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GENERAL HIGHER-ORDER BREATHERS AND ROGUE WAVES IN THE TWO-COMPONENT LONG-WAVE-SHORT-WAVE RESONANCE-INTERACTION MODEL

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arXiv 2022年

作者： Rao, Jiguang Malomed, Boris A. Mihalache, Dumitru He, Jingsong School of Mathematics and Statistics Hubei University of Science and Technology Hubei Xianning437100 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering Center for Light–Matter Interaction Tel Aviv University P.O.B. 39040 Ramat Aviv Tel Aviv Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile Horia Hulubei National Institute of Physics and Nuclear Engineering P.O. Box MG–6 MagureleRO-077125 Romania Institute for Advanced Study Shenzhen University Guangdong Shenzhen518060 China

General higher-order breather and rogue wave (RW) solutions to the two-component long wave–short wave resonance interaction (2-LSRI) model are derived via the bilinear Kadomtsev-Petviashvili hierarchy reduction method and are given in terms of determinants. Under particular parametric conditions, the breather solutions can reduce to homoclinic orbits, or a mixture of breathers and homoclinic orbits. There are three families of RW solutions, which correspond to a simple root, two simple roots, and a double root of an algebraic equation related to the dimension reduction procedure. The first family of RW solutions consists of N(N+1)2 bounded fundamental RWs, the second family is composed of N1(N1+1)2 bounded fundamental RWs co-2 existing with another N2(N2+1)2 fundamental RWs of different bounded state (N, N1, N2 being 2 positive integers), while the third one have [N12 + N22 - N1(N2 - 1)] fundamental bounded RWs (N1, N2 being non-negative integers). The second family can be regarded as the superpositions of the first family, while the third family can be the degenerate case of the first family under particular parameter choices. These diverse RW patterns are illustrated graphically. © 2022, CC BY.

关键词： Resonance

On arithmetic progressions in non-periodic self-affine tilings

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arXiv 2020年

作者： Nagai, Yasushi Akiyama, Shigeki Lee, Jeong-Yup School of Mathematics and Statistics Faculty of Science Technology Engineering and Mathematics The Open University Walton Hall Milton KeynesMK7 6AA United Kingdom Institute of Mathematics University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8571 Japan Department of Mathematics Education Catholic Kwandong University Gangneung Gangwon210-701 Korea Republic of KIAS 85 Hoegiro Dongdaemun-gu Seoul02455 Korea Republic of

We study the repetition of patches in self-affine tilings in Rd. In particular, we study the existence and non-existence of arithmetic progressions. We first show that an arithmetic condition of the expansion map for a self-affine tiling implies the non-existence of certain one-dimensional arithmetic progressions. Next, we show that the existence of full-rank infinite arithmetic progressions, pure discrete dynamical spectrum, and limit periodicity are all equivalent for a certain class of self-affine tilings. We finish by giving a complete picture for the existence/non-existence of full-rank infinite arithmetic progressions in the self-similar tilings in RdMSC Codes 52C23 (primary), 37B52 (secondary) Copyright © 2020, The Authors. All rights reserved.

关键词： Equivalence classes

Decoding asymptomatic COVID-19 infection and transmission

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arXiv 2020年

作者： Wang, Rui Chen, Jiahui Hozumi, Yuta Yin, Changchuan Wei, Guo-Wei Department of Mathematics Michigan State University MI48824 United States Department of Mathematics Statistics and Computer Science University of Illinois at Chicago ChicagoIL60607 United States Department of Electrical and Computer Engineering Michigan State University MI48824 United States Department of Biochemistry and Molecular Biology Michigan State University MI48824 United States

Coronavirus disease 2019 (COVID-19) is a continuously devastating public health and the world economy. One of the major challenges in controlling the COVID-19 outbreak is its asymptomatic infection and transmission, which are elusive and defenseless in most situations. The pathogenicity and virulence of asymptomatic COVID-19 remain mysterious. Based on the genotyping of 20656 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome isolates, we reveal that asymptomatic infection is linked to SARS-CoV-2 11083G>T mutation, i.e., leucine (L) to phenylalanine (F) substitution at the residue 37 (L37F) of nonstructure protein 6 (NSP6). By analyzing the distribution of 11083G>T in various countries, we unveil that 11083G>T may correlate with the hypotoxicity of SARS-CoV-2. Moreover, we show a global decaying tendency of the 11083G>T mutation ratio indicating that 11083G>T hinders SARS-CoV-2 transmission capacity. Sequence alignment found both NSP6 and residue 37 neighborhoods are relatively conservative over a few coronaviral species, indicating their importance in regulating host cell autophagy to undermine innate cellular defense against viral infection. Using machine learning and topological data analysis, we demonstrate that mutation L37F has made NSP6 energetically less stable. The rigidity and flexibility index and several network models suggest that mutation L37F may have compromised the NSP6 function, leading to a relatively weak SARS-CoV subtype. This assessment is a good agreement with our genotyping of SARS-CoV-2 evolution and transmission across various countries and regions over the past few months. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

General higher-order majorization-minimization algorithms for (non)convex optimization

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arXiv 2020年

作者： Necoara, Ion Lupu, Daniela Automatic Control and Systems Engineering Department University Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest050711 Romania

Majorization-minimization algorithms consist of successively minimizing a sequence of upper bounds of the objective function so that along the iterations the objective function decreases. Such a simple principle allows to solve a large class of optimization problems, even nonconvex and nonsmooth. We propose a general higher-order majorization-minimization algorithmic framework for minimizing an objective function that admits an approximation (surrogate) such that the corresponding error function has a higher-order Lipschitz continuous derivative. We present convergence guarantees for our new method for general optimization problems with (non)convex and/or (non)smooth objective function. For convex (possibly nonsmooth) problems we provide global sublinear convergence rates, while for problems with uniformly convex objective function we obtain locally faster superlinear convergence rates. We also prove global stationary point guarantees for general nonconvex (possibly nonsmooth) problems and under Kurdyka-Lojasiewicz property of the objective function we derive local convergence rates ranging from sublinear to superlinear for our majorization-minimization algorithm. Moreover, for unconstrained nonconvex problems we derive convergence rates in terms of first- and second-order optimality conditions. Copyright © 2020, The Authors. All rights reserved.

关键词： Convex optimization

Autonomous learning of nonlocal stochastic neuron dynamics

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arXiv 2020年

作者： Maltba, Tyler E. Zhao, Hongli Tartakovsky, Daniel M. Department of Statistics UC Berkeley BerkeleyCA94720 United States Department of Mathematics UC Berkeley BerkeleyCA94720 United States Department of Energy Resources Engineering Stanford University StanfordCA94305 United States

Neuronal dynamics is driven by externally imposed or internally generated random excitations/noise, and is often described by systems of random or stochastic ordinary differential equations. Such systems admit a distribution of solutions, which is (partially) characterized by the single-time joint probability density function (PDF) of system states. It can be used to calculate such information-theoretic quantities as the mutual information between the stochastic stimulus and various internal states of the neuron (e.g., membrane potential), as well as various spiking statistics. When random excitations are modeled as Gaussian white noise, the joint PDF of neuron states satisfies exactly a Fokker-Planck equation. However, most biologically plausible noise sources are correlated (colored). In this case, the resulting PDF equations require a closure approximation. We propose two methods for closing such equations: a modified nonlocal large-eddy-diffusivity closure and a data-driven closure relying on sparse regression to learn relevant features. The closures are tested for the stochastic non-spiking leaky integrate-and-fire and FitzHugh-Nagumo (FHN) neurons driven by sine-Wiener noise. Mutual information and total correlation between the random stimulus and the internal states of the neuron are calculated for the FHN neuron. Copyright © 2020, The Authors. All rights reserved.

关键词： Neurons

An Open-source UAV Digital Twin framework: A Case Study on Remote Sensing in the Andean Mountains

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Journal of Intelligent and Robotic Systems: Theory and Applications 2025年第2期111卷

作者： Valencia, Esteban Toapanta, Francisco Oña, Gabriel Carrillo, Andrey Aláez, Daniel Loyaga, Erick Chamorro, William Cruz, Patricio Abad, Jackeline Vandewalle, Patrick Laboratory of UAS ATA Research group Mechanical Engineering Department Escuela Politécnica Nacional Quito Ecuador Department of Statistics Computer Science and Mathematics Universidad Pública de Navarra Pamplona31006 Spain Institute of Smart Cities Universidad Pública de Navarra Pamplona31006 Spain KU Leuven Jan Pieter de Nayerlaan 5 Sint-Katelijne-Waver Belgium

The increasing demand for unmanned aerial vehicles (UAVs) in the aerospace industry highlights the need for precise simulation environments, especially in remote regions. This study develops an open-source framework for a customized UAV simulation environment using ROS-Gazebo and Ardupilot. The method includes a realistic reconstruction of the environment based on free satellite information, the ROS-Gazebo scheme for modeling and testing the UAV platform, and Ardupilot for mission design and deployment. The methodology aims to reduce costs in surveillance missions and conduct more efficient operations in high-risk and challenging areas. To evaluate the accuracy of UAV positioning for simulating real missions, an experimental validation of the digital twin was carried out using real flight data records from two self-built UAVs equipped with the open-source Ardupilot autopilot. One of the aircraft, a fixed-wing UAV, was tested near the Antisana volcano (4500 meters above sea level), where wind gusts reached speeds of 9 to 12 m/s. These tests revealed maximum errors of 9% in the Z-axis trajectory (altitude). The other aircraft, a quadcopter, was evaluated in the Parque Carolina in Quito (2800 meters above sea level), with wind gusts between 5 and 7 m/s, showing an error of 8% in the Z-axis trajectory. The presented results demonstrate the suitability of the proposed method for emulating complex missions using digital twin models. In this regard, the main contribution of this work lies in its potential for the precise prediction of flight missions in the Z-axis, a crucial variable for avoiding collisions in mountainous regions. © The Author(s) 2025.

关键词： Aerospace industry

A Comparison of Bagging and Boosting on Classification Data: Case Study on Rainfall Data in Sultan Syarif Kasim II Meteorological Station in Pekanbaru

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Journal of Physics: Conference Series 2021年第1期2049卷

作者： A Adnan A M Yolanda F Natasya Statistics Study Program Department of Mathematics Universitas Riau Jl. HR. Soebrantas Km. 12.5 Pekanbaru 28293 Indonesia

A frequent way for classification data is using a machine learning algorithm alongside ensemble methods like bagging and boosting. In earlier studies, these two algorithms have shown to be very accurate. The aim of this research is to discover performance of bagging and boosting to classify rainfall data obtained at the Sultan Syarif Kasim II Meteorological Station in Pekanbaru from 1 January 2018 until 31 July 2021. Rainfall data are classified into two categories: rainy and non-rainy. The parameters are average temperature, average humidity, sunshine duration, wind direction at maximum speed, and average wind speed. For comparison, this study developed Stochastic Gradient Boosting with Gradient Boosting Modelling and C5.0 from boosting, as well as Bagged Classification and Regression Tree (CART) and Random Forest from bagging. In order to generate reliable conclusions, each algorithm is run 30 times with repeated cross validation. The result demonstrates that Stochastic Gradient Boosting with Gradient Boosting Modelling is the best algorithm based on average accuracy.

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Non-singular anisotropic solutions for strange star model in f(R, T, RζγT ζγ) gravity theory

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arXiv 2025年

作者： Feng, Yihu Naseer, Tayyab Mustafa, G. Maurya, S.K. Department of Electronics and Information Engineering Bozhou University Anhui Bozhou236800 China Department of Mathematics and Statistics The University of Lahore 1-KM Defence Road Lahore54000 Pakistan Research Center of Astrophysics and Cosmology Khazar University AZ1096 Mehseti Street Baku41 Azerbaijan Department of Physics Zhejiang Normal University Jinhua321004 China Department of Mathematical and Physical Sciences College of Arts and Sciences University of Nizwa Nizwa Oman

This article focuses on different anisotropic models within the framework of a specific modified f (R, T, Rζγ T ζγ ) gravity theory. The study adopts a static spherically symmetric spacetime to determine the field equations for two different modified models: (i) f (R, T, Rζγ T ζγ ) = R + ηRζγ T ζγ , and (ii) f (R, T, Rζγ T ζγ ) = R(1 + ηRζγ T ζγ ), where η is a constant parameter. To address the additional degrees of freedom in the field equations and obtain their corresponding unique solution, the Durgapal-Fuloria spacetime geometry and MIT bag model are utilized. Matching conditions are applied to determine unknown constants within the chosen spacetime geometry. We adopt a certain range of model parameters to analyze the physical characteristics of the developed models in the interior distribution of a particular compact star candidate 4U 1820-30. Energy conditions and some other tests are also implemented to ensure their viability and stability. Additionally, the disappearing radial pressure constraint is employed to find the values of the model parameter, aligning with the observed information of an array of stars. The study concludes that both of our models are well-behaved and satisfy all necessary conditions, and thus we observe them suitable for the modeling of astrophysical objects. Copyright © 2025, The Authors. All rights reserved.

关键词： Anisotropy

2858 A network analysis of morbidities associated with mental-physical multimorbidity among Brazilian elderly people (ELSI-Brazil)Get access

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Age and Ageing 2025年第SUPPLEMENT_1期54卷

作者： Batista, SRR Wottrich, VS Pereira, EM Silva, RR School of Medicine Federal University of Goias Brazil Postgraduate Program in Medical Sciences Faculty of Medicine University of Brasília Brasília Brazil Institute of Tropical Pathology and Public Health Federal University of Goiás Goiânia Brazil Department of Health Municipality of Senador Canedo Senador Canedo Brazil Institute of Mathematics and Statistics Federal University of Goiás Goiânia Brazil