October 2020 arXiv papers — page 16

Keen You, Dan Goldwasser

We examine a new commonsense reasoning task: given a narrative describing a social interaction that centers on two protagonists, systems make inferences about the underlying relationship trajectory. Specifically, we propose two evaluation tasks: Relationship Outlook Prediction MCQ and Resolution Prediction MCQ. In Relationship Outlook Prediction, a system ma

Loukas Grafakos, Danqing He, Petr Honzík, Bae Jun Park

The $L^p$ boundedness theory of convolution operators is \linebreak based on an initial $L^2\to L^2$ estimate derived from the Fourier transform. The corresponding theory of multilinear operators lacks such a simple initial estimate in view of the unavailability of Plancherel's identity in this setting, and up to now it has not been clear what a natural init

Zhiying Huang, Hao Li, Ming Lei

With the number of smart devices increasing, the demand for on-device text-to-speech (TTS) increases rapidly. In recent years, many prominent End-to-End TTS methods have been proposed, and have greatly improved the quality of synthesized speech. However, to ensure the qualified speech, most TTS systems depend on large and complex neural network models, and i

Himanshi Garg, Christophe Pinte, Valentin Christiaens, Daniel Price

We present ALMA observations of the $^{12}$CO, $^{13}$CO, C$^{18}$O J=2-1 transitions and the 1.3\,mm continuum emission for the circumbinary disc around HD 142527, at an angular resolution of $\approx$\,0\farcs3. We observe multiple spiral structures in intensity, velocity and velocity dispersion for the $^{12}$CO and $^{13}$CO gas tracers. A newly detected

Hongqin Liu

Since a transcendental equation is involved in vapor liquid equilibrium (VLE) calculations with a cubic equation of state (EoS), any exact solution has to be carried out numerically with an iterative approach [1,2]. This causes significant wastes of repetitive human efforts and computing resources. Based on a recent study [3] on the Maxwell construction [4]

Kohei Ichikawa, Kunihiko Kaneko

Despite the significance of short-term memory in cognitive function, the process of encoding and sustaining the input information in neural activity dynamics remains elusive. Herein, we unveiled the significance of transient neural dynamics to short-term memory. By training recurrent neural networks to short-term memory tasks and analyzing the dynamics, the

Xiang I. A. Yang, Kevin Patrick Griffin

We revisit the grid-point requirement estimates in Choi and Moin [Phys. Fluid, 24, 011702 (2012)] and establish more general grid-point requirements for direct numerical simulations (DNS) and large-eddy simulations (LES) of a spatially developing turbulent boundary layer. We show that, by allowing the local grid spacing to scale with the local Kolmogorov len

Kazuki Shimada, Yuichiro Koyama, Naoya Takahashi, Shusuke Takahashi

Neural-network (NN)-based methods show high performance in sound event localization and detection (SELD). Conventional NN-based methods use two branches for a sound event detection (SED) target and a direction-of-arrival (DOA) target. The two-branch representation with a single network has to decide how to balance the two objectives during optimization. Usin

Alex Friedlan, Marc M. Dignam

Achieving a population imbalance between the two inequivalent valleys is a critical first step for any valleytronic device. A valley-polarization can be induced in biased bilayer graphene using circularly polarized light. In this paper, we present a detailed theoretical study of valley-polarization in biased bilayer graphene. We show that a nearly perfect va

Dominic C. Rose, Katarzyna Macieszczak, Igor Lesanovsky, Juan P. Garrahan

We study in detail an open quantum generalisation of a classical kinetically constrained model -- the East model -- known to exhibit slow glassy dynamics stemming from a complex hierarchy of metastable states with distinct lifetimes. Using the recently introduced theory of classical metastability for open quantum systems, we show that the driven open quantum

Quang Tran, Jeffery R. Roesler

Joint raveled or spalled damage (henceforth called joint damage) can affect the safety and long-term performance of concrete pavements. It is important to assess and quantify the joint damage over time to assist in building action plans for maintenance, predicting maintenance costs, and maximize the concrete pavement service life. A framework for the accurat

Yueru Chen, Yiting Shao, Jing Wang, Ge Li

Inspired by the recently proposed successive subspace learning (SSL) principles, we develop a successive subspace graph transform (SSGT) to address point cloud attribute compression in this work. The octree geometry structure is utilized to partition the point cloud, where every node of the octree represents a point cloud subspace with a certain spatial size

A. Lazarian, Thiem Hoang

We reveal a deep connection between alignment of dust grains by RAdiative torques (RATs) and MEchanical Torques (METs) and rotational disruption of grains introduced by Hoang et al. (2019). The disruption of grains happens if they have attractor points corresponding to high angular momentum (high-J). We introduce {\it fast disruption} for grains that are dir

Emaad Manzoor, Nihar B. Shah

Quantifying systematic disparities in numerical quantities such as employment rates and wages between population subgroups provides compelling evidence for the existence of societal biases. However, biases in the text written for members of different subgroups (such as in recommendation letters for male and non-male candidates), though widely reported anecdo

Jonas F. G. Santos, C. H. S. Vieira

Quantum Gaussian channels play a key role in quantum information theory. In particular, the attenuation and amplification channels are useful to describe noise and decoherence effects on continuous variables systems. They are directly associated to the beam splitter and two-mode squeezing operations, which have operational relevance in quantum protocols with

Hong Liu, Allan H. MacDonald, Dmitry K. Efimkin

We explain the strong interlayer drag resistance observed at low temperatures in bilayer electron-hole systems in terms of an interplay between local electron-hole-pair condensation and disorder-induced carrier density variations. Smooth disorder drives the condensate into a granulated phase where interlayer coherence is formed only in well separated and dis

Xiaobing Feng, Liet Vo

This paper is concerned with numerical analysis of two fully discrete Chorin-type projection methods for the stochastic Stokes equations with general non-solenoidal multiplicative noise. The first scheme is the standard Chorin scheme and the second one is a modified Chorin scheme which is designed by employing the Helmholtz decomposition on the noise functio

Stefan Kennedy, Niall Walsh, Kirils Sloka, Jennifer Foster

In this paper we perform an analytic comparison of a number of techniques used to detect fake and deceptive online reviews. We apply a number machine learning approaches found to be effective, and introduce our own approach by fine-tuning state of the art contextualised embeddings. The results we obtain show the potential of contextualised embeddings for fak

Hua Zheng, Ilya O. Ryzhov, Wei Xie, Judy Zhong

Comorbid chronic conditions are common among people with type 2 diabetes. We developed an Artificial Intelligence algorithm, based on Reinforcement Learning (RL), for personalized diabetes and multi-morbidity management with strong potential to improve health outcomes relative to current clinical practice. In this paper, we modeled glycemia, blood pressure a

Jun Usami, Koki Tokeshi, Tomohiro Matsui, Hiroshi Fukuyama

We developed a calorimeter with a vacuum container made of superconducting niobium (Nb) to study monolayers of helium adsorbed on graphite which are prototypical two-dimensional quantum matters below 1 K. Nb was chosen because of its small specific heat in the superconducting state. It is crucially important to reduce the addendum heat capacity ($C_{\rm{ad}}

Qidong Fu, Peng Wang, Changming Huang, Yaroslav V. Kartashov

Exploration of the impact of synthetic material landscapes featuring tunable geometrical properties on physical processes is a research direction that is currently of great interest because of the outstanding phenomena that are continually being uncovered. Twistronics and the properties of wave excitations in moir\'e lattices are salient examples. Moir\'e pa

Nathan G. Caldeira, Eduardo Folco Capossoli, Carlos A. D. Zarro, Henrique Boschi-Filho

In this work we study the fluctuation and dissipation of a string attached to a brane in a deformed and backreated AdS-Schwarzschild spacetime. This space is a solution of Einstein-dilaton equations and contains a conformal exponential factor $\exp(k/r^2)$ in the metric. We consider the backreaction contributions coming only from the exponential warp factor

Chenguang Lu

Many researchers want to unify probability and logic by defining logical probability or probabilistic logic reasonably. This paper tries to unify statistics and logic so that we can use both statistical probability and logical probability at the same time. For this purpose, this paper proposes the P-T probability framework, which is assembled with Shannon's

Srivatsan Chakram, Kevin He, Akash V. Dixit, Andrew E. Oriani

Interactions are essential for the creation of correlated quantum many-body states. While two-body interactions underlie most natural phenomena, three- and four-body interactions are important for the physics of nuclei [1], exotic few-body states in ultracold quantum gases [2], the fractional quantum Hall effect [3], quantum error correction [4], and hologra

Davi Lima, Carlos Gustavo Moreira

We prove that, for every $k\ge 4$, the sets $M(k)$ and $L(k)$, which are Markov and Lagrange dynamical spectra related to conservative horseshoes and associated to continued fractions with coefficients bounded by $k$ coincide with the intersections of the classical Markov and Lagrange spectra with $(-\infty, \sqrt{k^2+4k}]$. We also observe that, despite the

Hidekazu Yoshioka, Yumi Yoshioka

We present an exactly-solvable risk-minimizing stochastic differential game for flood management in rivers. The streamflow dynamics follow stochastic differential equations driven by a Levy process. An entropic dynamic risk measure is employed to evaluate a flood risk under model uncertainty. The problem is solved via a Hamilton-Jacobi-Bellman-Isaacs equatio

Amitava Banerjee, Joseph D. Hart, Rajarshi Roy, Edward Ott

We devise a machine learning technique to solve the general problem of inferring network links that have time-delays. The goal is to do this purely from time-series data of the network nodal states. This task has applications in fields ranging from applied physics and engineering to neuroscience and biology. To achieve this, we first train a type of machine

Masood S. Mortazavi

Semantically-aligned $(speech, image)$ datasets can be used to explore "visually-grounded speech". In a majority of existing investigations, features of an image signal are extracted using neural networks "pre-trained" on other tasks (e.g., classification on ImageNet). In still others, pre-trained networks are used to extract audio features prior to semantic

Y. G. Zheng, S. J. Kang, C. Y. Yang, J. M. Bai

The jets of blazars are renowned for their multi-wavelength flares and rapid extreme variability; however, there are still some important unanswered questions about the physical processes responsible for these spectral and temporal changes in emission properties. In this paper, we develop a time-dependent particle evolution model for the time-varying emissio

Daniel Perales, Pei-Lun Tseng

We introduce the notion of operator-valued infinitesimal (OVI) independence for the Boolean and monotone cases. Then show that OVI Boolean (resp. monotone) independence is equivalent to the operator-valued Boolean (resp. monotone) independence over an algebra of $2\times 2$ upper triangular matrices. Moreover, we derive formulas to obtain the OVI Boolean (re

Raif Rustamov, Subhabrata Majumdar

Collections of probability distributions arise in a variety of applications ranging from user activity pattern analysis to brain connectomics. In practice these distributions can be defined over diverse domain types including finite intervals, circles, cylinders, spheres, other manifolds, and graphs. This paper introduces an approach for detecting difference

Jose Daniel Rodriguez, Maurice Espinoza, Kareem Rahn-Chique, German Urbina-Villalba

The rate of micelle solubilization (SR) can be appraised following the decrease of the radius of a macroscopic drop of oil in contact with a surfactant solution [Todorov, 2002]. Alternatively, the time required for the dissolution of a liquid dispersion can be used for this purpose. Here, the decrease of the turbidity of a dodecane-in-water (d/w) nanoemulsio

Surojit Saha, Shireen Elhabian, Ross T. Whitaker

Mapping data from and/or onto a known family of distributions has become an important topic in machine learning and data analysis. Deep generative models (e.g., generative adversarial networks ) have been used effectively to match known and unknown distributions. Nonetheless, when the form of the target distribution is known, analytical methods are advantage

Patrick Godwin, Reed Essick, Chad Hanna, Kipp Cannon

We present updates to GstLAL, a matched filter gravitational-wave search pipeline, in Advanced LIGO and Virgo's third observing run. We discuss the incorporation of statistical data quality information into GstLAL's multi-dimensional likelihood ratio ranking statistic and additional improvements to search for gravitational wave candidates found in only one d

A. R. C. Buarque, W. S. Dias

The sensitivity of quantum systems to external disturbances is a fundamental problem for the implementation of functional quantum devices, quantum information and computation. Based on remarkable experimental progress in optics and ultra-cold gases, we study the consequences of a short-time (instantaneous) noise while an intensity-dependent phase acquisition

Masaki Nakamura, Kazutoshi Sakakibara, Kazuhiro Ogata

To develop IoT and/or CSP systems, we need consider both continuous data from physical world and discrete data in computer systems. Such a system is called a hybrid system. Because of density of continuous data, it is not easy to do software testing to ensure reliability of hybrid systems. Moreover, the size of the state space increases exponentially for mul

Hang Yu, Jim Fuller, Kevin B. Burdge

We study the flux variation in helium white dwarfs (WDs) induced by dynamical tides for a variety of WD models with effective temperatures ranging from $T$=10 kK to $T$=26 kK. At linear order, we find the dynamical tide can significantly perturb the observed flux in hot WDs. If the temperature $T\gtrsim14$ kK, then the dynamical tide may induce a fractional

Shahab Joudaki, Pedro G. Ferreira, Nelson A. Lima, Hans A. Winther

We provide an end-to-end exploration of a distinct modified gravitational theory in Jordan-Brans-Dicke (JBD) gravity, from an analytical and numerical description of the background expansion and linear perturbations, to the nonlinear regime captured with a hybrid suite of $N$-body simulations, to the parameter constraints from existing cosmological probes. T

Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta

For future learning systems, incremental learning is desirable because it allows for: efficient resource usage by eliminating the need to retrain from scratch at the arrival of new data; reduced memory usage by preventing or limiting the amount of data required to be stored -- also important when privacy limitations are imposed; and learning that more closel

Ian Marquette, Christiane Quesne

A shape invariant nonseparable and nondiagonalizable three-dimensional model with quadratic complex interaction was introduced by Bardavelidze, Cannata, Ioffe, and Nishnianidze. However, the complete hidden symmetry algebra and the description of the associated states that form Jordan blocks remained to be studied. We present a set of six operators $\{A^{\pm

Vladislav V. Kravchenko, Sergii M. Torba

We consider two main inverse Sturm-Liouville problems: the problem of recovery of the potential and the boundary conditions from two spectra or from a spectral density function. A simple method for practical solution of such problems is developed, based on the transmutation operator approach, new Neumann series of Bessel functions representations for solutio

Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic

Despite extensive standardization, diagnostic interviews for mental health disorders encompass substantial subjective judgment. Previous studies have demonstrated that EEG-based neural measures can function as reliable objective correlates of depression, or even predictors of depression and its course. However, their clinical utility has not been fully reali

Ian Marquette, Christiane Quesne

A shape invariant nonseparable and nondiagonalizable two-dimensional model with quadratic complex interaction, first studied by Cannata, Ioffe, and Nishnianidze, is re-examined with the purpose of exhibiting its hidden algebraic structure. The two operators $A^+$ and $A^-$, coming from the shape invariant supersymmetrical approach, where $A^+$ acts as a rais

Alejandro Morales, Tom Froese

The nervous system of the nematode soil worm Caenorhabditis elegans exhibits remarkable complexity despite the worm's small size. A general challenge is to better understand the relationship between neural organization and neural activity at the system level, including the functional roles of inhibitory connections. Here we implemented an abstract simulation

Lianghao Cao, Omar Ghattas, J. Tinsley Oden

We propose a fast and robust scheme for the direct minimization of the Ohta-Kawasaki energy that characterizes the microphase separation of diblock copolymer melts. The scheme employs a globally convergent modified Newton method with line search which is shown to be mass-conservative, energy-descending, asymptotically quadratically convergent, and three orde

C. Frohmaier, C. R. Angus, M. Vincenzi, M. Sullivan

We present measurements of the local core collapse supernova (SN) rate using SN discoveries from the Palomar Transient Factory (PTF). We use a Monte Carlo simulation of hundreds of millions of SN light curve realizations coupled with the detailed PTF survey detection efficiencies to forward-model the SN rates in PTF. Using a sample of 86 core collapse SNe, i

Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys, Eric Yang

The application of deep learning to pathology assumes the existence of digital whole slide images of pathology slides. However, slide digitization is bottlenecked by the high cost of precise motor stages in slide scanners that are needed for position information used for slide stitching. We propose GloFlow, a two-stage method for creating a whole slide image

Kenny Young, Richard S. Sutton

Despite empirical success, the theory of reinforcement learning (RL) with value function approximation remains fundamentally incomplete. Prior work has identified a variety of pathological behaviours that arise in RL algorithms that combine approximate on-policy evaluation and greedification. One prominent example is policy oscillation, wherein an algorithm

Qihang Lin, Negar Soheili, Runchao Ma, Selvaprabu Nadarajah

Recent efforts to accelerate first-order methods have focused on convex optimization problems that satisfy a geometric property known as error-bound condition, which covers a broad class of problems, including piece-wise linear programs and strongly convex programs. Parameter-free first-order methods that employ projection-free updates have the potential to

Denis Korolkov, Stepan Rakhimov

ESCAPE is a free python package and framework for creating applications for simulating and fitting of X-ray and neutron scattering data with current support for specular reflectivity, polarized neutron reflectometry, high resolution X-ray diffraction, small angle scattering with future support for off-specular scattering from structured samples with complica

Abhinav Singh, Patrick Xia, Guanghui Qin, Mahsa Yarmohammadi

Copy mechanisms are employed in sequence to sequence models (seq2seq) to generate reproductions of words from the input to the output. These frameworks, operating at the lexical type level, fail to provide an explicit alignment that records where each token was copied from. Further, they require contiguous token sequences from the input (spans) to be copied

Roberto O. Zurita, Gustavo S. Wiederhecker, Thiago P. Mayer Alegre

We propose a feasible waveguide design optimized for harnessing Stimulated Brillouin Scattering with long-lived phonons. The design consists of a fully suspended ridge waveguide surrounded by a 1D phononic crystal that mitigates losses to the substrate while providing the needed homogeneity for the build-up of the optomechanical interaction. The coupling fac

Mauro Fava, Nakib Haider Protik, Chunhua Li, Navaneetha Krishnan Ravichandran

The promise enabled by BAs high thermal conductivity in power electronics cannot be assessed without taking into account the reduction incurred when doping the material. Using first principles calculations, we determine the thermal conductivity reduction induced by different group IV impurities in BAs as a function of concentration and charge state. We unvei

Charles T. Sebens

Some authors have claimed that there exists a minimum size (on the order of the Compton radius) for electron states composed entirely of positive-frequency solutions to the free Dirac equation. Other authors have put forward counterexamples to such claims. This article asks how the counterexamples of A. J. Bracken and G. F. Melloy [J. Phys. A. 32, 6127 (1999

Jean-Paul Renne, Guillaume Roussellet, Gustavo Schwenkler

Are COVID-19 fatalities large when a federal government does not enforce containment policies and instead allow states to implement their own policies? We answer this question by developing a stochastic extension of a SIRD epidemiological model for a country composed of multiple states. Our model allows for interstate mobility. We consider three policies: ma

A. Ait Ben Hammou, M. Oulne

Within the collective Bohr Hamiltonian, the adoption of a mass tensor as a function of collective coordinates has demonstrated its importance for describing the structure of nuclei. On the other hand, for odd-mass nuclei, the Coriolis interaction between the rotational and single-particle motions affects significantly the structure of nuclear excited states.

Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers

We propose a novel unsupervised learning approach to 3D shape correspondence that builds a multiscale matching pipeline into a deep neural network. This approach is based on smooth shells, the current state-of-the-art axiomatic correspondence method, which requires an a priori stochastic search over the space of initial poses. Our goal is to replace this cos

Xin Gao, Sundaresh Ram, Jeffrey J. Rodriguez

For object detection in wide-area aerial imagery, post-processing is usually needed to reduce false detections. We propose a two-stage post-processing scheme which comprises an area-thresholding sieving process and a morphological closing operation. We use two wide-area aerial videos to compare the performance of five object detection algorithms in the absen

Wolfgang Hennig, Shawn Hoover

As radiation detector arrays in nuclear physics applications become larger and physically more separated, the time synchronization and trigger distribution between many channels of detector readout electronics become more challenging. Clocks and triggers are traditionally distributed through dedicated cabling, but newer methods such as the IEEE 1588 Precisio

Chandan K A Reddy, Vishak Gopal, Ross Cutler

Human subjective evaluation is the gold standard to evaluate speech quality optimized for human perception. Perceptual objective metrics serve as a proxy for subjective scores. The conventional and widely used metrics require a reference clean speech signal, which is unavailable in real recordings. The no-reference approaches correlate poorly with human rati

Lei Zhao

The aim of this note is to explain the integrability of an integrable Boltzmann billiard model, previously established by Gallavotti and Jauslin in arXiv:2008.01955, alternatively via the viewpoint of projective dynamics. The additional first integral is shown to be related to the energy of a corresponding system on a hemisphere. We show that this viewpoint

Senaida Hernández Santana, Andras Molnar, Christian Gogolin, J. Ignacio Cirac

While temperature is well understood as an intensive quantity in standard thermodynamics, it is less clear whether the same holds in the presence of strong correlations, especially in the case of quantum systems, which may even display correlations with no classical analogue. The problem lies in the fact that, under the presence of strong correlations, subsy

Sriram Gopalakrishnan, Subbarao Kambhampati

In situations where humans and robots are moving in the same space whilst performing their own tasks, predictable paths taken by mobile robots can not only make the environment feel safer, but humans can also help with the navigation in the space by avoiding path conflicts or not blocking the way. So predictable paths become vital. The cognitive effort for t

Zachary Feinstein, Andreas Sojmark

In this work we provide a simple setting that connects the structural modelling approach of Gai-Kapadia interbank networks with the mean-field approach to default contagion. To accomplish this we make two key contributions. First, we propose a dynamic default contagion model with endogenous early defaults for a finite set of banks, generalising the Gai-Kapad

Lei Zhao

In this paper, we consider a time-periodically forced Kepler problem in any dimensions, with an external force which we only assume to be regular in a neighborhood of the attractive center. We prove that there exist infinitely many periodic orbits in this system, with possible double collisions with the center regularized, which accumulate the attractive cen

Robert P. O'Shea, Shelby E. Temple, Gary P. Misson, Nicholas J. Wade

In 1844, the Austrian mineralogist Wilhelm von Haidinger reported he could see the polarization of light with the naked eye. It appears as a faint, blurry, transient, yellow hourglass shape superimposed on whatever one looks at. It is now commonly called Haidinger's brushes. To our surprise, even though the paper is well cited, we were unable to find a trans

Marimuthu Kalimuthu, Aditya Mogadala, Marius Mosbach, Dietrich Klakow

Visual captioning aims to generate textual descriptions given images or videos. Traditionally, image captioning models are trained on human annotated datasets such as Flickr30k and MS-COCO, which are limited in size and diversity. This limitation hinders the generalization capabilities of these models while also rendering them liable to making mistakes. Lang

Minh Triet Chau

We aim to solve semantic video segmentation in autonomous driving, namely road detection in real time video, using techniques discussed in (Shelhamer et al., 2016a). While fully convolutional network gives good result, we show that the speed can be halved while preserving the accuracy. The test dataset being used is KITTI, which consists of real footage from

A. L. C. Hayward, E. Bertok, U. Schneider, F. Heidrich-Meisner

Recent experiments with ultracold quantum gases have successfully realized integer-quantized topological charge pumping in optical lattices. Motivated by this progress, we study the effects of static disorder on topological Thouless charge pumping. We focus on the half-filled Rice-Mele model of free spinless fermions and consider random diagonal disorder. In

Mohamed Ismail Abdelrahman, Zeki Hayran, Aobo Chen, Francesco Monticone

This note is a comment on a recent article [Tsakmakidis, et al., Nat Commun 10 (2019)] that presents a thought-provoking proposal to overcome the bandwidth restrictions of invisibility cloaks based on using media that support superluminal (faster than light in free space) group and phase velocities. As illustrated in Fig. 1 of the original article, a wave pa

E. Wang, T. Nordlander, M. Asplund, A. M. Amarsi

Accurately known stellar lithium abundances may be used to shed light on a variety of astrophysical phenomena such as Big Bang nucleosynthesis, radial migration, ages of stars and stellar clusters, and planet engulfment events. We present a grid of synthetic lithium spectra that are computed in non-local thermodynamic equilibrium (NLTE) across the STAGGER gr

E. Fiorellino, D. Elia, Ph. André, A. Men'shchikov

The Herschel Gould Belt survey mapped the nearby (d < 500 pc) star-forming regions to understand better how the prestellar phase influences the star formation process. Here we report a complete census of dense cores in a 15 deg2 area of the Serpens star-forming region located between d=420 pc and 484 pc. The PACS and SPIRE cameras imaged this cloud from 70mi

Kaiming Fu, Yulu Jin, Zhousheng Chen

Diagnosis results are highly dependent on the volume of test set. To derive the most efficient test set, we propose several machine learning based methods to predict the minimum amount of test data that produces relatively accurate diagnosis. By collecting outputs from failing circuits, the feature matrix and label vector are generated, which involves the in

Junzhe Shi, Bin Xu, Xingyu Zhou, Jun Hou

Electric city bus gains popularity in recent years for its low greenhouse gas emission, low noise level, etc. Different from a passenger car, the weight of a city bus varies significantly with different amounts of onboard passengers. After analyzing the importance of battery aging and passenger load effects on an optimal energy management strategy, this stud

G. Wendell Misch, Surja K. Ghorui, Projjwal Banerjee, Yang Sun

We develop a method to compute thermally-mediated transition rates between the ground state and long-lived isomers in nuclei. We also establish criteria delimiting a thermalization temperature above which a nucleus may be considered a single species and below which it must be treated as two separate species: a ground state species, and an astrophysical isome

Yuanjie Li, Esha Datta, Jiaxin Ding, Ness Shroff

The demand for seamless Internet access under extreme user mobility, such as on high-speed trains and vehicles, has become a norm rather than an exception. However, the 4G/5G mobile network is not always reliable to meet this demand, with non-negligible failures during the handover between base stations. A fundamental challenge of reliability is to balance t

Jordi Paillisse, Marc Portoles, Albert Lopez, Alberto Rodriguez-Natal

Enterprise Networks, over the years, have become more and more complex trying to keep up with new requirements that challenge traditional solutions. Just to mention one out of many possible examples, technologies such as Virtual LANs (VLANs) struggle to address the scalability and operational requirements introduced by Internet of Things (IoT) use cases. To

Sourangsu Banerji, Yu Shi, Vivian Song-En Su, Udayan Ghosh

This letter reports proof-of-principle demonstration of 3D printable, low-cost, and compact THz spectral splitters based on diffractive optical elements (DOEs) designed to disperse the incident collimated broadband THz radiation (0.5 THz - 0.7 THz) at a pre-specified distance. Via inverse design, we show that it is possible to design such a diffractive optic

Ciria Lima-Dias, Antonela Monachesi, Sergio Torres-Flores, Arianna Cortesi

The nearby Hydra Cluster ($\sim$50 Mpc) is an ideal laboratory to understand, in detail, the influence of the environment on the morphology and quenching of galaxies in dense environments. We study the Hydra cluster galaxies in the inner regions ($1R_{200}$) of the cluster using data from the Southern Photometric Local Universe Survey (S-PLUS), which uses 12

Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar

Recently, invariant risk minimization (IRM) (Arjovsky et al.) was proposed as a promising solution to address out-of-distribution (OOD) generalization. In Ahuja et al., it was shown that solving for the Nash equilibria of a new class of "ensemble-games" is equivalent to solving IRM. In this work, we extend the framework in Ahuja et al. for linear regressions

Zhenzhen Dai, Ivan Jambor, Pekka Taimen, Milan Pantelic

Purpose: We aimed to develop deep machine learning (DL) models to improve the detection and segmentation of intraprostatic lesions (IL) on bp-MRI by using whole amount prostatectomy specimen-based delineations. We also aimed to investigate whether transfer learning and self-training would improve results with small amount labelled data. Methods: 158 patients

Hesam Hamledari, Martin Fischer

This paper presents a smart contract-based solution for autonomous administration of construction progress payments. It bridges the gap between payments (cash flow) and the progress assessments at job sites (product flow) enabled by reality capture technologies and building information modeling (BIM). The approach eliminates the reliance on the centralized a

Vitor M. de Oliveira, Matheus S. Palmero, Iberê L. Caldas

Hamiltonian systems that are either open, leaking, or contain holes in the phase space possess solutions that eventually escape the system's domain. The motion described by such escape orbits before crossing the escape threshold can be understood as a transient behavior. In this work, we introduce a numerical method to visually illustrate and quantify the tr

Alexander Garver, Khrystyna Serhiyenko

Maximal green sequences are important objects in representation theory, cluster algebras, and string theory. The two fundamental questions about maximal green sequences are whether a given algebra admits such sequences and, if so, does it admit only finitely many. We study maximal green sequences in the case of string algebras and give sufficient conditions

Jumana Almahmoud, Kruthika Kikkeri

Emotions recognition is commonly employed for health assessment. However, the typical metric for evaluation in therapy is based on patient-doctor appraisal. This process can fall into the issue of subjectivity, while also requiring healthcare professionals to deal with copious amounts of information. Thus, machine learning algorithms can be a useful tool for

Yejian Chen, Jafar Mohammadi, Stefan Wesemann, Thorsten Wild

Recently, Machine Learning (ML) is recognized as an effective tool for wireless communications and plays an evolutionary role to enhance Physical Layer (PHY) of 5th Generation (5G) and Beyond 5G (B5G) systems. In this paper, we focus on the ML-based channel estimation for 2- Dimensional (2D) massive antenna arrays. Due to the extremely high computational req

Yiqing Xu, Alexander Sharples, Julien Fatome, Stéphane Coen

Kerr microresonators driven in the normal dispersion regime typically require the presence of localized dispersion perturbations, such as those induced by avoided mode crossings, to initiate the formation of optical frequency combs. In this work, we experimentally demonstrate that this requirement can be lifted by driving the resonator with a pulsed pump sou

Dylan Ebert, Ellie Pavlick

We introduce a new dataset for training and evaluating grounded language models. Our data is collected within a virtual reality environment and is designed to emulate the quality of language data to which a pre-verbal child is likely to have access: That is, naturalistic, spontaneous speech paired with richly grounded visuospatial context. We use the collect

Benjamin Bally, Michael Bender

Many quantal many-body methods that aim at the description of self-bound nuclear or mesoscopic electronic systems make use of auxiliary wave functions that break one or several of the symmetries of the Hamiltonian in order to include correlations associated with the geometrical arrangement of the system's constituents. Such reference states have been used al

Raoul R. Wadhwa, Jacob G. Scott

We introduce ICON, an R package that contains 1075 complex network datasets in a standard edgelist format. All provided datasets have associated citations and have been indexed by the Colorado Index of Complex Networks - also referred to as ICON. In addition to supplying a large and diverse corpus of useful real-world networks, ICON also implements an S3 gen

Vladislav Barkanass, Jürgen Jost, Emil Saucan

Motivated by the methods and results of manifold sampling based on Ricci curvature, we propose a similar approach for networks. To this end we make appeal to three types of discrete curvature, namely the graph Forman-, full Forman- and Haantjes-Ricci curvatures for edge-based and node-based sampling. We present the results of experiments on real life network

Anthony J. Leggett, Ying Liu

Soon after the discovery of superconductivity in Sr2RuO4 (SRO) in 1994, it was conjectured that its order parameter (OP) has a form similar to that realized in the superfluid He-3, namely, odd parity and spin triplet. The chiral p-wave pairing realized in He-3 A-phase was favored by several early experiments, in particular, the muon spin rotation and the Kni

S. V. Poroseva, S. M. Murman

In the current study, model expressions for fifth-order velocity moments obtained from the truncated Gram-Charlier series expansions model for a turbulent flow field probability density function are validated using data from direct numerical simulation (DNS) of a planar turbulent flow in a strained channel. Simplicity of the model expressions, the lack of un

Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun

Spatial computing devices have been shown to significantly accelerate stencil computations, but have so far relied on unrolling the iterative dimension of a single stencil operation to increase temporal locality. This work considers the general case of mapping directed acyclic graphs of heterogeneous stencil computations to spatial computing systems, assumin

Noah J. Goodall

As automated vehicles receive more attention from the media, there has been an equivalent increase in the coverage of the ethical choices a vehicle may be forced to make in certain crash situations with no clear safe outcome. Much of this coverage has focused on a philosophical thought experiment known as the "trolley problem," and substituting an automated

Theophilus Agama

Motivated by the Pierce-Birkhoff conjecture, we launch an extension program for single variable expansivity theory. We study this notion under tuples of polynomials in the ring $\mathbb{R}[x_1,x_2,\ldots,x_n]$. As an application, we develop some class of inequalities to study the Pierce-Birkhoff conjecture.

Andrei Shubin

Let $\alpha > 0$ be any fixed non-integer, $I$ be any subinterval of $[0; 1)$. In the paper, we prove an analogue of Bombieri-Vinogradov theorem for the set of primes $p$ satisfying the condition $\{ p^{\alpha} \} \in I$. This strengthens the previous result of Gritsenko and Zinchenko.

William C. Abram, Jeffrey C. Lagarias, Daniel J. Slonim

This paper studies subsets of one-sided shift spaces on a finite alphabet. Such subsets arise in symbolic dynamics, in fractal constructions, and in number theory. We study a family of decimation operations, which extract subsequences of symbol sequences in infinite arithmetic progressions, and show they are closed under composition. We also study a family o

Julia Camps, Brodie Lawson, Christopher Drovandi, Ana Minchole

The realisation of precision cardiology requires novel techniques for the non-invasive characterisation of individual patients' cardiac function to inform therapeutic and diagnostic decision-making. The electrocardiogram (ECG) is the most widely used clinical tool for cardiac diagnosis. Its interpretation is, however, confounded by functional and anatomical

Thomas Peterken, Michael Merrifield, Alfonso Aragón-Salamanca, Vladimir Avila-Reese

It remains an open question as to how long ago the morphology that we see in a present-day galaxy was typically imprinted. Studies of galaxy populations at different redshifts reveal that the balance of morphologies has changed over time, but such snapshots cannot uncover the typical timescales over which individual galaxies undergo morphological transformat