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FRIENDS GUI: A Graphical User Interface for Data Collection and Visualization of Vaping Behavior from a Passive Vaping Monitor. FRIENDS GUI：从被动电子烟监视器收集数据和可视化电子烟行为的图形用户界面。
Journal of Open Research Software Pub Date : 2026-01-01 Epub Date: 2026-04-07 DOI: 10.5334/jors.613
Shehan Irteza Pranto, Brett Fassler, Md Rafi Islam, Ashley Schenkel, Larry W Hawk, Edward Sazonov
{"title":"FRIENDS GUI: A Graphical User Interface for Data Collection and Visualization of Vaping Behavior from a Passive Vaping Monitor.","authors":"Shehan Irteza Pranto, Brett Fassler, Md Rafi Islam, Ashley Schenkel, Larry W Hawk, Edward Sazonov","doi":"10.5334/jors.613","DOIUrl":"10.5334/jors.613","url":null,"abstract":"<p><p>Understanding puffing topography (PT), which includes puff duration, intra-puff interval, and puff count per session, is critical for evaluating Electronic Nicotine Delivery Systems (ENDS) use, toxicant exposure, and informing regulatory decisions. We developed FRIENDS (Flexible Robust Instrumentation of ENDS), an open-source device that can be attached to ENDS and records puffing and touching events. This paper introduces the FRIENDS graphical user interface (GUI) that improves accessibility and interpretability of data collected by FRIENDS. The GUI is a Python-based open-source tool that extracts, decodes, and visualizes 24-hour puffing data from the FRIENDS device. Validation using 24-hour experimental data confirmed accurate timestamp conversion, reliable event decoding, and effective behavioral visualization. The software is freely available on GitHub for public use.</p>","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"14 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13170370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Population Spatial Frequency Toolbox. 人口空间频率工具箱。
Journal of Open Research Software Pub Date : 2026-01-01 DOI: 10.5334/jors.610
Luis D Ramirez, Feiyi Wang, Emily Wiecek, Louis N Vinke, Sam Ling
{"title":"The Population Spatial Frequency Toolbox.","authors":"Luis D Ramirez, Feiyi Wang, Emily Wiecek, Louis N Vinke, Sam Ling","doi":"10.5334/jors.610","DOIUrl":"10.5334/jors.610","url":null,"abstract":"<p><p>A goal of vision science is to develop computational models that characterize the fundamental response properties of neurons in visual cortex. One such property is spatial frequency (SF) tuning: neural populations in visual cortex selectively respond to specific bands of SF, which determines the level of detail, coarse or fine, represented from the visual input. The Population Spatial Frequency Toolbox (pSF-Toolbox) is a MATLAB package for characterizing the SF tuning of neural populations from functional magnetic resonance imaging (fMRI) data. This open-source toolbox includes stimulus presentation scripts and voxel-wise parameter optimization tools validated across a range of vision studies.</p>","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"14 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13340908/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148406141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
WEARDA: Recording Wearable Sensor Data for Human Activity Monitoring WEARDA:记录用于人类活动监测的可穿戴传感器数据
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.454
Richard M. K. van Dijk, Daniela Gawehns, Matthijs van Leeuwen
{"title":"WEARDA: Recording Wearable Sensor Data for Human Activity Monitoring","authors":"Richard M. K. van Dijk, Daniela Gawehns, Matthijs van Leeuwen","doi":"10.5334/jors.454","DOIUrl":"https://doi.org/10.5334/jors.454","url":null,"abstract":"We present WEARDA,1 the open source WEARable sensor Data Acquisition software package. WEARDA facilitates the acquisition of human activity data with smartwatches and is primarily aimed at researchers who require transparency, full control, and access to raw sensor data. It provides functionality to simultaneously record raw data from four sensors&mdash;tri-axis accelerometer, tri-axis gyroscope, barometer, and GPS&mdash;which should enable researchers to, for example, estimate energy expenditure and mine movement trajectories. A Samsung smartwatch running the Tizen OS was chosen because of 1) the required functionalities of the smartwatch software API, 2) the availability of software development tools and accessible documentation, 3) having the required sensors, and 4) the requirements on case design for acceptance by the target user group. WEARDA addresses five practical challenges concerning preparation, measurement, logistics, privacy preservation, and reproducibility to ensure efficient and errorless data collection. The software package was initially created for the project &ldquo;Dementia back at the heart of the community&rdquo;,2 and has been successfully used in that context.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135210955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
CastorEDC API: A Python Package for Managing Real World Data in Castor Electronic Data Capture CastorEDC API:在Castor电子数据捕获中管理真实世界数据的Python包
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.436
Reinier Cornelis Anthonius van Linschoten, Sebastiaan Laurens Knijnenburg, Rachel Louise West, Desirée van Noord
{"title":"CastorEDC API: A Python Package for Managing Real World Data in Castor Electronic Data Capture","authors":"Reinier Cornelis Anthonius van Linschoten, Sebastiaan Laurens Knijnenburg, Rachel Louise West, Desirée van Noord","doi":"10.5334/jors.436","DOIUrl":"https://doi.org/10.5334/jors.436","url":null,"abstract":"Real world data is being used increasingly in medical research. Castor Electronic Data Capture is a secure and user-friendly platform for managing study data. Integrating data from several databases into a single Castor database is complex. We developed CastorEDC API, a free and open source Python package which can be used to interact with the API of Castor, and through which data can be imported from multiple sources into a Castor database. The importer reads, cleans, validates and imports data while accounting for differences in column structure and variable coding between databases. https://github.com/reiniervlinschoten/castoredc_api.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GTdownloader: A Python Package to Download, Visualize, and Export Georeferenced Tweets From the Twitter API GTdownloader:一个Python包，用于从Twitter API下载、可视化和导出地理参考推文
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.443
Juan Acosta-Sequeda, S. Derrible
{"title":"GTdownloader: A Python Package to Download, Visualize, and Export Georeferenced Tweets From the Twitter API","authors":"Juan Acosta-Sequeda, S. Derrible","doi":"10.5334/jors.443","DOIUrl":"https://doi.org/10.5334/jors.443","url":null,"abstract":"This article describes GTdowloader, a Python package that serves as both an API wrapper and as a geographic information pre-processing helper to facilitate the download of Twitter data from the Twitter API. Specifically, the package offers functions that enable the download of Twitter data through single functions that integrate access to the API call parameters in the form of familiar Python functions syntax. In addition, the data is available for download in common formats for further analysis","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70682487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Plots.jl – A User Extendable Plotting API for the Julia Programming Language 情节。Julia编程语言的用户可扩展绘图API
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.431
Simon Christ, Daniel Schwabeneder, Christopher Rackauckas, Michael Krabbe Borregaard, Thomas Breloff
{"title":"Plots.jl – A User Extendable Plotting API for the Julia Programming Language","authors":"Simon Christ, Daniel Schwabeneder, Christopher Rackauckas, Michael Krabbe Borregaard, Thomas Breloff","doi":"10.5334/jors.431","DOIUrl":"https://doi.org/10.5334/jors.431","url":null,"abstract":"There are many excellent plotting libraries. Each excels at a specific use case: one is particularly suited for creating printable 2D figures for publication, another for generating interactive 3D graphics, while a third may have excellent L<small>A</small>T<small>E</small>X integration or be ideal for creating dashboards on the web. The aim of <tt>Plots.jl</tt> is to enable the user to use the same syntax to interact with a range of different plotting libraries, making it possible to change the library that does the actual plotting (the <em>backend</em>) without needing to touch the code that creates the content – and without having to learn multiple application programming interfaces (API). This is achieved by separating the specification of the plot from the implementation of the graphical backend. This plot specification is extendable by a <em>recipe</em> system that allows package authors and users to create new types of plots, as well as to specify how to plot any type of object (e.g. a statistical model, a map, a phylogenetic tree or the solution to a system of differential equations) without depending on the <tt>Plots.jl</tt> package. This design supports a modular ecosystem structure for plotting and yields a high code reuse potential across the entire Julia package ecosystem. <tt>Plots.jl</tt> is publicly available at <a href=\"https://github.com/JuliaPlots/Plots.jl\" target=\"_blank\">https://github.com/JuliaPlots/Plots.jl</a>.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135959476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Automated Discovery of Container Executables 自动发现容器可执行文件
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.451
V. Sochat, Matthieu Muffato, Audrey Stott, Marco De La Pierre, Georgia K. Stuart
{"title":"Automated Discovery of Container Executables","authors":"V. Sochat, Matthieu Muffato, Audrey Stott, Marco De La Pierre, Georgia K. Stuart","doi":"10.5334/jors.451","DOIUrl":"https://doi.org/10.5334/jors.451","url":null,"abstract":"Linux container technologies such as Docker and Singularity offer encapsulated environments for easy execution of software. In high performance computing, this is especially important for evolving and complex software stacks with conflicting dependencies that must co-exist. Singularity Registry HPC (“shpc”) was created as an effort to install containers in this environment as modules, seamlessly allowing for typically hidden executables inside containers to be presented to the user as commands, and as such significantly simplifying the user experience. A remaining challenge, however, is deriving the list of important executables in the container. In this work, we present a new modular methodology that allows for discovering new containers in large community sets, deriving container entries with relevant executables therein, and fully automating both recipe generation and updates over time. As an exemplar outcome, we have employed this methodology to add to the Registry over 8,000 containers from the BioContainers community that can be maintained and updated by the software automation. All software is publicly available on the GitHub platform, and can be beneficial to container registries and infrastructure providers for automatically generating container modules, thus lowering the usage entry barrier and improving user experience.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70682496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Taskfarm: A Client/Server Framework for Supporting Massive Embarrassingly Parallel Workloads Taskfarm:一个支持大量并行工作负载的客户端/服务器框架
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.393
M. Hagdorn, N. Gourmelen
{"title":"Taskfarm: A Client/Server Framework for Supporting Massive Embarrassingly Parallel Workloads","authors":"M. Hagdorn, N. Gourmelen","doi":"10.5334/jors.393","DOIUrl":"https://doi.org/10.5334/jors.393","url":null,"abstract":"","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70682099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fan-Slicer: A Pycuda Package for Fast Reslicing of Ultrasound Shaped Planes 风扇切片机:一个Pycuda包快速切割超声形状的平面
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.422
João Ramalhinho, T. Dowrick, E. Bonmati, M. Clarkson
{"title":"Fan-Slicer: A Pycuda Package for Fast Reslicing of Ultrasound Shaped Planes","authors":"João Ramalhinho, T. Dowrick, E. Bonmati, M. Clarkson","doi":"10.5334/jors.422","DOIUrl":"https://doi.org/10.5334/jors.422","url":null,"abstract":"Fan-Slicer (https://github.com/UCL/fan-slicer) is a Python package that enables the fast sampling (slicing) of 2D ultrasound-shaped images from a 3D volume. To increase sampling speed, CUDA kernel functions are used in conjunction with the Pycuda package. The main features include functions to generate images from both 3D surface models and 3D volumes. Additionally, the package also allows for the sampling of images from curvilinear (fan shaped planes) and linear (rectangle shaped planes) ultrasound transducers. Potential uses of Fan-slicer include the generation of large datasets of 2D images from 3D volumes and the simulation of intra-operative data among others","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70682609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MARIO: A Versatile and User-Friendly Software for Building Input-Output Models 马里奥:一个多功能和用户友好的软件，用于建立输入输出模型
Journal of Open Research Software Pub Date : 2023-01-01 DOI: 10.5334/jors.473
Mohammad Amin Tahavori, Nicolò Golinucci, Lorenzo Rinaldi, Matteo Vincenzo Rocco, Emanuela Colombo
{"title":"MARIO: A Versatile and User-Friendly Software for Building Input-Output Models","authors":"Mohammad Amin Tahavori, Nicolò Golinucci, Lorenzo Rinaldi, Matteo Vincenzo Rocco, Emanuela Colombo","doi":"10.5334/jors.473","DOIUrl":"https://doi.org/10.5334/jors.473","url":null,"abstract":"MARIO (Multi-Regional Analysis of Regions through Input-Output) is a Python-based framework for building input-output models. It automates the parsing of well-known databases (e.g. EXIOBASE, EORA, Eurostat) and of customized tables. With respect to similar tools, like pymrio, it broadens the scope of application to supply-use tables and handles both monetary and physical units. Employing an intuitive Excel-based API, it facilitates advanced table manipulations and allows for modelling additional supply chains through a hybrid LCA approach. It provides built-in functions for footprinting and scenario analyses as well as for visualizations of model outcomes. Results are exportable into various formats, possibly supplemented by a metadata file tracking the full history of applied changes. MARIO comes with extensive documentation and is available on Zenodo, GitHub, or installable via PyPI.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135214705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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