Culture, in fact, also plays an important role in science which is, per se, a multitude of different cultures. The book attempts to build a bridge across three cultures: mathematical statistics, quantum theory and chemometrical methods. Of course, these three domains should not be taken as equals in any sense. But the book holds the important claim that it is possible to develop a common language which, at least to a certain extent, can create direct links and build bridges. From this point of departure, the book will be of interest to the following three types of scientists OCo statisticians, quantum physicists and chemometricians OCo and in particular, statisticians and physicists who are interested in interdisciplinary research. Written at a level that is accessible to general readers, not only the academics, the book will appeal to graduate students and mathematically educated persons of all disciplines as well as philosophers, pure and applied mathematicians, and the general public. Sample Chapter(s). Chapter 1: The Basic Elements (1,433 KB). Contents: The Basic Elements; Statistical Theory and Practice; Statistical Inference Under Symmetry; The Transition from Statistics to Quantum Theory; Quantum Mechanics from a Statistical Basis; Further Development of Quantum Mechanics; Decisions in Statistics; Multivariate Data Analysis and Statistics; Quantum Mechanics and the Diversity of Concepts. Readership: Graduate students and researchers in the field of statistics and mathematical physics."

This book discusses a link between statistical theory and quantum theory based on the concept of epistemic processes. The latter are processes, such as statistical investigations or quantum mechanical measurements, that can be used to obtain knowledge about something. Various topics in quantum theory are addressed, including the construction of a Hilbert space from reasonable assumptions and an interpretation of quantum states. Separate derivations of the Born formula and the one-dimensional Schrödinger equation are given. In concrete terms, a Hilbert space can be constructed under some technical assumptions associated with situations where there are two conceptual variables that can be seen as maximally accessible. Then to every accessible conceptual variable there corresponds an operator on this Hilbert space, and if the variables take a finite number of values, the eigenspaces/eigenvectors of these operators correspond to specific questions in nature together with sharp answers to these questions. This paves a new way to the foundations of quantum theory. The resulting interpretation of quantum mechanics is related to Hervé Zwirn's recent Convivial Solipsism, but it also has some relations to Quantum Bayesianism and to Rovelli's relational quantum mechanics. Niels Bohr's concept of complementarity plays an important role. Philosophical implications of this approach to quantum theory are discussed, including consequences for macroscopic settings. The book will benefit a broad readership, including physicists and statisticians interested in the foundations of their disciplines, philosophers of science and graduate students, and anyone with a reasonably good background in mathematics and an open mind.

Mathematical modelling of activated sludge systems is used widely for plant design, optimisation, training, controller design and research. The quality of simulation studies varies depending on the project objectives, finances and expertise available. Consideration has to be given to the model accuracy and the amount of time required carrying out a simulation study to produce the desired accuracy. Inconsistent approaches and insufficient documentation make quality assessment and comparison of simulation results difficult or almost impossible. A general framework for the application of activated sludge models is needed in order to overcome these obstacles. The genesis of the Good Modelling Practice (GMP) Task Group lies in a workshop held at the 4th IWA World Water Congress in Marrakech, Morocco where members of research groups active in wastewater treatment modelling came together to develop plans to synthesize the best practices of modellers from all over the world. The most cited protocols were included in the work, amongst others from: HSG (Hochschulgruppe), STOWA, BIOMATH and WERF. The goal of the group is to set up an internationally accepted framework to deal with the ASM type models in practice. This framework shall make modelling more straightforward and systematic to use especially for practitioners and consultants. Additionally, it shall help to define quality levels for simulation results, a procedure to assess this quality and to assist in the proper use of the models. The framework will describe a methodology for goal-oriented application of activated sludge models demonstrated by means of a concise guideline about the procedure of a simulation study and some illustrative case studies. The case studies shall give examples for the required data quality and quantity and the effort for calibration/validation with respect to a defined goal. The final report will include an extended appendix with additional information and details of methodologies. Additional features in Guidelines for Using Activated Sludge Models include a chapter on modelling industrial wastewater, an overview on the history, current practice and future of activated sludge modelling and several explanatory case studies. It can be used as an introductory book to learn about Good Modelling Practice (GMP) in activated sludge modelling and will be of special interest for process engineers who have no prior knowledge of modelling or for lecturers who need a textbook for their students. The STR can also be used as a modelling reference book and includes an extended appendix with additional information and details of methodologies. Scientific and Technical Report No. 22

Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments.

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Culture, in fact, also plays an important role in science which is, per se, a multitude of different cultures. The book attempts to build a bridge across three cultures: mathematical statistics, quantum theory and chemometrical methods. Of course, these three domains should not be taken as equals in any sense. But the book holds the important claim that it is possible to develop a common language which, at least to a certain extent, can create direct links and build bridges. From this point of departure, the book will be of interest to the following three types of scientists ? statisticians, quantum physicists and chemometricians ? and in particular, statisticians and physicists who are interested in interdisciplinary research. Written at a level that is accessible to general readers, not only the academics, the book will appeal to graduate students and mathematically educated persons of all disciplines as well as philosophers, pure and applied mathematicians, and the general public.

This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.