A New Model of Trend Inflation

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.

Fingerprinting the impacts of global change on tropical forests

Recent observations of widespread changes in mature tropical forests such as increasing tree growth, recruitment and mortality rates and increasing above-ground biomass suggest that 'global change' agents may be causing predictable changes in tropical forests. However, consensus over both the robustness of these changes and the environmental drivers that may be causing them is yet to emerge. This paper focuses on the second part of this debate. We review (i) the evidence that the physical, chemical and biological environment that tropical trees grow in has been altered over recent decades across large areas of the tropics, and (ii) the theoretical, experimental and observational evidence regarding the most likely effects of each of these changes on tropical forests. Ten potential widespread drivers of environmental change were identified: temperature, precipitation, solar radiation, climatic extremes (including El Niño Southern Oscillation events), atmospheric CO2 concentrations, nutrient deposition, O3/acid depositions, hunting, land-use change and increasing liana numbers. We note that each of these environmental changes is expected to leave a unique 'fingerprint' in tropical forests, as drivers directly force different processes, have different distributions in space and time and may affect some forests more than others (e.g. depending on soil fertility). Thus, in the third part of the paper we present testable a priori predictions of forest responses to assist ecologists in attributing particular changes in forests to particular causes across multiple datasets. Finally, we discuss how these drivers may change in the future and the possible consequences for tropical forests

Collaboration in the Semantic Grid: a Basis for e-Learning

The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

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

Rotational Velocities of Individual Components in Very Low Mass Binaries

We present rotational velocities for individual components of 11 very low mass (VLM) binaries with spectral types between M7 and L7.5. These results are based on observations taken with the near-infrared spectrograph, NIRSPEC, and the Keck II laser guide star adaptive optics system. We find that the observed sources tend to be rapid rotators (v sin i > 10 km s^(–1)), consistent with previous seeing-limited measurements of VLM objects. The two sources with the largest v sin i, LP 349–25B and HD 130948C, are rotating at ~30% of their break-up speed, and are among the most rapidly rotating VLM objects known. Furthermore, five binary systems, all with orbital semimajor axes ≾3.5 AU, have component v sin i values that differ by greater than 3σ. To bring the binary components with discrepant rotational velocities into agreement would require the rotational axes to be inclined with respect to each other, and that at least one component is inclined with respect to the orbital plane. Alternatively, each component could be rotating at a different rate, even though they have similar spectral types. Both differing rotational velocities and inclinations have implications for binary star formation and evolution. We also investigate possible dynamical evolution in the triple system HD 130948A–BC. The close binary brown dwarfs B and C have significantly different v sin i values. We demonstrate that components B and C could have been torqued into misalignment by the primary star, A, via orbital precession. Such a scenario can also be applied to another triple system in our sample, GJ 569A–Bab. Interactions such as these may play an important role in the dynamical evolution of VLM binaries. Finally, we note that two of the binaries with large differences in component v sin i, LP 349–25AB and 2MASS 0746+20AB, are also known radio sources

The correlation between reading and mathematics ability at age twelve has a substantial genetic component

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children’s ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child’s cognitive abilities at age twelve

Personalized Exposure Assessment: Promising Approaches for Human Environmental Health Research

New technologies and methods for assessing human exposure to chemicals, dietary and lifestyle factors, infectious agents, and other stressors provide an opportunity to extend the range of human health investigations and advance our understanding of the relationship between environmental exposure and disease. An ad hoc Committee on Environmental Exposure Technology Development was convened to identify new technologies and methods for deriving personalized exposure measurements for application to environmental health studies. The committee identified a “toolbox” of methods for measuring external (environmental) and internal (biologic) exposure and assessing human behaviors that influence the likelihood of exposure to environmental agents. The methods use environmental sensors, geographic information systems, biologic sensors, toxicogenomics, and body burden (biologic) measurements. We discuss each of the methods in relation to current use in human health research; specific gaps in the development, validation, and application of the methods are highlighted. We also present a conceptual framework for moving these technologies into use and acceptance by the scientific community. The framework focuses on understanding complex human diseases using an integrated approach to exposure assessment to define particular exposure–disease relationships and the interaction of genetic and environmental factors in disease occurrence. Improved methods for exposure assessment will result in better means of monitoring and targeting intervention and prevention programs

Heterologous Tissue Culture Expression Signature Predicts Human Breast Cancer Prognosis

BACKGROUND: Cancer patients have highly variable clinical outcomes owing to many factors, among which are genes that determine the likelihood of invasion and metastasis. This predisposition can be reflected in the gene expression pattern of the primary tumor, which may predict outcomes and guide the choice of treatment better than other clinical predictors. METHODOLOGY/PRINCIPAL FINDINGS: We developed an mRNA expression-based model that can predict prognosis/outcomes of human breast cancer patients regardless of microarray platform and patient group. Our model was developed using genes differentially expressed in mouse plasma cell tumors growing in vivo versus those growing in vitro. The prediction system was validated using published data from three cohorts of patients for whom microarray and clinical data had been compiled. The model stratified patients into four independent survival groups (BEST, GOOD, BAD, and WORST: log-rank test p = 1.7×10(−8)). CONCLUSIONS: Our model significantly improved the survival prediction over other expression-based models and permitted recognition of patients with different prognoses within the estrogen receptor-positive group and within a single pathological tumor class. Basing our predictor on a dataset that originated in a different species and a different cell type may have rendered it less sensitive to proliferation differences and endowed it with wide applicability. SIGNIFICANCE: Prognosis prediction for patients with breast cancer is currently based on histopathological typing and estrogen receptor positivity. Yet both assays define groups that are heterogeneous in survival. Gene expression profiling allows subdivision of these groups and recognition of patients whose tumors are very unlikely to be lethal and those with much grimmer outlooks, which can augment the predictive power of conventional tumor analysis and aid the clinician in choosing relaxed vs. aggressive therapy

Unlocking the bottleneck in forward genetics using whole-genome sequencing and identity by descent to isolate causative mutations

Forward genetics screens with N-ethyl-N-nitrosourea (ENU) provide a powerful way to illuminate gene function and generate mouse models of human disease; however, the identification of causative mutations remains a limiting step. Current strategies depend on conventional mapping, so the propagation of affected mice requires non-lethal screens; accurate tracking of phenotypes through pedigrees is complex and uncertain; out-crossing can introduce unexpected modifiers; and Sanger sequencing of candidate genes is inefficient. Here we show how these problems can be efficiently overcome using whole-genome sequencing (WGS) to detect the ENU mutations and then identify regions that are identical by descent (IBD) in multiple affected mice. In this strategy, we use a modification of the Lander-Green algorithm to isolate causative recessive and dominant mutations, even at low coverage, on a pure strain background. Analysis of the IBD regions also allows us to calculate the ENU mutation rate (1.54 mutations per Mb) and to model future strategies for genetic screens in mice. The introduction of this approach will accelerate the discovery of causal variants, permit broader and more informative lethal screens to be used, reduce animal costs, and herald a new era for ENU mutagenesis.The High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics is funded by Wellcome Trust grant reference 090532/Z/09/Z and MRC Hub grant G0900747 91070. This study was supported by Wellcome Trust Strategic Award 082030 (CCG), Wellcome Trust Studentship 094446/Z/10/Z (KRB), the Oxford NIHR Biomedical Research Centre, and the MRC Human Immunology Unit (RJC). AJR and GL were supported by Wellcome Trust grant 090532/Z/ 09/Z, CCG and AE by a Major initiative Award from the Clive and Vera Ramaciotti Foundation, and AE by an NHMRC Career Development Award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript