45 research outputs found

    Final Report - ILAW PCT, VHT, Viscosity, and Electrical Conductivity Model Development, VSL-07R1230-1

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    This report describes the results of work and testing specified by the Test Specifications (24590-LAW-TSP-RT-01-013 Rev.1 and 24590-WTP-TSP-RT-02-001 Rev.0), Test Plans (VSL-02T4800-1 Rev.1 & TP-RPP-WTP-179 Rev.1), and Text Exception (24590-WTP-TEF-RT-03-040). The work and any associated testing followed established quality assurance requirements and conducted as authorized. The descriptions provided in this test report are an accurate account of both the conduct of the work and the data collected. Results required by the Test Plans are reported. Also reported are any unusual or anomalous occurrences that are different from the starting hypotheses. The test results and this report have been reviewed and verified

    Bayesian D-Optimal Choice Designs for Mixtures

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    __Abstract__ \n \nConsumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents\' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. \n \nHowever, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs

    COVID-19 in cancer patients: clinical characteristics and outcome—an analysis of the LEOSS registry

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    Introduction Since the early SARS-CoV-2 pandemic, cancer patients have been assumed to be at higher risk for severe COVID-19. Here, we present an analysis of cancer patients from the LEOSS (Lean European Open Survey on SARS-CoV-2 Infected Patients) registry to determine whether cancer patients are at higher risk. Patients and methods We retrospectively analyzed a cohort of 435 cancer patients and 2636 non-cancer patients with confirmed SARS-CoV-2 infection, enrolled between March 16 and August 31, 2020. Data on socio-demographics, comorbidities, cancer-related features and infection course were collected. Age-, sex- and comorbidity-adjusted analysis was performed. Primary endpoint was COVID-19-related mortality. Results In total, 435 cancer patients were included in our analysis. Commonest age category was 76–85 years (36.5%), and 40.5% were female. Solid tumors were seen in 59% and lymphoma and leukemia in 17.5% and 11% of patients. Of these, 54% had an active malignancy, and 22% had recently received anti-cancer treatments. At detection of SARS-CoV-2, the majority (62.5%) presented with mild symptoms. Progression to severe COVID-19 was seen in 55% and ICU admission in 27.5%. COVID-19-related mortality rate was 22.5%. Male sex, advanced age, and active malignancy were associated with higher death rates. Comparing cancer and non-cancer patients, age distribution and comorbidity differed significantly, as did mortality (14% vs 22.5%, p value < 0.001). After adjustments for other risk factors, mortality was comparable. Conclusion Comparing cancer and non-cancer patients, outcome of COVID-19 was comparable after adjusting for age, sex, and comorbidity. However, our results emphasize that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions

    Interim results from UO/sub 2/ fuel oxidation tests in air

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    An experimental program is being conducted at Pacific Northwest Laboratory (PNL) to extend the characterization of spent fuel oxidation in air. To characterize oxidation behavior of irradiated UO/sub 2/, fuel oxidation tests were performed on declad light-water reactor spent fuel and nonirradited UO/sub 2/ pellets in the temperature range of 135 to 250/sup 0/C. These tests were designed to determine the important independent variables that might affect spent fuel oxidation behavior. The data from this program, when combined with the test results from other programs, will be used to develop recommended spent fuel dry-storage temperature limits in air. This report describes interim test results. The initial PNL investigations of nonirradiated and spent fuels identified the important testing variables as temperature, fuel burnup, radiolysis of the air, fuel microstructure, and moisture in the air. Based on these initial results, a more extensive statistically designed test matrix was developed to study the effects of temperature, burnup, and moisture on the oxidation behavior of spent fuel. Oxidation tests were initiated using both boiling-water reactor and pressurized-water reactor fuels from several different reactors with burnups from 8 to 34 GWd/MTU. A 10/sup 5/ R/h gamma field was applied to the test ovens to simulate dry storage cask conditions. Nonirradiated fuel was included as a control. This report describes experimental results from the initial tests on both the spent and nonirradiated fuels and results to date on the tests in a 10/sup 5/ R/h gamma field. 33 refs., 51 figs., 6 tabs
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