scholarly journals BIO-STATISTICS TECHNIQUES

2021 ◽  
Author(s):  
Dr.Gurusharan Kaur ◽  
Dr. Rajinder Kaur ◽  
Dr. Namrata Tripathi
Keyword(s):  
Data Analysis ◽  
Environmental Science ◽  
Life Science ◽  
Life Sciences ◽  
Complex World ◽  
Basic Principles ◽  
Science Field ◽  
Present Complex ◽  
Research Problems ◽  
Available Information

An Introduction has been designed to serve as a text for students studying science subjects such as biotechnology, micro-biology,Pharmacy and environmental science. In recent years, biostatistics has been used widely for solving research problems in life sciences. As with most tools, biostatistics is not of much use unless the user understands its application and purpose. In order to perform efficiently in the present complex world, a researcher in the life science field ought to know enough about the basic principles of data analysis and has to be certain that all available information is used effectively to solve a given problem.

scholarly journals Review of Emotional Intelligence: A Preliminary Map Across Latin America

2019 ◽  
Vol 34 (7) ◽  
pp. 1271-1271
Author(s):  
H Patino-Carvajal ◽  
L Tibiriçá ◽  
Y Garcia ◽  
A Maresco ◽  
I Tourgeman
Keyword(s):  
Emotional Intelligence ◽  
Data Analysis ◽  
Latin American ◽  
Life Science ◽  
Life Sciences ◽  
Inclusion Criteria ◽  
Related Subject ◽  
The Mean ◽  
Latin American Countries ◽  
Total Life

Abstract Objective The purpose of this study was to investigate the prevalence of Emotional Intelligence (EI) research among 19 Latin American countries. Participants and Method Respective to each country, Total Life Science publications and Psychology publications were gathered from “UNESCO Science Report Towards 2030.” Population and GDP statistics pertaining to each country were derived from CIA Factbook. Mean education and percentage of GDP allocated for education were gathered from UNESCO Institute for Statistics. The databases SciELO and Redalyc were used to exhume the number of published Emotional Intelligence articles. The term “inteligencia emocional” was used. Findings were filtered to meet inclusion criteria: peer-reviewed, published between 2008-2018, corresponding to a Psychology related subject. Duplicate articles, those that did not contain the term “inteligencia emocional” in the abstract and articles that were not listed under the Psychology category were excluded. Results Data analysis of 19 countries from 2008-2014 revealed the mean number of Emotional Intelligence published articles to be 2.65 (SD = 5.54) articles per country - with a maximum of 22 and a minimum of 0. The percent of articles featuring EI in relation to Total Psychology articles published had a mean of 7% - with Minimum of 0% and Maximum of 60%. Bolivia has the highest percentage of articles on EI (60%), whereas Colombia the highest total number of articles published (n = 41). Population was significantly correlated with Total Articles Published and Total Psychology Articles Published. Conclusions Emotional Intelligence in Latin American countries is not widely investigated. Findings revealed 12 out of 19 Latin American countries had one or more publications related to Emotional Intelligence. While population was shown to be related to the number of articles published in Life Sciences and Psychology, it did not reveal a correlation with the publication of studies regarding EI. Furthermore, education and GDP were not related to the overall publication of articles.

scholarly journals Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis

2015 ◽  
Vol 6 ◽  
Author(s):  
Afonso M. S. Duarte ◽  
Fotis E. Psomopoulos ◽  
Christophe Blanchet ◽  
Alexandre M. J. J. Bonvin ◽  
Manuel Corpas ◽  
...  
Keyword(s):  
Data Analysis ◽  
Life Science ◽  
Life Sciences ◽  
Science Data

User Evaluation of an Integrated Medical Workstation for Clinical Data Analysis

1993 ◽  
Vol 32 (05) ◽  
pp. 365-372 ◽  
Author(s):  
T. Timmeis ◽  
J. H. van Bemmel ◽  
E. M. van Mulligen
Keyword(s):  
Data Analysis ◽  
Clinical Research ◽  
Clinical Data ◽  
University Hospital ◽  
User Evaluation ◽  
Scientific Staff ◽  
Medical Institutions ◽  
Clinical Data Analysis ◽  
Research Problems ◽  
The University

AbstractResults are presented of the user evaluation of an integrated medical workstation for support of clinical research. Twenty-seven users were recruited from medical and scientific staff of the University Hospital Dijkzigt, the Faculty of Medicine of the Erasmus University Rotterdam, and from other Dutch medical institutions; and all were given a written, self-contained tutorial. Subsequently, an experiment was done in which six clinical data analysis problems had to be solved and an evaluation form was filled out. The aim of this user evaluation was to obtain insight in the benefits of integration for support of clinical data analysis for clinicians and biomedical researchers. The problems were divided into two sets, with gradually more complex problems. In the first set users were guided in a stepwise fashion to solve the problems. In the second set each stepwise problem had an open counterpart. During the evaluation, the workstation continuously recorded the user’s actions. From these results significant differences became apparent between clinicians and non-clinicians for the correctness (means 54% and 81%, respectively, p = 0.04), completeness (means 64% and 88%, respectively, p = 0.01), and number of problems solved (means 67% and 90%, respectively, p = 0.02). These differences were absent for the stepwise problems. Physicians tend to skip more problems than biomedical researchers. No statistically significant differences were found between users with and without clinical data analysis experience, for correctness (means 74% and 72%, respectively, p = 0.95), and completeness (means 82% and 79%, respectively, p = 0.40). It appeared that various clinical research problems can be solved easily with support of the workstation; the results of this experiment can be used as guidance for the development of the successor of this prototype workstation and serve as a reference for the assessment of next versions.

scholarly journals Wildfires Vegetation Recovery through Satellite Remote Sensing and Functional Data Analysis

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1305
Author(s):  
Feliu Serra-Burriel ◽  
Pedro Delicado ◽  
Fernando M. Cucchietti
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Vegetation Index ◽  
Vegetation Recovery ◽  
Functional Responses ◽  
Elapsed Time ◽  
Synthetic Controls ◽  
Available Information

In recent years, wildfires have caused havoc across the world, which are especially aggravated in certain regions due to climate change. Remote sensing has become a powerful tool for monitoring fires, as well as for measuring their effects on vegetation over the following years. We aim to explain the dynamics of wildfires’ effects on a vegetation index (previously estimated by causal inference through synthetic controls) from pre-wildfire available information (mainly proceeding from satellites). For this purpose, we use regression models from Functional Data Analysis, where wildfire effects are considered functional responses, depending on elapsed time after each wildfire, while pre-wildfire information acts as scalar covariates. Our main findings show that vegetation recovery after wildfires is a slow process, affected by many pre-wildfire conditions, among which the richness and diversity of vegetation is one of the best predictors for the recovery.

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