December 2020 arXiv papers — page 54

Samuel Daudin

Stochastic optimal control problems with constraints on the probability distribution of the final output are considered. Necessary conditions for optimality in the form of a coupled system of partial differential equations involving a forward Fokker-Planck equation and a backward Hamilton-Jacobi-Bellman equation are proved using convex duality techniques.

Changhong Fu, Ziang Cao, Yiming Li, Junjie Ye

In the domain of visual tracking, most deep learning-based trackers highlight the accuracy but casting aside efficiency. Therefore, their real-world deployment on mobile platforms like the unmanned aerial vehicle (UAV) is impeded. In this work, a novel two-stage Siamese network-based method is proposed for aerial tracking, \textit{i.e.}, stage-1 for high-qua

O. V. Ivanova, I. V. Luk'yanyk, N. N. Kiselev, V. L. Afanasiev

We carried out photometric and spectroscopic observations of comet 29P/Schwassmann-Wachmann 1 at the 6-m BTA telescope (SAO RAS, Russia) and the 1.6-m telescope of the National Laboratory for Astro-physics (LNA, Brazil) on February 20, 2012, and on May 31, 2011, respectively. The spectra revealed the presence of CO+ and N2+ emissions in the cometary coma at

Logambal Madhuanand, Francesco Nex, Michael Ying Yang

UAVs have become an essential photogrammetric measurement as they are affordable, easily accessible and versatile. Aerial images captured from UAVs have applications in small and large scale texture mapping, 3D modelling, object detection tasks, DTM and DSM generation etc. Photogrammetric techniques are routinely used for 3D reconstruction from UAV images wh

Sze-Shiang Feng, Mogus Mochena

As a sequel to our previous work\cite{Feng2020}, we propose in this paper a quantization scheme for Dirac field in de Sitter spacetime. Our scheme is covariant under both general transformations and Lorentz transformations. We first present a Hamiltonian structure, then quantize the field following the standard approach of constrained systems. For the free f

A. Menéndez-Vázquez, M. Kolstein, M. Martínez, Ll. M. Mir

We present results on the search for the coalescence of compact binary mergers using convolutional neural networks and the LIGO/Virgo data, corresponding to the O2 observation period. Two-dimensional images in time and frequency are used as input, and two sets of neural networks are trained separately for low mass (0.2 - 2.0 Msun) and high mass (25 - 100 Msu

Guillaume Carlier, Katharina Eichinger, Alexey Kroshnin

In this paper, we investigate properties of entropy-penalized Wasserstein barycenters introduced by Bigot, Cazelles and Papadakis (2019) as a regularization of Wasserstein barycenters first presented by Agueh and Carlier (2011). After characterizing these barycenters in terms of a system of Monge-Amp\`ere equations, we prove some global moment and Sobolev bo

Quentin Cohen-Solal, Tristan Cazenave

Deep Reinforcement Learning reaches a superhuman level of play in many complete information games. The state of the art algorithm for learning with zero knowledge is AlphaZero. We take another approach, Ath\'enan, which uses a different, Minimax-based, search algorithm called Descent, as well as different learning targets and that does not use a policy. We s

Maryam Saadati, Yousef Jamali

Type 2 diabetes (T2D) is a challenging metabolic disorder characterized by a substantial loss of $\beta$-cell mass and alteration of $\beta$-cell function in the islets of Langerhans, disrupting insulin secretion and glucose homeostasis. The mechanisms for deficiency in $\beta$-cell mass and function during the hyperglycemia development and T2D pathogenesis

Jingyu Guo, Hiroaki Ito, Yuji Higuchi, Klemen Bohinc

We investigated the phase separation of dioleoylphosphatidylserine (DOPS) and dipalmitoylphosphatidylcholine (DPPC) in giant unilamellar vesicles in hypotonic solution using fluorescence and confocal laser scanning microscopy. Although phase separation in charged lipid membranes is generally suppressed by the electrostatic repulsion between the charged headg

Rajat Gupta, Rahul Kumar

In this article, a $q$-series examined by Kluyver and Uchimura is generalized. This allows us to find generalization of the identities in the random acyclic digraph studied by Simon, Crippa, and Collenberg in 1993. As one of the corollaries of our main theorem, we get results of Dilcher and Andrews, Crippa, and Simon. This main theorem involves a surprising

Jiayu Zhai, Matthew Dobson, Yao Li

The time evolution of the probability distribution of a stochastic differential equation follows the Fokker-Planck equation, which usually has an unbounded, high-dimensional domain. Inspired by our early study in \cite{li2018data}, we propose a mesh-free Fokker-Planck solver, in which the solution to the Fokker-Planck equation is now represented by a neural

Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

This paper presents an information-theoretic framework for unifying active learning problems: level set estimation (LSE), Bayesian optimization (BO), and their generalized variant. We first introduce a novel active learning criterion that subsumes an existing LSE algorithm and achieves state-of-the-art performance in LSE problems with a continuous input doma

Penelope Jones, Fabian Coupette, Andreas Härtel, Alpha A. Lee

Electrolytes play an important role in a plethora of applications ranging from energy storage to biomaterials. Notwithstanding this, the structure of concentrated electrolytes remains enigmatic. Many theoretical approaches attempt to model the concentrated electrolytes by introducing the idea of ion pairs, with ions either being tightly `paired' with a count

Rahul Jilakara, David P. Waters

Studying for physics exams can be difficult and stressful, especially during a student's introductory year in physics. For students who do not plan to major in physics, the desire to do well is based less on understanding concepts and more on achieving a better grade. For this reason, students want to study as efficiently as possible by using the most optima

Xin Jin, Hongyu Zhang, Xiaodong Li, Haoyang Yu

With the development of cloud computing, the storage and processing of massive visual media data has gradually transferred to the cloud server. For example, if the intelligent video monitoring system cannot process a large amount of data locally, the data will be uploaded to the cloud. Therefore, how to process data in the cloud without exposing the original

Grigory Ivanov, Mariana Lopushanski

We provide an algorithm of constructing a rectifiable curve between two sufficiently close points of a proximally smooth set in a uniformly convex and uniformly smooth Banach space. Our algorithm returns a reasonably short curve between two sufficiently close points of a proximally smooth set, is iterative and uses a certain modification of the metric projec

Marcel Ausloos

Many still rightly wonder whether accounting numbers affect business value. Basic questions are why? and how? I aim at promoting an objective choice on how optimizing the most suitable valuation methods under a value-based management framework through some performance measurement systems. First, I present a comprehensive review of valuation methods. Three va

Bruno Olivieri, Marcelo Paulon, Markus Endler

Several situations exist where a geographic region of some size needs to be scanned or monitored through many sensors. Still, it is either absolutely impossible or prohibitively expensive to deploy and maintain wireless communication infrastructure for the distributed sensors. Either because the region is hidden behind walls, not easily accessible, hard to g

Philip Dawid

We conduct a review of the fiducial approach to statistical inference, following its journey from its initiation by R. A. Fisher, through various problems and criticisms, on to its general neglect, and then to its more recent resurgence. Emphasis is laid on the functional model formulation, which helps clarify the very limited conditions under which fiducial

Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet

This paper presents a novel approach to top-$k$ ranking Bayesian optimization (top-$k$ ranking BO) which is a practical and significant generalization of preferential BO to handle top-$k$ ranking and tie/indifference observations. We first design a surrogate model that is not only capable of catering to the above observations, but is also supported by a clas

Nicola Vassena

Sensitivity studies the network response to perturbations. We consider local perturbations of the concentrations of metabolites at an equilibrium. We investigate the responses in the network, both of the metabolite concentrations and of the reaction fluxes. Our approach is purely qualitative, rather than quantitative. In fact, our analysis is based, solely,

Per Johansson, Mattias Nordin

Double blind randomized controlled trials are traditionally seen as the gold standard for causal inferences as the difference-in-means estimator is an unbiased estimator of the average treatment effect in the experiment. The fact that this estimator is unbiased over all possible randomizations does not, however, mean that any given estimate is close to the t

Idan Pazi, Dvir Ginzburg, Dan Raviv

Alignment between non-rigid stretchable structures is one of the most challenging tasks in computer vision, as the invariant properties are hard to define, and there is no labeled data for real datasets. We present unsupervised neural network architecture based upon the spectral domain of scale-invariant geometry. We build on top of the functional maps archi

Marcel Ausloos, Francesca Bartolacci, Nicola G. Castellano, Roy Cerqueti

This paper analyzes the connection between innovation activities of companies -- implemented before a financial crisis -- and their performance -- measured after such a time of crisis. Pertinent data about companies listed in the STAR Market Segment of the Italian Stock Exchange is analyzed. Innovation is measured through the level of investments in total ta

Yu-Wei Chang, Tony W. H. Sheu

Image segmentation plays an important role in computer vision, object detection, traffic control, and video surveillance. Typically, it is a critical step in the 3D reconstruction of a specific organ in medical image processing which unveils the detailed tomography of organ, tumor, and nerve, and thus helping to improve the quality of surgical pathology. How

Manuel González, Antonio Martí nez-Abejón, Antonio Martinón

An operator $T$ from a Banach lattice $E$ into a Banach space is disjointly non-singular ($DN$-$S$, for short) if no restriction of $T$ to a subspace generated by a disjoint sequence is strictly singular. We obtain several results for $DN$-$S$ operators, including a perturbative characterization. For $E=L_p$ ($1< p<\infty$) we improve the results, and we sho

Yasar Sinan Nasir, Dongning Guo

A wireless network operator typically divides the radio spectrum it possesses into a number of subbands. In a cellular network those subbands are then reused in many cells. To mitigate co-channel interference, a joint spectrum and power allocation problem is often formulated to maximize a sum-rate objective. The best known algorithms for solving such problem

Feng Li, Kwok-Yan Lam, Min Jia, Jun Zhao

This paper presents a blockchain-based approach for securing spectrum sharing in multi-beam satellite systems. Satellite spectrum is a scarce resource that requires highly efficient management schemes for optimized sharing by network users. However, spectrum sharing is vulnerable to attacks by malicious protocol participants. In order to ensure efficient spe

K. N. Sjobak, E. Adli, R. Corsini, W. Farabolini

Active plasma lenses are compact devices developed as a promising beam-focusing alternative for charged particle beams, capable of short focal lengths for high-energy beams. We have previously shown that linear magnetic fields with gradients of around 0.3 kT/m can be achieved in argon-filled plasma lenses that preserve beam emittance [C.A. Lindstr{\o}m et al

Andrea Abrardo, Davide Dardari, Marco Di Renzo

In this paper, we consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the st

Andrew Spurr, Marcel Ausloos

We study the fundamental differences that separate: Litecoin; Bitcoin Gold; Bitcoin Cash; Ethereum; and Zcash from Bitcoin, and draw analysis to how these features are appreciated by the market, to ultimately make an inference as to how future successful cryptocurrencies may behave. We use Google Trend data, as well as price, volume and market capitalization

Yuxin Lin, Ning Hong, Baochang Shi, Zhenhua Chai

In this paper, we first present a multiple-relaxation-time lattice Boltzmann (MRT-LB) model for one-dimensional diffusion equation where the D1Q3 (three discrete velocities in one-dimensional space) lattice structure is considered. Then through the theoretical analysis, we derive an explicit four-level finite-difference scheme from this MRT-LB model. The res

Selma Mehyaoui

The origins of spontaneous movements have been investigated in human as well as in other vertebrates. Studies have reported an increase in neuronal activity one second before the onset of a given movement: this is known as readiness potential. The mechanisms underlying this increase are still unclear. Zebrafish larva is an ideal animal model to study the neu

Manuel González, Fernando León-Saavedra, María del Pilar Romero de la Rosa

A closed subspace $S$ of $\ell_\infty$ is said to be a \emph{$\ell_\infty$-Grothendieck subspace} if $c_0\subset S$ (hence $\ell_\infty\subset S^{**}$) and every $\sigma(S^*,S)$-convergent sequence in $S^*$ is $\sigma(S^*,\ell_\infty)$-convergent. Here we give examples of closed subspaces of $\ell_\infty$ containing $c_0$ which are or fail to be $\ell_\infty

R. Tufan Erdogan, Mohammed Alkhaled, Batuhan E. Kaynak, Hashim Alhmoud

Mass spectrometry of intact nanoparticles and viruses can serve as a potent characterization tool for material science and biophysics. Inaccessible by widespread commercial techniques, the mass of single nanoparticles and viruses (>10MDa) can be readily measured by NEMS (Nanoelectromechanical Systems) based Mass Spectrometry, where charged and isolated analy

Menglin Wang, Baisheng Lai, Jianqiang Huang, Xiaojin Gong

This paper tackles the purely unsupervised person re-identification (Re-ID) problem that requires no annotations. Some previous methods adopt clustering techniques to generate pseudo labels and use the produced labels to train Re-ID models progressively. These methods are relatively simple but effective. However, most clustering-based methods take each clust

Geoffrey Stewart Morrison, Reinoud D Stoel

Lennard (2013) [Fingerprint identification: how far have we come? Aus J Forensic Sci. doi:10.1080/00450618.2012.752037] proposes that the numeric output of statistical models should not be presented in court (except "if necessary" / "if required"). Instead he argues in favour of an "expert opinion" which may be informed by a statistical model but which is no

Martin Neuenhofen, Eric Kerrigan

We present a numerical method for the minimization of constrained optimization problems where the objective is augmented with large quadratic penalties of inconsistent equality constraints. Such objectives arise from quadratic integral penalty methods for the direct transcription of optimal control problems. The Augmented Lagrangian Method (ALM) has a number

Yao Deng, Xi Zheng, Tianyi Zhang, Guannan Lou

Autonomous driving has gained much attention from both industry and academia. Currently, Deep Neural Networks (DNNs) are widely used for perception and control in autonomous driving. However, several fatal accidents caused by autonomous vehicles have raised serious safety concerns about autonomous driving models. Some recent studies have successfully used th

Shreyank N Gowda, Marcus Rohrbach, Laura Sevilla-Lara

Action recognition is computationally expensive. In this paper, we address the problem of frame selection to improve the accuracy of action recognition. In particular, we show that selecting good frames helps in action recognition performance even in the trimmed videos domain. Recent work has successfully leveraged frame selection for long, untrimmed videos,

David A. Jorgensen, Liana M. Şega, Peder Thompson

Let $M$ and $N$ be finitely generated graded modules over a graded complete intersection $R$ such that $\operatorname{Ext}_R^i(M,N)$ has finite length for all $i\gg 0$. We show that the even and odd Hilbert polynomials, which give the lengths of $\operatorname{Ext}^i_R(M,N)$ for all large even $i$ and all large odd $i$, have the same degree and leading coeff

Ashutosh Tripathi, Yuexin Zhang, Askar B. Abdikamalov, Dimitry Ayzenberg

Einstein's theory of General Relativity predicts that the spacetime metric around astrophysical black holes is described by the Kerr solution. In this work, we employ state-of-the-art in relativistic reflection modeling to analyze a selected set of NuSTAR spectra of Galactic black holes to obtain the most robust and precise constraints on the Kerr black hole

Jean-Philippe Bernardy, Stergios Chatzikyriakidis

In this paper, we propose an implementation of temporal semantics which is suitable for inference problems. This implementation translates syntax trees to logical formulas, suitable for consumption by the Coq proof assistant. We support several phenomena including: temporal references, temporal adverbs, aspectual classes and progressives. We apply these sema

Ze Zheng, Andrei Komar, Khosro Zangeneh Kamali, John Noble

Optically resonant dielectric metasurfaces offer unique capability to fully control the wavefront, polarisation, intensity or spectral content of light based on the excitation and interference of different electric and magnetic Mie multipolar resonances. Recent advances of the wide accessibility in the nanofabrication and nanotechnologies have led to a surge

Edoardo Mainini, Danilo Percivale

We consider the topic of linearization of finite elasticity for pure traction problems. We characterize the variational limit for the approximating sequence of rescaled nonlinear elastic energies. We show that the limiting minimal value can be strictly lower than the minimal value of the standard linear elastic energy if a strict compatibility condition for

Abhijith Ajayakumar, Raju K george

In this paper, a necessary and sufficient condition for the controllability of networked systems with heterogeneous dynamics is established where the nodes are higher dimensional linear time invariant systems and the network topology is directed and weighted. The controllability of networked system over some specific topologies are also examined and some non

Rebecaa Pham, Marcel Ausloos

After the 2007/2008 financial crisis, the UK government decided that a change in regulation was required to amend the poor control of financial markets. The Financial Services Act 2012 was developed as a result in order to give more control and authority to the regulators of financial markets. Thus, the Financial Conduct Authority (FCA) succeeded the Financi

Walter F. Wreszinski

We provide a necessary and sufficient condition for the validity of the following Landsberg-Thirring theorem: for a real-valued function on a convex set, any two of the properties of superadditivity, concavity and homogeneity implies the third. Applications to statistical thermodynamics, following Thirring and Landsberg, are briefly reviewed.

Arun Sebastian, Manu Francis, Arun Mathew

Hearing aid is an electroacoustic device used to selectively amplify the audio sounds with an aim to make speech more intelligible for a hearing impaired person. Filter bank is one of the important parts of digital hearing aid where the sub band gains of each filter can be tuned to compensate an individuals unique hearing loss pattern. As the human perceptio

Md Rafiqul Islam Rabin, Mohammad Amin Alipour

The correctness of compilers is instrumental in the safety and reliability of other software systems, as bugs in compilers can produce executables that do not reflect the intent of programmers. Such errors are difficult to identify and debug. Random test program generators are commonly used in testing compilers, and they have been effective in uncovering bug

Alexandre Duval, Thomas Lamson, Gael de Leseleuc de Kerouara, Matthias Gallé

It is standard procedure these days to solve Information Extraction task by fine-tuning large pre-trained language models. This is not the case for generation task, which relies on a variety of techniques for controlled language generation. In this paper, we describe a system that fine-tunes a natural language generation model for the problem of solving Writ

Marcel Ausloos

A spectacular order-order-like transition is presented in the distribution of hagiotoponyms in France. Data analysis and displays distinguish male and female cases. The respective hapax values point to a very large variety of saints with a specific devotion. The most popular ones are St. Martin and the apostles. The less popular ones are not so well known. T

Waqqas-ur-Rehman Butt, Martin Servin

This paper presents a multi stage 3D shape reconstruction system of multiple object scenes by considering the silhouette inconsistencies in shape-from silhouette SFS method. These inconsistencies are common in multiple view images due to object occlusions in different views, segmentation and shadows or reflection due to objects or light directions. These fac

Y. A. Fofanov, I. M. Sokolov, R. Kaiser, W. Guerin

We study numerically the slow (subradiant) decay of the fluorescence of motionless atoms after a weak pulsed excitation. We show that, in the linear-optics regime and for an excitation detuned by several natural linewidths, the slow decay rate can be dominated by close pairs of atoms (dimers) forming superradiant and subradiant states. However, for a large-e

Zhang-Hua Fu, Kai-Bin Qiu, Hongyuan Zha

For the traveling salesman problem (TSP), the existing supervised learning based algorithms suffer seriously from the lack of generalization ability. To overcome this drawback, this paper tries to train (in supervised manner) a small-scale model, which could be repetitively used to build heat maps for TSP instances of arbitrarily large size, based on a serie

Anurag Singh, Deepak Kumar Sharma, Sudhir Kumar Sharma

Successful applications of deep learning (DL) requires large amount of annotated data. This often restricts the benefits of employing DL to businesses and individuals with large budgets for data-collection and computation. Summarization offers a possible solution by creating much smaller representative datasets that can allow real-time deep learning and anal

Matin Macktoobian, Ricardo Araújo, Loïc Grossen, Luzius Kronig

The data throughput of massive spectroscopic surveys in the course of each observation is directly coordinated with the number of optical fibers which reach their target. In this paper, we evaluate the safety and the performance of the astrobots coordination in SDSS-V by conducting various experimental and simulated tests. We illustrate that our strategy pro

Tobias Herrig, Roman-Pascal Riwar

The outlook of protected quantum computing spurred enormous progress in the search for topological materials, sustaining a continued race to find the most experimentally feasible platform. Here, we show that one of the simplest quantum circuits, the Cooper-pair transistor, exhibits a nontrivial Chern number which has not yet been discussed, in spite of the e

Clara Abaurrea-Velasco, Celia Lozano, Clemens Bechinger, Joost de Graaf

Recent experiments show a strong rotational-diffusion enhancement for self-propelled microrheological probes in colloidal glasses. Here, we provide microscopic understanding using simulations with a frictional probe-medium coupling that converts active translation into rotation. Diffusive enhancement emerges from the medium's disordered structure and peaks a

Mihai-Silviu Lazorec, Marius Tarnauceanu

The same-order type $\tau_e(G)$ of a finite group $G$ is a set formed of the sizes of the equivalence classes containing the same order elements of $G$. In this paper, we study an arithmetical property of this set. More exactly, we outline some results on the classification and existence of finite groups whose same-order types are arithmetic progressions for

Nora Bruns

Network scanning has been a widely used technique to gather information on the Internet as a whole. The transition from IPv4 to IPv6 causes traditional network scanning to become less useful. An increasing number of hosts is either IPv6-only or not publicly addressable via IPv4 due to the use of NAT, prompting a need for network scanning techniques for the I

Ferdinand Ihringer, Francesco Pavese, Valentino Smaldore

Let $H(n, q^2)$ be a non-degenerate Hermitian variety of $PG(n, q^2)$, $n \ge 2$. Let NU$(n+1, q^2)$ be the graph whose vertices are the points of $PG(n, q^2) \setminus H(n, q^2)$ and two vertices $P_1$, $P_2$ are adjacent if the line joining $P_1$ and $P_2$ is tangent to $H(n, q^2)$. Then NU$(n + 1, q^2)$ is a strongly regular graph. In this paper we show t

Yejiang Wang, Yuhai Zhao, Zhengkui Wang, Chengqi Zhang

Multi-graph multi-label learning (\textsc{Mgml}) is a supervised learning framework, which aims to learn a multi-label classifier from a set of labeled bags each containing a number of graphs. Prior techniques on the \textsc{Mgml} are developed based on transfering graphs into instances and focus on learning the unseen labels only at the bag level. In this p

Arvid Perego, Antonio Rapagnetta

In this paper we study the second integral cohomology of moduli spaces of semistable sheaves on projective K3 surfaces. If $S$ is a projective K3 surface, $v$ a Mukai vector and $H$ a $v-$generic polarization on $S$, we show that $H^{2}(M_{v},\mathbb{Z})$ is a free $\mathbb{Z}-$module of rank 23 carrying a pure weight-two Hodge structure and a lattice struct

Xiaojian Zhang, Yu Yang, Abigail L. Cochran, Noreen McDonald

The traditional demand-responsive paratransit system plays an important role in connecting people to health care, particularly those who are carless, low-income, senior, underinsured/uninsured, or who have a disability. However, the existing paratransit system usually has low service quality due to long waiting times, low operation frequencies, and high cost

T. Hakioglu, Wei-Chi Chiu, R. S. Markiewicz, Bahadur Singh

Spin-momentum locking is a unique intrinsic feature of strongly spin-orbit coupled materials and a key to their promise of applications in spintronics and quantum computation. Much of the existing work, in topological and non-topological pure materials, has been focused on the orthogonal locking in the vicinity of the $\Gamma$ point where the directions of s

Supriyo Ghosh, D. K. Ojha, J. P. Ninan

We present here quantitative diagnostic tools for cool giants that employ low-resolution near-infrared spectroscopy in the $K$-band for stellar population studies. In this study, a total of 260 cool giants (177 stars observed with X-shooter and 83 stars observed with NIFS) are used covering a wider metallicity range than in earlier works. We measure equivale

Lev Titarchuk, Elena Seifina

We discovered a so called high-temperature blackbody (HBB) component, found in the 15 -- 40 keV range, in the broad-band X-ray energy spectra of black hole (BH) candidate sources. A detailed study of this spectral feature is presented using data from five of the Galactic BH binaries, Cyg X-1, GX 339-4, GRS 1915+105, SS 433 and V4641~Sgr in the low/hard, inte

Aniq Ur Rahman, Mustafa A. Kishk, Mohamed-Slim Alouini

We study the interaction of WiFi and 5G cellular networks as they exploit the recently unlocked 6-GHz spectrum for unlicensed access while conforming to the constraints imposed by the incumbent users. We derive the theoretical performance metrics for users of each radio access technology using stochastic geometry, thereby capturing the aggregate behaviour of

Yingjie Liu

Although much significant progress has been made in the research field of object detection with deep learning, there still exists a challenging task for the objects with small size, which is notably pronounced in UAV-captured images. Addressing these issues, it is a critical need to explore the feature extraction methods that can extract more sufficient feat

Ciro Ciliberto, Thomas Dedieu

Let $\mathcal{KC}_g ^k$ be the moduli stack of pairs $(S,C)$ with $S$ a $K3$ surface and $C\subset S$ a genus $g$ curve with divisibility $k$ in $\mathrm{Pic}(S)$. In this article we study the forgetful map $c_g^k:(S,C) \mapsto C$ from $\mathcal{KC}_g ^k$ to $\mathcal{M}_g$ for $k>1$. First we compute by geometric means the dimension of its general fibre. Th

Ludovic Mignot

In this document, we propose a description, via a Haskell implementation, of a generalization of the notion of regular expression allowing us to group the definitions and the methods of (tree or word) automata constructions over one generic structure, based on enriched category theory tools. We first recall several methods of conversion from expressions to a

Ziwen Zhang, Huiyuan Wang, Wentao Luo, H. J. Mo

Based on the spectroscopic and shear catalogs for SDSS galaxies in the local Universe, we compare optically-selected active galactic nuclei (AGNs) with control star-forming and quiescent galaxies on galactic, inter-halo and larger scales. We find that AGNs are preferentially found in two specific stages of galaxy evolution: star-burst and `green valley' phas

Etido P. Inyang, Ephraim P. Inyang, Eddy S. William, Etebong E. Ibekwe

We solved the radial Schr"odinger equation analytically using the Exact Quantization Rule approach to obtain the energy eigenvalues with the Extended Cornell potential ECP. The present results are applied for calculating the mass spectra of heavy mesons such as charmonium cc and bottomonium bb, and heavylight mesons such as bottom-charm bc and charm-Strange

Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

We present a novel deep reinforcement learning method to learn construction heuristics for vehicle routing problems. In specific, we propose a Multi-Decoder Attention Model (MDAM) to train multiple diverse policies, which effectively increases the chance of finding good solutions compared with existing methods that train only one policy. A customized beam se

Xiao Chen

Assuming an exponential power distribution is one way to deal with outliers in regression and clustering, which can increase the robustness of the analysis. Gaussian distribution is a special case of an exponential distribution. And an exponential power distribution can be viewed as a scale mixture of normal distributions. Thus, model selection methods devel

Roberto Cavoretto, Alessandra De Rossi, Wolfgang Erb

Partition of unity methods (PUMs) on graphs are simple and highly adaptive auxiliary tools for graph signal processing. Based on a greedy-type metric clustering and augmentation scheme, we show how a partition of unity can be generated in an efficient way on graphs. We investigate how PUMs can be combined with a local graph basis function (GBF) approximation

Nikolaos Syrrakos

We analytically calculate one-loop five-point Master Integrals, \textit{pentagon integrals}, with up to one off-shell leg to arbitrary order in the dimensional regulator in $d=4-2\epsilon$ space-time dimensions. A pure basis of Master Integrals is constructed for the pentagon family with one off-shell leg, satisfying a single-variable canonical differential

Andronikos Paliathanasis

The group properties of the shallow-water equations with the complete Coriolis force is the subject of this study. In particular we apply the Lie theory to classify the system of three nonlinear partial differential equations according to the admitted Lie point symmetries. For each case of the classification problem the one-dimensional optimal system is dete

B. I. Ermolaev, S. I. Troyan

We present calculation of F_L in the double-logarithmic approximation and demonstrate that the synergic effect of the factor 1/x from the \alpha_s^2-order and the steep x-dependence of the totally resummed double logarithmic contributions of higher orders ensures the power-like rise of F_L at small x and arbitrary Q^2.

Hansjoerg Albrecher, Pablo Azcue, Nora Muler

We study the problem of optimal dividend payout from a surplus process governed by Brownian motion with drift under the additional constraint of ratcheting, i.e. the dividend rate can never decrease. We solve the resulting two-dimensional optimal control problem, identifying the value function to be the unique viscosity solution of the corresponding Hamilton

Binyi Su, Haiyong Chen, Zhong Zhou

The multi-scale defect detection for photovoltaic (PV) cell electroluminescence (EL) images is a challenging task, due to the feature vanishing as network deepens. To address this problem, an attention-based top-down and bottom-up architecture is developed to accomplish multi-scale feature fusion. This architecture, called Bidirectional Attention Feature Pyr

Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh Iyer

Large scale machine learning and deep models are extremely data-hungry. Unfortunately, obtaining large amounts of labeled data is expensive, and training state-of-the-art models (with hyperparameter tuning) requires significant computing resources and time. Secondly, real-world data is noisy and imbalanced. As a result, several recent papers try to make the

Amay SM Cheam, Marc Fredette, Matthieu Marbac, Fabien Navarro

The COVID-19 pandemic has taken the world by storm with its high infection rate. Investigating its geographical disparities has paramount interest in order to gauge its relationships with political decisions, economic indicators, or mental health. This paper focuses on clustering the daily death rates reported in several regions of Europe and the United Stat

Tomoki Nosaka

We review our recent work [arXiv:2009.10759] where we studied the chaotic property of the two coupled Sachdev-Ye-Kitaev systems exhibiting a Hawking-Page like phase transition. By computing the out-of-time-ordered correlator in the large N limit by using the bilocal field formalism, we found that the chaos exponent of this model shows a discontinuous fall-of

Ayse Borat, Mehmetcik Pamuk, Tane Vergili

We study properties of contiguity distance between simplicial maps. In particular, we show that simplicial versions of $LS$-category and topological complexity are particular cases of this more general notion.

Alex J. Schimmoller, Gerard McCaul, Hartmut Abele, Denys I. Bondar

Erik Verlinde's theory of entropic gravity [arXiv:1001.0785], postulating that gravity is not a fundamental force but rather emerges thermodynamically, has garnered much attention as a possible resolution to the quantum gravity problem. Some have ruled this theory out on grounds that entropic forces are by nature noisy and entropic gravity would therefore di

Tae-Yong An, Minyeong Je, Seung Hun Roh, Subramani Surendran

The nitrogen (N2) reduction reaction (NRR) is an eco-friendly alternative to the Haber-Bosch process to produce ammonia (NH3) with high sustainability. However, the significant magnitude of uphill energies in the multi-step NRR pathways is a bottleneck of its serial reactions. Herein, the concept of a parallelized reaction is proposed to actively promote NH3

Jun Gao, Qingyi Huo, Jie Ma

Resolving a conjecture of Bollob\'{a}s and Erd\H{o}s, Gy\'{a}rf\'{a}s proved that every graph $G$ of chromatic number $k+1\geq 3$ contains cycles of $\lfloor\frac{k}{2}\rfloor$ distinct odd lengths. We strengthen this prominent result by showing that such $G$ contains cycles of $\lfloor\frac{k}{2}\rfloor$ consecutive odd lengths. Along the way, combining ext

Qijun Tong, Kei Kobayashi

The distance and divergence of the probability measures play a central role in statistics, machine learning, and many other related fields. The Wasserstein distance has received much attention in recent years because of its distinctions from other distances or divergences. Although~computing the Wasserstein distance is costly, entropy-regularized optimal tra

Simon Brandhorst, Ichiro Shimada

We calculate the automorphism group of certain Enriques surfaces. The Enriques surfaces that we investigate include very general $n$-nodal Enriques surfaces and very general cuspidal Enriques surfaces. We also describe the action of the automorphism group on the set of smooth rational curves and on the set of elliptic fibrations.

Guangqian Jiao, Shoubao Zhu, Jizhou He, Yongli Ma

We derive the general probability distribution function of stochastic work for quantum Otto engines in which both the isochoric and driving processes are irreversible due to finite time duration. The time-dependent power fluctuations, average power, and thermodynamic efficiency are explicitly obtained for a complete cycle operating with an analytically solva

Ritesh Ghosh, Sibasish Laha

The reprocessed X-ray emission from Active Galactic Nuclei (AGN) is an important diagnostic tool to study the dynamics and geometry of the matter surrounding the supermassive black holes (SMBHs). We present a broadband (optical-UV to hard X-ray) spectral study of the bare Seyfert 1 galaxy, ESO~511--G030, using multi-epoch Suzaku and XMM-Newton data from 2012

Wentao Zhao, Dalin Zhou, Xinguo Qiu, Wei Jiang

Graph neural networks (GNNs) have been investigated for potential applicability in multiple fields that employ graph data. However, there are no standard training settings to ensure fair comparisons among new methods, including different model architectures and data augmentation techniques. We introduce a standard, reproducible benchmark to which the same tr

M. Onorato, G. Dematteis, D. Proment, A. Pezzi

We predict negative temperature states in the Discrete Nonlinear Sch\"odinger equation as exact solutions of the associated Wave Kinetic equation. Those solutions are consistent with the classical thermodynamics formalism. Explicit calculation of the entropy as a function of the energy and number of particles is performed analytically. Direct numerical simul

Jeffery L. Tallon, John W. Loram

The cuprate superconductor YBa$_2$Cu$_4$O$_8$, in comparison with most other cuprates, has a stable stoichiometry, is largely free of defects and may be regarded as the canonical underdoped cuprate, displaying marked pseudogap behaviour and an associated distinct weakening of superconducting properties. This cuprate `pseudogap' manifests as a partial gap in

Yuichi Ito, George L. Hashimoto, Yoshiyuki O. Takahashi, Masaki Ishiwatari

The existence of liquid water within an oxidized environment on early Mars has been inferred by the Mn-rich rocks found during recent explorations on Mars. The oxidized atmosphere implied by the Mn-rich rocks would basically be comprised of CO$_2$ and H$_2$O without any reduced greenhouse gases such as H$_2$ and CH$_4$. So far, however, it has been thought t

Piotr Antonik, Michiel Hermans, Marc Haelterman, Serge Massar

Reservoir computing is a bio-inspired computing paradigm for processing time dependent signals. The performance of its analogue implementations matches other digital algorithms on a series of benchmark tasks. Their potential can be further increased by feeding the output signal back into the reservoir, which would allow to apply the algorithm to time series

Xiaoling Wu, Xinhui Liang, Yaoqi Tian, Fan Yang

Quantum information processing based on Rydberg atoms emerged as a promising direction two decades ago. Recent experimental and theoretical progresses have shined exciting light on this avenue. In this concise review, we will briefly introduce the basics of Rydberg atoms and their recent applications in associated areas of neutral atom quantum computation an