LEADER 00892nam0-22003011i-450- 001 990007972760403321 005 20110209143050.0 010 $a3740000481 035 $a000797276 035 $aFED01000797276 035 $a(Aleph)000797276FED01 035 $a000797276 100 $a20041214d1987----km-y0itay50------ba 101 0 $ager 102 $aDE 105 $ay-------001yy 200 1 $aRömisches Recht und römische Rechtsgeschichte$feine Einführung von Gottfried Hartel und Elemer Polay 210 $aWeimar$cH. Bohlaus$d1987 215 $a268 p.$d22 cm 700 1$aHartel,$bGottfried$0423566 701 1$aPolay,$bElemer$0230647 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990007972760403321 952 $aDDR-VII D 012$b1447 ddr$fDDR$m21-3216 959 $aDDR 996 $aRömisches Recht und römische Rechtsgeschichte$9751692 997 $aUNINA LEADER 04708nam 2200553 450 001 9910698645803321 005 20230611131907.0 010 $a9783031094545$b(electronic bk.) 010 $z9783031094538 024 7 $a10.1007/978-3-031-09454-5 035 $a(MiAaPQ)EBC7236549 035 $a(Au-PeEL)EBL7236549 035 $a(DE-He213)978-3-031-09454-5 035 $a(OCoLC)1376457045 035 $a(PPN)269656448 035 $a(EXLCZ)9926435291300041 100 $a20230611h20232013 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematical modeling for epidemiology and ecology /$fGlenn Ledder 205 $aSecond edition. 210 1$aNew York, NY :$cSpringer Science+Business Media, LLC,$d[2023] 210 4$d©2013 215 $a1 online resource (376 pages) 225 1 $aSpringer Undergraduate Texts in Mathematics and Technology,$x1867-5514 311 08$aPrint version: Ledder, Glenn Mathematical Modeling for Epidemiology and Ecology Cham : Springer International Publishing AG,c2023 9783031094538 320 $aIncludes bibliographical references and index. 327 $aPart I Mathematical Modeling -- 1 Modeling in Biology -- 2 Empirical Modeling -- 3 Mechanistic Modeling. Part II Dynamical Systems -- 4 Dynamics of Single Populations -- 5 Discrete Linear Systems -- 6 Nonlinear Dynamical Systems -- Appendix A. Using Matlab and Octave -- Appendix B. Derivatives and Differentiation -- Appendix C. Nonlinear Optimization -- Appendix D. A Runge-Kutta Method for Numerical Solution of Differential Equations -- Appendix E. Scales and Dimensionless Parameters -- Appendix F. Approximating a Nonlinear System at an Equilibrium Point -- Appendix G. Best Practices in the Use of Algebra -- Hints and Answers to Selected Problems -- Index. 330 $aMathematical Modeling for Epidemiology and Ecology provides readers with the mathematical tools needed to understand and use mathematical models and read advanced mathematical biology books. It presents mathematics in biological contexts, focusing on the central mathematical ideas and the biological implications, with detailed explanations. The author assumes no mathematics background beyond elementary differential calculus. An introductory chapter on basic principles of mathematical modeling is followed by chapters on empirical modeling and mechanistic modeling. These chapters contain a thorough treatment of key ideas and techniques that are often neglected in mathematics books, such as the Akaike Information Criterion. The second half of the book focuses on analysis of dynamical systems, emphasizing tools to simplify analysis, such as the Routh-Hurwitz conditions and asymptotic analysis. Courses can be focused on either half of the book or thematically chosen material from both halves, such as a course on mathematical epidemiology. The biological content is self-contained and includes many topics in epidemiology and ecology. Some of this material appears in case studies that focus on a single detailed example, and some is based on recent research by the author on vaccination modeling and scenarios from the COVID-19 pandemic. The problem sets feature linked problems where one biological setting appears in multi-step problems that are sorted into the appropriate section, allowing readers to gradually develop complete investigations of topics such as HIV immunology and harvesting of natural resources. Some problems use programs written by the author for Matlab or Octave; these combine with more traditional mathematical exercises to give students a full set of tools for model analysis. Each chapter contains additional case studies in the form of projects with detailed directions. New appendices contain mathematical details on optimization, numerical solution of differential equations, scaling, linearization, and sophisticated use of elementary algebra to simplify problems. 410 0$aSpringer Undergraduate Texts in Mathematics and Technology,$x1867-5514 606 $aBiology$xMathematical models 606 $aComputational biology 606 $aEcology$xMathematical models 606 $aEpidemiology$xMathematical models 615 0$aBiology$xMathematical models. 615 0$aComputational biology. 615 0$aEcology$xMathematical models. 615 0$aEpidemiology$xMathematical models. 676 $a570.15118 700 $aLedder$b Glenn$01063205 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910698645803321 996 $aMathematical Modeling for Epidemiology and Ecology$93200490 997 $aUNINA LEADER 00787nam a2200229 i 4500 001 991004384838507536 005 20250616112006.0 008 250616s2017 it e 00000 ita 020 $a9788884198334 040 $aBibl. Dip.le Aggr. Scienze Giuridiche - Sez. Studi Giuridici$bita 082 04$a872.04 100 1 $aAlciato, Andrea$0544196 245 00$aFilargiro :$bcommedia /$cAndrea Alciato ; introduzione di Giovanni Rossi ; testo latino e versione italiana a cura di Raffaele Ruggiero 260 $aTorino :$bAragno,$c2017 300 $aXCII, 108 p. ;$c24 cm 490 1 $aBiblioteca Aragno 600 14$aAlciato, Andrea. Philargyrus 700 1 $aRuggiero, Raffaele 700 1 $aRossi, Giovanni 912 $a991004384838507536 996 $aFilargiro$94397199 997 $aUNISALENTO