December 2020 arXiv papers — page 128

Alexander Okhotin, Victor L. Selivanov

Automata operating on strings of nested brackets, known as input-driven pushdown automata, and as visibly pushdown automata, have been studied since the 1980s. They were extended to the case of infinite strings by Alur and Madhusudan ("Visibly pushdown languages", STOC 2004). This paper investigates the properties of these automata under the assumpti

Ayiaz Kaderali, Theodore Stanoev

We consider an anisotropic inhomogeneous model to simulate measured vertical-seismic-profile traveltimes. In this model, we assume that velocity increases linearly with depth and anisotropy is the result of elliptical velocity dependence. Using a series of sources in a line to a single receiver, we minimize the least-squares residual between measured and mod

M. Muccino, L. Izzo, O. Luongo, K. Boshkayev

Observations of gamma-ray bursts up to $z\sim 9$ are best suited to study the possible evolution of the Universe equation of state at intermediate redshifts. We apply the Combo-relation to a sample of 174 gamma ray bursts to investigate possible evidence of evolving dark energy parameter $w(z)$. We first build a gamma ray burst Hubble's diagram and then

Edmondo Trentin

Albeit worryingly underrated in the recent literature on machine learning in general (and, on deep learning in particular), multivariate density estimation is a fundamental task in many applications, at least implicitly, and still an open issue. With a few exceptions, deep neural networks (DNNs) have seldom been applied to density estimation, mostly due to t

Karen Leung, Edward Schmerling, Mengxuan Zhang, Mo Chen

Action anticipation, intent prediction, and proactive behavior are all desirable characteristics for autonomous driving policies in interactive scenarios. Paramount, however, is ensuring safety on the road -- a key challenge in doing so is accounting for uncertainty in human driver actions without unduly impacting planner performance. This paper introduces a

Michal H. Kolář, Lars V. Bock, Helmut Grubmüller

The proteasome is a large biomolecular complex responsible for protein degradation. It is under intense research due to its fundamental role in cellular homeostasis, and tremendous potential for medicinal applications. Recent data from X-ray crystallography and cryo-electron microscopy have suggested that there is a large-scale structural change upon binding

Allan Sapucaia, Pedro J. de Rezende, Cid C. de Souza

The partition of a problem into smaller sub-problems satisfying certain properties is often a key ingredient in the design of divide-and-conquer algorithms. For questions related to location, the partition problem can be modeled, in geometric terms, as finding a subdivision of a planar map -- which represents, say, a geographical area -- into regions subject

L. Lindegren, S. A. Klioner, J. Hernández, A. Bombrun

Gaia Early Data Release 3 (Gaia EDR3) contains results for 1.812 billion sources in the magnitude range G = 3 to 21 based on observations collected by the European Space Agency Gaia satellite during the first 34 months of its operational phase. We describe the input data, the models, and the processing used for the astrometric content of Gaia EDR3, as well a

Silas Alben

We study the efficiency of sliding locomotion for three-link bodies in the presence of dry (Coulomb) friction. Friction coefficient space can be partitioned into several regions, each with distinct types of efficient kinematics. These include kinematics resembling lateral undulation with very anisotropic friction, small-amplitude reciprocal kinematics, very

Rajesh P. N. Rao

Brain-computer interfaces (BCIs) use decoding algorithms to control prosthetic devices based on brain signals for restoration of lost function. Computer-brain interfaces (CBIs), on the other hand, use encoding algorithms to transform external sensory signals into neural stimulation patterns for restoring sensation or providing sensory feedback for closed-loo

Akshay Joshi, Ankit Agrawal, Sushmita Nair

The artistic style of a painting is a rich descriptor that reveals both visual and deep intrinsic knowledge about how an artist uniquely portrays and expresses their creative vision. Accurate categorization of paintings across different artistic movements and styles is critical for large-scale indexing of art databases. However, the automatic extraction and

P. J. Lloreda-Jurado, E. Chicardi, A. Paul, R. Sepúlveda

Wicks are the main component of Loop Heat Pipe systems, whereby coolant liquid flow through their porous structure. They are usually formed by a primary wick to produce liquid transportation by capillary force, and a secondary wick that is continuously wetted by the liquid coolant. Traditionally, the two wicks are manufactured separately and subsequently joi

Grigory Safronov

Baikal-GVD is a cubic-kilometer scale deep-underwater neutrino detector being constructed in Lake Baikal. It is designed to detect neutrinos from $\sim$100 GeV to multi-PeV energies and beyond. Detector deployment began in Spring 2015. Since April 2020 the detector includes seven 8-string clusters carrying in total 2016 optical modules located at depths from

Samuel Marc Denton, Ansaf Salleb-Aouissi

Research in machine learning has successfully developed algorithms to build accurate classification models. However, in many real-world applications, such as healthcare, customer satisfaction, and environment protection, we want to be able to use the models to decide what actions to take. We investigate the concept of actionability in the context of Support

Amanda K. Glazer, Jacob V. Spertus, Philip B. Stark

U.S. elections rely heavily on computers such as voter registration databases, electronic pollbooks, voting machines, scanners, tabulators, and results reporting websites. These introduce digital threats to election outcomes. Risk-limiting audits (RLAs) mitigate threats to some of these systems by manually inspecting random samples of ballot cards. RLAs have

Runyu Mao, Jiangpeng He, Zeman Shao, Sri Kalyan Yarlagadda

Food recognition is one of the most important components in image-based dietary assessment. However, due to the different complexity level of food images and inter-class similarity of food categories, it is challenging for an image-based food recognition system to achieve high accuracy for a variety of publicly available datasets. In this work, we propose a

James E. Newman, Moshe Y. Vardi

The matrix permanent belongs to the complexity class #P-Complete. It is generally believed to be computationally infeasible for large problem sizes, and significant research has been done on approximation algorithms for the matrix permanent. We present an implementation and detailed runtime analysis of one such Markov Chain Monte Carlo (MCMC) based Fully Pol

Medet Nursultanov, Julie Rowlett, David Sher

We announce a new result which shows that under either Dirichlet, Neumann, or Robin boundary conditions, the corners in a planar domain are a spectral invariant of the Laplacian. For the case of polygonal domains, we show how a locality principle, in the spirit of Kac's "principle of not feeling the boundary" can be used together with calculation

Zhonghua Zheng, Joseph Ching, Jeffrey H. Curtis, Yu Yao

The aerosol mixing state significantly affects the climate and health impacts of atmospheric aerosol particles. Simplified aerosol mixing state assumptions, common in Earth System models, can introduce errors in the prediction of these aerosol impacts. The aerosol mixing state index, a metric to quantify aerosol mixing state, is a convenient measure for quan

Hannah Altmann, Sean K. Sather-Wagstaff

Gerko proves that if an artinian local ring $(R,\mathfrak{m}_R)$ possesses a sequence of strongly Tor-independent modules of length $n$, then $\mathfrak{m}_R^n\neq 0$. This generalizes readily to Cohen-Macaulay rings. We present a version of this result for non-Cohen-Macaulay rings.

Mnerh Alqahtani, Tobias Grafke

Large deviation theory and instanton calculus for stochastic systems are widely used to gain insight into the evolution and probability of rare events. At its core lies the realization that rare events are, under the right circumstances, dominated by their least unlikely realization. Their computation through a saddle-point approximation of the path integral

Gabriel Mersy, Jin Hong Kuan

Given recent advances in deep music source separation, we propose a feature representation method that combines source separation with a state-of-the-art representation learning technique that is suitably repurposed for computer audition (i.e. machine listening). We train a depthwise separable convolutional neural network on a challenging electronic dance mu

Kfir Goldberg, Stav Shapiro, Elad Richardson, Shai Avidan

The search for efficient neural network architectures has gained much focus in recent years, where modern architectures focus not only on accuracy but also on inference time and model size. Here, we present FUN, a family of novel Frequency-domain Utilization Networks. These networks utilize the inherent efficiency of the frequency-domain by working directly

Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan

Influence maximization (IM) has garnered a lot of attention in the literature owing to applications such as viral marketing and infection containment. It aims to select a small number of seed users to adopt an item such that adoption propagates to a large number of users in the network. Competitive IM focuses on the propagation of competing items in the netw

G. Cantatore, H. Fischer, W. Funk, M. Karuza

We investigate the prospects for direct detection of Dark Matter (DM) particles, such as dark photons, incident on the upper atmosphere. A recent work relates the burst-like temperature excursions in the stratosphere at heights of ~38-47 km with incident invisible streaming matter. Surprisingly, dark photons match the reasoning presented in that work provide

Roger D. Soberanis-Mukul, Nassir Navab, Shadi Albarqouni

Organ segmentation in CT volumes is an important pre-processing step in many computer assisted intervention and diagnosis methods. In recent years, convolutional neural networks have dominated the state of the art in this task. However, since this problem presents a challenging environment due to high variability in the organ's shape and similarity betwe

Damien Cabut, Marc Michard, Serge Simoens, Loic Mees

In order to better understand the hydroplaning phenomenon, local velocity measurements of water flow are performed inside the tire grooves of a real car rolling through a water puddle. Velocity fields are obtained by combining refraction Particle Image Velocimetry (r-PIV) illumination, seeding fluorescent particles and either the classical 2D2C or a 2D3C ste

Ilya Boldyrev, Sergey Gaifullin

In this paper we prove criteria for a nonnormal toric variety to be flexible, to be rigid and to be almost rigid. For rigid and almost rigid toric varieties we describe the automorphism group explicitly.

Olga Verkhoglyadova, Charles Bussy-Virat, Amir Caspi, David Jackson

Gaps in space weather observations that can be addressed with small satellites are identified. Potential improvements in solar inputs to space weather models, space radiation control, estimations of energy budget of the upper Earth's atmosphere, and satellite drag modeling are briefly discussed. Key observables, instruments and observation strategies by

Vladyslav Bohun, Alexander Iksanov, Alexander Marynych, Bohdan Rashytov

Let $(ξ_k,η_k)_{k\in\mathbb{N}}$ be independent identically distributed random vectors with arbitrarily dependent positive components. We call a (globally) perturbed random walk a random sequence $(T_k)_{k\in\mathbb{N}}$ defined by $T_k:=ξ_1+\cdots+ξ_{k-1}+η_k$ for $k\in\mathbb{N}$. Further, by an iterated perturbed random walk is meant the sequence of point

Lluís Alsedà, Salvador Borrós-Cullell

In this article we present an efficient algorithm to compute rotation intervals of circle maps of degree one. It is based on the computation of the rotation number of a monotone circle map of degree one with a constant section. The main strength of this algorithm is that it computes \emph{exactly} the rotation interval of a natural subclass of the continuous

Miguel Morata-Dolz, Diego Bueso, Maria Piles, Gustau Camps-Valls

Global warming is leading to unprecedented changes in our planet, with great societal, economical and environmental implications, especially with the growing demand of biofuels and food. Assessing the impact of climate on vegetation is of pressing need. We approached the attribution problem with a novel nonlinear Granger causal (GC) methodology and used a la

Xin Zhang, Jicheng Wang, Yee Sin Ang, Juncheng Guo

We theoretically study the efficiency limits and performance characteristics of few-layer graphene-semiconductor solar cells (FGSCs) based on a Schottky contact device structure. We model and compare the energy conversion efficiency of various configurations by explicitly considering the non-Richardson thermionic emission across few-layer graphene/semiconduc

Marcel Schmittfull, Marko Simonović, Mikhail M. Ivanov, Oliver H. E. Philcox

We develop an analytical forward model based on perturbation theory to predict the redshift-space galaxy overdensity at the field level given a realization of the initial conditions. We find that the residual noise between the model and simulated galaxy density has a power spectrum that is white on large scales, with size comparable to the shot noise. In the

Zhesen Yang

In conventional Hermitian systems with the open boundary condition, Bloch's theorem is perturbatively broken down, which means although the crystal momentum is not a good quantum number, the eigenstates are the superposition of several extended Bloch waves. In this paper, we show that Bloch's theorem can be non-perturbatively broken down in some Herm

Arnaud Beauville

A family of K3 surfaces $\mathscr{X}\rightarrow B$ has the \emph{Franchetta property} if the Chow group of 0-cycles on the generic fiber is cyclic. The generalized Franchetta conjecture proposed by O'Grady asserts that the universal family $\mathscr{X}_g\rightarrow \mathscr{F}_g$ of polarized K3 of degree $2g-2$ has the Franchetta property. While this is

Bernhelm Booss-Bavnbek, Jian Deng, Yuting Zhou, Chaofeng Zhu

We consider a continuous family of linear elliptic differential operators of arbitrary order over a smooth compact manifold with boundary. Assuming constant dimension of the spaces of inner solutions, we prove that the orthogonalized Calderón projections of the underlying family of elliptic operators form a continuous family of projections. Hence, its images

Benson Tsz Kin Leung, Pinar Yildirim

An increasing number of politicians are relying on cheaper, easier to access technologies such as online social media platforms to communicate with their constituency. These platforms present a cheap and low-barrier channel of communication to politicians, potentially intensifying political competition by allowing many to enter political races. In this study

Qiwei Li, Minzhe Zhang, Yang Xie, Guanghua Xiao

The location, timing, and abundance of gene expression (both mRNA and proteins) within a tissue define the molecular mechanisms of cell functions. Recent technology breakthroughs in spatial molecular profiling, including imaging-based technologies and sequencing-based technologies, have enabled the comprehensive molecular characterization of single cells whi

Radu Alexandru Rosu, Sven Behnke

Modern rendering libraries provide unprecedented realism, producing real-time photorealistic 3D graphics on commodity hardware. Visual fidelity, however, comes at the cost of increased complexity and difficulty of usage, with many rendering parameters requiring a deep understanding of the pipeline. We propose EasyPBR as an alternative rendering library that

Nabil Ibtehaz, S. M. Shakhawat Hossain Sourav, Md. Shamsuzzoha Bayzid, M. Sohel Rahman

Background: The inception of next generations sequencing technologies have exponentially increased the volume of biological sequence data. Protein sequences, being quoted as the `language of life', has been analyzed for a multitude of applications and inferences. Motivation: Owing to the rapid development of deep learning, in recent years there have been

Alexis Tsoukiàs

Should we be concerned by the massive use of devices and algorithms which automatically handle an increasing number of everyday activities within our societies? The paper makes a short overview of the scientific investigation around this topic, showing that the development, existence and use of such autonomous artifacts is much older than the recent interest

M. Baur, T. Jagdhuber, M. Link, M. Piles

In this study the framework of the $τ$-$ω$ model is used to derive vegetation loss coefficients and canopy penetration depths from SMAP multi-temporal retrievals of vegetation optical depth, single scattering albedo and ICESat lidar vegetation heights. The vegetation loss coefficients serve as a global indicator of how strong absorption and scattering proces

Dara Entekhabi, Alexandra Konings, Maria Piles, Narendra Das

Over land the vegetation canopy affects the microwave brightness temperature by emission, scattering and attenuation of surface soil emission. The questions addressed in this study are: 1) what is the transparency of the vegetation canopy for different biomes around the Globe at the low-frequency L-band?, 2) what is the seasonal amplitude of vegetation micro

Jie Ou, Hong Wu

In this paper, we propose efficient and effective methods for 2D human pose estimation. A new ResBlock is proposed based on depthwise separable convolution and is utilized instead of the original one in Hourglass network. It can be further enhanced by replacing the vanilla depthwise convolution with a mixed depthwise convolution. Based on it, we propose a bo

Natalia Jurga, Lawrence D. Lee

We study a natural class of invariant measures supported on the attractors of a family of nonlinear, non-conformal iterated function systems introduced by Falconer, Fraser and Lee. These are pushforward quasi-Bernoulli measures, a class which includes the well-known class of Gibbs measures for Hölder continuous potentials. We show that these measures are exa

N. Sánchez, A. González-Zamora, J. Martínez-Fernández, M. Piles

An application of the Soil Moisture Agricultural Drought Index (SMADI) at the global scale is presented. The index integrates surface soil moisture from the SMOS mission with land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS and allows for global drought monitoring at medium spatial scales (0.05 deg).. Biweekly maps

Paolo Leonetti

We show that a real sequence $x$ is convergent if and only if there exist a regular matrix $A$ and an $F_{σδ}$-ideal $\mathcal{I}$ on $\mathbf{N}$ such that the set of subsequences $y$ of $x$ for which $Ay$ is $\mathcal{I}$-convergent is of the second Baire category. This includes the cases where $\mathcal{I}$ is the ideal of asymptotic density zero sets, th

Jan David Smeddinck

Physical activity plays a major role both in prevention and in the treatment of afflictions linked to a modern sedentary lifestyle and improvements on life expectancy, for example though the application area of physiotherapy. Motion-based games for health (MGH) are being discussed in research and industry for their ability to play a supportive role in health

Sabah Sabaghy, Jeffrey Walker, Luigi Renzullo, Ruzbeh Akbar

Soil moisture impacts exchanges of water, energy and carbon fluxes between the land surface and the atmosphere. Passive microwave remote sensing at L-band can capture spatial and temporal patterns of soil moisture in the landscape. Both ESA and NASA have launched L-band radiometers, in the form of the SMOS and SMAP satellites respectively, to monitor soil mo

Jim Agler, Zinaida Lykova, N. J. Young

The symmetrized bidisc \[ G \stackrel{\rm{def}}{=}\{(z+w,zw):|z|<1,\ |w|<1\}, \] under the Carathéodory metric, is a complex Finsler space of cohomogeneity $1$ in which the geodesics, both real and complex, enjoy a rich geometry. As a Finsler manifold, $G$ does not admit a natural notion of angle, but we nevertheless show that there {\em is} a notion of orth

R Canavan, M Freer

The relationship between the deformed harmonic oscillator and the formation of molecular cluster structures, whereby valence neutrons are exchanged between cluster cores, is examined. It is found that there is a strong connection between the properties of the valence orbitals associated with deformed structures in the deformed harmonic oscillator and the mol

Mariana Verezhak, Steven Van Petegem, Angel Rodriguez-Fernandez, Pierre Godard

Strain and defects in crystalline materials are responsible for the distinct mechanical, electric and magnetic properties of a desired material, making their study an essential task in material characterization, fabrication and design. Existing techniques for the visualization of strain fields, such as transmission electron microscopy and diffraction, are de

M. Piles, D. Chaparro, D. Entekhabi, A. G. Konings

The ESA&#39;s SMOS and the NASA&#39;s SMAP missions, launched in 2009 and 2015, respectively, are the first two missions having on-board L-band microwave sensors, which are very sensitive to the water content in soils and vegetation. Focusing on the vegetation signal at L-band, we have implemented an inversion approach for SMAP that allows deriving vegetatio

Yizhou Liu, Claudia Solis-Lemus

WI Fast Stats is the first and only dedicated tool tailored to the WI Fast Plants educational objectives. WI Fast Stats is an integrated animated web page with a collection of R-developed web apps that provide Data Visualization and Data Analysis tools for WI Fast Plants data. WI Fast Stats is a user-friendly easy-to-use interface that will render Data Scien

Juan Carlos Ferrando

If $T$ is a (densely defined) self-adjoint operator acting on a complex Hilbert space $\mathcal{H}$ and $I$ stands for the identity operator, we introduce the delta function operator $λ\mapsto δ\left(λI-T\right) $ at $T$. When $T$ is a bounded operator, then $δ\left(λI-T\right) $ is an operator-valued distribution. If $T$ is unbounded, $δ\left(λI-T\right) $

Julie Rowlett, Max Blom, Henrik Nordell, Oliver Thim

The mathematics of crystalline structures connects analysis, geometry, algebra, and number theory. The planar crystallographic groups were classified in the late 19th century. One hundred years later, Bérard proved that the fundamental domains of all such groups satisfy a very special analytic property: the Dirichlet eigenfunctions for the Laplace eigenvalue

A. Vigan, M. Postnikova, A. Caillat, J. -F. Sauvage

Future high-contrast imagers on ground-based extremely large telescopes will have to deal with the segmentation of the primary mirrors. Residual phase errors coming from the phase steps at the edges of the segments will have to be minimized in order to reach the highest possible wavefront correction and thus the best contrast performance. To study these effe

Kenzo Sasaki, Diogo C. Barros, André V. G. Cavalieri, Lionel Larchevêque

The mechanisms governing the low-frequency unsteadiness in the shock wave/turbulent boundary layer interaction at Mach 2 are considered. The investigation is conducted based on the numerical database issued from large-eddy simulations covering approximately 300 cycles of the low-frequency shock fluctuations. The evaluation of the spectrum in the interaction

Olha Buchel, Anton Ninkov, Danise Cathel, Yaneer Bar-Yam

During the COVID-19 pandemic, governments have tried to keep their territories safe by isolating themselves from others, limiting non-essential travel and imposing mandatory quarantines for travelers. While large-scale quarantine has been the most successful short-term policy, it is unsustainable over long periods as it exerts enormous costs on societies. As

Jun-Zhang Wang, Xiang Liu, Takayuki Matsuki

Motivated by a recent successful dynamical explanation for the newly observed fully-charm structure $X(6900)$ in the mass spectrum of di-$J/ψ$ by LHCb [J.~Z.~Wang \textit{et al.} arXiv:2008.07430], in this work, we extend the same dynamical rescattering mechanism to predict the line shape of more potential fully-heavy structures in the invariant mass spectru

Charley Presigny, Petter Holme, Alain Barrat

In many data sets, crucial elements co-exist with non-essential ones and noise. For data represented as networks in particular, several methods have been proposed to extract a &#34;network backbone&#34;, i.e., the set of most important links. However, the question of how the resulting compressed views of the data can effectively be used has not been tackled.

Yacine Aoun

The purpose of this modest note is to provide a short proof of the sharpness of the phase transition for the Random-cluster model with $q=2$ by extending the approach developed by Duminil-Copin and Tassion for $q=1$. This in particular implies the exponential decay of the two point-correlation function in the subcritical Ising model.

Zhiyuan Lin, Zhuoran Wang, Guohui Yuan, Jean-Pierre Leburton

A novel design-friendly device called the transistor-injected dual doping quantum cascade laser (TI-D2QCL) with two different doping in each stack of a homogeneous superlattice is proposed. By adjusting the base-emitter bias Vbe of the bipolar transistor to supply electrons in the dual doping regions, charge quasi-neutrality can be achieved to generate diffe

Yuxing Zhou, Bin Li, Zhefeng Lou, Huancheng Chen

A feasible strategy to realize the Majorana fermions is searching for a simple compound with both bulk superconductivity and Dirac surface states. In this paper, we performed calculations of electronic band structure, the Fermi surface and surface states, as well as measured the resistivity, magnetization, specific heat for TlSb compound with a CsCl-type str

Changda Zhou, Zhen Mou, Rui Bao, Zhong Li

In view of wide applications of structured light fields and plasmonic vortices, we propose the concept of compound plasmonic vortex and design several structured plasmonic vortex generators. This kind of structured plasmonic vortex generators consists of multiple spiral nanoslits and they can generate two or more concentric plasmonic vortices. Different from

Taehyeon Kim, Sangmin Bae, Jin-woo Lee, Seyoung Yun

Federated learning has emerged as an innovative paradigm of collaborative machine learning. Unlike conventional machine learning, a global model is collaboratively learned while data remains distributed over a tremendous number of client devices, thus not compromising user privacy. However, several challenges still remain despite its glowing popularity; abov

Peter Zograf

An explicit closed form expression for 2-correlators of Witten&#39;s two dimensional topological gravity is derived in arbitrary genus.

Nozomi Nishizawa, Bassam Al-Qadi, Takahiro Kuchimaru

Depolarization of circularly polarized light scattered from biological tissues depends on structural changes in cell nuclei, which can provide valuable information for differentiating cancer tissues concealed in healthy tissues. In this study, we experimentally verified the possibility of cancer identification using scattering of circularly polarized light.

Zhuangbin Tan, Bobing Ye, Xuefeng Zhang

TianQin is a proposed space-based gravitational-wave observatory mission to be deployed in high circular Earth orbits. The equilateral-triangle constellation, with a nearly fixed orientation, can be distorted primarily under the lunisolar perturbations. To accommodate science payload requirements, one must optimize the orbits to stabilize the configuration i

Bo-Bing Ye, Xuefeng Zhang, Ming-Yue Zhou, Yan Wang

TianQin is a geocentric space-based gravitational-wave observatory mission consisting of three drag-free controlled satellites in an equilateral triangle with an orbital radius of $ 10^{5}$ km. The constellation faces the white-dwarf binary RX J0806.3+1527 located slightly below the ecliptic plane, and is subject to gravitational perturbations that can disto

Florian Hörsch, Zoltán Szigeti

We attempt to generalize a theorem of Nash-Williams stating that a graph has a $k$-arc-connected orientation if and only if it is $2k$-edge-connected. In a strongly connected digraph we call an arc {\it deletable} if its deletion leaves a strongly connected digraph. Given a $3$-edge-connected graph $G$, we define its Frank number $f(G)$ to be the minimum num

Li Wang, Jiaqun Wei, Haicheng Zhang

We give a simultaneous generalization of recollements of abelian categories and triangulated categories, which we call recollements of extriangulated categories. For a recollement $(\mathcal{A}$, $\mathcal{B}$, $\mathcal{C})$ of extriangulated categories, we show that cotorsion pairs in $\mathcal{A}$ and $\mathcal{C}$ induce cotorsion pairs in $\mathcal{B}$

Liekang Zeng, Xu Chen, Zhi Zhou, Lei Yang

Recent advances in artificial intelligence have driven increasing intelligent applications at the network edge, such as smart home, smart factory, and smart city. To deploy computationally intensive Deep Neural Networks (DNNs) on resource-constrained edge devices, traditional approaches have relied on either offloading workload to the remote cloud or optimiz

Lu Lv, Qingqing Wu, Zan Li, Zhiguo Ding

In this paper, we investigate covert communication in an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) system, where a legitimate transmitter (Alice) applies NOMA for downlink and uplink transmissions with a covert user (Bob) and a public user (Roy) aided by an IRS. Specifically, we propose new IRS-assisted downlink and

Wanli Xie, Wen-Ze Wu, Chong Liu, Tao Zhang

Foresight of CO$_2$ emissions from fuel combustion is essential for policy-makers to identify ready targets for effective reduction plans and further to improve energy policies and plans. For the purpose of accurately forecasting the future development of China&#39;s CO$_2$ emissions from fuel combustion, a novel continuous fractional nonlinear grey Bernoull

Tao Luo, Zheng Ma, Zhiwei Wang, Zhi-Qin John Xu

A supervised learning problem is to find a function in a hypothesis function space given values on isolated data points. Inspired by the frequency principle in neural networks, we propose a Fourier-domain variational formulation for supervised learning problem. This formulation circumvents the difficulty of imposing the constraints of given values on isolate

Branka Mirchevska, Maria Hügle, Gabriel Kalweit, Moritz Werling

Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the optimal trajectory for this short horizon may still result in a sub-optimal long-term solution. At the same time, the resulting short-term trajectories allow for effective, comfort

Rashid Riahi, Seyed Zafarollah Kalantari

Equilibrium sequences were developed for rotating NS in the relativistic mean-field interaction framework using four density-dependent equations of state for the NS matter. These sequences were constructed for the observed rotation frequencies of 25, 317, 346, 716, and 1122 Hz. The bounds of sequences were calculated in each model to determine the stability

Hendrik Speleers, Deepesh Toshniwal

In this paper, we describe a general class of $C^1$ smooth rational splines that enables, in particular, exact descriptions of ellipses and ellipsoids - some of the most important primitives for CAD and CAE. The univariate rational splines are assembled by transforming multiple sets of NURBS basis functions via so-called design-through-analysis compatible ex

Mihir Dharmadhikari, Tung Dang, Kostas Alexis

This manuscript presents enhancements on our motion-primitives exploration path planning method for agile exploration using aerial robots. The method now further integrates a global planning layer to facilitate reliable large-scale exploration. The implemented bifurcation between local and global planning allows for efficient exploration combined with the ab

De-Jian Liu, Ye Xu, Ying-Jie Li, Sheng Zheng

We present a study of molecular outflows using six molecular lines (including 12CO/13CO/C18O/HCO+(J = 1-0) and SiO/CS(J = 2-1)) toward nine nearby high-mass star-forming regions with accurate known distances. This work is based on the high-sensitivity observations obtained with the 14-m millimeter telescope of Purple Mountain Observatory Delingha (PMODLH) ob

Yao Wan, Yang He, Jian-Guo Zhang, Yulei Sui

We present NaturalCC, an efficient and extensible toolkit to bridge the gap between natural language and programming language, and facilitate the research on big code analysis. Using NaturalCC, researchers both from natural language or programming language communities can quickly and easily reproduce the state-of-the-art baselines and implement their approac

Taiji Suzuki, Shunta Akiyama

Establishing a theoretical analysis that explains why deep learning can outperform shallow learning such as kernel methods is one of the biggest issues in the deep learning literature. Towards answering this question, we evaluate excess risk of a deep learning estimator trained by a noisy gradient descent with ridge regularization on a mildly overparameteriz

Roi Ronen, Yoav Y. Schechner, Eshkol Eytan

We derive computed tomography (CT) of a time-varying volumetric translucent object, using a small number of moving cameras. We particularly focus on passive scattering tomography, which is a non-linear problem. We demonstrate the approach on dynamic clouds, as clouds have a major effect on Earth&#39;s climate. State of the art scattering CT assumes a static

Nikita Karagodin, Mikhail Lifshits

For a class of Gaussian stationary processes, we prove a limit theorem on the convergence of the distributions of the scaled last exit time over a slowly growing linear boundary. The limit is a double exponential (Gumbel) distribution.

Anubhav Bhatt, Harish Ganesh, S. L. Ceccio

Flow topology and unsteady cavitation dynamics in the wake of a backward facing step was investigated using high speed videography and time-resolved X-Ray densitometry, along with static and dynamic pressure measurements. The measurements are used to inform the understanding of underlying mechanisms of observed flow dynamics as they are related to shock wave

Bablu Mukherjee, Ryoma Hayakawa, Kenji Watanabe, Takashi Taniguchi

We investigate a two-dimensional (2D) heterostructure consisting of few-layer direct bandgap ReS2, a thin h-BN layer and a monolayer graphene for application to various electronic devices. Metal-insulator-semiconductor (MIS)-type devices with two-dimensional (2D) van-der-Waals (vdW) heterostructures have recently been studied as important components to reali

U. Chaulagain, C. Stehlé, P. Barroso, M. Kozlova

Radiative shocks are strong shocks characterized by plasma at a high temperature emitting an important fraction of its energy as radiation. Radiative shocks are commonly found in many astrophysical systems and are templates of radiative hydrodynamic flows, which can be studied experimentally using high-power lasers. This is not only important in the context

Themistoklis Botsas, Jonathan A. Cumming, Ian H. Jermyn

In petroleum well test analysis, deconvolution is used to obtain information about the reservoir system. This information is contained in the response function, which can be estimated by solving an inverse problem in the pressure and flow rate measurements. Our Bayesian approach to this problem is based upon a parametric physical model of reservoir behaviour

Lior Gelberg, David Mendlovic, Dan Raviv

We present a novel architecture for person identification based on typing-style, constructed of adaptive non-local spatio-temporal graph convolutional network. Since type style dynamics convey meaningful information that can be useful for person identification, we extract the joints positions and then learn their movements&#39; dynamics. Our non-local approa

Liangjian Chen, Shih-Yao Lin, Yusheng Xie, Yen-Yu Lin

Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and multi-view images often results in significant performance gains. However, existing multi-view datasets are relatively small with hand joints annotated by off-the-shelf trackers o

Liangjian Chen, Shih-Yao Lin, Yusheng Xie, Yen-Yu Lin

Estimating 3D hand pose directly from RGB imagesis challenging but has gained steady progress recently bytraining deep models with annotated 3D poses. Howeverannotating 3D poses is difficult and as such only a few 3Dhand pose datasets are available, all with limited samplesizes. In this study, we propose a new framework of training3D pose estimation models f

Hangtian Jia, Yujing Hu, Yingfeng Chen, Chunxu Ren

The development of deep reinforcement learning (DRL) has benefited from the emergency of a variety type of game environments where new challenging problems are proposed and new algorithms can be tested safely and quickly, such as Board games, RTS, FPS, and MOBA games. However, many existing environments lack complexity and flexibility and assume the actions

Zhong-Heng Li

It is well known that Teukolsky equation of gravitational perturbations provides a powerful tool for the investigation of the ringdown phase of a binary black hole merger, but it is applicable only for final configurations in the Kerr cases. Here we introduce a new concept: the spin-coefficient connection. Employing it and a new transformation function, we f

Qibin Zheng, Yanlin Huang, Di Huang, Jianglai Liu

The PandaX project consists of a series of xenon-based experiments that are used to search for dark matter (DM) particles and to study the fundamental properties of neutrinos. The next DM experiment PandaX-4T will be using 4 ton liquid xenon in the sensitive volume, which is nearly a factor of seven larger than that of the previous experiment PandaX-II. Due

Arvind W Kiwelekar, Swanand Navandar, Dharmendra K. Yadav

Computational Thinking (CT) has emerged as one of the vital thinking skills in recent times, especially for Science, Technology, Engineering and Management (STEM) graduates. Educators are in search of underlying cognitive models against which CT can be analyzed and evaluated. This paper suggests adopting Kahneman&#39;s two-systems model as a framework to und

Xiaowei Chen, Wing Fung Chong, Runhuan Feng, Linfeng Zhang

Repeated history of pandemics, such as SARS, H1N1, Ebola, Zika, and COVID-19, has shown that pandemic risk is inevitable. Extraordinary shortages of medical resources have been observed in many parts of the world. Some attributing factors include the lack of sufficient stockpiles and the lack of coordinated efforts to deploy existing resources to the locatio

Harish S. Bhat, Majerle Reeves, Ramin Raziperchikolaei

While there has been a surge of recent interest in learning differential equation models from time series, methods in this area typically cannot cope with highly noisy data. We break this problem into two parts: (i) approximating the unknown vector field (or right-hand side) of the differential equation, and (ii) dealing with noise. To deal with (i), we desc

Magda H. Barecka, Joel W. Ager, Alexei A. Lapkin

Electrochemical conversion of CO2 (CO2R) into fuels and chemicals can both reduce CO2 emissions and allow for clean manufacturing in the scenario of significant expansion of renewable power generation. However, large-scale process deployment is currently limited by unfavourable process economics resulting from significant up- and down-stream costs for obtain