Advanced Applications of Template Offshore Platform Capacity Analysis Tools: A Fast Ultimate Strength Analysis Tool

2000 ◽  
Author(s):  
Allen M. Brooks ◽  
Kris A. Digre
Keyword(s):  
Ultimate Strength ◽  
Offshore Platform ◽  
Strength Analysis ◽  
Capacity Analysis ◽  
Analysis Tool ◽  
Analysis Tools ◽  
Advanced Applications

A New Analysis Tool for Continuous Glucose Monitor Data

2021 ◽  
pp. 193229682110289
Author(s):  
Evan Olawsky ◽  
Yuan Zhang ◽  
Lynn E Eberly ◽  
Erika S Helgeson ◽  
Lisa S Chow
Keyword(s):  
Glucose Monitoring ◽  
Glycemic Variability ◽  
R Package ◽  
Analysis Tool ◽  
Continuous Glucose Monitor ◽  
Analysis Tools ◽  
R Shiny ◽  
Primary Driver ◽  
Rich Information ◽  
Web App

Background: With the development of continuous glucose monitoring systems (CGMS), detailed glycemic data are now available for analysis. Yet analysis of this data-rich information can be formidable. The power of CGMS-derived data lies in its characterization of glycemic variability. In contrast, many standard glycemic measures like hemoglobin A1c (HbA1c) and self-monitored blood glucose inadequately describe glycemic variability and run the risk of bias toward overreporting hyperglycemia. Methods that adjust for this bias are often overlooked in clinical research due to difficulty of computation and lack of accessible analysis tools. Methods: In response, we have developed a new R package rGV, which calculates a suite of 16 glycemic variability metrics when provided a single individual’s CGM data. rGV is versatile and robust; it is capable of handling data of many formats from many sensor types. We also created a companion R Shiny web app that provides these glycemic variability analysis tools without prior knowledge of R coding. We analyzed the statistical reliability of all the glycemic variability metrics included in rGV and illustrate the clinical utility of rGV by analyzing CGM data from three studies. Results: In subjects without diabetes, greater glycemic variability was associated with higher HbA1c values. In patients with type 2 diabetes mellitus (T2DM), we found that high glucose is the primary driver of glycemic variability. In patients with type 1 diabetes (T1DM), we found that naltrexone use may potentially reduce glycemic variability. Conclusions: We present a new R package and accompanying web app to facilitate quick and easy computation of a suite of glycemic variability metrics.

Buckling/Ultimate Strength Evaluation for Continuous Stiffened Panel Under Combined Shear and Thrust

2016 ◽  
Author(s):  
Hiroaki Ogawa ◽  
Tomoki Takami ◽  
Akira Tatsumi ◽  
Yoshiteru Tanaka ◽  
Shinichi Hirakawa ◽  
...  
Keyword(s):  
Ultimate Strength ◽  
Fem Analysis ◽  
Strength Analysis ◽  
Stiffened Panel ◽  
Fe Modeling ◽  
Test Results ◽  
Strength Evaluation ◽  
Shear Buckling ◽  
Collapse Behavior ◽  
Good Agreement

In this study, FE modeling method for the buckling/ultimate strength analysis of a continuous stiffened panel under combined shear and thrust is proposed. In order to validate the proposed method, shear buckling collapse tests of a stiffened panel and FEM analysis are carried out. As the result of these, it is confirmed that the buckling collapse behavior and the ultimate strength estimated by the proposed method are in good agreement with the test results.

scholarly journals Towards the Development of Language Analysis Tools for the Written Latgalian Language

2020 ◽  
Author(s):  
Daiga Deksne ◽  
Anna Vulāne
Keyword(s):  
Web Service ◽  
Morphological Analysis ◽  
Written Language ◽  
Analysis Tool ◽  
Tool Development ◽  
Joint Effort ◽  
Analysis Tools ◽  
Language Analysis ◽  
Wide Range ◽  
Development Of Language

This paper reports on the development of spell checking and morphological analysis tools for Latgalian. The Latgalian written language is a historic variant of the Latvian language. There is a wide range of language analysis tools available for Latvian, whereas the Latgalian language lacks such tools. The work is done by the joint effort of linguists who work on morphologically marked lexicon creation and IT specialists who work on language tool development. For the creation of a morphological analysis tool, we reuse the FST technology used for the Latvian morphological analyzer. We create a spelling dictionary that can be used with the Hunspell engine. All tools are accessible via Web Service. For now, the Latgalian lexicon contains 13,139 lemmas marked by 105 inflection groups. The work of lexicon replenishment still continues.

scholarly journals StrainPro – a highly accurate Metagenomic strain-level profiling tool

2019 ◽  
Author(s):  
Hsin-Nan Lin ◽  
Yaw-Ling Lin ◽  
Wen-Lian Hsu
Keyword(s):  
Microbial Community ◽  
Relative Abundance ◽  
Taxonomic Diversity ◽  
Evaluation Study ◽  
Taxonomic Composition ◽  
Strain Level ◽  
Metagenomic Analysis ◽  
Reference Database ◽  
Analysis Tool ◽  
Analysis Tools

ABSTRACTCharacterizing the taxonomic diversity of a microbial community is very important to understand the roles of microorganisms. Next generation sequencing (NGS) provides great potential for investigation of a microbial community and leads to Metagenomic studies. NGS generates DNA fragment sequences directly from microorganism samples, and it requires analysis tools to identify microbial species (or taxonomic composition) and estimate their relative abundance in the studied community. However, only a few tools could achieve strain-level identification and most tools estimate the microbial abundances simply according to the read counts. An evaluation study on metagenomic analysis tools concludes that the predicted abundance differed significantly from the true abundance. In this study, we present StrainPro, a novel metagenomic analysis tool which is highly accurate both at characterizing microorganisms at strain-level and estimating their relative abundances. A unique feature of StrainPro is it identifies representative sequence segments from reference genomes. We generate three simulated datasets using known strain sequences and another three simulated datasets using unknown strain sequences. We compare the performance of StrainPro with seven existing tools. The results show that StrainPro not only identifies metagenomes with high precision and recall, but it is also highly robust even when the metagenomes are not included in the reference database. Moreover, StrainPro estimates the relative abundance with high accuracy. We demonstrate that there is a strong positive linear relationship between observed and predicted abundances.

scholarly journals IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

mBio ◽  
2015 ◽  
Vol 6 (4) ◽  
Author(s):  
Michalis Hadjithomas ◽  
I-Min Amy Chen ◽  
Ken Chu ◽  
Anna Ratner ◽  
Krishna Palaniappan ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Secondary Metabolism ◽  
Genomic Data ◽  
Gene Clusters ◽  
Metagenomic Data ◽  
Integrated Analysis ◽  
Analysis Tool ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Analysis Tools

ABSTRACTIn the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time inAlphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules.IMPORTANCEIMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

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