Freeware Tools Research Articles

Assessment of macroscopically inhomogeneous fracture toughness data sets using the simplified and multimodal master curve methods

A number of large, historical fracture toughness data sets have been analyzed according to the provisions of ASTM E1921-22a, in order to compare two Master Curve methods for assessing potential macroscopic material inhomogeneity: simplified method and multimodal approach. Analyses conducted on 51 data sets, 20 of which inhomogeneous, demonstrated substantial equivalence between the two approaches, even below the current applicability limit of the multimodal method (20 data points). A revised (lower) limit might be considered for future revisions of the E1921 standard. Overall, the simplified method provides slightly more conservative assessments, while the multimodal approach is more accurate. Freeware tools are currently available for the application of both methodologies, and of ASTM E1921 in general, for the analysis of fracture toughness data obtained in the ductile-to-brittle transition regime.

Use of image processing based on freeware tools to illustrate mixing processes for educational purposes

Use of image processing based on freeware tools to illustrate mixing processes for educational purposes

Knowledge mapping and research hotspots of immunotherapy in renal cell carcinoma: A text-mining study from 2002 to 2021.

BackgroundRenal cell carcinoma (RCC) is one of the most lethal urological malignancies, and because early-stage RCC is asymptomatic, many patients present metastatic diseases at first diagnosis. With the development of immunotherapy, the treatment of RCC has entered a new stage and has made a series of progress. This study mainly outlines the knowledge map and detects the potential research hotspots by using bibliometric analysis.MethodsPublications concerning RCC immunotherapy from 2002 to 2021 in the Web of Science Core Collection were collected. Visualization and statistical analysis were mainly performed by freeware tools VOSviewer, CiteSpace, R software, and Microsoft Office Excel 2019.ResultsA total of 3,432 papers were collected in this study, and the annual number of papers and citations showed a steady growth trend. The United States is the leading country with the most high-quality publications and is also the country with the most international cooperation. The University of Texas MD Anderson Cancer Center is the most productive organization. The Journal of Clinical Oncology is the highest co-cited journal, and Brian I. Rini is both the most prolific author and the author with the largest centrality. The current research hotspots may be focused on “immune checkpoint inhibitors (ICIs),” “PD-1,” and “mammalian target of rapamycin.”ConclusionImmunotherapy has a bright future in the field of RCC treatment, among which ICIs are one of the most important research hotspots. The main future research directions of ICI-based immunotherapy may focus on combination therapy, ICI monotherapy, and the development of new predictive biomarkers.

A dataset of Oceanographic and biogeochemical anomalies in the Caribbean Sea.

This article describes six ocean datasets consistent in anomalies of biogeochemical, physical, sea wave, biological, oceanic and chemical parameters (DACS-BGC, DACS-PHY, DACS-WAVE, DACS-BIO, DACS-OCE and DACS-CHEM) in several time scales from 3-hourly to monthly frequencies, either on the sea surface, downward/upward fluxes between the ocean and the atmosphere and the water column in the Caribbean basin (Gulf of Mexico, Caribbean Sea and Atlantic Ocean) in a geographical domain from latitudes 8 degrees to 35 degrees North and from longitudes 45 degrees to 100 degrees West, obtained, from several satellites, modeling services and observational programs. The datasets were created in NetCDF format conserving their original horizontal resolutions of 1.0, 0.5, 0.26, 0.08333 and 0.04 degrees in gridded structure; only the WAVEWATCH3 dataset has a non-uniform step in latitude and longitude. This internal data structure facilitates its handling due to a wide diversity of existent freeware tools, and it is mainly intended to support researchers to understand the evolution and cycles of physical, biogeochemical, chemical, sea wave, oceanic and biological parameters linked to global climate change.

Database of oceanographic anomalies and atmospheric surface fluxes for the study of climate change in the Brazilian Northeast.

This paper presents three datasets of anomalies of oceanic physical parameters and surface atmospheric fluxes in the northeast region of Brazil, geographically limited by 42.5°W - 29.75°W / 20.5°S - 1.25°N, calculated from the SODA, TROPFLUX and GPCP datasets. The DASAF-BNE (Daily Anomalies of the Surface Atmospheric Fluxes of the Brazilian Northeast), DRA-BNE (Daily Rainfall Anomalies in the Brazilian Northeast), and MAOP-BNE (Monthly Anomalies of Oceanographic Parameters in the Brazilian Northeast) datasets are generated with 0.25° resolution bilinearly interpolating the original datasets. This database includes four files in NetCDF format, which facilitates its handling due to the diversity of freeware tools that exist, DASAF-BNE and DRA-BNE have a daily frequency, while MAOP-BNE has a monthly frequency. This database is mainly intended to research climate changes in the Brazilian Northeast.

AERODYNAMIC ANALYSIS OF THE CLARK YH AIRFOIL

The analysis of the performance of aerodynamic airfoils leads to optimized approaches regarding the pre-design of fixed and rotating lifting surfaces, with implications on the global characteristics and performances of aircraft. The 2D aerodynamics of the airfoils provides indications on the aeromechanical behavior of the selected geometric elements, which may come as constructive solutions depending on the typology of the missions and the initial requirements of the project. The article provides a scrutiny of and certain educational perspectives on the Clark YH profile analysis, using freeware tools (Javafoil, Profiles and XFLR5).

Learning Bayesian networks from demographic and health survey data

Child mortality from preventable diseases such as pneumonia and diarrhoea in low and middle-income countries remains a serious global challenge. We combine knowledge with available Demographic and Health Survey (DHS) data from India, to construct Causal Bayesian Networks (CBNs) and investigate the factors associated with childhood diarrhoea. We make use of freeware tools to learn the graphical structure of the DHS data with score-based, constraint-based, and hybrid structure learning algorithms. We investigate the effect of missing values, sample size, and knowledge-based constraints on each of the structure learning algorithms and assess their accuracy with multiple scoring functions. Weaknesses in the survey methodology and data available, as well as the variability in the CBNs generated by the different algorithms, mean that it is not possible to learn a definitive CBN from data. However, knowledge-based constraints are found to be useful in reducing the variation in the graphs produced by the different algorithms, and produce graphs which are more reflective of the likely influential relationships in the data. Furthermore, valuable insights are gained into the performance and characteristics of the structure learning algorithms. Two score-based algorithms in particular, TABU and FGES, demonstrate many desirable qualities; (a) with sufficient data, they produce a graph which is similar to the reference graph, (b) they are relatively insensitive to missing values, and (c) behave well with knowledge-based constraints. The results provide a basis for further investigation of the DHS data and for a deeper understanding of the behaviour of the structure learning algorithms when applied to real-world settings.

Management of Internet Bandwidth Implementing CoovaChilli and Free Radius

With rapid growth in popularity and use of Internet in academic institutions, the institutions are struggling to keep up with the demand. They need capability to effectively control, monitor and optimize the available bandwidth to ensure good service at optimum cost. This paper has described implementation of Coovachilli and free radius for management of internet bandwidth in academic institutions. During this research, freeware tools such as Freeradius and CoovaChilli have been used to manage Internet bandwidth on a per-user basis based on user credentials. The mechanisms have been used to control bandwidth of Wireless users. Same can be used for wired connections also. When a user tries to connect, the user is redirected to a captive portal under CoovaChilli. There the user provides login and password. Based on the credentials thus provided, CoovaChilli checks identity with the Freeradius. If authorized, the client is allowed access with the bandwidth as mentioned in the profile of the user in WISPr attributes define in Radreply table of Freeradius. When the user is not authorized, CoovaChilli sends an error message. This paper demonstrates that bandwidth can be effectively monitored, managed and optimized by using cost-effective open-source tools in the existing network scenario of the institution.

Edutainment and practice in video-based learning: enriching educational videos with interactive activities and games

Video-based learning has a long history but the transfer of educational videos to the web has given a powerful potential to this form of learning. Today, there is an abundance of independent educators, trainers, and educational organisations that use online video for educational content delivery. In most cases however, the videos that exist in educational platforms do not contain any aspects of interactivity and educational entertainment (edutainment). These are mostly non-interactive videos and in cases where there is interactivity this is mainly restricted to in-video quizzes and user annotations. The aim of this paper is to present solutions on how to develop interactive video-based learning environments using open source and freeware tools. In these solutions educational videos are enriched with knowledge testing activities, games, and hands-on practice exercises for learning software applications. The developed video-based learning environments were used and evaluated in classroom settings and some findings are reported in the paper.

Consideration about UAV command and control. Ground Control Station

In the field of UAV, information processing centers most often materialize through ground control stations (GCS) that are used in various variants from simple commercial products in the form of tablets or radio control stations for controlling the vector within the visual range at low altitudes and autonomies, or portable, fixed or self-propelled technologies for missions beyond the visual range at high altitudes and autonomies. The article wants an overview of the theoretical bases on the construction and operation of GCS and aspects of flight mission debriefing using freeware tools.

An assessment of the operational freeware management tools for multi-reservoir systems

Abstract Water resources management is one of the most challenging problems of the water sector. The complexity of this problem is mostly attributed to the dynamic nature of the natural hydrosystems, of which the inputs are characterized by stochasticity. The assessment of the impact of alternative decisions on such a system requires a probabilistic approach. It is evident that this is a very demanding task even for a single-reservoir system, not to mention multi-reservoir systems. For this reason, computer codes have been developed since the early 1970s to help with this procedure. Nowadays, these codes have evolved into decision support platforms that offer a user interface to assist the pre-processing and the post-processing. However, the majority of the available tools are commercial and require a considerable amount of money for a licence. Thankfully, a few freeware tools that are based on the simulation–optimization method and with a modern user interface exist. The objective of this study is to assess the performance of these freeware tools. The assessment is based both on an analysis of the theoretical basis and on an application of the models on a simplified representation of the Athens water supply system.

A Program Optimization Method for Embedded Software Developed Using Open Sources

Program optimization or software optimization is the process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. When developing software for embedded systems, open source libraries are usually used. An Embedded software built using a variety of open software and libraries is apt to have too many unused codes because open source libraries contain many functions and features to be used in various applications. In this paper, we describe the process of a library optimization method to reduce memory consumption for the user interface software of a set-top box product. The overall optimization process uses freeware tools developed for the Linux operating system. We devised an optimization technique to compensate for operation imperfections in the target system. The original Qt library of 19.57 MB was optimized to be 7.26 MB in program image size. In the case of the DirectFB library, 3.2 MB was reduced to 2.4 MB. The optimization process can be applied to any embedded software that are developed with open source libraries or sources.

Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence.

The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust (Austropuccinia psidii) on paperbark tea trees (Melaleuca quinquenervia) in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral image sensors, and data processing algorithms using machine learning. Imagery is acquired using a Headwall Nano-Hyperspec camera, orthorectified in Headwall SpectralView, and processed in Python programming language using eXtreme Gradient Boosting (XGBoost), Geospatial Data ion Library (GDAL), and Scikit-learn third-party libraries. In total, 11,385 samples were extracted and labelled into five classes: two classes for deterioration status and three classes for background objects. Insights reveal individual detection rates of 95% for healthy trees, 97% for deteriorated trees, and a global multiclass detection rate of 97%. The methodology is versatile to be applied to additional datasets taken with different image sensors, and the processing of large datasets with freeware tools.

Vídeos educacionais de curta duração para o ensino de Bioquímica

Vídeos educacionais de curta duração (até 5 minutos), de conteúdos distintos, estão sendo criados no Laboratório de Biocalorimetria (LaBioCal) do IBqM/UFRJ e depositados no canal “Tempo de Ciência” do YouTube (https://www.youtube.com/playlist?list=PLJO7zS-49NtHJXZr1zpunle40HxKb3BEz). Os vídeos estão sendo criados com a ferramenta PowToon com áudio previamente gravado pelo programa Audacity, ambos na versão livre. Os vídeos são utilizados, atualmente, pelos alunos do curso de Licenciatura em Ciências Biológicas do CEDERJ e estão disponíveis ao público em geral. Devido a uma atualização dos mesmos, a publicação foi refeita recentemente, levando o contador a reiniciar a contagem de visualizações. Dessa forma, os vídeos têm de cerca de 200 a 400 visualizações no momento desta inscrição. O objetivo é introduzir um tema que deve ser visualizado antes da aula teórica mas, também, permitir a visualização do mesmo após a aula, como uma forma de revisão do conteúdo. As vantagens de um vídeo de curta duração é a de permitir melhor assimilação, já que o espectador mantém sua atenção, e revisão contínua, já que o espectador tem o domínio das pausas e continuidades que ocorrem a seu tempo. A aceitação dessa ferramenta educacional pelos alunos tem sido muito grande, como observado em relatos espontâneos enviados por email. Uma avaliação formal está sendo feita por um formulário online (em andamento).

Predicting the bioconcentration factor through a conformation-independent QSPR study

The ANTARES dataset is a large collection of known and verified experimental bioconcentration factor data, involving 851 highly heterogeneous compounds from which 159 are pesticides. The BCF ANTARES data were used to derive a conformation-independent QSPR model. A large set of 27,017 molecular descriptors was explored, with the main intention of capturing the most relevant structural characteristics affecting the studied property. The structural descriptors were derived with different freeware tools, such as PaDEL, Epi Suite, CORAL, Mold2, RECON, and QuBiLs-MAS, and so it was interesting to find out the way that the different descriptor tools complemented each other in order to improve the statistical quality of the established QSPR. The best multivariable linear regression models were found with the Replacement Method variable sub-set selection technique. The proposed QSPR model improves previous reported models of the bioconcentration factor in the present dataset.

NeuronRead, an open source semi-automated tool for morphometric analysis of phase contrast and fluorescence neuronal images.

Neurons are specialized cells of the Central Nervous System whose function is intricately related to the neuritic network they develop to transmit information. Morphological evaluation of this network and other neuronal structures is required to establish relationships between neuronal morphology and function, and may allow monitoring physiological and pathophysiologic alterations. Fluorescence-based microphotographs are the most widely used in cellular bioimaging, but phase contrast (PhC) microphotographs are easier to obtain, more affordable, and do not require invasive, complicated and disruptive techniques. Despite the various freeware tools available for fluorescence-based images analysis, few exist that can tackle the more elusive and harder-to-analyze PhC images. To surpass this, an interactive semi-automated image processing workflow was developed to easily extract relevant information (e.g. total neuritic length, average cell body area) from both PhC and fluorescence neuronal images. This workflow, named 'NeuronRead', was developed in the form of an ImageJ macro. Its robustness and adaptability were tested and validated on rat cortical primary neurons under control and differentiation inhibitory conditions. Validation included a comparison to manual determinations and to a golden standard freeware tool for fluorescence image analysis. NeuronRead was subsequently applied to PhC images of neurons at distinct differentiation days and exposed or not to DAPT, a pharmacological inhibitor of the γ-secretase enzyme, which cleaves the well-known Alzheimer's amyloid precursor protein (APP) and the Notch receptor. Data obtained confirms a neuritogenic regulatory role for γ-secretase products and validates NeuronRead as a time- and cost-effective useful monitoring tool.

Sensitivity Analysis and Calibration of a Rainfall-Runoff Model with the Combined Use of EPA-SWMM and Genetic Algorithm

An integrated Visual Basic Application interface is described that allows for sensitivity analysis, calibration and routing of hydraulichydrological models. The routine consists in the combination of three freeware tools performing hydrological modelling, hydraulic modelling and calibration. With such an approach, calibration is made possible even if information about sewers geometrical features is incomplete. Model parameters involve storage coefficient, time of concentration, runoff coefficient, initial abstraction and Manning coefficient; literature formulas are considered and manipulated to obtain novel expressions and variation ranges. A sensitivity analysis with a local method is performed to obtain information about collinearity among parameters and a ranking of influence. The least important parameters are given a fixed value, and for the remaining ones calibration is performed by means of a genetic algorithm implemented in GANetXL. Single-event calibration is performed with a selection of six rainfall events, which are chosen so to avoid non-uniform rainfall distribution; results are then successfully validated with a sequence of four events.

Blood flow in cerebral arteries – automated way from Computed Tomography to ANSYS Fluent

<p style="text-align: justify;">With the constant growth of computer simulation significance in science and engi-neering, many new fields are gaining access to these powerful tools. One of these new disciplines is medicine. Human body provides many fascinating areas that could be researched from completely different angle and could gain all the benefits that computer simulation offers. For example blood flow in human arteries can be stud-ied using Computational Fluid Dynamics. Researchers of cerebrovascular disorders can get an insight view on physical phenomena of blood flow and study risk factors of embolism or cerebral aneurysm.</p><p style="text-align: justify;">Main issue in using computer simulation in medical research is the complexity and uniqueness of geometry that needs to be handled. After all, human body is one of the most sophisticated engineering systems created by nature. In this paper, a workflow for creating a numerical mesh for CFD simulation purposes is shown. Application shown in the example focus on cerebral arteries blood flow simulation. Numerical mesh is generated based on CT scan of patient’s head, using freeware tools Slicer3D and AutoIt3 as well as commercial software ANSYS Fluent Meshing 15.0.</p>

Teaching Earth Signals Analysis Using the Java-DSP Earth Systems Edition: Modern and Past Climate Change

ABSTRACT Modern data collection in the Earth Sciences has propelled the need for understanding signal processing and time-series analysis techniques. However, there is an educational disconnect in the lack of instruction of time-series analysis techniques in many Earth Science academic departments. Furthermore, there are no platform-independent freeware tools available for teaching Earth signals analysis. In order to address these issues, we developed the Java-Digital Signal Processing/Earth Systems Edition (J-DSP/ESE), a platform-independent software tool that can be integrated with the Earth Science university curriculum for signal processing and analysis instruction. This tool has an intuitive block-based programming environment, and students do not need be familiar with any programming language to use it. In order to demonstrate the utility of this software in an instructional environment, we developed three tutorials related to basic signal processing, and signal analysis of modern and past climate change. The tutorials use published data to examine the relationship between 20th century atmospheric CO2 and global temperature, and the relationship between ocean temperature and solar radiation over the past 300,000 y. The tutorials were administered in two workshops with different communities of students in Earth Science and electrical engineering. Our technical assessments show that the students were able to comprehend basic signal processing and analysis of climate signals using J-DSP/ESE. In the subjective assessments, a vast majority of students stated that the software was easy to learn and use, and that it significantly improved their understanding of climate change.

Proteomics made more accessible

MS-based proteomics is a bioinformatic-intensive field. Additionally, the instruments and instrument-related and analytic software are expensive. Some free Internet-based proteomics tools have gained wide usage, but there have not been any single bioinformatic framework that in an easy and intuitive way guided the user through the whole process from analyses to submission. Together, these factors may have limited the expansion of proteomics analyses, and also the secondary use (reanalyses) of proteomic data. Vaudel et al. (Proteomics 2014, 14, 1001-1005) are now describing their Compomics framework that guides the user through all the main steps, from the database generation, via the analyses and validation, and through the submission process to PRIDE, a proteomic data bank. Vaudel et al. partly base the framework on tools that they have developed themselves, and partly they are integrating other freeware tools into the workflow. One of the most interesting aspects with the Compomics framework is the possibility of extending MS-based proteomics outside the MS laboratory itself. With the Compomics framework, any laboratory can handle large amounts of proteomic data, thereby facilitating collaboration and in-depth data analyses. The described software also opens the potential for any laboratory to reanalyze data deposited in PRIDE.