LEADER 03691nam 2200721Ia 450 001 9911137973203321 005 20251116174021.0 010 $a9786611372897 010 $a9781281372895 010 $a1281372897 010 $a9789812703248 010 $a9812703241 035 $a(CKB)1000000000334241 035 $a(EBL)296183 035 $a(OCoLC)476063963 035 $a(SSID)ssj0000209510 035 $a(PQKBManifestationID)12045025 035 $a(PQKBTitleCode)TC0000209510 035 $a(PQKBWorkID)10266013 035 $a(PQKB)11083940 035 $a(WSP)00000803 035 $a(Au-PeEL)EBL296183 035 $a(CaPaEBR)ebr10174115 035 $a(CaONFJC)MIL137289 035 $a(MiAaPQ)EBC296183 035 $a(Perlego)848297 035 $a(EXLCZ)991000000000334241 100 $a20070413d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNetworks of interacting machines $eproduction organization in complex industrial systems and biological cells /$feditors, Dieter Armbruster, Kunihiko Kaneko, Alexander S. Mikhailov 205 $a1st ed. 210 $aHackensack, NJ $cWorld Scientific$dc2005 215 $a1 online resource (280 p.) 225 1 $aWorld Scientific lecture notes in complex systems ;$vv. 3 300 $aDescription based upon print version of record. 311 08$a9789812564986 311 08$a9812564985 320 $aIncludes bibliographical references. 327 $aPreface; CONTENTS; 1 Continuum Models for Interacting Machines Dieter Armbruster, Pierre Degond, Christian Ringhofer; 2 Supply and Production Networks: From the Bullwhip Effect to Business Cycles Dirk Helbing, Stefan Lammer; 3 Managing Supply-Demand Networks in Semiconductor Manufacturing Karl Kempf; 4 Modelling Manufacturing Systems for Control: A Validation Study Erjen Lefeber, Roel van den Berg, J.E. Rooda; 5 Adaptive Networks of Production Processes Adam Ponzi; 6 Universal Statistics of Cells with Recursive Production Kunihiko Kanelco, Chikara Furusaura 327 $a7 Intracellular Networks of Interacting Molecular Machines Alexander S . Mikhailov8 Cell is Noisy Tatsuo Shibata; 9 An Intelligent Slime Mold: A Self-organizing System of Cell Shape and Information Tetsuo Ueda; 10 Communication and Structure within Networks Kim Sneppen, Martin Rosvall, Ala Trusina 330 $aThis review volume is devoted to a discussion of analogies and differences of complex production systems - natural, as in biological cells, or man-made, as in economic systems or industrial production. Taking this unified look at production is based on two observations: Cells and many biological networks are complex production units that have evolved to solve production problems in a reliable and optimal way in a highly stochastic environment. On the other hand, industrial production is becoming increasingly complex and often hard to predict. As a result, modeling and control of such productio 410 0$aWorld Scientific lecture notes in complex systems ;$vv. 3. 606 $aProduction management 606 $aProduction (Economic theory) 606 $aCell interaction 615 0$aProduction management. 615 0$aProduction (Economic theory) 615 0$aCell interaction. 676 $a658.5 700 $aArmbruster$b Dieter$058523 701 $aKaneko$b Kunihiko$022992 701 $aMikhailov$b A. S$g(Alexander S.),$f1950-$0622611 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911137973203321 996 $aNetworks of interacting machines$94838602 997 $aUNINA LEADER 04153nam 22007094a 450 001 9911148619903321 005 20251017110112.0 010 $a9786610180202 010 $a9780309168298 010 $a0309168295 010 $a9781280180200 010 $a128018020X 010 $a9780309507554 010 $a0309507553 035 $a(CKB)111069351130800 035 $a(OCoLC)52806850 035 $a(CaPaEBR)ebrary10032353 035 $a(SSID)ssj0000214200 035 $a(PQKBManifestationID)11173719 035 $a(PQKBTitleCode)TC0000214200 035 $a(PQKBWorkID)10156629 035 $a(PQKB)10606523 035 $a(MiAaPQ)EBC3375167 035 $a(Au-PeEL)EBL3375167 035 $a(CaPaEBR)ebr10032353 035 $a(CaONFJC)MIL18020 035 $a(OCoLC)923254431 035 $a(Perlego)4730684 035 $a(DNLM)1176986 035 $a(BIP)8101493 035 $a(EXLCZ)99111069351130800 100 $a20030106d2003 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOffspring $ehuman fertility behavior in biodemographic perspective /$fKenneth W. Wachter, Rodolfo A. Bulatao, editors 205 $a1st ed. 210 $aWashington, D.C. $cNational Academies Press$d2003 215 $a1 online resource (397 p.) 300 $a"Panel for the Workshop on the Biodemography of Fertility and Family Behavior." 300 $aThe papers contained in this volume were presented at the Workshop on the Biodemography of Fertility and Family Behavior, held at the National Academies in Washington, D.C., in June 2002"--p. viii. 311 08$a9780309087186 311 08$a030908718X 320 $aIncludes bibliographical references and index. 327 $aFront Matter -- Preface -- Contents -- Tables and Figures -- 1 Biodemography of Fertility and Family Formation -- 2 Genetic Influences on Fertility: Strengths and Limitations of Quantitative Inferences -- 3 Education, Fertility, and Heritability: Explaining a Paradox -- 4 The Neural Basis of Pair Bonding in a Monogamous Species: A Model for Understanding the Biological Basis of Human Behavior -- 5 Hormonal Mediation of Physiological and Behavioral Processes That Influence Fertility -- 6 Intraspecific Variability in Fertility and Offspring Survival in a Nonhuman Primate: Behavioral Control of Ecological and Social Sources -- 7 An Evolutionary and Ecological Analysis of Human Fertility, Mating Patterns, and Parental Investment -- 8 Sexually Antagonistic Coevolution: Theory, Evidence, and Implications for Patterns of Human Mating and Fertility -- 9 Pubertal Maturation, Adrenarche, and the Onset of Reproduction in Human Males -- 10 Energetics, Sociality, and Human Reproduction: Life History Theory in Real Life -- 11 Evolutionary Biology and Rational Choice in Models of Fertility -- 12 Reflections on Demographic, Evolutionary, and Genetic Approaches to the Study of Human Reproductive Behavior -- Contributors and Other Workshop Participants -- Index. 330 $aDespite recent advances in our understanding of the genetic basis of human behavior, little of this work has penetrated into formal demography. Very few demographers worry about how biological processes might affect voluntary behavior choices that have demographic consequences even though behavioral geneticists have documented genetics effects on variables such as parenting and divorce. Offspring: Human Fertility Behavior in Demographic Perspective brings together leading researchers from a wide variety of disciplines to review the state of research in this emerging field and to identify promising research directions for the future. 517 3 $aHuman fertility behavior in biodemographic perspective 606 $aFertility, Human$vCongresses 606 $aDemography$vCongresses 615 0$aFertility, Human 615 0$aDemography 676 $a304.6/32 701 $aWachter$b Kenneth W 701 $aBulatao$b Rodolfo A.$f1944- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911148619903321 997 $aUNINA