LEADER 05421nam 2200733Ia 450 001 9910139007803321 005 20200520144314.0 010 $a9783527652471 010 $a3527652477 010 $a9783527652457 010 $a3527652450 010 $a9781299464384 010 $a1299464386 010 $a9783527652488 010 $a3527652485 035 $a(CKB)2550000001019428 035 $a(EBL)1166788 035 $a(OCoLC)850209440 035 $a(SSID)ssj0000914433 035 $a(PQKBManifestationID)11958115 035 $a(PQKBTitleCode)TC0000914433 035 $a(PQKBWorkID)10863980 035 $a(PQKB)11437583 035 $a(MiAaPQ)EBC1166788 035 $a(Au-PeEL)EBL1166788 035 $a(CaPaEBR)ebr10687839 035 $a(CaONFJC)MIL477688 035 $a(PPN)176508880 035 $a(Perlego)1002111 035 $a(EXLCZ)992550000001019428 100 $a20130411d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aHandbook of biopolymer-based materials $efrom blends and composites to gels and complex networks /$fS. Thomas ...[et.al.] 205 $a1st ed. 210 $aWeinheim $cWiley$d2013 215 $a1 online resource (909 p.) 300 $aDescription based upon print version of record. 311 08$a9783527328840 311 08$a352732884X 327 $aHandbook of Biopolymer-Based Materials: From Blends and Composites to Gels and Complex Networks; Contents; Foreword; List of Contributors; 1 Biopolymers: State of the Art, New Challenges, and Opportunities; 1.1 Introduction; 1.2 Biopolymers: A Niche For Fundamental Research in Soft Matter Physics; 1.3 Biopolymers: An Endless Source of Applications; 1.4 Topics Covered by the Book; 1.5 Conclusions; References; 2 General Overview of Biopolymers: Structure, Properties, and Applications; 2.1 Introduction; 2.2 Plant Cell Wall Polysaccharides; 2.2.1 Cellulose; 2.2.1.1 Cellulose Extraction 327 $a2.2.1.2 Nanocellulose2.2.1.3 Microfibrillated Cellulose; 2.2.1.4 Cellulose Nanowhiskers; 2.2.2 Hemicelluloses; 2.2.2.1 Galactomannans; 2.2.2.2 Konjac Glucomannan; 2.2.2.3 Xylan; 2.2.2.4 Xyloglucan; 2.2.3 Pectins; 2.3 Biocomposites; 2.3.1 Natural Fiber Composites; 2.3.2 Cellulose Composites; 2.3.3 Cellulose-Polymer Interactions; 2.3.4 Semi-Solid Composites; 2.4 Future Outlook; References; 3 Biopolymers from Plants; 3.1 Introduction; 3.2 Lipid and Phenolic Biopolymers; 3.2.1 The Biopolymer Cutin; 3.2.1.1 Cutin Monomers: Biosynthesis and Physicochemical Characteristics 327 $a3.2.1.2 Molecular Architecture of Cutin3.2.1.3 Cutin Biosynthesis; 3.2.2 Lignin; 3.2.2.1 Monomer Precursors and Chemical Reactivity; 3.2.2.2 Lignin Biosynthesis; 3.2.3 Suberin; 3.2.3.1 Chemical Composition; 3.2.3.2 Biosynthesis and Fine Structure; 3.3 Carbohydrate Biopolymers: Polysaccharides; 3.3.1 Structural Polysaccharides; 3.3.1.1 Cellulose; 3.3.1.2 Hemicellulose; 3.3.1.3 Pectin; 3.3.2 Storage Polysaccharides; 3.3.2.1 Starch; 3.3.2.2 Fructans: Inulin; 3.3.3 Other: Gums (Guar Gum, Gum Arabic, Gum Karaya, Gum Tragacanth, and Locust Bean Gum); 3.4 Isoprene Biopolymers: Natural Rubber 327 $a3.4.1 cis-Polyisoprene3.4.1.1 Occurrence; 3.4.1.2 Composition, Structure, and Properties; 3.4.1.3 cis-1,4-Polyisoprene Biosynthesis; 3.4.1.4 Applications; 3.4.2 trans-Polyisoprene; 3.5 Concluding Remarks; References; 4 Bacterial Biopolymers and Genetically Engineered Biopolymers for Gel Systems Application; 4.1 Introduction; 4.1.1 Nucleic Acid Biopolymers: Central Dogma; 4.2 Microbial Polysaccharides as Biopolymers; 4.2.1 Synthesis and Applications; 4.3 Microbial Biopolymers as Drug Delivery Vehicle; 4.3.1 ?-Poly-L-Lysine (?-PL) and Its Applications 327 $a4.3.2 Polyhydroxyalkanoates and Its Applications4.4 Polyanhydrides; 4.5 Recombinant Protein Polymer Production; 4.6 Recombinant Genetically Engineered Biopolymer : Elastin; 4.7 Collagen as an Ideal Biopolymer; 4.7.1 Microbial Recombinant Collagens: Production in Pichia Pastoris; 4.8 Biopolymers for Gel System; 4.9 Hydrogels of Biopolymers for Regenerative Medicine; 4.9.1 Polysaccharide Hydrogels; 4.9.2 Cellulose-Derived Biopolymers-Based Hydrogels; 4.9.3 Protein Biopolymers-Based Hydrogels; 4.10 Supermacroporous Cryogel Matrix from Biopolymers; 4.10.1 Protein Cryogel 327 $a4.11 Biopolymers Impact on Environment 330 $aThis first systematic scientific reference in the area of micro and nanostructured biopolymer systems discusses in two volumes the morphology, structure, dynamics, properties and applications of all important biopolymers, as well as their blends, composites, interpenetrating networks and gels.Selected leading researchers from industry, academia, government and private research institutions around the globe comprehensively review recent accomplishments in the field. They examine the current state of the art, new challenges, opportunities and applications, discussing all the synthetic routes 606 $aBiopolymers 606 $aBiotechnology 615 0$aBiopolymers. 615 0$aBiotechnology. 676 $a572.3 676 $a572.33 701 $aThomas$b Sabu$0851308 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139007803321 996 $aHandbook of biopolymer-based materials$92214408 997 $aUNINA LEADER 04192nam 22007815 450 001 9910736996503321 005 20251008131351.0 010 $a9783031333903 010 $a303133390X 024 7 $a10.1007/978-3-031-33390-3 035 $a(CKB)27926266400041 035 $a(DE-He213)978-3-031-33390-3 035 $a(MiAaPQ)EBC30766894 035 $a(Au-PeEL)EBL30766894 035 $a(PPN)272261114 035 $a(MiAaPQ)EBC30766893 035 $a(Au-PeEL)EBL30766893 035 $a(MiAaPQ)EBC30673883 035 $a(Au-PeEL)EBL30673883 035 $a(OCoLC)1392163422 035 $a(EXLCZ)9927926266400041 100 $a20230802d2023 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied Statistical Learning $eWith Case Studies in Stata /$fby Matthias Schonlau 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource 225 1 $aStatistics and Computing,$x2197-1706 311 08$a9783031333897 320 $aIncludes bibliographical references and index. 327 $aPreface -- 1 Prologue -- 2 Statistical Learning: Concepts -- 3 Statistical Learning: Practical Aspects -- 4 Logistic Regression -- 5 Lasso and Friends -- 6 Working with Text Data -- 7 Nearest Neighbors -- 8 The Naive Bayes Classifier -- 9 Trees -- 10 Random Forests -- 11 Boosting -- 12 Support Vector Machines -- 13 Feature Engineering -- 14 Neural Networks -- 15 Stacking -- Index. 330 $aThis textbook provides an accessible overview of statistical learning methods and techniques, and includes case studies using the statistical software Stata. After introductory material on statistical learning concepts and practical aspects, each further chapter is devoted to a statistical learning algorithm or a group of related techniques. In particular, the book presents logistic regression, regularized linear models such as the Lasso, nearest neighbors, the Naive Bayes classifier, classification trees, random forests, boosting, support vector machines, feature engineering, neural networks, and stacking. It also explains how to construct n-gram variables from text data. Examples, conceptual exercises and exercises using software are featured throughout, together with case studies in Stata, mostly from the social sciences; true to the book?s goal to facilitate the use of modern methods of data science in the field. Although mainly intended for upper undergraduate and graduate students in the social sciences, given its applied nature, the book will equally appeal to readers from other disciplines, including the health sciences, statistics, engineering and computer science. 410 0$aStatistics and Computing,$x2197-1706 606 $aMachine learning 606 $aSocial sciences$xStatistical methods 606 $aStatistics 606 $aStatistics$xComputer programs 606 $aQuantitative research 606 $aStatistical Learning 606 $aMachine Learning 606 $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aStatistical Software 606 $aData Analysis and Big Data 615 0$aMachine learning. 615 0$aSocial sciences$xStatistical methods. 615 0$aStatistics. 615 0$aStatistics$xComputer programs. 615 0$aQuantitative research. 615 14$aStatistical Learning. 615 24$aMachine Learning. 615 24$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 615 24$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aStatistical Software. 615 24$aData Analysis and Big Data. 676 $a006.31 700 $aSchonlau$b Matthias$01741902 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736996503321 996 $aApplied Statistical Learning$94168286 997 $aUNINA