Open Source Software Tools Research Articles

COVID-19 CT Scan Lung Segmentation: How We Do It.

The National Health Systems have been severely stressed out by the COVID-19 pandemic because 14% of patients require hospitalization and oxygen support, and 5% require admission to an Intensive Care Unit (ICU). Relationship between COVID-19 prognosis and the extent of alterations on chest CT obtained by both visual and software-based quantification that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one has been proven. While commercial applications for automatic medical image computing and visualization are expensive and limited in their spread, the open-source systems are characterized by not enough standardization and time-consuming troubles. We analyzed chest CT exams on 246 patients suspected of COVID-19 performed in the Emergency Department CT room. The lung parenchyma segmentation was obtained by a threshold-based method using the open-source 3D Slicer software and software tools called “Segment Editor” and “Segment Quantification.” For the three main characteristics analyzed on lungs affected by COVID-19 pneumonia, a specifical densitometry value range was defined: from − 950 to − 700 HU for well-aerated parenchyma; from − 700 to − 250 HU for interstitial lung disease; from − 250 to 250 HU for parenchymal consolidation. For the well-aerated parenchyma and the interstitial alterations, the procedure was semi-automatic with low time consumption, whereas consolidations’ analysis needed manual interventions by the operator. After the chest CT, 13% of the sample was admitted to intensive care, while 34% of them to the sub-intensive care. In patients moved to intensive care, the parenchyma analysis reported a higher crazy paving presentation. The quantitative analysis of the alterations affecting the lung parenchyma of patients with COVID-19 pneumonia can be performed by threshold method segmentation on 3D Slicer. The segmentation could have an important role in the quantification in different COVID-19 pneumonia presentations, allowing to help the clinician in the correct management of patients.

Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture

Digital solutions in agricultural management promote food security and support the sustainable use of resources. As a result, remote sensing (RS) can be seen as an innovation for the fast generation of reliable information for agricultural management. Near real-time processed RS data can be used as a tool for decision making on multiple scales, from subplot to the global level. This high potential is not yet fully applied, due to often limited access to ground truth information, which is crucial for the development of transferable applications and acceptance. In this study we present a digital workflow for the acquisition, processing and dissemination of agroecological information based on proprietary and open-source software tools with state-of-the-art web-mapping technologies. Data is processed in near real-time and thus can be used as ground truth information to enhance quality and performance of RS-based products. Data is disseminated by easy-to-understand visualizations and download functionalities for specific application levels to serve specific user needs. It thus can increase expert knowledge and can be used for decision support at the same time. The fully digital workflow underpins the great potential to facilitate quality enhancement of future RS products in the context of precision agriculture by safeguarding data quality. The generated FAIR (findable, accessible, interoperable, reusable) datasets can be used to strengthen the relationship between scientists, initiatives and stakeholders.

Feasibility Analysis of Phenotype Quantification from Unstructured Clinical Interactions.

We conducted a feasibility analysis to determine the quality of data that could be collected ambiently during routine clinical conversations. We used inexpensive, consumer-grade hardware to record unstructured dialogue and open-source software tools to quantify and model face, voice (acoustic and language) and movement features. We used an external validation set to perform proof-of-concept predictive analyses and show that clinically relevant measures can be produced without a restrictive protocol.

How Gender-Biased Tools Shape Newcomer Experiences in OSS Projects

Previous research has revealed that newcomer women are disproportionately affected by gender-biased barriers in open source software (OSS) projects. However, this research has focused mainly on social/cultural factors, neglecting the software tools and infrastructure. To shed light on how OSS tools and infrastructure might factor into OSS barriers to entry, we conducted two studies: (1) a field study with five teams of software professionals, who worked through five use cases to analyze the tools and infrastructure used in their OSS projects; and (2) a diary study with 22 newcomers (9 women and 13 men) to investigate whether the barriers matched the ones identified by the software professionals. The field study produced a bleak result: software professionals found gender biases in 73 percent of all the newcomer barriers they identified. Further, the diary study confirmed these results: Women newcomers encountered gender biases in 63 percent of barriers they faced. Fortunately, many kinds of barriers and biases revealed in these studies could potentially be ameliorated through changes to the OSS software environments and tools.

Cost-effective automated multipurpose delivery system software for hospitals

Covid-19 pandemic has impacted every aspect of our society. One of the worst affected parts is the countries’ health systems. Our goal is to provide a proof of concept for cost effective automated delivery system which can be used by hospitals for distributing medicine and food to patients in non-intensive wards, so medical personnel exposure to the virus can be minimized. Only free and open source software tools are used. Working proof of concept of the system is created consisted of: robot platform running ROS, SQL Server relational database, Web App. Limitations are identified. Testing is successful. We have showed that using free and open-source software and tools, it is possible to achieve the goal of creating the system.

Mlphon: A Multifunctional Grapheme-Phoneme Conversion Tool Using Finite State Transducers

In this article we present the design and the development of a knowledge based computational linguistic tool, Mlphon [em.el.foːɳ] for Malayalam language. Mlphon computationally models linguistic rules using finite state transducers and performs multiple functions including grapheme to phoneme (g2p) and phoneme to grapheme (p2g) conversions, syllabification, phonetic feature analysis and script grammar check. This open source software tool, released under MIT license, is developed as a one-stop solution to handle different speech related text processing tasks for automatic speech recognition, text to speech synthesis and non-speech natural language processing tasks including syllable subword based language modeling, phoneme diversity analysis and text sanity check. The tool is evaluated on a manually crafted gold standard lexicon. Mlphon performs orthographic syllabification with 99% accuracy with a syllable error rate of 0.62% on the gold standard lexicon. For grapheme to phoneme conversion task, overall phoneme recognition accuracy of 99% with a phoneme error rate of 0.55% is obtained on gold standard lexicon. Additionally an extrinsic evaluation of Mlphon is performed by employing the pronunciation lexicon created using Mlphon, in Malayalam automatic speech recognition (ASR) task. Performance analysis in terms of the computation time of lexicon creation process and the word error rate (WER) on ASR task are presented along with a comparison over other automated tools for lexicon creation. Pronunciation lexicons with more than 100k commonly used Malayalam words in phonemised and syllabified forms is created and they are published as open language resources along with this work. We also demonstrate the usage of Mlphon on different natural language processing applications - syllable subword ASR, assisted pronunciation learning, phoneme diversity analysis and text sanity check. Being a knowledge based solution with open source code, Mlphon can be adapted to other languages of similar script nature.

UHAS-MIDA Software Package: Mass Isotopomer Distribution Analysis-Applying the Inverse Matrix for the Determination of Stable Isotopes of Chromium Distribution during Red Blood Cell Labelling

Clinical assessment of fluid volume status in children during malaria can be taxing and often inaccurate. During malaria, changes in fluid volume are rather multifarious and estimating this parameter, especially in sick children is very challenging for clinicians who frequently rely on indices such as long capillary refill times, tachycardia, central venous pressure and decreased urine volume as guides. Here, we present the UHAS-MIDA, an open-source software tool that calculates the red blood cell (RBC) concentration and blood volume during malaria in children determined using a stable isotope of chromium (53Cr as the label) by gas chromatography-mass spectrometry in selective ion monitoring (GC/MS-SIM) analysis. A key component involves the determination of the compositions of the most abundant naturally occurring isotopes of Cr (50Cr, 52Cr, 53Cr), and converting the proportions into a 3 × 3 matrix. To estimate unknown proportions of chromium isotopic mixtures from the measured abundances of three ions, an inverse matrix was calculated. The inverse together with several inputs is then used to calculate the corrected MS ion abundances. Thus, we constructed the software tool UHAS- MIDA using HTML, CSS/Bootstrap, JavaScript, and PHP scripting languages. The tool enables the user to efficiently determine RBC concentration and fluid volume. The source code, binary packages and associated materials for UHAS-MIDA are freely available at https://github.com/bentil078/Abaye-et-al_UHASmida

Using RNA-Seq for Transcriptome Profiling of Botrylloides sp. Regeneration.

The decrease in sequencing costs and technology improvements has led to the adoption of RNA-sequencing to profile transcriptomes from further non-traditional regeneration model organisms such as the colonial ascidian Botrylloides leachii. The relatively unbiased way in which transcripts are identified and quantified makes this technique suitable to detect large-scale changes in expression, and the identification of novel transcripts and isoforms. Of particular interest to many researchers is the discovery of differentially expressed transcripts across different treatment conditions or stages of regeneration. This protocol describes a workflow starting from processing raw sequencing reads, mapping reads, assembly of transcripts, and measuring their abundance, creating lists of differentially expressed genes and their biological interpretation using gene ontologies. All programs used in this protocol are open-source software tools and freely available.

Extraction of transforming sequences and sentence histories from writing process data: a first step towards linguistic modeling of writing

Producing written texts is a non-linear process: in contrast to speech, writers are free to change already written text at any place at any point in time. Linguistic considerations are likely to play an important role, but so far, no linguistic models of the writing process exist. We present an approach for the analysis of writing processes with a focus on linguistic structures based on the novel concepts of transforming sequences, text history, and sentence history. The processing of raw keystroke logging data and the application of natural language processing tools allows for the extraction and filtering of product and process data to be stored in a hierarchical data structure. This structure is used to re-create and visualize the genesis and history for a text and its individual sentences. Focusing on sentences as primary building blocks of written language and full texts, we aim to complement established writing process analyses and, ultimately, to interpret writing timecourse data with respect to linguistic structures. To enable researchers to explore this view, we provide a fully functional implementation of our approach as an open-source software tool and visualizations of the results. We report on a small scale exploratory study in German where we used our tool. The results indicate both the feasibility of the approach and that writers actually revise on a linguistic level. The latter confirms the need for modeling written text production from the perspective of linguistic structures beyond the word level.

Bibliometric analysis of isotopic studies on Quaternary megafauna available in the Scopus database.

The number of isotopic studies on Quaternary megafauna has increased over the last decades, yet, there is no published data addressing the status of scientific production of this research field. The present study shows the results of a bibliometric research carried out in the Scopus database where the publishing trends within this scientific field was analyzed using the open source software tool SciMAT. We retrieved 278 papers published from 1980 to 2019 and observed that a significant increase in publishing has mainly occurred in the last decade analyzed here. We also identified some of the field´s most influential articles and journals; recognized that carbon, oxygen and nitrogen isotopes are the most used markers in these studies; and that the most cited taxa are representatives of Equidae, Bovidae and Proboscidae. Also, Paleoecology is the basic thematic area, whereas Climate and Paleoenvironmental Changes is the one with the greatest development potential. Our results clearly show that the isotopic study on Quaternary megafauna is still under development and that some subjects could be further explored, such as analyzing more taxa within Carnivora, Pilosa, Notoungulata, Cetartiodactyla and Perissodactyla as well as using other less frequent stable isotope markers, such as strontium, calcium and hydrogen.

Open-source software tools for strategic noise mapping: a case study

Currently, the European Union has adopted a series of measures to combat noise problems, focusing on some key indicators, such as the daily and night level of noise. Among the possible actions to manage environmental noise, there are the creation of noise maps and the adoption of action plans. Noise maps are, usually, produced by modelling and simulating data relating to traffic and various activities of an area. However, in some cases, these input data are not available or it is not possible to include all noise sources in the models used, causing difficulties in the prediction and analysis of the environmental impacts of noise. In this paper, starting from the analysis of open-source software tools for data collection, noise modelling and mapping, i.e. Openstreet Map, Noise Modelling and QGIS, based on free and public licenses, a methodology for the creation of noise maps will be presented. Finally, the outputs of the application of the methodology to the city centre of the Municipality of Nocera Inferiore, in south Italy, will be the creation of noise maps characterized by the spatial representation of the main standard noise indicators.

Teaching cellular metabolism using metabolic model simulations

Teaching biology contents to chemical engineers is usually a challenging task, as it generally does not fit well to the quantitative approach with which engineering students are familiar. Here, we show that quantitative aspects of cellular metabolism can be explored using simulation tools, contributing to the engagement of students regarding this topic. Using OptFlux, an open-source software tool developed for metabolic engineering research, the students simulated the behavior of Escherichia coli and Saccharomyces cerevisiae cells under different environmental conditions. Exploring the user-friendly features of OptFlux, we present a set of four simulation tasks where the students are encouraged to discuss fundamental metabolic pathways such as glycolysis and the TCA cycle, the effect of genetic modifications on carbon flux redistribution through the metabolic network, and other important aspects of cell metabolism. The responses of the students to a questionnaire regarding the suitability of using OptFlux as an educational tool showed that their overall opinion was highly positive. Most students had no difficulties using the software and believed that the proposed exercises using OptFlux constituted a good strategy for teaching and reviewing cell metabolism concepts. Given these results, we believe that this alternative approach is a useful methodology for engaging students and facilitating the teaching of cellular metabolism to chemical engineers.

A Monitoring Digital Twin for Services of Controlled Environment Agriculture

Due to the higher level of automation than traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. Digital Twin (DT) is considered a technology with the potential to bring CEA to new levels of productivity and sustainability. In this context, a monitoring Digital Twin (mDT) has been developed to provide services for the monitoring of the different subsystems of CEA facilities. By integrating open-source software tools, an architecture was built able to: i) gather different types of data collected from a CEA facility; ii) store the collected data and calculate relevant features from them; iii) locally and remotely display the assessed data. The implemented mDT has the potential to generate a database of CEA data that in future may be utilized by predictive and prescriptive algorithms to suggest actions able to improve the productivity and sustainability of the process.

A modular platform for automated cryo-FIB workflows.

Lamella micromachining by focused ion beam milling at cryogenic temperature (cryo-FIB) has matured into a preparation method widely used for cellular cryo-electron tomography. Due to the limited ablation rates of low Ga+ ion beam currents required to maintain the structural integrity of vitreous specimens, common preparation protocols are time-consuming and labor intensive. The improved stability of new-generation cryo-FIB instruments now enables automated operations. Here, we present an open-source software tool, SerialFIB, for creating automated and customizable cryo-FIB preparation protocols. The software encompasses a graphical user interface for easy execution of routine lamellae preparations, a scripting module compatible with available Python packages, and interfaces with three-dimensional correlative light and electron microscopy (CLEM) tools. SerialFIB enables the streamlining of advanced cryo-FIB protocols such as multi-modal imaging, CLEM-guided lamella preparation and in situ lamella lift-out procedures. Our software therefore provides a foundation for further development of advanced cryogenic imaging and sample preparation protocols.

A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states

Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of available tools that enable efficient and scalable DA in a non-intrusive fashion and that support implementation flexibility. This paper presents an open-source software tool (PESTPP-DA) that implements a range of data assimilation methods—Ensemble Kalman filter, Ensemble Kalman Smoother and Ensemble Smoother—using the widely known PEST model-interface protocols, to interact with any model. Two iterative solutions can be used for nonlinear and/or non-Gaussian assimilation problems. To demonstrate the broad range of PESTPP-DA applications, two synthetic case studies are presented: (1) the Lorenz model and (2) a groundwater pumping test in the presence of a non-Gaussian hydraulic conductivity field.

EScience Infrastructures in Physical Chemistry.

As the volume of data associated with scientific research has exploded over recent years, the use of digital infrastructures to support this research and the data underpinning it has increased significantly. Physical chemists have been making use of eScience infrastructures since their conception, but in the last five years their usage has increased even more. While these infrastructures have not greatly affected the chemistry itself, they have in some cases had a significant impact on how the research is undertaken. The combination of the human effort of collaboration to create open source software tools and semantic resources, the increased availability of hardware for the laboratories, and the range of data management tools available has made the life of a physical chemist significantly easier. This review considers the different aspects of eScience infrastructures and explores how they have improved the way in which we can conduct physical chemistry research.

Efficiency of +IDonBlender Photogrammetric Tool in Facial Prosthetics Rehabilitation – An Evaluation Study

Several open-source 3D modeling software tools have recently been featured to reconstruct a 3D image-based model using Structure from Motion (SfM) algorithms such as +IDonBlender. It is, therefore, necessary to evaluate the accuracy of the models extracted from this tool to prove effectiveness for different applications. This paper aims to evaluate the +IDonBlender methodology tool in rehabilitating facial deformations. +IDonBlender is an add-on tool programmed within Blender software and designed for medical applications. In this research, two individuals from different genders have volunteered to contribute to this study, one with severe facial deformation and the other is healthy with no defects. To assess the robustness of the derived digital model from the +IDonBlender methodology, Agisoft Metashape was used to process the data and create a reference model for comparison purposes. Various scenarios were followed for evaluation: (i) scaling the model based on reference ground truth points, (ii) scaling the model based on known real distance between two reference points, and (iii) cloud-to-mesh (C2M) analysis was applied to individual scenarios to assess the accuracy of the +IDonBlender model through cloud compare analysis. Next, the density analysis of the model was also used to investigate the model resolution for further post-processing and prototyping. The results show that the variation between the tested and the reference models in terms of coordinates and distance measurements was (0.470 mm) and (0.471mm), respectively. Despite the fact that the +IDonBlender model resolution was lower than the Metashape model, the overall results delivered acceptable geometric error values. Therefore, following visual and statistical point clouds data analysis, one can claim the robustness of the +IDonBlender 3D modeling tool for maxillofacial rehabilitation, surgical planning and other clinical applications.

Micro-Meta App: an interactive tool for collecting microscopy metadata based on community specifications

For quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.

Lifelong training program on QGIS tools for earth observation sciences in south-east Europe

Earth Observation (EO) data are an indispensable source of useful geospatial information, which can be efficiently combined with other data within the latest released open-source QGIS software. This paper aims: i) to present a general overview of the QGIS EO plugins; ii) to promote the Lifelong Learning (LLL) courses for open-source QGIS software tools provided by the Geo-SEE Institute from Skopje; iii) to appreciate the advantages of open-source QGIS for developing and improving EO applications. The training objectives are to enhance the research, development tools and technologies of QGIS and stimulate the obtaining and disseminating knowledge to utilize the open-source GIS software. Furthermore, there is a growing need to increase the number of well-educated professionals on issues related to the EO sciences in South-East Europe (SEE), who are better prepared for the labor market in today's digital revolution by using QGIS tools and plugins combined with other related GIS software platforms provided by the OSGeo family.

EntropyHub: An open-source toolkit for entropic time series analysis.

An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods. To date, packages for performing entropy analysis are often run using graphical user interfaces, lack the necessary supporting documentation, or do not include functions for more advanced entropy methods, such as cross-entropy, multiscale cross-entropy or bidimensional entropy. In light of this, this paper introduces EntropyHub, an open-source toolkit for performing entropic time series analysis in MATLAB, Python and Julia. EntropyHub (version 0.1) provides an extensive range of more than forty functions for estimating cross-, multiscale, multiscale cross-, and bidimensional entropy, each including a number of keyword arguments that allows the user to specify multiple parameters in the entropy calculation. Instructions for installation, descriptions of function syntax, and examples of use are fully detailed in the supporting documentation, available on the EntropyHub website– www.EntropyHub.xyz. Compatible with Windows, Mac and Linux operating systems, EntropyHub is hosted on GitHub, as well as the native package repository for MATLAB, Python and Julia, respectively. The goal of EntropyHub is to integrate the many established entropy methods into one complete resource, providing tools that make advanced entropic time series analysis straightforward and reproducible.