To this end, we investigate two formalisms with deep sentiment representations that capture sentim

U. Messer, S. Fausser

Warmth and competence represent the fundamental traits in social judgment that determine emotional reactions and behavioral intentions towards social targets. This research investigates whether an algorithm can learn visual representations of social categorization and accurately predict human perceivers' impressions of warmth and competence in face images. I

Na Lei, Xiaopeng Zheng, Zhongxuan Luo, Feng Luo

This work discovers the equivalence relation between quadrilateral meshes and meromorphic quartic. Each quad-mesh induces a conformal structure of the surface, and a meromorphic differential, where the configuration of singular vertices correspond to the configurations the poles and zeros (divisor) of the meroromorphic differential. Due to Riemann surface th

Xiaoyu Chen, Qixin Wang, Jinzhou Ge, Yi Zhang

At present, supervised stereo methods based on deep neural network have achieved impressive results. However, in some scenarios, accurate three-dimensional labels are inaccessible for supervised training. In this paper, a self-supervised network is proposed for binocular disparity matching (SDMNet), which computes dense disparity maps from stereo image pairs

Mobarakol Islam, Yueyuan Li, Hongliang Ren

Directing of the task-specific attention while tracking instrument in surgery holds great potential in robot-assisted intervention. For this purpose, we propose an end-to-end trainable multitask learning (MTL) model for real-time surgical instrument segmentation and attention prediction. Our model is designed with a weight-shared encoder and two task-oriente

A. A. Chrimes, A. J. Levan, E. R. Stanway, E. Berger

The number of long gamma-ray bursts (GRBs) known to have occurred in the distant Universe (z greater than 5) is small (approx 15), however these events provide a powerful way of probing star formation at the onset of galaxy evolution. In this paper, we present the case for GRB100205A being a largely overlooked high-redshift event. While initially noted as a

Fernando F. Ferreira, A. Christian Silva, Ju-Yi Yen

We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our study reports short, medium and long term effects by looking at the Sharpe ratio (SR). We calculate the Sharpe ratio of o

Veronika Dubinkina, Yulia Fridman, Parth Pratim Pandey, Sergei Maslov

Microbial communities routinely have several possible species compositions or community states observed for the same environmental parameters. Changes in these parameters can trigger abrupt and persistent transitions (regime shifts) between such community states. Yet little is known about the main determinants and mechanisms of multistability in microbial co

Feiping Nie, Hua Wang, Zheng Wang, Heng Huang

As one of the most popular linear subspace learning methods, the Linear Discriminant Analysis (LDA) method has been widely studied in machine learning community and applied to many scientific applications. Traditional LDA minimizes the ratio of squared L2-norms, which is sensitive to outliers. In recent research, many L1-norm based robust Principle Component

A. Nicholas Day, Victor Falgas-Ravry

Let $\Lambda$ be an infinite connected graph, and let $v_0$ be a vertex of $\Lambda$. We consider the following positional game. Two players, Maker and Breaker, play in alternating turns. Initially all edges of $\Lambda$ are marked as unsafe. On each of her turns, Maker marks $p$ unsafe edges as safe, while on each of his turns Breaker takes $q$ unsafe edges

XiaoYu Chen, Xu Wang, Lianfa Bai, Jing Han

In this paper, we present a convolution neural network based method to recover the light intensity distribution from the overlapped dispersive spectra instead of adding an extra light path to capture it directly for the first time. Then, we construct a single-path sub-Hadamard snapshot spectrometer based on our previous dual-path snapshot spectrometer. In th

Liu Ziyin, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov

We deal with the \textit{selective classification} problem (supervised-learning problem with a rejection option), where we want to achieve the best performance at a certain level of coverage of the data. We transform the original $m$-class classification problem to $(m+1)$-class where the $(m+1)$-th class represents the model abstaining from making a predict

Jiaxin Wang, Tess R. Jaffe, Torsten A. Enßlin, Piero Ullio

We present version X of the hammurabi package, the HEALPix-based numeric simulator for Galactic polarized emission. Improving on its earlier design, we have fully renewed the framework with modern C++ standards and features. Multi-threading support has been built in to meet the growing computational workload in future research. For the first time, we present

Bruno G. da Costa, Ignacio S. Gomez

In this work we calculate the Cram\'{e}r-Rao, the Fisher-Shannon and the L\'{o}pez-Ruiz-Mancini-Calbert (LMC) complexity measures for eigenstates of a deformed Schr\"{o}dinger equation, being this intrinsically linked with position-dependent mass (PDM) systems. The formalism presented is illustrated with a particle confined in an infinite potential well. Abr

Gal Raayoni, Shahar Gottlieb, George Pisha, Yoav Harris

Fundamental mathematical constants like $e$ and $\pi$ are ubiquitous in diverse fields of science, from abstract mathematics to physics, biology and chemistry. For centuries, new formulas relating fundamental constants have been scarce and usually discovered sporadically. Here we propose a novel and systematic approach that leverages algorithms for deriving

Johan Andersson, Linnea Rousu

We generalize a version of Lavrent\'ev's theorem which says that a function that is continuous on a compact set K with connected complement and without interior points can be uniformly approximated as closely as desired by a polynomial without zeros on the set K, so that the polynomial can avoid values from any given countable set. We also prove a correspond

David B. Blumenthal, Johann Gamper, Sébastien Bougleux, Luc Brun

The graph edit distance (GED) is a flexible distance measure which is widely used for inexact graph matching. Since its exact computation is NP-hard, heuristics are used in practice. A popular approach is to obtain upper bounds for GED via transformations to the linear sum assignment problem with error-correction (LSAPE). Typically, local structures and dist

Rob Egrot

We define a fragment of monadic infinitary second-order logic corresponding to an abstract separation property. We use this to define the concept of a separation subclass. We use model theoretic techniques and games to show that separation subclasses whose axiomatisations are recursively enumerable in our second-order fragment can also be recursively axiomat

C. Pinçon

Analytical resonance conditions for oscillation modes in stars are very helpful both to predict and to examine their frequency spectra, as well as to make the link with their internal properties. In this short paper, we introduce a general quantization expression for oscillation modes accounting for the possible existence of a local sharp variation in the eq

Samy Mailoud, Fausto Borgonovi, Felix Izrailev

As recently manifested , the quench dynamics of isolated quantum systems consisting of a finite number of particles, is characterized by an exponential spreading of wave packets in the many-body Hilbert space. This happens when the inter-particle interaction is strong enough, thus resulting in a chaotic structure of the many-body eigenstates considered in an

Fabio Botelho, Alexandre Molter

In this article we develop a duality principle and concerning computational method for a structural optimization problem in elasticity. We consider the problem of finding the optimal topology for an elastic solid which minimizes its structural inner energy resulting from the action of external loads to be specified. The main results are obtained through stan

Faeq Alrimawi, Liliana Pasquale, Deepak Mehta, Nobukazu Yoshioka

Cyber-physical systems (CPSs) are part of most critical infrastructures such as industrial automation and transportation systems. Thus, security incidents targeting CPSs can have disruptive consequences to assets and people. As prior incidents tend to re-occur, sharing knowledge about these incidents can help organizations be more prepared to prevent, mitiga

Bjørn-Olav H. Eriksen, Glenn Bitar, Morten Breivik, Anastasios M. Lekkas

This paper presents a three-layered hybrid collision avoidance (COLAV) system for autonomous surface vehicles, compliant with rules 8 and 13-17 of the International Regulations for Preventing Collisions at Sea (COLREGs). The COLAV system consists of a high-level planner producing an energy-optimized trajectory, a model predictive control based mid-level COLA

Julian Braun, Bernd Schmidt

We derive von-K\'arm\'an plate theory from three dimensional, purely atomistic models with classical particle interaction. This derivation is established as a $\Gamma$-limit when considering the limit where the interatomic distance $\varepsilon$ as well as the thickness of the plate $h$ tend to zero. In particular, our analysis includes the ultrathin case wh

Alexander Bulinski, Denis Dimitrov

Wide conditions are provided to guarantee asymptotic unbiasedness and L^2-consistency of the introduced estimates of the Kullback-Leibler divergence for probability measures in R^d having densities w.r.t. the Lebesgue measure. These estimates are constructed by means of two independent collections of i.i.d. observations and involve the specified k-nearest ne

Saikat Roy, Arun S. Moharir

This work is aimed at understanding the basic principles of adsorption process in great details as adsorptive separation process has broad applications in the industry. To this end, a simple mathematical model has been used to describe transient fixed bed physical adsorption process. Governing equations are solved numerically to obtain breakthrough curves fo

Adam Lev-Libfeld, Alex Margolin, Amnon Barak

Recent increased interest in Cloud computing emphasizes the need to find an adequate solution to the load-balancing problem in parallel computing -- efficiently running several jobs concurrently on a cluster of shared computers (nodes). One approach to solve this problem is by preemptive process migration -- the transfer of running processes between nodes. A

Debin Meng, Xiaojiang Peng, Kai Wang, Yu Qiao

The video-based facial expression recognition aims to classify a given video into several basic emotions. How to integrate facial features of individual frames is crucial for this task. In this paper, we propose the Frame Attention Networks (FAN), to automatically highlight some discriminative frames in an end-to-end framework. The network takes a video with

Émilie Charlier, Svetlana Puzynina, Élise Vandomme

In this paper we introduce and study new notions of uniform recurrence in multidimensional words. A $d$-dimensional word is called \emph{uniformly recurrent} if for all $(s_1,\ldots,s_d)\in\mathbb{N}^d$ there exists $n\in\mathbb{N}$ such that each block of size $(n,\ldots,n)$ contains the prefix of size $(s_1,\ldots,s_d)$. We are interested in a modification

Giuseppe Belgioioso, Angelia Nedić, Sergio Grammatico

We design the first fully-distributed algorithm for generalized Nash equilibrium seeking in aggregative games on a time-varying communication network, under partial-decision information, i.e., the agents have no direct access to the aggregate decision. The algorithm is derived by integrating dynamic tracking into a projected pseudo-gradient algorithm. The co

Chenxi Xiu, Xihua Chu

The purpose of this study is to propose a modified micromorphic continuum model for granular materials based on a micromechanics approach. In this model, Cauchy stress and the couple stress are symmetric conjugated with the symmetric strain and the symmetric curvature respectively, and the relative stress measures are asymmetric conjugated with the asymmetri

Xingkang He, Karl Henrik Johansson, Haitao Fang

We study distributed filtering for a class of uncertain systems over corrupted communication channels. We propose a distributed robust Kalman filter with stochastic gains, through which upper bounds of the conditional mean square estimation errors are calculated online. We present a robust collective observability condition, under which the mean square error

Ryo Tazaki, Hidekazu Tanaka, Akimasa Kataoka, Satoshi Okuzumi

Dust coagulation in a protoplanetary disk is the first step of planetesimal formation. However, a pathway from dust aggregates to planetesimals remains unclear. Both numerical simulations and laboratory experiments have suggested the importance of dust structure in planetesimal formation, but it is not well constrained by observations. We study how dust stru

Valery Gritsenko, Nils-Peter Skoruppa, Don Zagier

We define theta blocks as products of Jacobi theta functions divided by powers of the Dedekind eta-function and show that they give a powerful new method to construct Jacobi forms and Siegel modular forms, with applications also in lattice theory and algebraic geometry. One of the central questions is when a theta block defines a Jacobi form. It turns out th

Babak Vosoughi Lahijani, Nicolas Descharmes, Raphael Barbey, Gael D. Osowiecki

Guiding and confining light at interfaces is crucial for applications involving light-matter interactions such as surface spectroscopy, nonlinear optics, and quantum information technology. While dielectric surface waves offer promising perspectives for strong light confinement at non-absorbing interfaces, their capacity has not yet been widely explored. Her

Mousomi Bhakta, Anup Biswas, Debdip Ganguly, Luigi Montoro

Our main aim is to study Green function for the fractional Hardy operator $P:=(-\Delta)^s -\frac{\theta}{|x|^{2s}}$ in $\mathbb{R}^N$, where $0<\theta<\Lambda_{N,s}$ and $\Lambda_{N,s}$ is the best constant in the fractional Hardy inequality. Using Green function, we also show that the integral representation of the weak solution holds.

Jérôme Adda, Christian Decker, Marco Ottaviani

Clinical research should conform to high standards of ethical and scientific integrity, given that human lives are at stake. However, economic incentives can generate conflicts of interest for investigators, who may be inclined to withhold unfavorable results or even tamper with data in order to achieve desired outcomes. To shed light on the integrity of cli

Marcely Zanon Boito, Aline Villavicencio, Laurent Besacier

Since Bahdanau et al. [1] first introduced attention for neural machine translation, most sequence-to-sequence models made use of attention mechanisms [2, 3, 4]. While they produce soft-alignment matrices that could be interpreted as alignment between target and source languages, we lack metrics to quantify their quality, being unclear which approach produce

Shunsuke A. Sato, Angel Rubio

Aiming to combine density functional theory (DFT) and wavefunction theory, we study a mapping from the many-body interacting system to an effectively-interacting Kohn-Sham system instead of a non-interacting Kohn-Sham system. Because a ground state of effectively-interacting systems requires having a solution for the correlated many-body wavefunctions, this

Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni

Continual learning (CL) is a particular machine learning paradigm where the data distribution and learning objective changes through time, or where all the training data and objective criteria are never available at once. The evolution of the learning process is modeled by a sequence of learning experiences where the goal is to be able to learn new skills al

Anders Edelbo Lillie, Emil Refsgaard Middelboe

This paper surveys and presents recent academic work carried out within the field of stance classification and fake news detection. Echo chambers and the model organism problem are examples that pose challenges to acquire data with high quality, due to opinions being polarised in microblogs. Nevertheless it is shown that several machine learning approaches a

Bing Liu, Rui-zhi Yang, Xiao-na Sun, Felix Aharonian

We present a detailed study of the gamma-ray emission from the direction of the star-forming region W30 based on a decade of the Fermi Large Area Telescope data in the 0.3-300 GeV photon energy range. The morphological and spectral analyses allow us to resolve the gamma-ray emission into two extended structures from different origins. One of them mostly over

Jing-Fei Zhang, Bo Wang, Xin Zhang

We investigate what role the SKA neutral hydrogen (HI) intensity mapping (IM) sky survey observation will play in weighing neutrinos in cosmology. We use the simulated data of the baryon acoustic oscillation (BAO) measurements from the HI IM survey based on SKA1 and SKA2 to do the analysis. For the current observations, we use the Planck 2015 cosmic microwav

Alexander Lerch, Claire Arthur, Ashis Pati, Siddharth Gururani

Music Information Retrieval (MIR) tends to focus on the analysis of audio signals. Often, a single music recording is used as representative of a "song" even though different performances of the same song may reveal different properties. A performance is distinct in many ways from a (arguably more abstract) representation of a "song," "piece," or musical sco

Finn M. Stokes, Waseem Kamleh, Derek B. Leinweber

First principles calculations of the form factors of baryon excitations are now becoming accessible through advances in Lattice QCD techniques. In this paper, we explore the utility of the parity-expanded variational analysis (PEVA) technique in calculating the Sachs electromagnetic form factors for excitations of the proton and neutron. We study the two low

Olga I. Piskounova, Konstantine A. Kotelnikov

The event of astroparticle collision at high energy was detected in 1975 during the balloon flight in the stratosphere. The data of hundred particle tracks in x-ray films have been re-analyzed in the style of LHC experiments: rapidity distributions of charged particles and transverse mass spectra of multi-particle production have been built. The comparison o

Manfried Faber

We investigate a classical statistical model and show that Mermin's version of a Bell inequality is violated. We get this violation, if the measurement modifies the ensemble, a feature, which is also characteristic for measurement processes for quantum systems.

Alejandro Aguado, Victor Lopez, Diego Lopez, Momtchil Peev

Quantum computers will change the cryptographic panorama. A technology once believed to lay far away into the future is increasingly closer to real world applications. Quantum computers will break the algorithms used in our public key infrastructure and in our key exchange protocols, forcing a complete retooling of the cryptography as we know it. Quantum Key

Yu Liu, Jiahui Li, Xiujun Zhang, Shidong Zhou

The sparsity and the severe attenuation of millimeter-wave (mmWave) channel imply that highly directional communication is needed. The narrow beam produced by large array requires accurate alignment, which is difficult to achieve when serving fast-moving users. In this paper, we focus on accurate two-dimensional (2D) beam and channel tracking problem aiming

John Lång, I. S. W. B. Prasetya

This paper presents a case study on applying two model checkers, SPIN and DIVINE, to verify key properties of a C++ software framework, known as ADAPRO, originally developed at CERN. SPIN was used for verifying properties on the design level. DIVINE was used for verifying simple test applications that interacted with the implementation. Both model checkers w

Xi Geng, Cheng Ouyang, Samy Tindel

This article is concerned with stochastic differential equations driven by a $d$ dimensional fractional Brownian motion with Hurst parameter $H>1/4$, understood in the rough paths sense. Whenever the coefficients of the equation satisfy a uniform hypoellipticity condition, we establish a sharp local estimate on the associated control distance function and a

W. Moon, N. J. Balmforth, J. S. Wettlaufer

We analyze the fluctuation-driven escape of particles from a metastable state under the influence of a weak periodic force. We develop an asymptotic method to solve the appropriate Fokker-Planck equation with mixed natural and absorbing boundary conditions. The approach uses two boundary layers flanking an interior region; most of the probability is concentr

Adam R. Patel, Yunping Zhang, Alexey Shashurin

This paper presents a novel micropropulsion system for nanosatellite applications - a liquid fed pulsed-plasma thruster (LF-PPT) comprised of a Lorentz-force pulsed plasma accelerator (PPA) and a low-energy surface flashover (LESF) igniter. A 3 {\mu}F / 2 kV capacitor bank, offering shot energies of < 6 J, supported PPA current pulsed durations of ~ 16 {\mu}

Felix Stahlberg, Bill Byrne

We describe two entries from the Cambridge University Engineering Department to the BEA 2019 Shared Task on grammatical error correction. Our submission to the low-resource track is based on prior work on using finite state transducers together with strong neural language models. Our system for the restricted track is a purely neural system consisting of neu

Chaolong Jiang, Yuezheng Gong, Wenjun Cai, Yushun Wang

In this paper, we present a linearly implicit energy-preserving scheme for the Camassa-Holm equation by using the multiple scalar auxiliary variables approach, which is first developed to construct efficient and robust energy stable schemes for gradient systems. The Camassa-Holm equation is first reformulated into an equivalent system by utilizing the multip

Dionisis Stefanatos, Emmanuel Paspalakis

In this article we propose a novel method to accelerate adiabatic passage in a two-level system with only longitudinal field (detuning) control, while the transverse field is kept constant. The suggested method is a modification of the Roland-Cerf protocol, during which the parameter quantifying local adiabaticity is held constant. Here, we show that with a

Jyrki Kauppinen, Pekka Malmi

In this paper we will prove that GCM-models used in IPCC report AR5 fail to calculate the influences of the low cloud cover changes on the global temperature. That is why those models give a very small natural temperature change leaving a very large change for the contribution of the green house gases in the observed temperature. This is the reason why IPCC

Reza Shokri, Martin Strobel, Yair Zick

Privacy and transparency are two key foundations of trustworthy machine learning. Model explanations offer insights into a model's decisions on input data, whereas privacy is primarily concerned with protecting information about the training data. We analyze connections between model explanations and the leakage of sensitive information about the model's tra

Dmytro Dubyna, Watson Kuo

A design of LEGO-like construction set that allows assembling of different linear arrays of three-dimensional (3D) cavities and qubits for circuit quantum electrodynamics (cQED) experiments has been developed. A study of electromagnetic properties of qubit-3D cavity arrays has been done by using high frequency structure simulator (HFSS). A technique for esti

B. Quinn

The status of Lorentz- and CPT-violation searches using measurements of the anomalous magnetic moment of the muon is reviewed. Results from muon g-2 experiments have set the majority of the most stringent limits on Standard- Model Extension Lorentz and CPT violation in the muon sector. These limits are consistent with calculations of the level of Standard-Mo

Prateek Anand, Samriddhi Sankar Ray, Ganesh Subramanian

We examine the dynamics of small anisotropic particles (spheroids) sedimenting through homogeneous isotropic turbulence using direct numerical simulations and theory. The gravity-induced inertial torque acting on sub-Kolmogorov spheroids leads to pronouncedly non-Gaussian orientation distributions localized about the broadside-on(to gravity) orientation. Ori

Akash Choudhary, Di Li, T. Renganathan, Xiangchun Xuan

Advancements in understanding the lateral migration of particles have helped in enhanced separation in microfluidic devices. In this work, we investigate the effects of electrokinetics on the particle migration in a viscoelastic flow, where the electric field is applied parallel to the flow. Through experiments and theoretical analysis, we show that the inte

Kristian Brock

This manuscript introduces an \proglang{R} package called \pkg{trialr} that implements a collection of clinical trial methods in \proglang{Stan} and \proglang{R}. In this article, we explore three methods in detail. The first is the continual reassessment method for conducting phase I dose-finding trials that seek a maximum tolerable dose. The second is EffT

Ranbir Dhounchak, Veeraruna Kavitha

The decomposable branching processes are relatively less studied objects, particularly in the continuous time framework. In this paper, we consider various variants of decomposable continuous time branching processes. As usual practice in the theory of decomposable branching processes, we group various types into irreducible classes. These irreducible classe

Mohan. R, B. N. Suhas

The purpose of this paper is to provide a common framework for studying various generalizations of Leavitt algebras and Leavitt path algebras. This paper consists of two parts. In part I we define Cohn-Leavitt path algebras of a new class of graphs with an additional structure called bi-separated graphs, which generalize the constructions of Leavitt path alg

Masahide Sato

We report on self-assemblies formed from spherical patchy particles interacting by a long-range attraction through a patch region in a two-dimensional system. We performed Monte Carlo simulations to find stable structures in a system with constant number of particles under constant temperature and constant pressure (NPT system), in which particles interact v

Sandeep Singh Adhikari, Sukhneer Singh, Anoop Rajagopal, Aruna Rajan

Extracting fashion attributes from images of people wearing clothing/fashion accessories is a very hard multi-class classification problem. Most often, even catalogues of fashion do not have all the fine-grained attributes tagged due to prohibitive cost of annotation. Using images of fashion articles, running multi-class attribute extraction with a single mo

Jorrit H. J. Hagen, Amina Helmi, Maarten A. Breddels

We test the ability of Schwarzschild's orbit superposition method in measuring the mass content, scale radius and shape of a flattened dwarf spheroidal galaxy. Until now, most dynamical model efforts have assumed that dwarf spheroidal galaxies and their host halos are spherical. We use an Evans model (1993) to construct an isothermal mock galaxy whose proper

Roberto Zucchini

The geometry of the total space of a principal bundle with regard to the action of the bundle's structure group is elegantly described by the bundle's operation, a collection of derivations consisting of the de Rham differential and the contraction and Lie derivatives of all vertical vector fields and satisfying the six Cartan relations. Connections and gaug

Jan Govaerts

There exist instances of dynamical systems possessing symmetry transformations of which the conserved Noether charges generating these symmetries feature an explicit time dependence in their functional representation over phase space. The generators of such symmetries certainly do not commute with the Hamiltonian, and yet these charges are conserved observab

Wadut Shaikh

In order to disentangle CNM effects from the ``hot'' QGP effects, quarkonium production is studied in p--Pb collisions in which QGP formation is not expected. ALICE has measured the $\Upsilon$ production in p--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV at backward ($-$4.46 $<y_{\rm cms}<$ $-$2.96) and forward (2.03 $< y_{\rm cms}<$ 3.53) rapidity down t

Ninh Van Thu, Nguyen Quang Dieu

The purpose of this article is twofold. The first aim is to characterize $h$-extendibility of smoothly bounded pseudoconvex domains in $\mathbb C^{n+1}$ by their noncompact automorphism groups. Our second goal is to show that if the squeezing function tends to $1$ at an $h$-extendible boundary point of a smooth pseudoconvex domain in $\mathbb C^{n+1}$, then

Yi Liao, Yasheng Wang, Qun Liu, Xin Jiang

We present a simple yet effective method for generating high quality classical Chinese poetry with Generative Pre-trained Language Model (GPT). The method adopts a simple GPT model, without using any human crafted rules or features, or designing any additional neural components. While the proposed model learns to generate various forms of classical Chinese p

Erika Zetterlund, Jason Glenn, Erik Rosolowsky

We investigate how the properties of Galactic giant molecular clouds (GMCs) and their denser substructures (clumps) correlate with the local star formation rate. We trace clouds using the $^{12}$CO(3-2) transition, as observed by the CO High Resolution Survey (COHRS). We identify their constituent clumps using thermal dust emission, as observed by the Hersch

Hasan Fallahgoul, Kihun Nam

Carr and Wu (2004), henceforth CW, developed a framework that encompasses almost all of the continuous-time models proposed in the option pricing literature. Their framework hinges on the stopping time property of the time changes. By analyzing the measurability of the time changes with respect to the underlying filtration, we show that all models CW propose

Matthias Huss, Simon Förster

The Little Ice Age in Europe (between about 1350 and 1850) marked the largest glacier extent over the entire Holocene period. Although several authors have investigated the causes of the substantial glacier advances in the mid-19th century and the rapid retreat following this phase, a conclusive insight linking all relevant components is still lacking. The s

Amir Bar, Michal Mauda, Yoni Turner, Michal Safadi

Head CT is one of the most commonly performed imaging studied in the Emergency Department setting and Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present BloodNet, a deep learning architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisiti

S. Posen, A. Romanenko, A. Grassellino, O. S. Melnychuk

We report on an effort to improve the performance of superconducting radiofrequency cavities by the use of heat treatment in a temperature range sufficient to dissociate the natural surface oxide. We find that the residual resistance is significantly decreased, and we find an unexpected reduction in the BCS resistance. Together these result in extremely high

Elena Montes, Monique Shotande, Daniel Helm, Christan Grant

Data scientists are constantly creating methods to efficiently and accurately populate big data sets for use in large-scale applications. Many recent efforts utilize crowd-sourcing and textual interfaces. In this paper, we propose a new method of curating data; namely, creating a multi-device Amazon Alexa Skill in the form of a research trivia game. Users ex

Tao Wang, Xianghu Wang, Zhilei Deng, Jiacheng Sun

Semiconductor lasers are notoriously sensitive to optical feedback, and their dynamics and coherence can be significantly modified through optical reinjection. We concentrate on the dynamical properties of a very small (i.e., microscale) Vertical Cavity Surface Emitting Laser (VCSEL) operated in the low coherence region between the emission of (partially) co

Qi Meng, Emiko Hiyama, Kadir Utku Can, Philipp Gubler

Several compact $sssc\bar c$ pentaquark resonances are predicted in a potential quark model. The Hamiltonian is the best available one, which reproduces the masses of the low-lying charmed and strange hadrons well. Full five-body calculations are carried out by the use of the Gaussian expansion method, and the relevant baryon-meson thresholds are taken into

Joenio Marques da Costa

This article presents a theoretical summary of the source code static analysis, its definition, uses and applications, how static analysis is performed, their intermediate representation formats, models and most common analysis techniques, ends up presenting a set of free and freely available downloadable static analysis tools, academic software tools develo

Qiang Jia

We study the low energy dynamics of a single Dp-brane carrying sufcient large number of D0-brane charges in type IIA theory. We assume the D-brane topology to be $R \times \mathcal{M}_{2n} $ , where $\mathcal{M}_{2n}$ is a closed manifold admitting a symplectic structure. We propose a new gauge fixing condition which eliminates the spatial gauge fluctuations

Alireza Heidari, Ihab F. Ilyas, Theodoros Rekatsinas

We study the problem of recovering the latent ground truth labeling of a structured instance with categorical random variables in the presence of noisy observations. We present a new approximate algorithm for graphs with categorical variables that achieves low Hamming error in the presence of noisy vertex and edge observations. Our main result shows a logari

Samuel Pinilla, Jorge Bacca, Cesar Vargas, Juan Carlos Poveda-Jaramillo

X-ray crystallography (XC) is an experimental technique used to determine three-dimensional crystalline structures. The acquired data in XC, called diffraction patterns, is the Fourier magnitudes of the unknown crystalline structure. To estimate the crystalline structure from its diffraction patterns, we propose to modify the traditional system by including

Kartik Lakhotia, Qing Dong, Rajgopal Kannan, Viktor Prasanna

Point-to-Point Shortest Distance (PPSD) query is a crucial primitive in graph database applications. Hub labeling algorithms compute a labeling that converts a PPSD query into a list intersection problem (over a pre-computed indexing) enabling swift query response. However, constructing hub labeling is computationally challenging. Even state-of-the-art paral

Anthony Degleris, Ben Antin, Surya Ganguli, Alex H Williams

Identifying recurring patterns in high-dimensional time series data is an important problem in many scientific domains. A popular model to achieve this is convolutive nonnegative matrix factorization (CNMF), which extends classic nonnegative matrix factorization (NMF) to extract short-lived temporal motifs from a long time series. Prior work has typically fi

Chihiro Noguchi, Yoshiyuki Kabashima

In order to solve large matrix completion problems with practical computational cost, an approximate approach based on matrix factorization has been widely used. Alternating least squares (ALS) and stochastic gradient descent (SGD) are two major algorithms to this end. In this study, we propose a new algorithm, namely cavity-based matrix factorization (CBMF)

Xinwei Li, Katsumasa Yoshioka, Ming Xie, G. Timothy Noe

We report results of terahertz Faraday and Kerr rotation spectroscopy measurements on thin films of $\text{Bi}_{1-x}\text{Sb}_{x}$, an alloy system that exhibits a semimetal-to-topological-insulator transition as the Sb composition $x$ increases. By using a single-shot time-domain terahertz spectroscopy setup combined with a table-top pulsed mini-coil magnet