Use Of Computational Tools Research Articles

Conocimientos, actitudes y disposición para el desarrollo sostenible en la universidad: Podcasts y concienciación ambiental

La investigación que da origen al presente artículo tuvo como objetivo estudiar las relaciones entre conocimiento, actitudes y disposición ambiental frente a los factores cargo y sexo de los miembros de una comunidad universitaria en Ecuador. La muestra estuvo conformada por 795 personas entre autoridades, profesorado, alumnado, personal administrativo y personal de servicios, quienes participaron en el proyecto durante el periodo 2018-2019. Los instrumentos administrados fueron: la escala de actitudes culturales hacia el desarrollo sostenible de estudiantes universitarios, el cuestionario conocimiento y actitudes hacia el calentamiento global y la escala de voluntad para mitigar los efectos del cambio climático por razones antropogénicas. El análisis estadístico de los datos colectados muestra que existen relaciones significativas entre conocimiento y actitudes ambientales con los factores cargo y sexo de los participantes; mientras que no existen relaciones significativas entre la voluntad para mitigar los efectos del cambio climático y los factores cargo y sexo. También se presenta una intervención educativa que hace uso de podcasts para fortalecer la conciencia ambiental de las personas. Los resultados permiten concluir que el uso creativo de herramientas informáticas tales como los podcasts, aportan al fortalecimiento de la conciencia ambiental en una comunidad universitaria.

Molecular dynamic mechanism(s) of inhibition of bioactive antiviral phytochemical compounds targeting cytochrome P450 3A4 and P-glycoprotein

P-glycoprotein (ABCB1) and cytochrome P450 3A4 (CYP3A4) metabolize almost all known human immunodeficiency virus' protease inhibitor drugs (PIs). Over induction of these proteins’ activities has been linked to rapid metabolism of PIs which are then pumped out of the circulatory system, eventually leading to drug-resistance in HIV-positive patients. This study aims to determine, with the use of computational tools, the inhibitory potential of four phytochemical compounds (PCs) (epigallocatechin gallate (EGCG), kaempferol-7-glucoside (K7G), luteolin (LUT) and ellagic acid (EGA)) in inhibiting the activities of these drug-metabolizing proteins. The comparative analysis of the MM/GBSA results revealed that the binding affinity (ΔGbind) of EGCG and K7G for CYP3A4 and ABCB1 are higher than LUT and EGA and fall between the ΔGbind of the inhibitors of CYP3A4 and ABCB1 (Ritonavir (strong inhibitor) and Lopinavir (moderate inhibitor)). The structural analysis (RMSD, RMSF, RoG and protein-ligand interaction plots) also confirmed that EGCG and K7G showed similar inhibitory activities with the inhibitors. The study has shown that EGCG and K7G have inhibitory activities against the two proteins and assumes they could decrease intracellular efflux of PIs, consequently increasing the optimal concentration of PIs in the systemic circulation. Communicated by Ramaswamy H. Sarma

Role of CRISPR/Cas9 in Genetic Manipulation of ROS1 and EGFR Genes using Synthego Platform

Mutations and fusions in kinase enzymes are often observed in cancer prognosis. The growth and survival of tumor cells depend on the activation of kinase enzymes which when activated unrestrained can lead to the uncontrolled division of malignant lung cells. Thus, their inhibition is viewed as a promising and effective anti-cancer therapy. ROS1 and EGFR are two tyrosine kinases that have been explored as the genes responsible for Non-Small Cell Lung Cancer (NSCLC). By interrupting the unchecked division of these genes, the development of malignant lung cancer cells can be blocked. The results show 4 of the top-line RNAs for altering the gene quality as well as the target sequences relevant to cleavage by that gRNA, 4 for each gene. We propose a genetic approach of controlling the ROS1 and EGFR genes guided by CRISPR/Cas-9 to guarantee fewer symptoms and an increasingly powerful treatment, by the use of computational tools.

Comparação de simulações dinâmicas de máquinas síncronas entre o ANATEM – CEPEL e o modelo de dois eixos

Transient stability analysis for electrical power systems is essential for the correct functioning of the system. Thus, due to reliability and efficiency, the use of computational tools has been widely used in order to assist in studies and in the search for solutions that involve stability analysis. The number of disturbances that can affect an electrical power system is very large, and the degree of seriousness of these disorders is related to the complexity of the arrangement and the control meshes. With good approximation,   the two-axis model of the synchronous machine  connected   to an infinite bus will be used,  the problem will be implemented in the Simulink tool® of MATLAB® and after the simulation will have its results compared with results obtained with ANATEM.&nbsp

A relevância dos Sistemas de Informação Geográfica (SIGs) na Educação Profissional e Tecnológica (EPT): A contribuição da Geografia na consolidação desse conhecimento

Os Sistemas de Informações Geográficas (SIGs) são produtos dos avanços tecnológicos que a sociedade produz ao longo da história humana, principalmente a partir de meados do século XX, resultados principalmente da criação dos computadores e de sua constante modernização. O objetivo desse artigo é, portanto, incentivar o uso desses sistemas informacionais como recurso pedagógico no processo de ensino e aprendizagem da Geografia sobretudo na Educação Profissional e Tecnológica (EPT). A utilização de ferramentas computacionais têm sido progressivamente importantes na solução dos problemas socioespaciais que afligem a sociedade, colaborando com o planejamento urbano e com a gestão ambiental dos recursos naturais. A Geografia é uma das ciências que melhor se apropriam desse conhecimento, principalmente no ensino dos conteúdos geográficos. Defende-se também nesse estudo o emprego dessas ferramentas tecnológicas na resolução dos problemas oriundos de planejamentos equivocados por parte dos gestores públicos. Além disso, também podem ser usadas para sugestões de melhoria do espaço geográfico. O artigo tem caráter bibliográfico trabalhando com autores que tratem da caracterização dos SIGs sob vários aspectos, como a conceituação, estrutura e utilização. Os SIGs são um conjunto de programas que podem, se usados e metodologicamente bem estruturados, contribuir com a melhoria da qualidade de ensino da Geografia principalmente na EPT.

The integrated use of in silico methods for the hepatotoxicity potential of Piper methysticum

Herbal products as supplements and therapeutic intervention have been used for centuries. However, their toxicities are not completely evaluated and the mechanisms are not clearly understood. Dried rhizome of the plant kava (Piper methysticum) is used for its anxiolytic, and sedative effects. The drug is also known for its hepatotoxicity potential. Major constituents of the plant were identified as kavalactones, alkaloids and chalcones in previous studies. Kava hepatotoxicity mechanism and the constituent that causes the toxicity have been debated for decades. In this paper, we illustrated the use of computational tools for the hepatotoxicity of kava constituents. The proposed mechanisms and major constituents that are most probably responsible for the toxicity have been scrutinized. According to the experimental and prediction results, the kava constituents play a substantial role in hepatotoxicity by some means or other via glutathione depletion, CYP inhibition, reactive metabolite formation, mitochondrial toxicity and cyclooxygenase activity. Some of the constituents, which have not been tested yet, were predicted to involve mitochondrial membrane potential, caspase-3 stimulation, and AhR activity. Since Nrf2 activation could be favorable for prevention of hepatotoxicity, we also suggest that these compounds should undergo testing given that they were predicted not to be activating Nrf2. Among the major constituents, alkaloids appear to be the least studied and the least toxic group in general. The outcomes of the study could help to appreciate the mechanisms and to prioritize the kava constituents for further testing.

Multimodal input during technology-assisted teacher instruction and English learner's learning experience

ABSTRACT The proliferation of educational technologies has had a profound impact on the dynamics of education and has raised questions regarding how the nature of teaching and learning should be conceptualized. This study explores how the use of technology mediates class interaction, shapes class discourse, and supports the English learners’ language development. This study's findings show that technology worked as a mediational tool in the classroom to influence class interactions and student learning experience. The study also draws our attention to the important role of the teacher in orchestrating multimodal interactions and providing learners with clear intentions of multiple modes and with necessary linguistic scaffolding, suggesting that teachers should be mindful of the role that social interactions play in achieving an intended pedagogical purpose with the use of computer tools.

HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy.

PURPOSEHLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures.METHODSHere we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization.RESULTSTo illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles.CONCLUSIONThese workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development.

Perception of consultants, feedlot owners, and packers regarding management and marketing decisions on feedlots: a national survey in Brazil (Part II)

Research interviews with agribusiness professionals are carried out in several countries for updating and developing technologies. This study aimed to investigate the perception of Brazilian feeders regarding management and marketing tools used in the feedlot industry. Interviews were conducted with groups: nutritionist-consultants (n = 23), feedlot owners (n = 21), and packer-owned feedlots (n = 8). Roughly 58% of the interviewees worked with two cycles of animals per year. Roughly 80% of animals on feedlots were males, with 73% of the respondents having fed only intact males and 75% of the animals were Nellore breed. Among the criteria used for pen formation, weight was the most common (75%). The use of computational tools for feedlot management (71%) and diet formulation (69%) were found to be common, although interviewees did not use any software to characterize feeder animals. In 44% of the respondent feedlots, animals that reached the desired weight and degree of finish were removed for slaughter, whereas the unfinished animals remained in the same pen. We found that a need, therefore, exists to develop efficient strategies for forming homogeneous pens upon animal entry onto feedlots, and maintaining homogenous pens upon the exit of animals for slaughter.

DMAKit: A user-friendly web platform for bringing state-of-the-art data analysis techniques to non-specific users

Tremendous advances in different areas of knowledge are producing vast volumes of data, a quantity so large that it has made necessary the development of new computational algorithms. Among the algorithms developed, we find Machine Learning models and specific data mining techniques that might be useful for all areas of knowledge. The use of computational tools for data analysis is increasingly required, given the need to extract meaningful information from such large volumes of data. However, there are no free access libraries, modules, or web services that comprise a vast array of analytical techniques in a user-friendly environment for non-specific users. Those that exist raise high usability barriers for those untrained in the field as they usually have specific installation requirements and require in-depth programming knowledge, or may result expensive. As an alternative, we have developed DMAKit, a user-friendly web platform powered by DMAKit-lib, a new library implemented in Python, which facilitates the analysis of data of different kind and origins. Our tool implements a wide array of state-of-the-art data mining and pattern recognition techniques, allowing the user to quickly implement classification, prediction or clustering models, statistical evaluation, and feature analysis of different attributes in diverse datasets without requiring any specific programming knowledge. DMAKit is especially useful for users who have large volumes of data to be analyzed but do not have the informatics, mathematical, or statistical knowledge to implement models. We expect this platform to provide a way to extract information and analyze patterns through data mining techniques for anyone interested in applying them with no specific knowledge required. Particularly, we present several cases of study in the areas of biology, biotechnology, and biomedicine, where we highlight the applicability of our tool to ease the labor of non-specialist users to apply data analysis and pattern recognition techniques. DMAKit is available for non-commercial use as an open-access library, licensed under the GNU General Public License, version GPL 3.0. The web platform is publicly available at https://pesb2.cl/dmakitWeb. Demonstrative and tutorial videos for the web platform are available in https://pesb2.cl/dmakittutorials/. Complete urls for relevant content are listed in the Data Availability section.

Use of modern information and communication technologies in the process of preparation of future bachelors of motor transport

The importance of application of modern information technologies in the educational process of training future bachelors of road transport is outlined. It has been found that the use of computer tools makes the learning process more technological and effective. The focus is on the introduction of elements of computer-aided design in the educational process.

An in-silico approach: identification of PPAR-γ agonists from seaweeds for the management of Alzheimer’s Disease

Alzheimer’s Disease is a complex progressive neurodegenerative disorder characterized by neurofibrillary tangles and senile plaques in various parts of the brain particularly cerebral cortex affecting memory and cognition. Nuclear receptors such as Peroxisome proliferator-activated receptor γ [PPAR-γ] is reported to have a role in lipid and glucose homeostasis in the brain, reduces the synthesis of Aβ (beta-amyloid plaques) and also regulates mitochondrial biogenesis and inhibit the neuro-inflammation, which contributes for the improvement in the cognitive function in AD. Hence PPAR-γ is one of the newer targets for the researchers to understand the pathology of AD and to evolve the novel strategy to retard/reverse the progression of AD. PPAR-γ agonists such as Rosiglitazone and Pioglitazone have shown promising results in AD by decreasing neuro-inflammation and restoring glucose dysmetabolism leading to a reduction in neuronal deterioration. These agonists possess poor blood-brain permeability and are poor candidates for clinical use in AD. Therefore, search, design, and development for new PPAR- γ agonists with improved BBB penetration ability are imperative. The present work deals with the use of computational tools and techniques such as molecular docking, molecular dynamics to discover PPAR-γ agonists from the unexplored Seaweed Metabolite Database and predicts it’s toxicological and physiochemical profile, thereby saving time and resources. Out of 1,110 seaweed compounds, the hit molecule BS052 displayed a strong binding affinity towards PPAR-γ, which possessed better lipid solubility indicating the potential to be considered as a PPAR-γ agonist, which may be useful in the management of AD. Communicated by Ramaswamy H. Sarma.

Use of computer tools in small and medium-sized enterprises: Statistical model for the creation of financial value in the productive sectors

This presents the use of computer tools for the evaluation of the generation of financial value of small and medium-sized enterprises in the municipality of Ocaña, department of Norte de Santander, Colombia. In this regard, since small and medium-sized enterprises are organizations that promote economic development, it became necessary, through the use of computer tools, to use a statistical model that evaluates in financial terms the value creation of the productive sectors. As a result, the research, using a descriptive and correlational methodology, established the computational tools to be used for the design of the statistical model, which will characterize the main determinants in the creation or destruction of value of the business structure by means of the variables of permanence, number of employees, and commercial activity. From the point of view of financial management, the financial structure was evaluated with the statistical model, establishing in terms of investment decisions, financing, and liquidity how these organizations are financially positioned; therefore, by means of statistical correlations, the relationship of dependence of financial management on the creation or destruction of value was determined.

Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods

The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.

Mineração de dados utilizando Damicore: estudo de caso das entrevistas dos atletas olímpicos brasileiros

The Olympic Studies Group, from the University of Sao Paulo, has been conducting research since the 2000s in the Olympic universe. One of them involves interviewing the Brazilian Olympic athletes. There is a hypothesis in the group that, through the use of computational tools, new subjects and knowledge may emerge from the analysis of these interviews. For this study, it was proposed to use the Damicore tool, precisely in the search for patterns that can indicate the paths that researchers can follow. Several tests were performed in order to determine an initial model of analysis, moving from a merely intuitive assumption to another, based on more concrete results. Patterns were detected in relation to the interviewers of some modalities, besides pointing out which modalities probably had relevant subjects, given their volume of interviews.

Propuesta didáctica para la comprensión, consolidación y aplicación de las principales técnicas de conteo en la resolución y comprobación de problemas de probabilidad

The Teaching-Learning process is complex; First, the interest, and motivation of the student is important. In addition to the above, the social and cultural context can have a positive or negative influence on learning in the area of mathematics and particularly on the notions of probability. The present work presents a didactic proposal that is supported by the use of computational tools. The objective of this proposal is to improve the understanding and fixation of concepts of counting techniques through the use of visual and descriptive forms (appropriate tables and codifications). Real-life examples are presented, so that the student can build formal definitions that allow generalizations under mathematical rigor. For the design of the teaching strategy we rely on constructivist and learning theories under didactic situations. These teaching models have great educational potential because they encourage reflection and analysis. In this way the student acquires skills in the approach, resolution, interpretation and verification of probability problems. In a second stage it is expected to experiment with the application of this proposal in the classroom. In this way, difficulties in teaching-learning processes can be identified and innovative teaching strategies can be proposed.

Using Mathcad to facilitate the design of chemical reactors involving multiple reactions

AbstractThe pedagogy of teaching chemical reaction engineering is continually advancing through the use of new computational tools and, therefore, the integration of these new tools into the Chemical Engineering degree is challenging. This paper reports an educational experience dealing with the use of Mathcad software to complement and to facilitate the design of chemical reactors involving multiple reactions. A continuous stirred‐tank reactor taking place series reactions and two reactors (continuous stirred‐tank reactor or plug flow reactor) arranged in series involving parallel reactions were presented as case studies. This experience, which was carried out with the third‐year chemical engineering students enrolled in the chemical reactors course, revealed that Mathcad facilitates the understanding of the theoretical concepts related to multiple reactions and also reduces the complexity of mathematical calculation to a minimum. Thus, the use of this computer tool allows the teacher (a) to delve deeper into more issues related to the design of chemical reactors, and (b) to consider this tool perfectly useful for other courses corresponding to the Chemical Engineering degree.

Inverse-QSPR for de novo Design: A Review.

The use of computer tools to solve chemistry-related problems has given rise to a large and increasing number of publications these last decades. This new field of science is now well recognized and labelled Chemoinformatics. Among all chemoinformatics techniques, the use of statistical based approaches for property predictions has been the subject of numerous research reflecting both new developments and many cases of applications. The so obtained predictive models relating a property to molecular features - descriptors - are gathered under the acronym QSPR, for Quantitative Structure Property Relationships. Apart from the obvious use of such models to predict property values for new compounds, their use to virtually synthesize new molecules - de novo design - is currently a high-interest subject. Inverse-QSPR (i-QSPR) methods have hence been developed to accelerate the discovery of new materials that meet a set of specifications. In the proposed manuscript, we review existing i-QSPR methodologies published in the open literature in a way to highlight developments, applications, improvements and limitations of each.

Open Data Kit: Mobile Data Collection Framework For Developing Countries

To evaluate and improve the delivery of health care services and programs; to collect and share information on agro-biodiversity; to fill the gaps in the data of artisanal or industrial fisheries, the use of computer tools of data collection is a major asset. It is now obvious that most of these tools are difficult to use in developing countries. And this is because of the complexity of use, either because they are commercial solutions or simply because these tools require a stable internet connection. This study is the result of thorough research on Open Data Kit (ODK), a suite of tools fully compatible with the context of developing countries and fully open source software. This article traces the research work done for the design, implementation, and improvement of ODK. A description of the different ODK extensions that can be found in the literature is given in addition to the reasons that explain the success of ODK in developing countries. To highlight the utility of ODK, an analysis of the areas of use of ODK has been made. This analysis concludes that ODK is mainly used to improve the intervention effectiveness of health system agents in developing countries.

Gene Tags Assessment by Comparative Genomics (GTACG): A User-Friendly Framework for Bacterial Comparative Genomics.

Genomics research has produced an exponential amount of data. However, the genetic knowledge pertaining to certain phenotypic characteristics is lacking. Also, a considerable part of these genomes have coding sequences (CDSs) with unknown functions, posing additional challenges to researchers. Phylogenetically close microorganisms share much of their CDSs, and certain phenotypes unique to a set of microorganisms may be the result of the genes found exclusively in those microorganisms. This study presents the GTACG framework, an easy-to-use tool for identifying in the subgroups of bacterial genomes whose microorganisms have common phenotypic characteristics, to find data that differentiates them from other associated genomes in a simple and fast way. The GTACG analysis is based on the formation of homologous CDS clusters from local alignments. The front-end is easy to use, and the installation packages have been developed to enable users lacking knowledge of programming languages or bioinformatics analyze high-throughput data using the tool. The validation of the GTACG framework has been carried out based on a case report involving a set of 161 genomes from the Xanthomonadaceae family, in which 19 families of orthologous proteins were found in 90% of the plant-associated genomes, allowing the identification of the proteins potentially associated with adaptation and virulence in plant tissue. The results show the potential use of GTACG in the search for new targets for molecular studies, and GTACG can be used as a research tool by biologists who lack advanced knowledge in the use of computational tools for bacterial comparative genomics.