1.

Record Nr.

UNINA990008646010403321

Autore

Grossmann, Atina

Titolo

Jews, germans and allies : close encounters in occupied Germany / Atina Grossmann

Pubbl/distr/stampa

Princeton : Princeton University Press, ©2007

ISBN

978-0-691-089713

Descrizione fisica

XX, 393 p. : ill. ; 24 cm

Disciplina

940.531814

Locazione

FSPBC

Collocazione

XIV B 2057

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9911105945603321

Autore

Rao V. S (Vallurupalli Sivaji), <1940, >

Titolo

Transgenic herbicide resistance in plants / / V.S. Rao, International Weed Scientist and Affiliate Member, Department of Plant Sciences, University of California, Davis, CA USA

Pubbl/distr/stampa

Boca Raton : , : CRC Press, , [2015]

©2015

ISBN

0-429-16892-6

1-4665-8738-5

9780429168925

Edizione

[1st ed.]

Descrizione fisica

1 online resource (480 p.)

Disciplina

631.5/233

631.5233

Soggetti

Transgenic plants

Herbicide-resistant crops

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

Front Cover; Dedication; Preface; Acknowledgment; Contents; Acronyms; The Author; 1. Introduction; 2. Herbicide Resistance; 3. Gene, Genome, and Crop Improvement; 4. Transgenic Engineering; 5. Transgenes in Herbicide and Insect Resistance; 6. Herbicide-Resistant Transgenic Crops; 7. Transgenic Phytoremediation of Herbicides and Explosives in Soil and Environment; 8. Adoption and Regulation of Transgenic Crops; 9. Benefi ts, Risks, and Issues Associated with Transgenic Crops and Foods; Appendix; Glossary; Color Plate Section

Sommario/riassunto

This book provides a comprehensive and in-depth discussion on the development of herbicide resistance during the past 50 years, emphasizing the biochemical pathways of herbicide resistance in weeds. It discusses the principles of plant genetics, different methods of genetic engineering, makingof transgenic plants, various transgenic crops conferred with herbicide resistance, evolution of weed, problems subsequent to growing of transgenic crops, benefits and risks of growing transgenic crops, and management of transgenic crops. Packed with up-to-date information, the book includes relevant refe



3.

Record Nr.

UNINA9910863146103321

Autore

Zaslavski Alexander J.

Titolo

The Projected Subgradient Algorithm in Convex Optimization / / by Alexander J. Zaslavski

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020

ISBN

3-030-60300-8

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (VI, 146 p.)

Collana

SpringerBriefs in Optimization, , 2191-575X

Disciplina

519.6

Soggetti

Mathematical optimization

Calculus of variations

Numerical analysis

Calculus of Variations and Optimization

Numerical Analysis

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

1. Introduction -- 2. Nonsmooth Convex Optimization -- 3. Extensions -- 4. Zero-sum Games with Two Players -- 5. Quasiconvex Optimization -- References.

Sommario/riassunto

This focused monograph presents a study of subgradient algorithms for constrained minimization problems in a Hilbert space. The book is of interest for experts in applications of optimization to engineering and economics. The goal is to obtain a good approximate solution of the problem in the presence of computational errors. The discussion takes into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for different steps are different, in general. The book is especially useful for the reader because it contains solutions to a number of difficult and interesting problems in the numerical optimization. The subgradient projection algorithm is one of the most important tools in optimization theory and its applications. An optimization problem is described by an objective function and a set of feasible points. For this algorithm each iteration consists of two steps. The first step requires a calculation of a subgradient of the objective function; the second requires a calculation



of a projection on the feasible set. The computational errors in each of these two steps are different. This book shows that the algorithm discussed, generates a good approximate solution, if all the computational errors are bounded from above by a small positive constant. Moreover, if computational errors for the two steps of the algorithm are known, one discovers an approximate solution and how many iterations one needs for this. In addition to their mathematical interest, the generalizations considered in this book have a significant practical meaning.