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Hydrogen lithography has been used to template phosphine-based surface chemistry to fabricate atomic-scale devices, a process we abbreviate as atomic precision advanced manufacturing (APAM). Here, we use mid-infrared variable angle spectroscopic ellipsometry (IR-VASE) to characterize single-nanometer thickness phosphorus dopant layers (δ-layers) in silicon made using APAM compatible processes. A large Drude response is directly attributable to the δ-layer and can be used for nondestructive monitoring of the condition of the APAM layer when integrating additional processing steps. The carrier density and mobility extracted from our room temperature IR-VASE measurements are consistent with cryogenic magneto-transport measurements, showing that APAM δ-layers function at room temperature. Finally, the permittivity extracted from these measurements shows that the doping in the APAM δ-layers is so large that their low-frequency in-plane response is reminiscent of a silicide. However, there is no indication of a plasma resonance, likely due to reduced dimensionality and/or low scattering lifetime.
In a singularly perturbed limit, we analyse the existence and linear stability of steady-state hotspot solutions for an extension of the 1-D three-component reaction-diffusion (RD) system formulated and studied numerically in Jones et. al. [Math. Models. Meth. Appl. Sci., 20, Suppl., (2010)], which models urban crime with police intervention. In our extended RD model, the field variables are the attractiveness field for burglary, the criminal population density and the police population density. Our model includes a scalar parameter that determines the strength of the police drift towards maxima of the attractiveness field. For a special choice of this parameter, we recover the ‘cops-on-the-dots’ policing strategy of Jones et. al., where the police mimic the drift of the criminals towards maxima of the attractiveness field. For our extended model, the method of matched asymptotic expansions is used to construct 1-D steady-state hotspot patterns as well as to derive nonlocal eigenvalue problems (NLEPs) that characterise the linear stability of these hotspot steady states to
(1) timescale instabilities. For a cops-on-the-dots policing strategy, we prove that a multi-hotspot steady state is linearly stable to synchronous perturbations of the hotspot amplitudes. Alternatively, for asynchronous perturbations of the hotspot amplitudes, a hybrid analytical–numerical method is used to construct linear stability phase diagrams in the police vs. criminal diffusivity parameter space. In one particular region of these phase diagrams, the hotspot steady states are shown to be unstable to asynchronous oscillatory instabilities in the hotspot amplitudes that arise from a Hopf bifurcation. Within the context of our model, this provides a parameter range where the effect of a cops-on-the-dots policing strategy is to only displace crime temporally between neighbouring spatial regions. Our hybrid approach to study the NLEPs combines rigorous spectral results with a numerical parameterisation of any Hopf bifurcation threshold. For the cops-on-the-dots policing strategy, our linear stability predictions for steady-state hotspot patterns are confirmed from full numerical PDE simulations of the three-component RD system.
The aim of this chapter is two-fold. First, the authors present a practical application of multidisciplinary research based on the experience of editing a book comprised of multidisciplinary cases and focusing on two chapter cases. There are many theoretical accounts of how one may approach multidisciplinary research, but here the authors aim to offer a practical account of how the theoretical goal of multidisciplinary research can play out in the ‘real world’. After addressing the current conceptual understanding of multidisciplinary versus interdisciplinary research, the authors will explain how useful these concepts, in fact, are when applied to the typical constraints that many academics face today in conducting joint research. The authors, who are both editors of the book, will provide lessons for future multidisciplinary collaboration and suggestions for developing methods of multidisciplinary research.
Political science does not offer a distinct subdiscipline to address the subject of energy. Insofar as political science has addressed energy, it has focused on issues often neglected by other disciplines, notably the role of geopolitics and international relations, and the domestic politics of resource-rich states. Apart from the different subfields, we examine different approaches including realism, constructivism, liberalism and Marxism. The rise and fall and rise again of academic articles on energy in leading political science journals is reviewed and linked to exogenous forces such as the price of oil. Two distinct energy topics which have received attention are nuclear power and the oil crises of 1973–79 because of their wider geopolitical ramifications. Perhaps the most prominent or consistent thread through studies of the politics of energy is the question of energy security or energy independence. Finally, in recent years, energy has increasingly emerged as a focus for study in environmental politics and climate change politics in particular.
In this chapter, the air pollution trends in historical London (1950 – 66) and contemporary Beijing (2000 – 16) are compared. In both cases, coal is the main source of air pollution, due to coal-fired electricity generation and coal-burning activities that provide heating. In London, the Clean Air Act of 1956 marked a successful milestone in the history of air pollution abatement in the UK. In Beijing, various policies have been introduced but air qualities in China have not been improved substantially. By examining the effectiveness of respective pollution control regulations/policies in a broader socioeconomic context, policy implications on respective jurisdictions are drawn. For effective implementation of air pollution control policies at the local level, it would be good for China to move beyond simply introducing stringent policies and regulations at the central or the provincial level. More resources can be re-directed to resolving the competing interests of stakeholders across different levels of jurisdictions.
Energy policy making is complex, and policy makers have traditionally relied on evidence and assessments dominated by a handful of disciplines from the natural and physical sciences. These assessments have often focused on technological solutions with the implicit message that the answer to policy needs lies in identifying and developing the right technology. Historically, however, problems arise in the implementation process of new technologies. These obstacles may be better understood, and either alleviated or avoided, through a more holistic analysis of energy policy requirements that includes multidisciplinary approaches from the social sciences and humanities. This chapter introduces the main ideas of the book, including an overview of each chapter and the most important arguments of the book.
The final chapter presents responses to the content of the entire book by policy practitioners who have dealt with the realities of constructing and implementing policies. They include essays by Emily Shuckburgh, OBE, deputy head of the Polar Oceans Team at the British Antarctic Survey; John Deutch, currently Institute Professor at the Massachusetts Institute of Technology and former Deputy Secretary of Energy in the United States; and Lord Ronald Oxburgh, who is a British parliamentarian, member of the House of Lords, a former chairman of Shell and himself a geologist and geophysicist. These ‘technologists’ offer three different perspectives on the topic of ‘good energy policy’. Finally the editors provide the main lessons learned from the book and offer suggestions for future directions of multidisciplinary research in energy policy.
In this chapter, we discuss the evolution of the field of ‘ethics of nuclear energy’, regarding its past, present and future. We will first review the history of this field in the previous four decades, focusing on new and emerging challenges of nuclear energy production and waste disposal, in light of several important developments. Four of the most pressing ethical challenges will be further reviewed in the chapter. First, what is a morally ‘acceptable’ nuclear energy production method, if we consider the existing and possible new technologies? Second, provided a new tendency to consider nuclear waste disposal with several countries, what would be the new ethical and governance challenges of these multinational collaborations? Third, how should we deal with the (safety) challenges of the new geographic distribution of nuclear energy, tilting towards emerging economies with less experience with nuclear technology? Fourth, nuclear energy projects engender highly emotional controversies. Neither ignoring the emotions of the public nor taking them as a reason to prohibit or restrict a technology – we call them technocratic populist pitfalls respectively – seem to be able to guide responsible policy making.
Drawing on political science, economics, philosophy, theology, social anthropology, history, management studies, law, and other subject areas, In Search of Good Energy Policy brings together leading academics from across the social sciences and humanities to offer an innovative look at why science and technology, and the type of quantification they champion, cannot alone meet the needs of energy policy making in the future. Featuring world-class researchers from the University of Cambridge and other leading universities around the world, this innovative book presents an interdisciplinary dialogue in which scientists and practitioners reach across institutional divides to offer their perspectives on the relevance of multi-disciplinary research for 'real world' application. This work should be read by anyone interested in understanding how multidisciplinary research and collaboration is essential to crafting good energy policy.
Domestic dogs display complex roaming behaviours, which need to be captured to more realistically model the spread of rabies. We have previously shown that roaming behaviours of domestic dogs can be categorised as stay-at-home, roamer and explorer in the Northern Peninsular Area (NPA), Queensland, Australia. These roaming behaviours are likely to cause heterogeneous contact rates that influence the speed or pattern of rabies spread in a dog population. The aim of this study was to define contact spatial kernels using the overlap of individual dog utilisation distributions to describe the daily probability of contact between pairs of dogs exhibiting these three a priori roaming behaviours. We further aimed to determine if the kernels lead to different predicted rabies outbreaks (outbreak duration and number of rabid dogs) by incorporating the spatial kernels into a previously developed rabies spread model for the NPA. Spatial kernels created with both dogs in a pair being explorers or one dog explorer and one dog roamer (who roamed away from their residence) produced short but large outbreaks compared with spatial kernels with at least one stay-at-home dog. Outputs from this model incorporating heterogeneous contacts demonstrate how roaming behaviours influence disease spread in domestic dog populations.
We introduce a Bayesian approach to conduct inferential analyses on dyadic data while accounting for interdependencies between observations through a set of additive and multiplicative effects (AME). The AME model is built on a generalized linear modeling framework and is thus flexible enough to be applied to a variety of contexts. We contrast the AME model to two prominent approaches in the literature: the latent space model (LSM) and the exponential random graph model (ERGM). Relative to these approaches, we show that the AME approach is (a) to be easy to implement; (b) interpretable in a general linear model framework; (c) computationally straightforward; (d) not prone to degeneracy; (e) captures first-, second-, and third-order network dependencies; and (f) notably outperforms ERGMs and LSMs on a variety of metrics and in an out-of-sample context. In summary, AME offers a straightforward way to undertake nuanced, principled inferential network analysis for a wide range of social science questions.