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  • 1
    Electronic Resource
    Electronic Resource
    Analysis of residence time distribution in the extrusion process including the effect of 3-D circulatory flow (1993)
    Stamford, Conn. [u.a.] : Wiley-Blackwell
    Polymer Engineering and Science 33 (1993), S. 959-970 
    Details
    ISSN: 0032-3888
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Physics
    Notes: It is of great importance to accurately measure or predict the Residence Time Distribution (RTD) in designing extruders and/or in setting up a proper operating condition, because chemical reactions depend significantly on the RTD and temperature when chemical reactions take place during the extrusion process. A previous method to predict the RTD can analytically determine RTD, Residence Time Distribution Function f(t) and Cumulative Residence Time Distribution Function F(t), based on a simplified two-dimensional velocity field in an extruder. However, this previous method cannot accurately take into account the three-dimensional circulatory flow inside the extruder. The present paper suggests a new method to accurately determine the RTD taking into account the three-dimensional circulatory flow and presents a new formula derived to calculate f(t). In order to demonstrate the applicability of the new method including the circulatory flow effect, RTD, f(t) and F(t) were calculated based on a three-dimensional velocity field obtained via a quasi-three-dimensional finite element analysis. It was found that the previous method has a tendency to underestimate the RTD, owing to the neglect of the three-dimensional circulatory flow in comparison with the new method.
    Additional Material: 13 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/pen.760331505
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Kinematics and deformation characteristics as a mixing measure in the screw extrusion process (1994)
    Stamford, Conn. [u.a.] : Wiley-Blackwell
    Polymer Engineering and Science 34 (1994), S. 174-189 
    Details
    ISSN: 0032-3888
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Physics
    Notes: The present paper proposes “Deformation Characteristics” (DC) as a new deformation measure of screw extrusion processes, based on the Green deformation tensor. In contrast to previous strain measures heuristically proposed by Mohr, et al., Mckelvey, and Pinto and Tadmor, the new DC can naturally incorporate the demixing phenomena and systematically take into account the three-dimensional circulatory flow with the screw flight effect. Therefore, DC can be regarded as an improved strain measure. “Weighted Average Deformation characteristics” (WADC) is also proposed to indicate the overall deformation characteristics as a quantitative measure to the “goodness of mixing” of the extrusion process. The present paper includes discussion on delicate differences between DC and several other strain measures in case of the two-dimensional velocity approximation, and on the application of DC into a general three-dimensional velocity field obtained by a quasi-three-dimensional finite element analysis of extrusion processes. In determining WADC in the three-dimensional application, the residence time distribution function, including the three-dimensional circulatory flow effect, is used.
    Additional Material: 15 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/pen.760340303
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    Paper (German National Licenses)
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  • 3
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    Privacy preserving protocol for detecting genetic relatives using rare variants (2014)
    Oxford University Press
    Details
    Publication Date: 2014-06-17
    Description: Motivation: High-throughput sequencing technologies have impacted many areas of genetic research. One such area is the identification of relatives from genetic data. The standard approach for the identification of genetic relatives collects the genomic data of all individuals and stores it in a database. Then, each pair of individuals is compared to detect the set of genetic relatives, and the matched individuals are informed. The main drawback of this approach is the requirement of sharing your genetic data with a trusted third party to perform the relatedness test. Results: In this work, we propose a secure protocol to detect the genetic relatives from sequencing data while not exposing any information about their genomes. We assume that individuals have access to their genome sequences but do not want to share their genomes with anyone else. Unlike previous approaches, our approach uses both common and rare variants which provide the ability to detect much more distant relationships securely. We use a simulated data generated from the 1000 genomes data and illustrate that we can easily detect up to fifth degree cousins which was not possible using the existing methods. We also show in the 1000 genomes data with cryptic relationships that our method can detect these individuals. Availability: The software is freely available for download at http://genetics.cs.ucla.edu/crypto/ . Contact: fhormoz@cs.ucla.edu or eeskin@cs.ucla.edu Supplementary information: Supplementary data are available at Bioinformatics online
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 4
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    Identifying genetic relatives without compromising privacy [METHOD] (2014)
    Cold Spring Harbor Laboratory Press
    Details
    Publication Date: 2014-04-02
    Description: The development of high-throughput genomic technologies has impacted many areas of genetic research. While many applications of these technologies focus on the discovery of genes involved in disease from population samples, applications of genomic technologies to an individual’s genome or personal genomics have recently gained much interest. One such application is the identification of relatives from genetic data. In this application, genetic information from a set of individuals is collected in a database, and each pair of individuals is compared in order to identify genetic relatives. An inherent issue that arises in the identification of relatives is privacy. In this article, we propose a method for identifying genetic relatives without compromising privacy by taking advantage of novel cryptographic techniques customized for secure and private comparison of genetic information. We demonstrate the utility of these techniques by allowing a pair of individuals to discover whether or not they are related without compromising their genetic information or revealing it to a third party. The idea is that individuals only share enough special-purpose cryptographically protected information with each other to identify whether or not they are relatives, but not enough to expose any information about their genomes. We show in HapMap and 1000 Genomes data that our method can recover first- and second-order genetic relationships and, through simulations, show that our method can identify relationships as distant as third cousins while preserving privacy.
    Electronic ISSN: 1549-5469
    Topics: Biology , Medicine
    Published by Cold Spring Harbor Laboratory Press
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  • 5
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    Genetic and environmental control of host-gut microbiota interactions [RESEARCH] (2015)
    Cold Spring Harbor Laboratory Press
    Details
    Publication Date: 2015-10-02
    Description: Genetics provides a potentially powerful approach to dissect host-gut microbiota interactions. Toward this end, we profiled gut microbiota using 16s rRNA gene sequencing in a panel of 110 diverse inbred strains of mice. This panel has previously been studied for a wide range of metabolic traits and can be used for high-resolution association mapping. Using a SNP-based approach with a linear mixed model, we estimated the heritability of microbiota composition. We conclude that, in a controlled environment, the genetic background accounts for a substantial fraction of abundance of most common microbiota. The mice were previously studied for response to a high-fat, high-sucrose diet, and we hypothesized that the dietary response was determined in part by gut microbiota composition. We tested this using a cross-fostering strategy in which a strain showing a modest response, SWR, was seeded with microbiota from a strain showing a strong response, A x B19. Consistent with a role of microbiota in dietary response, the cross-fostered SWR pups exhibited a significantly increased response in weight gain. To examine specific microbiota contributing to the response, we identified various genera whose abundance correlated with dietary response. Among these, we chose Akkermansia muciniphila , a common anaerobe previously associated with metabolic effects. When administered to strain A x B19 by gavage, the dietary response was significantly blunted for obesity, plasma lipids, and insulin resistance. In an effort to further understand host-microbiota interactions, we mapped loci controlling microbiota composition and prioritized candidate genes. Our publicly available data provide a resource for future studies.
    Electronic ISSN: 1549-5469
    Topics: Biology , Medicine
    Published by Cold Spring Harbor Laboratory Press
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  • 6
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    Efficient and Accurate Multiple-Phenotype Regression Method for High Dimensional Data Considering Population Structure [Methods, Technology, and Resources] (2016)
    Genetics Society of America (GSA)
    In: Genetics
    Details
    Publication Date: 2016-12-08
    Description: A typical genome-wide association study tests correlation between a single phenotype and each genotype one at a time. However, single-phenotype analysis might miss unmeasured aspects of complex biological networks. Analyzing many phenotypes simultaneously may increase the power to capture these unmeasured aspects and detect more variants. Several multivariate approaches aim to detect variants related to more than one phenotype, but these current approaches do not consider the effects of population structure. As a result, these approaches may result in a significant amount of false positive identifications. Here, we introduce a new methodology, referred to as GAMMA for generalized analysis of molecular variance for mixed-model analysis, which is capable of simultaneously analyzing many phenotypes and correcting for population structure. In a simulated study using data implanted with true genetic effects, GAMMA accurately identifies these true effects without producing false positives induced by population structure. In simulations with this data, GAMMA is an improvement over other methods which either fail to detect true effects or produce many false positive identifications. We further apply our method to genetic studies of yeast and gut microbiome from mice and show that GAMMA identifies several variants that are likely to have true biological mechanisms.
    Keywords: Methods, Technology, & Resources
    Print ISSN: 0016-6731
    Topics: Biology
    Published by Genetics Society of America (GSA)
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