scholarly journals A comparison of Galactic electron density models using PyGEDM

2021 ◽  
Vol 38 ◽  
Author(s):  
D. C. Price ◽  
C. Flynn ◽  
A. Deller
Keyword(s):  
Electron Density ◽  
Large Scale ◽  
Galactic Halo ◽  
Application Programming Interface ◽  
Dispersion Measure ◽  
Radio Pulsars ◽  
Distribution Models ◽  
Distance Measurements ◽  
Application Programming ◽  
The Impact

Abstract Galactic electron density distribution models are crucial tools for estimating the impact of the ionised interstellar medium on the impulsive signals from radio pulsars and fast radio bursts. The two prevailing Galactic electron density models (GEDMs) are YMW16 (Yao et al. 2017, ApJ, 835, 29) and NE2001 (Cordes & Lazio 2002, arXiv e-prints, pp astro–ph/0207156). Here, we introduce a software package PyGEDM which provides a unified application programming interface for these models and the YT20 (Yamasaki & Totani 2020, ApJ, 888, 105) model of the Galactic halo. We use PyGEDM to compute all-sky maps of Galactic dispersion measure (DM) for YMW16 and NE2001 and compare the large-scale differences between the two. In general, YMW16 predicts higher DM values towards the Galactic anticentre. YMW16 predicts higher DMs at low Galactic latitudes, but NE2001 predicts higher DMs in most other directions. We identify lines of sight for which the models are most discrepant, using pulsars with independent distance measurements. YMW16 performs better on average than NE2001, but both models show significant outliers. We suggest that future campaigns to determine pulsar distances should focus on targets where the models show large discrepancies, so future models can use those measurements to better estimate distances along those line of sight. We also suggest that the Galactic halo should be considered as a component in future GEDMs, to avoid overestimating the Galactic DM contribution for extragalactic sources such as FRBs.

scholarly journals Statistical Measurements of Dispersion Measure Fluctuations of FRBs

2021 ◽  
Vol 922 (2) ◽  
pp. L31
Author(s):  
Siyao Xu ◽  
David H. Weinberg ◽  
Bing Zhang
Keyword(s):  
Electron Density ◽  
Large Scale ◽  
Density Fluctuations ◽  
Clear Correlation ◽  
Dispersion Measure ◽  
Large Dispersion ◽  
Dispersion Measures ◽  
The Difference ◽  
Electron Density Fluctuations ◽  
Scale Turbulence

Abstract Extragalactic fast radio bursts (FRBs) have large dispersion measures (DMs) and are unique probes of intergalactic electron density fluctuations. By using the recently released First CHIME/FRB Catalog, we reexamined the structure function (SF) of DM fluctuations. It shows a large DM fluctuation similar to that previously reported in Xu & Zhang, but no clear correlation hinting toward large-scale turbulence is reproduced with this larger sample. To suppress the distortion effect from FRB distances and their host DMs, we focus on a subset of CHIME catalog with DM < 500 pc cm−3. A trend of nonconstant SF and nonzero correlation function (CF) at angular separations θ less than 10° is seen, but with large statistical uncertainties. The difference found between SF and that derived from CF at θ ≲ 10° can be ascribed to the large statistical uncertainties or the density inhomogeneities on scales on the order of 100 Mpc. The possible correlation of electron density fluctuations and inhomogeneities of density distribution should be tested when several thousands of FRBs are available.

scholarly journals The impact of large scale ionospheric structure on radio occultation retrievals

2011 ◽  
Vol 4 (12) ◽  
pp. 2837-2850 ◽  
Author(s):  
A. J. Mannucci ◽  
C. O. Ao ◽  
X. Pi ◽  
B. A. Iijima
Keyword(s):  
Electron Density ◽  
Large Scale ◽  
Radio Occultation ◽  
Quiet Time ◽  
Ionospheric Electron Density ◽  
Observation Strategy ◽  
Climatological Model ◽  
Ionospheric Data Assimilation ◽  
Using Data ◽  
The Impact

Abstract. We study the impact of large-scale ionospheric structure on the accuracy of radio occultation (RO) retrievals. We use a climatological model of the ionosphere as well as an ionospheric data assimilation model to compare quiet and geomagnetically disturbed conditions. The presence of ionospheric electron density gradients during disturbed conditions increases the physical separation of the two GPS frequencies as the GPS signal traverses the ionosphere and atmosphere. We analyze this effect in detail using ray-tracing and a full geophysical retrieval system. During quiet conditions, our results are similar to previously published studies. The impact of a major ionospheric storm is analyzed using data from the 30 October 2003 "Halloween" superstorm period. At 40 km altitude, the refractivity bias under disturbed conditions is approximately three times larger than quiet time. These results suggest the need for ionospheric monitoring as part of an RO-based climate observation strategy. We find that even during quiet conditions, the magnitude of retrieval bias depends critically on assumed ionospheric electron density structure, which may explain variations in previously published bias estimates that use a variety of assumptions regarding large scale ionospheric structure. We quantify the impact of spacecraft orbit altitude on the magnitude of bending angle and retrieval error. Satellites in higher altitude orbits (700+ km) tend to have lower residual biases due to the tendency of the residual bending to cancel between the top and bottomside ionosphere. Another factor affecting accuracy is the commonly-used assumption that refractive index is unity at the receiver. We conclude with remarks on the implications of this study for long-term climate monitoring using RO.

scholarly journals Comparing protein structures with RINspector automation in Cytoscape

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 563 ◽  
Author(s):  
Guillaume Brysbaert ◽  
Théo Mauri ◽  
Marc F. Lensink
Keyword(s):  
Protein Structures ◽  
Application Programming Interface ◽  
Easy Access ◽  
Network Centrality ◽  
Backbone Flexibility ◽  
Residue Interaction ◽  
Application Programming ◽  
Quaternary Structures ◽  
The Impact ◽  
Programming Interface

Residue interaction networks (RINs) have been shown to be relevant representations of the tertiary or quaternary structures of proteins, in particular thanks to network centrality analyses. We recently developed the RINspector 1.0.0 Cytoscape app, which couples centrality analyses with backbone flexibility predictions. This combined approach permits the identification of crucial residues for the folding or function of the protein that can constitute good targets for mutagenesis experiments. Here we present an application programming interface (API) for RINspector 1.1.0 that enables interplay between Cytoscape, RINspector and external languages, such as R or Python. This API provides easy access to batch centrality calculations and flexibility predictions, and allows for the easy comparison of results between different structures. These comparisons can lead to the identification of specific and conserved central residues, and show the impact of mutations to these and other residues on the flexibility of the proteins. We give two use cases to demonstrate the interest of these functionalities and provide the corresponding scripts: the first concerns NMR conformers, the second focuses on mutations in a structure.

scholarly journals GeNePy3D: a quantitative geometry python toolbox for large scale bioimaging

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1374 ◽  
Author(s):  
Minh-Son Phan ◽  
Anatole Chessel
Keyword(s):  
Large Scale ◽  
Application Programming Interface ◽  
Scale Space ◽  
Experimental Conditions ◽  
Computational Tools ◽  
3D Geometry ◽  
Application Programming ◽  
Reusable Containers ◽  
Microscopy Techniques ◽  
Programming Interface

The advent of large-scale fluorescence and electronic microscopy techniques along with maturing image analysis is giving life sciences a deluge of geometrical objects in 2D/3D(+t) to deal with. These objects take the form of large scale, localised, precise, single cell, quantitative data such as cells’ positions, shapes, trajectories or lineages, axon traces in whole brains atlases or varied intracellular protein localisations, often in multiple experimental conditions. The data mining of those geometrical objects requires a variety of mathematical and computational tools of diverse accessibility and complexity. Here we present a new Python library for quantitative 3D geometry called GeNePy3D which helps handle and mine information and knowledge from geometric data, providing a unified application programming interface (API) to methods from several domains including computational geometry, scale space methods or spatial statistics. By framing this library as generically as possible, and by linking it to as many state-of-the-art reference algorithms and projects as needed, we help render those often specialist methods accessible to a larger community. We exemplify the usefulness of the  GeNePy3D toolbox by re-analysing a recently published whole-brain zebrafish neuronal atlas, with other applications and examples available online. Along with an open source, documented and exemplified code, we release reusable containers to allow for convenient and wide usability and increased reproducibility.

scholarly journals Comparing protein structures with RINspector automation in Cytoscape

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 563 ◽  
Author(s):  
Guillaume Brysbaert ◽  
Théo Mauri ◽  
Marc F. Lensink
Keyword(s):  
Protein Structures ◽  
Application Programming Interface ◽  
Easy Access ◽  
Network Centrality ◽  
Backbone Flexibility ◽  
Residue Interaction ◽  
Application Programming ◽  
Quaternary Structures ◽  
The Impact ◽  
Programming Interface

Residue interaction networks (RINs) have been shown to be relevant representations of the tertiary or quaternary structures of proteins, in particular thanks to network centrality analyses. We recently developed the RINspector Cytoscape app, which couples centrality analyses with backbone flexibility predictions. This combined approach permits the identification of crucial residues for the folding or function of the protein that can constitute good targets for mutagenesis experiments. Here we present an application programming interface (API) for RINspector that enables interplay between Cytoscape, RINspector and external languages, such as R or Python. This API provides easy access to batch centrality calculations and flexibility predictions, and allows for the easy comparison of results between different structures. These comparisons can lead to the identification of specific and conserved central residues, and show the impact of mutations to these and other residues on the flexibility of the proteins. We give two use cases to demonstrate the interest of these functionalities and provide the corresponding scripts: the first concerns NMR conformers, the second focuses on mutations in a structure.

scholarly journals Innovative management of accelerometry, inertial, acoustic, and satellite data using netCDF and Postgres

2018 ◽  
Author(s):  
Alex Nunes ◽  
Damian Lidgard ◽  
Franziska Broell
Keyword(s):  
High Resolution ◽  
Satellite Data ◽  
Large Scale ◽  
Cluster Computing ◽  
Movement Ecology ◽  
Application Programming Interface ◽  
Easy Access ◽  
Application Programming ◽  
Original Size ◽  
User Friendly

In 2015, as part of the Ocean Tracking Network’s bioprobe initiative, 20 grey seals (Halichoerus grypus) were tagged with a high-resolution (> 30 Hz) inertial tags (> 30 Hz), a depth-temperature satellite tag (0.1 Hz), and an acoustic transceiver on Sable Island for 6 months. Comparable to similar large-scale studies in movement ecology, the unprecedented size of the data (gigabytes for a single seal) collected by these instruments raises new challenges in efficient database management. Here we propose the utility of Postgres and netCDF for storing the biotelemetry data and associated metadata. While it was possible to write the lower-resolution (acoustic and satellite) data to a Postgres database, netCDF was chosen as the format for the high-resolution movement (acceleration and inertial) records. Even without access to cluster computing, data could be efficiently (CPU time) recorded, as 920 million records were written in < 3 hours. ERDDAP was used to access and link the different datastreams with a user-friendly Application Programming Interface. This approach compresses the data to a fifth of its original size, and storing the data in a tree-like structure enables easy access and visualization for the end user.

scholarly journals Innovative management of accelerometry, inertial, acoustic, and satellite data using netCDF and Postgres

2018 ◽  
Author(s):  
Alex Nunes ◽  
Damian Lidgard ◽  
Franziska Broell
Keyword(s):  
High Resolution ◽  
Satellite Data ◽  
Large Scale ◽  
Cluster Computing ◽  
Movement Ecology ◽  
Application Programming Interface ◽  
Easy Access ◽  
Application Programming ◽  
Original Size ◽  
User Friendly

In 2015, as part of the Ocean Tracking Network’s bioprobe initiative, 20 grey seals (Halichoerus grypus) were tagged with a high-resolution (> 30 Hz) inertial tags (> 30 Hz), a depth-temperature satellite tag (0.1 Hz), and an acoustic transceiver on Sable Island for 6 months. Comparable to similar large-scale studies in movement ecology, the unprecedented size of the data (gigabytes for a single seal) collected by these instruments raises new challenges in efficient database management. Here we propose the utility of Postgres and netCDF for storing the biotelemetry data and associated metadata. While it was possible to write the lower-resolution (acoustic and satellite) data to a Postgres database, netCDF was chosen as the format for the high-resolution movement (acceleration and inertial) records. Even without access to cluster computing, data could be efficiently (CPU time) recorded, as 920 million records were written in < 3 hours. ERDDAP was used to access and link the different datastreams with a user-friendly Application Programming Interface. This approach compresses the data to a fifth of its original size, and storing the data in a tree-like structure enables easy access and visualization for the end user.

MAGICPL: A Generic Process Description Language for Distributed Pseudonymization Scenarios

2021 ◽  
Author(s):  
Galina Tremper ◽  
Torben Brenner ◽  
Florian Stampe ◽  
Andreas Borg ◽  
Martin Bialke ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
Application Programming Interface ◽  
Research Network ◽  
Description Language ◽  
National Network ◽  
Data Flows ◽  
Small Set ◽  
Application Programming ◽  
Insight Into

Abstract Objectives Pseudonymization is an important aspect of projects dealing with sensitive patient data. Most projects build their own specialized, hard-coded, solutions. However, these overlap in many aspects of their functionality. As any re-implementation binds resources, we would like to propose a solution that facilitates and encourages the reuse of existing components. Methods We analyzed already-established data protection concepts to gain an insight into their common features and the ways in which their components were linked together. We found that we could represent these pseudonymization processes with a simple descriptive language, which we have called MAGICPL, plus a relatively small set of components. We designed MAGICPL as an XML-based language, to make it human-readable and accessible to nonprogrammers. Additionally, a prototype implementation of the components was written in Java. MAGICPL makes it possible to reference the components using their class names, making it easy to extend or exchange the component set. Furthermore, there is a simple HTTP application programming interface (API) that runs the tasks and allows other systems to communicate with the pseudonymization process. Results MAGICPL has been used in at least three projects, including the re-implementation of the pseudonymization process of the German Cancer Consortium, clinical data flows in a large-scale translational research network (National Network Genomic Medicine), and for our own institute's pseudonymization service. Conclusions Putting our solution into productive use at both our own institute and at our partner sites facilitated a reduction in the time and effort required to build pseudonymization pipelines in medical research.

Distant reading 940,000 online circulations of 26 iconic photographs

2021 ◽  
pp. 146144482110494
Author(s):  
Thomas Smits ◽  
Ruben Ros
Keyword(s):  
Digital Media ◽  
Language Processing ◽  
Large Scale ◽  
Application Programming Interface ◽  
Processing Technique ◽  
Distant Reading ◽  
Media Impact ◽  
Large Scale Analysis ◽  
Iconic Images ◽  
Application Programming

How do digital media impact the meaning of iconic photographs? Recent studies have suggested that online circulation, especially in a memeified form, might lead to the erosion, fracturing, or collapsing of the original contextual meaning of iconic pictures. Introducing a distant reading methodology to the study of iconic photographs, we apply the Google Cloud Vision Application Programming Interface (GCV API) to retrieve 940,000 online circulations of 26 iconic images between 1995 and 2020. We use document embeddings, a Natural Language Processing technique, to map in what contexts iconic photographs are circulated online. The article demonstrates that constantly changing configurations of contextual imagetexts, self-referential image-texts, and non-referential image/texts shape the online live of iconic photographs: ebbs and flows of slowly disappearing, suddenly resurfacing, and newly found meanings. While iconic photographs might not need captions to speak, this article argues that a large-scale analysis of texts can help us better grasp what they say.

scholarly journals Chinese Text Project: a dynamic digital library of premodern Chinese

2019 ◽  
Author(s):  
Donald Sturgeon
Keyword(s):  
Digital Library ◽  
Chinese Text ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Large Scale ◽  
Application Programming Interface ◽  
Transcription System ◽  
Application Programming ◽  
Chinese Writing ◽  
Programming Interface

Abstract This article presents technical approaches and innovations in digital library design developed during the design and implementation of the Chinese Text Project, a widely-used, large-scale full-text digital library of premodern Chinese writing. By leveraging a combination of domain-optimized Optical Character Recognition, a purpose-designed crowdsourcing system, and an Application Programming Interface (API), this project simultaneously provides a sustainable transcription system, search interface and reading environment, as well as an extensible platform for transcribing and working with premodern Chinese textual materials. By means of the API, intentionally loosely integrated text mining tools are used to extend the platform, while also being reusable independently with materials from other sources and in other languages.

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