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Presents an annotated translation of his seminal publication on chemical thermodynamics.
In this historical volume Salvatore Califano traces the developments of ideas and theories in physical and theoretical chemistry throughout the 20th century. This seldom-told narrative provides details of topics from thermodynamics to atomic structure, radioactivity and quantum chemistry. Califano’s expertise as a physical chemist allows him to judge the historical developments from the point of view of modern chemistry. This detailed and unique historical narrative is fascinating for chemists working in the fields of physical chemistry and is also a useful resource for science historians who will enjoy access to material not previously dealt with in a coherent way.
An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online