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      Resistance of the fiber-derived geotextile from Typha domingensis submitted to field degradation

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          Abstract

          Geotextiles made from plant fibers creates a suitable environment for plant growth as part of soil bioengineering techniques. The faster decomposition of plant fiber geotextiles compared to synthetic ones demands the use of composites that enhance their waterproofing and extend their durability in the environment. The objective of this work was to evaluate the resistance of a geotextile made with Thypha domingensis to degradation caused by climatic variables. Tensile strength tests were conducted in the laboratory in order to evaluate the degradation of geotextiles treated with single and double layers of waterproofing resin. Based on Scanning Electron Microscopy (SEM) images, it was verified that applying double layer of waterproofing resin delays the fibers degradation up to 120 days of exposure to the effects of climatic variables other than temperature. The maximum resistance losses due to the geotextile's exposure to degradation were statistically significant for all three treatments: control-without waterproofing resin, with one layer resin, and with two layers resin. Therefore, waterproofing resin, provides a long-term protective solution for geotextiles made from cattail fibers.

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          Statistical Power Analysis for the Behavioral Sciences

          <i>Statistical Power Analysis</i> is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: <br> * a chapter covering power analysis in set correlation and multivariate methods;<br> * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and;<br> * expanded power and sample size tables for multiple regression/correlation.<br>
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            Advanced statistics: bootstrapping confidence intervals for statistics with "difficult" distributions.

            The use of confidence intervals in reporting results of research has increased dramatically and is now required or highly recommended by editors of many scientific journals. Many resources describe methods for computing confidence intervals for statistics with mathematically simple distributions. Computing confidence intervals for descriptive statistics with distributions that are difficult to represent mathematically is more challenging. The bootstrap is a computationally intensive statistical technique that allows the researcher to make inferences from data without making strong distributional assumptions about the data or the statistic being calculated. This allows the researcher to estimate confidence intervals for statistics that do not have simple sampling distributions (e.g., the median). The purposes of this article are to describe the concept of bootstrapping, to demonstrate how to estimate confidence intervals for the median and the Spearman rank correlation coefficient for non-normally-distributed data from a recent clinical study using two commonly used statistical software packages (SAS and Stata), and to discuss specific limitations of the bootstrap.
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              Soil erosion in the Anthropocene: Research needs

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                Author and article information

                Contributors
                vidal.center@academico.ufs.br
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 April 2024
                15 April 2024
                2024
                : 14
                : 8648
                Affiliations
                [1 ]Agronomy Engineering Department, Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) São Cristóvão, Sergipe Brazil
                [2 ]Graduate Program in Intellectual Property Science, Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) Avenida Marechal Rondon Jardim S/N - Rosa Elze, São Cristóvão, Sergipe 49100-000 Brazil
                [3 ]Chemical Engineering Department, Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) São Cristóvão, Sergipe Brazil
                [4 ]Graduate Program in Materials Science and Engineering (P2CEM), Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) São Cristóvão, Sergipe Brazil
                [5 ]Chemistry Department, Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) São Cristóvão, Sergipe Brazil
                [6 ]Biological Sciences Department, Universidade Federal de Sergipe-UFS, ( https://ror.org/028ka0n85) São Cristóvão, Sergipe Brazil
                Author information
                http://orcid.org/0000-0003-3575-8105
                http://orcid.org/0000-0001-8659-8557
                http://orcid.org/0000-0002-8701-0118
                http://orcid.org/0000-0002-4982-1913
                http://orcid.org/0000-0001-9425-0921
                http://orcid.org/0000-0002-5280-9763
                http://orcid.org/0000-0002-0111-1699
                Article
                56978
                10.1038/s41598-024-56978-3
                11018824
                38622156
                2be4f8bf-e8c6-4f87-a8ec-2cd8ec2d0f85
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 July 2023
                : 13 March 2024
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                tensile strength,soil bioengineering,natural fiber,ecology,natural hazards,engineering,materials science

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