arXiv papers from July 2021

Subhajit Paul, Suman Majumder, Subir K Das, Wolfhard Janke

Dynamics of various biological filaments can be understood within the framework of active polymer models. Here we consider a bead-spring model for a flexible polymer chain in which the active interaction among the beads is introduced via an alignment rule adapted from the Vicsek model. Following a quench from the high-temperature coil phase to a low-temperat

Alexandru Chirvasitu

The characteristic index of a locally compact connected group $G$ is the non-negative integer $d$ for which we have a homeomorphism $G\cong K\times \mathbb{R}^d$ with $K\le G$ maximal compact. We prove that the characteristic indices of closed connected subgroups are dominated by those of the ambient groups.

Sayak Nag, Dripta S. Raychaudhuri, Sujoy Paul, Amit K. Roy-Chowdhury

In many applications, we are constrained to learn classifiers from very limited data (few-shot classification). The task becomes even more challenging if it is also required to identify samples from unknown categories (open-set classification). Learning a good abstraction for a class with very few samples is extremely difficult, especially under open-set set

Sergey P. Suetin

Under the assumption of the existence of Stahl's $S$-compact set we give a short proof of the limit zeros distribution of Pad\'e polynomials and convergence in capacity of diagonal Pad\'e approximants for a generic class of algebraic functions. The proof is direct but not from the opposite as Stahl's original proof is. The generic class means in particular t

Nihal Ahmed, Ashfaq Ahmed, Sakan Binte Imran

Atherosclerosis is a state wherein plaque (fat, cholesterol, and different substances) develops inside the veins that in the end prompts carotid artery stenosis which is a phase of narrowing in the huge courses situated on either side of the neck that convey blood to the brain, face, and head. Carotid stenosis is regularly connected with perpetual injury of

Anastasiya Tanana

In this paper, we study expected utility maximization under ratchet and drawdown constraints on consumption in a general incomplete semimartingale market using duality methods. The optimization is considered with respect to two parameters: the initial wealth and the essential lower bound on consumption process. In order to state the problem and define the pr

Yue Zheng, Imtiar Niloy, Paolo Celli, Ian Tobasco

Mechanical metamaterials exhibit exotic properties at the system level, that emerge from the interactions of many nearly rigid building blocks. Determining these emergent properties theoretically has remained an open challenge outside of a few select examples. Here, for a large class of periodic and planar kirigami, we provide a coarse-graining rule linking

Kelvin Cheng, Christopher Healey, Tianfu Wu

Stereo matching has recently witnessed remarkable progress using Deep Neural Networks (DNNs). But, how robust are they? Although it has been well-known that DNNs often suffer from adversarial vulnerability with a catastrophic drop in performance, the situation is even worse in stereo matching. This paper first shows that a type of weak white-box attacks can

Olga Movilla Miangolarra, Amirhossein Taghvaei, Rui Fu, Yongxin Chen

We consider a rudimentary model for a heat engine, known as the Brownian gyrator, that consists of an overdamped system with two degrees of freedom in an anisotropic temperature field. Whereas the hallmark of the gyrator is a nonequilibrium steady-state curl-carrying probability current that can generate torque, we explore the coupling of this natural gyrati

V. A. Allakhverdyan, A. D. Avrorin, A. V. Avrorin, V. M. Aynutdinov

The Baikal-GVD is a neutrino telescope under construction in Lake Baikal. The main goal of the Baikal-GVD is to observe neutrinos via detecting the Cherenkov radiation of the secondary charged particles originating in the interactions of neutrinos. In 2021, the installation works concluded with 2304 optical modules installed in the lake resulting in effectiv

Shah Zeb, Muhammad Ahmad Rathore, Aamir Mahmood, Syed Ali Hassan

The 6G vision is envisaged to enable agile network expansion and rapid deployment of new on-demand microservices (e.g., visibility services for data traffic management, mobile edge computing services) closer to the network's edge IoT devices. However, providing one of the critical features of network visibility services, i.e., data flow prediction in the net

Jinyan Su, Lijie Hu, Di Wang

In this paper, we revisit the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) and provide excess population risks for some special classes of functions that are faster than the previous results of general convex and strongly convex functions. In the first part of the paper, we study the case where the population risk function satisf

Kaiyi Ji

Bilevel optimization has become a powerful framework in various machine learning applications including meta-learning, hyperparameter optimization, and network architecture search. There are generally two classes of bilevel optimization formulations for machine learning: 1) problem-based bilevel optimization, whose inner-level problem is formulated as findin

Wenda Zhou, Shirin Jalali, Arian Maleki

The problem of recovering a structured signal from its linear measurements in the presence of speckle noise is studied. This problem appears in many imaging systems such as synthetic aperture radar and optical coherence tomography. The current acquisition technology oversamples signals and converts the problem into a denoising problem with multiplicative noi

B. Dubetsky

A local positional system (LPS) is proposed, in which particles are launched at given velocities, and a sensor system measures the trajectory of particles in the platform frame. These measurements allow us to restore the position and orientation of the platform in the frame of the rotating Earth, without solving navigation equations. If there are also veloci

J. C. del Valle, Alexander V. Turbiner

For one-dimensional power-like potentials $|x|^m, m > 0$ the Bohr-Sommerfeld Energies (BSE) extracted explicitly from the Bohr-Sommerfeld quantization condition are compared with the exact energies. It is shown that for the ground state as well as for all positive parity states the BSE are always above the exact ones contrary to the negative parity states wh

Elliot Hong, Dan Ismailescu, Alex Kwak, Grace Yeeun Park

We prove that every unit area convex pentagon is contained in a convex quadrilateral of area no greater than $3/\sqrt{5}$, and that every unit area convex hexagon is contained in a convex pentagon of area no greater than $7/6$. Both results are tight as the case of the regular pentagon (hexagon) shows. We conjecture that for every $n\ge 6$, every unit area c

Arunima Bhattacharya, Jingyi Chen, Micah Warren

In this paper, we prove that any $C^{1}$-regular Hamiltonian stationary Lagrangian submanifold in a symplectic manifold is smooth. More broadly, we develop a regularity theory for a class of fourth order nonlinear elliptic equations with two distributional derivatives. Our fourth order regularity theory originates in the geometrically motivated variational p

Jennifer Roloff, Viviana Cavaliere, Marc-André Pleier, Lailin Xu

Longitudinal vector boson scattering provides an important probe of electroweak symmetry breaking, bringing sensitivity to physics beyond the Standard Model as well as constraining properties of the Higgs boson. It is a difficult process to study due to the small production cross section and challenging separation of the different polarization states. We stu

Jiaxi Cheng, Zhenhao Cen, Siliu Xu

Plasmon-induced transparency (PIT) displays complex nonlinear dynamics that find critical phenomena in areas such as nonlinear waves. However, such a nonlinear solution depends sensitively on the selection of parameters and different potentials in the Schr\"odinger equation. Despite this complexity, the machine learning community has developed remarkable eff

Eva Lope-Oter, Felipe J. Llanes-Estrada

Neutron stars and their mergers provide the highest-density regime in which Einstein's equations in full (with a matter source) can be tested against modified theories of gravity. But doing so requires a priori knowledge of the Equation of State from nuclear and hadron physics, where no contamination from computations of astrophysics observables within Gener

Arunkumar C. S

We initiate a study of non-commutative Choquet boundary for spaces of unbounded operators. We define the notion of local boundary representations for local operator systems in locally C$^*$-algebras and prove that local boundary representations provide an intrinsic invariant for a particular class of local operator systems. An appropriate analog of purity of

L. A. Sromovsky, K. H. Baines, P. M. Fry

Cassini/ISS imagery and Cassini/VIMS spectral imaging observations from 0.35 to 5.12 microns show that between 2012 and 2017 the region poleward of the Saturn's northern hexagon changed from dark blue/green to a moderately brighter gold color, except for the inner eye region (88.2 deg - 90 deg N), which remained relatively unchanged. These and even more dram

Yann Damour, Mickaël Véril, Fábris Kossoski, Michel Caffarel

Following our recent work on the benzene molecule [\href{https://doi.org/10.1063/5.0027617}{J.~Chem.~Phys.~\textbf{153}, 176101 (2020)}], itself motivated by the blind challenge of Eriksen \textit{et al.} [\href{https://doi.org/10.1021/acs.jpclett.0c02621}{J.~Phys.~Chem.~Lett.~\textbf{11}, 8922 (2020)}] on the same system, we report accurate full configurati

Alexander M. Zenner, Erwin Böttinger, Stefan Konigorski

N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, none support non-experts in conducting their own user-centric trials. In this study we present StudyMe, an open-source mobile application that is freel

Damon Pham, Daniel McDonald, Lei Ding, Mary Beth Nebel

Artifacts in functional MRI (fMRI) data cause deviations from common distributional assumptions, introduce spatial and temporal outliers, and reduce the signal-to-noise ratio of the data -- all of which can have negative consequences for downstream statistical analysis. Scrubbing is a technique for excluding fMRI volumes thought to be contaminated by artifac

Prachi Gupta, Harish S. Bhat, Karnamohit Ranka, Christine M. Isborn

We develop a statistical method to learn a molecular Hamiltonian matrix from a time-series of electron density matrices. We extend our previous method to larger molecular systems by incorporating physical properties to reduce dimensionality, while also exploiting regularization techniques like ridge regression for addressing multicollinearity. With the learn

J. D. García-Aguilar, Juan Carlos Gómez-Izquierdo

The lepton sector is studied within a flavored non-renormalizable model where the $\mathbf{S}_{3}\otimes \mathbf{Z}_{2}$ flavor symmetry drives the Yukawa couplings. In this framework, the effective neutrino mass, that comes from the type II see-saw mechanism, as well as the charged lepton mass matrices are hierarchical and possessed (under a benchmark in th

Joy T. Wu, Nkechinyere N. Agu, Ismini Lourentzou, Arjun Sharma

Despite the progress in automatic detection of radiologic findings from chest X-ray (CXR) images in recent years, a quantitative evaluation of the explainability of these models is hampered by the lack of locally labeled datasets for different findings. With the exception of a few expert-labeled small-scale datasets for specific findings, such as pneumonia a

Edward Walton

We consider the exotic vortex equations on compact Riemann surfaces. These generalise the well-known Jackiw-Pi and Ambj{\o}rn-Olesen vortex equations and arise as equations for Bogomolny-Prasad-Sommerfield-like configurations in nonrelativistic Chern-Simons-matter theories. We show that (exotic) vortex solutions in $U(N)$ gauge theories with a single fundame

Gil Ben Zvi, Eyal Leizerovich, Nimrod Talmon

We investigate an iterative deliberation process for an agent community wishing to make a joint decision. We develop a general model consisting of a community of n agents, each with their initial ideal point in some metric space (X, d), such that in each iteration of the iterative deliberation process, all agents move slightly closer to the current winner, a

Kuntal Patel, Javed Shaikh, Absar Lakdawala, Atul Sharma

Adaptive interface-Mesh un-Refinement (AiMuR) based Sharp-Interface Level-Set-Method (SI-LSM) is proposed for both uniform and non-uniform Cartesian-Grid. The AiMuR involves interface location based dynamic un-refinement (with merging of the four control volumes) of the Cartesian grid away from the interface. The un-refinement is proposed for the interface s

Layton A. Hall, Ayman F. Abouraddy

It has long been thought that normal group-velocity dispersion (GVD) cannot be produced in free space via angular dispersion. Indeed, conventional diffractive or dispersive components such as gratings or prisms produce only anomalous GVD. We identify the conditions that must be fulfilled by the angular dispersion introduced into a plane-wave pulse to yield n

Stefano Di Sabatino, Pierre-François Loos, Pina Romaniello

Using the simple (symmetric) Hubbard dimer, we analyze some important features of the $GW$ approximation. We show that the problem of the existence of multiple quasiparticle solutions in the (perturbative) one-shot $GW$ method and its partially self-consistent version is solved by full self-consistency. We also analyze the neutral excitation spectrum using t

Jasleen Gund, R. K. Brojen Singh

Synaptic plasticity and neuron cross-talk are some of the important key mechanisms underlying formation of dynamic clusters of active neurons. The essence of this study is to model and decipher the mechanism of emergence of a task-specific functional connectivity among a population of neurons. We have used our proposed neuron activity pattern (NAP) model to

Chao Liu, Sencheng Yu, Mark Yim

Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by n

Mika Hämäläinen, Khalid Alnajjar

We survey human evaluation in papers presenting work on creative natural language generation that have been published in INLG 2020 and ICCC 2020. The most typical human evaluation method is a scaled survey, typically on a 5 point scale, while many other less common methods exist. The most commonly evaluated parameters are meaning, syntactic correctness, nove

Jonathan Jaquette

In this paper, we study the dynamics of a class of nonlinear Schr\"odinger equation $ i u_t = \triangle u + u^p $ for $ x \in \mathbb{T}^d$. We prove that the PDE is integrable on the space of non-negative Fourier coefficients, in particular that each Fourier coefficient of a solution can be explicitly solved by quadrature. Within this subspace we demonstrat

Yi Ji, Simon Mak, Derek Soeder, J-F Paquet

With advances in scientific computing and mathematical modeling, complex scientific phenomena such as galaxy formations and rocket propulsion can now be reliably simulated. Such simulations can however be very time-intensive, requiring millions of CPU hours to perform. One solution is multi-fidelity emulation, which uses data of different fidelities to train

Kyle Lee, Jian-Wei Qiu, George Sterman, Kazuhiro Watanabe

Heavy quarkonium production at high transverse momentum ($p_T$) in hadronic collisions is explored in the QCD factorization approach. We find that the leading power in the $1/p_T$ expansion is responsible for high $p_T$ regime, while the next-to-leading power contribution is necessary for the low $p_T$ region. We present the first numerical analysis of the s

Mason C. Marshall, Reza Ebadi, Connor Hart, Matthew J. Turner

Crystal strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, precision measurement and control of diamond crystal strain is a key challenge. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution,

Song Zhang, Amritanshu Pandey, Xiaochuan Luo, Maggy Powell

Motivated by The Federal Energy Regulatory Commission's (FERC) recent direction and ever-growing interest in cloud adoption by power utilities, a Task Force was established to assist power system practitioners with secure, reliable and cost-effective adoption of cloud technology to meet various business needs. This paper summarizes the business drivers, chal

You-Wei Luo, Chuan-Xian Ren

As a vital problem in classification-oriented transfer, unsupervised domain adaptation (UDA) has attracted widespread attention in recent years. Previous UDA methods assume the marginal distributions of different domains are shifted while ignoring the discriminant information in the label distributions. This leads to classification performance degeneration i

Raj Kolamuri, Zilin Si, Yufan Zhang, Arpit Agarwal

Rotational displacement about the grasping point is a common grasp failure when an object is grasped at a location away from its center of gravity. Tactile sensors with soft surfaces, such as GelSight sensors, can detect the rotation patterns on the contacting surfaces when the object rotates. In this work, we propose a model-based algorithm that detects tho

Mario Bravo, Thierry Champion, Roberto Cominetti

We present a self-contained analysis of a particular family of metrics over the set of non-negative integers. We show that these metrics, which are defined through a nested sequence of optimal transport problems, provide tight estimates for general Krasnosel'skii-Mann fixed point iterations for non-expansive maps. We also describe some of their very special

Mónica Clapp, Mayra Soares

We study the existence and asymptotic behavior of solutions having positive and sign-changing components to the singularly perturbed system of elliptic equations \begin{equation*} \begin{cases} -\varepsilon^2\Delta u_i+u_i=\mu_i|u_i|^{p-2}u_i + \sum\limits_{\substack{j=1 \\ j \not=i}}^\ell\lambda_{ij}\beta_{ij}|u_j|^{\alpha_{ij}}|u_i|^{\beta_{ij} -2}u_i,\\ u

Andrea Cini, Ivan Marisca, Cesare Alippi

Dealing with missing values and incomplete time series is a labor-intensive, tedious, inevitable task when handling data coming from real-world applications. Effective spatio-temporal representations would allow imputation methods to reconstruct missing temporal data by exploiting information coming from sensors at different locations. However, standard meth

Farshid Raissi, Mina Amirmazlaghani, Ali Rajabi

Nano-electronic integrated circuit technology is exclusively based on MOSFET transistor due to its scalability down to the nanometer range. On the other hand, Bipolar Junction Transistor (BJT), which provides unmatched analog characteristics and frequency response, cannot be scaled to nanometer regime without the loss of transistor action. Here a versatile n

Yiqun Diao, Oliver Zhao, Priya Kothapalli, Peter Monteleone

Carotid artery stenosis is the narrowing of carotid arteries, which supplies blood to the neck and head. In this work, we train a model to predict the severity of the stenosis blockage based on SRUC criteria variables and other patient information. We implement classic machine learning methods, decision trees and random forests, used in a previous experiment

Akshita Jha, Bhanukiran Vinzamuri, Chandan K. Reddy

With the growing interest in the machine learning community to solve real-world problems, it has become crucial to uncover the hidden reasoning behind their decisions by focusing on the fairness and auditing the predictions made by these black-box models. In this paper, we propose a novel method to address two key issues: (a) Can we simultaneously learn fair

Milton Arencibia, Paul A. Cassak, Michael A. Shay, Eric R. Priest

We develop a first-principles scaling theory of the spreading of three-dimensional (3D) magnetic reconnection of finite extent in the out of plane direction. This theory addresses systems with or without an out of plane (guide) magnetic field, and with or without Hall physics. The theory reproduces known spreading speeds and directions with and without guide

Mark Rucker, Stephen Adams, Roy Hayes, Peter A. Beling

In adversarial environments, one side could gain an advantage by identifying the opponent's strategy. For example, in combat games, if an opponents strategy is identified as overly aggressive, one could lay a trap that exploits the opponent's aggressive nature. However, an opponent's strategy is not always apparent and may need to be estimated from observati

Muddasir Naeem, Noor-ul-ain Fatima, Mukhtar Hussain, Tayyab Imran

We report the design simulation of the Raman spectrometer using optical system design software Zemax. The design is based on the Czerny-turner configuration which includes an optical system consisting of an entrance slit, two concave mirrors, reflecting type diffraction grating, and an image detector. The system's modelling approach is suggested by introduci

Hedieh Ajam, Marzieh Najafi, Vahid Jamali, Bernhard Schmauss

In this paper, we investigate the modeling and design of intelligent reflecting surface (IRS)-assisted optical communication systems which are deployed to relax the line-of-sight (LOS) requirement in multi-link free space optical (FSO) systems. The FSO laser beams incident on the optical IRSs have a Gaussian power intensity profile and a nonlinear phase prof

Felipe Colombelli, Thayne Woycinck Kowalski, Mariana Recamonde-Mendoza

The discovery of disease biomarkers from gene expression data has been greatly advanced by feature selection (FS) methods, especially using ensemble FS (EFS) strategies with perturbation at the data level (i.e., homogeneous, Hom-EFS) or method level (i.e., heterogeneous, Het-EFS). Here we proposed a Hybrid EFS (Hyb-EFS) design that explores both types of per

Carlos R. Handy, John Klauder

Normally, the half-harmonic oscillator is active when $x>0$ and absent when $x<0$. From a canonical quantization perspective, this leads to odd eigenfunctions being present while even eigenfunctions are absent. In that case, only the usual odd eigenfunctions will appear if the wall slides to negative infinity. However, if an affine quantization is used, slid

John K Sellers

We present a deterministic relationship between relative primes and twin primes in successively larger sequences of the natural numbers. This enables setting a finite lower limit on the occurrence of actual twin primes in an unbounded selection of domains.

Winston Heap, Anurag Sahay, Trevor D. Wooley

Suppose that $\theta$ is irrational. Then almost all elements $\nu\in {\mathbb Z}[\theta]$ that may be written as a $k$-fold product of the shifted integers $n+\theta$ $(n\in {\mathbb N})$ are thus represented essentially uniquely.

Shiqi Jia, Jie Peng, Yuqiong Cheng, Shubo Wang

The practical applications of chiral discrimination are usually limited by the weak chiral response of enantiomers and the high complexity of detection methods. Here, we propose to use the C lines (i.e., lines of polarization singularities) emerged in light scattering by a metal sphere to detect small chiral particles. Using full-wave numerical simulations a

Zherong Pan, Duo Zhang, Changhe Tu, Xifeng Gao

We propose an optimization-based approach to plan power grasps. Central to our method is a reformulation of grasp planning as an infinite program under complementary constraints (IPCC), which allows contacts to happen between arbitrary pairs of points on the object and the robot gripper. We show that IPCC can be reduced to a conventional finite-dimensional n

Paolo Soffitta, Luca Baldini, Ronaldo Bellazzini, Enrico Costa

While X-ray Spectroscopy, Timing and Imaging have improved verymuch since 1962, when the first astronomical non-solar source was discovered, especially with the launch of Newton/X-ray Multi-Mirror Mission, Rossi/X-ray Timing Explorer and Chandra/Advanced X-ray Astrophysics Facility, the progress of X-ray polarimetry has been meager. This is in part due to th

Abby Bishop, Lu Lu, Albrecht Karle, Ben Hokanson-Fasig

The IceCube Neutrino Observatory has discovered a diffuse astrophysical flux up to 10 PeV and is now planning a large extension with IceCube-Gen2, including an optical array and a large radio array at shallow depth [1]. Neutrino searches for energies >100 PeV are best done with such shallow radio detectors like the Askaryan Radio Array (ARA) or similar (buri

Santolo Leveque, John W. Pearson

We derive novel, fast, and parameter-robust preconditioned iterative methods for steady and time-dependent Navier--Stokes control problems. Our approach may be applied to time-dependent problems which are discretized using backward Euler or Crank--Nicolson, and is also a valuable candidate for Stokes control problems discretized using Crank--Nicolson. The ke

Davide Ancona, Pietro Barbieri, Elena Zucca

We propose a simple calculus for processing data streams (infinite flows of data series), represented by finite sets of equations built on stream operators. Furthermore, functions defining streams are regularly corecursive, that is, cyclic calls are detected, avoiding non-termination as happens with ordinary recursion in the call-by-value evaluation strategy

Larry Bates, Richard Cushman, Jędrzej Śniatycki

In this paper we study differential forms and vector fields on the orbit space of a proper action of a Lie group on a smooth manifold, defining them as multilinear maps on the generators of infinitesimal diffeomorphisms, respectively. This yields an intrinsic view of vector fields and differential forms on the orbit space.

Ana-Maria Bucur, Ioana R. Podină, Liviu P. Dinu

In this work, we provide an extensive part-of-speech analysis of the discourse of social media users with depression. Research in psychology revealed that depressed users tend to be self-focused, more preoccupied with themselves and ruminate more about their lives and emotions. Our work aims to make use of large-scale datasets and computational methods for a

Rong An, Xiang Jiang, Li-Gang Cao, Feng-Shou Zhang

A unified theoretical model reproducing charge radii of known atomic nuclei plays an essential role in making extrapolations for unknown nuclei. Recently developed new ansatz which phenomenologically takes into account the neutron-proton short-range correlations ($np$-SRCs) can describe the discontinuity properties and odd-even staggering (OES) effect of cha

Hare Krishna, D. Rodriguez-Gomez

We study 2-point correlation functions for scalar operators in position space through holography including bulk cubic couplings as well as higher curvature couplings to the square of the Weyl tensor. We focus on scalar operators with large conformal dimensions. This allows us to use the geodesic approximation for propagators. In addition to the leading order

Christian Ellis, Maggie Wigness, John G. Rogers, Craig Lennon

Traditional imitation learning provides a set of methods and algorithms to learn a reward function or policy from expert demonstrations. Learning from demonstration has been shown to be advantageous for navigation tasks as it allows for machine learning non-experts to quickly provide information needed to learn complex traversal behaviors. However, a minimal

Sam Dillavou, Menachem Stern, Andrea J. Liu, Douglas J. Durian

In typical artificial neural networks, neurons adjust according to global calculations of a central processor, but in the brain neurons and synapses self-adjust based on local information. Contrastive learning algorithms have recently been proposed to train physical systems, such as fluidic, mechanical, or electrical networks, to perform machine learning tas

Mingyuan Luo, Xin Yang, Xiaoqiong Huang, Yuhao Huang

3D ultrasound (US) is widely used for its rich diagnostic information. However, it is criticized for its limited field of view. 3D freehand US reconstruction is promising in addressing the problem by providing broad range and freeform scan. The existing deep learning based methods only focus on the basic cases of skill sequences, and the model relies on the

Muhammad Monjurul Karim, Yu Li, Ruwen Qin

Traffic accident anticipation is a vital function of Automated Driving Systems (ADSs) for providing a safety-guaranteed driving experience. An accident anticipation model aims to predict accidents promptly and accurately before they occur. Existing Artificial Intelligence (AI) models of accident anticipation lack a human-interpretable explanation of their de

Krzysztof Zajkowski

The Weibull distribution can be obtained using a power transformation from the standard exponential distribution. In this article, we will consider a symmetrized power transformation of a random variable with the standard normal distribution. We will call its distribution the $\alpha$-{\it normal (Gaussian) distribution}. We examine properties of this distri

Adam Fortais, Elsie Loukiantchenko, Kari Dalnoki-Veress

The buckling and twisting of slender, elastic fibers is a deep and well-studied field. A slender elastic rod that is twisted with respect to a fixed end will spontaneously form a loop, or hockle, to relieve the torsional stress that builds. Further twisting results in the formation of plectonemes -- a helical excursion in the fiber that extends with addition

Kishore Tumarada, Yifan Zhang, Fan Yang, Eduard Dragut

Opinion prediction is an emerging research area with diverse real-world applications, such as market research and situational awareness. We identify two lines of approaches to the problem of opinion prediction. One uses topic-based sentiment analysis with time-series modeling, while the other uses static embedding of text. The latter approaches seek user-spe

A. Silantyev

We construct Quantum Representation Theory which describes quantum analogue of representations in frame of "non-commutative linear geometry" developed by Manin. To do it we generalise the internal hom-functor to the case of adjunction with a parameter and construct a general approach to representations of a monoid in a symmetric monoidal category with a para

Yoshiki Kubotani, Yoshihiro Fukuhara, Shigeo Morishima

A major challenge in the field of education is providing review schedules that present learned items at appropriate intervals to each student so that memory is retained over time. In recent years, attempts have been made to formulate item reviews as sequential decision-making problems to realize adaptive instruction based on the knowledge state of students.

Zhen Pan, Huan Yang

Accretion disks of active galactic nuclei (AGN) have been proposed as promising sites for producing both (stellar-mass) compact object mergers and extreme mass ratio inspirals. Along with the disk-assisted migration/evolution process, ambient gas materials inevitably accrete onto the compact objects. The description of this process is subject to significant

Zahra Davari, Sohrab Rahvar

In this work, we investigate the MOdified Gravity (MOG) theory for dynamics of the universe and compare the results with the $\Lambda$CDM cosmology. We study the background cosmological properties of the MOG model and structure formation at the linear perturbation level. We compare the two models with the currently available cosmological data by using statis

H. T. Cui, M. Qin, L. Tang, H. Z. Shen

In this work, the exact dynamics of excitation in the generalized Aubry-Andr\'{e}-Harper model coupled with an Ohmic-type environment is discussed by evaluating the survival probability and inverse participation ratio of the state of system. In contrast to the common belief that localization will preserve the information of the initial state in the system ag

Logan Chariker, Joel Lebowitz

We investigate the macroscopic time evolution and stationary states of a mean field generalized contact process in $\mathbb{R}^d$. The model is described by a coupled set of nonlinear integral-differential equations. It was inspired by a model of neurons with discrete voltages evolving by a stochastic integrate and fire mechanism. We obtain a complete soluti

Vladimir Koltchinskii, Martin Wahl

Let $\{P_{\theta}:\theta \in {\mathbb R}^d\}$ be a log-concave location family with $P_{\theta}(dx)=e^{-V(x-\theta)}dx,$ where $V:{\mathbb R}^d\mapsto {\mathbb R}$ is a known convex function and let $X_1,\dots, X_n$ be i.i.d. r.v. sampled from distribution $P_{\theta}$ with an unknown location parameter $\theta.$ The goal is to estimate the value $f(\theta)$

Uttaran Bhattacharya, Elizabeth Childs, Nicholas Rewkowski, Dinesh Manocha

We present a generative adversarial network to synthesize 3D pose sequences of co-speech upper-body gestures with appropriate affective expressions. Our network consists of two components: a generator to synthesize gestures from a joint embedding space of features encoded from the input speech and the seed poses, and a discriminator to distinguish between th

Anshul Mittal, Noveen Sachdeva, Sheshansh Agrawal, Sumeet Agarwal

Deep extreme classification (XC) seeks to train deep architectures that can tag a data point with its most relevant subset of labels from an extremely large label set. The core utility of XC comes from predicting labels that are rarely seen during training. Such rare labels hold the key to personalized recommendations that can delight and surprise a user. Ho

Radhika P, Anu Mol Joy

Pipelines for water supply are susceptible to burst-leakage due to fluid pressures of various nature. High pressure heads resulting in circumferential and (or) axial stresses larger than the material yield stress could cause pipe failure. Of equal concern is the local boiling or cavitation effect in regions of fluid pressure dropping below its vapor pressure

Vidas Regelskis, Bart Vlaar

Lie algebra involutions and their fixed-point subalgebras give rise to symmetric spaces and real forms of complex Lie algebras, and are well-studied in the context of symmetrizable Kac-Moody algebras. In this paper we study a generalization. Namely, we introduce the concept of a pseudo-involution, an automorphism which is only required to act involutively on

Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim

Neural network pruning is useful for discovering efficient, high-performing subnetworks within pre-trained, dense network architectures. More often than not, it involves a three-step process -- pre-training, pruning, and re-training -- that is computationally expensive, as the dense model must be fully pre-trained. While previous work has revealed through ex

Ilmari Kangasniemi, Aleksis Koski, Jani Onninen

We study solutions of the inner-variational equation associated with the Dirichlet energy in the plane, given homeomorphic Sobolev boundary data. We prove that such a solution is monotone if and only if its Jacobian determinant does not change sign. These solutions, called monotone Hopf-harmonics, are a natural alternative to harmonic homeomorphisms. Examini

Wei W. Xing, Xiang Jin, Yi Liu, Dan Niu

One of the greatest challenges in IC design is the repeated executions of computationally expensive SPICE simulations, particularly when highly complex chip testing/verification is involved. Recently, pseudo transient analysis (PTA) has shown to be one of the most promising continuation SPICE solver. However, the PTA efficiency is highly influenced by the in

Peng Wu, Julius Partridge, Enrico Anderlini, Yuanchang Liu

Hybrid-electric propulsion systems powered by clean energy derived from renewable sources offer a promising approach to decarbonise the world's transportation systems. Effective energy management systems are critical for such systems to achieve optimised operational performance. However, developing an intelligent energy management system for applications suc

Hai-Xiao Wang, Yige Chen, Guang-Yu Guo, Hae-Young Kee

The simulation of fermionic relativistic physics, e.g., Dirac and Weyl physics, has led to the discovery of many unprecedented phenomena in photonics, of which the optical-frequency realization is, however, still challenging. Here, surprisingly, we discover that the woodpile photonic crystals commonly used for optical frequency applications host exotic fermi

Wen-Yuan Ai, Marco Drewes, Dražen Glavan, Jan Hajer

We study how oscillations of a scalar field condensate are damped due to dissipative effects in a thermal medium. Our starting point is a non-linear and non-local condensate equation of motion descending from a 2PI-resummed effective action derived in the Schwinger-Keldysh formalism appropriate for non-equilibrium quantum field theory. We solve this non-loca

Yuliia Boiarinova, Yakov Kalinovskiy, Dmitriy Lande

In recent years, the direction of the study of networks in which connections correspond to the mutual influences of nodes has been developed. Many works have been devoted to the study of such complex networks, but most often they relate to the spread of one type of activity (influence). In the process of development of the newest technologies various mathema

Ngo Phuc Duc Loc

In the first scenario, we revise the upper bound of the cutoff scale of the dimension-six potential Higgs operator required for a successful electroweak baryogenesis in the case of a modified expansion history caused by the existence of a non-interacting scalar field at the time phase transition happens. The upper bound 860 GeV of the cutoff scale in the con

Hans Nikolaus Beck, Nayel Fabian Salem, Veronica Haber, Matthias Rauschenbach

If we consider information as the basis of action, it may be of interest to examine the flow and acquisition of information between the actors in traffic. The central question is, which signals an automaton has to receive, decode or send in road traffic in order to act safely and in a conform manner to valid standards. The phenomenon-signal-model is a method

Hira Asif, Ramazan Sahin

Spatio-temporal control of ultrafast plasmon resonances has gained research interest in recent years because of their tremendous implications in nonlinear optics and ultrafast quantum technology. In particular, the lifetime of ultrashort plasmon oscillations has become a debatable subject in recent experimental and theoretical studies to fulfill the future c

Loic Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai

Datasets are rarely a realistic approximation of the target population. Say, prevalence is misrepresented, image quality is above clinical standards, etc. This mismatch is known as sampling bias. Sampling biases are a major hindrance for machine learning models. They cause significant gaps between model performance in the lab and in the real world. Our work

Moira Shooter, Charles Malleson, Adrian Hilton

Estimating the pose of animals can facilitate the understanding of animal motion which is fundamental in disciplines such as biomechanics, neuroscience, ethology, robotics and the entertainment industry. Human pose estimation models have achieved high performance due to the huge amount of training data available. Achieving the same results for animal pose es

Alex H. Ardila, Takahisa Inui

We establish the scattering of solutions to the focusing mass supercritical nonlinear Schr\"odinger equation with a repulsive Dirac delta potential \[ i\partial_{t}u+\partial^{2}_{x}u+\gamma\delta(x)u+|u|^{p-1}u=0, \quad (t,x)\in {\mathbb R}\times{\mathbb R}, \] at the mass-energy threshold, namely, when $E_{\gamma}(u_{0})[M(u_{0})]^{\sigma}=E_{0}(Q)[M(Q)]^{

Yuan Xu

We study orthogonal structures and Fourier orthogonal series on the surface of a paraboloid $\mathbb{V}_0^{d+1} = \{(x,t): \|x\| = \sqrt{t}, \, x \in \mathbb{R}^d, \, 0\le t<1\}$. The reproducing kernels of the orthogonal polynomials with respect to $t^\beta(1-t)^\gamma$ on $\mathbb{V}_0^{d+1}$ are related to the reproducing kernels of the Jacobi polynomials