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Heavily worn teeth are one of the most prominent features of archaeological and fossil hominid dentitions. This chapter describes in detail the different patterns of wear and distinguishes between wear resulting from deliberate modification and wear resulting from contact with food and other residues in the mouth. It shows how different aspects of this wear can be measured and described, on both macroscopic and microscopic scales. In addition, it explores the possible mechanisms of wear and critically reviews the evidence that wear pattern provides for diet and non-dietary uses of teeth in the past.
The most common dental diseases in people today are dental caries, or decay, and periodontal disease. Evidence for them is sparse in fossil hominds, although more cases have been found in Upper Palaeolithic contexts. They become more common in Neolithic and later contexts, but only reached modern levels in post-industrial societies. Both conditions result from the presence of dental plaque on the teeth, so this chapter starts with a concise introduction to plaque biology. The deeper layers of a plaque accumulation become mineralised to form the deposits known as dental calculus or tartar. This has become a focus of recent anthropological research, particularly in relation to past diet. The chapter goes on to summarise recent clinical evidence for the way in which the lesions of dental caries and periodontal disease develop, and describes their pattern of occurrence in living people. This is contrasted with the archaeological pattern. The effect of diet, particularly the carbohydrate component, is discussed. Ancient jaws from older individuals show the combined effects of bone loss due to periodontal disease, loss due to infections which follow exposure of the pulp chamber by caries or fracturing, and the body’s compensation for tooth wear by remodelling of the bone in the jaws. The chapter explores the ways in which these different factors can be disentangled.
Geostatistics provides tools for spatio-temporal data analysis. The subsurface application we cover in this book is sustainable farming in Denmark. Readers will learn about geophysical techniques for infering the redox conditions of the subsurface. A second application happens at the surface of the Earth: glaciers melting in Antarctica. We introduce a significant ongoing effort in radar imaging mapping of the Thwaites glacier in Antarctica. Both cases call for building spatial models from incomplete data: spatial interpolation. We cover geostatistical methods for capturing spatial variability with variograms and illustrate why variograms are essential to spatial interpolation, kriging. We introduce conditional simulation as a method for generating many interpolated maps that reproduce realistic variation. We show how these maps represent spatial uncertainty, and thereby affect prediction, such as predicting redox conditions in Danish agricultural areas. Finally, we introduce ways of spatial interpolating using training images. We show how using exisiting training image the exposed Arctic topography can help us interpolate Antarctica.
Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.
How closely do most of us follow the normative model when we make probability judgments? Until the late 1960s, it was thought that even people with little experience did reasonably well at it intuitively (Peterson & Beach, 1967). Since then, psychologists have found that we do poorly at making probability judgments – in systematic ways. It is not just that our judgments are erroneous. Our judgments are erroneous because we attend to variables that we should ignore and ignore variables to which we should attend.
Turbomachines are the heart of all production jet engines and power generation gas turbines. This book discusses six basic types of turbomachines directly: axial flow compressors, axial flow pumps, radial flow compressors, centrifugal pumps, axial flow gas turbines, and axial flow hydraulic turbines. Two other basic types that are used in practice are not covered in this text because of their limited application in propulsion and power generation: radial inflow gas turbines and radial inflow hydraulic turbines. The basic derivations of the equations for each machine type are covered in this chapter rather than in the chapters in which the machines are discussed. As will be shown, the resulting fundamental equations apply to all types of turbomachines, regardless of categorization. Application of the equations with complementing internal velocity information is, however, different for the different turbomachines. Advanced details can be found in texts, including Stodola (1927), Howell (1945a, 1945b), Shepherd (1956), Vavra (1974), Dixon (1975, 1998), Osborn (1977), Balje (1981), Whittle (1981), Wallis (1983), Turton (1984), Hill and Peterson (1992), Logan (1993), Japikse and Baines (1994), Cohen et al. (1996), Hah (1997), and Wilson and Korakianitis (2014). Cumpsty and Greitzer (2004) present an interesting review of turbomachinery development. Furthermore, Denton and Dawes (1998), Elmendorf et al. (1998), LeJambre et al. (1998), Rhie et al. (1998), Adamczyk (2000), and Denton (2010) show how modern computational fluid dynamic (CFD) tools can effectively be used for the complex 3-D analysis and design of turbomachines and also cover some of the limitations. In the following three chapters the equations developed in this chapter will be used to find the operating characteristics of compressors and turbines.
The purposes of the diffuser or inlet are first to bring air smoothly into the gas turbine. Second, for a propulsion diffuser to slow the fluid and to increase the pressure, or for a power generation inlet to increase the fluid speed and to decrease the pressure. And third, to deliver a uniform flow to the compressor. As indicated by studies for cycle analyses in Chapter 3, gas turbine performance improves with increasing pressure to the burner. The first component the air encounters is the diffuser or inlet, and the second component is the compressor. Thus, if the diffuser or inlet incurs a large total pressure loss, the total pressure into the burner will be reduced by the compressor total pressure ratio times this loss. For example, if 2 psia are lost in the diffuser or inlet, for a large engine this can result in 50 psia less in the burner.
As discussed in Chapters 1–4, the purpose of the turbine is to extract energy from the fluid to drive the compressive devices. The actual operation of the turbine is in some respects similar to, but opposite that, of the compressor. That is, energy is extracted from the fluid and the pressure and temperature drop through the turbine. Typically, 70–80 percent of the enthalpy increase from the burner is used by the turbine to drive the compressor. For jet propulsion the remainder is used to generate thrust in the nozzle, while for a power generation unit the remainder is used to generate auxiliary power.
Part II was concerned with thinking about beliefs. Part III is about decision making, the thinking we do when we choose an action, including both the decisions that affect only the decision maker and the decisions that affect others, that is, decisions that raise moral questions. We shall also examine long-term planning, with special emphasis on the choice of personal goals. Part III is concerned mostly with inference rather than search – in particular, with how we infer a course of action from our goals and from evidence concerning the consequences of our options for achieving them.