An electrostatic positron beam and its use in an experimental investigation of the first excited state of positronium

The purely leptonic character of positronium, the bound state of an electron and positron, presents the opportunity to test quantum electrodynamics in the absence of quantum chromodynamical effects. In recent years persistent discrepancies have arisen between experiment and theory for values of the decay rate of the l3S1 state, thus far unreconciled, and therefore investigations of other positronium states desirable. The main body of this work has involved a study of the first excited state of this system, known as Ps*. Its production by positron impact on solid surfaces was examined, and an experiment to measure the radiative lifetime of the 23P1-13S1 transition performed. In order to carry out this work it was necessary to design an electrostatic positron beam, operable at low transport energies, ∼ 100eV, with reasonable efficiency and beam quality. Measurements of the Ps* yield have supported recent disparate measurements by providing a link between, and possible re-interpretation of, some aspects of these studies. Peak yields of several percent were observed from a variety of targets, all without prior surface treatment. Studies of positron re-emission from the same untreated targets were also made in order to estimate the energy regime of the Ps* formed and therefore shed some additional light on the formation process. An attempt to make the first measurement of a positronium radiative lifetime was made, with many unforeseen difficulties arising. This work has identified the main problems that may be encountered in an experiment of this kind, and steps were taken to minimise their impact, to the point that the transition was isolated. Such steps however have precluded a meaningful analysis of the lifetime by virtue of their effects on the resolution of the measuring system, however as a result of the experience gained through this work the prospects for future successful experiments are much improved

ATLAS: A flexible and extensible architecture for linguistic annotation

We describe a formal model for annotating linguistic artifacts, from which we derive an application programming interface (API) to a suite of tools for manipulating these annotations. The abstract logical model provides for a range of storage formats and promotes the reuse of tools that interact through this API. We focus first on ``Annotation Graphs,'' a graph model for annotations on linear signals (such as text and speech) indexed by intervals, for which efficient database storage and querying techniques are applicable. We note how a wide range of existing annotated corpora can be mapped to this annotation graph model. This model is then generalized to encompass a wider variety of linguistic ``signals,'' including both naturally occuring phenomena (as recorded in images, video, multi-modal interactions, etc.), as well as the derived resources that are increasingly important to the engineering of natural language processing systems (such as word lists, dictionaries, aligned bilingual corpora, etc.). We conclude with a review of the current efforts towards implementing key pieces of this architecture.Comment: 8 pages, 9 figure

Pump-probe differencing technique for cavity-enhanced, noise-canceling saturation laser spectroscopy

We present an experimental technique enabling mechanical-noise free, cavity-enhanced frequency measurements of an atomic transition and its hyperfine structure. We employ the 532nm frequency doubled output from a Nd:YAG laser and an iodine vapour cell. The cell is placed in a traveling-wave Fabry-Perot interferometer (FPI) with counter-propagating pump and probe beams. The FPI is locked using the Pound-Drever-Hall (PDH) technique. Mechanical noise is rejected by differencing pump and probe signals. In addition, this differenced error signal gives a sensitive measure of differential non-linearity within the FPI.Comment: 3 pages, 5 figures, submitted to Optics Letter

Applicant Reactions to Selection Procedures: An Updated Model and Meta-Analysis

[Excerpt] An updated theoretical model of applicant reactions to selection procedures is proposed and tested using meta-analysis. Results from 86 independent samples (N = 48,750) indicated that applicants who hold positive perceptions about selection are more likely to view the organization favorably and report stronger intentions to accept job offers and recommend the employer to others. Applicant perceptions were positively correlated with actual and perceived performance on selection tools and with self perceptions. The average correlation between applicant perceptions and gender, age, and ethnic background was near zero. Face validity and perceived predictive validity were strong predictors of many applicant perceptions including procedural justice, distributive justice, attitudes towards tests, and attitudes towards selection. Interviews and work samples were perceived more favorably than cognitive ability tests, which were perceived more favorably than personality inventories, honesty tests, biodata, and graphology. The discussion identifies remaining theoretical and methodological issues as well as directions for future research

Extending reservoir computing with random static projections : a hybrid between extreme learning and RC

Reservoir Computing is a relatively new paradigm in the field of neural networks that has shown promise in applications where traditional recurrent neural networks have performed poorly. The main advantage of using reservoirs is that only the output weights are trained, reducing computational requirements significantly. There is a trade-off, however, between the amount of memory a reservoir can possess and its capability of mapping data into a highly non-linear transformation space. A new, hybrid architecture, combining a reservoir with an extreme learning machine, is presented which overcomes this trade-off, whose performance is demonstrated on a 4th order polynomial modelling task and an isolated spoken digit recognition task

Research Investments and Market Structure in the Food Processing, Agricultural Input, and Biofuel Industries Worldwide

Meeting growing global demand for food, fiber, and biofuel requires robust investment in agricultural research and development (R&D) from both public and private sectors. This study examines global R&D spending by private industry in seven agricultural input sectors, food manufacturing, and biofuel and describes the changing structure of these industries. In 2007 (the latest year for which comprehensive estimates are available), the private sector spent 19.7 billion on food and agricultural research (56 percent in food manufacturing and 44 percent in agricultural input sectors) and accounted for about half of total public and private spending on food and agricultural R&D in high-income countries. In R&D related to biofuel, annual private-sector investments are estimated to have reached 1.47 billion worldwide by 2009. Incentives to invest in R&D are influenced by market structure and other factors. Agricultural input industries have undergone significant structural change over the past two decades, with industry concentration on the rise. A relatively small number of large, multinational firms with global R&D and marketing networks account for most R&D in each input industry. Rising market concentration has not generally been associated with increased R&D investment as a percentage of industry sales.agricultural biotechnology, agricultural chemicals, agricultural inputs, animal breeding, animal health, animal nutrition, aquaculture, biofuel, concentration ratio, crop breeding, crop protection, farm machinery, fertilizers, Herfindahl index, globalization, market share, market structure, research intensity, seed improvement, Productivity Analysis,

Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning. We present a more holistic approach to determine ecosystem function resilience, using long‐term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into “response guilds.” We then use “production functions” combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning. Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny—a useful insight for conservation management of rare species with limited population monitoring data. Our approach holds promise for overcoming the impasse in predicting the responses of ecosystem functions to environmental change. Quantifying co‐varying species' responses to multivariate environmental change should enable us to significantly advance our predictions of ecosystem function resilience and enable proactive ecosystem management

The Perfect Spill: Solutions for Averting the Next Deepwater Horizon

In this article the authors comment on the oil spill incident from the Deepwater Horizon, particularly on its economic and ecological damages. The authors highlighted the disaster as an event wherein much is needed to be learned so that future oil spills can be avoided. One lesson refers to the valuability of natural capital assets and other public entities that are at risks due to private interests and that better regulations and incentives are needed to protect these assets against risks

Molecular epidemiology of NDM-1-producing Enterobacteriaceae and Acinetobacter baumannii isolates from Pakistan

The molecular epidemiology of 66 NDM-producing isolates from 2 Pakistani hospitals was investigated, with their genetic relatedness determined using repetitive sequence-based PCR (Rep-PCR). PCR-based replicon typing and screening for antibiotic resistance genes encoding carbapenemases, other β-lactamases, and 16S methylases were also performed. Rep-PCR suggested a clonal spread of Enterobacter cloacae and Escherichia coli. A number of plasmid replicon types were identified, with the incompatibility A/C group (IncA/C) being the most common (78%). 16S methylase-encoding genes were coharbored in 81% of NDM-producing Enterobacteriaceae. Copyrigh