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Moda, fe y fantasía en la nueva física del universo
by Roger Penrose¿Qué influencias pueden tener la moda, la fe y la fantasía en las investigaciones científicas que buscan entender el comportamiento del universo? ¿Son los físicos teóricos inmunes a las tendencias, las creencias dogmáticas o los revoloteos fantásticos? Roger Penrose responde a estas y a otras muchas preguntas en este su nuevo libro. En Moda, fe y fantasía en la nueva física del universo, el aclamado físico Roger Penrose nos explica por qué los investigadores que trabajan en la última frontera de la física son, de hecho, tan susceptibles a estas fuerzas como el resto de mortales. En este polémico libro, Penrose muestra que la moda, la fe y la fantasía -pese a ser útiles y hasta esenciales en física- pervierten la investigación actual en tres de las áreas más importantes de esta disciplina: la teoría de cuerdas, la mecánica cuántica y la cosmología. El resultado final es una importante crítica de los avances más significativos de la física actual, de la mano de uno de sus principales representantes. Reseñas:«El optimismo de Penrose es contagioso.»Leer «Cuando Penrose habla, los científicos escuchan.»The New York Times Book Review
Modal Empiricism: Interpreting Science Without Scientific Realism (Synthese Library #440)
by Quentin RuyantThis book proposes a novel position in the debate on scientific realism: Modal Empiricism. Modal empiricism is the view that the aim of science is to provide theories that correctly delimit, in a unified way, the range of experiences that are naturally possible given our position in the world. The view is associated with a pragmatic account of scientific representation and an original notion of situated modalities, together with an inductive epistemology for modalities. It purports to provide a faithful account of scientific practice and of its impressive achievements, and defuses the main motivations for scientific realism. More generally, Modal Empiricism purports to be the precise articulation of a pragmatist stance towards science.This book is of interest to any philosopher involved in the debate on scientific realism, or interested in how to properly understand the content, aim and achievements of science.
Modalanalyse (Fachwissen Technische Akustik)
by Michael MöserIn diesem Band der Reihe Fachwissen Technische Akustik wird das Verfahren der experimentellen Modalanalyse vorgestellt. Mit diesem Verfahren können die von der Ausbreitung von Luft- und Körperschall bestimmten dynamischen Eigenschaften von Systemen untersucht werden. Beispiele für solche Systeme sind Strukturen im Maschinen- und Fahrzeugbau oder auch kleinere Innenräume, deren akustischen Verhalten von Interesse ist. In einer Einführung wird zunächst auf den Zusammenhang des physikalischen Modells und des systemtheoretischen Modells eingegangen sowie der Nutzen des modalen Modells für die Beschreibung der Systemeigenschaften erläutert. Danach wird die dem modalen Modell zugrunde liegende Theorie sowie der Zusammenhang der modalen Parameter mit den im Systemmodell verwendeten Frequenzgängen dargestellt. Verschiedene Verfahren der experimentellen Modalanalyse werden diskutiert, darunter sowohl solche zur getrennten Bestimmung einzelner modaler Parameter als auch solche, bei denen eine Vielzahl modaler Parameter gleichzeitig aus den gemessenen Frequenzgängen ermittelt wird. Zusätzlich wird auf das praktische Vorgehen bei der Gewinnung der dazu notwendigen Messdaten und die Möglichkeiten zur Überprüfung der Ergebnisse eingegangen. Zur Demonstration der verschiedenen Möglichkeiten und Verfahren wird ein einfaches praktisches Beispiel ausführlich behandelt. Das umfasst die Vorgehensweise bei der Messung ebenso wie die Anwendung unterschiedlich aufwändiger Verfahren zur Extraktion der modalen Parameter. Dazu werden zahlreiche Ergebnisse gezeigt, so dass Möglichkeiten und Grenzen der experimentellen Modalanalyse deutlich werden.
Model Averaging (SpringerBriefs in Statistics)
by David FletcherThis book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models.
Model Based Approach for Energy and Resource Efficient Machining Systems (Sustainable Production, Life Cycle Engineering and Management)
by Nadine MadanchiThis book provides a concept to analyze and increase the energy and resource efficiency of machining systems. Machining systems are widely used to produce workpieces in large quantities and with complex geometrical shapes. These systems, however, are also relevant in terms of energy and resource consumption, which is strongly connected to the choice of cutting fluid strategy. Within the focus of the concept, cutting fluid connects the elements of the machining system and results in interactions between them. Based on this description and an extensive literature review, a modeling approach is developed that comprises the relations between process parameters, cutting fluid strategies, and relevant machining system elements. The performance of the machining system is assessed with regard to environmental, economic as well as technological indicators and improved by various organizational and technical measures. The exemplary application of the developed concept is carried out in the context of two case studies and also indicates the corresponding effects of improvement measures.
Model Behavior: Animal Experiments, Complexity, and the Genetics of Psychiatric Disorders
by Nicole C. NelsonMice are used as model organisms across a wide range of fields in science today—but it is far from obvious how studying a mouse in a maze can help us understand human problems like alcoholism or anxiety. How do scientists convince funders, fellow scientists, the general public, and even themselves that animal experiments are a good way of producing knowledge about the genetics of human behavior? In Model Behavior, Nicole C. Nelson takes us inside an animal behavior genetics laboratory to examine how scientists create and manage the foundational knowledge of their field. Behavior genetics is a particularly challenging field for making a clear-cut case that mouse experiments work, because researchers believe that both the phenomena they are studying and the animal models they are using are complex. These assumptions of complexity change the nature of what laboratory work produces. Whereas historical and ethnographic studies traditionally portray the laboratory as a place where scientists control, simplify, and stabilize nature in the service of producing durable facts, the laboratory that emerges from Nelson’s extensive interviews and fieldwork is a place where stable findings are always just out of reach. The ongoing work of managing precarious experimental systems means that researchers learn as much—if not more—about the impact of the environment on behavior as they do about genetics. Model Behavior offers a compelling portrait of life in a twenty-first-century laboratory, where partial, provisional answers to complex scientific questions are increasingly the norm.
Model Choice in Nonnested Families
by Basilio De Pereira Carlos Alberto PereiraThis book discusses the problem of model choice when the statistical models are separate, also called nonnested. Chapter 1 provides an introduction, motivating examples and a general overview of the problem. Chapter 2 presents the classical or frequentist approach to the problem as well as several alternative procedures and their properties. Chapter 3 explores the Bayesian approach, the limitations of the classical Bayes factors and the proposed alternative Bayes factors to overcome these limitations. It also discusses a significance Bayesian procedure. Lastly, Chapter 4 examines the pure likelihood approach. Various real-data examples and computer simulations are provided throughout the text.
Model Driven Engineering for Distributed Real-Time Embedded Systems 2009: Advances, Standards, Applications and Perspectives (Wiley-iste Ser.)
by Mireille Blay-Fornarino Sylvain Robert Jean-Philippe Babau Joël Champeau Antonio SabettaModel-based development methods, and supporting technologies, can provide the techniques and tools needed to address the dilemma between reducing system development costs and time, and developing increasingly complex systems. This book provides the information needed to understand and apply model-drive engineering (MDE) and model-drive architecture (MDA) approaches to the development of embedded systems. Chapters, written by experts from academia and industry, cover topics relating to MDE practices and methods, as well as emerging MDE technologies. Much of the writing is based on the presentations given at the Summer School “MDE for Embedded Systems” held at Brest, France, in September 2004.
Model Elements and Network Solutions of Heat, Mass and Momentum Transport Processes
by George L. DankoThis work provides an enormous contribution to the broad effort of modeling heat, mass and momentum transport in multi-physics problems with the development of new solution approaches. It re-visits the time-honored technique of network application using flow network solutions for all transport process components for a coupled modeling task. The book further provides as formulation of the conservation laws for mass, energy and momentum, specifically for the branches and nodes of transport networks using the combination of the Eulerian and Lagrangean modeling methods. With the extension of Bernoulli's original concept, a new solution is given for the flow field of viscous and compressible fluids as driven by the balance of mechanical energy, coupled to the thermodynamics of the transport system. Applicable to simple or large-scale tasks, the new model elements and methods are built on first principles. Throughout the work, the book provides original formulations, their mathematical derivations as well as applications in a numerical solution scheme.
Model Elements and Network Solutions of Heat, Mass and Momentum Transport Processes (Heat and Mass Transfer)
by George L. DankoThis work provides an enormous contribution to the broad effort of modeling heat, mass and momentum transport in multi-physics problems with the development of new solution approaches. It re-visits the time-honored technique of network application using flow network solutions for all transport process components for a coupled modeling task. The book further provides as formulation of the conservation laws for mass, energy and momentum, specifically for the branches and nodes of transport networks using the combination of the Eulerian and Lagrangean modeling methods. With the extension of Bernoulli’s original concept, a new solution is given for the flow field of viscous and compressible fluids as driven by the balance of mechanical energy, coupled to the thermodynamics of the transport system. Applicable to simple or large-scale tasks, the new model elements and methods are built on first principles. Throughout the work, the book provides original formulations, their mathematical derivations as well as applications in a numerical solution scheme.
Model Order Reduction for Design, Analysis and Control of Nonlinear Vibratory Systems (CISM International Centre for Mechanical Sciences #614)
by Attilio Frangi Cyril TouzéThe book presents reduction methods that are using tools from dynamical systems theory in order to provide accurate models for nonlinear dynamical solutions occurring in mechanical systems featuring either smooth or non smooth nonlinearities. The cornerstone of the chapters is the use of methods defined in the framework of the invariant manifold theory for nonlinear systems, which allows definitions of efficient methods generating the most parsimonious nonlinear models having minimal dimension, and reproducing the dynamics of the full system under generic assumptions. Emphasis is put on the development of direct computational methods for finite element structures. Once the reduced order model obtained, numerical and analytical methods are detailed in order to get a complete picture of the dynamical solutions of the system in terms of stability and bifurcation. Applications from the MEMS and aerospace industry are covered and analyzed. Geometric nonlinearity, friction nonlinearity and contacts in jointed structures, detection and use of internal resonance, electromechanical and piezoelectric coupling with passive control, parametric driving are surveyed as key applications. The connection to digital twins is reviewed in a general manner, opening the door to the efficient use of invariant manifold theory for nonlinear analysis, design and control of engineering structures.
Model Organisms (Elements in the Philosophy of Biology)
by Sabina Leonelli Rachel AnkenyThis Element presents a philosophical exploration of the concept of the 'model organism' in contemporary biology. Thinking about model organisms enables us to examine how living organisms have been brought into the laboratory and used to gain a better understanding of biology, and to explore the research practices, commitments, and norms underlying this understanding. We contend that model organisms are key components of a distinctive way of doing research. We focus on what makes model organisms an important type of model, and how the use of these models has shaped biological knowledge, including how model organisms represent, how they are used as tools for intervention, and how the representational commitments linked to their use as models affect the research practices associated with them.
Model Organisms for Microbial Pathogenesis, Biofilm Formation and Antimicrobial Drug Discovery
by Busi Siddhardha Madhu Dyavaiah Asad SyedThis book provides essential insights into microbial pathogenesis, host-pathogen interactions, and the anti-microbial drug resistance of various human pathogens on the basis of various model organisms. The initial sections of the book introduce readers to the mechanisms of microbial pathogenesis, host-pathogen interactions, anti-microbial drug resistance, and the dynamics of biofilm formation. Due to the emergence of various microbial resistant strains, it is especially important to understand the prognosis for microbial infections, disease progression profiles, and mechanisms of resistance to antibiotic therapy in order to develop novel therapeutic strategies. In turn, the second part of the book presents a comparative analysis of various animal models to help readers understand microbial pathogenesis, host-pathogen interactions, anti-microbial drug discovery, anti-biofilm therapeutics, and treatment regimes. Given its scope, the book represents a valuable asset for microbiologists, biotechnologists, medical professionals, drug development researchers, and pharmacologists alike.
Model Organisms to Study Biological Activities and Toxicity of Nanoparticles
by Busi Siddhardha Madhu Dyavaiah Kaviyarasu KasinathanThis book provides a comprehensive overview of state-of-the-art applications of nanotechnology in biology and medicine, as well as model organisms that can help us understand the biological activity and associated toxicity of nanoparticles, and devise strategies to minimize toxicity and enhance therapies. Thanks to their high surface-to-volume ratio, nanoparticles are characterized by excellent biocompatibility and bioavailability, a high therapeutic index, and relatively low toxicity, which has led to their widespread application in the early diagnosis of diseases, comprehensive monitoring of disease progression, and improved therapeutics. The book also explores nanoparticle-based insecticides and their mechanisms of action, and provides a comparative analysis of the various model organisms that are used to understand the biological properties of nanoparticles. Further, it describes various in-vivo models that yield important insights into nanomaterial-mediated toxicity, promoting the optimal utilization of nanoparticles. In closing, the book discusses future perspectives and regulatory issues concerning the use of nanomaterials in translational research.
Model Plants and Crop Improvement
by Rajeev K. Virshney Robert M.D. KoebnerBringing together experts from across the globe, Model Plants and Crop Improvement provides a critical assessment of the potential of model plant species for crop improvement. The first comprehensive summary of the use of model plant systems, the book delineates the model species' contribution to understanding the genomes of crop species. It provides an in-depth examination of the achievements and limitations of the model paradigm and explores how continued research in models can contribute to the goal of delivering the outputs of molecular biology to crops. This timely volume is the first comprehensive summary for studying the development of plant species of particular agricultural significance.
Model Predictive Control
by Basil Kouvaritakis Mark CannonFor the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses.
Model Predictive Control (IEEE Press)
by Baocang Ding Yuanqing YangModel Predictive Control Understand the practical side of controlling industrial processes Model Predictive Control (MPC) is a method for controlling a process according to given parameters, derived in many cases from empirical models. It has been widely applied in industrial units to increase revenue and promoting sustainability. Systematic overviews of this subject, however, are rare, and few draw on direct experience in industrial settings. Assuming basic knowledge of the relevant mathematical and algebraic modeling techniques, the book’s title combines foundational theories of MPC with a thorough sense of its practical applications in an industrial context. The result is a presentation uniquely suited to rapid incorporation in an industrial workplace. Model Predictive Control readers will also find: Two-part organization to balance theory and applications Selection of topics directly driven by industrial demand An author with decades of experience in both teaching and industrial practice This book is ideal for industrial control engineers and researchers looking to understand MPC technology, as well as advanced undergraduate and graduate students studying predictive control and related subjects.
Model Predictive Control of Wind Energy Conversion Systems
by Bin Wu Venkata YaramasuThe authors provide a comprehensive analysis from the electrical engineering aspect of power converters, wind energy systems and predictive control employed in a wide variety of conversion systems. The content of the book includes an overview of wind energy system configurations, power converters and predictive control; modeling and control of grid-connected two-level and multilevel voltage source converters; and predictive control of standalone three-leg and four-leg converters with an output LC filter. It also explores predictive control of several power converter configurations for the full variable-speed permanent magnet synchronous generator (PMSG) and squirrel cage induction generator (SCIG) based WECS, and semi variable-speed doubly-fed induction generator (DFIG) based WECS; and low voltage ride-through operation of PMSG and IG WECS.Reflecting the latest technologies in the field, Model Predictive Control of Wind Energy Conversion Systems is a valuable reference for academic researchers, practicing engineers, and other professionals. It can also be used as a textbook for graduate-level and advanced undergraduate courses.
Model Predictive Control: Approaches Based On The Extended State Space Model And Extended Non-minimal State Space Model
by Furong Gao Ridong Zhang Anke XueThis monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering.
Model Predictive Vibration Control
by Boris Rohaľ-Ilkiv Gergely TakácsReal-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: · the implementation of computationally efficient algorithms · control strategies in simulation and experiment and · typical hardware requirements for piezoceramics actuated smart structures. The use of a simple laboratory model and inclusion of over 170 illustrations provides readers with clear and methodical explanations, making Model Predictive Vibration Control the ideal support material for graduates, researchers and industrial practitioners with an interest in efficient predictive control to be utilized in active vibration attenuation.
Model Reduction for Circuit Simulation
by Peter Benner E. Jan ter Maten Michael HinzeSimulation based on mathematical models plays a major role in computer aided design of integrated circuits (ICs). Decreasing structure sizes, increasing packing densities and driving frequencies require the use of refined mathematical models, and to take into account secondary, parasitic effects. This leads to very high dimensional problems which nowadays require simulation times too large for the short time-to-market demands in industry. Modern Model Order Reduction (MOR) techniques present a way out of this dilemma in providing surrogate models which keep the main characteristics of the device while requiring a significantly lower simulation time than the full model. With Model Reduction for Circuit Simulation we survey the state of the art in the challenging research field of MOR for ICs, and also address its future research directions. Special emphasis is taken on aspects stemming from miniturisations to the nano scale. Contributions cover complexity reduction using e.g., balanced truncation, Krylov-techniques or POD approaches. For semiconductor applications a focus is on generalising current techniques to differential-algebraic equations, on including design parameters, on preserving stability, and on including nonlinearity by means of piecewise linearisations along solution trajectories (TPWL) and interpolation techniques for nonlinear parts. Furthermore the influence of interconnects and power grids on the physical properties of the device is considered, and also top-down system design approaches in which detailed block descriptions are combined with behavioral models. Further topics consider MOR and the combination of approaches from optimisation and statistics, and the inclusion of PDE models with emphasis on MOR for the resulting partial differential algebraic systems. The methods which currently are being developed have also relevance in other application areas such as mechanical multibody systems, and systems arising in chemistry and to biology. The current number of books in the area of MOR for ICs is very limited, so that this volume helps to fill a gap in providing the state of the art material, and to stimulate further research in this area of MOR. Model Reduction for Circuit Simulation also reflects and documents the vivid interaction between three active research projects in this area, namely the EU-Marie Curie Action ToK project O-MOORE-NICE (members in Belgium, The Netherlands and Germany), the EU-Marie Curie Action RTN-project COMSON (members in The Netherlands, Italy, Germany, and Romania), and the German federal project System reduction in nano-electronics (SyreNe).
Model Systems and the Neurobiology of Associative Learning: A Festschrift in Honor of Richard F. Thompson
by Mark A. Gluck Joseph E. Steinmetz Paul R. SolomonThis volume contains a collection of papers written by former students, postdoctoral fellows, and colleagues of Richard Thompson and represent written versions of papers presented at the Festschrift symposium. The Festschrift provided an excellent opportunity for the participants to recount their memories and experiences of working with one of the leading figures in behavioral neuroscience, and to place their current research in the context of earlier research conducted in the Thompson laboratory. As a Festschrift volume, the various chapters contain numerous and sometimes very personal references to Richard Thompson's influence on the careers of the authors, as well as summaries of past and present work being conducted in the authors' laboratories. Part I includes studies of spinal cord plasticity and the involvement of the hippocampus and related structure in classical eyeblink conditioning. Part II explores the critical role of the cerebellum and associated areas in classical eyeblink conditioning. Part III focuses on a continued exploration of the involvement of the cerebellum in classical eyeblink conditioning using standard procedures as well as innovative molecular biology and genetic techniques. It also includes studies aimed at delineating modulatory influences on learning such as stress and hormonal factors. The incredible influence that Richard Thompson has had on the fields of experimental psychology and neuroscience should be evident on reading the contributions made by the various authors to this volume. The research conducted in Thompson's laboratory over the years has been cutting-edge, comprehensive, and influential. Therefore, this volume is dedicated to Richard F. Thompson a productive, innovative scientist and outstanding mentor.
Model Systems in Behavioral Ecology: Integrating Conceptual, Theoretical, and Empirical Approaches
by Lee Alan DugatkinA key way that behavioral ecologists develop general theories of animal behavior is by studying one species or a closely related group of species--''model systems''--over a long period. This book brings together some of the field's most respected researchers to describe why they chose their systems, how they integrate theoretical, conceptual, and empirical work, lessons for the practice of the discipline, and potential avenues of future research. Their model systems encompass a wide range of animals and behavioral issues, from dung flies to sticklebacks, dolphins to African wild dogs, from foraging to aggression, territoriality to reproductive suppression. <p><p> Model Systems in Behavioral Ecology offers an unprecedented ''systems'' focus and revealing insights into the confluence of personal curiosity and scientific inquiry. It will be an invaluable text for behavioral ecology courses and a helpful overview--and a preview of coming developments--for advanced researchers. The twenty-five chapters are divided into four sections: insects and arachnids, amphibians and reptiles, birds, and mammals.
Model Systems in Biology: History, Philosophy, and Practical Concerns
by Georg StriedterHow biomedical research using various animal species and in vitro cellular systems has resulted in both major successes and translational failure.In Model Systems in Biology, comparative neurobiologist Georg Striedter examines how biomedical researchers have used animal species and in vitro cellular systems to understand and develop treatments for human diseases ranging from cancer and polio to Alzheimer&’s disease and schizophrenia. Although there have been some major successes, much of this &“translational&” research on model systems has failed to generalize to humans. Striedter explores the history of such research, focusing on the models used and considering the question of model selection from a variety of perspectives—the philosophical, the historical, and that of practicing biologists. Striedter reviews some philosophical concepts and ethical issues, including concerns over animal suffering and the compromises that result. He traces the history of the most widely used animal and in vitro models, describing how they compete with one another in a changing ecosystem of models. He examines how therapies for bacterial and viral infections, cancer, cardiovascular diseases, and neurological disorders have been developed using animal and cell culture models—and how research into these diseases has both taken advantage of and been hindered by model system differences. Finally, Striedter argues for a &“big tent&” biology, in which a diverse set of models and research strategies can coexist productively.
Model Systems in Catalysis
by Robert RiouxThe book concentrates on heterogeneous catalysis, but extends well beyond the most obvious model system - the single crystal. The book builds upon increasing complexity into catalyst models - that is building catalysts with controlled properties that begin to rival the complexity found in industrial based heterogeneous catalysts. This includes the deposition of clusters on flat, thin oxide surfaces amenable to characterize by electron, ion and photon based spectroscopic techniques, the thermal decomposition of organometallic clusters on surfaces with well-defined stoichiometry, to the tethering of homogeneous catalysts to metal oxide surfaces (i.e. heterogenized homogeneous catalysis) and finally evolving to a supported structural and functional mimic of the ultimate catalyst, the enzyme.