检索结果-内蒙古大学图书馆

Impact of periodic vaccination in SEIRS seasonal model

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Gabrick, Enrique C. Brugnago, Eduardo L. de Souza, Silvio L.T. Iarosz, Kelly C. Szezech, José D. Viana, Ricardo L. Caldas, Iberê L. Batista, Antonio M. Kurths, Jürgen Potsdam Institute for Climate Impact Research Telegrafenberg A31 Potsdam14473 Germany Department of Physics Humboldt University Berlin Newtonstraße 15 Berlin12489 Germany Graduate Program in Science State University of Ponta Grossa PR Ponta Grossa84030-900 Brazil Institute of Physics University of São Paulo SP São Paulo05508-090 Brazil Federal University of São João del-Rei Campus Centro-Oeste Divinópolis MG 35501-296 Brazil University Center UNIFATEB PR Telêmaco Borba84266-010 Brazil Department of Mathematics and Statistics State University of Ponta Grossa PR Ponta Grossa84030-900 Brazil Department of Physics Federal University of Paraná PR Curitiba81531-980 Brazil

We study three different strategies of vaccination in a SEIRS (Susceptible-Exposed-Infected-Recovered-Susceptible) seasonal forced model, which are: (i) continuous vaccination;(ii) periodic short time localized vaccination and (iii) periodic pulsed width campaign. Considering the first strategy, we obtain an expression for the basic reproduction number and infer a minimum vaccination rate necessary to ensure the stability of the disease-free equilibrium (DFE) solution. In the second strategy, the short duration pulses are added to a constant baseline vaccination rate. The pulse is applied according to the seasonal forcing phases. The best outcome is obtained by locating the intensive immunization at inflection of the transmissivity curve. There, a vaccination rate of 44.4% of susceptible individuals is enough to ensure DFE. For the third vaccination proposal, additionally to the amplitude, the pulses have a prolonged time width. We obtain a non-linear relationship between vaccination rates and the duration of the campaign. Our simulations show that the baseline rates, as well as the pulse duration, can substantially improve the vaccination campaign effectiveness. These findings are in agreement with our analytical expression. We show a relationship between the vaccination parameters and the accumulated number of infected individuals, over the years and show the relevance of the immunisation campaign annual reaching for controlling the infection spreading. Regarding the dynamical behaviour of the model, our simulations shows that chaotic and periodic solutions, as well as bi-stable regions, depend on the vaccination parameters range. © 2024, CC BY.

关键词： Immunization

Exploration of optical, structural, and electrochemical properties of ZnO/MWCNTs nanocomposites for usage in supercapacitor

学校读者我要写书评

暂无评论

Journal of Energy Storage 2025年 125卷

作者： Ravina Srivastava, Garima Kumar, Shalendra Gautam, Nitin Kumar Dalela, Saurabh Ahmad, M. Ayaz Quraishi, A.M. Alvi, P.A. Department of Physical Science Banasthali Vidyapith Rajasthan 304022 India Department of Physics University of Petroleum & Energy Studies Dehradun India Department of Pure and Applied Physics University of Kota Rajasthan Kota India Department of Mathematics Physics and Statistics Faculty of Natural Sciences University of Guyana P.O. Box 101110 Georgetown Guyana Department of Electrical Engineering College of Engineering Qassim University Buraydah51452 Saudi Arabia

Motivated by the unique characteristics of ZnO nanoparticles and MWCNTs for use in energy devices, the study has been oriented towards the nanocomposites made of ZnO with different wt% MWCNTs. The ZnO/MWCNTs nanocomposites have been prepared by a simple solution mixing. The nanocomposites have been characterized to seek their usage in supercapacitor applications. XRD (X-Ray Diffraction) with Rietveld refinement, Raman, FTIR, photo-spectrometers, and FE-SEM with EDX (Energy Dispersive X-rays) have been utilized for getting information about structure, Raman bands, functional groups, optical bandgap, and surface characteristics, respectively. Moreover, cyclic voltammetry (CV), galvanostatic charge discharge (GCD), and electrochemical impedance spectroscopy (EIS) have been used to analyze the electrochemical properties. For 1 M KOH aqueous used as electrolyte in three electrode configurations, the nanocomposites display distinct capacitive behaviors. The highest specific capacitance has been noticed for ZnO/1 wt% MWCNTs electrode at 5 mV/s scan rate. From the CV curve, it is ∼25.54 F/g, and from the GCD curve, it is ∼6.9 F/g. Thus, the integration of ZnO with MWCNTs in nanocomposites enhances supercapacitor performance by combining high electrical conductivity with superior electrochemical properties. This synergy improves charge storage capacity and stability, making them ideal for advanced energy storage applications. © 2025 Elsevier Ltd

关键词： Cyclic voltammetry

Spectral dimension of simple random walk on a long-range percolation cluster

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Can, Van Hao Croydon, David A. Kumagai, Takashi Institute of Mathematics Vietnam Academy of Science and Technology 18 Hoang Quoc Viet Cau Giay Hanoi Viet Nam Department of Statistics and Data Science National University of Singapore 6 Science Drive 2 Singapore117546 Singapore Research Institute for Mathematical Sciences Kyoto University Kyoto606-8502 Japan Department of Mathematics Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo169-8555 Japan

Consider the long-range percolation model on the integer lattice Zd in which all nearest-neighbour edges are present and otherwise x and y are connected with probability qx,y := 1−exp(−|x−y|−s), independently of the state of other edges. Throughout the regime where the model yields a locally-finite graph, (i.e. for s > d,) we determine the spectral dimension of the associated simple random walk, apart from at the exceptional value d = 1, s = 2, where the spectral dimension is discontinuous. Towards this end, we present various on-diagonal heat kernel bounds, a number of which are new. In particular, the lower bounds are derived through the application of a general technique that utilises the translation invariance of the model. We highlight that, applying this general technique, we are able to partially extend our main result beyond the nearest-neighbour setting, and establish lower heat kernel bounds over the range of parameters s ∈ (d, 2d). We further note that our approach is applicable to short-range models as *** Codes 60K37 (primary), 35K05, 60J15, 60J35, 60J74, 82B43. Copyright © 2021, The Authors. All rights reserved.

关键词： Solvents

A Deep Neural Network for Cervical Cell Detection Based on Cytology Images

学校读者我要写书评

暂无评论

SSRN

SSRN 2022年

作者： Fang, Ming Lei, Xiujuan Liao, Bo Wu, Fang-Xiang Division of Biomedical Engineering University of Saskatchewan 57 Campus Drive SaskatoonSKS7N 5A9 Canada School of Computer Science Shaanxi Normal University 620 West Chang’an Avenue Shaanxi Xi’an710119 China School of Mathematics and Statistics Hainan Normal University 99 Longkun South Road Hainan Haikou571158 China Department of Mechanical Engineering Department of Computer Science University of Saskatchewan 57 Campus Drive SaskatoonSKS7N 5A9 Canada

Cervical cancer is one of the most common cancers among women. Fortunately, cervical cancer istreatable if it is diagnosed timely and administered appropriately. The death rate of cervical cancer hasbeen greatly reduced since Pap smear test was applied. However, Pap smear test is a time-consumingand error-prone process. Moreover, classifying cervical cells into different categories is clinicallymeaningful but also challenging in the field of cervical cancer detection. To address these concerns,computer-aided diagnosis systems with deep learning need to be designed to automatically analyzecervical cytology images. In this study, we construct a deep convolutional neural network with featurerepresentations learned via multiple kernels with different sizes to automatically classify cervicalcytology images, named DeepCELL. Firstly, we design three different basic modules of DeepCELL tocapture feature information via multiple kernels with different sizes. Then, we stack several such basicmodules to form the cervical cell classification model. Finally, we perform a series of experiments toevaluate the proposed method on two cervical cytology datasets: Herlev and SIPaKMeD. Our methodachieves the accuracy of 95.628%, precision of 95.685%, recall of 95.647% and F-score of 95.636% onSIPaKMeD dataset, which are the highest among all competing methods. Similarly, our method alsoachieves satisfactory result on Herlev dataset. In summary, extensive experimental results demonstratethat our proposed method has a promising performance in cervical cell image classification. © 2022, The Authors. All rights reserved.

关键词： Image classification

Finite-size effects on the convergence time in continuous-opinion dynamics

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Jo, Hang-Hyun Masuda, Naoki Department of Physics The Catholic University of Korea Bucheon14662 Korea Republic of Department of Mathematics State University of New York at Buffalo 14260-2900 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo 14260-5030 United States

We study finite-size effects on the convergence time in a continuous-opinion dynamics model. In the model, each individual's opinion is represented by a real number on a finite interval, e.g., [0;1], and a uniformly randomly chosen individual updates its opinion by partially mimicking the opinion of a uniformly randomly chosen neighbor. We numerically find that the characteristic time to the convergence increases as the system size increases according to a particular functional form in the case of lattice networks. In contrast, unless the individuals perfectly copy the opinion of their neighbors in each opinion updating, the convergence time is approximately independent of the system size in the case of regular random graphs, uncorrelated scale-free networks, and complete graphs. We also provide a mean-field analysis of the model to understand the case of the complete graph. Copyright © 2021, The Authors. All rights reserved.

关键词： Graph theory

Breaking Mechanical Holography in Combinatorial Metamaterials

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Sirote-Katz, Chaviva Palti, Ofri Spiro, Naomi Kálmán, Tamás Shokef, Yair Department of Biomedical Engineering Tel Aviv University Tel Aviv69978 Israel The Future Scientists Center Alpha Program Tel Aviv Youth University Tel Aviv69978 Israel University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Mathematics Institute of Science Tokyo H-214 2-12-1 Ookayama Tokyo Meguro-ku152-8551 Japan Hiroshima University Higashi-Hiroshima Hiroshima739-8526 Japan School of Mechanical Engineering Tel Aviv University Tel Aviv69978 Israel Center for Computational Molecular and Materials Science Tel Aviv University Tel Aviv69978 Israel Center for Physics and Chemistry of Living Systems Tel Aviv University Tel Aviv69978 Israel

Combinatorial mechanical metamaterials are made of anisotropic, flexible blocks, such that multiple metamaterials may be constructed using a single block type, and the system’s response strongly depends on the mutual orientations of the blocks within the lattice. We study a family of possible block types for the square, honeycomb, and cubic lattices. Blocks that are centrally symmetric induce holographic order, such that mechanical compatibility (meaning that blocks do not impede each other’s motion) implies bulk-boundary coupling. With them, one can design a compatible metamaterial that will deform in any desired texture only on part of its boundary. With blocks that break holographic order, we demonstrate how to design the deformation texture on the entire boundary. Correspondingly, the number of compatible holographic metamaterials scales exponentially with the boundary, while in non-holographic cases we show that it scales exponentially with the bulk. © 2024, CC BY.

关键词： Holography

The role of modularity in self-organisation dynamics in biological networks

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Siebert, Bram A. Hall, Cameron L. Gleeson, James P. Asllani, Malbor MACSI Department of Mathematics and Statistics University of Limerick LimerickV94 T9PX Ireland Department of Engineering Mathematics University of Bristol Bristol Woodland Road CliftonBS8 1UB United Kingdom

Interconnected ensembles of biological entities are perhaps some of the most complex systems that modern science has encountered so far. In particular, scientists have concentrated on understanding how the complexity of the interacting structure between different neurons, proteins or species inuences the functioning of their respective systems. It is well-established that many biological networks are constructed in a highly hierarchical way with two main properties: Short average paths that join two apparently distant nodes (neuronal, species, or protein patches) and a high proportion of nodes in modular aggregations. Although several hypotheses have been proposed so far, still little is known about the relation of the modules with the dynamical activity in such biological systems. Here we show that network modularity is a key ingredient for the formation of self-organising patterns of functional activity, independently of the topological peculiarities of the structure of the modules. In particular, we show that macroscopic spatial patterns at the modular scale can develop in this case, which may explain how spontaneous order in biological networks follows their modular structural organisation. Our results also show that Turing patterns on biological complex networks can be a signature of the presence of modular structure and consequently a possible protocol for community detection. We test our results on real-world networks to confirm the important role of modularity in creating macro-scale patterns. Copyright © 2020, The Authors. All rights reserved.

关键词： Proteins

Identifying Central Nodes in Multiplex Networks by Embracing Layer-Specific Heterogeneity via DomiRank

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Zheng, Ru Engsig, Marcus Tejedor, Alejandro Moreno, Yamir School of Mathematics and Statistics Central South University Changsha410083 China Universidad de Zaragoza Spain Directed Energy Research Centre Technology Innovation Institute Abu Dhabi United Arab Emirates Department of Theoretical Physics University of Zaragoza Spain Department of Civil and Environmental Engineering University of California Irvine United States

The robustness and resilience of complex systems are crucial for maintaining functionality amid disruptions or intentional attacks. Many such systems can be modeled as networks, where identifying structurally central nodes is essential for assessing their robustness and susceptibility to failure. Traditional centrality metrics often face challenges in identifying structurally important nodes in networks exhibiting heterogeneity at the network scale, with multilayer networks being a prime example of such networks. These metrics typically fail to balance the trade-off between capturing local layer-specific structures and integrating global multiplex connectivity. In this study, we extend DomiRank centrality, a metric that has been shown to effectively assess nodal importance across diverse monoplex topologies, to multiplex networks. Our approach combines layer-specific DomiRank calculations with a global contextualization step, incorporating multiplex-wide DomiRank scores to combine rankings. Through synthetic and real-world network studies, we demonstrate that our generalized DomiRank framework significantly improves the identification of key nodes in highly heterogeneous multiplex networks. This work advances centrality-based robustness assessments by addressing the fundamental trade-off between layer adaptability and multiplex-wide coherence. © 2025, CC BY.

关键词：

Approximate injectivity and smallness in metric-enriched categories

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Adámek, Jiří Rosický, Jiří Department of Mathematics Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Department of Theoretical Computer Science Technical University Braunschweig Germany Department of Mathematics and Statistics Masaryk University Faculty of Sciences Kotlářská 2 Brno611 37 Czech Republic

MSC Codes 18C35, 18D20, 46M10Properties of categories enriched over the category of metric spaces are investigated and applied to a study of well-known constructions of metric and Banach spaces. We prove e.g. that weighted limits and colimits exist in a metric-enriched category iff ordinary limits and colimits exist and Ε-(co)equalizers are given by Ε-(co)isometries for all Ε. An object is called approximately injective w.r.t. a morphism h: A → A′ iff morphisms from A into it are arbitrarily close to those morphisms that factorize through h. We investigate classes of objects specified by their approximate injectivity w.r.t. given morphisms. They are called approximate-injectivity classes. And we also study, conversely, classes of morphisms specified by the property that certain objects are approximately injective w.r.t. them. For every class of morphisms satisfying a mild smallness condition we prove that the corresponding approximate-injectivity class is weakly reflective, and we study the properties of the reflection morphisms. As an application we present a new categorical proof of the essential uniqueness of the Gurarii space. Copyright © 2020, The Authors. All rights reserved.

关键词： Banach spaces