LEADER 04737nam 22008175 450 001 996466701103316 005 20211103131513.0 010 $a1-280-38226-0 010 $a9786613560179 010 $a90-481-3797-7 024 7 $a10.1007/978-90-481-3797-8 035 $a(CKB)2670000000028991 035 $a(SSID)ssj0000450394 035 $a(PQKBManifestationID)11271513 035 $a(PQKBTitleCode)TC0000450394 035 $a(PQKBWorkID)10444987 035 $a(PQKB)11068887 035 $a(DE-He213)978-90-481-3797-8 035 $a(MiAaPQ)EBC3065430 035 $a(PPN)149065558 035 $a(EXLCZ)992670000000028991 100 $a20100623d2010 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aSymmetries of Integro-Differential Equations$b[electronic resource] $eWith Applications in Mechanics and Plasma Physics /$fby Sergey V. Meleshko, Yurii N. Grigoriev, N. Kh. Ibragimov, Vladimir F. Kovalev 205 $a1st ed. 2010. 210 1$aDordrecht :$cSpringer Netherlands :$cImprint: Springer,$d2010. 215 $a1 online resource (XIII, 305 p.) 225 1 $aLecture Notes in Physics,$x0075-8450 ;$v806 300 $aBibliographic Level Mode of Issuance: Monograph 311 0 $a90-481-3796-9 320 $aIncludes bibliographical references and index. 327 $ato Group Analysis of Differential Equations -- to Group Analysis and Invariant Solutions of Integro-Differential Equations -- The Boltzmann Kinetic Equation and Various Models -- Plasma Kinetic Theory: Vlasov?Maxwell and Related Equations -- Symmetries of Stochastic Differential Equations -- Delay Differential Equations. 330 $aThis book aims to coherently present applications of group analysis to integro-differential equations in an accessible way. The book will be useful to both physicists and mathematicians interested in general methods to investigate nonlinear problems using symmetries. Differential and integro-differential equations, especially nonlinear, present the most effective way for describing complex processes. Therefore, methods to obtain exact solutions of differential equations play an important role in physics, applied mathematics and mechanics. This book provides an easy to follow, but comprehensive, description of the application of group analysis to integro-differential equations. The book is primarily designed to present both fundamental theoretical and algorithmic aspects of these methods. It introduces new applications and extensions of the group analysis method. The authors have designed a flexible text for postgraduate courses spanning a variety of topics. 410 0$aLecture Notes in Physics,$x0075-8450 ;$v806 606 $aMathematical physics 606 $aMechanics 606 $aAtoms 606 $aPhysics 606 $aPlasma (Ionized gases) 606 $aContinuum physics 606 $aTheoretical, Mathematical and Computational Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P19005 606 $aClassical Mechanics$3https://scigraph.springernature.com/ontologies/product-market-codes/P21018 606 $aAtoms and Molecules in Strong Fields, Laser Matter Interaction$3https://scigraph.springernature.com/ontologies/product-market-codes/P24025 606 $aMathematical Methods in Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P19013 606 $aPlasma Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P24040 606 $aClassical and Continuum Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P2100X 615 0$aMathematical physics. 615 0$aMechanics. 615 0$aAtoms. 615 0$aPhysics. 615 0$aPlasma (Ionized gases). 615 0$aContinuum physics. 615 14$aTheoretical, Mathematical and Computational Physics. 615 24$aClassical Mechanics. 615 24$aAtoms and Molecules in Strong Fields, Laser Matter Interaction. 615 24$aMathematical Methods in Physics. 615 24$aPlasma Physics. 615 24$aClassical and Continuum Physics. 676 $a530.15535 700 $aMeleshko$b Sergey V$4aut$4http://id.loc.gov/vocabulary/relators/aut$01057829 702 $aGrigoriev$b Yurii N$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aIbragimov$b N. Kh$g(Nail? Khai?rullovich)$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aKovalev$b Vladimir F$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a996466701103316 996 $aSymmetries of Integro-Differential Equations$92494826 997 $aUNISA LEADER 03086nam 22006133a 450 001 9910346851203321 005 20250203235427.0 010 $a9783038974345 010 $a303897434X 024 8 $a10.3390/books978-3-03897-434-5 035 $a(CKB)4920000000095155 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/42229 035 $a(ScCtBLL)c7695129-37ca-42ca-bd90-6a4c6e16fe0d 035 $a(OCoLC)1163814011 035 $a(oapen)doab42229 035 $a(EXLCZ)994920000000095155 100 $a20250203i20182019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aBiological Networks$fRudiyanto Gunawan, Neda Bagheri 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2018. 215 $a1 electronic resource (174 p.) 311 08$a9783038974338 311 08$a3038974331 330 $aNetworks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales-from ecosystems to individual cells and from years to milliseconds. For these networks, the concept "the whole is greater than the sum of its parts" applies as a norm rather than an exception. Meanwhile, continued advances in molecular biology and high-throughput technology have enabled a broad and systematic interrogation of whole-cell networks, allowing the investigation of biological processes and functions at unprecedented breadth and resolution-even down to the single-cell level. The explosion of biological data, especially molecular-level intracellular data, necessitates new paradigms for unraveling the complexity of biological networks and for understanding how biological functions emerge from such networks. These paradigms introduce new challenges related to the analysis of networks in which quantitative approaches such as machine learning and mathematical modeling play an indispensable role. The Special Issue on "Biological Networks" showcases advances in the development and application of in silico network modeling and analysis of biological systems. 606 $aBiology, life sciences$2bicssc 610 $aPathway crosstalk 610 $aAlzheimer?s disease 610 $aBioenergy crops 610 $aModel identification 610 $aMetabolic networks 610 $aHost?pathogen interactions 610 $aSingle cell 610 $aParameter sensitivity 610 $aTuberculosis 610 $aMultivariate statistical analysis 610 $aSystems biology 610 $aBiological networks 610 $aMathematical modeling 610 $aLignin biosynthesis 610 $aDesign of experiments 615 7$aBiology, life sciences 700 $aGunawan$b Rudiyanto$01787457 702 $aBagheri$b Neda 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910346851203321 996 $aBiological Networks$94320912 997 $aUNINA