Free Open Source Software Tools Research Articles

A Comprehensive Roadmap to 50 Years of (Satellite) Earth Observation Resources for the Island of Ireland (1972 – 2023)

A comprehensive review of optical (panchromatic, multispectral and hyperspectral) and synthetic aperture radar satellite imagery coverage for terrestrial and near-shore areas of interest on the island of Ireland. The review spans 50 years and includes approximately 170+ retired and operational Earth Observation (EO) satellite sensors, and a further 60+ EO satellite sensors which are planned to be launched over the next five years. Satellite characteristics and sensor capabilities are listed in tabular form and the extents of the spatial and temporal coverage of the island of Ireland are estimated for each sensor (as available). Guidance on how to access this data is provided, with an emphasis on gaining free or reduced cost access for research and scientific purposes. Information on free open source software tools for viewing, processing and analysing EO imagery is provided, along with a selection of online resource and reference materials.

A Comprehensive Roadmap to 50 Years of (Satellite) Earth Observation Resources for the Island of Ireland (1972 – 2023)

A comprehensive review of optical (panchromatic, multispectral and hyperspectral) and synthetic aperture radar satellite imagery coverage for terrestrial and near-shore areas of interest on the island of Ireland. The review spans 50 years and includes approximately 170+ retired and operational Earth Observation (EO) satellite sensors, and a further 60+ EO satellite sensors which are planned to be launched over the next five years.Satellite characteristics and sensor capabilities are listed in tabular form and the extents of the spatial and temporal coverage of the island of Ireland are estimated for each sensor (as available). Guidance on how to access this data is provided, with an emphasis on gaining free or reduced cost access for research and scientific purposes.Information on free open source software tools for viewing, processing and analysing EO imagery is provided, along with a selection of online resource and reference materials.

Qualitative and Quantitative Shotgun Proteomics Data Analysis from Data-Dependent Acquisition Mass Spectrometry.

Shotgun proteomics is the inferential analysis of proteoforms using peptide proxies produced by enzyme-catalyzed hydrolysis of entire proteomes. Such peptides are usually identified by nanoflow liquid chromatography coupled to tandem mass spectrometry analysis (nLC-MS/MS). Traditionally, MS/MS analysis is performed in data-dependent acquisition (DDA) mode, which usually produces a pattern of fragment masses unique to a single peptide's fragmentation. Here, I describe a statistically rigorous qualitative and quantitative computational analysis for shotgun proteomics DDA analysis using free open-source software tools. MS/MS data are used to identify peptides, and the area of peptide mass/charge over chromatographic elution is used to quantify peptides. All peptides that uniquely map to a protein sequence predicted from the genome are combined into a single protein quantity, which can then be compared across experimental conditions. Statistically significant protein changes can be summarized using gene ontology or pathway term enrichment analysis.

Using Open-Source Data and Software to Analyse Land-Use Changes and Deforestation in Marqués de Comillas, Chiapa, Mexico (Work in Progress)

This project aimed to exploit existing open data and open-source software to allow visualising and finding spatial coincidences between three groups of indicators: 1) agricultural activity, 2) land use and forest cover changes, and 3) spatial distribution patterns of vegetation loss. This paper presents preliminary results of developing an interactive map using R, Leaflet, and QGIS to perform a simple overlay analysis of layers containing better policy and decision-making indicators. The map uses open data available through the Mexican government platforms, and all processing, storage and publication are done using free open-source software tools. The data used in this project was limited to the Marqués de Comillas municipality because of its importance in Mexico’s forest ecosystem. The maps are a work in progress and a continuation of research done for a geomatics graduate program in Centro de Investigación en Ciencias de Información Geoespacial.

Environmental factors and human activity as drivers of tree cover and density on the Island of Socotra, Yemen

Socotra Island, in the western Indian Ocean, harbors high biodiversity and endemism and makes up the largest part of the Socotra archipelago UNESCO World Heritage site. Its climatic, pedological, and geomorphological characteristics, together with the long geological isolation and inaccessibility, led to the flourishing of unique tree diversity, with great cultural and ecological value. Lately, trees on Socotra are facing new threats linked to the abandonment of traditional management practices, climate change impacts, and growing human pressure. This study assesses the relative influence of environmental factors and human activity as drivers of tree cover and density, which can be used to support land management policies for the conservation of this key local resource. Tree cover and density were assessed on a total of 3600 plots of 0.5 ha each, laid on a regular grid covering the entire area of the island through Collect Earth, a free open source software tool that allows an augmented visual interpretation of high-resolution satellite images. A total of 770,000 trees, with an average of 2.14 trees/ha, were estimated on the island. The collected data was validated by ground surveys in 26 plots. The relative influence of selected predictors (seven environmental, two anthropic) on tree cover and density was analyzed through logistic and survival regression. Tree cover and density were found to be impacted positively by steeper slopes, higher rainfall, and marked precipitation seasonality and negatively by relatively warmer temperatures and a higher sand content in the soil. Distance of each plot from the nearest road and settlement was calculated and neither of these anthropic predictors emerged as significant, indicating that the limited number of trees present are not currently as affected by anthropic pressure, but, instead, their presence is mostly limited by the harsh climatic and pedological factors. However, as human population and development increase, periods of drought rise, and extreme and random climatic events intensify, these additional stresses on the environment could negatively impact the availability of natural resources in the terrestrial environment. Lastly, potential recommendations to the existing conservation policies and Socotra Conservation Zoning Plan are discussed based on the results.

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media.

SummaryFor many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe limitations in the analysis of the nanoparticle dispersion by light scattering techniques. Here we present an alternative analysis and associated workflow which utilises electron microscopy. The need to collect large, statistically relevant datasets by imaging vacuum dried, plunge frozen aliquots of suspension was accomplished by developing an automated STEM imaging protocol implemented in an SEM fitted with a transmission detector. Automated analysis of images of agglomerates was achieved by machine learning using two free open‐source software tools: CellProfiler and ilastik. The specific results and overall workflow described enable accurate nanoparticle agglomerate analysis of particles suspended in aqueous media containing other potential confounding components such as salts, vitamins and proteins.Lay DescriptionIn order to further advance studies in both nanomedicine and nanotoxicology, we need to continue to understand the dispersion of nanoparticles in biological fluids. These biological environments often contain a number of components such as salts, vitamins and proteins which can lead to difficulties when using traditional techniques to monitor dispersion. Here we present an alternative analysis which utilises electron microscopy. In order to use this approach statistically relevant large image datasets were collected from appropriately prepared samples of nanoparticle suspensions by implementing an automated imaging protocol. Automated analysis of these images was achieved through machine learning using two readily accessible freeware; CellProfiler and ilastik. The workflow presented enables accurate nanoparticle dispersion analysis of particles suspended in more complex biological media.

Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks.

Neurophysiology requires an extensive workflow of information analysis routines, which often includes incompatible proprietary software, introducing limitations based on financial costs, transfer of data between platforms, and the ability to share. An ecosystem of free open-source software exists to fill these gaps, including thousands of analysis and plotting packages written in Python and R, which can be implemented in a sharable and reproducible format, such as the Jupyter electronic notebook. This tool chain can largely replace current routines by importing data, producing analyses, and generating publication-quality graphics. An electronic notebook like Jupyter allows these analyses, along with documentation of procedures, to display locally or remotely in an internet browser, which can be saved as an HTML, PDF, or other file format for sharing with team members and the scientific community. The present report illustrates these methods using data from electrophysiological recordings of the musk shrew vagus-a model system to investigate gut-brain communication, for example, in cancer chemotherapy-induced emesis. We show methods for spike sorting (including statistical validation), spike train analysis, and analysis of compound action potentials in notebooks. Raw data and code are available from notebooks in data supplements or from an executable online version, which replicates all analyses without installing software-an implementation of reproducible research. This demonstrates the promise of combining disparate analyses into one platform, along with the ease of sharing this work. In an age of diverse, high-throughput computational workflows, this methodology can increase efficiency, transparency, and the collaborative potential of neurophysiological research.

Transforming High School Classrooms with Free/Open Source Software: It's Time for an Open Source Software Revolution

Free/Open Source Software (FOSS) applications meet many of the software needs of high school science classrooms. In spite of the availability and quality of FOSS tools, they remain unknown to many teachers and utilized by fewer still. In a world where most software has restrictions on copying and use, FOSS is an anomaly, free to use and to redistribute without restrictions. Using FOSS instead of the ubiquitous proprietary applications most commonly used can seem as heretical and as impossible as did Copernicus's suggestion that the Earth was not the center of the universe. This paper suggests one of the factors that keeps schools from adopting—or even considering—FOSS is that its very existence can be written off as an anomaly. Additionally, it shows similarities between the development of FOSS and the development of scientific knowledge. Moreover, it provides examples of FOSS for high school science classrooms.