Open Source Software Applications Research Articles

Evaluation of Open-Source Ciliary Analysis Software in Primary Ciliary Dyskinesia: A Comparative Assessment.

Primary Ciliary Dyskinesia (PCD) is a rare genetic disorder characterized by alterations in motile cilia function. The diagnosis of PCD is challenging due to the lack of standardized methods in clinical practice. High-speed video microscopy analysis (HSVA) directly evaluates ciliary beat frequency (CBF) in PCD. Recently, open-source ciliary analysis software applications have shown promise in measuring CBF accurately. However, there is limited knowledge about the performance of different software applications, creating a gap in understanding their comparative effectiveness in measuring CBF in PCD. We compared two open-source software applications, CiliarMove (v219) and Cilialyzer (v1.2.1-b3098cb), against the manual count method. We used high-speed videos of nasal ciliary brush samples from PCD RSPH4A-positive (PCD (RSPH4A)) patients and healthy controls. All three methods showed lower median CBF values for patients with PCD (RSPH4A) than in healthy controls. CiliarMove and Cilialyzer identified lower CBF in patients with PCD (RSPH4A), similarly to the manual count. Cilialyzer, CiliarMove, and manual count methods demonstrated statistical significance (p-value < 0.0001) in the difference of median CBF values between patients with PCD (RSPH4A) and healthy controls. Correlation coefficients between the manual count values against both software methods demonstrated positive linear relationships. These findings support the utility of open-source software-based analysis tools. Further studies are needed to validate these findings with other genetic variants and identify the optimal software for accurate CBF measurement in patients with PCD.

PyMBE: The Python-based molecule builder for ESPResSo.

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software application to design custom coarse-grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides, and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of ESPResSo offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is prone to mistakes, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in ESPResSo using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems, which contain several types of reactive groups, is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in ESPResSo, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE), which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article.

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer

New therapies are being developed for breast cancer, and in this process, some “old” biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker’s intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs’ clinical utility.Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs.Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%.Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Characterizing Usability Issue Discussions in Open Source Software Projects

Usability is a crucial factor but one of the most neglected concerns in open source software (OSS). While far from an ideal approach, a common practice that OSS communities adopt to collaboratively address usability is through discussions on issue tracking systems (ITSs). However, there is little knowledge about the extent to which OSS community members engage in usability issue discussions, the aspects of usability they frequently target, and the characteristics of their collaboration around usability issue discussions. This knowledge is important for providing practical recommendations and research directions to better support OSS communities in addressing this important topic and improve OSS usability in general. To help achieve this goal, we performed an extensive empirical study on issues discussed in five popular OSS applications: three data science notebook projects (Jupyter Lab, Google Colab, and CoCalc) and two code editor projects (VSCode and Atom). Our results indicated that while usability issues are extensively discussed in the OSS projects, their scope tended to be limited to efficiency and aesthetics. Additionally, these issues are more frequently posted by experienced community members and display distinguishable characteristics, such as involving more visual communication and more participants. Our results provide important implications that can inform the OSS practitioners to better engage the community in usability issue discussion and shed light on future research efforts toward collaboration techniques and tools for discussing niche topics in diverse communities, such as the usability issues in the OSS context.

Effective Application of Artificial Intelligence Techniques in Security Risk Assessment and Dependency Analysis of Open Source Components

Abstract With the wide application of open source software, the security of open source components has become a non-negligible problem in software development. In this paper, based on the research on deep learning algorithms, the deep reinforcement learning algorithm DQN is proposed, and the DQN-LightGBM model is constructed by combining LightGBM classifiers to achieve better mining performance. This model introduces the attention mechanism and BiLSTM network, and the TextACBL vulnerability identification algorithm is proposed. In the end, the performance of the open source component vulnerability mining model is evaluated to investigate its impact on vulnerability identification, risk assessment, and dependency analysis of open source components. The results show that the performance of DQN-LightGBM model is above 0.9 in accuracy, checking accuracy, checking completeness, AUC value, and F1, and the mining completion time is only 54s, which is the best. The accuracy of TextACBL model in identifying the types of vulnerabilities is above 94%, and the vulnerability danger levels on the seven items measured are high, low, high, high, and high risk, respectively, medium risk, high risk, and medium risk. The differences in the global graph features of the identified normal and vulnerability samples are obvious, and there are frequent dependencies in the probability graphs of the opcodes of the vulnerability samples. This study allows for the assessment of security risks of open source components and the comprehensive, accurate, and efficient conduct of dependency analysis.

Smart grading: A generative AI-based tool for knowledge-grounded answer evaluation in educational assessments

Evaluating text-based answers obtained in educational settings or behavioral studies is time-consuming and resource-intensive. Applying novel artificial intelligence tools such as ChatGPT might support the process. Still, currently available implementations do not allow for automated and case-specific evaluations of large numbers of student answers. To counter this limitation, we developed a flexible software and user-friendly web application that enables researchers and educators to use cutting-edge artificial intelligence technologies by providing an interface that combines large language models with options to specify questions of interest, sample solutions, and evaluation instructions for automated answer scoring. We validated the method in an empirical study and found the software with expert ratings to have high reliability. Hence, the present software constitutes a valuable tool to facilitate and enhance text-based answer evaluation.•Generative AI-enhanced software for customizable, case-specific, and automized grading of large amounts of text-based answers.•Open-source software and web application for direct implementation and adaptation.

Scalable generalized screening for high-order terms in the many-body expansion: Algorithm, open-source implementation, and demonstration.

The many-body expansion lies at the heart of numerous fragment-based methods that are intended to sidestep the nonlinear scaling of abinitio quantum chemistry, making electronic structure calculations feasible in large systems. In principle, inclusion of higher-order n-body terms ought to improve the accuracy in a controllable way, but unfavorable combinatorics often defeats this in practice and applications with n ≥ 4 are rare. Here, we outline an algorithm to overcome this combinatorial bottleneck, based on a bottom-up approach to energy-based screening. This is implemented within a new open-source software application ("Fragme∩t"), which is integrated with a lightweight semi-empirical method that is used to cull subsystems, attenuating the combinatorial growth of higher-order terms in the graph that is used to manage the calculations. This facilitates applications of unprecedented size, and we report four-body calculations in (H2O)64 clusters that afford relative energies within 0.1 kcal/mol/monomer of the supersystem result using less than 10% of the unique subsystems. We also report n-body calculations in (H2O)20 clusters up to n = 8, at which point the expansion terminates naturally due to screening. These are the largest n-body calculations reported to date using ab initio electronic structure theory, and they confirm that high-order n-body terms are mostly artifacts of basis-set superposition error.

Applying a Geographic Information System and Other Open-Source Software to Geological Mapping and Modeling: History and Case Studies

Open-source software applications, especially those useful for GIS, have been used in the field of geology both in research and teaching at the University of Urbino for decades. The experiences described in this article range from land-surveying cases to cartographic processing and 3D printing of geological models. History of their use and development is punctuated by trials, failures, and slowdowns, but the idea of using digital tools in areas where they are traditionally frowned upon, such as in soil geology, is now rooted in and validated by applications in projects of various types. Although the current situation is not definitive, given that the evolution of information technology provides increasingly faster tools that are performance-oriented and easier to use, this article aims to contribute to the development of methodologies through an exchange of information and experiences.

Tridimensional characterization of open cells and hollow strut cavities from SiC and ZrO2 foams: A study accomplished with open-source software tools

The characterization of ceramic foams via X-ray microtomography imaging method is often restricted to a general overview of samples, either to perform qualitative or quantitative analyses. To assess the foam with a focus on some specific components of its structure, such as hollow struts’ cavities and open cells, the generalized characterizations must be overcome. This work presents image analysis methodologies, based on open-source software, tools, and plugins, to achieve the aforementioned characterizations. SiC and ZrO2 foams samples were analyzed and some of the results were compared with those accomplished with pieces of commercial software. The results show good agreement between open-source and commercial software applications, indicating that the presented methodologies can be freely applied by any researcher to analyze their foams.

Analisis Deformasi Jalan Penghubung Antara Kelurahan Sanga-Sanga Dalam dan Kelurahan Pendingin Tahun 2015 dan 2021 Menggunakan Metode Interferometry Synthetic Aperture Radar

The rise of coal mining in the East Kalimantan area which is close to public road access is thought to affect the quality and sustainability of surrounding public road access. The aim of this research is to determine the use of remote sensing data to analyze land subsidence or deformation that occurs on the connecting road between Sanga-Sanga Dalam Village and Pendingin Village, Sanga-Sanga District, Kutai Kartanegara Regency. The method used in this research is quantitative descriptive, namely determining ground deformation on roads obtained by analyzing Sentinel-1 imagery in 2015 and Sentinel-1 imagery in 2021. Ground deformation can be identified using a satellite-based remote sensing method through interferometry of two SAR images (interferometry synthetic aperture radar or InSAR) uses the Sentinel application platform (SNAP) which is an open source software (FOSS) application. Interferometry can represent changes in the line of sight between the ground and satellites in general. Changes in line of sight can be interpreted as signals of ground deformation. The results of this research can provide adequate information regarding comparative data on land elevation on the Sanga-Sanga Dalam - Pendingin road from several points experiencing land subsidence or deformation on average of 161.3 cm with an average land subsidence rate of 23.04 cm/year . Thus, remote sensing technology using the InSAR technique can be used to determine changes that occur in a short time and at low cost.

RGBradford: Protein Quantitation with a Smartphone Camera.

Protein quantitation is an essential procedure in life sciences research. Amongst several other methods, the Bradford assay is one of the most used. Because of its widespread, the limitations and advantages of the Bradford assay have been exhaustively reported, including several modifications of the original method to improve its performance. One of the alterations of the original method is the use of a smartphone camera as an analytical instrument. Taking advantage of the three forms of the Coomassie Brilliant Blue dye that exist in the conditions of the Bradford assay, this paper describes how to accurately quantify protein in samples using color data extracted from a single picture of a microplate. After performing the assay in a microplate, a picture is taken using a smartphone camera, and RGB color data is extracted from the picture using a free and open-source image analysis software application. Then, the ratio of blue to green intensity (in the RGB scale) of samples with unknown concentrations of protein is used to calculate the protein content based on a standard curve. No significant difference is observed between values calculated using RGB color data and those calculated using conventional absorbance data.

Development of a spatial orientation model for the actuator of a mechatronic system

Purpose. Development of a control system for a mechatronic system, taking into account the geometric solution of the inverse kinematics problem. The methods. The research was based on the principles of theoretical and applied mechanics, as well as the Denavit-Hartenberg transformation model. The formation of graphical computational models and kinematic diagrams simplified the development of the mathematical model of the dynamic system without considering the forces acting on the mechanism links. The possibility of using matrix transformations to simplify the search for generalized coordinates and transition to the local disposition of each link was explored for further integration of the obtained results into automation and control systems. Findings. The obtained results, determining the trajectory of the gripper using inverse kinematics models, allowed the development of algorithms for determining the position of mechanism links with the possibility of software implementation of the control system. Identifying patterns for determining accurate position coordinates by the matrix method allows the application of open-source software for real-time position calculations. The originality. The use of modern technologies for visual assessment of the external environment and coordinating control impulses of the executive body drive was first achieved based on the mathematical model of the inverse kinematics of a multi-link mechanism. This automated the determination of local coordinates for each link within its degrees of freedom and algorithmized this process. Combining the mathematical models of mechanism kinematics and the matrix form of coordinate search allows investigating the influence of the displacement of the i-th link of the mechatronic technical complex on the overall system, considering the acting force systems and the specified spatial orientation of both the executive body and intermediate links. Practical implementation. The implementation of obtained kinematic models using the matrix method enables the software realization of algorithms for searching the coordinates of the i-th mechanism link, automating the control process with the task of final positions, determining the level of integral error during the displacement of the initial link, and providing the possibility of programming autonomous mechatronic systems with open-source code. As a result, the introduction of semi or fully autonomous technical complexes will automate technological processes in various industries.

Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool

Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles tailored for research software have been proposed by the FAIR for Research Software (FAIR4RS) Working Group. They provide a foundation for optimizing the reuse of research software. The FAIR4RS principles are, however, aspirational and do not provide practical instructions to the researchers. To fill this gap, we propose in this work the first actionable step-by-step guidelines for biomedical researchers to make their research software compliant with the FAIR4RS principles. We designate them as the FAIR Biomedical Research Software (FAIR-BioRS) guidelines. Our process for developing these guidelines, presented here, is based on an in-depth study of the FAIR4RS principles and a thorough review of current practices in the field. To support researchers, we have also developed a workflow that streamlines the process of implementing these guidelines. This workflow is incorporated in FAIRshare, a free and open-source software application aimed at simplifying the curation and sharing of FAIR biomedical data and software through user-friendly interfaces and automation. Details about this tool are also presented.

CoDEvo: Column family database evolution using model transformations

In recent years, software applications have been working with NoSQL databases as they have emerged to handle big data more efficiently than traditional databases. The data models of these databases are designed to satisfy the requirements of the software application, which means that the models must evolve when the requirements of the software application change. To avoid mistakes during the design and evolution of these NoSQL models, there are several methodologies that recommend using a conceptual model. This implies that consistency between the conceptual model and the schema must be maintained when either evolving the database or the software application. In this work, we propose CoDEvo, a model-driven engineering approach that uses model transformations to address the evolution of a NoSQL column family DBMS schema when the underlying conceptual model evolves due to software requirement changes, aiming to maintain consistency between the schema and conceptual model. We have addressed this problem by defining transformation rules that determine how to evolve the schema for a specific conceptual model change. To validate these transformations, we applied them to conceptual model changes from 9 open-source software applications, comparing the output schemas from CoDEvo with the schemas that were defined in these applications.

Mapping the functional interactions at the tumor-immune checkpoint interface

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses suggest that CD86-CD70 and CD274-CD70 immunoregulatory interactions are significantly associated with IFNγ expression in uterine corpus endometrial carcinoma and basal-like breast cancer, respectively. The open-source ImogiMap software and user-friendly web application will enable future applications of ImogiMap. Such applications may guide the discovery of previously unknown tumor-immune interactions and immunotherapy targets.

A Review and Testing of Fault Tolerance Levels of Anti-Poaching Cybersecurity System

The development of anti-poaching networks and systems has created a new environment for animals in game reserves all over the world. Advanced technologies such as heat sensors, drones, and trip wires help prevent poachers from entering the property and therefore, creating a safer environment for animals to roam freely. Radio frequency identification (RFID) systems are used to track the location of animals. These networks are, however, susceptible to being hacked if not properly protected with cybersecurity tools, resulting in cyber-criminals gaining access into the network. Many attacks or threats can be executed on the RFID network due to some exposed vulnerabilities of elements within the anti-poaching network. The purpose of this paper is to explore the empirical methods of common attacks, used by cyber-criminals, to attack the anti-poaching network, and whether these methods used are effective in identifying weaknesses within the network. This will be executed by creating an experimental structure of the anti-poaching system with a specialised focus on the RFID elements, using quantitative research methods to produce findings. GNS3, an open-source software application that has specifically been chosen to conduct this research, is used to build the network simulation in order to analyse the weaknesses of the network. Cybersecurity protocols are implemented to protect the network and aim to protect the animals. The attacks performed, such as Flood and Scapy attacks, have shown that the anti-poaching network is vulnerable to penetration from cyber-criminals. A hypothesis test was conducted to determine whether the attacks had a significant effect on the network, by using the average ping time from specific nodes to Google. It was found that the average ping time increased by 2.0020 units, therefore stating that the elements of the network were successfully attacked. The fault tolerance test shows that the availability of the anti-poaching network is roughly 90 percent which concludes that the network is configured to deliver quality performance and handle failures, should there be any intervention. This will allow game reserves to implement and have information on a better and safer RFID system for the animals.

Towards the Development of Emotions through the Use of Augmented Reality for the Improvement of Teaching-Learning Processes

This research aims to determine how the use of Augmented Reality technology propiciates learning achievements through generate emotions in students. The metodology used for development of this research was the selection and application of ARToolKit open-source software, specialized in augmented reality implementation, after that, we implemented a 3D model on the topic “Cell Biology” developed in “Unity3D”. A Likert scale test according to main emotions is applied to a sample of 50 students selected through simple random sampling from a total population of 100 students. The sample is divided into two groups, 25 students for the experimental group and 25 students for the control group. In experimental group, Augmented Reality will be used during three learning sessions. In control group Augmented Reality is not used. In both cases the Likert scale test will be applied after each learning session. At the end of the three learning sessions, a competency-based evaluation is applied according to selected criteria. The results show that 80% of the 25 students in the experimental group improved their academic performance with respect to the control group, which maintained a standard average academic performance of 50%. In conclusion, we can say that the use of Augmented Reality technology in the development of sessions in teaching-learning process, generate emotions in students who are enable to improve their learnings.

Parcel Manager: A parcel reshaping model incorporating design rules of residential development

AbstractParcels are the smallest units of land usually considered for urban development purposes. Analyses at the parcel level allow taking into account the administrative and physical environment of buildings with accuracy (roads, surrounding buildings, local design rules for building construction). In this article, we propose a free and open source software application, namely Parcel Manager, whose aims are twofold: (1) to assess the effects of different parcel reshaping rules and planning principles on the location, the number, and the shape of reshaped parcels; and (2) to provide a basis to assess the potential for new building construction. To this end, Parcel Manager simulates a large variety of parcel reshaping processes, with or without the joint creation of new roads, and produces realistic parcel layouts that represent either infill urban developments, edge expansions, or leapfrog developments. It can be used to determine if the densification of built parcels is feasible or not, regarding planning and design rules as well as the current urban fabric. The current version of Parcel Manager only concerns the reshaping of parcels dedicated to the construction of residential buildings but not other types of buildings.

Meta-analysis using Python: a hands-on tutorial

BackgroundMeta-analysis is a central method for quality evidence generation. In particular, meta-analysis is gaining speedy momentum in the growing world of quantitative information. There are several software applications to process and output expected results. Open-source software applications generating such results are receiving more attention. This paper uses Python’s capabilities to provide applicable instruction to perform a meta-analysis.MethodsWe used the PythonMeta package with several modifications to perform the meta-analysis on an open-access dataset from Cochrane. The analyses were complemented by employing Python’s zEpid package capable of creating forest plots. Also, we developed Python scripts for contour-enhanced funnel plots to assess funnel plots asymmetry. Finally, we ran the analyses in R and STATA to check the cross-validity of the results.ResultsA stepwise instruction on installing the software and packages and performing meta-analysis was provided. We shared the Python codes for meta-analysts to follow and generate the standard outputs. Our results were similar to those yielded by R and STATA.ConclusionWe successfully produced standard meta-analytic outputs using Python. This programming language has several flexibilities to improve the meta-analysis results even further.

MCCL: an open-source software application for Monte Carlo simulations of radiative transport.

.The Monte Carlo Command Line application (MCCL) is an open-source software package that provides Monte Carlo simulations of radiative transport through heterogeneous turbid media. MCCL is available on GitHub through our virtualphotonics.org website, is actively supported, and carries extensive documentation. Here, we describe the main technical capabilities, the overall software architecture, and the operational details of MCCL.