121 research outputs found

    A flashback on the dawn of the meteorite impact/extinction theory

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    Presented are my personal recollections on some of the major contributions by the Alvarez groups to the birth and development of the meteorite impact/extinction theory

    Linear chaos for the Quick-Thinking-Driver model

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s00233-015-9704-6In recent years, the topic of car-following has experimented an increased importance in traffic engineering and safety research. This has become a very interesting topic because of the development of driverless cars (Google driverless cars, http://en.wikipedia.org/wiki/Google_driverless_car).Driving models which describe the interaction between adjacent vehicles in the same lane have a big interest in simulation modeling, such as the Quick-Thinking-Driver model. A non-linear version of it can be given using the logistic map, and then chaos appears. We show that an infinite-dimensional version of the linear model presents a chaotic behaviour using the same approach as for studying chaos of death models of cell growth.The authors were supported by a grant from the FPU program of MEC and MEC Project MTM2013-47093-P.Conejero, JA.; Murillo Arcila, M.; Seoane-Sepúlveda, JB. (2016). Linear chaos for the Quick-Thinking-Driver model. Semigroup Forum. 92(2):486-493. https://doi.org/10.1007/s00233-015-9704-6S486493922Aroza, J., Peris, A.: Chaotic behaviour of birth-and-death models with proliferation. J. Differ. Equ. Appl. 18(4), 647–655 (2012)Banasiak, J., Lachowicz, M.: Chaos for a class of linear kinetic models. C. R. Acad. Sci. Paris Série II 329, 439–444 (2001)Banasiak, J., Lachowicz, M.: Topological chaos for birth-and-death-type models with proliferation. Math. Models Methods Appl. Sci. 12(6), 755–775 (2002)Banasiak, J., Lachowicz, M., Moszyński, M.: Topological chaos: when topology meets medicine. Appl. Math. Lett. 16(3), 303–308 (2003)Banasiak, J., Moszyński, M.: A generalization of Desch–Schappacher–Webb criteria for chaos. Discret. Contin. Dyn. Syst. 12(5), 959–972 (2005)Banasiak, J., Moszyński, M.: Dynamics of birth-and-death processes with proliferation–stability and chaos. Discret. Contin. Dyn. Syst. 29(1), 67–79 (2011)Banks, J., Brooks, J., Cairns, G., Davis, G., Stacey, P.: On Devaney’s definition of chaos. Am. Math. Mon. 99(4), 332–334 (1992)Barrachina, X., Conejero, J.A.: Devaney chaos and distributional chaos in the solution of certain partial differential equations. Abstr. Appl. Anal. 457,019, 11 (2012)Bermúdez, T., Bonilla, A., Martínez-Giménez, F., Peris, A.: Li-Yorke and distributionally chaotic operators. J. Math. Anal. Appl. 373(1), 83–93 (2011)Brackstone, M., McDonald, M.: Car-following: a historical review. Transp. Res. Part F 2(4), 181–196 (1999)Brzeźniak, Z., Dawidowicz, A.L.: On periodic solutions to the von Foerster–Lasota equation. Semigroup Forum 78, 118–137 (2009)Chandler, R.E., Herman, R., Montroll, E.W.: Traffic dynamics: studies in car following. Op. Res. 6, 165–184 (1958)Chung, C.C., Gartner, N.: Acceleration noise as a measure of effectiveness in the operation of traffic control systems. Operations Research Center. Massachusetts Institute of Technology. Cambridge (1973)CNN (2014) Driverless car tech gets serious at CES. http://edition.cnn.com/2014/01/09/tech/innovation/self-driving-cars-ces/ . Accessed 7 Apr 2014Conejero, J.A., Rodenas, F., Trujillo, M.: Chaos for the hyperbolic bioheat equation. Discret. Contin. Dyn. Syst. 35(2), 653–668 (2015)DARPA Grand Challenge. http://en.wikipedia.org/wiki/2005_DARPA_Grand_Challenge#2005_Grand_Challengede Laubenfels, R., Emamirad, H., Protopopescu, V.: Linear chaos and approximation. J. Approx. Theory 105(1), 176–187 (2000)Desch, W., Schappacher, W., Webb, G.F.: Hypercyclic and chaotic semigroups of linear operators. Ergod. Theory Dyn. Syst. 17(4), 793–819 (1997)El Mourchid, S.: The imaginary point spectrum and hypercyclicity. Semigroup Forum 73(2), 313–316 (2006)El Mourchid, S., Metafune, G., Rhandi, A., Voigt, J.: On the chaotic behaviour of size structured cell populations. J. Math. Anal. Appl. 339(2), 918–924 (2008)El Mourchid, S., Rhandi, A., Vogt, H., Voigt, J.: A sharp condition for the chaotic behaviour of a size structured cell population. Differ. Integral Equ. 22(7–8), 797–800 (2009)Engel, K.-J., Nagel, R.: One-Parameter Semigroups for Linear Evolution Equations. Graduate Texts in Mathematics, vol. 194. Springer, New York, 2000. With contributions by Brendle S., Campiti M., Hahn T., Metafune G., Nickel G., Pallara D., Perazzoli C., Rhandi A., Romanelli S., and Schnaubelt RGodefroy, G., Shapiro, J.H.: Operators with dense, invariant, cyclic vector manifolds. J. Funct. Anal. 98(2), 229–269 (1991)Greenshields, B.D.: The photographic method of studying traffic behavior. In: Proceedings of the 13th Annual Meeting of the Highway Research Board, pp. 382–399 (1934)Greenshields, B.D.: A study of traffic capacity. In: Proceedings of the 14th Annual Meeting of the Highway Research Board, pp. 448–477 (1935)Grosse-Erdmann, K.G., Peris Manguillot, A.: Linear Chaos. Universitext. Springer, London (2011)Herman, R., Montroll, E.W., Potts, R.B., Rothery, R.W.: Traffic dynamics: analysis of stability in car following. Op. Res. 7, 86–106 (1959)Helly, W.: Simulation of Bottleneckes in Single-Lane Traffic Flow. Research Laboratories, General Motors. Elsevier, New York (1953)Li, T.: Nonlinear dynamics of traffic jams. Phys. D 207(1–2), 41–51 (2005)Lo, S.C., Cho, H.J.: Chaos and control of discrete dynamic traffic model. J. Franklin Inst. 342(7), 839–851 (2005)Martínez-Giménez, F., Oprocha, P., Peris, A.: Distributional chaos for backward shifts. J. Math. Anal. Appl. 351(2), 607–615 (2009)Pipes, L.A.: An operational analysis of traffic dynamics. J. Appl. Phys. 24, 274–281 (1953

    Phylogenetic Relationships of the Marine Haplosclerida (Phylum Porifera) Employing Ribosomal (28S rRNA) and Mitochondrial (cox1, nad1) Gene Sequence Data

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    The systematics of the poriferan Order Haplosclerida (Class Demospongiae) has been under scrutiny for a number of years without resolution. Molecular data suggests that the order needs revision at all taxonomic levels. Here, we provide a comprehensive view of the phylogenetic relationships of the marine Haplosclerida using many species from across the order, and three gene regions. Gene trees generated using 28S rRNA, nad1 and cox1 gene data, under maximum likelihood and Bayesian approaches, are highly congruent and suggest the presence of four clades. Clade A is comprised primarily of species of Haliclona and Callyspongia, and clade B is comprised of H. simulans and H. vansoesti (Family Chalinidae), Amphimedon queenslandica (Family Niphatidae) and Tabulocalyx (Family Phloeodictyidae), Clade C is comprised primarily of members of the Families Petrosiidae and Niphatidae, while Clade D is comprised of Aka species. The polyphletic nature of the suborders, families and genera described in other studies is also found here

    Molecular Phylogeny of the Astrophorida (Porifera, Demospongiaep) Reveals an Unexpected High Level of Spicule Homoplasy

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    Background: The Astrophorida (Porifera, Demospongiae(rho)) is geographically and bathymetrically widely distributed. Systema Porifera currently includes five families in this order: Ancorinidae, Calthropellidae, Geodiidae, Pachastrellidae and Thrombidae. To date, molecular phylogenetic studies including Astrophorida species are scarce and offer limited sampling. Phylogenetic relationships within this order are therefore for the most part unknown and hypotheses based on morphology largely untested. Astrophorida taxa have very diverse spicule sets that make them a model of choice to investigate spicule evolution. Methodology/Principal Findings: With a sampling of 153 specimens (9 families, 29 genera, 89 species) covering the deep- and shallow-waters worldwide, this work presents the first comprehensive molecular phylogeny of the Astrophorida, using a cytochrome c oxidase subunit I (COI) gene partial sequence and the 59 end terminal part of the 28S rDNA gene (C1-D2 domains). The resulting tree suggested that i) the Astrophorida included some lithistid families and some Alectonidae species, ii) the sub-orders Euastrophorida and Streptosclerophorida were both polyphyletic, iii) the Geodiidae, the Ancorinidae and the Pachastrellidae were not monophyletic, iv) the Calthropellidae was part of the Geodiidae clade (Calthropella at least), and finally that v) many genera were polyphyletic (Ecionemia, Erylus, Poecillastra, Penares, Rhabdastrella, Stelletta and Vulcanella). Conclusion: The Astrophorida is a larger order than previously considered, comprising ca. 820 species. Based on these results, we propose new classifications for the Astrophorida using both the classical rank-based nomenclature (i.e., Linnaean classification) and the phylogenetic nomenclature following the PhyloCode, independent of taxonomic rank. A key to the Astrophorida families, sub-families and genera incertae sedis is also included. Incongruences between our molecular tree and the current classification can be explained by the banality of convergent evolution and secondary loss in spicule evolution. These processes have taken place many times, in all the major clades, for megascleres and microscleres

    Marine Biodiversity in the Caribbean: Regional Estimates and Distribution Patterns

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    This paper provides an analysis of the distribution patterns of marine biodiversity and summarizes the major activities of the Census of Marine Life program in the Caribbean region. The coastal Caribbean region is a large marine ecosystem (LME) characterized by coral reefs, mangroves, and seagrasses, but including other environments, such as sandy beaches and rocky shores. These tropical ecosystems incorporate a high diversity of associated flora and fauna, and the nations that border the Caribbean collectively encompass a major global marine biodiversity hot spot. We analyze the state of knowledge of marine biodiversity based on the geographic distribution of georeferenced species records and regional taxonomic lists. A total of 12,046 marine species are reported in this paper for the Caribbean region. These include representatives from 31 animal phyla, two plant phyla, one group of Chromista, and three groups of Protoctista. Sampling effort has been greatest in shallow, nearshore waters, where there is relatively good coverage of species records; offshore and deep environments have been less studied. Additionally, we found that the currently accepted classification of marine ecoregions of the Caribbean did not apply for the benthic distributions of five relatively well known taxonomic groups. Coastal species richness tends to concentrate along the Antillean arc (Cuba to the southernmost Antilles) and the northern coast of South America (Venezuela – Colombia), while no pattern can be observed in the deep sea with the available data. Several factors make it impossible to determine the extent to which these distribution patterns accurately reflect the true situation for marine biodiversity in general: (1) highly localized concentrations of collecting effort and a lack of collecting in many areas and ecosystems, (2) high variability among collecting methods, (3) limited taxonomic expertise for many groups, and (4) differing levels of activity in the study of different taxa
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