December 2020 arXiv papers — page 141

Huiping Zhuang, Zhiping Lin, Kar-Ann Toh

Decoupled learning is a branch of model parallelism which parallelizes the training of a network by splitting it depth-wise into multiple modules. Techniques from decoupled learning usually lead to stale gradient effect because of their asynchronous implementation, thereby causing performance degradation. In this paper, we propose an accumulated decoupled le

Aaron Dutle, César Muñoz, Esther Conrad, Alwyn Goodloe

The Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a software architecture incorporating a set of algorithms to enable autonomous operations of unmanned aircraft applications. This paper provides an overview of Monitoring ICAROUS, a project whose objective is to provide a formal approach to generating runtime m

Bojing Feng, Wenfang Xue, Bindang Xue, Zeyu Liu

Credit rating is an analysis of the credit risks associated with a corporation, which reflect the level of the riskiness and reliability in investing. There have emerged many studies that implement machine learning techniques to deal with corporate credit rating. However, the ability of these models is limited by enormous amounts of data from financial state

Yu Wang, Ziqiao Guan, Wei Hou, Fusheng Wang

Chronic kidney disease (CKD) has a poor prognosis due to excessive risk factors and comorbidities associated with it. The early detection of CKD faces challenges of insufficient medical histories of positive patients and complicated risk factors. In this paper, we propose the TRACE (Transformer-RNN Autoencoder-enhanced CKD Detector) framework, an end-to-end

Aolan Sun, Jianzong Wang, Ning Cheng, Huayi Peng

This paper introduces a graphical representation approach of prosody boundary (GraphPB) in the task of Chinese speech synthesis, intending to parse the semantic and syntactic relationship of input sequences in a graphical domain for improving the prosody performance. The nodes of the graph embedding are formed by prosodic words, and the edges are formed by t

Sompong Dhompongsa, Poom Kumam

A new and simple method for quasi-convex optimization is introduced from which its various applications can be derived. Especially, a global optimum under constrains can be approximated for all continuous functions.

Juan Escudero-Pedrosa, Felipe J. Llanes-Estrada, José Antonio Oller, Alexandre Salas-Bernárdez

Effective Field Theories (EFTs) for Goldstone Boson scattering at a low order allow the computation of near--threshold observables in terms of a few coefficients arranged by a counting. As a matter of principle they should make sense up to an energy scale $E\sim 4πF$ but the expansion in powers of momentum violates exact elastic unitarity and renders the der

Babis Magoutas, Dimitris Apostolou, Gregoris Mentzas

Modern organizations need real-time awareness about the current business conditions and the various events that occur from multiple and heterogeneous environments and influence their business operations. Moreover, based on real-time awareness they need a mechanism that allows them to respond quickly to the changing business conditions, in order to either avo

Fabian Faust, Aurélien Thierry, Tilo Müller, Felix Freiling

In contrast to the common habit of taking full bitwise copies of storage devices before analysis, selective imaging promises to alleviate the problems created by the increasing capacity of storage devices. Imaging is selective if only selected data objects from an image that were explicitly chosen are included in the copied data. While selective imaging has

Babis Magoutas, Gregoris Mentzas

Adaptivity and personalization technologies appear not to be very much used in eparticipation projects to date. These technologies are commonly used to overcome the overflow of information and service providers adopt them in order to acquire a better knowledge of their end-users and optimize their service offerings. In this paper we investigate the potential

Sebastiaan Y. Haffert, Christoph U. Keller, Richard Dekany

Laser guide stars (LGS) are used in many adaptive optics systems to extend sky coverage. The most common wavefront sensor used in combination with a LGS is a Shack-Hartmann wavefront sensor (SHWFS). The Shack-Hartmann has a major disadvantage for extended source wavefront sensing because it directly samples the image. In this proceeding we propose to use the

Mihaela Dimovska, Donatello Materassi

Networked dynamic systems are often abstracted as directed graphs, where the observed system processes form the vertex set and directed edges are used to represent non-zero transfer functions. Recovering the exact underlying graph structure of such a networked dynamic system, given only observational data, is a challenging task. Under relatively mild well-po

Debora Pavela, Bojan Novaković, Valerio Carruba, Viktor Radović

The Karma asteroid family is a group of primitive asteroids in the middle part of the main belt, just at the outer edge of the 3J:1A mean-motion resonance. We obtained the list of the family members with 317 asteroids and estimated that it was formed by the catastrophic disruption of a parent body that was between 34 and 41 km in diameter. Based on the V-sha

Amit Seta, Luiz Felippe S. Rodrigues, Christoph Federrath, Christopher A. Hales

Fluctuation dynamos are thought to play an essential role in magnetized galaxy evolution, saturating within $\sim0.01~$Gyr and thus potentially acting as seeds for large-scale dynamos. However, unambiguous observational confirmation of the fluctuation dynamo action in a galactic environment is still missing. This is because, in spiral galaxies, it is difficu

Trevor Londt, Xiaoying Gao, Peter Andreae

DenseNet architectures have demonstrated impressive performance in image classification tasks, but limited research has been conducted on using character-level DenseNet (char-DenseNet) architectures for text classification tasks. It is not clear what DenseNet architectures are optimal for text classification tasks. The iterative task of designing, training a

Ilias, Chenn, Israel Michael Sigal

Starting from the microscopic reduced Hartree-Fock equation, we derive the nanoscopic linearized Poisson-Boltzmann equation for the electrostatic potential associated with the electron density.

Simon J D Cox, Alejandra N Gonzalez-Beltran, Barbara Magagna, Maria-Cristina Marinescu

We present ten simple rules that support converting a legacy vocabulary -- a list of terms available in a print-based glossary or table not accessible using web standards -- into a FAIR vocabulary. Various pathways may be followed to publish the FAIR vocabulary, but we emphasise particularly the goal of providing a distinct IRI for each term or concept. A st

A. D. Bermúdez Manjarres, N. Marín-Medina

We revisit quantum-classical hybrid systems of the Sudarshan type under the light of Galilean covariance. We show that these kind of hybrids cannot be given as a unitary representation of the Galilei group and at the same time conserve the total linear momentum unless the interaction term only depends on the relative canonical velocities.

David Nesvorny, Fernando V. Roig, Rogerio Deienno

The terrestrial planets are believed to have formed by violent collisions of tens of lunar- to Mars-size protoplanets at time t<200 Myr after the protoplanetary gas disk dispersal (t_0). The solar system giant planets rapidly formed during the protoplanetary disk stage and, after t_0, radially migrated by interacting with outer disk planetesimals. An early (

Rohan Proctor, Charles Patrick Martin

The popularity of applying machine learning techniques in musical domains has created an inherent availability of freely accessible pre-trained neural network (NN) models ready for use in creative applications. This work outlines the implementation of one such application in the form of an assistance tool designed for live improvisational performances by lap

Alexander Madurowicz, Bruce Macintosh, Lisa Poyneer, Duan Li

During its move from the mountaintop of Cerro Pachon in Chile to the peak of Mauna Kea in Hawaii, the Gemini Planet Imager will make a pit stop to receive various upgrades, including a pyramid wavefront sensor. As a highly non-linear sensor, a standard approach to linearize the response of the pyramid is induce a rapid circular modulation of the beam around

Ningcheng Li, Jonathan Wakim, Yilun Koethe, Timothy Huber

Purpose: To evaluate manual and automatic registration times as well as accuracy with augmented reality during alignment of a holographic 3-dimensional (3D) model onto the real-world environment. Method: 18 participants in various stages of clinical training across two academic centers registered a 3D CT phantom model onto a CT grid using the HoloLens 2 augm

Magdalena Laurien, Himanshu Saini, Oleg Rubel

Recently, a number of new two-dimensional (2D) materials based on puckered phosphorene and arsenene have been predicted with moderate band gaps, good absorption properties and carrier mobilities superior to transition metal dichalcogenides. For heterojunction applications, it is important to know the relative band alignment of these new 2D materials. We repo

Bartolomé Coll, Joan Josep Ferrando, Juan Antonio Sáez

In a recent paper (Coll {\em et al} 2019 {\it Class. Quantum Grav.} {\bf 36} 175004) we have studied a family of Szekeres-Szafron solutions of class II in local thermal equilibrium (singular models). In this paper we deal with a similar study for all other class II Szekeres-Szafron solutions without symmetries. These models in local thermal equilibrium (regu

S. J. Tingay, W. Joubert

We have realised a simple prototype system to perform searches for short timescale optical transients, utilising the novel drift scan imaging technique described by Tingay (2020). We used two coordinated and aligned cameras, with an overlap field-of-view of approximately 3.7 sq. deg., to capture over 34000 X 5 second images during approximately 24 hours of o

Samuel Totorica, Masahiro Hoshino, Tom Abel, Frederico Fiuza

Magnetic reconnection is a fundamental plasma process that is thought to play a key role in the production of nonthermal particles associated with explosive phenomena in space physics and astrophysics. Experiments at high-energy-density facilities are starting to probe the microphysics of reconnection at high Lundquist numbers and large system sizes. We have

Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz

Class imbalance is a problem of significant importance in applied deep learning where trained models are exploited for decision support and automated decisions in critical areas such as health and medicine, transportation, and finance. The challenge of learning deep models from imbalanced training data remains high, and the state-of-the-art solutions are typ

Charles Patrick Martin, Zeruo Liu, Yichen Wang, Wennan He

This work examines how head-mounted AR can be used to build an interactive sonic landscape to engage with a public sculpture. We describe a sonic artwork, &#34;Listening To Listening&#34;, that has been designed to accompany a real-world sculpture with two prototype interaction schemes. Our artwork is created for the HoloLens platform so that users can have

Zhi Tian, Chunhua Shen, Xinlong Wang, Hao Chen

We present a high-performance method that can achieve mask-level instance segmentation with only bounding-box annotations for training. While this setting has been studied in the literature, here we show significantly stronger performance with a simple design (e.g., dramatically improving previous best reported mask AP of 21.1% in Hsu et al. (2019) to 31.6%

Juan Sosa, Lina Buitrago

In this paper, we provide a review on both fundamentals of social networks and latent space modeling. The former discusses important topics related to network description, including vertex characteristics and network structure; whereas the latter articulates relevant advances in network modeling, including random graph models, generalized random graph models

Daniel Lacker, Lane Chun Yeung

Inequalities between transportation costs and Fisher information are known to characterize certain concentration properties of Markov processes around their invariant measures. This note provides a new characterization of the quadratic transportation-information inequality $W_2I$ in terms of a dimension-free concentration property for i.i.d. (conditionally o

Cai Li, Luo Xiao, Sheng Luo

Studies of Alzheimer&#39;s disease (AD) often collect multiple longitudinal clinical outcomes, which are correlated and predictive of AD progression. It is of great scientific interest to investigate the association between the outcomes and time to AD onset. We model the multiple longitudinal outcomes as multivariate sparse functional data and propose a func

Felipe J Medina-Aguayo, J Andrés Christen

Handling multimodality that commonly arises from complicated statistical models remains a challenge. Current Markov chain Monte Carlo (MCMC) methodology tackling this subject is based on an ensemble of chains targeting a product of power-tempered distributions. Despite the theoretical validity of such methods, practical implementations typically suffer from

Panayiotis Moutis, Omid Alizadeh-Mousavi

Real-time monitoring of distribution systems has be-come necessary, due to the deregulation of electricity markets and the wide deployment of distributed energy resources. To monitor voltage and current at sub-cycle detail, requires, typically, major investment undertaking and disruptions to the operation of the grid. In this work, measurements of the low vo

Andrew J. Lawler, Viviana Acquaviva

Bayesian model comparison frameworks can be used when fitting models to data in order to infer the appropriate model complexity in a data-driven manner. We aim to use them to detect the correct number of major episodes of star formation from the analysis of the spectral energy distributions (SEDs) of galaxies, modeled after 3D-HST galaxies at z ~ 1. Starting

J. Crestani, M. Fabrizio, V. F. Braga, C. Sneden

We performed the largest and most homogeneous spectroscopic survey of field RR Lyraes (RRLs). We secured $\approx$6,300 high resolution (HR, R$\sim$35,000) spectra for 143 RRLs (111 fundamental, RRab; 32 first overtone, RRc). The atmospheric parameters were estimated by using the traditional approach and the iron abundances were measured by using an LTE line

Panayiotis Moutis, Omid Alizadeh-Mousavi

The ever-increasing deployment of distributed resources and the opportunities offered to loads for more active roles has changed the previously unidirectional and relatively straight-forward operating profile of distribution systems (DS). DS will be required to be monitored closely for robustness and sufficient power quality. State estimation of transmission

J. Takata, X. F. Wang, H. H. Wang, L. C. -C. Lin

We report a study of the X-ray emission from the white dwarf/M-type star binary system AR Scorpii using archival data taken in 2016-2020. It has been known that the X-ray emission is dominated by the optically thin thermal plasma emission, and its flux level varies significantly over the orbital phase. The X-ray emission also contains a component that modula

Maxime Amram, Jack Dunn, Ying Daisy Zhuo

We propose an approach for learning optimal tree-based prescription policies directly from data, combining methods for counterfactual estimation from the causal inference literature with recent advances in training globally-optimal decision trees. The resulting method, Optimal Policy Trees, yields interpretable prescription policies, is highly scalable, and

Karan Sikka, Indranil Sur, Susmit Jha, Anirban Roy

We target the problem of detecting Trojans or backdoors in DNNs. Such models behave normally with typical inputs but produce specific incorrect predictions for inputs poisoned with a Trojan trigger. Our approach is based on a novel observation that the trigger behavior depends on a few ghost neurons that activate on trigger pattern and exhibit abnormally hig

Jaime Román-Garza, Simone S. Bavera, Tassos Fragos, Emmanouil Zapartas

Recent detailed 1D core-collapse simulations have brought new insights on the final fate of massive stars, which are in contrast to commonly used parametric prescriptions. In this work, we explore the implications of these results to the formation of coalescing black-hole (BH) - neutron-star (NS) binaries, such as the candidate event GW190426_152155 reported

Florence Tsang, Tristan Walker, Ryan A. MacDonald, Armin Sadeghi

Mobile robots are often tasked with repeatedly navigating through an environment whose traversability changes over time. These changes may exhibit some hidden structure, which can be learned. Many studies consider reactive algorithms for online planning, however, these algorithms do not take advantage of the past executions of the navigation task for future

Xiaodong Cheng, Jacquelien M. A. Scherpen

Network systems consist of subsystems and their interconnections, and provide a powerful framework for analysis, modeling and control of complex systems. However, subsystems may have high-dimensional dynamics, and the amount and nature of interconnections may also be of high complexity. Therefore, it is relevant to study reduction methods for network systems

Huyuan Chen, Hichem Hajaiej

In this paper, we develop the Littman-Stampacchia-Weinberger duality approach to obtain global W^1,p estimates for a class of elliptic problems involving Leray-Hardy operators and measure sources in a distributional framework associated with a dual formulation with a specific weight function.

A. Zdeb, M. Warda, L. M. Robledo

The microscopic studies on nuclear fission require the evaluation of the potential energy surface as a function of the collective coordinates. A reasonable choice of constraints on multipole moments should be made to describe the topography of the surface completely within a reasonable amount of computing time. We present a detailed analysis of fission barri

Faisal Nawab

We propose WedgeChain, a data store that spans both edge and cloud nodes (an edge-cloud system). WedgeChain consists of a logging layer and a data indexing layer. In this study, we encounter two challenges: (1) edge nodes are untrusted and potentially malicious, and (2) edge-cloud coordination is expensive. WedgeChain tackles these challenges by the followin

Mark Curiel, Elizabeth Gross, Carlos Munoz

Chemical reaction networks are often used to model and understand biological processes such as cell signaling. Under the framework of chemical reaction network theory, a process is modeled with a directed graph and a choice of kinetics, which together give rise to a dynamical system. Under the assumption of mass action kinetics, the dynamical system is polyn

Martin Stano, Wanda Benesova, Lukas Samuel Martak

In many practical applications, deep neural networks have been typically deployed to operate as a black box predictor. Despite the high amount of work on interpretability and high demand on the reliability of these systems, they typically still have to include a human actor in the loop, to validate the decisions and handle unpredictable failures and unexpect

Paul Corlies, George D. McDonald, Alexander G. Hayes, James J. Wray

From orbit, the visibility of Titan&#39;s surface is limited to a handful of narrow spectral windows in the near-infrared (near-IR), primarily from the absorption of methane gas. This has limited the ability to identify specific compounds on the surface -- to date Titan&#39;s bulk surface composition remains unknown. Further, understanding of the surface com

Gabriel Schamberg, Sourish Chakravarty, Taylor E. Baum, Emery N. Brown

Burst suppression is an electroencephalography (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. Its distinctive feature is alternation between short temporal segments of near-isoelectric inactivity (suppressions) and relatively high-voltage activity (bursts). Prior modeling studies suggest that

Stephan Haarmann, Marco Montali, Mathias Weske

Traditionally, business process management focuses on structured, imperative processes. With the increasing importance of knowledge work, semi-structured processes are entering center stage. Existing approaches to modeling knowledge-intensive business processes use data objects but fail to sufficiently take into account data object cardinalities. Hence, they

Percy Deift, Luen-Chau Li, Herbert Spohn, Carlos Tomei

We consider the open Toda chain with external forcing, and in the case when the forcing stretches the system, we derive the longtime behavior of solutions of the chain. Using an observation of Jürgen Moser, we then show that the system is completely integrable, in the sense that the $2N$-dimensional system has $N$ functionally independent Poisson commuting i

Afonso S. Bandeira, Dmitriy Kunisky, Alexander S. Wein

Montanari and Richard (2015) asked whether a natural semidefinite programming (SDP) relaxation can effectively optimize $\mathbf{x}^{\top}\mathbf{W} \mathbf{x}$ over $\|\mathbf{x}\| = 1$ with $x_i \geq 0$ for all coordinates $i$, where $\mathbf{W} \in \mathbb{R}^{n \times n}$ is drawn from the Gaussian orthogonal ensemble (GOE) or a spiked matrix model. In s

Alexander Maletzky

We present a generic and executable formalization of signature-based algorithms (such as Faugère&#39;s $F_5$) for computing Gröbner bases, as well as their mathematical background, in the Isabelle/HOL proof assistant. Said algorithms are currently the best known algorithms for computing Gröbner bases in terms of computational efficiency. The formal developme

K. Baudin, A. Fusaro, J. Garnier, N. Berti

The wave turbulence theory predicts that a conservative system of nonlinear waves can exhibit a process of condensation, which originates in the singularity of the Rayleigh-Jeans equilibrium distribution of classical waves. Considering light propagation in a multimode fiber, we show that light condensation is driven by an energy flow toward the higher-order

Khalfalla Awedat, Almabrok Essa

One of the most serious global health threat is COVID-19 pandemic. The emphasis on improving diagnosis and increasing the diagnostic capability helps stopping its spread significantly. Therefore, to assist the radiologist or other medical professional to detect and identify the COVID-19 cases in the shortest possible time, we propose a computer-aided detecti

M. Houzet, L. I. Glazman

We investigate inelastic microwave photon scattering by a transmon qubit embedded in a high-impedance circuit. The transmon undergoes a charge-localization (Schmid) transition upon the impedance reaching the critical value. Due to the unique transmon level structure, the fluorescence spectrum carries a signature of the transition point. At higher circuit imp

Francis Ogoke, Kazem Meidani, Amirreza Hashemi, Amir Barati Farimani

Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order of features for each sample. They thus cannot be easily constructed for an unstructured dataset. Therefore, a graph based data-driven model to perform inference on fields defined on

Charles Semple, Gerry Toft

Rooted triples, rooted binary phylogenetic trees on three leaves, are sufficient to encode rooted binary phylogenetic trees. That is, if $\mathcal T$ and $\mathcal T&#39;$ are rooted binary phylogenetic $X$-trees that infers the same set of rooted triples, then $\mathcal T$ and $\mathcal T&#39;$ are isomorphic. However, in general, this sufficiency does not

Renyue Cen

From a new perspective, we re-examine self-gravity and turbulence jointly, in hopes of understanding the physical basis for one of the most important empirical relations governing clouds in the interstellar medium (ISM), the Larson&#39;s Relation relating velocity dispersion ($σ_R$) to cloud size ($R$). We report on two key new findings. First, the correct f

Sachin Mehta, Amit Kumar, Fitsum Reda, Varun Nasery

Video transmission applications (e.g., conferencing) are gaining momentum, especially in times of global health pandemic. Video signals are transmitted over lossy channels, resulting in low-quality received signals. To restore videos on recipient edge devices in real-time, we introduce an efficient video restoration network, EVRNet. EVRNet efficiently alloca

Niv Buchbinder, Christian Coester, Joseph, Naor

We consider the online $k$-taxi problem, a generalization of the $k$-server problem, in which $k$ servers are located in a metric space. A sequence of requests is revealed one by one, where each request is a pair of two points, representing the start and destination of a travel request by a passenger. The goal is to serve all requests while minimizing the di

Nicolas T. Kurtovic, Paola Pinilla, Feng Long, Myriam Benisty

We aim to estimate if structures, such as cavities, rings, and gaps, are common in disks around VLMS and to test models of structure formation in these disks. We also aim to compare the radial extent of the gas and dust emission in disks around VLMS, which can give us insight about radial drift. We studied six disks around VLMS in the Taurus star-forming reg

Trevor Londt, Xiaoying Gao, Bing Xue, Peter Andreae

Character-level convolutional neural networks (char-CNN) require no knowledge of the semantic or syntactic structure of the language they classify. This property simplifies its implementation but reduces its classification accuracy. Increasing the depth of char-CNN architectures does not result in breakthrough accuracy improvements. Research has not establis

Hassan Shapourian, Roger S. K. Mong, Shinsei Ryu

A basic diagnostic of entanglement in mixed quantum states is known as the partial transpose and the corresponding entanglement measure is called the logarithmic negativity. Despite the great success of logarithmic negativity in characterizing bosonic many-body systems, generalizing the partial transpose to fermionic systems remained a technical challenge un

Puyuan Peng, Herman Kamper, Karen Livescu

We propose a new unsupervised model for mapping a variable-duration speech segment to a fixed-dimensional representation. The resulting acoustic word embeddings can form the basis of search, discovery, and indexing systems for low- and zero-resource languages. Our model, which we refer to as a maximal sampling correspondence variational autoencoder (MCVAE),

Zhenghan Liao, Suriyanarayanan Vaikuntanathan

Combinations of gyroscopic forces and nonequilibrium activity has been explored recently in rectifying energy in networks with complex geometries and topologies [Phys. Rev. X 10, 021036]. Based on this previous work, here we study the effect of added time-periodic modulations. Numerical calculations show that the time-modulated network generates net energy t

Brannon B. Klopfer, Stewart A. Koppell, Adam J. Bowman, Yonatan Israel

We present the design and prototype of a switchable electron mirror, along with a technique for driving it with a flat-top pulse. We employ a general technique for electronic pulse-shaping, where high fidelity of the pulse shape is required but the characteristics of the system, which are possibly nonlinear, are not known. This driving technique uses an arbi

Lita M. de la Cruz, Evan E. Schneider, Eve C. Ostriker

Supernova-driven galactic winds are multiphase streams of gas that are often observed flowing at a range of velocities out of star-forming regions in galaxies. In this study, we use high resolution 3D simulations of multiphase galactic winds modeled with the hydrodynamics code Cholla to investigate the connection between numerical studies and observations. U

Jake D. Turner, Andrew Ridden-Harper, Ray Jayawardhana

Theory suggests that the orbits of some close-in giant planets should decay due to tidal interactions with their host stars. To date, WASP-12b is the only hot Jupiter reported to have a decaying orbit, at a rate of 29$\pm$2 msec year$^{-1}$. We analyzed data from NASA&#39;s Transiting Exoplanet Survey Satellite (TESS) to verify that WASP-12b&#39;s orbit is i

Dave Zhenyu Chen, Ali Gholami, Matthias Nießner, Angel X. Chang

We introduce the task of dense captioning in 3D scans from commodity RGB-D sensors. As input, we assume a point cloud of a 3D scene; the expected output is the bounding boxes along with the descriptions for the underlying objects. To address the 3D object detection and description problems, we propose Scan2Cap, an end-to-end trained method, to detect objects

Ren Zhang, Yangqian Yan, Qi Zhou

By engineering laser-atom interactions, both Hall ribbons and Hall cylinders as fundamental theoretical tools in condensed matter physics have recently been synthesized in laboratories. Here, we show that turning a synthetic Hall ribbon into a synthetic Hall cylinder could naturally lead to localization. Unlike a Hall ribbon, a Hall cylinder hosts an intrins

ChangHoon Hahn, Francisco Villaescusa-Navarro

Massive neutrinos suppress the growth of structure on small scales and leave an imprint on large-scale structure that can be measured to constrain their total mass, $M_ν$. With standard analyses of two-point clustering statistics, $M_ν$ constraints are severely limited by parameter degeneracies. Hahn et al.(2020) demonstrated that the bispectrum, the next hi

Chibuzor C. Nnanatu, Murray S. A. Thompson, Michael A. Spence, Elena Couce

Many wild species affected by human activities require multiple surveys with differing designs to capture behavioural response to wide ranging habitat conditions and map and quantify them. While data from for example intersecting but disparate fish surveys using different gear, are widely available, differences in design and methodology often limit their int

M. Sharif, Arfa Waseem

This paper discusses the configuration of gravitational vacuum star or gravastar with the impact of geometry and matter coupling present in $f(R,T)$ gravity. The gravastar is also conceptualized as a substitute for a black hole which is illustrated by three geometries known as (1) the interior geometry, (2) the intermediate thin-shell and (3) the exterior ge

Justin Kane Gunn, Hadi Akbarzadeh Khorshidi, Uwe Aickelin

This paper primarily presents two methods of ranking aggregated fuzzy numbers from intervals using the Interval Agreement Approach (IAA). The two proposed ranking methods within this study contain the combination and application of previously proposed similarity measures, along with attributes novel to that of aggregated fuzzy numbers from interval-valued da

Brian Courtehoute, Detlef Plump

When using graph transformation rules to implement graph algorithms, a challenge is to match the efficiency of programs in conventional languages. To help overcome that challenge, the graph programming language GP 2 features rooted rules which, under mild conditions, can match in constant time on bounded degree graphs. In this paper, we present an efficient

Andrea Corradini, Maryam Ghaffari Saadat, Reiko Heckel

In modelling complex systems with graph grammars (GGs), it is convenient to restrict the application of rules using attribute constraints and negative application conditions (NACs). However, having both attributes and NACs in GGs renders the behavioural analysis (e.g. unfolding) of such systems more complicated. We address this issue by an approach to encode

Bao Wang, Qiang Ye

Momentum plays a crucial role in stochastic gradient-based optimization algorithms for accelerating or improving training deep neural networks (DNNs). In deep learning practice, the momentum is usually weighted by a well-calibrated constant. However, tuning hyperparameters for momentum can be a significant computational burden. In this paper, we propose a no

Shahnawaz Ahmed, Carlos Sánchez Muñoz, Franco Nori, Anton Frisk Kockum

We apply deep-neural-network-based techniques to quantum state classification and reconstruction. We demonstrate high classification accuracies and reconstruction fidelities, even in the presence of noise and with little data. Using optical quantum states as examples, we first demonstrate how convolutional neural networks (CNNs) can successfully classify sev

Son T. Nguyen, Matthias R. Schindler, Roxanne P. Springer, Jared Vanasse

We extend from operators with one derivative to operators with three derivatives the analysis of two-body hadronic parity violation in a combined pionless effective field theory (EFT$_{π\!/}$) and large-$N_c$ expansion, where $N_c$ is the number of colors in quantum chromodynamics (QCD). In elastic scattering, these operators contribute to $S$-$P$ and $P$-$D

Tapomayukh Bhattacharjee, Henry M. Clever, Joshua Wade, Charles C. Kemp

Humans and robots can recognize materials with distinct thermal effusivities by making physical contact and observing temperatures during heat transfer. This works well with room temperature materials and humans and robots at human body temperatures. Past research has shown that cooling or heating a material can result in temperatures that are similar to con

Md Sirajus Salekin, Ghada Zamzmi, Dmitry Goldgof, Rangachar Kasturi

The current practice for assessing neonatal postoperative pain relies on bedside caregivers. This practice is subjective, inconsistent, slow, and discontinuous. To develop a reliable medical interpretation, several automated approaches have been proposed to enhance the current practice. These approaches are unimodal and focus mainly on assessing neonatal pro

Panayiotis Moutis, Omid Alizadeh-Mousavi

Distribution system and market operators will need or be required to monitor closely distribution systems, due to the presence of multiple actors, such as generating and storage units, as also active loads. The reason for this is the effect of these latter actors to system operation as also to ensure they follow their commitments in the deregulated market fr

William J. Miller, Jason W. Barnes, Shannon M. MacKenzie

Given a light source, a spherical reflector, and an observer, where on the surface of the sphere will the light be directly reflected to the observer, i.e. where is the the specular point? This is known as the Alhazen-Ptolemy problem, and finding this specular point for spherical reflectors is useful in applications ranging from computer rendering to atmosph

Marcos A. Capistrán, Antonio Capella, J. Andrés Christen

The effective reproduction number $R_t$ measures an infectious disease&#39;s transmissibility as the number of secondary infections in one reproduction time in a population having both susceptible and non-susceptible hosts. Current approaches do not quantify the uncertainty correctly in estimating $R_t$, as expected by the observed variability in contagion p

Shir Gur, Ameen Ali, Lior Wolf

Neural network visualization techniques mark image locations by their relevancy to the network&#39;s classification. Existing methods are effective in highlighting the regions that affect the resulting classification the most. However, as we show, these methods are limited in their ability to identify the support for alternative classifications, an effect we

Pengsheng Wen, Jeremy W. Holt

We examine the properties of the isospin-asymmetry expansion of the nuclear equation of state from chiral two- and three-body forces. We focus on extracting the high-order symmetry energy coefficients that consist of both normal terms (occurring with even powers of the isospin asymmetry) as well as terms involving the logarithm of the isospin asymmetry that

Mehdi Noroozi

This paper introduces a novel and fully unsupervised framework for conditional GAN training in which labels are automatically obtained from data. We incorporate a clustering network into the standard conditional GAN framework that plays against the discriminator. With the generator, it aims to find a shared structured mapping for associating pseudo-labels wi

Ümit Akıncı, Yusuf Yüksel

The isothermal magnetic entropy change has been obtained for the bilayer system that consists of $S_u$ and $S_l$ valued spins in each layer. The relation between the IMEC and the spin value as well as the value of exchange interaction between two layers have been obtained. Recently experimentally given double peaks behavior for manganite bilayers has been de

Dokhyam Hoshen

This paper introduces MakeupBag, a novel method for automatic makeup style transfer. Our proposed technique can transfer a new makeup style from a reference face image to another previously unseen facial photograph. We solve makeup disentanglement and facial makeup application as separable objectives, in contrast to other current deep methods that entangle t

Víctor Hernández-Santamaría, Pedro González Casanova

In this paper, we prove a Carleman estimate for fully-discrete approximations of parabolic operators in which the discrete parameters $h$ and $\triangle t$ are connected to the large Carleman parameter. We use this estimate to obtain relaxed observability inequalities which yield, by duality, controllability results for fully-discrete linear and semilinear p

Stephanie C. Ross, Johanna L. Mathieu

When providing bulk power system services, a third-party aggregator could inadvertently cause operational issues at the distribution level. We propose a coordination architecture in which an aggregator and distribution operator coordinate to avoid distribution network constraint violations, while preserving private information. The aggregator controls thermo

Siddhant Doshi, Sundeep Prabhakar Chepuri

The 2019 novel coronavirus (SARS-CoV-2) pandemic has resulted in more than a million deaths, high morbidities, and economic distress worldwide. There is an urgent need to identify medications that would treat and prevent novel diseases like the 2019 coronavirus disease (COVID-19). Drug repurposing is a promising strategy to discover new medical indications o

Matt Hohertz

In his 2006 paper, Jin proves that Kalantari&#39;s bounds on polynomial zeros, indexed by $m \leq 2$ and called $L_m$ and $U_m$ respectively, become sharp as $m\rightarrow\infty$. That is, given a degree $n$ polynomial $p(z)$ not vanishing at the origin and an error tolerance $ε> 0$, Jin proves that there exists an $m$ such that $\frac{L_m}{ρ_{min}} > 1-ε$,

Panagiotis Anagnostou, Petros T. Barmbas, Aristidis G. Vrahatis, Sotiris K. Tasoulis

We are in the era where the Big Data analytics has changed the way of interpreting the various biomedical phenomena, and as the generated data increase, the need for new machine learning methods to handle this evolution grows. An indicative example is the single-cell RNA-seq (scRNA-seq), an emerging DNA sequencing technology with promising capabilities but s

Hesam Hamledari, Martin Fischer

Supply chain integration remains an elusive goal for the construction and engineering industry. The high degree of fragmentation and the reliance on third-party financial institutions has pushed the physical and financial supply chains apart. The paper demonstrates how blockchain-based crypto assets (crypto currencies and crypto tokens) can address this limi

Wen Xiao, Patrick Huber, Giuseppe Carenini

The multi-head self-attention of popular transformer models is widely used within Natural Language Processing (NLP), including for the task of extractive summarization. With the goal of analyzing and pruning the parameter-heavy self-attention mechanism, there are multiple approaches proposing more parameter-light self-attention alternatives. In this paper, w

H. Batelaan, Eric Jones, Wayne Cheng-Wei Huang, Roger Bach

We provide support for the claim that momentum is conserved for individual events in the electron double slit experiment. The natural consequence is that a physical mechanism is responsible for this momentum exchange, but that even if the fundamental mechanism is known for electron crystal diffraction and the Kapitza-Dirac effect, it is unknown for electron

Sinem Güler, Bülent Ünal

The purpose of this article is to study generalized quasi Yamabe gradient solitons on warped product manifolds. First, we obtain some necessary and sufficient conditions for the existence of generalized quasi Yamabe gradient solitons equipped with the warped product structure. Then we study three important applications in the Lorentzian and the neutral setti