674 research outputs found

    Effect of venting range hood flow rate on size-resolved ultrafine particle concentrations from gas stove cooking

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    Cooking is the main source of ultrafine particles (UFP) in homes. This study investigated the effect of venting range hood flow rate on size-resolved UFP concentrations from gas stove cooking. The same cooking protocol was conducted 60 times using three venting range hoods operated at six flow rates in twin research houses. Size-resolved particle (10–420 nm) concentrations were monitored using a NanoScan scanning mobility particle sizer (SMPS) from 15 min before cooking to 3 h after the cooking had stopped. Cooking increased the background total UFP number concentrations to 1.3 × 103 particles/cm3 on average, with a mean exposure-relevant source strength of 1.8 × 1012 particles/min. Total particle peak reductions ranged from 25% at the lowest fan flow rate of 36 L/s to 98% at the highest rate of 146 L/s. During the operation of a venting range hood, particle removal by deposition was less significant compared to the increasing air exchange rate driven by exhaust ventilation. Exposure to total particles due to cooking varied from 0.9 to 5.8 × 104 particles/cm3·h, 3 h after cooking ended. Compared to the 36 L/s range hood, higher flow rates of 120 and 146 L/s reduced the first-hour post-cooking exposure by 76% and 85%, respectively. © 2018 Crown Copyright. Published with license by Taylor & Francis Group, LLC

    Stoics against stoics in Cudworth's "A Treatise of Freewill"

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    In his 'A Treatise of Freewill', Ralph Cudworth argues against Stoic determinism by drawing on what he takes to be other concepts found in Stoicism, notably the claim that some things are ‘up to us’ and that these things are the product of our choice. These concepts are central to the late Stoic Epictetus and it appears at first glance as if Cudworth is opposing late Stoic voluntarism against early Stoic determinism. This paper argues that in fact, despite his claim to be drawing on Stoic doctrine, Cudworth uses these terms with a meaning first articulated only later, by the Peripatetic commentator Alexander of Aphrodisias

    Optimally splitting cases for training and testing high dimensional classifiers

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    <p>Abstract</p> <p>Background</p> <p>We consider the problem of designing a study to develop a predictive classifier from high dimensional data. A common study design is to split the sample into a training set and an independent test set, where the former is used to develop the classifier and the latter to evaluate its performance. In this paper we address the question of what proportion of the samples should be devoted to the training set. How does this proportion impact the mean squared error (MSE) of the prediction accuracy estimate?</p> <p>Results</p> <p>We develop a non-parametric algorithm for determining an optimal splitting proportion that can be applied with a specific dataset and classifier algorithm. We also perform a broad simulation study for the purpose of better understanding the factors that determine the best split proportions and to evaluate commonly used splitting strategies (1/2 training or 2/3 training) under a wide variety of conditions. These methods are based on a decomposition of the MSE into three intuitive component parts.</p> <p>Conclusions</p> <p>By applying these approaches to a number of synthetic and real microarray datasets we show that for linear classifiers the optimal proportion depends on the overall number of samples available and the degree of differential expression between the classes. The optimal proportion was found to depend on the full dataset size (n) and classification accuracy - with higher accuracy and smaller <it>n </it>resulting in more assigned to the training set. The commonly used strategy of allocating 2/3rd of cases for training was close to optimal for reasonable sized datasets (<it>n </it>≥ 100) with strong signals (i.e. 85% or greater full dataset accuracy). In general, we recommend use of our nonparametric resampling approach for determing the optimal split. This approach can be applied to any dataset, using any predictor development method, to determine the best split.</p

    Can changing the timing of outdoor air intake reduce indoor concentrations of traffic-related pollutants in schools?

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    Traffic emissions have been associated with a wide range of adverse health effects. Many schools are situated close to major roads, and as children spend much of their day in school, methods to reduce traffic‐related air pollutant concentrations in the school environment are warranted. One promising method to reduce pollutant concentrations in schools is to alter the timing of the ventilation so that high ventilation time periods do not correspond to rush hour traffic. Health Canada, in collaboration with the Ottawa‐Carleton District School Board, tested the effect of this action by collecting traffic‐related air pollution data from four schools in Ottawa, Canada, during October and November 2013. A baseline and intervention period was assessed in each school. There were statistically significant (P < 0.05) reductions in concentrations of most of the pollutants measured at the two late‐start (9 AM start) schools, after adjusting for outdoor concentrations and the absolute indoor–outdoor temperature difference. The intervention at the early‐start (8 AM start) schools did not have significant reductions in pollutant concentrations. Based on these findings, changing the timing of the ventilation may be a cost‐effective mechanism of reducing traffic‐related pollutants in late‐start schools located near major roads

    Validity of an isometric mid-thigh pull dynamometer in male youth athletes

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    The purpose of the present study was to investigate the validity of an isometric mid-thigh pull dynamometer against a criterion measure (i.e., 1,000 Hz force platform) for assessing muscle strength in male youth athletes. Twenty-two male adolescent (age 15.3 ± 0.5 years) rugby league players performed four isometric mid-thigh pull efforts (i.e., two on the dynamometer and two on the force platform) separated by 5 minutes rest in a randomised and counterbalanced order. Mean bias, typical error of estimate (TEE) and Pearson correlation coefficient for peak force (PF) and peak force minus body weight (PFBW) from the force platform were validated against peak force from the dynamometer (DynoPF). When compared to PF and PFBW, mean bias (with 90% Confidence limits) for DynoPF was very large (-32.4 [-34.2 to -30.6] %) and moderate (-10.0 [-12.8 to -7.2] %), respectively. The TEE was moderate for both PF (8.1 [6.3 to 11.2] %) and PFBW (8.9 [7.0 to 12.4]). Correlations between DynoPF and PF (r 0.90 [0.79 to 0.95]) and PFBW (r 0.90 [0.80 to 0.95] were nearly perfect. The isometric mid-thigh pull assessed using a dynamometer underestimated PF and PFBW obtained using a criterion force platform. However, strong correlations between the dynamometer and force platform suggest that a dynamometer provides an appropriate alternative to assess isometric mid-thigh pull strength when a force platform is not available. Therefore, practitioners can use an isometric mid-thigh pull dynamometer to assess strength in the field with youth athletes but should be aware that it underestimates peak force

    Criteria for the use of omics-based predictors in clinical trials.

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    The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to 'omics'-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength. The checklist will be used to evaluate proposals for NCI-sponsored clinical trials in which omics tests will be used to guide therapy
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