Software Tools Research Articles

Gene signatures for cancer research: A 25-year retrospective and future avenues.

Over the past two decades, extensive studies, particularly in cancer analysis through large datasets like The Cancer Genome Atlas (TCGA), have aimed at improving patient therapies and precision medicine. However, limited overlap and inconsistencies among gene signatures across different cohorts pose challenges. The dynamic nature of the transcriptome, encompassing diverse RNA species and functional complexities at gene and isoform levels, introduces intricacies, and current gene signatures face reproducibility issues due to the unique transcriptomic landscape of each patient. In this context, discrepancies arising from diverse sequencing technologies, data analysis algorithms, and software tools further hinder consistency. While careful experimental design, analytical strategies, and standardized protocols could enhance reproducibility, future prospects lie in multiomics data integration, machine learning techniques, open science practices, and collaborative efforts. Standardized metrics, quality control measures, and advancements in single-cell RNA-seq will contribute to unbiased gene signature identification. In this perspective article, we outline some thoughts and insights addressing challenges, standardized practices, and advanced methodologies enhancing the reliability of gene signatures in disease transcriptomic research.

Brain morphometry and chronic inflammation in Bangladeshi children growing up in extreme poverty

Abstract Over three hundred million children live in environments of extreme poverty, and the biological and psychosocial hazards endemic to these environments often expose these children to infection, disease, and inflammatory responses. Chronic inflammation in early childhood has been associated with diminished cognitive outcomes, and despite this established relationship, the mechanisms explaining how inflammation affects brain development are not well known. Importantly, the prevalence of chronic inflammation in areas of extreme poverty raises the possibility that it may also serve as a mechanism explaining the known relationship between low socioeconomic status (SES) and altered brain development. To examine these potential pathways, seventy-nine children growing up in an extremely poor, urban area of Bangladesh underwent MRI scanning at 6 years of age. Structural brain images were submitted to Mindboggle software, a Docker-compliant and high-reproducibility tool for regional estimations of volume, surface area, cortical thickness, sulcal depth, and mean curvature. C-reactive protein was assayed at eight time points between infancy and 5 years of age, and the frequency with which children had elevated concentrations of inflammatory marker represented the measure of chronic inflammation. Childhood SES was measured with maternal education and income-to-needs (i.e., monthly household income divided by the number of household members). Chronic inflammation predicted volume in bilateral basal ganglia structures and mediated the link between maternal education and bilateral putamen volumes. These findings suggest that chronic inflammation is associated with brain morphometry in the basal ganglia, predominantly the putamen, and further offers inflammation as a potential mechanism linking SES to brain development.

Exploring the Antidiabetic Potential of Salvia officinalis Using Network Pharmacology, Molecular Docking and ADME/Drug-Likeness Predictions.

A combination of network pharmacology, molecular docking and ADME/drug-likeness predictions was employed to explore the potential of Salvia officinalis compounds to interact with key targets involved in the pathogenesis of T2DM. These were predicted using the SwissTargetPrediction, Similarity Ensemble Approach and BindingDB databases. Networks were constructed using the STRING online tool and Cytoscape (v.3.9.1) software. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis and molecular docking were performed using DAVID, SHINEGO 0.77 and MOE suite, respectively. ADME/drug-likeness parameters were computed using SwissADME and Molsoft L.L.C. The top-ranking targets were CTNNB1, JUN, ESR1, RELA, NR3C1, CREB1, PPARG, PTGS2, CYP3A4, MMP9, UGT2B7, CYP2C19, SLCO1B1, AR, CYP19A1, PARP1, CYP1A2, CYP1B1, HSD17B1, and GSK3B. Apigenin, caffeic acid, oleanolic acid, rosmarinic acid, hispidulin, and salvianolic acid B showed the highest degree of connections in the compound-target network. Gene enrichment analysis identified pathways involved in insulin resistance, adherens junctions, metabolic processes, IL-17, TNF-α, cAMP, relaxin, and AGE-RAGE in diabetic complications. Rosmarinic acid, caffeic acid, and salvianolic acid B showed the most promising interactions with PTGS2, DPP4, AMY1A, PTB1B, PPARG, GSK3B and RELA. Overall, this study enhances understanding of the antidiabetic activity of S. officinalis and provides further insights for future drug discovery purposes.

Real-Time Simulator for Dynamic Systems on FPGA

This work presents the development of an embedded platform using Field Programmable Gate Arrays (FPGAs) for real-time simulation of dynamic systems in industrial plants. The platform, Real-Time Simulator for Dynamic Systems in FPGA (RTSDS-FPGA), is designed for industrial and academic applications. In industrial contexts, the RTSDS-FPGA facilitates the optimization and tuning of embedded control algorithms, while in academia, it supports research on new embedded solutions in automation and control. It is also an educational tool for undergraduate and postgraduate students developing embedded control system projects. Additionally, the simulator accelerates the simulation of slow dynamic systems, significantly reducing overall simulation time. Experimental results demonstrate the platform’s capability to perform real-time simulations effectively, validating its accuracy and performance through comparative analyses with established software tools such as Matlab/Simulink.

Met4DX: A Unified and Versatile Data Processing Tool for Multidimensional Untargeted Metabolomics Data.

Liquid chromatography-mass spectrometry (LC-MS) is a powerful tool in untargeted metabolomics, enabling the high-sensitivity and high-specificity characterization of metabolites. The integration of ion mobility (IM) with LC-MS, known as LC-IM-MS, enhances the analytical depth, facilitating more comprehensive metabolite profiling. However, the complexity of data generated by these technologies presents significant challenges in data processing. Addressing these challenges, we developed Met4DX, a unified and versatile software tool for processing both 3D and 4D untargeted metabolomics data. Met4DX incorporates a new MS1-oriented peak detection approach coupled with our bottom-up assembly algorithm, enabling highly sensitive and comprehensive peak detection in untargeted metabolomics data. Additionally, Met4DX employs a uniform quantification strategy to enhance the precision of peak integration across different samples. The software provides a user-friendly interface that simplifies data processing with default parameter sets, consolidating peak detection, alignment, quantification, and other procedures into a single streamlined workflow. Together, Met4DX offers a comprehensive solution for multidimensional metabolomics data processing, transforming raw data from diverse MS instruments into a final feature table containing quantification and identification results. We postulate Met4DX facilitates metabolite discovery in biological samples by deciphering the complex untargeted metabolomics data. Met4DX is freely available on the Internet (https://met4dx.zhulab.cn/).

GVAF: generalized, flexible filtering software for annotated variant files.

In the rapidly advancing field of genomics, many tools have been developed to interpret genetic variants using next-generation sequencing (NGS) data. However, these tools often produce annotated variant files in different formats, which require specific software or programming skills to filter and analyze. To provide a filtering tool that can be used with diverse variant annotation tools without requiring specific software or programming skills. We developed Germline Variant Annotation and Filtering (GVAF), a command-line software tool that can handle annotated variant files in any table-shaped format. GVAF offers powerful filtering operations without the need for additional software or programming expertise. Built on the Java framework and bash scripts, it provides extensive features, including flexible filtering rules, recognition of genotype-related fields from variant call format (VCF) files, and customizable result generation. GVAF also integrates easily into existing data analysis pipelines. Compared to other tools, GVAF offers a broader range of functionalities, making it more flexible and intuitive for managing annotated variant files. This GVAF software and online manual is publicly available at https://www.sysbiolab.org/gvaf for academic users and is designed to streamline the variant interpretation process, aiding researchers in producing meaningful results.

Algorithms and software for processing images of the structure of metallic materials for the purpose of determining creep characteristics

The paper contains a description of the approach, algorithms, and software tool for image analysis of deformed material structures. The developed approach is based on the analysis of the microstructure of the material to identify important factors that affect high-temperature deformation during creep in a heat-resistant nickel-based alloy, namely, the dimensions of the channels and their orientation. The developed software tool uses algorithms for converting images into binary black and white using the Otsu method. The intensity of the gradient at each point of the image is visualized using the Sobel operator. Fragment boundaries are determined using the Canny edge detector. Straight line segments are found using the Hough transformation. The software tool is implemented in the Python programming language using the OpenCV library. The main components are described and a flow chart of the program is provided. With the use of the developed software, the transformation of the known experimentally obtained images of the structures of the specimens from heat-resistant nickel-based alloy CMSX-4 deformed at a temperature of 1273K and in a wide range of stresses at different time moments was performed. The results of the analysis of the dimensions of the g-phase channels in the alloy using quantitative evaluation of transformed binary images are discussed. The found characteristics were matched to the value of the creep strain rate, which was determined by calculation based on known experimental data. The possibility of determining the transition from the secondary creep to the stage of avalanche-like growth of strains and hidden damage is shown. For the considered example, the location of the channels in the representative image was determined. A technique for correcting creep curves with the involvement of material structure image processing data is proposed.

Environmental impacts and BIM: a Portuguese heritage case study

PurposeThis paper aims to compare the possible environmental impacts of different rehabilitation solutions proposed to a case study of a Portuguese vernacular building, bearing in mind the need to search for less impactful practices in accordance with global agendas and, simultaneously, the importance of preserving heritage assets.Design/methodology/approachThe two proposed solutions differ from each other in the selection of materials, varying from the exclusive use of conventional contemporary materials to the use of locally sourced and natural-based materials, considering the Portuguese and local scenario. Results obtained from Life Cycle Assessment procedures are the basis of comparison, which were developed using a Building Information Model (BIM)-integrated analytical plugin.FindingsProducing Heritage Building Information Model (HBIM) models was essential to the analysis, and therefore is a vital part of the used methodology; nevertheless, the modelling of heritage buildings itself plays an important part in preserving heritage assets once it provides precise documenting and managing tools. The results depict variation in values for different indicators in both cases, whose interpretation might need further development to get to deeper conclusions. It has been found that the software tools are still not well adapted to analyse heritage or historic buildings, and therefore adaptations had to take place to overcome these limitations.Originality/valueThe study distinguishes itself by involving the production of HBIM models and the use of BIM-integrated Life Cycle Assessment plugins as well as its analyses, to validate this approach.

БІЛІМ БЕРУ ЖҮЙЕСІНДЕ ГЕЙМИФИКАЦИЯ ҚҰРАЛДАРЫН ҚОЛДАНУДЫҢ МҮМКІНДІКТЕРІН ТАЛДАУ

In the modern information educational environment, there is a growing interest in the use of computer games to improve the quality of education, which determines the relevance of the proposed study for the analysis of software with the possibility of gamification of the educational process in the context of the requirements of the state, society and education. The research methodology is the study of information sources of psychological, pedagogical, methodological and technical orientation, the analysis of computer educational games of foreign and domestic authors. The article considers the need for gamification of the educational process, the principles of gamification, its impact on student motivation and participation, as well as the main aspects of the optimal implementation of game elements in training. Modern software resources and platforms offering gamification in the educational process of personal development are analyzed. All software tools with the possibility of gamification of training were divided into groups: gaming platforms, educational quests, learning management services and game development sites. Particular attention is paid to methods for evaluating the effectiveness of gamified programs and platforms, which will allow creating the best didactic tasks and recommendations for teachers. Gamification can increase student motivation and their participation in various educational tasks. Intrinsic and extrinsic motivation have a special impact on students' cognitive abilities regarding learning outcomes and improve overall academic performance. Motivation, which is an important means of achieving learning goals, motivates students according to their interests. Since students perceive information differently, they can choose their activities according to their learning preferences. According to the research topic, the positive situation of gamified learning is analyzed and the relevance of digital gamification in education is determined.

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ В ОБРАЗОВАНИИ

The article is devoted to the problem of using robots in the educational process in the training of specialists. The article describes training robots based on the Robot Operating System, i.e. based on a set of software libraries and tools that help create applications for robots. Robot Integration with ROS (Robot Operating System) is the process of combining the hardware and software components of a robot with the ROS infrastructure. This allows the robot to interact with other devices and systems, as well as use a variety of ready-made tools and libraries available within the ecosystem. Robot Integration with ROS (Robot Operating System) is the process of combining the hardware and software components of a robot with the ROS infrastructure. This allows the robot to interact with other devices and systems, as well as use a variety of ready-made tools and libraries available within the ecosystem. Project Development: Using ROS, students can develop their own robotics projects, ranging from simple mobile robots for indoor navigation to complex manipulators for performing tasks in industry. Project Development: Using ROS, students can develop their own robotics projects, ranging from simple mobile robots for indoor navigation to complex manipulators for performing tasks in industry.

Effect of resveratrol supplementation on metabolic risk markers and anthropometric parameters in individuals with obesity or overweight: A systematic review and meta-analysis of randomized controlled trials

BackgroundObesity, a progressively widespread disease with a multifaceted etiology, affects nearly 800 million people worldwide. Recent trials suggest that resveratrol, a polyphenolic compound, can be effective for metabolic risk markers and anthropometric parameters in Individuals with Obesity or Overweight. However, a comprehensive analysis is necessary to consolidate these results. ObjectivesTo evaluate the impact of 4-week resveratrol supplementation on metabolic risk markers and anthropometric parameters in individuals with obesity or overweight. MethodsA comprehensive search was executed across PubMed, Cochrane Library, Scopus, Google Scholar, and clinicaltrials.gov, yielding 43 studies after the omission of 20 duplicates. RevMan 5.4 software was used to statistically analyze randomized controlled studies to gauge the impact of resveratrol on the said outcomes in Individuals with Obesity or Overweight. Quality of bias and potential publication bias were measured using the Cochrane Risk of Bias tool and CMA4 software, respectively. Certainty of the evidence was appraised using GRADEpro software. Data was quantified as the standardized mean difference (SMD) and 95 % confidence intervals (CI). ResultsThe meta-analysis included 5 trials with 419 participants, evaluating the effect of intervention. Resveratrol showed no significant impact on triglycerides (SMD = 0.11, 95%CI [-0.14, 0.35], P = 0.39, I2 = 0 %), total cholesterol (SMD = 0.04, 95%CI [-0.26, 0.33], P = 0.82, I2 = 0 %), or HbA1c (SMD = 0.00, 95%CI [-0.99, 1.00], P = 0.99, I2 = 80 %). Similarly, no significant effect was observed for insulin levels (SMD = −0.00, 95%CI [-0.25, 0.24], P = 0.97, I2 = 0 %), AST (SMD = 0.15, 95%CI [-0.35, 0.65], P = 0.55, I2 = 0 %), or ALT (SMD = −0.03, 95%CI [-0.46, 0.39], P = 0.98, I2 = 0 %). Additionally, resveratrol had no significant effect on BMI (MD = 0.21, 95%CI [-0.970, 1.39], P = 0.70, I2 = 0 %). ConclusionsOur results tagged with p-value>0.05 are an evidence-based indication that resveratrol supplementation does not lead to significant improvements in metabolic or anthropometric parameters. This suggests that resveratrol may not be an effective standalone intervention for managing obesity-related outcomes. Therefore, future research should be redirected to evaluating its potential effects on other health metrics to elucidate its efficacy and therapeutic potential better.

Kallisto, bustools and kb-python for quantifying bulk, single-cell and single-nucleus RNA-seq.

The term 'RNA-seq' refers to a collection of assays based on sequencing experiments that involve quantifying RNA species from bulk tissue, single cells or single nuclei. The kallisto, bustools and kb-python programs are free, open-source software tools for performing this analysis that together can produce gene expression quantification from raw sequencing reads. The quantifications can be individualized for multiple cells, multiple samples or both. Additionally, these tools allow gene expression values to be classified as originating from nascent RNA species or mature RNA species, making this workflow amenable to both cell-based and nucleus-based assays. This protocol describes in detail how to use kallisto and bustools in conjunction with a wrapper, kb-python, to preprocess RNA-seq data. Execution of this protocol requires basic familiarity with a command line environment. With this protocol, quantification of a moderately sized RNA-seq dataset can be completed within minutes.

Modular Microgrid Technology with a Single Development Environment Per Life Cycle

The life cycle of a microgrid covers all the stages from idea to implementation, through exploitation until the end of its life, with a lifespan of around 25 years. Covering them usually requires several software tools, which can make the integration of results from different stages difficult and may imply costs being hard to estimate from the beginning of a project. This paper proposes a unified platform composed of four modules developed in MATLAB 2022b, designed to assist all the processes a microgrid passes through during its lifetime. This entire platform can be used by a user with low IT knowledge, because it is completed with fill-in-the-blank alone, as a major advantage. The authors detail the architecture, functions and development of the platform, either by highlighting the novel integration of existing MATLAB tools or by developing new ones and designing new user interfaces linked with scripts based on its complex mathematical libraries. By consolidating processes into a single platform, the proposed solution enhances integration, reduces complexity and provides better cost predictability throughout the project’s duration. A proof-of-concept for this platform was presented by applying the life-cycle assessment process on a real-case study, a microgrid consisting of a photovoltaic plant, and an office building as the consumer and energy storage units. This platform has also been developed by involving students within summer internships, as a process strengthening the cooperation between industry and academia. Being an open-source application, the platform will be used within the educational process, where the students will have the possibility to add functionalities, improve the graphical representation, create new reports, etc.

The Ambiguity Box: A new tool to generate ambiguity in the lab

The Ambiguity Box is a software tool that visualizes uncertainty in laboratory experiments. It is a dynamic frame composed of squares that randomly change colours, creating an uncertain and ambiguous environment. This encourages participants to infer the probabilities of each colour. The tool contributes to the economic literature by introducing a new layer of uncertainty, overcoming limitations of traditional tools like the Bingo Blower. The Ambiguity Box is more practical as it is software-based and can be used with any electronic device. It is flexible, allowing experimenters to predetermine the number of squares of each colour, making it adaptable to various experimental designs. It is easily scalable, suitable for use in different contexts, and allows for the exploration of decision-making under ambiguity in diverse settings, dealing also with extremely low probabilities.

Determining Potential Groundwater Recharge Zones in the North Gujarat Region of Gujarat State Using Techniques of Geoinformatics and Multi-Criteria Decision Analysis

The rapid increase in population and industrialization has significantly raised the consumption of groundwater resources for domestic, agricultural, and industrial purposes. This study aims to develop groundwater recharge potential zone maps to assist in the construction of artificial recharge structures in the North Gujarat Region of Gujarat, India. An integrated approach of remote sensing (RS), geographical information system (GIS), and multi-criteria decision analysis (MCDA) were used to achieve this goal. Influencing factors of groundwater availability included geology, soil, lineament density, slope, rainfall, land use/land cover, geomorphology, and drainage density, were analyzed to delineate potential groundwater recharge zones. each influencing parameter was determined by using Saaty's Analytic Hierarchy Process (AHP) method, and sub-parameters were ranked according to the AHP scale. A weighted overlay analysis tool in ArcGIS software was employed to map the groundwater recharge potential zones in the North Gujarat region. The classified results of the recharge potential area in the study area consist of excellent (9.93%), good (27.90%), moderate (17.58%), poor (3.92%), and very poor (0.92%) These findings provide valuable insights for effectively planning and managing groundwater resource development in the region.

Efficiency and mechanistic insights of photocatalytic degradation and sterilization utilizing g-C3N4/WO3-x Z-scheme heterojunction under full-spectrum light

Designing highly efficient full-spectrum responsive Z-scheme heterojunction for wastewater decontamination and disinfection is urgently essential. Herein, a novel Z-scheme g-C3N4/WO3-x heterojunction was successfully synthesized by a facile wet impregnation method for the highly efficient photocatalytic degradation and sterilization. Benefiting from the accelerated charge separation, broadened light absorption to near infrared region, and appropriate band energy, optimized g-C3N4/WO3-x heterojunction exhibited photocatalytic degradation of 86.3 % and 97.4 % tetracycline in 2 h under visible light and full-spectrum light, respectively. Meanwhile, 6.5-log of Escherichia coli strains could also be inactivated by optimized g-C3N4/WO3-x heterojunction within 45 min and 15 min under visible light and full-spectrum light, respectively. Impressively, it also exhibited desirable anti-interference ability and satisfying photocatalytic degradation capacity with various key experimental parameters. The plausible degradation pathways of TC and the main active species involved in the photocatalysis were investigated based on liquid chromatography-mass spectrometer (LC-MS) and electron paramagnetic resonance (EPR) analysis. Mineralization process of TC was further confirmed by three-dimensional fluorescence spectra (3D EMMs). Besides, Toxicity Estimation Software Tool (T.E.S.T.) and Ecological Structure-Activity Relationships (ECOSAR) program were applied to predict the noxiousness of TC and its potential intermediates. The results suggested that the excitotoxicity of intermediates generally decreased relative to the pristine TC. Finally, we propose a plausible enhancement mechanism of photocatalytic degradation and sterilization. This work sheds a new light on the design of novel full-spectrum responsive Z-scheme heterojunction for environmental remediation.

Evaluating pedagogical approaches to enhance students’ comprehension in maritime English: The Norwegian case

This study aims to test and evaluate various pedagogical strategies that can improve students’ comprehension of Maritime English course materials and help them confidently participate in English-based assessments. A comparative research methodology was employed, focusing on integrating specific strategies and tools into the curricula of maritime programs. The study focused on the Norwegian case at NTNU in Ålesund, featuring a 3-year Shipping Management program (Bachelor’s degree) with 45-60 students. The findings from the Norwegian case demonstrate a significant improvement in students’ willingness and ability to engage in English-language assessments, highlighting the effectiveness of the pedagogical approaches implemented. The study results align with existing literature, highlighting the need for continuous innovation in pedagogical approaches to Maritime English education. By the end of the course, 72.2% of students felt comfortable taking the exam in English, compared to only 25.8% at the beginning of the semester. Weekly lectures in English with presentations were identified as the most helpful tool, followed by group work, homework, and vocabulary lists. The use of digital interaction and software tools received a high score – 8.0 out of 10.0. The significant improvement in students’ confidence in English, along with their strong overall ratings of teaching tools, demonstrates the effectiveness of these methods in overcoming initial language barriers. Further recommendations include combining traditional teaching methods with modern digital tools to enhance learning outcomes. By focusing on student-centered approaches and integrating both traditional techniques and technological tools, institutions can foster the development of a more proficient maritime workforce.

Life cycle assessment and generative design: development of a national LCA tool for exterior walls

PurposeThe promotion of sustainable design is demanded globally. The life cycle assessment (LCA) proved its reliability in this mission, but the difficulty and time required to apply it discouraged designers. This research aims to integrate LCA into the building design process through a software tool, taking advantage of generative design features. This will facilitate decision-making by architects and construction professionals.Design/methodology/approachThe study develops the EGY-LCA (http://egy-lca.com/). This prototype tool suggests exterior wall design alternatives for residential buildings in Egypt, using the environmental impact indicators of LCA data and other criteria related to national codes, materials, construction methods and required thermal resistance. Within a generative design process, the algorithm tests every possible wall method with materials and thickness combinations for each layer in compliance with inputs. The paper begins by explaining the tool’s working method. Afterward, different sets of inputs are examined and the values of the resultant environmental impacts of several suggested wall solutions are statistically analyzed. The application demonstrates the importance of the generative design tool. Proposing several solutions based on a set of inputs facilitates the selection of sustainable choices and allows comparisons between alternatives.FindingsThe prototype experiment confirms the research hypothesis. Unlike the available LCA tools, architects can make decisions with limited LCA experience if the data and equations are integrated into a generative design tool. The prototype proves its applicability for exterior wall alternatives.Research limitations/implicationsThe prototype is the initial step toward a whole-building LCA tool. It includes limited LCA stages and materials for the external wall. Future research is required to expand this parametric tool concept to include all the building components. The framework in Section 5 proposes a visualization.Practical implicationsThe prototype tool: EGY-LCA (http://egy-lca.com/). The value added to the design and construction sectors through the uncomplicated LCA application is fostering sustainable design, generative design tools can achieve this.Originality/valueThe novelty of this work is that it is the first initiative offering a parametric LCA tool. It promotes the application of LCA at the design stage using generative design, which contributes to sustainable development.

Comprehensive Data Evaluation Methods Used in Developing the SWGDRUG Mass Spectral Reference Library for Seized Drug Identification.

The mass spectral library of the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG) is the most comprehensive free reference database of its kind in the world. It provides reliable mass spectra for identification of seized drugs, their metabolites, and related forensic compounds when using gas chromatography/mass spectrometry (GC/MS). The SWGDRUG library (version 3.13) contains spectra for 3598 compounds. All spectra are evaluated by the Mass Spectrometry Data Center (MSDC) at the National Institute of Standards and Technology (NIST). Over the past few years, new evaluation methods aided by improved software have been developed. First, all chemical information, such as chemical structure and name, is confirmed. Second, the product ions in each spectrum are verified to match the compound structure using the NIST MS Interpreter software tool. Subsequently, the mass spectra are compared to the same or similar compounds across six different mass spectral reference libraries using three distinct library search methods. Additionally, the NIST Artificial Intelligence Retention Indices (AIRI) software is used to help confirm the corresponding compounds of spectra, especially for those without molecular ions. Low-quality and incorrect spectra are rejected for inclusion in the library.

Estimating Energy Needs for Climate-Controlled Greenhouses in Syria with a Software Tool

Amid the current conditions in Syria, the study of energy consumption within plastic greenhouses emerges as a fundamental element in the agricultural economy, especially in areas subject to extreme climate variations. With many thermal power stations ceasing operation due to conflicts and the diminishing sources of energy, understanding energy consumption becomes more urgent to enhance productivity and reduce costs. Successful management of protected agriculture requires in-depth knowledge of weather dynamics and the optimal environmental conditions for crops. To implement effective management of plastic greenhouses, it is essential to recognize how climatic fluctuations affect plant growth and production throughout the various seasons. Heating systems form a significant part of the costs in constructing plastic greenhouses, and deficiencies in these systems can lead to negative impacts on quality, quantity, duration of cultivation, and production volume. Therefore, accurately calculating heating costs is crucial for reducing operational expenses. This study included the development of a computer program to determine the heating needs of plastic greenhouses, considering various factors such as the geographical location of the greenhouse, crop type, covering materials, heating system used, and land area. The results showed that Syria needs 4.56 megawatts of energy for the greenhouses, with the Tartus Governorate consuming the largest share, with energy consumption rates in Tartus, Latakia, Homs, and Damascus countryside amounting to 3.6, 0.3, 0.51, and 0.19 megawatts, respectively. The crops of tomatoes, vegetables, strawberries, and tropical plants consumed 2.2, 1.66, 2.21, and 0.244 megawatts of energy, respectively. This study is an important step towards achieving sustainable and efficient agriculture that contributes to supporting the economy and protecting the environment in Syria.