scholarly journals Analysis of polish community on streaming platform twitch.tv during COVID-19 epidemy

2021 ◽  
Vol 21 ◽  
pp. 344-348
Author(s):  
Kamil Jeżowski ◽  
Marcin Badurowicz
Keyword(s):  
R Language

The paper describes the process of analyzing the data of the Polish community on the Twitch.tv streaming platform. The research was conducted on the basis of three issues. Separate graphs have been generated for each of the questions. The code was written in R language. Conclusions were drawn on the basis of the generated graphs.

FORMATION OF METASUBJECT COMPETENCIES IN THE COURSE “INFORMATION TECHNOLOGIES” BY MEANS OF THE BIG DATA PROCESSING LANGUAGE R

2019 ◽  
pp. 12-22
Author(s):  
D. M. Nazarov
Keyword(s):  
Data Processing ◽  
Information Technologies ◽  
Data Sets ◽  
Training Methods ◽  
Economic Knowledge ◽  
R Language ◽  
Currency Exchange ◽  
Business Informatics ◽  
Exchange Data ◽  
Processing Language

The article describes the training methods in the course “Information Technologies” for the future bachelors of the directions “Economics”, “Management”, “Finance”, “Business Informatics”, the development of metasubject competencies of the student while his use of tools for data processing by means of the language R. The metasubject essence of the work is to update traditional economic knowledge and skills through various presentation forms of the same data sets. As part of the laboratory work described in the article, future bachelors learn to use the basic tools of the R language and acquire specific skills and abilities in R-Studio using the example of processing currency exchange data. The description of the methods is presented in the form of the traditional Key-by-Key technology, which is widely used in teaching information technologies.

Exploring the Mechanism of Lingzhu San in Treating Febrile Seizures by Using Network Pharmacology

2020 ◽  
Vol 23 ◽  
Author(s):  
Xiao Zhou ◽  
Xiao-Fei Zhang ◽  
Dong-Yan Guo ◽  
Yan-Jun Yang ◽  
Lin Liu ◽  
...  
Keyword(s):  
Febrile Seizures ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Compounds ◽  
Potential Core ◽  
R Language ◽  
The Core ◽  
Multiple Factors ◽  
Therapeutic Mechanism

Objective: Lingzhu San (LZS) is a traditional Chinese medicine (TCM) prescription which can be effective in treating febrile seizures (FS) and has few researches on the mechanisms. In order to better guide the clinical use of LZS, we used the research ideas and methods of network pharmacology to find the potential core compounds, targets and pathways of LZS in the complex TCM system for the treatment of FS, and predict the mechanism. Materials and Methods: Databases such as BATMAN, TCMSP, TCMID, and SWISS TARGET are used to mine the active compounds and targets of LZS, and the target information of FS was obtained through GENECARDS and OMIM. Using Venny2.1.0 and Cytoscape software to locked the potential core compounds and targets of FS. The R language and ClusterProfiler software package were adopt to enrich and analyze the KEGG and GO pathways of the core targets and the biological processes and potential mechanisms of the core targets were revealed. Results: 187 active compounds and 2113 target proteins of LZS were collected. And 38 potential core compounds, 35 core targets and 775 metabolic and functional pathways were screened which involved in mediating FS. Finally, the role of the core compounds, targets and pivotal pathways of LZS regulated FS in the pathogenesis and therapeutic mechanism of FS was discussed and clarified. Conclusions: In this paper, the multi-compounds, multi-targets and multi-pathways mechanism of LZS in the treatment of FS was preliminarily revealed through the analysis of network pharmacology data, which is consistent with the principle of multi-compounds compatibility of TCM prescriptions and unified treatment of diseases from multiple angles, and it provides a new way for TCM to treat complex diseases caused by multiple factors.

Dynamic page sharing optimization for the R language

2015 ◽  
Vol 50 (2) ◽  
pp. 79-90 ◽  
Author(s):  
Helena Kotthaus ◽  
Ingo Korb ◽  
Michael Engel ◽  
Peter Marwedel
Keyword(s):  
R Language

scholarly journals Calumenin contributes to epithelial-mesenchymal transition and predicts poor survival in glioma

2021 ◽  
Vol 12 (1) ◽  
pp. 67-75
Author(s):  
Ying Yang ◽  
Jin Wang ◽  
Shihai Xu ◽  
Fei Shi ◽  
Aijun Shan
Keyword(s):  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Malignant Gliomas ◽  
Strongly Correlated ◽  
Who Grade ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis ◽  
R Language ◽  
Biological Adhesion ◽  
Tcga Dataset

Abstract Background Calumenin (CALU) has been reported to be associated with invasiveness and metastasis in some malignancies. However, in glioma, the role of CALU remains unclear. Methods Clinical and transcriptome data of 998 glioma patients, including 301 from CGGA and 697 from TCGA dataset, were included. R language was used to perform statistical analyses. Results CALU expression was significantly upregulated in more malignant gliomas, including higher grade, IDH wildtype, mesenchymal, and classical subtype. Gene Ontology analysis revealed that CALU-correlated genes were mainly enriched in cell/biological adhesion, response to wounding, and extracellular matrix/structure organization, all of which were strongly correlated with the epithelial-mesenchymal transition (EMT) phenotype. GSEA further validated the profound involvement of CALU in EMT. Subsequent GSVA suggested that CALU was particularly correlated with three EMT signaling pathways, including TGFβ, PI3K/AKT, and hypoxia pathway. Furthermore, CALU played synergistically with EMT key markers, including N-cadherin, vimentin, snail, slug, and TWIST1. Survival and Cox regression analysis showed that higher CALU predicted worse survival, and the prognostic value was independent of WHO grade and age. Conclusions CALU was correlated with more malignant phenotypes in glioma. Moreover, CALU seemed to serve as a pro-EMT molecular target and could contribute to predict prognosis independently in glioma.

scholarly journals Sparse HJ Biplot: A New Methodology via Elastic Net

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1298
Author(s):  
Mitzi Cubilla-Montilla ◽  
Ana Belén Nieto-Librero ◽  
M. Purificación Galindo-Villardón ◽  
Carlos A. Torres-Cubilla
Keyword(s):  
Multivariate Analysis ◽  
Elastic Net ◽  
Massive Datasets ◽  
New Techniques ◽  
Modern Approach ◽  
R Language ◽  
Reduced Dimensions ◽  
Analysis Technique ◽  
Practical Support ◽  
Novel Algorithm

The HJ biplot is a multivariate analysis technique that allows us to represent both individuals and variables in a space of reduced dimensions. To adapt this approach to massive datasets, it is necessary to implement new techniques that are capable of reducing the dimensionality of the data and improving interpretation. Because of this, we propose a modern approach to obtaining the HJ biplot called the elastic net HJ biplot, which applies the elastic net penalty to improve the interpretation of the results. It is a novel algorithm in the sense that it is the first attempt within the biplot family in which regularisation methods are used to obtain modified loadings to optimise the results. As a complement to the proposed method, and to give practical support to it, a package has been developed in the R language called SparseBiplots. This package fills a gap that exists in the context of the HJ biplot through penalized techniques since in addition to the elastic net, it also includes the ridge and lasso to obtain the HJ biplot. To complete the study, a practical comparison is made with the standard HJ biplot and the disjoint biplot, and some results common to these methods are analysed.

A Finding Aid for The Equity

2018 ◽  
Author(s):  
Jeff Blackadar
Keyword(s):  
Language Processing ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Large Collection ◽  
Digital History ◽  
R Language ◽  
Potential Value ◽  
Optical Character ◽  
Text Searching ◽  
Person Location

Bibliothèque et Archives Nationales du Québec digitally scanned and converted to text a large collection of newspapers to create a resource of tremendous potential value to historians. Unfortunately, the text files are difficult to search reliably due to many errors caused by the optical character recognition (OCR) text conversion process. This digital history project applied natural language processing in an R language computer program to create a new and useful index of this corpus of digitized content despite OCR related errors. The project used editions of The Equity, published in Shawville, Quebec since 1883. The program extracted the names of all the person, location and organization entities that appeared in each edition. Each of the entities was cataloged in a database and related to the edition of the newspaper it appeared in. The database was published to a public website to allow other researchers to use it. The resulting index or finding aid allows researchers to access The Equity in a different way than just full text searching. People, locations and organizations appearing in the Equity are listed on the website and each entity links to a page that lists all of the issues that entity appeared in as well as the other entities that may be related to it. Rendering the text files of each scanned newspaper into entities and indexing them in a database allows the content of the newspaper to be interacted with by entity name and type rather than just a set of large text files. Website: http://www.jeffblackadar.ca/graham_fellowship/corpus_entities_equity/

Sign in / Sign up

Export Citation Format

Share Document