The creation of The four million : O. Henry's influences and working methods

The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Title from PDF of title page (University of Missouri--Columbia, viewed on September 24, 2009).Thesis advisor: Dr. Tom Quirk.M.A. University of Missouri--Columbia 2008.Though O. Henry's The Four Million was intended as an attack on Ward McAllister's idea of the Four Hundred, each man is mentioned only in passing in studies of the other. One chapter therefore contrasts the two men by bringing together readings of McAllister's memoir, accounts of his career, and the secondary literature on O. Henry. Another chapter examines the work of Anne Partlan, the writer that O. Henry said inspired him to write about the shopgirls of New York. This section focuses on "Among Themselves," the story O. Henry singled out as a special influence, and Partlan's other work for Success magazine around the turn of the century. A final chapter attempts to assemble material for a compositional history of The Four Million. While the results are necessarily inconclusive, some tentative conclusions are reached about how much O. Henry was involved in the selection and arrangement of stories for the book and how much was left to his publisher and others. The results demonstrate that some established ideas about O. Henry - that he was in the vanguard in pushing back against the idea of the Four Hundred and that he moved in on Partlan's fictional territory - are not borne out by the facts and must be tested against original sources.Includes bibliographical reference

Forecasting in dynamic factor models using Bayesian model averaging

This paper considers the problem of forecasting in dynamic factor models using Bayesian model averaging. Theoretical justifications for averaging across models, as opposed to selecting a single model, are given. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms which simulate from the space defined by all possible models. We discuss how these simulation algorithms can also be used to select the model with the highest marginal likelihood (or highest value of an information criterion) in an efficient manner. We apply these methods to the problem of forecasting GDP and inflation using quarterly U.S. data on 162 time series. For both GDP and inflation, we find that the models which contain factors do out-forecast an AR(p), but only by a relatively small amount and only at short horizons. We attribute these findings to the presence of structural instability and the fact that lags of dependent variable seem to contain most of the information relevant for forecasting. Relative to the small forecasting gains provided by including factors, the gains provided by using Bayesian model averaging over forecasting methods based on a single model are appreciable

Enhancing the discovery of rare disease variants through hierarchical modeling

Advances in next-generation sequencing technology are enabling researchers to capture a comprehensive picture of genomic variation across large numbers of individuals with unprecedented levels of efficiency. The main analytic challenge in disease mapping is how to mine the data for rare causal variants among a sea of neutral variation. To achieve this goal, investigators have proposed a number of methods that exploit biological knowledge. In this paper, I propose applying a Bayesian stochastic search variable selection algorithm in this context. My multivariate method is inspired by the combined multivariate and collapsing method. In this proposed method, however, I allow an arbitrary number of different sources of biological knowledge to inform the model as prior distributions in a two-level hierarchical model. This allows rare variants with similar prior distributions to share evidence of association. Using the 1000 Genomes Project single-nucleotide polymorphism data provided by Genetic Analysis Workshop 17, I show that through biologically informative prior distributions, some power can be gained over noninformative prior distributions

UK National Ecosystem Assessment Follow-on. Work package 7: Operationalising scenarios in the UK National Ecosystem Assessment Follow-on

Summary Study aims and approach An aim of the UK NEA Follow-on (UK NEAFO) is to develop and communicate the evidence base of the UK NEA and make it relevant to decision and policy making. It also provides an important opportunity for those working on scenario methods and concepts to scrutinise the role of futures thinking in the management of ecosystem services and so develop their effectiveness as decision support tools. In this study we have therefore asked: how can the UK NEA scenarios help us to understand, manage and communicate the consequences of changes in ecosystem services across all scales? There are many different understandings about what scenarios are, and what they should be used for. To clarify the issues surrounding the role of scenarios, we have approached this work from two angles. We have firstly looked at the way the storylines can support decision making processes. Secondly, we have looked at the content of the scenarios themselves and explored how through the use of models the UK NEA scenarios as products might be refined to enhance their value as analytical tools. Scenarios in Action We used the opportunity of a series of meetings with stakeholders to develop the UK NEA scenarios from a process perspective. These meetings took various forms, but throughout the main aim was to find out whether people found the scenarios sufficiently believable, challenging and relevant. In workshops organised by the scenario team in Leeds, Edinburgh and Belfast, we worked with participants on a series of tasks designed to help them immerse themselves in the scenarios and reflect on them critically. While those we worked with had many comments about the scenarios in detail, the evidence we collected from these meetings suggests that the majority of people found the scenarios to be plausible and the projections consistent. The majority also agreed with the proposition that the suite of scenarios as a whole addressed a relevant ranges of issues. We explored with the workshop participants several ways in which the storylines could be enriched, by: developing the narrative about the way people might live in the different scenario worlds; developing time-lines for the scenarios; thinking more deeply about regional and local differences; and, exploring how the scenarios would frustrate or facilitate the embedding of the ecosystem approach in decision making. We found that while all of these elements had value in terms of stimulating discussion and understanding of the scenarios, they were not needed in order to address deficiencies in the original storylines in terms of plausibility or credibility. The evidence we collected therefore suggests that the existing narratives are probably sufficient as an entry point for discussions about the future of ecosystem services in the UK. What was apparent from the observations that we made in the workshops was that it would probably be a mistake to ‘over-engineer’ or ‘over-specify’ the narratives because there needs to be room for discussion and probing. We were struck how people took the existing scenarios and found new features and ideas in them than had not been identified by in the original work. For example, in one session National Security, with its emphasis on resource efficiency, was found to be ‘greener’ than it initially looks. In another Local Stewardship was discovered to need some degree of central control and regulation to work efficiently. These kinds of discussion are evidence of the reflection, deliberation and social learning that can be promoted by using the UK NEA scenarios. UK NEAFO Work Package 7: Operationalising scenarios 7 In the workshop we organised in Belfast we found that the presentation of the scenarios could be tailored to a specific region (i.e. Northern Ireland) and, through area-specific breakout groups during the workshop, to specific localities within it. However, our experiences here emphasised the need for considerable preparation, consultation with the stakeholder community, and changing of the workshop format to make the scenarios intelligible and engaging to local stakeholders. Work on the use of the scenarios in a more explicit decision support role will be reported via the work on response options (WP8), which considered how they could be used to ‘stress-test’ policy response options. The experience gained from the work undertaken in the early stages of UK NEAFO was that the scenarios appeared to provide a suitable platform for the work, but that the stresstesting methodology needed to be refined. During the follow-on we have also interviewed policy leads in Defra, for example, to gain a better picture of policy needs, and the way scenarios might usefully serve them. Apart from the challenge of ‘relevance’ it is clear that the time needed for people to work with scenarios probably means that they are less useful to policy customers in the context of their everyday work but can be useful at a very broad and strategic level. However, there is clearly an opportunity for scenarios to be used more extensively through commissioned work. The importance of commissioned work has been emphasised during the follow-on phase by invitations to observe the work of the CAMERAS1 work in Scotland, and the Noise Study being undertaken for Defra. Both are actively using the UK NEA scenarios. The outcomes of these on-going studies will be reported elsewhere by others. Nevertheless, even though these projects are at a preliminary stage they help us better understand how scenarios can be used to communicate the consequences of changes in ecosystem services to different groups and individuals. Scenarios as products: developing the model base The UK NEA scenarios were initially used to make both qualitative and quantitative projections. The quantitative work mainly involved modelling how land cover would change under the different scenarios (Haines-Young et al. 2011). Although these data were used to make an analysis of the changes in marginal economic values for some ecosystem services during the initial phase of the UK NEA, they have not been fully exploited. At the time it was recognised that there were many gaps in our understanding of the links between land cover and ecosystem services; UK NEAFO has provided the opportunity to address some of these deficiencies. Thus in the follow-on work we have sought to extend the range of models that can be used to explore the UK NEA scenarios. The modelling work has not sought to change the scenarios fundamentally, but to enrich the insights that can be derived from exploring the differences between them in a systematic, and quantitative way. The goal, has been to extend the analysis that can be built up around the narratives and hence enrich the scenarios as ‘products’. Four topic areas were selected as the focus for this work: flood and drought risk (based on an analysis of changes in river flows), biodiversity (farmland birds), marine and cultural ecosystem services. Catchment modelling We looked at the effects of land-use change on river flows under each of the UK NEA scenarios. We modelled hydrological discharge within 34 UK catchments and calculated four hydrological indicators for each catchment: average annual discharge, flood hazard, and Q5 and Q95 (measures of the magnitude of unusually high (Q5) and unusually low (Q95) flows). For our flood hazard indicator we calculated the interval between floods of a size currently occurring every 30 years. Although we kept climate constant in the models, as we wanted to isolate the effects of land cover change, we ran them for both the high and low climate change land cover variants for each scenario. 1 A Coordinated Agenda for Marine, Environment and Rural Affairs Science, 2011-2016. http://www.scotland.gov.uk/Topics/Research/About/EBAR/CAMERASsite In general, the ‘green’ scenarios, Nature@Work and Green and Pleasant Land, as well as National Security, were associated with lower flows than currently occur (when measured using any of the four indicators). However, for a given scenario there was a great deal of variability between catchments in terms of the size and statistical significance of the differences. The magnitude of change across all scenarios and catchments ranged from -13% to 6% for average annual discharge, -14 to 7% for Q5, -24 to 27 % for Q95 and -16 to 36 years for flood hazard. Differences were particularly evident between Nature@Work and World Markets, with the latter associated with higher flows than occur currently, and the majority of the statistically significant increased flows. Some catchments showed significant changes that were different in sign between these two scenarios. Taken together, our results indicate that that in managing change a balance needs to be struck between alleviating the likelihoods of increased drought and increased flooding, depending on the likely effects of these phenomena in the catchment. Farmland birds We looked at the relationship between land use data produced during the first phase of the UK NEA and models of farmland bird populations, in 1kmx1km squares covered by the Breeding Bird Survey (BBS) and Winter Farmland Bird Survey (WFBS). We used Functional Space Models to estimate the annual population growth rate under each scenario of each of the 19 farmland bird species used to calculate the farmland bird index (Gregory et al. 2004). We used this to look at the relationship between land use under the scenarios and: i) the average population growth rate for all 19 species, and ii) a subset of 11 species showing declining population trends under current land use. Overall we found that land use change across the scenarios had relatively little impact. However, the only statistically significant change was for declining species under Green and Pleasant Land, where population growth rates became significantly more negative. We used Mechanistic Models to estimate the number of over-winter ‘bird-days’ for two types of seed-eating farmland birds, a yellowhammer-type and linnet-type These species were chosen because they differ in their food preferences with respect to cereal, oil and weed seeds, but between them are representative of the diversity of seed-eating farmland birds as a whole. We found a significant decline in the ecological value of lowland agricultural areas for these species across all UK NEA scenarios, but the greatest impact was for scenarios with the highest monetised values for ecosystem services, as measured by the first phase of the UK NEA (Nature@Work, Green and Pleasant Land). This appears to be due to the fact that, compared with the baseline, the area of arable crops declines most sharply under these scenarios, due partly to changes in land use but also because of conversion of arable land to other habitats important for ecosystem services (e.g. woodland). Taken together these results imply a trade-off between overall value for ecosystem services and conservation of farmland birds, and highlight the need to consider the specific impacts of land use change on biodiversity, alongside other ecosystem services. Marine ecosystem services Only a limited attempt was made to model marine ecosystem services during the first phase of the UK NEA. In the follow-on we have conducted preliminary work to produce spatially explicit models for three important marine ecosystem services: fisheries landings, aquaculture production and carbon sequestration. We made comparisons between baseline data and time slices for 2015, 2030 UK NEAFO Work Package 7: Operationalising scenarios 9 and 2060 under four of the UK NEA scenarios that were considered most relevant for the sector, and mapped these across UK territorial waters. There is a high degree of uncertainty associated with the models, mainly due to a lack of suitable data and poor knowledge of the drivers of change. In many cases, in the absence of robust quantitative models, we needed to take the qualitative descriptions of the UK NEA scenarios and combine these with expert knowledge to estimate changes in the three types of ecosystem service. We estimated that in three of the four scenarios: Nature@Work, Local Stewardship and National Security, fisheries landings would be, by 2060 only slightly lower or at higher levels than they are today. Under World Markets, however, projected landings would decline significantly by 2060, due to a lack of regulation combined with high levels of investment from private capital. In the light of this, it was interesting that aquaculture was at higher levels under World Markets than under any of the other scenarios, although all of them showed higher levels than the baseline. This was because under this scenario more investment capital would be available to invest in fish farms. We believe that carbon sequestration would be most likely to be impacted by the World Markets and Natural Security, due to higher CO2 emissions causing an increase in ocean acidification. Our results, although tentative, mark a significant first step in attempts to map and project the impact of possible future change on marine ecosystem services. Cultural Ecosystem Services In the first phase of the UK NEA, the relationship between the drivers of change and cultural ecosystem services (CES) was mainly explored through the impact they had on land cover. For UK NEAFO, we additionally used the Monitor of Engagement for the Natural Environment (MENE) dataset. We examined how the UK NEA scenarios can be used as a framework to explore the relationship between the supply of cultural spaces in the landscape and peoples preferences for different types of natural spaces and practices in them. We have developed a Bayesian Belief Network (BBN) that allows users to explore these relationships interactively and look at the potential impacts of changes socio-demographic structure of the kind described by the UK NEA scenarios. Our spatial analysis of the MENE data showed that people tend to select locations with higher woodland cover than the average for the surroundings, when they travel intermediate distances from their home, but that this tendency declines when they travel longer distances. Woodland cover is projected to double under both Nature@Work and Green and Pleasant Land, and both provide more opportunities to visit woodland close to home than under scenarios such as World Markets. However, our analysis shows that on the basis of the current geography of people and woodlands, the way planting is targeting under Green and Pleasant Land has the potential to deliver greater joint benefits from biodiversity change and cultural ecosystem services than Nature@Work. The BBN we have developed using the HUGIN Expert software allows the relationships within the MENE data to be explored interactively; it is hosted on a prototype website that is open to the wider community. By examining the relationships between socio-demographic characteristics of the MENE respondents, the types of natural spaces they visit and the activities they do in them, this BBN tool allows users to explore the impacts of possible future change on the supply and demand of CES. Conclusion How can plausible future scenarios help understand, manage and communicate the consequences of changes in ecosystem services across all scales? In this work we have shown that they can be used to promote understanding by the deliberative processes that they engender. The UK NEA scenarios appear to be sufficiently rich and comprehensive to support debate across a wide range of topic areas relevant to current policy concerns. The scenarios can also help understanding by providing a framework in which current models can be applied and the outcome used both to test the plausibility of the scenarios themselves and to deepen the insights that can be derived from them. These analytical ‘scenario products’ can be equally important both in terms of deepening our understanding of the assumptions on which the scenarios are built and in stimulating debate about their implications. We have shown that the distinction between the ‘process’ and ‘product’ dimensions of scenario thinking is a useful one, given the many ways scenarios can be used. The distinction clarifies some of the different purposes and problems that scenarios work seeks to address. However, our work also demonstrates that both components have their strengths, and neither can be taken isolation. If we are to use scenarios to understand, manage and communicate the consequences of changes in ecosystem services across different scales and in different contexts, then targeted analytical studies developed within the qualitative framework of the UK NEA scenarios, can enrich our understanding of today’s issues and how we might respond to them

Re-examining the consumption-wealth relationship : the role of model uncertainty

This paper discusses the consumption-wealth relationship. Following the recent influential workof Lettau and Ludvigson [e.g. Lettau and Ludvigson (2001), (2004)], we use data on consumption, assets andlabor income and a vector error correction framework. Key …ndings of their work are that consumption doesrespond to permanent changes in wealth in the expected manner, but that most changes in wealth are transitoryand have no e¤ect on consumption. We investigate the robustness of these results to model uncertainty andargue for the use of Bayesian model averaging. We …nd that there is model uncertainty with regards to thenumber of cointegrating vectors, the form of deterministic components, lag length and whether the cointegratingresiduals a¤ect consumption and income directly. Whether this uncertainty has important empirical implicationsdepends on the researcher's attitude towards the economic theory used by Lettau and Ludvigson. If we workwith their model, our findings are very similar to theirs. However, if we work with a broader set of models andlet the data speak, we obtain somewhat di¤erent results. In the latter case, we …nd that the exact magnitudeof the role of permanent shocks is hard to estimate precisely. Thus, although some support exists for the viewthat their role is small, we cannot rule out the possibility that they have a substantive role to play

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

Time-integrated luminosity recorded by the BABAR detector at the PEP-II e+e- collider

This article is the Preprint version of the final published artcile which can be accessed at the link below.We describe a measurement of the time-integrated luminosity of the data collected by the BABAR experiment at the PEP-II asymmetric-energy e+e- collider at the ϒ(4S), ϒ(3S), and ϒ(2S) resonances and in a continuum region below each resonance. We measure the time-integrated luminosity by counting e+e-→e+e- and (for the ϒ(4S) only) e+e-→μ+μ- candidate events, allowing additional photons in the final state. We use data-corrected simulation to determine the cross-sections and reconstruction efficiencies for these processes, as well as the major backgrounds. Due to the large cross-sections of e+e-→e+e- and e+e-→μ+μ-, the statistical uncertainties of the measurement are substantially smaller than the systematic uncertainties. The dominant systematic uncertainties are due to observed differences between data and simulation, as well as uncertainties on the cross-sections. For data collected on the ϒ(3S) and ϒ(2S) resonances, an additional uncertainty arises due to ϒ→e+e-X background. For data collected off the ϒ resonances, we estimate an additional uncertainty due to time dependent efficiency variations, which can affect the short off-resonance runs. The relative uncertainties on the luminosities of the on-resonance (off-resonance) samples are 0.43% (0.43%) for the ϒ(4S), 0.58% (0.72%) for the ϒ(3S), and 0.68% (0.88%) for the ϒ(2S).This work is supported by the US Department of Energy and National Science Foundation, the Natural Sciences and Engineering Research Council (Canada), the Commissariat à l’Energie Atomique and Institut National de Physique Nucléaire et de Physiquedes Particules (France), the Bundesministerium für Bildung und Forschung and Deutsche Forschungsgemeinschaft (Germany), the Istituto Nazionale di Fisica Nucleare (Italy), the Foundation for Fundamental Research on Matter (The Netherlands), the Research Council of Norway, the Ministry of Education and Science of the Russian Federation, Ministerio de Ciencia e Innovación (Spain), and the Science and Technology Facilities Council (United Kingdom). Individuals have received support from the Marie-Curie IEF program (European Union) and the A.P. Sloan Foundation (USA)