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1. |
Record Nr. |
UNISA996418438103316 |
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Autore |
Moruzzi Giovanni |
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Titolo |
Essential Python for the Physicist [[electronic resource] /] / by Giovanni Moruzzi |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (304 pages) |
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Classificazione |
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Disciplina |
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Soggetti |
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Physics |
Computer programming |
Numerical analysis |
Computer graphics |
Numerical and Computational Physics, Simulation |
Programming Techniques |
Numeric Computing |
Computer Graphics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- 1 Python Basics and the Interactive Mode -- 2 Python Scripts -- 3 Plotting with Matplotlib -- 4 Numerical Solution of Equations -- Numerical Solution of Ordinary Dierential Equations (ODE) -- 6 Tkinter Graphics -- 7 Tkinter Animation -- 8. Classes -- 9 Appendix. |
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Sommario/riassunto |
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This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is |
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dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton’s equations) and quantum mechanics (Schroedinger’s equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions at two boundaries is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython. |
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2. |
Record Nr. |
UNINA9910975309703321 |
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Titolo |
Allocating federal funds for state programs for English language learners / / National Research Council of the National Academies |
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Pubbl/distr/stampa |
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Washington, D.C., : National Academies Press, 2011 |
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ISBN |
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9786613213396 |
9780309216739 |
0309216737 |
9781283213394 |
1283213397 |
9780309186599 |
0309186595 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (239 p.) |
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Disciplina |
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Soggetti |
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English language - Study and teaching - Foreign speakers - United States - Finance |
Education - Finance |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"Panel to Review Alternative Data Sources for the Limited-English Proficiency Allocation Formula under Title III, Part A, Elementary and Secondary Education Act, Committee on National Statistics and Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education." |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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""Front Matter""; ""Acknowledgments""; ""Contents""; ""Tables, Figures, and Boxes""; ""Acronyms and Abbreviations""; ""Summary""; ""1 Introduction""; ""2 American Community Survey Estimates""; ""3 Quality and Comparability of State Tests of English Language Proficiency""; ""4 State Procedures for Identifying and Classifying English Language Learners""; ""5 Comparison of American Community Survey Estimates and State Counts""; ""6 Comparability of Estimates of Immigrant School-Age Children""; ""7 Decision Criteria and Recommendations""; ""References and Bibliography"" |
""Appendix A: Review of English Language Proficiency Tests""""Appendix B: Biographical Sketches of Panel Members and Staff""; ""Committee on National Statistics""; ""Board on Testing and Assessment"" |
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Sommario/riassunto |
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As the United States continues to be a nation of immigrants and their children, the nation's school systems face increased enrollments of students whose primary language is not English. With the 2001 reauthorization of the Elementary and Secondary Education Act (ESEA) in the No Child Left Behind Act (NCLB), the allocation of federal funds for programs to assist these students to be proficient in English became formula-based: 80 percent on the basis of the population of children with limited English proficiency and 20 percent on the basis of the population of recently immigrated children and youth. Title III of NCLB directs the U.S. Department of Education to allocate funds on the basis of the more accurate of two allowable data sources: the number of students reported to the federal government by each state education agency or data from the American Community Survey (ACS). The department determined that the ACS estimates are more accurate, and since 2005, those data have been basis for the federal distribution of Title III funds. Subsequently, analyses of the two data sources have raised concerns about that decision, especially because the two allowable data sources would allocate quite different amounts to the states. In addition, while shortcomings were noted in the data provided by the states, the ACS estimates were shown to fluctuate between years, causing concern among the states about the unpredictability and unevenness of program funding. In this context, the U.S. Department of Education commissioned the National Research Council to address the accuracy of the estimates from the two data sources and the factors that influence the estimates. The resulting book also considers means of increasing the accuracy of the data sources or alternative data sources that could be used for allocation purposes. |
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