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This chapter provides a brief outline of the Fiat Group's origins, business activities, and organizational model. Section 4.2 outlines a profile of the company by describing its main business operations as well as by providing a series of significant performance indicators. Sections 4.3-4.5 analyse the distinctive chronological phases characterizing the development of the company. Finally, Section 4.6 presents the main structural principles underlying the organizational model currently adopted by Fiat at the plant level, and hence in the plants considered in this study.

This chapter covers regression-discontinuity models for analyzing the data from single case designs. Auto-regressive-integrated-moving-average models are also described and illustrated. These statistical methods are useful when there are a large number of observations in the phases of a single case design. These methods are described in detail and illustrated using data from a study of the implementation of an Aggression Replacement Training program implemented in a runaway shelter.

This chapter concerns the influence of noise and periodic rhythms on the firing patterns of neurons in their subthreshold regime. Such a regime conceals many computations that lead to successive decisions to fire or not fire, and noise and rhythms are important components of these decisions. We first consider a TypeII neuron model, the FitzHugh-Nagumo model, characterized by a resonant frequency. In the subthreshold regime, noise induces firings with a regularity that increases with noise intensity. At a certain finite noise level, the regularity may be maximized, but this depends on the numerical implementation of an absolute refractory period. We discuss measures of this coherence resonance based on the coefficient of variation (CV) of interspike intervals and spike train power spectra. We then characterize its phase locking to periodic input, and how this locking is modified by noise. This lays the foundation for understanding how noise can express subthreshold signals in the spike train. We discuss measures and qualitative features of this stochastic resonance across all time-scales of periodic forcing. We show how the resonance relates to firing once per forcing cycle, on average, or submultiples thereof at higher forcing frequencies where refractory effects come into play. For slow forcing the optimal noise is independent of forcing period. We then discuss coherence resonance and stochastic resonance in the quadratic integrate-and-fire model of TypeI dynamics. The presence of a full coherence resonance depends on the interpretation of the model, particularly the boundaries for firing and reset. Our study is motivated by the observation of randomly phase locked firing activity in a large number of neurons, especially those involved in transducing physical stimuli such as temperature, sound, pressure, and electric fields, but also in central neurons involved in the generation of various rhythms.

Spatial structure is the result of locational decisions reflecting criteria operating at a variety of scales. Thus the CA land use model is augmented with a regionalized, spatial interaction based dynamic model of population and employment that captures spatial processes operating at intermediate scales. The model is structurally very similar to typical transportation models, but with output representing yearly migrations of activity rather than hourly flows. The regional activity totals generated by the model are translated into cell demands for the various land uses, so the CA is now constrained regionally rather than globally. This integrated multiscale model continues to be linked interactively to demographic, economic and other relevant models. For some applications a transportation model is included in order to produce a high-resolution LUTI (Land Use – Transportation Interaction) model. Applications to Dublin (including one for wastewater treatment infrastructure planning) The Netherlands, Puerto Rico, and New Zealand are discussed.

This chapter suggests that core studies of emotion can contribute importantly to speech models. Inadequacies of current speech models are pointed out and the usefulness of an integrated physical cognitive model is presented. A suitable model of emotion that can be tightly correlated with a speech model is proposed, and the resulting speech model can incorporate emotive content. The advantages of building the model of speech with expressive and emotive content are presented, as well as the case for building the model in computational terms; computational adequacy is highlighted.

Integrated models of cognitive systems can be contrasted with the dominant variety of cognitive modeling that produces single-focus models of cognitive functions such as control of eye movements, visual attention, categorization, decision making, or memory. Such single-focus models are necessary but not sufficient for understanding human cognition. Although single-focused models are not usually created to be part of a larger, more integrated system, if cast in the right form, they can play strong roles in building integrated models of cognitive systems. Builders of integrated models need to explain what they mean by integration. This chapter proposes a new vocabulary that, if adopted, will clarify for the modeling community some of the issues in building integrated models. It may also lead to ways of separating the evaluation of integrated models from their component single-focus models. The heart of the chapter introduces and discusses three types of control and three types of components of integrated models of cognitive systems.

This chapter deals with the critical examination of the nature of the processes that generated the Terminal Late Woodland-Mississippian transition. In particular, it covers the heterarchical polyistic locale-centric account of the Terminal Late Woodland-Mississippian transition. It presents this as an alternative to the different versions of the current hierarchical monistic modular polity account of this same transition. Following the hermeneutic spiral method, it first reviews and then critiques the latter accounts. For this purpose, it integrates Thomas Emerson's and Timothy Pauketat's versions as the most influential of these. For the sake of convenience, it is called the Nucleated-Sequential Settlement Articulation model of the Terminal Late Woodland-Mississippian transition. Next, the alternative heterarchical polyistic locale-centric view is reported, which it termed the Integrated-to-Bifurcated Settlement Articulation model of the transition. It confirms the greater adequacy of the Integrated-to-Bifurcated Settlement Articulation model compared to the Nucleated-Sequential Settlement Articulation model of the archaeological record marking the emergence of the Mississippian period by showing how the former can give a more coherent account for a number of apparently unrelated patternings compared to their explanation under the latter.

The past twenty years have seen a giant leap forward in our knowledge about the neural mechanisms that transiently or permanently bind information in memory. This chapter reviews some of this work on the basis of existing connectionist models and proposes an integrated model. First, it delineates four different binding mechanisms that are important in memory. Then it presents a network model of working memory based on synchronized neuronal activation patterns that can be actively maintained and manipulated in recurrent loops between posterior and prefrontal cortical areas. The chapter also reviews some work on the modelling of storage and consolidation in long-term memory. The final section integrates the two approaches.

This chapter demonstrates how grand unified theories of cognition can be combined with the idea that the mind is a collection of disparate simple mechanisms. It first describes the “adaptive toolbox” model of the mind put forth by Gigerenzer and colleagues: a collection of simple heuristic mechanisms that can be used to good effect on particular tasks and in particular environments. This model is aimed at describing how humans (and other animals) can make good decisions despite the limitations that we face in terms of information, time, and cognitive processing ability — namely, by employing ecological rationality, that is, using heuristics that are fit to the structure of information in different task environments, and letting the environment itself exert significant control over what components of cognition are employed. Yet such a disintegrated and externally driven view of cognition can still ultimately come together within an integrated model of a cognitive system, as this chapter shows via an implementation within the ACT-R (adaptive control of thought-rational) cognitive architecture of two simple decision heuristics that exploit patterns of recognition and familiarity information.

Reasons for considering integrated models of cognitive systems as a desideratum are myriad, ranging from deeply theoretical interest in the structure of cognition for its own sake to the desire to gain leverage on difficult applied problems to pedagogical interests in blending cognitive psychology with related disciplines like artificial intelligence. What is remarkable is how much progress has been made by human factors researchers and practitioners in domains like commercial aviation despite the profound lack of a good integrated theory of perception, cognition, and motor control. The notion of everything fitting together raises what is known as “the jigsaw puzzle problem.” The analogy here is that the whole cognitive science endeavor has as one of its goals the construction of a complete and detailed picture of human cognition and performance (which would nicely support the interactive behavior triad).

It is argued in the Conclusion that the book has covered a range of topics too broad to be summarized in a single argument. Although the main findings of the book are presented in an integrated form in two diagrams delineating the relationships between public and private security on the one hand, and between high and low policing on the other, each of the nine chapters of the book is a self‐contained whole, in which specific conclusions relevant to the topic under discussion are formulated. The final conclusion of the book is devoted to extracting from these nine chapters the main point made in each of them.

The present study incorporated game-theoretic solutions into a well-known integrated assessment (IA) model. The extensive simulations of game-theoretic solutions in the RICE model have shown that the regional incentive to join the global coalition of greenhouse gas (GHG) mitigation is an important aspect of IA modeling. This epilogue suggests future research directions and topics employing the research methodologies in this book. These include coalition formation in an uncertain system, in-depth analysis of subcoalitions, and structuring the “closed-loop” strategies in an IA modeling/game-theoretic solution framework.

This chapter summarizes the evidence for and against each of the hypotheses comprised in my theoretical framework, comparing and contrasting the findings from the five case studies. The study confirms the considerable explanatory power of the rationalist baseline hypothesis, but also demonstrates its clear limitations. A pragmatic concern for treaty effectiveness influenced European responses to US policy in all five cases, and could even fully explain them in some instances. However, it was insufficient to explain European decisions in other cases where neither accommodation nor non-hegemonic cooperation was the clearly superior strategic option in terms of treaty effectiveness. In these cases, economic cost constraint and, above all, different types of normative considerations tipped the balance for or against non-hegemonic cooperation from the perspective of European governments.

By examining degree plans and conducting interviews with faculty and students at various national and international institutions, the authors of this chapter have generated four curricular models that suggest how existing degree plans and/or core music courses might be productively modified. The enhanced core model (1) aims to broaden the scope of existing curricula by emphasizing more diverse, cross-disciplinary content. The pluralist model (2) requires students to diversify their focus during their first two years of study in order to incorporate a greater degree of critical thinking, creative engagement, and broad skill sets into the major. The integrated model (3) emphasizes music making as the primary mode of learning basic skills and reduces overall requirements by combining courses such as ear training, music theory, and keyboard skills into a single class. Finally, the capstone model (4) demonstrates how self-directed and highly individualized projects can be incorporated into degree plans.

Using the International Monetary Fund's Global Integrated Monetary and Fiscal Model (GIMF), this chapter assesses the effectiveness of expansionary fiscal policy when monetary policy accommodates the shock, such as was the case in the coordinated fiscal expansion of 2008–2009. After reviewing the literature on activist monetary and fiscal policies, the chapter describes the key features of the economic model in which the policy rules are imbedded. It then introduces simple fiscal policy as a countercyclical tool to show the dynamics of policy coordination and how features such as financial accelerators affect the dynamics of policy coordination. Three scenarios are given: an expansionary fiscal policy when the monetary policy rate has not reached its lower bound, an expansionary fiscal policy when the policy rate is at its lower bound, and an expansionary fiscal policy with the market perception of unsustainable debt. The simulations show that fiscal stimulus is significantly more effective in boosting economic output when the higher real interest rates that it can generate are offset by other policy measures.

This chapter discusses the history, institutional structure, mandate, procedural characteristics, and agency performance of the competition law system of the United States. The US enforcement system is complex. There are two major federal enforcement agencies and fifty state enforcement agencies, plus five federal districts or territories, and enforcement through private litigation. The state attorneys general can enforce federal antitrust law as well as state antitrust law when state residents are injured. The two US federal agencies are the Department of Justice Antitrust Division and the Federal Trade Commission. The former is a division of the executive branch; the latter is an independent regulatory agency. The Antitrust Division of the Department of Justice follows the bifurcated judicial model, investigating cases and bringing enforcement actions in federal courts of general jurisdiction. The Federal Trade Commission, consisting of five commissioners, follows the integrated agency model, with power to investigate and adjudicate cases internally, subject to subsequent appellate court review.

Using the International Monetary Fund's Global Integrated Monetary and Fiscal Model (GIMF), this chapter examines how combining fiscal adjustment with structural reform and coordinated fiscal policy can reduce public debt, encourage economic growth, and lower global imbalances for all participating countries. It first considers the virtuous circle that can be generated when fiscal consolidation is accompanied by productivity-enhancing structural reform and monetary easing before discussing the specifics of the hypothetical policy actions put into the GIMF and the key features of the model in which the coordinated policy actions are embedded. It then reviews previous studies of the macroeconomic effects of fiscal consolidation. It shows that fiscal consolidation is typically associated with shrinking current-account deficits and slowing growth, but that structural and fiscal reform creates the potential for the world economy to grow while rebalancing global demand. The chapter also illustrates the potential for a virtuous circle to arise.

This chapter examines the feasibility of limiting the average global temperature rise, using the latest version of the TIAM-UCL global integrated assessment model. Given the continuing delay in implementing a global agreement on GHG emission reduction, we first examine the window of opportunity for continuing to increase emissions while still limiting the average surface temperature rise. The chapter constructs a number of specific scenarios leading to different long-term temperature increases to explore the resource and technology needs implied in each. It focuses in particular on the dynamics of coal-to-gas switching, and on the decarbonization of the electricity sector. The differences in mitigation and costs between high-, middle-, and low-income regions are also discussed. Finally, the chapter compares the rates of technology deployment required in the emissions mitigation scenarios with deployment rates observed historically.