September 2020 arXiv papers — page 10

Lizeth Carolina Riascos-Álvarez, Merve Bodur, Dionne M. Aleman

Kidney paired donation programs allow patients registered with an incompatible donor to receive a suitable kidney from another donor, as long as the latter's co-registered patient, if any, also receives a kidney from a different donor. The kidney exchange problem (KEP) aims to find an optimal collection of kidney exchanges taking the form of cycles and c

Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao

Adversarial perturbations are critical for certifying the robustness of deep learning models. A universal adversarial perturbation (UAP) can simultaneously attack multiple images, and thus offers a more unified threat model, obviating an image-wise attack algorithm. However, the existing UAP generator is underdeveloped when images are drawn from different im

Udayan B. Darji, Benito Pires

The notions of chaos and frequent hypercyclicity enjoy an intimate relationship in linear dynamics. Indeed, after a series of partial results, it was shown by Bayart and Rusza in 2015 that for backward weighted shifts on $\ell_p(\mathbb{Z})$, the notions chaos and frequent hypercyclicity coincide. It is with some effort that one shows that these two notions

Daisuke Suyama, Masahiko Yoshinaga

The modules of logarithmic derivations for the (extended) Catalan and Shi arrangements associated with root systems are known to be free. However, except for a few cases, explicit bases for such modules are not known. In this paper, we construct explicit bases for type $A$ root systems. Our construction is based on Bandlow-Musiker's integral formula for

Dustin Combs, Gordon Jones, William Anderson, Frank Calaprice

High precision measurements of isospin $T=1/2$ decays in the neutron and nuclei provide strong model-independent constraints on extensions to the standard model of particle physics. A measurement of the $β$-asymmetry in $^{19}$Ne decay between the initial nuclear spin and the direction of the emitted positron is presented which establishes this decay as the

Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte

We introduce Latent Meaning Cells, a deep latent variable model which learns contextualized representations of words by combining local lexical context and metadata. Metadata can refer to granular context, such as section type, or to more global context, such as unique document ids. Reliance on metadata for contextualized representation learning is apropos i

Brian Lester

Two competing file formats have become the de facto standards for distributing pre-trained word embeddings. Both are named after the most popular pre-trained embeddings that are distributed in that format. The GloVe format is an entirely text based format that suffers from huge file sizes and slow reads, and the word2vec format is a smaller binary format tha

Mengyuan Lee, Seyyedali Hosseinalipour, Christopher G. Brinton, Guanding Yu

The combinatorial auction (CA) is an efficient mechanism for resource allocation in different fields, including cloud computing. It can obtain high economic efficiency and user flexibility by allowing bidders to submit bids for combinations of different items instead of only for individual items. However, the problem of allocating items among the bidders to

Yuteng Zhu, Graham D. Finlayson

In this paper, we present the detailed mathematical derivation of the gradient and Hessian matrix for the Vora-Value based colorimetric filter optimization. We make a full recapitulation of the steps involved in differentiating the objective function and reveal the positive-definite Hessian matrix when a positive regularizer is applied. This paper serves as

Hao Guo, Varghese Mathai

Let $G$ be a linear Lie group acting properly and isometrically on a $G$-spin$^c$ manifold $M$ with compact quotient. We show that Poincaré duality holds between $G$-equivariant $K$-theory of $M$, defined using finite-dimensional $G$-vector bundles, and $G$-equivariant $K$-homology of $M$, defined through the geometric model of Baum and Douglas.

Jiapeng Zhao, Jianming Dai, Boris Braverman, Xi-Cheng Zhang

In contrast with imaging using position-resolving cameras, single-pixel imaging uses a bucket detector along with spatially structured illumination for image recovery. This emerging imaging technique is a promising candidate for a broad range of applications due to high signal-to-noise ratio (SNR) and sensitivity, and applicability in a wide range of frequen

Jianhao Jiao, Peng Yun, Lei Tai, Ming Liu

Extrinsic perturbation always exists in multiple sensors. In this paper, we focus on the extrinsic uncertainty in multi-LiDAR systems for 3D object detection. We first analyze the influence of extrinsic perturbation on geometric tasks with two basic examples. To minimize the detrimental effect of extrinsic perturbation, we propagate an uncertainty prior on e

Philipp Sadler

The internal workings of modern deep learning models stay often unclear to an external observer, although spatial attention mechanisms are involved. The idea of this work is to translate these spatial attentions into natural language to provide a simpler access to the model's function. Thus, I took a neural image captioning model and measured the reactio

Shengdong Zhang, Shihui You, Longfei Chen, Xiaofei Liu

The relationship between the macroscopic response of the slope and the macrostructure of the force chain network under the action of the metal plate was studied by the particle discrete element method and the persistent homology. The particle accumulation model was used to simulate the instability process of slope under the continuous downward action of meta

Bhavin Joshi, Tapan Pathak, Vatsal Patel, Sarth Kanani

The design of products and services such as a Smart doorbell, demonstrating video analytics software/algorithm functionality, is expected to address a new kind of requirements such as designing a scalable solution while considering the trade-off between cost and accuracy; a flexible architecture to deploy new AI-based models or update existing models, as use

Osama Shahid, Mohammad Nasajpour, Seyedamin Pouriyeh, Reza M. Parizi

COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards finding a cur

Maarten Bieshaar, Jens Schreiber, Stephan Vogt, André Gensler

In this article, we present a novel approach to multivariate probabilistic forecasting. Our approach is based on an extension of single-output quantile regression (QR) to multivariate-targets, called quantile surfaces (QS). QS uses a simple yet compelling idea of indexing observations of a probabilistic forecast through direction and vector length to estimat

L. Campanelli

According to the Blackett conjecture, any neutral rotating body acquires a magnetic moment proportional to its angular momentum. Using the data on the dipolar magnetic field of Mars, we put a stringent upper limit on the value of the Blackett's constant, the dimensionless constant that relates the magnetic moment to the angular momentum. As a consequence

Aliaksandr V. Yakutovich, Kristjan Eimre, Ole Schütt, Leopold Talirz

Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited experience in (and time for) user interface design, which can make research software difficult to install and use for novices.

Radosław K. Wojciechowski

The goal of this article is to survey various results concerning stochastic completeness of graphs. In particular, we present a variety of formulations of stochastic completeness and discuss how a discrepancy between uniqueness class and volume growth criteria in the continuous and discrete settings was ultimately resolved via the use of intrinsic metrics. A

Maaike Burghoorn, Maaike H. T. de Boer, Stephan Raaijmakers

Transformer models have shown impressive performance on a variety of NLP tasks. Off-the-shelf, pre-trained models can be fine-tuned for specific NLP classification tasks, reducing the need for large amounts of additional training data. However, little research has addressed how much data is required to accurately fine-tune such pre-trained transformer models

Sourav Mukherjee, Tim Oates, Vince DiMascio, Huguens Jean

In this paper, we consider the problem of organizing supporting documents vital to U.S. work visa petitions, as well as responding to Requests For Evidence (RFE) issued by the U.S.~Citizenship and Immigration Services (USCIS). Typically, both processes require a significant amount of repetitive manual effort. To reduce the burden of mechanical work, we apply

Kellen Gillespie, Ioannis C. Konstantakopoulos, Xingzhi Guo, Vishal Thanvantri Vasudevan

User interactions with personal assistants like Alexa, Google Home and Siri are typically initiated by a wake term or wakeword. Several personal assistants feature "follow-up" modes that allow users to make additional interactions without the need of a wakeword. For the system to only respond when appropriate, and to ignore speech not intended for it

Xing Wang, Yijun Wang, Bin Weng, Aleksandr Vinel

We have proposed to develop a global hybrid deep learning framework to predict the daily prices in the stock market. With representation learning, we derived an embedding called Stock2Vec, which gives us insight for the relationship among different stocks, while the temporal convolutional layers are used for automatically capturing effective temporal pattern

Suresh Ramasamy, Ross L. Hatton

In this paper, we identify optimal swimming strategies for drag-dominated swimmers with a passive elastic joint. We use resistive force theory (RFT) to obtain the dynamics of the system. We then use frequency domain analysis to relate the motion of the passive joint to the motion of the actuated joint. We couple this analysis with elements of the geometric f

Dong Quan Ngoc Nguyen, Lin Xing

In many real world datasets arising from social networks, there are hidden higher order relations among data points which cannot be captured using graph modeling. It is natural to use a more general notion of hypergraphs to model such social networks. In this paper, we introduce a new local geometry of hyperdges in hypergraphs which allows to capture higher

Sofiane Bourouaine, Jean C. Perez, Kristopher C. Klein, Christopher H. K. Chen

We use \emph{Parker Solar Probe} (\emph{PSP}) in-situ measurements to analyze the characteristics of solar wind turbulence during the first solar encounter covering radial distances between $35.7R_\odot$ and $41.7R_\odot$. In our analysis we isolate so-called switchback (SB) intervals (folded magnetic field lines) from non-switchback (NSB) intervals, which m

Nabil Abid, Giovanni Chillemi, Ahmed Rebai

Since the first reports of a coronavirus (CoV) disease 2019 (COVID-19) caused by severe acute respiratory syndrome virus (SARS-CoV-2) in Wuhan, Hubei province, China, scientists are working around the clock to find sound answers to the issue of its origin. While the number of scientific articles on SARS-CoV-2 is increasing, there are still many gaps as to it

Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin

Hypergraph data appear and are hidden in many places in the modern age. They are data structure that can be used to model many real data examples since their structures contain information about higher order relations among data points. One of the main contributions of our paper is to introduce a new topological structure to hypergraph data which bears a res

Shengdong Zhang, Shihui You, Longfei Chen, Xiaofei Liu

Using software UDEC to simulate the instability failure process of slope under seismic load, studing the dynamic response of slope failure, obtaining the deformation characteristics and displacement cloud map of slope, then analyzing the instability state of slope by using the theory of persistent homology, generates bar code map and extracts the topological

Shengdong Zhang, Shihui You, Longfei Chen, Xiaofei Liu

The damage characteristics of a shallow buried tunnel under multiple explosive loads is an important research issue in the design and evaluation of protective engineering. It is of great significance to develop a method for early warning of the safety of the shallow buried features. The discrete element method is used to establish a mechanical model of the s

Shengdong Zhang, Shihui You, Longfei Chen, Xiaofei Liu

The particle discrete element simulation of the instability and failure process of the granular slope accumulator model when the metal plate continues downward is obtained, and the two-dimensional total velocity vector of soil particle velocity and slope slip during the instability and failure of the slope accumulator are obtained. Macro-response processes s

Paul Scherer, Maja Trȩbacz, Nikola Simidjievski, Zohreh Shams

We propose a method for gene expression based analysis of cancer phenotypes incorporating network biology knowledge through unsupervised construction of computational graphs. The structural construction of the computational graphs is driven by the use of topological clustering algorithms on protein-protein networks which incorporate inductive biases stemming

Lingjing Wang, Xiang Li, Yi Fang

Point cloud registration is the process of aligning a pair of point sets via searching for a geometric transformation. Unlike classical optimization-based methods, recent learning-based methods leverage the power of deep learning for registering a pair of point sets. In this paper, we propose to develop a novel model that organically integrates the optimizat

Colin Littlefield, Peter Garnavich

AE Aqr objects are a class of cataclysmic variable stars in which the rapidly rotating magnetosphere of the white dwarf (WD) primary centrifugally expels most infalling gas before it can accrete onto the WD. The expulsion of the accretion flow via this "magnetic propeller" extracts angular momentum from the WD and produces large-amplitude, aperiodic

Matteo Ronchetti

This work presents TorchRadon -- an open source CUDA library which contains a set of differentiable routines for solving computed tomography (CT) reconstruction problems. The library is designed to help researchers working on CT problems to combine deep learning and model-based approaches. The package is developed as a PyTorch extension and can be seamlessly

S. I. Kruglov

The source of the universe inflation is electromagnetic fields obeying rational nonlinear electrodynamics proposed earlier. Within this model the singularities of the electric field at the center of charges, the Ricci scalar, the Ricci tensor squared and the Kretschmann scalar are absent. We consider the universe which is filled by stochastic magnetic fields

Xiaorong Hu, Chenguang Zhao, Gang Wang

Today's intelligent traffic light control system is based on the current road traffic conditions for traffic regulation. However, these approaches cannot exploit the future traffic information in advance. In this paper, we propose GPlight, a deep reinforcement learning (DRL) algorithm integrated with graph neural network (GNN) , to relieve the traffic co

Lance Eliot

Legal Judgment Prediction (LJP) is a longstanding and open topic in the theory and practice-of-law. Predicting the nature and outcomes of judicial matters is abundantly warranted, keenly sought, and vigorously pursued by those within the legal industry and also by society as a whole. The tenuous act of generating judicially laden predictions has been limited

Bangzheng Sun, Marina Orio, Andrej Dobrotka, Gerardo Juan Manuel Luna

We present X-ray observations of novae V2491 Cyg and KT Eri about 9 years post-outburst, of the dwarf nova and post-nova candidate EY Cyg, and of a VY Scl variable. The first three objects were observed with XMM-Newton, KT Eri also with the Chandra ACIS-S camera, V794 Aql with the Chandra ACIS-S camera and High Energy Transmission Gratings. The two recent no

S. Smerechynskyi, M. Tsizh, B. Novosyadlyj

We study the density distribution of the minimally-coupled scalar field dark energy inside a neutron star. The dark energy is considered in the hydrodynamical representation as a perfect fluid with three parameters (background density, equation of state, and effective sound speed). The neutron star matter is modeled with three unified equations of state, dev

Orestis Zachariadis, Nitin Satpute, Juan Gómez-Luna, Joaquín Olivares

Sparse general matrix-matrix multiplication (spGEMM) is an essential component in many scientific and data analytics applications. However, the sparsity pattern of the input matrices and the interaction of their patterns make spGEMM challenging. Modern GPUs include Tensor Core Units (TCUs), which specialize in dense matrix multiplication. Our aim is to re-pu

Rebecca Briffa, Salvatore Capozziello, Jackson Levi Said, Jurgen Mifsud

We apply Gaussian processes (GP) in order to impose constraints on teleparallel gravity and its $f(T)$ extensions. We use available $H(z)$ observations from (i) cosmic chronometers data (CC); (ii) Supernova Type Ia (SN) data from the compressed Pantheon release together with the CANDELS and CLASH Multi-Cycle Treasury programs; and (iii) baryonic acoustic osc

Fulvio Melia

The recent measurement of a cutoff k_min in the fluctuation power spectrum P(k) of the cosmic microwave background may vitiate the possibility that slow-roll inflation can simultaneously solve the horizon problem and account for the formation of structure via the growth of quantum fluctuations in the inflaton field. Instead, we show that k_min may be interpr

Van Duong Dinh

We consider the cubic nonlinear fourth-order Schrödinger equation \[ i\partial_t u - Δ^2 u + μΔu = \pm |u|^2 u, \quad μ\geq 0 \] on $\mathbb{R}^N, N \geq 5$ with random initial data. We prove almost sure local well-posedness below the scaling critical regularity. We also prove probabilistic small data global well-posedness and scattering. Finally, we prove t

Alexander Barabash

All existing positive results on two-neutrino double beta decay and two-neutrino double electron capture in different nuclei have been analyzed. Weighted average and recommended half-life values for $^{48}$Ca, $^{76}$Ge, $^{82}$Se, $^{96}$Zr, $^{100}$Mo, $^{100}$Mo - $^{100}$Ru ($0^+_1$), $^{116}$Cd, $^{128}$Te, $^{130}$Te, $^{136}$Xe, $^{150}$Nd, $^{150}$Nd

Jinsheng Chen, Giuseppe Greco, Alessandra Palmigiano, Apostolos Tzimoulis

We introduce proper display calculi for basic monotonic modal logic, the conditional logic CK and a number of their axiomatic extensions. These calculi are sound, complete, conservative and enjoy cut elimination and subformula property. Our proposal applies the multi-type methodology in the design of proper display calculi, starting from a semantic analysis

B. P. Duggal, I. H. Kim

Given Hilbert space operators $T, S\in\B$, let $\triangle$ and $δ\in B(\B)$ denote the elementary operators $\triangle_{T,S}(X)=(L_TR_S-I)(X)=TXS-X$ and $δ_{T,S}(X)=(L_T-R_S)(X)=TX-XS$. Let $d=\triangle$ or $δ$. Assuming $T$ commutes with $S^*$, and choosing $X$ to be the positive operator $S^{*n}S^n$ for some positive integer $n$, this paper exploits proper

Udi Boker, Denis Kuperberg, Karoliina Lehtinen, Michał Skrzypczak

We study alternating parity good-for-games (GFG) automata, i.e., alternating parity automata where both conjunctive and disjunctive choices can be resolved in an online manner, without knowledge of the suffix of the input word still to be read. We show that they can be exponentially more succinct than both their nondeterministic and universal counterparts. F

Camille Coti, David Monniaux, Hang Yu

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications.Here we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems.This type of parallel applications is challenging, because several tasks mightbe computing the same region. In this paper, we are p

Rabiul Hasan Kabir, Kooktae Lee

An Optimal Transport (OT)-based decentralized collaborative multi-robot exploration strategy is proposed in this paper. This method is to achieve an efficient exploration with a predefined priority in the given domain. In this context, the efficiency indicates how a team of robots (agents) cover the domain reflecting the corresponding priority map (or degree

Huaishao Luo, Yu Shi, Ming Gong, Linjun Shou

Span extraction is an essential problem in machine reading comprehension. Most of the existing algorithms predict the start and end positions of an answer span in the given corresponding context by generating two probability vectors. In this paper, we propose a novel approach that extends the probability vector to a probability matrix. Such a matrix can cove

R. Ferreira, F. N. Lima, A. S. Ribeiro

We construct the one-dimensional analogous of von-Neumann Wigner potential to the relativistic Klein-Gordon operator, in which is defined taking asymptotic mathematical rules in order to obtain existence conditions of eigenvalues embedded in the continuous spectrum. Using our constructed potential, we provide an explicit and analytical example of the Klein-G

Zheng Gong, Ming Li, Xianwen Liu, Yuntao Xu

Microcavity solitons enable miniaturized coherent frequency comb sources. However, the formation of microcavity solitons can be disrupted by stimulated Raman scattering (SRS), particularly in the emerging crystalline microcomb materials with high Raman gain. Here, we propose and implement dissipation control---tailoring the energy dissipation of selected cav

Andean E. Medjedovic

In this paper we look at Grothendieck's work on classifying holomorphic bundles over the complex projective line. The paper is divided into $4$ parts. The first and second part we build up the necessary background to talk about vector bundles, sheaves, cohomology, etc. The main result of the $3^{rd}$ chapter is the classification of holomorphic vector bu

Thomas Choi, Peng Luo, Akshay Ramesh, Andreas F. Molisch

With the growing interest in cell-free massive multiple-input multiple-output (MIMO) systems, the benefits of single-antenna access points (APs) versus multi-antenna APs must be analyzed in order to optimize deployment. In this paper, we compare various antenna system topologies based on achievable downlink spectral efficiency, using both measured and synthe

Abhishek Sharma, Maks Ovsjanikov

We propose a totally functional view of geometric matrix completion problem. Differently from existing work, we propose a novel regularization inspired from the functional map literature that is more interpretable and theoretically sound. On synthetic tasks with strong underlying geometric structure, our framework outperforms state of the art by a huge margi

S. C. Burd, R. Srinivas, H. M. Knaack, W. Ge

Strong and precisely-controlled interactions between quantum objects are essential for quantum information processing, simulation, and sensing, and for the formation of exotic quantum matter. A well-established paradigm for coupling otherwise weakly-interacting quantum objects is to use auxiliary bosonic quantum excitations to mediate the interactions. Impor

Charles Daly

A closed affine manifold is a closed manifold with coordinate patches into affine space whose transition maps are restrictions of affine automorphisms. Such a structure gives rise to a local diffeomorphism from the universal cover of the manifold to affine space that is equivariant with respect to a homomorphism from the fundamental group to the group of aff

Joaquin Vieira, James Aguirre, C. Matt Bradford, Jeffrey Filippini

Understanding the formation and evolution of galaxies over cosmic time is one of the foremost goals of astrophysics and cosmology today. The cosmic star formation rate has undergone a dramatic evolution over the course of the last 14 billion years, and dust obscured star forming galaxies (DSFGs) are a crucial component of this evolution. A variety of importa

Guangmo Tong

Given a combinatorial optimization problem taking an input, can we learn a strategy to solve it from the examples of input-solution pairs without knowing its objective function? In this paper, we consider such a setting and study the misinformation prevention problem. Given the examples of attacker-protector pairs, our goal is to learn a strategy to compute

Sualeh Asif, Michael Coulombe, Erik D. Demaine, Martin L. Demaine

We prove that the classic falling-block video game Tetris (both survival and board clearing) remains NP-complete even when restricted to 8 columns, or to 4 rows, settling open problems posed over 15 years ago [BDH+04]. Our reduction is from 3-Partition, similar to the previous reduction for unrestricted board sizes, but with a better packing of buckets. On t

Lizardo H. C. M. Nunes, E. V. L. de Mello

We have shown that the weak-coupling limit superconductors are well described by $ q \sim 1 $, where $ q $ is a real parameter which characterizes the degree of nonextensivity of Tsallis' entropy. Nevertheless, small deviations with respect to q=1 provide better agreement when compared with experimental results. We have also shown that the generalized BC

Ha Dao, Kensuke Fukuda

Various in-browser privacy protection techniques have been designed to protect end-users from third-party tracking. In an arms race against these counter-measures, the tracking providers developed a new technique called CNAME cloaking based tracking to avoid issues with browsers that block third-party cookies and requests. To detect this tracking technique,

R. El Harti, A. ElKachkouri, A. Ghanmi

The so-called weighted solid Cauchy transform, from inside the unit disc into the complement of its closure, is considered and their basic properties such as boundedness is studied for appropriate probability measures. The action the disc polynomials is explicitly computed and used to describe the range of its restriction on the weighted true poly-Bergman sp

Michael J. Kurtz, Alberto Accomazzi, Edwin A. Henneken

In this whitepaper we advocate that the Planetary Science (PS) community build a discipline-specific digital library, in collaboration with the existing astronomy digital library, ADS. We suggest that the PS data archives increase their level of curation to allow for direct linking between the archival data and the derived journal articles. And we suggest th

Sergey Goncharov, Renato Neves, José Proença

Hybrid programs combine digital control with differential equations, and naturally appear in a wide range of application domains, from biology and control theory to real-time software engineering. The entanglement of discrete and continuous behaviour inherent to such programs goes beyond the established computer science foundations, producing challenges rela

C. W. Greeff

The perturbative expansion introduced by Zwanzig [R. W. Zwanzig, J. Chem. Phys. {\bf 22}, 1420 (1954)] expresses the difference in Helmholtz free energy between a system of interest and that of a reference system as series of cumulants $κ_n$ of the potential energy difference between the two systems. This expansion has attractive features as a method for obt

Joel F. Tasker, Jonathan Frazer, Giacomo Ferranti, Euan J. Allen

Photonic quantum technology can be enhanced by monolithic fabrication of both the underpinning quantum hardware and the corresponding electronics for classical readout and control. Together, this enables miniaturisation and mass-manufacture of small quantum devices---such as quantum communication nodes, quantum sensors and sources of randomness---and promise

Alexander Arbieto, Alexandre Trilles

We study iterated function systems (IFS) with compact parameter space. We show that the space of IFS with phase space $X$ is the hyperspace of the space of self continuous maps of $X$. With this result we obtain that the Hausdorff distance is a natural metric for this space which we use to define topological stability. Then we prove, in the context of IFS, t

Vladimir Gurvich

Consider an electrical circuit $G$ each directed edge $e$ of which is a semiconductor with a monomial conductance function $y_e^* = f_e(y_e) = y_e^s / μ_e^r$ if $y_e \geq 0$ and $y_e^* = 0$ if $y_e \leq 0$. Here $e$ is a directed edge, $y_e$ is the potential difference (voltage), $y_e^*$ is the current in $e$, and $μ_e$ is the resistance of $e$; furthermore,

Sylvia J. Bintrim, Timothy C. Berkelbach

Efficient computer implementations of the GW approximation must approximate a numerically challenging frequency integral; the integral can be performed analytically, but doing so leads to an expensive implementation whose computational cost scales as $O(N^6)$ where $N$ is the size of the system. Here we introduce a new formulation of the full-frequency GW ap

Jonatas S. de Souza, Jair M. Abe, Luiz A. de Lima, Nilson A. de Souza

Rapid technological change and globalization have created new challenges when it comes to the protection and processing of personal data. In 2018, Brazil presented a new law that has the proposal to inform how personal data should be collected and treated, to guarantee the security and integrity of the data holder. The purpose of this paper is to emphasize t

Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin

A weighted directed network (WDN) is a directed graph in which each edge is associated to a unique value called weight. These networks are very suitable for modeling real-world social networks in which there is an assessment of one vertex toward other vertices. One of the main problems studied in this paper is prediction of edge weights in such networks. We

Minseon Shin

We compute the cohomological Brauer groups of twists of weighted projective spaces and weighted projective stacks.

Nan Ding, Xinjie Fan, Zhenzhong Lan, Dale Schuurmans

Models based on the Transformer architecture have achieved better accuracy than the ones based on competing architectures for a large set of tasks. A unique feature of the Transformer is its universal application of a self-attention mechanism, which allows for free information flow at arbitrary distances. Following a probabilistic view of the attention via t

Saurabh Kulshreshtha, José Luis Redondo-García, Ching-Yun Chang

Multilingual BERT (mBERT) has shown reasonable capability for zero-shot cross-lingual transfer when fine-tuned on downstream tasks. Since mBERT is not pre-trained with explicit cross-lingual supervision, transfer performance can further be improved by aligning mBERT with cross-lingual signal. Prior work proposes several approaches to align contextualised emb

Elias Nehme, Boris Ferdman, Lucien E. Weiss, Tal Naor

A long-standing challenge in multiple-particle-tracking is the accurate and precise 3D localization of individual particles at close proximity. One established approach for snapshot 3D imaging is point-spread-function (PSF) engineering, in which the PSF is modified to encode the axial information. However, engineered PSFs are challenging to localize at high

Sakina Othmani, Nasser-eddine Tatar

In this paper, stability and synchronization of a Caputo fractional BAM neural network system of high-order type and neutral delays are examined. A mixture of properties of fractional calculus, Laplace transform, and analytical techniques is used to derive Mittag-Leffler stability and synchronization for two classes of activation functions. A fractional vers

H. Xu, Y. Zhou, U. Bechstedt, J. Böker

The proton--proton elastic differential cross section at very small four momentum transfer squared has been measured at three different incident proton momenta in the range of 2.5 to 3.2 GeV/c by detecting the recoil proton at polar angles close to $90^\circ$. The measurement was performed at COSY with the KOALA detector covering the Coulomb-nuclear interfer

Xing Wang, Alexander Vinel

Existing exploration strategies in reinforcement learning (RL) often either ignore the history or feedback of search, or are complicated to implement. There is also a very limited literature showing their effectiveness over diverse domains. We propose an algorithm based on the idea of reannealing, that aims at encouraging exploration only when it is needed,

Bruno Fava, Hedibert F. Lopes

The emergence of Big Data raises the question of how to model economic relations when there is a large number of possible explanatory variables. We revisit the issue by comparing the possibility of using dense or sparse models in a Bayesian approach, allowing for variable selection and shrinkage. More specifically, we discuss the results reached by Giannone,

Jeet Yadav, Tushar Goyal

Detumbling refers to the act of dampening the angular velocity of the satellite. This operation is of paramount importance since it is virtually impossible to nominally perform any other operation without some degree of attitude control. Common methods used to detumble satellites usually involve magnetic actuation, paired with different types of sensors whic

Alexis Vasseur, Jincheng Yang

We study the second spatial derivatives of suitable weak solutions to the incompressible Navier-Stokes equations in dimension three. We show that it is locally $L ^{\frac43, q}$ for any $q > \frac43$, which improves from the current result $L ^{\frac43, \infty}$. Similar improvements in Lorentz space are also obtained for higher derivatives of the vorticity

J. Martins, L. Defaveri, D. O. Soares-Pinto, S. M. D. Queirós

We explore the role a non-Markovian memory kernel plays on information exchange and entropy production in the context of a external work protocol. The Jarzynski Equality is shown to hold for both the harmonic and the non-harmonic models. We observe the memory function acts as an information pump, recovering part of the information lost to the thermal reservo

R. J. Koch, R. Sinclair, M. T. McDonnell, R. Yu

The local structure of NaTiSi$_{2}$O$_{6}$ is examined across its Ti-dimerization orbital-assisted Peierls transition at 210 K. An atomic pair distribution function approach evidences local symmetry breaking preexisting far above the transition. The analysis unravels that on warming the dimers evolve into a short range orbital degeneracy lifted (ODL) state o

Gaganjeet Reen, Manasi Mohandas, S Venkatesan

Electronic Health Records(EHR) are gaining a lot of popularity all over the world. The current EHR systems however have their fair share of problems related to privacy and security. We have proposed a mechanism which provides a solution to most of these problems. Using a permissioned Ethereum blockchain allows the hospitals and patients across the world to b

Lucio Pancaldi, Pietro Dirix, Adele Fanelli, Diego Ghezzi

Minimally invasive medical procedures, such as endovascular catheterization, have drastically reduced procedure time and associated complications. However, many regions inside the body, such as in the brain vasculature, still remain inaccessible due to the lack of appropriate guidance technologies. Here, experimentally and through numerical simulations, we s

E. Gioan, I. P. Silva

We introduce a family of nonnegative integer vectors - primitive vectors - defining hyperplanes of the real affine cube over $C^n:=\{-1,1\}^n$ and study their properties with respect to the rectangles of the cube. As a consequence we give a short proof that, for small dimensions ($n\leq 7$), the real affine cube can be recovered from its signed rectangles an

Edward F. Redish

The key difference between math as math and math in science is that in science we blend our physical knowledge with our knowledge of math. This blending changes the way we put meaning to math and even to the way we interpret mathematical equations. Learning to think about physics with math instead of just calculating involves a number of general scientific t

Sravan Pannala, Puneet Valecha, Peyman Mohtat, Jason B. Siegel

Accurate tracking of the internal electrochemical states of lithium-ion battery during cycling enables advanced battery management systems to operate the battery safely and maintain high performance while minimizing battery degradation. To this end, techniques based on voltage measurement have shown promise for estimating the lithium surface concentration of

Dessislava H. Kochloukova

We calculate the Bieri-Neumann-Strebel-Renz invariant $Σ^1(G)$ for even Artin groups $G$ with underlying graph $Γ$ such that if there is a closed reduced path in $Γ$ with all labels bigger than 2 then the length of such path is always odd. We show that $Σ^1(G)^c$ is a rationally defined spherical polyhedron.

Alexander Scarlatos

The world of audio production and design has long been a difficult one to break into, requiring expertise and a working knowledge of the standard digital audio paradigms. This paper describes a novel interface that makes audio production and design more intuitive for novices, using sound-to-space relations that people have learned throughout daily life, such

Ara Basmajian, Nicholas G. Vlamis

It is an open problem to provide a characterization of quasiconformally homogeneous Riemann surfaces. We show that given the current literature, this problem can be broken into four open cases with respect to the topology of the underlying surface. The main result is a characterization in one of the these open cases; in particular, we prove that every quasic

Samreen Anjum, Chi Lin, Danna Gurari

Crowdsourcing is a valuable approach for tracking objects in videos in a more scalable manner than possible with domain experts. However, existing frameworks do not produce high quality results with non-expert crowdworkers, especially for scenarios where objects split. To address this shortcoming, we introduce a crowdsourcing platform called CrowdMOT, and in

Chacha Chen, Chieh-Yang Huang, Yaqi Hou, Yang Shi

The competition of extracting COVID-19 events from Twitter is to develop systems that can automatically extract related events from tweets. The built system should identify different pre-defined slots for each event, in order to answer important questions (e.g., Who is tested positive? What is the age of the person? Where is he/she?). To tackle these challen

Nicholas Halliwell, Freddy Lecue

Convolutional neural networks (CNNs) are commonly used for image classification. Saliency methods are examples of approaches that can be used to interpret CNNs post hoc, identifying the most relevant pixels for a prediction following the gradients flow. Even though CNNs can correctly classify images, the underlying saliency maps could be erroneous in many ca

Abeba Birhane, Olivia Guest

This article sets out our perspective on how to begin the journey of decolonising computational fields, such as data and cognitive sciences. We see this struggle as requiring two basic steps: a) realisation that the present-day system has inherited, and still enacts, hostile, conservative, and oppressive behaviours and principles towards women of colour (WoC

Debolina Misra, Satyesh K. Yadav

Using first-principles modelling based on density functional theory we show that oxides implanted with transition metal can act as support for Au single atoms, which are stable against agglomeration. In our previous work we have shown that implanted transition metal, doped in BaO is stable as interstitial in various charge states by transferring the excess c

Václav Mácha, Emil Wiedemann

We construct two particular solutions of the full Euler system which emanate from the same initial data. Our aim is to show that the convex combination of these two solutions form a measure-valued solution which may not be approximated by a sequence of weak solutions. As a result, the weak* closure of the set of all weak solutions, considered as parametrized