Measurements of Photon and Neutral Pion Production in Heavy Ion Collisions at RHIC

Inclusive transverse momentum spectra of photons and neutral pions about mid-rapidity are presented for Au+Au collisions at sqrt(s_NN} = 130 GeV. Photon pair conversions have been reconstructed from charged tracks measured with the central Time Projection Chamber (TPC) of STAR. Contributions of the pi^0 -> \gamma\gamma decay in the inclusive photon spectra have been studied. It was found that this contribution begins to decrease at a transverse momentum of 1.65 GeV/c in the top 11% most central centrality class.Comment: 5 pages, 3 figures, contribution to the Proceedings of Quark Matter 2002, Nantes, France, July 18-24, 200

The Lothian Birth Cohort 1936: a study to examine influences on cognitive ageing from age 11 to age 70 and beyond

BACKGROUND: Cognitive ageing is a major burden for society and a major influence in lowering people's independence and quality of life. It is the most feared aspect of ageing. There are large individual differences in age-related cognitive changes. Seeking the determinants of cognitive ageing is a research priority. A limitation of many studies is the lack of a sufficiently long period between cognitive assessments to examine determinants. Here, the aim is to examine influences on cognitive ageing between childhood and old age. METHODS/DESIGN: The study is designed as a follow-up cohort study. The participants comprise surviving members of the Scottish Mental Survey of 1947 (SMS1947; N = 70,805) who reside in the Edinburgh area (Lothian) of Scotland. The SMS1947 applied a valid test of general intelligence to all children born in 1936 and attending Scottish schools in June 1947. A total of 1091 participants make up the Lothian Birth Cohort 1936. They undertook: a medical interview and examination; physical fitness testing; extensive cognitive testing (reasoning, memory, speed of information processing, and executive function); personality, quality of life and other psycho-social questionnaires; and a food frequency questionnaire. They have taken the same mental ability test (the Moray House Test No. 12) at age 11 and age 70. They provided blood samples for DNA extraction and testing and other biomarker analyses. Here we describe the background and aims of the study, the recruitment procedures and details of numbers tested, and the details of all examinations. DISCUSSION: The principal strength of this cohort is the rarely captured phenotype of lifetime cognitive change. There is additional rich information to examine the determinants of individual differences in this lifetime cognitive change. This protocol report is important in alerting other researchers to the data available in the cohort

Profiles of physical, emotional and psychosocial wellbeing in the Lothian birth cohort 1936

<p>Abstract</p> <p>Background</p> <p>Physical, emotional, and psychosocial wellbeing are important domains of function. The aims of this study were to explore the existence of separable groups among 70-year olds with scores representing physical function, perceived quality of life, and emotional wellbeing, and to characterise any resulting groups using demographic, personality, cognition, health and lifestyle variables.</p> <p>Methods</p> <p>We used latent class analysis (LCA) to identify possible groups.</p> <p>Results</p> <p>Results suggested there were 5 groups. These included High (n = 515, 47.2% of the sample), Average (n = 417, 38.3%), and Poor Wellbeing (n = 37, 3.4%) groups. The two other groups had contrasting patterns of wellbeing: one group scored relatively well on physical function, but low on emotional wellbeing (Good Fitness/ Low Spirits,n = 60, 5.5%), whereas the other group showed low physical function but relatively well emotional wellbeing (Low Fitness/Good Spirits, n = 62, 5.7%). Salient characteristics that distinguished all the groups included smoking and drinking behaviours, personality, and illness.</p> <p>Conclusions</p> <p>Despite there being some evidence of these groups, the results also support a largely one-dimensional construct of wellbeing in old age—for the domains assessed here—though with some evidence that some individuals have uneven profiles.</p

Childhood neurodevelopment after prescription of maintenance methadone for opioid dependency in pregnancy:a systematic review and meta-analysis

Aim: To systematically review and meta‐analyse studies of neurodevelopmental outcome of children born to mothers prescribed methadone in pregnancy. Method: MEDLINE, Embase, and PsycINFO were searched for studies published from 1975 to 2017 reporting neurodevelopmental outcomes in children with prenatal methadone exposure. Results: Forty‐one studies were identified (2283 participants). Eight studies were amenable to meta‐analysis: at 2 years the Mental Development Index weighted mean difference of children with prenatal methadone exposure compared with unexposed infants was −4.3 (95% confidence interval [CI] −7.24 to −1.63), and the Psychomotor Development Index weighted mean difference was −5.42 (95% CI −10.55 to −0.28). Seven studies reported behavioural scores and six found scores to be lower among methadone‐exposed children. Twelve studies reported visual outcomes: nystagmus and strabismus were common; five studies reported visual evoked potentials of which four described abnormalities. Factors that limited the quality of some studies, and introduced risk of bias, included absence of blinding, small sample size, high attrition, uncertainty about polydrug exposure, and lack of comparison group validity. Interpretation: Children born to mothers prescribed methadone in pregnancy are at risk of neurodevelopmental problems but risk of bias limits inference about harm. Research into management of opioid use disorder in pregnancy should include evaluation of childhood neurodevelopmental outcome

Branch Mode Selection during Early Lung Development

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modesComment: Initially published at PLoS Comput Bio

Feature selection for chemical sensor arrays using mutual information

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays

Estimated pre-morbid IQ effects on cognitive and functional outcomes in Alzheimer disease: a longitudinal study in a treated cohort

Abstract Background Cognitive reserve is thought to influence the degree of neuropathology needed for diagnosis of Alzheimer disease (AD). Cognitive reserve can be operationally defined as the hypothesized capacity of the mature adult brain to sustain the effects of disease or injury without manifesting clinical symptoms of AD, but sufficient to cause clinical dementia in an individual possessing less cognitive reserve. Its effect on the subsequent course of AD is less clear. Pre-morbid IQ is a useful measure of cognitive reserve. Methods We studied 659 consecutive patients with AD at a tertiary referral memory clinic. Patients were assessed on six cognitive tests at baseline. Activities of Daily Living (ADL) were measured on the Instrumental Activities of Daily Living (IADL) scale and Physical Self-Maintenance Scale (PSMS). The National Adult Reading Test (NART) was used to estimate pre-morbid IQ. Patients were followed up after starting a cholinesterase inhibitor over 78 weeks. Mixed general linear models estimated the effects of NART on cognition and ADL. Results Three hundred and fifty-five patients had NART scored with a mean estimated pre-morbid IQ of 104.7 (standard deviation 18.5). NART increased overall cognitive ability by 2.7% for every 10 IQ points (p Conclusion Our data support the hypothesis that cognitive reserve continues to have a limited influence on cognition after AD has been diagnosed and thus, indirectly, has an impact on ADL.</p

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

The potential for land sparing to offset greenhouse gas emissions from agriculture

Greenhouse gas emissions from global agriculture are increasing at around 1% per annum, yet substantial cuts in emissions are needed across all sectors. The challenge of reducing agricultural emissions is particularly acute, because the reductions achievable by changing farming practices are limited and are hampered by rapidly rising food demand. Here we assess the technical mitigation potential offered by land sparing-increasing agricultural yields, reducing farm land area and actively restoring natural habitats on the land spared. Restored habitats can sequester carbon and can offset emissions from agriculture. Using the United Kingdom as an example, we estimate net emissions in 2050 under a range of future agricultural scenarios. We find that a land-sparing strategy has the technical potential to achieve significant reductions in net emissions from agriculture and land-use change. Coupling land sparing with demand-side strategies to reduce meat consumption and food waste can further increase the technical mitigation potential, however economic and implementation considerations might limit the degree to which this technical potential could be realised in practice.This research was funded by the Cambridge Conservation Initiative Collaborative Fund for Conservation and we thank its major sponsor Arcadia. We thank J. Bruinsma for the provision of demand data, the CEH for the provision of soil data and J. Spencer for invaluable discussions. A.L. was supported by a Gates Cambridge Scholarship.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nclimate291