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"Prologue: Lipidology - the science of lipids -- I THE OVERLOOKED MOLECULES -- Life from molecules -- Head and tail -- Oil and water -- Lipids speak the language of curvature -- A matter of softness -- Soft shells shape up -- Biological membranes - models and fashion -- II LIPIDS MAKE SENSE -- Lipids in bilayers - a stress-full and busy life -- The more we are together -- Lipids in Flatland -- Social Lipids -- Lively lipids provide for function -- Proteins at lipid mattresses -- III LIPIDS IN ACTION -- Cholesterol on the scene -- Lipids in charge -- Being smart - a _shy matter of fat -- Liquor and drugs - as a matter of fat-. Lipid eaters -- Powerful and strange lipids at work -- Survival by lipids -- Epilogue: Fat for Future -- Bibliography -- Sources for Figures. \u2013 Index."
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"title": "Analytic Number Theory, Approximation Theory, and Special Functions : In Honor of Hari M. Srivastava",
"abstract": [
"Part I. Analytic Number Theory, Combinatorics, and Special Sequences of Numbers and Polynomials -- The mean values of the Riemann Zeta function on the critical line (A. Ivi\u0107) -- Explicit bounds concerning non-trivial zeros of the Riemann Zeta function (M. Hassani) -- On the value-distribution of logarithmic derivatives of Dirichlet L-functions (Y. Ihara, K. Matsumoto) -- Multiple Gamma functions and their applications (J. Choi) -- On partition functions of hyperbolic three-geometry and associated Hilbert schemes (A.A. Bytsenko and E. Elizalde) -- Families of twisted Bernoulli numbers, twisted Bernoulli polynomials and their applications (Y. Simsek) -- Combinatorial interpretation of a generalized basic series (A.K. Agarwal, M. Rana) -- Identities for reciprocal binomials (A. Sofo) -- A note on q-Stirling numbers (M. Merca) -- Part II. Analytic Inequalities and Applications -- A survey on Cauchy-Bunyakovsky-Schwarz inequality for power series (A. Ibrahim, S.S. Dragomir) -- Topics in special functions III (G.D. Anderson, M. Vuorinen, X. Zhang) -- Completely monotone functions-a digest (M. Merkle) -- New applications of superquadracity (S. Abramovich) -- Green's operator and differential forms (S. Ding, Y. Xing) -- Multidimensional discrete Hilbert-type inequalities, operators and compositions (B. Yang) -- The function (bx-ax)/x: Ratio's properties (F. Qi, Q.-M. Luo, B.-N. Guo) -- On the approximation and bounds of the Gini mean difference (P. Cerone) -- On parametric nonconvex variational inequalities (M.A. Noor) -- Part III. Approximation of Functions and Quadratures -- Simultaneous approximation for Stancu type generalization of certain summation-integral typfe operators (N.K. Govil, V. Gupta) -- Korovkin type approximation theorem for functions of two variables via statistical summability (M. Mursaleen, S.A. Mohiuddine) -- Reflections on the Baker-Gammel-Wills (Pad\u00e9) conjecture (D.S. Lubinsky) -- Optimal quadrature formulas and interpolation splines minimizing the semi-norm in the Hilbert space K2(P2) (A.R. Hayotov, G.V. Milovanovi\u0107, K.M. Shadimetov) -- Numerical integration of highly oscillating functions (G.V. Milovanovi\u0107, M.P. Stani\u0107) -- Part IV. Orthogonality, Transformations and Applications -- Asymptotic reductions between the Wilson polynomials and the lower level polynomials of the Askey scheme (C. Ferreira, J.L. L\u00f3pez, E.P. Sinus\u00eda) -- On a direct Uvarov-Chihara problem and some extensions (K. Castillo, L. Garza, F. Marcell\u00e1n) -- On special cases of Boas-Buck type polynomial sequences (A.F. Loureiro, S. Yakubovich) -- Goursat's hypergeometric transformations, revisited (P.W. Karlsson) -- Convolutions product and differential and integro-differential equations (A. Kili\u00e7man) -- Orthogonally additive-additive functional equation (C. Park) -- Part V. Special and Complex Functions and Applications -- Alternating Mathieu series, Hilbert-Eisteinstein series and their generalized Omega functions (A. Baricz, P.L. Butzer, T.K. Pog\u00e1ny) -- Properties of the product of modified Bessel functions (A. Baricz, T.K. Pog\u00e1ny) -- Mapping properties of an integral operator involving Bessel functions (S. Porwal, D. Breaz) -- Poincar\u00e9 \u03b1-series for classical Schottky groups (V.V. Mityushev) -- Inclusion properties for certain classes of meromorphic multivalent functions (N.E. Cho) -- A journey from Gross-problem to Fujimoto-condition (I. Lahiri, A Banerjee) -- Index",
"This book, in honor of Hari M. Srivastava, discusses essential developments in mathematical research in a variety of problems. It contains thirty-five articles, written by eminent scientists from the international mathematical community, including both research and survey works. Subjects covered include analytic number theory, combinatorics, special sequences of numbers and polynomials, analytic inequalities and applications, approximation of functions and quadratures, orthogonality, and special and complex functions. The mathematical results and open problems discussed in this book are presented in a simple and self-contained manner. The book contains an overview of old and new results, methods, and theories toward the solution of longstanding problems in a wide scientific field, as well as new results in rapidly progressing areas of research. The book will be useful for researchers and graduate students in the fields of mathematics, physics, and other computational and applied sciences"
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"Abbreviations and Notation -- Philosophy of Targeted Learning in Data Science -- Part I: Introductory Chapters.- 1. The Statistical Estimation Problem in Complex Longitudinal Big Data.- 2. Longitudinal Causal Models.- 3. Super Learner for Longitudinal Problems.- 4. Longitudinal Targeted Maximum Likelihood Estimation (LTMLE).- 5. Understanding LTMLE.- 6. Why LTMLE?.- Part II:Additional Core Topics.- 7. One-Step TMLE.- IV: Observational Longitudinal Data.- 19. Super Learning in the ICU.- 20. Stochastic Single-Time-Point Interventions.- 21. Stochastic Multiple-Time-Point Interventions on Monitoring and Treatment.- 22. Collaborative LTMLE.- Part V: Optimal Dynamic Regimes.- 23. Targeted Adaptive Designs Learning the Optimal Dynamic Treatment.- 24. Targeted Learning of the Optimal Dynamic Treatment.- 25. Optimal Dynamic Treatments under Resource Constraints.- Part VI: Computing.- 26. ltmle() for R.- 27. Scaled Super Learner for R.- 28. Scaling CTMLE for Julia.- Part VII: Special Topics.-29. Data-Adaptive Target Parameters.- 30. Double Robust Inference for LTMLE.- 31. Higher-Order TMLE.- Appendix.- A. Online Targeted Learning Theory.- B. Computerization of the calculation of efficient influence curve.- C. TMLE applied to Capture/Recapture.- D. TMLE for High Dimensional Linear Regression.- E. TMLE of Causal Effect Based on Observing a Single Time Series",
"This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose\u2019s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics"
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