scholarly journals Adding Taxonomic Dimensions to the Scientific Names Index in the Biodiversity Heritage Library via Integration with the Catalogue of Life

2020 ◽  
Vol 4 ◽  
Author(s):  
Dmitry Mozzherin ◽  
Geoffrey Ower
Keyword(s):  
Open Source ◽  
Relevant Information ◽  
Open Source Program ◽  
Taxonomic Information ◽  
Source Program ◽  
Names Project ◽  
Over Time ◽  
First Descriptions ◽  
Index Search

The most significant specialized and open resource for biodiversity literature is the Biodiversity Heritage Library (BHL). BHL contains more than 200,000 volumes that cover hundreds of years of biological publications. The Catalogue of Life (CoL) is the largest aggregator of global taxonomic information. The Global Names project collaborates with BHL and CoL to create a BHL scientific names index that is continuously improved. The index allows researchers to conveniently find relevant information about any name. Building a scientific names index is challenging because scientific names are quite dynamic and can dramatically change in taxonomic meaning over time. According to our estimates, on average, there are three scientific names per species. Also, a significant number of scientific names have fallen into disuse. For example, approximately 25% of names used in Zoology between 1750–1850 and collected by Charles Sherborn into Index Animalium disappeared from current nomenclatural and taxonomic databases. It is important, therefore, to add "taxonomic intelligence" to BHL names index search and present not only data about a specific name-string but also about all known synonyms so that all relevant information in BHL can be consolidated and conveniently accessed from taxonomic information aggregators like CoL. We developed an open source program "bhlnames", which creates a two-way bridge between the Catalogue of Life and Biodiversity Heritage Library. It provides the location of information in BHL about a taxon, using all names associated with the taxon according to Catalogue of Life synonymy data. Using that information, it attempts to provide CoL with a BHL link to the first descriptions of scientific names in the literature.

scholarly journals AutoMeKin2021 : An open‐source program for automated reaction discovery

2021 ◽  
Author(s):  
Emilio Martínez‐Núñez ◽  
George L. Barnes ◽  
David R. Glowacki ◽  
Sabine Kopec ◽  
Daniel Peláez ◽  
...  
Keyword(s):  
Open Source ◽  
Reaction Discovery ◽  
Open Source Program ◽  
Source Program

The Rise of Open Source Program Office

2021 ◽  
Vol 23 (1) ◽  
pp. 27-33
Author(s):  
Hussan Munir ◽  
Carl-Erik Mols
Keyword(s):  
Open Source ◽  
Open Source Program ◽  
Source Program

Control of Void Formation in Adhesively Bonded Joints in the Presence of Filler

2020 ◽  
Vol 2020 (1) ◽  
pp. 000246-000258
Author(s):  
Nina S. Dytiuk ◽  
Thomas F. Marinis ◽  
Joseph W. Soucy
Keyword(s):  
Finite Element ◽  
Open Source ◽  
Void Formation ◽  
Adhesive Joints ◽  
Bonded Joints ◽  
Volatile Species ◽  
Adhesively Bonded ◽  
Adhesively Bonded Joints ◽  
Open Source Program ◽  
Source Program

Abstract Adhesively bonded joints are ubiquitous in electronic assemblies that are used in a wide range of applications, which include automotive, medical, military, space and communications. The steady drive to reduce the size of assemblies in all of these applications, while providing increased functionality, generates a need for adhesive joints of higher strength, improved thermal and electrical conductivity and better dielectric isolation. All of these attributes of adhesive joints are degraded by the presence of voids in them. The quest to minimize voids in bonded structures motivated a previous study of their formation in a solvent cast, die bond epoxy film, which undergoes a liquid phase transition during cure. That work is extended in this study by including the effects of various filler morphologies in the adhesive. Fillers are added to adhesives to facilitate handling of thin sheet formats, control bond line thickness and reduce coefficient of thermal expansion. As such, fillers are selected to be inert with respect to the adhesive chemistry, while being readily wetted by it in the liquid state. Common filler morphologies include woven and molded open meshes, fibers chopped to uniform length, and spheres of uniform or distributed diameters. Void formation is influenced by a number factors, which include wettability of the bonded surfaces, adsorbed water, amount of solvent retained in the film, volume of entrapped air, thermal profile of the cure schedule, and clamping pressure during cure. The presence of fillers in the adhesive adds the additional factors of constrained diffusion paths and increased area for void nucleation. We have changed our approach to modeling the diffusion of volatile species in adhesive joints from a finite difference calculation in a uniform adhesive medium used previously, to a finite element model of a complex diffusion space. The open source program Gmsh is used to generate the diffusion space from a set of input parameters. The calculations of concentration profiles and diffusion fluxes of volatile species at the void interface are made using the open source finite element program elmer. As done previously, the position of the void interface is updated by integrating the product of time and flux of diffusing species over the area of the interface. The internal pressure of the void is determined by application of the Young-Laplace equation, while Henry’s law is used to estimate the concentration of diffusing species adjacent to the void interface. The calculation proceeds for a time equivalent to the integral of the time temperature product required to achieve a 70% cure state of the adhesive, at which point the void interface is immobile. The experimental approach is the same as used previously, with the filled adhesive sandwiched between glass slides and cured on a hot plate while imaged through a microscope. Images are automatically captured and analyzed by using the open source program imageJ, which allows us to track the evolution of individual voids as well as the time dependent distribution of the void population. We are working to correlate these experimental results with the predictions of our finite element calculations to allow us to make insightful choices of adhesives and optimize our bonding processes.

Identifying ZooMS Spectra (mammals) using mMass v1

2021 ◽  
Author(s):  
Samantha Brown
Keyword(s):  
Open Source ◽  
Information Contact ◽  
Learning Tool ◽  
Open Source Program ◽  
Source Program ◽  
The University

This is a guide to identifying ZooMS spectra for mammals using the open-source program mMass (Niedermeyer and Strohalm 2012). This guide is intended as a learning tool for students and researchers at the University of Tubingen and is not meant to replace formal ZooMS marker training. If you use this guide to analyse your ZooMS spectra or to convert your data into an open-source format, please cite this document. For further information contact Dr. Samantha Brown (samantha.brown (at) uni-tuebingen.de)

scholarly journals Gypsum-DL: an open-source program for preparing small-molecule libraries for structure-based virtual screening

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Patrick J. Ropp ◽  
Jacob O. Spiegel ◽  
Jennifer L. Walker ◽  
Harrison Green ◽  
Guillermo A. Morales ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Open Source ◽  
Small Molecule ◽  
Open Source Program ◽  
Source Program ◽  
Small Molecule Libraries

scholarly journals DrawGlycan-SNFG and gpAnnotate: rendering glycans and annotating glycopeptide mass spectra

2019 ◽  
Author(s):  
Kai Cheng ◽  
Gabrielle Pawlowski ◽  
Xinheng Yu ◽  
Yusen Zhou ◽  
Sriram Neelamegham
Keyword(s):  
Mass Spectrometry ◽  
Open Source ◽  
Mass Spectra ◽  
Supplementary Information ◽  
Supplementary Data ◽  
International Union ◽  
Open Source Program ◽  
Source Program ◽  
Wide Range ◽  
Peptide Modifications

Abstract Summary This manuscript describes an open-source program, DrawGlycan-SNFG (version 2), that accepts IUPAC (International Union of Pure and Applied Chemist)-condensed inputs to render Symbol Nomenclature For Glycans (SNFG) drawings. A wide range of local and global options enable display of various glycan/peptide modifications including bond breakages, adducts, repeat structures, ambiguous identifications etc. These facilities make DrawGlycan-SNFG ideal for integration into various glycoinformatics software, including glycomics and glycoproteomics mass spectrometry (MS) applications. As a demonstration of such usage, we incorporated DrawGlycan-SNFG into gpAnnotate, a standalone application to score and annotate individual MS/MS glycopeptide spectrum in different fragmentation modes. Availability and implementation DrawGlycan-SNFG and gpAnnotate are platform independent. While originally coded using MATLAB, compiled packages are also provided to enable DrawGlycan-SNFG implementation in Python and Java. All programs are available from https://virtualglycome.org/drawglycan; https://virtualglycome.org/gpAnnotate. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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