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(Gastropoda: Littorinidae) in the Temperate Southern Hemisphere: the Genera Nodilittorina, Austrolittorina and Afrolittorina
© Copyright Australian Museum, 2004 Records of the Australian Museum (2004) Vol. 56: 75–122. ISSN 0067-1975 The Subfamily Littorininae (Gastropoda: Littorinidae) in the Temperate Southern Hemisphere: The Genera Nodilittorina, Austrolittorina and Afrolittorina DAVID G. REID* AND SUZANNE T. WILLIAMS Department of Zoology, The Natural History Museum, London SW7 5BD, United Kingdom [email protected] · [email protected] ABSTRACT. The littorinine gastropods of the temperate southern continents were formerly classified together with tropical species in the large genus Nodilittorina. Recently, molecular data have shown that they belong in three distinct genera, Austrolittorina, Afrolittorina and Nodilittorina, whereas the tropical species are members of a fourth genus, Echinolittorina. Austrolittorina contains 5 species: A. unifasciata in Australia, A. antipodum and A. cincta in New Zealand, and A. fernandezensis and A. araucana in western South America. Afrolittorina contains 4 species: A. africana and A. knysnaensis in southern Africa, and A. praetermissa and A. acutispira in Australia. Nodilittorina is monotypic, containing only the Australian N. pyramidalis. This paper presents the first detailed morphological descriptions of the African and Australasian species of these three southern genera (the eastern Pacific species have been described elsewhere). The species-level taxonomy of several of these has been confused in the past; Afrolittorina africana and A. knysnaensis are here distinguished as separate taxa; Austrolittorina antipodum is a distinct species and not a subspecies of A. unifasciata; Nodilittorina pyramidalis is separated from the tropical Echinolittorina trochoides with similar shell characters. In addition to descriptions of shells, radulae and reproductive anatomy, distribution maps are given, and the ecological literature reviewed. -
Opinion-Based Centrality in Multiplex Networks: a Convex Optimization Approach
Opinion-Based Centrality in Multiplex Networks: A Convex Optimization Approach Alexandre Reiffers-Masson and Vincent Labatut Laboratoire Informatique d'Avignon (LIA) EA 4128 Universit´ed'Avignon, France June 12, 2017 Abstract Most people simultaneously belong to several distinct social networks, in which their relations can be different. They have opinions about certain topics, which they share and spread on these networks, and are influenced by the opinions of other persons. In this paper, we build upon this observation to propose a new nodal centrality measure for multiplex networks. Our measure, called Opinion centrality, is based on a stochastic model representing opinion propagation dynamics in such a network. We formulate an optimization problem consisting in maximizing the opinion of the whole network when controlling an external influence able to affect each node individually. We find a mathematical closed form of this problem, and use its solution to derive our centrality measure. According to the opinion centrality, the more a node is worth investing external influence, and the more it is central. We perform an empirical study of the proposed centrality over a toy network, as well as a collection of real-world networks. Our measure is generally negatively correlated with existing multiplex centrality measures, and highlights different types of nodes, accordingly to its definition. Cite as: A. Reiffers-Masson & V. Labatut. Opinion-based Centrality in Multiplex Networks. Network Science, 5(2):213-234, 2017. Doi: 10.1017/nws.2017.7 1 Introduction In our ultra-connected world, many people simultaneously belong to several distinct social networks, in which their relations can be different. -
Modeling Customer Preferences Using Multidimensional Network Analysis in Engineering Design
Modeling customer preferences using multidimensional network analysis in engineering design Mingxian Wang1, Wei Chen1, Yun Huang2, Noshir S. Contractor2 and Yan Fu3 1 Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA 2 Science of Networks in Communities, Northwestern University, Evanston, IL 60208, USA 3 Global Data Insight and Analytics, Ford Motor Company, Dearborn, MI 48121, USA Abstract Motivated by overcoming the existing utility-based choice modeling approaches, we present a novel conceptual framework of multidimensional network analysis (MNA) for modeling customer preferences in supporting design decisions. In the proposed multidimensional customer–product network (MCPN), customer–product interactions are viewed as a socio-technical system where separate entities of `customers' and `products' are simultaneously modeled as two layers of a network, and multiple types of relations, such as consideration and purchase, product associations, and customer social interactions, are considered. We first introduce a unidimensional network where aggregated customer preferences and product similarities are analyzed to inform designers about the implied product competitions and market segments. We then extend the network to a multidimensional structure where customer social interactions are introduced for evaluating social influence on heterogeneous product preferences. Beyond the traditional descriptive analysis used in network analysis, we employ the exponential random graph model (ERGM) as a unified statistical -
Multilayer Networks
Journal of Complex Networks (2014) 2, 203–271 doi:10.1093/comnet/cnu016 Advance Access publication on 14 July 2014 Multilayer networks Mikko Kivelä Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK Alex Arenas Departament d’Enginyeria Informática i Matemátiques, Universitat Rovira I Virgili, 43007 Tarragona, Spain Marc Barthelemy Downloaded from Institut de Physique Théorique, CEA, CNRS-URA 2306, F-91191, Gif-sur-Yvette, France and Centre d’Analyse et de Mathématiques Sociales, EHESS, 190-198 avenue de France, 75244 Paris, France James P. Gleeson MACSI, Department of Mathematics & Statistics, University of Limerick, Limerick, Ireland http://comnet.oxfordjournals.org/ Yamir Moreno Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, Zaragoza 50018, Spain and Department of Theoretical Physics, University of Zaragoza, Zaragoza 50009, Spain and Mason A. Porter† Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, by guest on August 21, 2014 Oxford OX2 6GG, UK and CABDyN Complexity Centre, University of Oxford, Oxford OX1 1HP, UK †Corresponding author. Email: [email protected] Edited by: Ernesto Estrada [Received on 16 October 2013; accepted on 23 April 2014] In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such ‘multilayer’ features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize ‘traditional’ network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. -
Evolving Networks and Social Network Analysis Methods And
DOI: 10.5772/intechopen.79041 ProvisionalChapter chapter 7 Evolving Networks andand SocialSocial NetworkNetwork AnalysisAnalysis Methods and Techniques Mário Cordeiro, Rui P. Sarmento,Sarmento, PavelPavel BrazdilBrazdil andand João Gama Additional information isis available atat thethe endend ofof thethe chapterchapter http://dx.doi.org/10.5772/intechopen.79041 Abstract Evolving networks by definition are networks that change as a function of time. They are a natural extension of network science since almost all real-world networks evolve over time, either by adding or by removing nodes or links over time: elementary actor-level network measures like network centrality change as a function of time, popularity and influence of individuals grow or fade depending on processes, and events occur in net- works during time intervals. Other problems such as network-level statistics computation, link prediction, community detection, and visualization gain additional research impor- tance when applied to dynamic online social networks (OSNs). Due to their temporal dimension, rapid growth of users, velocity of changes in networks, and amount of data that these OSNs generate, effective and efficient methods and techniques for small static networks are now required to scale and deal with the temporal dimension in case of streaming settings. This chapter reviews the state of the art in selected aspects of evolving social networks presenting open research challenges related to OSNs. The challenges suggest that significant further research is required in evolving social networks, i.e., existent methods, techniques, and algorithms must be rethought and designed toward incremental and dynamic versions that allow the efficient analysis of evolving networks. Keywords: evolving networks, social network analysis 1. -
Moluscos Del Perú
Rev. Biol. Trop. 51 (Suppl. 3): 225-284, 2003 www.ucr.ac.cr www.ots.ac.cr www.ots.duke.edu Moluscos del Perú Rina Ramírez1, Carlos Paredes1, 2 y José Arenas3 1 Museo de Historia Natural, Universidad Nacional Mayor de San Marcos. Avenida Arenales 1256, Jesús María. Apartado 14-0434, Lima-14, Perú. 2 Laboratorio de Invertebrados Acuáticos, Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Apartado 11-0058, Lima-11, Perú. 3 Laboratorio de Parasitología, Facultad de Ciencias Biológicas, Universidad Ricardo Palma. Av. Benavides 5400, Surco. P.O. Box 18-131. Lima, Perú. Abstract: Peru is an ecologically diverse country, with 84 life zones in the Holdridge system and 18 ecological regions (including two marine). 1910 molluscan species have been recorded. The highest number corresponds to the sea: 570 gastropods, 370 bivalves, 36 cephalopods, 34 polyplacoforans, 3 monoplacophorans, 3 scaphopods and 2 aplacophorans (total 1018 species). The most diverse families are Veneridae (57spp.), Muricidae (47spp.), Collumbellidae (40 spp.) and Tellinidae (37 spp.). Biogeographically, 56 % of marine species are Panamic, 11 % Peruvian and the rest occurs in both provinces; 73 marine species are endemic to Peru. Land molluscs include 763 species, 2.54 % of the global estimate and 38 % of the South American esti- mate. The most biodiverse families are Bulimulidae with 424 spp., Clausiliidae with 75 spp. and Systrophiidae with 55 spp. In contrast, only 129 freshwater species have been reported, 35 endemics (mainly hydrobiids with 14 spp. The paper includes an overview of biogeography, ecology, use, history of research efforts and conser- vation; as well as indication of areas and species that are in greater need of study. -
Multidimensional Network Analysis
Universita` degli Studi di Pisa Dipartimento di Informatica Dottorato di Ricerca in Informatica Ph.D. Thesis Multidimensional Network Analysis Michele Coscia Supervisor Supervisor Fosca Giannotti Dino Pedreschi May 9, 2012 Abstract This thesis is focused on the study of multidimensional networks. A multidimensional network is a network in which among the nodes there may be multiple different qualitative and quantitative relations. Traditionally, complex network analysis has focused on networks with only one kind of relation. Even with this constraint, monodimensional networks posed many analytic challenges, being representations of ubiquitous complex systems in nature. However, it is a matter of common experience that the constraint of considering only one single relation at a time limits the set of real world phenomena that can be represented with complex networks. When multiple different relations act at the same time, traditional complex network analysis cannot provide suitable an- alytic tools. To provide the suitable tools for this scenario is exactly the aim of this thesis: the creation and study of a Multidimensional Network Analysis, to extend the toolbox of complex network analysis and grasp the complexity of real world phenomena. The urgency and need for a multidimensional network analysis is here presented, along with an empirical proof of the ubiquity of this multifaceted reality in different complex networks, and some related works that in the last two years were proposed in this novel setting, yet to be systematically defined. Then, we tackle the foundations of the multidimensional setting at different levels, both by looking at the basic exten- sions of the known model and by developing novel algorithms and frameworks for well-understood and useful problems, such as community discovery (our main case study), temporal analysis, link prediction and more. -
Design and Analysis of Graph-Based Codes Using Algebraic Lifts and Decoding Networks Allison Beemer University of Nebraska - Lincoln, [email protected]
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Dissertations, Theses, and Student Research Papers Mathematics, Department of in Mathematics 3-2018 Design and Analysis of Graph-based Codes Using Algebraic Lifts and Decoding Networks Allison Beemer University of Nebraska - Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/mathstudent Part of the Discrete Mathematics and Combinatorics Commons, and the Other Mathematics Commons Beemer, Allison, "Design and Analysis of Graph-based Codes Using Algebraic Lifts nda Decoding Networks" (2018). Dissertations, Theses, and Student Research Papers in Mathematics. 87. https://digitalcommons.unl.edu/mathstudent/87 This Article is brought to you for free and open access by the Mathematics, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Dissertations, Theses, and Student Research Papers in Mathematics by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. DESIGN AND ANALYSIS OF GRAPH-BASED CODES USING ALGEBRAIC LIFTS AND DECODING NETWORKS by Allison Beemer A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfilment of Requirements For the Degree of Doctor of Philosophy Major: Mathematics Under the Supervision of Professor Christine A. Kelley Lincoln, Nebraska March, 2018 DESIGN AND ANALYSIS OF GRAPH-BASED CODES USING ALGEBRAIC LIFTS AND DECODING NETWORKS Allison Beemer, Ph.D. University of Nebraska, 2018 Adviser: Christine A. Kelley Error-correcting codes seek to address the problem of transmitting information effi- ciently and reliably across noisy channels. Among the most competitive codes developed in the last 70 years are low-density parity-check (LDPC) codes, a class of codes whose structure may be represented by sparse bipartite graphs. -
The Key Technology of Computer Network Vulnerability Assessment Based on Neural Network
Wang J Wireless Com Network (2020) 2020:222 https://doi.org/10.1186/s13638-020-01841-y RESEARCH Open Access The key technology of computer network vulnerability assessment based on neural network Shaoqiang Wang* *Correspondence: [email protected] Abstract School of Computer With the wide application of computer network, network security has attracted more Science and Technology, Changchun University, and more attention. The main reason why all kinds of attacks on the network can pose Changchun 130022, Jilin, a great threat to the network security is the vulnerability of the computer network China system itself. Introducing neural network technology into computer network vulner- ability assessment can give full play to the advantages of neural network in network vulnerability assessment. The purpose of this article is by organizing feature map neural network, and the combination of multilayer feedforward neural network, the training samples using SOM neural network clustering, the result of clustering are added to the original training samples and set a certain weight, based on the weighted iterative update ceaselessly, in order to improve the convergence speed of BP neural network. On the BP neural network, algorithm for LM algorithm was improved, the large matrix inversion in the LM algorithm using the parallel algorithm method is improved for solving system of linear equations, and use of computer network vulnerability assess- ment as the computer simulation and analysis on the actual example designs a set of computer network vulnerability assessment scheme, fnally the vulnerability is lower than 0.75, which is benefcial to research on related theory and application to provide the reference and help. -
Multidimensional Analysis of Complex Networks
Alma Mater Studiorum Universita’ di Bologna Computer Science Department Ph.D. Thesis Multidimensional analysis of complex networks Possamai Lino Ph.D. Supervisors: Prof. Massimo Marchiori Prof. Alessandro Sperduti Ph.D. Coordinator: Prof. Maurizio Gabbrielli DOTTORATO DI RICERCA IN INFORMATICA - Ciclo XXV Settore Concorsuale di afferenza: 01/B1 Settore Scientifico disciplinare: INF/01 Esame Finale Anno 2013 Ai miei genitori. Abstract The analysis of Complex Networks turn out to be a very promising field of research, testified by many research projects and works that span different fields. Until recently, those analysis have been usually focused on deeply characterize a single aspect of the system, therefore a study that considers many informative axes along with a network evolve is lacking. In this Thesis, we propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions of a system, namely space and time. In order to achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network behavior as a whole. By focusing on space dimension, we were able to characterize spatial alteration in terms of abstraction levels. We propose a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We call this analysis telescopic as it recalls the magnification and reduction process of the lens. Through this line of research we have successfully verified that statistical indicators, that are frequently used in many complex networks researches, depends strongly on the granularity (i.e., the detail level) with which a system is described and on the class of networks considered. -
Research Article Multilayer Network-Based Production Flow Analysis
Hindawi Complexity Volume 2018, Article ID 6203754, 15 pages https://doi.org/10.1155/2018/6203754 Research Article Multilayer Network-Based Production Flow Analysis Tamás Ruppert, Gergely Honti, and János Abonyi MTA-PE “Lendület” Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, Veszprém, Hungary Correspondence should be addressed to János Abonyi; [email protected] Received 24 February 2018; Revised 18 May 2018; Accepted 27 May 2018; Published 16 July 2018 Academic Editor: Dimitris Mourtzis Copyright © 2018 Tamás Ruppert et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A multilayer network model for the exploratory analysis of production technologies is proposed. To represent the relationship between products, parts, machines, resources, operators, and skills, standardized production and product-relevant data are transformed into a set of bi- and multipartite networks. This representation is beneficial in production flow analysis (PFA) that is used to identify improvement opportunities by grouping similar groups of products, components, and machines. It is demonstrated that the goal-oriented mapping and modularity-based clustering of multilayer networks can serve as a readily applicable and interpretable decision support tool for PFA, and the analysis of the degrees and correlations of a node can identify critically important skills and resources. The applicability of the proposed methodology is demonstrated by a well-documented benchmark problem of a wire-harness production process. The results confirm that the proposed multilayer network can support the standardized integration of production-relevant data and exploratory analysis of strongly interconnected production systems. -
Patrones Filogeográficos De Dos Moluscos Intermareales a Lo Largo De Un Gradiente Biogeográfico En La Costa Norte Del Perú
PATRONES FILOGEOGRÁFICOS DE DOS MOLUSCOS INTERMAREALES A LO LARGO DE UN GRADIENTE BIOGEOGRÁFICO EN LA COSTA NORTE DEL PERÚ TESIS PARA OPTAR EL GRADO DE MAESTRO EN CIENCIAS DEL MAR BACH. SERGIO BARAHONA PADILLA LIMA – PERÚ 2017 ASESOR DE LA TESIS Aldo Santiago Pacheco Velásquez PhD. en Ciencias Naturales Profesor invitado de la Maestría en Ciencias del Mar de la Universidad Peruana Cayetano Heredia Laboratorio CENSOR, Instituto de Ciencias Naturales Alexander Von Humboldt, Universidad de Antofagasta, Chile CO-ASESORA DE LA TESIS Ximena Vélez Zuazo PhD. en Ecología y Evolución Directora del Programa Marino de Monitoreo y Evaluación de la Biodiversidad (BMAP) del Instituto Smithsonian de Biología de la Conservación, Perú JURADO EVALUADOR DE LA TESIS Dr. Dimitri Gutiérrez Aguilar (Presidente) Dr. Pedro Tapia Ormeño (Secretario) Dr. Jorge Rodríguez Bailón (Vocal) DEDICATORIA Esta tesis está dedicada a mi amada familia, a mis dos padres y a mi hermana, quienes estuvieron, están y estarán siempre allí, apoyándome y dándome ánimos para seguir adelante en esta ardua pero satisfactoria labor que es la investigación. AGRADECIMIENTOS La presente tesis fue financiada por la beca de estudios de posgrado otorgada por FONDECYT (Fondo Nacional de Desarrollo Científica, Tecnológico y e Innovación Tecnológica), CIENCIACTIVA y el Consejo Nacional de Ciencia y Tecnología (CONCYTEC) del Ministerio de Educación del Perú, en el marco del programa de posgrado de Ciencias del Mar de la Universidad Peruana Cayetano Heredia. A mi asesor, Aldo Pacheco Velásquez, por su paciencia y significativos aportes de conocimiento que permitieron atacar la tesis desde varias perspectivas. A mi co- asesora Ximena Vélez-Zuazo, a quien considero una hermana mayor, por el constante ánimo y soporte durante la ejecución de la tesis.