LEADER 05381nam 2200649Ia 450 001 9910452302903321 005 20200520144314.0 010 $a981-4520-82-9 035 $a(CKB)2550000001096047 035 $a(EBL)1275565 035 $a(OCoLC)851695521 035 $a(SSID)ssj0000970791 035 $a(PQKBManifestationID)12431446 035 $a(PQKBTitleCode)TC0000970791 035 $a(PQKBWorkID)11020634 035 $a(PQKB)10459174 035 $a(MiAaPQ)EBC1275565 035 $a(WSP)00008846 035 $a(PPN)189547154 035 $a(Au-PeEL)EBL1275565 035 $a(CaPaEBR)ebr10731532 035 $a(CaONFJC)MIL502622 035 $a(EXLCZ)992550000001096047 100 $a20130718d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBIOMAT 2012$b[electronic resource] $eInternational Symposium on Mathematical and Computational Biology, Tempe, Arizona, USA, 6-10 November 2012 /$fedited by Rubem P Mondaini 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific$dc2013 215 $a1 online resource (406 p.) 300 $aDescription based upon print version of record. 311 $a981-4520-81-0 311 $a1-299-71371-8 320 $aIncludes bibliographical references and index. 327 $aContents; Preface; Editorial Board of the BIOMAT Consortium; Professor C.E.M. Pearce - In Memoriam; Mathematical Epidemiology; Compartmental Age of Infection Epidemic Models Fred Brauer; 1. Epidemic models with homogeneous mixing; 1.1. The simple Kermack-McKendrick model; 1.2. Models with disease deaths; 1.3. More complicated epidemic models; 2. The age of infection epidemic model; 2.1. The initial exponential growth rate; 3. Heterogeneous mixing age of infection models; 3.1. The final size relations; 3.2. The initial exponential growth rate; 4. Different models for the same epidemic 327 $aReferencesMathematical Modelling of Infectious Diseases; Lyme Pathogen Transmission in Tick Populations with Multiple Host Species Yijun Lou, Jianhong Wu, Xiaotian Wu; 1. Introduction; 2. The Model and Analysis; 2.1. The Tick Population Dynamics; 2.2. The Global Dynamics; 3. Numerical Simulations; 3.1. Climate Warming Effects; 3.2. Host Diversity Effects; 3.2.1. Effects of Adding Alternative Hosts without Interspecific Host Competition; 3.2.2. Effects of Adding the Alternative Host with Interspecific Host Competition; 3.3. Sensitivity Analysis; 4. Discussion; Acknowledgements; References 327 $aQuantifying the Risk of Mosquito-Borne Infections Basing on the Equilibrium Prevalence in Humans Marcos Amaku, Francisco A.B. Coutinho, Eduardo Massad1. Introduction; 2. The Model; 3. Estimating Risks; 4. Discussion; Acknowledgments; Conflicts of Interest; References; Seasonal Fluctuation in Tsetse Fly Populations and Human African Trypanosomiasis: A Mathematical Model T. Madsen, D.I. Wallace, N. Zupan; 1. Introduction; 2. Insect population submodel; 2.1. Insect Model Equations; 2.2. Explanation of Equations; 2.3. Temperature Model; 3. Analysis of model 327 $a3.1. Instability of the model with constant temperature D3.2. Sufficient insect death leads to stability; 3.3. Variable temperature as a switched system; 4. Numerical results of insect submodel; 4.1. Rogers' model revisited; 5. Sensitivity of the model; 6. Summary of results; References; Modelling Physiological Disorders; A Mathematical Model for the Immunotherapy of Advanced Prostate Cancer Travis Portz, Yang Kuang; 1. Introduction; 2. The Model; 3. Numerical Simulations; 4. Mathematical Analysis; 5. Discussion; Acknowledgements; References 327 $aSeizure Manifold of the Epileptic Brain: A State Space Reconstruction Approach Mujahid N. Syed, Pando G. Georgiev, Panos M. Pardalos1. Introduction; 2. Review; 2.1. Embedding; 3. Methodology; 3.1. Preprocessing; Filtering Noise; Identifying Stationarity; Identifying Determinism; 3.2. Manifold Generation; Time Delay Embedding; Embedding Dimension; Delay Time; 3.3. Measures of DDS; Fractal Dimension; Lyapunov Exponents; Kolmogorov Entropy; 3.4. Surrogate Tests; Surrogate Data Test 1; Surrogate Data Test 2; Surrogate Data Test 3; 3.5. Low Dimensional Phase Portraits; 4. Seizure Manifold 327 $a5. Criticism 330 $aThis is a book of a series on interdisciplinary topics of the Biological and Mathematical Sciences. The chapters correspond to selected papers on special research themes, which were presented at BIOMAT 2012 International Symposium on Mathematical and Computational Biology, in Tempe, Arizona, USA, November 6-10. This book contains state-of-the art articles on special research topics on mathematical biology, biological physics and mathematical modeling of biosystems; comprehensive reviews on interdisciplinary areas written by prominent leaders of scientific research groups. The treatment is both 606 $aBiology$xMathematical models$vCongresses 606 $aBiomathematics$vCongresses 608 $aElectronic books. 615 0$aBiology$xMathematical models 615 0$aBiomathematics 676 $a570.15118 701 $aMondaini$b R$g(Rubem)$0849245 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910452302903321 996 $aBIOMAT 2012$92261573 997 $aUNINA