scholarly journals met: Expanding on old estimations of biodiversityfrom eDNA with a new software framework

2021 ◽  
Author(s):  
David Molik ◽  
Caroline DeVoto ◽  
Daniel Molik

(1) Motivation: A long standing problem in Environmental DNA has been the inability to compute across large number of datasets. Here we introduce an Open Source software frame work that can store a large number of Environmental DNA datasets, as well as provide a platform for analysis, in an easily customizable way. We show the utility of such an approach by analyzing over 1400 arthropod datasets. (2) Results: This article introduces a new software framework, met, which utilizes large numbers ofmetabarcode datasets to draw conclusions about patterns of diversity at large spatial scales. Given more accurate estimations on the distribution of variance in metabarcode datasets, this software framework could facilitate novel analyses that are outside the scope of currently available similar platforms. (3) Availability: All code are published under the Mozilla Public License ver 2.0 on the met project page: https://doi.org/10.17605/OSF.IO/SPB8V

Author(s):  
Damien Rompapas ◽  
Charlton Rodda ◽  
Bryan Christopher Brown ◽  
Noah Benjamin Zerkin ◽  
Alvaro Cassinelli

Author(s):  
Henri E. Z. Tonnang ◽  
Ritter A. Guimapi ◽  
Bruce Anani ◽  
Dan Makumbi ◽  
Bester Mudereri ◽  
...  

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework is implemented in R, providing a flexible and easy‐to‐use GUI interface. Since this allows appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.


Author(s):  
Ruben van Wendel de Joode ◽  
Sebastian Spaeth

Most open source software is developed in online communities. These communities are typically referred to as “open source software communities” or “OSS communities.” In OSS communities, the source code, which is the human-readable part of software, is treated as something that is open and that should be downloadable and modifiable to anyone who wishes to do so. The availability of the source code has enabled a practice of decentralized software development in which large numbers of people contribute time and effort. Communities like Linux and Apache, for instance, have been able to connect thousands of individual programmers and professional organizations (although most project communities remain relatively small). These people and organizations are not confined to certain geographical places; on the contrary, they come from literally all continents and they interact and collaborate virtually.


2021 ◽  
Author(s):  
Helen J Curtis ◽  
Brian MacKenna ◽  
Alex J Walker ◽  
Peter Inglesby ◽  
Richard Croker ◽  
...  

Background The COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data. Objective To describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples. Methods Working on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020. Results Much activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as no change from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline. Conclusions We successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.


Agriculture ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 515
Author(s):  
Henri E. Z. Tonnang ◽  
Ritter A. Guimapi ◽  
Anani Y. Bruce ◽  
Dan Makumbi ◽  
Bester T. Mudereri ◽  
...  

Understanding the detailed timing of crop phenology and their variability enhances grain yield and quality by providing precise scheduling of irrigation, fertilization, and crop protection mechanisms. Advances in information and communication technology (ICT) provide a unique opportunity to develop agriculture-related tools that enhance wall-to-wall upscaling of data outputs from point-location data to wide-area spatial scales. Because of the heterogeneity of the worldwide agro-ecological zones where crops are cultivated, it is unproductive to perform plant phenology research without providing means to upscale results to landscape-level while safeguarding field-scale relevance. This paper presents an advanced, reproducible, and open-source software for plant phenology prediction and mapping (PPMaP) that inputs data obtained from multi-location field experiments to derive models for any crop variety. This information can then be applied consecutively at a localized grid within a spatial framework to produce plant phenology predictions at the landscape level. This software runs on the ‘Windows’ platform and supports the development of process-oriented and temperature-driven plant phenology models by intuitively and interactively leading the user through a step-by-step progression to the production of spatial maps for any region of interest in sub-Saharan Africa. Maize (Zea mays L.) was used to demonstrate the robustness, versatility, and high computing efficiency of the resulting modeling outputs of the PPMaP. The framework was implemented in R, providing a flexible and easy-to-use GUI interface. Since this allows for appropriate scaling to the larger spatial domain, the software can effectively be used to determine the spatially explicit length of growing period (LGP) of any variety.


2013 ◽  
Vol 11 (S1) ◽  
pp. S134-S145 ◽  
Author(s):  
Alexander Falenski ◽  
Matthias Filter ◽  
Christian Thöns ◽  
Armin A. Weiser ◽  
Jan-Frederik Wigger ◽  
...  

2015 ◽  
Vol 19 (6) ◽  
pp. 937-949 ◽  
Author(s):  
Stefan Pauliuk ◽  
Guillaume Majeau‐Bettez ◽  
Christopher L. Mutel ◽  
Bernhard Steubing ◽  
Konstantin Stadler

Author(s):  
D. Seider ◽  
P. M. Fischer ◽  
M. Litz ◽  
A. Schreiber ◽  
A. Gerndt

2020 ◽  
Vol 245 ◽  
pp. 02032
Author(s):  
Carl Vuosalo ◽  
Sunanda Banerjee ◽  
Markus Frank ◽  
Vladimir Ivanchenko ◽  
Sergio Lo Meo ◽  
...  

DD4hep is an open-source software toolkit that provides comprehensive and complete generic detector descriptions for high energy physics (HEP) detectors. The Compact Muon Solenoid collaboration (CMS) has recently evaluated and adopted DD4hep to replace its custom detector description software. CMS has demanding software requirements as a very large, longrunning experiment that must support legacy geometries and study many possible upgraded detector designs of a constantly evolving detector that will be taking data for many years to come. CMS has chosen DD4hep since it is a high-quality, community-supported solution that will benefit from continuing modernization and maintenance. This presentation will discuss the issues of DD4hep adoption, the advantages and disadvantages of the various design choices, performance results, and the integration of the plugin systems from CMS and Gaudi, another open-source software framework. Recommendations about DD4hep based upon the CMS use cases will also be presented.


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