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The purpose of this paper is to present weighted residual method (WRM) for evaluating damping ratio of unreinforced glued‐laminated (glulam) wood beams and also reinforced glulam beams with E‐glass reinforced epoxy polymer (GRP) plates.

In this method, created error from the regression curve to the peak points of experimental displacement values is minimized. Several weight functions such as Galerkin weight function, Petrov‐Galerkin weight functions, and least square weight function are used for minimizing this error and results from these methods are compared to the existing methods as; logarithmic decrement analysis (LDA), Hilbert transform analysis (HTA), moving block analysis (MBA), and half power bandwidth (HPB).

Because WRM tries to minimize the error function provided from differences between theoretical and experimental fitted curves, comparison among these methods indicate that proposed procedure is useful for any range of damping ratios and it gives better values in comparison with the other methods. Due to the initial conditions and weight function used in Galerkin weighted residual method, damping ratio values obtained from this method have different values from the other weighted residual methods. Among the existing methods, HPB method could not predict damping ratio of the glulam beams accurately.

This paper is a high quality research paper that presents weighted residual method (WRM) for evaluating damping ratio of unreinforced glued‐laminated (glulam) wood beams and also reinforced glulam beams with E‐glass reinforced epoxy polymer (GRP) plates. In this paper, LDA, HTA, MBA, and HPB methods are used and an analytical investigation of damping ratios of glulam beams unreinforced and reinforced with GRP plates is proposed by using weighted residual method (WRM). Although there is a simplifier assumption in some of existing methods, proposed method shows the damping ratio can be calculated without any requirement to simplifier assumption.

This study aims to examine the research productivity of Pakistan Agricultural Research Council’s (PARC’s) researchers published during 2001–2020 by using scientometric indicators. The study explored the growth and collaborative trends along with authorship and institutional collaborative patterns at the national and international levels.

The study was conducted in four phases. Firstly, a search strategy was designed to retrieve reliable data sets. During the second phase, data from PARC research was retrieved from Scopus and Web of Science (WoS). In the third phase, the data were combined, and duplications were removed. Finally, the data were analysed using RStudio and VOSviewer.

The study identified 2,868 research publications from 16 communication channels spanning over the period of 2001–2020. The growth rate varied during the study period and the year 2020 was the most productive year of the organization. Most of the research was produced in multi-authorship and five authors were dominant. Pakistan Journal of Botany was the most preferred and cited source. Moreover, PARC research collaboration with Pakistani researchers was more than their international counterparts.

Like other research, this research has some limitations. For example, this research is based on secondary data extracted from WoS and Scopus databases, world-renowned online academic. However, researchers should keep in mind while interpreting the results of this study. Secondly, the research publications published by PARC researchers during 2001–2020 were considered. Finally, this research considered English language literature only.

The study’s key theoretical contribution is its strategy for merging WoS and Scopus in RStudio, while its findings could assist agriculture research stakeholders in identifying new areas of research, awards, promotions and identification of research gaps.

To the best of the author’s knowledge, this study is the first to use scientometric indicators to evaluate PARC’s research productivity. This detailed analysis provides a deeper understanding of PARC’s contribution to agriculture research and its potential implications.