Software Tools Research Articles

A Smart Application Frame of Remote Sensing in Non-grain Production Data Governance

Abstract. This study addresses the intricate challenges encountered in the data governance process of Non-grain Production (NGP) on Arable land. This involves managing data from diverse sources, with varying accuracies and formats, and utilizing multiple specialized software tools. An object-oriented approach is adopted to encapsulate experiential knowledge related to the data and associated processing methods, thus creating an Application Knowledge Body Model (AKBM). This model acts as a conduit between users and computational resources, encompassing various types of data and their corresponding processing and analysis methods. Moreover, by employing model inference techniques to devise methods for transitioning from raw data models to target models, a foundation is laid for the accumulation, sharing, and intelligent application of expertise on data, methods, models, and knowledge.The application examples demonstrate that users can directly construct new solutions containing relevant data and associated processing methods, rather than grappling with a multitude of data files and complex specialized software when encountering novel challenges. This promotes collaborative development in data governance on geospatial big data platforms, significantly enhancing governance efficiency, improving the quality of information support in NGP cultivation management, advancing current technological capabilities, and fostering the progression of related technologies.

Technical and Enviro-economic Analysis of a 0.78 kWp PV System

Aim: To determine the technical, economic and environmental performance analysis of an installed PV backup system. Study Design: To attain this goal, analysis were performed using a freely available PVSyst 6.7.0 software tool. Economic evaluation was performed using respective present worth of individual component prices. Environmental performance comparison is made between the PV system and diesel generator when each is used as an independent backup system. Input in-situ measured data were determined, measured and keyed into the tool. Place and Duration of Study: The system is installed in an institutional building in a tropical climatic zone with coordinates 0.42 N and 35.03 E. The system was studied for a period of one year where data was collected and recorded for techno-enviroeconomic analysis. Methodology: The system consists of four PV modules rated at 0.78 KWp, charge controller and an inverter unit and battery bank, and is utilized as a power backup system to supply electricity whenever power failure occurs, which is frequent and real in Kenya. The techno-enviroeconomic performances analysis of the system were evaluated using the PVSyst software, a freely available design and analytical tool, where input data were measured and recorded at the site. Results: The performance analysis of the system showed that PV array efficiency of 13.24%, FF of 0.68, CF of 21.23%, and PR of 73.63% and generated electrical energy of 1092 kWh/year. The LCOE of PV electricity was 0.059 $/kWh, while total saving of CO2 emission in tons of CO2 was 9.0 tCO2 with LCE value of 331 gCO2/ kWh. Conclusion: Techno- enviroeconomic performance results of the studied PV system show that the system can contribute significantly to the mitigation of CO2 emission. This work also could be helpful for consumers and policy makers in the choice of renewable based or fossil based backup generation systems.

Noninvasive Atherosclerotic Phenotyping: The Next Frontier into Understanding the Pathobiology of Coronary Artery Disease.

Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.

Specific Grammatical Aspects of Translating the Iaea Regulatory Documents into the Russian Language

The article discusses some grammatical features of the IAEA safety requirements and guides in the English language and in their Russian translations. Considering that these documents make a foundation of the global nuclear safety system, and grammar is the backbone of the language and an essential constituent of the communication content, the paper is focused on the analysis of the ways of translating specific grammatical structures, which determines current importance of this study. The aim of the work is to compare typical grammatical constructions used in the texts of the Russian translations of the IAEA publications under consideration with the grammatical features of similar Rostechnadzor’s regulatory documentation. The main tasks of the authors are to compare the ways of translating English modal and passive constructions, English verbals and verbal structures into Russian and to verify the translator’s choice of a certain grammatical structure in the translations of the regulations and guidelines under consideration. Taking research tasks predetermined the choice of the following research methods: comparative analysis; linguistic and statistical analysis; contextual analysis; inductive and deductive analysis. To obtain linguistic and statistical analysis data, the authors applied such software tools as SDL Trados, Adobe Acrobat, Excel and MS Word. In order to ensure the correctness of the results, only the substantive part of the documents under consideration was analyzed.The analysis has brought to the following results: the need to comply with the regulatory requirements narrows the choice of Russian modal constructions in the translation of "should" statements used in IAEA documents. The issue of changing the regulatory requirement that prescribes to use the Russian verb "следует" has to be treated very carefully, considering the established practice of both translating the IAEA safety guides and their understanding by the target users; the translation of English passive constructions and verbals used in the IAEA safety guides gives clear preference to the use of Russian indefinite-personal structures with verbs in the active voice in the 3rd person plural; the grammatical structures used in the translation of the IAEA publications in question generally correspond to the grammatical structures used in the Rostechnadzor regulatory documents, which is predetermined by the information nature and ensures a fairly high similarity of their style.

Constructing a CeFeO3/LaFeO3/ZnIn2S4 double Z-scheme heterojunction for photocatalytic atrazine degradation under visible light irradiation

The limited light absorption range and rapid recombination of interfacial charges were deemed to be the main restriction of the photocatalysts for atrazine (ATZ) degradation, and the construction of Z-scheme heterojunction was an effective strategy. Herein, a CeFeO3/LaFeO3/ZnIn2S4 (CFO/LFO/ZIS) double Z-scheme ternary heterojunction photocatalyst was fabricated by the in-situ precipitation and hydrothermal method. The photocatalytic ATZ degradation efficiency of optimized heterojunction reached 52% within 175 min under visible light irradiation, which was 3.1, 3.7 and 1.7 times higher than that of CFO, LFO and ZIS, respectively. The enhanced photocatalytic activity was due to the excellent light capture capacity and improved photogenerated charge separation in CFO/LFO/ZIS double Z-scheme heterojunction photocatalyst. Meanwhile, some environmental factors on the influence of photocatalytic ATZ degradation performance were systematically investigated. Quenching experiments confirmed that ·OH, h+ and 1O2 were the main active species during the photocatalytic ATZ degradation process. The possible photogenerated charge separation route was proposed via the analysis of the IEF effects between CFO, LFO and ZIS. Finaly, the possible ATZ degradation pathway was deduced by LC-MS measurement and toxicity assessment of the intermediates were also evaluated by the Toxicity Estimation Software Tool (TEST). This work not only provided a potential magnetic recyclable ferrate based double Z-scheme heterojunction photocatalyst for enhancing photogenerated charge separation and light absorption, but also evaluated the intermediate toxicity and related environmental factors on the activity of photocatalyst, which was facilitating the practical application for the degradation of ATZ.

Ionic Liquid-Based Green Solvents for Extraction and Purification of Natural Plant Products

Introduction: This research paper explores the environmental sustainability of ionic liquid-based green solvents in the extraction and purification of natural plant products, with a focus on their entire life cycle. The objectives of the study were to assess the environmental impact of ionic liquid synthesis, energy consumption, water usage, emissions, recycling rates, policy effects, and stakeholder perceptions. Method: Methodologically, we conducted a comprehensive Life Cycle Assessment (LCA) that involved primary data collection through field surveys and interviews with key stakeholders in the ionic liquid production and usage industry across various regions in India. The data were analyzed using specialized LCA software tools to quantify environmental impacts. Key findings include the identification of synthesis as a major contributor to environmental impact, emphasizing the need for greener synthesis methods. Result: The study revealed the significant carbon footprint, energy consumption, and water usage during production, highlighting opportunities for improvement. Emissions data underscored the importance of emission control measures, particularly for greenhouse gases and volatile organic compounds. Recycling and reuse were identified as environmentally friendly disposal methods. Policy compliance varied among stakeholders, indicating room for stricter regulations. Stakeholder perceptions varied, with researchers having the most positive outlook. Implications of the findings extend to sustainable chemistry practices, emphasizing interdisciplinary collaboration and the importance of considering the entire life cycle of chemical processes. Conclusion: This research contributes to a deeper understanding of green solvents and provides a foundation for promoting sustainable practices in industrial processes in India and globally

Gamification improves learning: Experience in a training activity of computer programming in higher education

AbstractBackgroundEffective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with positive empirical results on computer programming formative activities and showing under what conditions gamification is effective still need to be included.ObjectivesThis study aimed to quantify the effects of gamification techniques in software tools that support computer programming learning applied to data‐structures university students. The study focused on determining whether there are differences in learning when using gamification techniques in online exercising formative activities. The effects of gamification on learning objectives with diverse complexity are studied.MethodsThe study was conducted on computer engineering university students following a pretest‐intervention‐posttest design. They were divided into control and experimental groups, where both used a bank of exercises in Moodle to support learning. The experimental group considered gamification techniques, including points, leaderboards, and badges.Results and ConclusionsGamification techniques significantly outperformed in learning gains in exercising activities without gamification. Regarding learning complexity, increasing taxonomic complexity did not negatively affect gamification learning effects.

Research on internet of things (IoT) indexed in Web of Science from 2011–2022

Academic publications have increased geometrically in the rapidly developing field of Internet of Things (IoT). Using the keywords “Internet of Things” in titles and abstracts, a large collection of scientific publications from 2011 to 2022 that were indexed in the Web of Science were examined in this study. Several software tools, including VOSviewer, ScientoPy, Biblioshiny and MS Excel, were used to analyze the data. According to the study's findings, the majority of publications in the field of IoT are written in English, and publications in this area are steadily rising. Rodrigues, Joel J. P. C. is the most prolific author. The most productive nation was found to be China, the Beijing University Posts & Telecommunication, a thriving institution. After the US and India, China has produced the greatest number of articles and received the greatest number of citations. The IEEE was found to be the most prolific publishing source, and the IEEE Internet of Things Journal was the most productive journal.

COSGAP: COntainerized Statistical Genetics Analysis Pipelines.

The collection and analysis of sensitive data in large-scale consortia for statistical genetics is hampered by multiple challenges, due to their non-shareable nature. Time-consuming issues in installing software frequently arise due to different operating systems, software dependencies, and limited internet access. For federated analysis across sites, it can be challenging to resolve different problems, including format requirements, data wrangling, setting up analysis on high-performance computing (HPC) facilities, etc. Easier, more standardized, automated protocols and pipelines can be solutions to overcome these issues. We have developed one such solution for statistical genetic data analysis using software container technologies. This solution, named COSGAP: "COntainerized Statistical Genetics Analysis Pipelines," consists of already established software tools placed into Singularity containers, alongside corresponding code and instructions on how to perform statistical genetic analyses, such as genome-wide association studies, polygenic scoring, LD score regression, Gaussian Mixture Models, and gene-set analysis. Using provided helper scripts written in Python, users can obtain auto-generated scripts to conduct the desired analysis either on HPC facilities or on a personal computer. COSGAP is actively being applied by users from different countries and projects to conduct genetic data analyses without spending much effort on software installation, converting data formats, and other technical requirements. COSGAP is freely available on GitHub (https://github.com/comorment/containers) under the GPLv3 license.

Lifetime assessment of deep-sea manned cabin with PMMA pressure-resistant hull prior to micro-cracks

Fully-transparent cabin type, utilized in manned submersibles, is typically constructed using viscoelastic PMMA (polymethyl methacrylate) material. Accurate fatigue life assessment of manned cabin is of paramount importance to ensure structural safety. In this study, a calculation process for evaluating the fatigue life of PMMA manned cabins based on a continuum damage mechanics model combined with the viscoelastic constitutive relationship of the PMMA material in response to the absence of related specification is proposed. Fatigue tests of PMMA material are performed for determination of damage evolution model parameters and the calculation process is validated by the fatigue test data. Tailored subroutines are then developed by using ABAQUS software tool, respectively for structural analysis of a typical manned cabin with PMMA pressure-resistant hull, openings, hatches and penetration plates and simulating trapezoidal loading history acting on manned cabin. Subroutine coupling is accordingly employed to conduct parametric analysis on fatigue crack initiation life of the fully-transparent manned cabin with consideration of different outside pressure level and operation time and valuable results are obtained for identifying key areas of concern. This study intends to contribute to further cabins safety enhancement, as well as to design optimization and fatigue analysis of underwater structures involving PMMA materials.

New Scientific Field for Modelling Complex Dynamical Systems: The Cybernetics Artificial Intelligence (CAI)

Artificial Intelligence (AI) has been considered a revolutionary and world-changing science, although it is still a young field and has a long way to go before it can be established as a viable theory. Every day, new knowledge is created at an unthinkable speed, and the Big Data Driven World is already upon us. AI has developed a wide range of theories and software tools that have shown remarkable success in addressing difficult and challenging societal problems. However, the field also faces many challenges and drawbacks that have led some people to view AI with skepticism. One of the main challenges facing AI is the difference between correlation and causation, which plays an important role in AI studies. Additionally, although the term Cybernetics should be a part of AI, it was ignored for many years in AI studies. To address these issues, the Cybernetic Artificial Intelligence (CAI) field has been proposed and analyzed here for the first time. Despite the optimism and enthusiasm surrounding AI, its future may turn out to be a “catastrophic Winter” for the whole world, depending on who controls its development. The only hope for the survival of the planet lies in the quick development of Cybernetic Artificial Intelligence and the Wise Anthropocentric Revolution. The text proposes specific solutions for achieving these two goals. Furthermore, the importance of differentiating between professional/personal ethics and eternal values is highlighted, and their importance in future AI applications is emphasized for solving challenging societal problems. Ultimately, the future of AI heavily depends on accepting certain ethical values.

Role of N6-methyladenosine-related lncRnas in pseudoexfoliation glaucoma

ABSTRACT To explore the role of lncRNA m6A methylation modification in aqueous humour (AH) of patients with pseudoexfoliation glaucoma (PXG). Patients with open-angle PXG under surgery from June 2021 to December 2021 were selected. Age- and gender-matched patients with age-related cataract (ARC) were chosen as control. Patients underwent detailed ophthalmic examinations. 0.05–0.1 ml AH were extracted during surgery for MeRIP-Seq and RNA-Seq. Joint analysis was used to screen lncRNAs with differential m6A methylation modification and expression. Online software tools were used to draw lncRNA-miRNA-mRNA network (ceRNA). Expression of lncRNAs and mRNAs was confirmed using quantitative real-time PCR. A total of 4151 lncRNAs and 4386 associated m6A methylation modified peaks were identified in the PXG group. Similarly, 2490 lncRNAs and 2595 associated m6A methylation modified peaks were detected in the control. Compared to the ARC group, the PXG group had 234 hypermethylated and 402 hypomethylated m6A peaks, with statistically significant differences (| Fold Change (FC) |≥2, p < 0.05). Bioinformatic analysis revealed that these differentially methylated lncRNA enriched in extracellular matrix formation, tight adhesion, TGF- β signalling pathway, AMPK signalling pathway, and MAPK signalling pathway. Joint analysis identified 10 lncRNAs with differential m6A methylation and expression simultaneously. Among them, the expression of ENST000000485383 and ROCK1 were confirmed downregulated in the PXG group by RT-qPCR. m6A methylation modification may affect the expression of lncRNA and participate in the pathogenesis of PXG through the ceRNA network. ENST000000485383-hsa miR592-ROCK1 May be a potential target pathway for further investigation in PXG m6A methylation.

Comparative Analysis of Weather Forecasting Using LSTM, BiLSTM, and CLSTM Networks

Weather prediction plays vital role in the evaluation of various processes and phenomenon for the betterment of society. Weather forecasting depends on many parameters hence, it’s a multivariable prediction problem. Behavior of data involved in the prediction are in majority of time stochastics hence, conventional mathematical approaches are failed to predict accurate data. Classical computational methods fail in predicting chaotic data due to its limitation to have know-how about behavior of data. Artificial Intelligence and Data Processing techniques is appealing investigators due to its efficiency to predict data based on its learning capability, without any know-how about the behavior of data. In this paper, Artificial Intelligence based approach LSTM, BiLSTM, and CLSTM are used to predict time series weather data prediction. Data considered are Pressure, Humidity, Temperature, and Maximum wind speed as input data. Neural Network based approaches are used to predict Average wind speed based on above inputs. The performance of above Artificial based approaches is compared to predict time series Average wind speed. MATLAB is used as software tool to implement Artificial Intelligence approaches. It has been observed that CLSTM algorithm outperformed other two algorithms LSTM and BiLSTM algorithm.

Sustainable-Driven Renovation of Existing Residential Buildings in China: A Systematic Exploration Based on Review and Solution Approaches

Under the backdrop of China’s national strategy to achieve carbon neutrality by 2060, efforts are underway across governmental, corporate, societal, and individual sectors to actively explore energy-saving renovations in existing buildings. Given that residential buildings constitute a significant proportion of the total energy consumption throughout the lifecycle of buildings in China, sustainable renovation of residential structures can contribute significantly to implementing China’s carbon emission reduction policies. While there exists a plethora of technological means in the market aimed at improving the energy performance of residential buildings, there still needs to be a more systematic discussion on the framework for sustainable renovation of existing Chinese residential buildings, with knowledge dissemination still needing to be more cohesive. In this context, this paper provides a comprehensive review of the field, utilizing bibliometric methods. Through a systematic review of selected peer-reviewed literature from the Web of Science and Scopus databases, the study focuses on the sustainable renovation of existing Chinese residential buildings, categorizing the process into three main stages: sustainable renovation, building performance simulation and suitability assessment. The paper also reviews the research methods adopted by previous researchers in the renovation, simulation and assessment stages, considering various optimization algorithms, variables, objectives, and software tools. Subsequently, the paper synthesizes a research framework comprising these three stages combined for different research objectives, aiming to assist policymakers, designers, and researchers in gaining a comprehensive understanding of the implementation status of sustainable renovation in existing Chinese residential buildings, identifying barriers to implementation, and formulating more efficient renovation policies and strategies for the future.

Regulatory landscape enrichment analysis (RLEA): a computational toolkit for non-coding variant enrichment and cell type prioritization

BackgroundAs genomic studies continue to implicate non-coding sequences in disease, testing the roles of these variants requires insights into the cell type(s) in which they are likely to be mediating their effects. Prior methods for associating non-coding variants with cell types have involved approaches using linkage disequilibrium or ontological associations, incurring significant processing requirements. GaiaAssociation is a freely available, open-source software that enables thousands of genomic loci implicated in a phenotype to be tested for enrichment at regulatory loci of multiple cell types in minutes, permitting insights into the cell type(s) mediating the studied phenotype.ResultsIn this work, we present Regulatory Landscape Enrichment Analysis (RLEA) by GaiaAssociation and demonstrate its capability to test the enrichment of 12,133 variants across the cis-regulatory regions of 44 cell types. This analysis was completed in 134.0 ± 2.3 s, highlighting the efficient processing provided by GaiaAssociation. The intuitive interface requires only four inputs, offers a collection of customizable functions, and visualizes variant enrichment in cell-type regulatory regions through a heatmap matrix. GaiaAssociation is available on PyPi for download as a command line tool or Python package and the source code can also be installed from GitHub at https://github.com/GreallyLab/gaiaAssociation.ConclusionsGaiaAssociation is a novel package that provides an intuitive and efficient resource to understand the enrichment of non-coding variants across the cis-regulatory regions of different cells, empowering studies seeking to identify disease-mediating cell types.

PHYLOGENETIC ANALYSIS OF TWELVE BULGARIAN SEQUENCES BASED ON PARTIAL OPEN READING FRAME 2 GENOME FRAGMENT OF HEPATITIS E VIRUS

Background: Hepatitis E virus (HEV) causes both acute and chronic liver inflammation. HEV is transmitted through the fecal-oral mechanism and infects both animals and humans. The virus belongs to the Hepeviridae family and its genome is a single stranded RNA molecule. Thanks to molecular sequencing methods different genotypes and subgenotypes have been established. The aim of the present study was to identify and characterize Bulgarian HEV sequences by applying Sanger sequencing technique for a genome fragment in Open Reading Frame 2 (ORF2 region). Material and methods: Twelve retrospective samples from patients with serologically confirmed HEV infection (anti-HEV IgM and IgG positive) were sequenced by Sanger sequencing. Sequencing data were analysed by BioEdit, MEGA11 and NCBI Genbank software tools. Results: The results revealed that all isolates assign to species Paslahepevirus balayani. Phylogenetic analysis showed that HEV isolates were characterized with considerable genetic diversity. The sequences were sub-clustered into the following subgenotypes: HEV-3e, 3m, 3f and 3c. Conclusion: We successfully applied the Sanger method for hepatitis E virus RNA sequencing. The established heterogeneity of subgenotypes requires further study in order to determine the circulation of all possible subgenotypes of HEV in the country.

Population analysis using GIS software tools A case study of Chengdu

Population analysis using GIS software tools A case study of Chengdu

BeST-Graft viewer, a new system to improve the bone allograft–recipient matching process

Introduction:Tissue establishments are responsible for processing, testing, preserving, storing, and distributing allografts from donors to be transplanted into recipients. In some situations, a matching process is required to determine the allograft that best fits the recipient. Allograft morphology is a key consideration for the matching process. The manual procedures applied to obtain these parameters make the process error-prone. Material and Methods:A new system to manage bone allograft–recipient matching for tissue establishments is proposed. The system requires bone allografts to be digitalized and the resulting images to be stored in a DICOM file. The system provides functionalities to: (i) manage DICOM files (registered in the PACs) from both allografts and recipients; (ii) reconstruct 3D models from DICOM images; (iii) explore 3D models using 2D, 3D, and multiplanar reconstructions; (iv) take allograft and recipient measurements; and (v) visualize and interact with recipient and allograft data simultaneously. The system has been installed in the Barcelona Tissue Bank (Banc de Sang i Teixits), which has digitalized the bone allografts to test the system. Results:A use case with a femur is presented to test all the viewer functionalities. In addition, the recipient–allograft workflow is evaluated to show the steps of the procedure where the viewer can be used. Conclusions:The bone allograft–recipient matching procedure can be optimized using software tools with functionalities to visualize, interact, and take measurements.

In-Depth Analysis of the Selection of PBPK Modeling Tools: Bibliometric and Social Network Analysis of the Open Systems Pharmacology Community.

Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network.

PATHOMIC FUSION: CANCER DIAGNOSIS AND PROGNOSIS INTEGRATION

PATHOMIC FUSION: CANCER DIAGNOSIS AND PROGNOSIS INTEGRATION