750 research outputs found

    Temporal and spatial dynamics of CO2 air-sea flux in the Gulf of Maine

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    Ocean surface layer carbon dioxide (CO2) data collected in the Gulf of Maine from 2004 to 2008 are presented. Monthly shipboard observations are combined with additional higher‐resolution CO2 observations to characterize CO2 fugacity ( fCO2) and CO2 flux over hourly to interannual time scales. Observed fCO2 andCO2 flux dynamics are dominated by a seasonal cycle, with a large spring influx of CO2 and a fall‐to‐winter efflux back to the atmosphere. The temporal results at inner, middle, and outer shelf locations are highly correlated, and observed spatial variability is generally small relative to the monthly to seasonal temporal changes. The averaged annual flux is in near balance and is a net source of carbon to the atmosphere over 5 years, with a value of +0.38 mol m−2 yr−1. However, moderate interannual variation is also observed, where years 2005 and 2007 represent cases of regional source (+0.71) and sink (−0.11) anomalies. We use moored daily CO2 measurements to quantify aliasing due to temporal undersampling, an important error budget term that is typically unresolved. The uncertainty of our derived annual flux measurement is ±0.26 mol m−2 yr−1 and is dominated by this aliasing term. Comparison of results to the neighboring Middle and South Atlantic Bight coastal shelf systems indicates that the Gulf of Maine exhibits a similar annual cycle and range of oceanic fCO2 magnitude but differs in the seasonal phase. It also differs by enhanced fCO2 controls by factors other than temperature‐driven solubility, including biological drawdown, fall‐to‐winter vertical mixing, and river runoff

    A Comparison of Machine Learning Algorithms for the Surveillance of Autism Spectrum Disorder

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    The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. We applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms' performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations

    Services for Adults with an Autism Spectrum Disorder

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    Objective: The need for useful evidence about services is increasing as larger numbers of children identified with an autism spectrum disorder age toward adulthood. The objective of this review was to characterize the topical and methodological aspects of research on services for supporting success in work, education, and social participation among adults with an autism spectrum disorder and to propose recommendations for moving this area of research forward. Method: Review of literature published in English from 2000 to 2010.Results: We found that the evidence base about services for adults with an ASD is underdeveloped and can be considered a field of inquiry that is relatively unformed. Extant research does not reflect the demographic or impairment heterogeneity of the population, the range of services that adults with autism require in order to function with purposeful lives in the community, and the need for coordination across service systems and sectors. Conclusions: Future studies must examine issues related to cost and efficiency given the broader sociopolitical and economic context of service provision. Furthermore, future research needs to consider how demographic and impairment heterogeneity have implications for building an evidence base that will have greater external validity

    JASPer controls interphase histone H3S10 phosphorylation by chromosomal kinase JIL-1 in Drosophila

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    In flies, the chromosomal kinase JIL-1 is responsible for most interphase histone H3S10 phosphorylation and has been proposed to protect active chromatin from acquiring heterochromatic marks, such as dimethylated histone H3K9 (H3K9me2) and HP1. Here, we show that JIL-1's targeting to chromatin depends on a PWWP domain-containing protein JASPer (JIL-1 Anchoring and Stabilizing Protein). JASPer-JIL-1 (JJ)-complex is the major form of kinase in vivo and is targeted to active genes and telomeric transposons via binding of the PWWP domain of JASPer to H3K36me3 nucleosomes, to modulate transcriptional output. JIL-1 and JJ-complex depletion in cycling cells lead to small changes in H3K9me2 distribution at active genes and telomeric transposons. Finally, we identify interactors of the endogenous JJ-complex and propose that JIL-1 not only prevents heterochromatin formation but also coordinates chromatin-based regulation in the transcribed part of the genome

    Advanced Parental Age and the Risk of Autism Spectrum Disorder

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    This study evaluated independent effects of maternal and paternal age on risk of autism spectrum disorder. A case-cohort design was implemented using data from 10 US study sites participating in the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network. The 1994 birth cohort included 253,347 study-site births with complete parental age information. Cases included 1,251 children aged 8 years with complete parental age information from the same birth cohort and identified as having an autism spectrum disorder based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision criteria. After adjustment for the other parent's age, birth order, maternal education, and other covariates, both maternal and paternal age were independently associated with autism (adjusted odds ratio for maternal age ≄35 vs. 25–29 years = 1.3, 95% confidence interval: 1.1, 1.6; adjusted odds ratio for paternal age ≄40 years vs. 25–29 years = 1.4, 95% confidence interval: 1.1, 1.8). Firstborn offspring of 2 older parents were 3 times more likely to develop autism than were third- or later-born offspring of mothers aged 20–34 years and fathers aged <40 years (odds ratio = 3.1, 95% confidence interval: 2.0, 4.7). The increase in autism risk with both maternal and paternal age has potential implications for public health planning and investigations of autism etiology

    Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

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    The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

    Standalone vertex ïŹnding in the ATLAS muon spectrometer

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    A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

    Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

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    Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ Îł, H → Z Z∗ →4l and H →W W∗ →lÎœlÎœ. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined ïŹts probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

    Measurement of the top quark pair cross section with ATLAS in pp collisions at √s=7 TeV using final states with an electron or a muon and a hadronically decaying τ lepton

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    A measurement of the cross section of top quark pair production in proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 7 TeV is reported. The data sample used corresponds to an integrated luminosity of 2.05 fb -1. Events with an isolated electron or muon and a τ lepton decaying hadronically are used. In addition, a large missing transverse momentum and two or more energetic jets are required. At least one of the jets must be identified as originating from a b quark. The measured cross section, σtt-=186±13(stat.)±20(syst.)±7(lumi.) pb, is in good agreement with the Standard Model prediction
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