167 research outputs found

    Structural Loads and Preliminary Structural Design for a World Speed Record-Breaking Turbo-Prop Racing Airplane

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    The Cal Poly SLO Turbo-Prop Racer project aims to design a world speed record-breaking aircraft, capable of flying more than 550 miles per hour on a 3-kilometer closed course. To further this endeavor, this thesis presents the calculations of load distributions across the aircraft’s wing and tail and preliminary structural estimates of primary structural components for verification of the loads calculations and for use in a future finite element model. The aircraft’s fundamental design characteristics effect on the structure of the aircraft, namely the unique Y-tail design, are first examined. Then, loads are calculated in accordance with the regulation dictated by CS-23. Maneuvering loads, gust loads, ground loads, and engine loads are calculated through the Vortex-Lattice Method and CS-23 to provide input for detailed structural analysis. Structural thickness estimates are found using simplified analytical stress analysis. The wing and tail’s primary spars’ spar-caps and shear-webs, the wing and tail skins, and the rear fuselage are all calculated. The loads and thicknesses found are shown to be within order of reason and to support the fundamental design characteristics of the aircraft, pushing the project to continue toward its goal

    A demonstration of modeling count data with an application to physical activity

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    Counting outcomes such as days of physical activity or servings of fruits and vegetables often have distributions that are highly skewed toward the right with a preponderance of zeros, posing analytical challenges. This paper demonstrates how such outcomes may be analyzed with several modifications to Poisson regression. Five regression models 1) Poisson, 2) overdispersed Poisson, 3) negative binomial, 4) zero-inflated Poisson (ZIP), and 5) zero-inflated negative binomial (ZINB) are fitted to data assessing predictors of vigorous physical activity (VPA) among Latina women. The models are described, and analytical and graphical approaches are discussed to aid in model selection. Poisson regression provided a poor fit where 82% of the subjects reported no days of VPA. The fit improved considerably with the negative binomial and ZIP models. There was little difference in fit between the ZIP and ZINB models. Overall, the ZIP model fit best. No days of VPA were associated with poorer self-reported health and less assimilation to Anglo culture, and marginally associated with increasing BMI. The intensity portion of the model suggested that increasing days of VPA were associated with more education, and marginally associated with increasing age. These underutilized models provide useful approaches for handling counting outcomes

    Radiation survival of murine and human melanoma cells utilizing two assay systems: monolayer and soft agar.

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    The radiation response of murine and human melanoma cells assayed in bilayer soft agar and monolayer was examined. Cells from the murine melanoma Cloudman S91 CCL 53.1 cell line and three human melanoma cell strains (C8146C, C8161, and R83-4) developed in our laboratory were irradiated by single dose X-rays and plated either in agar or on plastic. D0 values were the same within 95% confidence intervals for cells from the human melanoma cell strains C8146C, C8161, and R83-4 but were dissimilar for the murine cell line CCL 53.1 Dq values were different for all cells studied. The shape of the survival curve for all four melanomas was not identical for cells assayed in soft agar versus cells grown on plastic. This would indicate that apparent radiosensitivity was influenced by the method of assay although there were no apparent consistent differences between the curves generated by monolayer or bilayer soft agar assays

    De la planification stratégique au management stratégique dans les municipalités

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    Le prĂ©sent document dresse un Ă©tat des savoir-faire en planification stratĂ©gique municipale. Il s’inspire de la littĂ©rature acadĂ©mique et professionnelle sur le sujet et d’observations sur les expĂ©riences de 16 villes quĂ©bĂ©coises et canadiennes (voir annexe A). Pour une municipalitĂ© qui n’a pas encore menĂ© un exercice de planification stratĂ©gique, il donne des indications Ă  la fois sur le contenu et sur les processus de prĂ©paration et de mise en oeuvre d’un plan stratĂ©gique. Pour une municipalitĂ© qui en a dĂ©jĂ  fait, il fournit une grille de rĂ©flexion sur un management stratĂ©gique en continu

    A Prospective Study of Lupus and Rheumatoid Arthritis in Relation to Deployment in Support of Iraq and Afghanistan: The Millennium Cohort Study

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    The objective of this study was to prospectively assess the association between deployment in support of the operations in Iraq and Afghanistan and newly reported lupus and rheumatoid arthritis while also considering the effects of demographic, behavioral, and occupational characteristics. A total of 77,047 (2001–2003) and 31,110 (2004–2006) participants completed the baseline Millennium Cohort questionnaire and were resurveyed approximately every 3 years. Longitudinal analyses were used to assess the adjusted association between deployment to Iraq and Afghanistan with and without combat exposures and newly reported disease. After adjusting, deployment was not significantly associated with newly reported lupus compared with nondeployers. However, compared with nondeployers, deployers with and without combat exposures were significantly less likely to newly report rheumatoid arthritis. Women, non-Hispanic black, and Hispanic participants had a significantly elevated risk for both diseases. Overall, deployment was not associated with an increased risk of newly reported lupus or rheumatoid arthritis

    Analysing count data of Butterflies communities in Jasin, Melaka: a poisson regression analysis

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    Counting outcomes normally have remaining values highly skewed toward the right as they are often characterized by large values of zeros. The data of butterfly communities, had been taken from Jasin, Melaka and consists of 131 number of subject visits in Jasin, Melaka. In this paper, considering the count data of butterfly communities, an analysis is considered Poisson regression analysis as it is assumed to be an alternative way on better suited to the counting process. This research paper is about analysing count data from zero observation ecological inference of butterfly communities in Jasin, Melaka by using Poisson regression analysis. The software for Poisson regression is readily available and it is becoming more widely used in many field of research and the data was analysed by using SAS software. The purpose of analysis comprised the framework of identifying the concerns. Besides, by using Poisson regression analysis, the study determines the fitness of data for accessing the reliability on using the count data. The finding indicates that the highest and lowest number of subject comes from the third family (Nymphalidae) family and fifth (Hesperidae) family and the Poisson distribution seems to fit the zero values

    A cautionary note regarding count models of alcohol consumption in randomized controlled trials

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    BACKGROUND: Alcohol consumption is commonly used as a primary outcome in randomized alcohol treatment studies. The distribution of alcohol consumption is highly skewed, particularly in subjects with alcohol dependence. METHODS: In this paper, we will consider the use of count models for outcomes in a randomized clinical trial setting. These include the Poisson, over-dispersed Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial. We compare the Type-I error rate of these methods in a series of simulation studies of a randomized clinical trial, and apply the methods to the ASAP (Addressing the Spectrum of Alcohol Problems) trial. RESULTS: Standard Poisson models provide a poor fit for alcohol consumption data from our motivating example, and did not preserve Type-I error rates for the randomized group comparison when the true distribution was over-dispersed Poisson. For the ASAP trial, where the distribution of alcohol consumption featured extensive over-dispersion, there was little indication of significant randomization group differences, except when the standard Poisson model was fit. CONCLUSION: As with any analysis, it is important to choose appropriate statistical models. In simulation studies and in the motivating example, the standard Poisson was not robust when fit to over-dispersed count data, and did not maintain the appropriate Type-I error rate. To appropriately model alcohol consumption, more flexible count models should be routinely employed

    Statistical methods for assays with limits of detection: Serum bile acid as a differentiator between patients with normal colons, adenomas, and colorectal cancer

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    In analytic chemistry a detection limit (DL) is the lowest measurable amount of an analyte that can be distinguished from a blank; many biomedical measurement technologies exhibit this property. From a statistical perspective, these data present inferential challenges because instead of precise measures, one only has information that the value is somewhere between 0 and the DL (below detection limit, BDL). Substitution of BDL values, with 0 or the DL can lead to biased parameter estimates and a loss of statistical power. Statistical methods that make adjustments when dealing with these types of data, often called left-censored data, are available in many commercial statistical packages. Despite this availability, the use of these methods is still not widespread in biomedical literature. We have reviewed the statistical approaches of dealing with BDL values, and used simulations to examine the performance of the commonly used substitution methods and the most widely available statistical methods. We have illustrated these methods using a study undertaken at the Vanderbilt-Ingram Cancer Center, to examine the serum bile acid levels in patients with colorectal cancer and adenoma. We have found that the modern methods for BDL values identify disease-related differences that are often missed, with statistically naive approaches

    The impact of attrition on the representativeness of cohort studies of older people

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    Background: There are well-established risk factors, such as lower education, for attrition of study participants. Consequently, the representativeness of the cohort in a longitudinal study may deteriorate over time. Death is a common form of attrition in cohort studies of older people. The aim of this paper is to examine the effects of death and other forms of attrition on risk factor prevalence in the study cohort and the target population over time

    Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

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    BACKGROUND: Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. METHODS: Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. RESULTS: Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. CONCLUSIONS: The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit
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