scholarly journals Accessible data curation and analytics for international-scale citizen science datasets

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Benjamin Murray ◽  
Eric Kerfoot ◽  
Liyuan Chen ◽  
Jie Deng ◽  
Mark S. Graham ◽  
...  
Keyword(s):  
Citizen Science ◽  
Open Source Software ◽  
Data Analytics ◽  
Data Curation ◽  
Reproducible Research ◽  
Self Assessment ◽  
Commodity Hardware ◽  
Alternative Technologies ◽  
International Research Group ◽  
Open Source Software Package

AbstractThe Covid Symptom Study, a smartphone-based surveillance study on COVID-19 symptoms in the population, is an exemplar of big data citizen science. As of May 23rd, 2021, over 5 million participants have collectively logged over 360 million self-assessment reports since its introduction in March 2020. The success of the Covid Symptom Study creates significant technical challenges around effective data curation. The primary issue is scale. The size of the dataset means that it can no longer be readily processed using standard Python-based data analytics software such as Pandas on commodity hardware. Alternative technologies exist but carry a higher technical complexity and are less accessible to many researchers. We present ExeTera, a Python-based open source software package designed to provide Pandas-like data analytics on datasets that approach terabyte scales. We present its design and capabilities, and show how it is a critical component of a data curation pipeline that enables reproducible research across an international research group for the Covid Symptom Study.

OnPoint: A package for online experiments in motor control and motor learning

2020 ◽  
Author(s):  
Jonathan Sanching Tsay ◽  
Alan S. Lee ◽  
Guy Avraham ◽  
Darius E. Parvin ◽  
Jeremy Ho ◽  
...  
Keyword(s):  
Motor Control ◽  
Motor Learning ◽  
Open Source Software ◽  
Research Progress ◽  
Global Pandemic ◽  
Large N ◽  
Open Source Software Package ◽  
Potential Applications ◽  
Temporal And Spatial ◽  
The One

Motor learning experiments are typically run in-person, exploiting finely calibrated setups (digitizing tablets, robotic manipulandum, full VR displays) that provide high temporal and spatial resolution. However, these experiments come at a cost, not limited to the one-time expense of purchasing equipment but also the substantial time devoted to recruiting participants and administering the experiment. Moreover, exceptional circumstances that limit in-person testing, such as a global pandemic, may halt research progress. These limitations of in-person motor learning research have motivated the design of OnPoint, an open-source software package for motor control and motor learning researchers. As with all online studies, OnPoint offers an opportunity to conduct large-N motor learning studies, with potential applications to do faster pilot testing, replicate previous findings, and conduct longitudinal studies (GitHub repository: https://github.com/alan-s-lee/OnPoint).

scholarly journals Integration of enabling methods for the automated flow preparation of piperazine-2-carboxamide

2014 ◽  
Vol 10 ◽  
pp. 641-652 ◽  
Author(s):  
Richard J Ingham ◽  
Claudio Battilocchio ◽  
Joel M Hawkins ◽  
Steven V Ley
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Package ◽  
Flow Chemistry ◽  
Raspberry Pi ◽  
Step Flow ◽  
Simultaneous Control ◽  
Open Source Software Package

Here we describe the use of a new open-source software package and a Raspberry Pi® computer for the simultaneous control of multiple flow chemistry devices and its application to a machine-assisted, multi-step flow preparation of pyrazine-2-carboxamide – a component of Rifater®, used in the treatment of tuberculosis – and its reduced derivative piperazine-2-carboxamide.

scholarly journals ogttMetrics: Data structures and algorithms for oral glucose tolerance tests

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 684
Author(s):  
Benjamin J. Stubbs ◽  
Keith Frankston ◽  
Marcel Ramos ◽  
Nancy Laranjo ◽  
Frank M. Sacks ◽  
...  
Keyword(s):  
Glucose Tolerance ◽  
Open Source Software ◽  
Oral Glucose ◽  
Oral Glucose Tolerance ◽  
Estimation Of Parameters ◽  
Large Clinical Trial ◽  
Oral Glucose Tolerance Tests ◽  
Open Source Software Package ◽  
Glucose Tolerance Tests ◽  
Data Structures And Algorithms

We describe an open source software package, ogttMetrics, to compute diverse measures of glucose metabolism derived from oral glucose tolerance tests (OGTTs). Tools are provided to organize, visualize and compare OGTT data from large cohorts. Numerical difficulties in estimation of parameters of the Bergman minimal model are described, and in one large clinical trial, the simpler closed form index of Matsuda is observed to lead to similar rankings of individuals with respect to insulin sensitivity, and similar inferences concerning effects of modifications to carbohydrate content and glycemic index of experimental diets.

scholarly journals An open source software package for primality testing of numbers of the form p2^n+1, with no constraints on the relative sizes of p and 2^n

2018 ◽  
Author(s):  
Tejas R. Rao
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Package ◽  
Primality Testing ◽  
Fermat Number ◽  
Open Source Software Package ◽  
Sierpinski Numbers ◽  
Efficient Software

We develop an efficient software package to test for the primality of p2^n+1, p prime and p>2^n. This aids in the determination of large, non-Sierpinski numbers p, for prime p, and in cryptography. It furthermore uniquely allows for the computation of the smallest n such that p2^n+1 is prime when p is large. We compute primes of this form for the first one million primes p and find four primes of the form above 1000 digits. The software may also be used to test whether p2^n+1 divides a generalized fermat number base 3.

scholarly journals Modelling nonlinear dynamics of interacting tipping elements on complex networks: the PyCascades package

2021 ◽  
Author(s):  
Nico Wunderling ◽  
Jonathan Krönke ◽  
Valentin Wohlfarth ◽  
Jan Kohler ◽  
Jobst Heitzig ◽  
...  
Keyword(s):  
Dynamical Systems ◽  
Open Source Software ◽  
Software Package ◽  
Model Systems ◽  
Stochastic Dynamical Systems ◽  
Moisture Recycling ◽  
Modelling Framework ◽  
Different Types ◽  
Open Source Software Package ◽  
The Individual

AbstractTipping elements occur in various systems such as in socio-economics, ecology and the climate system. In many cases, the individual tipping elements are not independent of each other, but they interact across scales in time and space. To model systems of interacting tipping elements, we here introduce the PyCascades open source software package for studying interacting tipping elements (10.5281/zenodo.4153102). PyCascades is an object-oriented and easily extendable package written in the programming language Python. It allows for investigating under which conditions potentially dangerous cascades can emerge between interacting dynamical systems, with a focus on tipping elements. With PyCascades it is possible to use different types of tipping elements such as double-fold and Hopf types and interactions between them. PyCascades can be applied to arbitrary complex network structures and has recently been extended to stochastic dynamical systems. This paper provides an overview of the functionality of PyCascades by introducing the basic concepts and the methodology behind it. In the end, three examples are discussed, showing three different applications of the software package. First, the moisture recycling network of the Amazon rainforest is investigated. Second, a model of interacting Earth system tipping elements is discussed. And third, the PyCascades modelling framework is applied to a global trade network.

SpiderRadio: A cognitive radio network with commodity hardware and open source software

2011 ◽  
Vol 49 (3) ◽  
pp. 101-109 ◽  
Author(s):  
S. Sengupta ◽  
K. Hong ◽  
R. Chandramouli ◽  
K.P. Subbalakshmi
Keyword(s):  
Cognitive Radio ◽  
Open Source ◽  
Open Source Software ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Commodity Hardware

scholarly journals Using Open-Source Software for Sign Language Learning and Assessment

2019 ◽  
Vol 14 (19) ◽  
pp. 188
Author(s):  
Tobias Haug ◽  
Sarah Ebling
Keyword(s):  
Adult Learners ◽  
Language Learning ◽  
Open Source ◽  
Sign Language ◽  
Open Source Software ◽  
Self Assessment ◽  
Web Based ◽  
Swiss German ◽  
Feedback Questionnaire ◽  
The Web

This study reports on the use of an open-source software for sign language learning and (self-)assessment. A Yes/No vocabulary size test for Swiss German Sign Language (Deutschschweizerische Gebärdensprache, DSGS) was developed, targeting beginning adult learners. The Web-based test, which can be used for self-assessment or placement purposes, was administered to 20 DSGS adult learners of ages 24 to 55 (M = 39.3). The learners filled out a background questionnaire, took the Yes/No test tests, and filled out a feedback questionnaire. The comments provided by the learners about the suitability of the Web-based DSGS vocabulary self-assessment instrument provided concrete feedback towards improvement of the system.

scholarly journals Development and Evaluation of an Open-Source Software Package “CGITA” for Quantifying Tumor Heterogeneity with Molecular Images

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yu-Hua Dean Fang ◽  
Chien-Yu Lin ◽  
Meng-Jung Shih ◽  
Hung-Ming Wang ◽  
Tsung-Ying Ho ◽  
...  
Keyword(s):  
Open Source ◽  
Texture Analysis ◽  
Open Source Software ◽  
Software Package ◽  
Tumor Heterogeneity ◽  
Locally Advanced ◽  
Image Texture ◽  
Pixel Intensity ◽  
Open Source Software Package ◽  
Molecular Images

Background. The quantification of tumor heterogeneity with molecular images, by analyzing the local or global variation in the spatial arrangements of pixel intensity with texture analysis, possesses a great clinical potential for treatment planning and prognosis. To address the lack of available software for computing the tumor heterogeneity on the public domain, we develop a software package, namely, Chang-Gung Image Texture Analysis (CGITA) toolbox, and provide it to the research community as a free, open-source project.Methods. With a user-friendly graphical interface, CGITA provides users with an easy way to compute more than seventy heterogeneity indices. To test and demonstrate the usefulness of CGITA, we used a small cohort of eighteen locally advanced oral cavity (ORC) cancer patients treated with definitive radiotherapies.Results. In our case study of ORC data, we found that more than ten of the current implemented heterogeneity indices outperformed SUVmeanfor outcome prediction in the ROC analysis with a higher area under curve (AUC). Heterogeneity indices provide a better area under the curve up to 0.9 than the SUVmeanand TLG (0.6 and 0.52, resp.).Conclusions. CGITA is a free and open-source software package to quantify tumor heterogeneity from molecular images. CGITA is available for free for academic use athttp://code.google.com/p/cgita.

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