Numerical Evaluation of the Extended Endplate Moment Connection Subjected to Cyclic Loading

In this paper, the seismic behaviour of extended endplate moment connection is analysed using finite element method (FEM). First, an existing test setup is modelled and analysed using ANSYS computer program. The model is validated by comparing the results from the finite element with the experimental ones. Afterwards, by changing the dimensions of members of the connection, their effect on the overall seismic performance of connection is investigated. The results show that by enlarging the column depth and stiffening the connection, the seismic performance is improved and the thickness of endplate should be chosen in a way that its moment capacity is larger than the plastic moment of beam

Visualizing Hot and Emerging Topics in Biochemistry and Molecular Biology in Iran

The purpose of this descriptive research was to identify hot and emerging topics in Biochemistry and Molecular Biology in Iran and to map the intellectual structure of this field in a ten-year period. The intellectual structure of the field of Biochemistry and Molecular Biology in Iran was studied by analyzing co-occurrences of keywords and cited references. The research population of this study was all research and review papers of Iranian researchers published in journals indexed by the Web of Science database from 2008 to 2017. The collected data from Web of Science were analyzed by the CiteSpace Software in order to map the intellectual structure of this field. The results showed that the keywords such as gene expression, protein, in vitro, oxidative stress, binding, apoptosis and cell were among the hot research topics in Iran and terms such as chitosan, nanocomposite, antibacterial activity, dynamics molecules, stem cells, mesenchymal stem cells and immobilization have been indicative of the emerging topics in Iranian research in the studied time period. Increasing publications in the field of Biochemistry and Molecular Biology in Iran at the international level and its inclusion in the country's research priorities led us to conduct a scientometric study of this research area. Therefore, due to the hot and emerging topics identified in this research, such studies can be used as a road map for the country's large-scale scientific planning and policy

Current and Future Perspectives on the COVID-19 Vaccine: A Scientometric Review

This study attempted to draw the present and future perspective of the COVID-19 vaccine by identifying the most important scientists and their scientific contexts, trends of research topics, and relationships between different entities. Methods: To achieve this purpose, bibliometric and scientometric techniques were used to analyze 6288 scientific documents contributing to COVID-19 vaccines from the beginning of 2019 to 13 December 2021, indexed in the Web of Science. Results: The United States (US) had the greatest impact by publishing 2104 documents and receiving 32,958 citations. The US and the UK countries had the highest level of scientific collaborations with 192 collaborative studies. The University of Oxford and the Harvard Medical School were the most active institutions, and the University of Oxford and Emory University were the most influential institutions. Pollard AJ and Lambe T had the most publications and the highest citations and h-index. T Lambe, SC Gilbert, M Voysey, and AJ Pollard from the University of Oxford had the highest number of co-authorships. More than 19% of the research was conducted in the field of immunology. The Vaccines journal had the most publications, with 425 articles. The US Department of Health & Human Services granted the most research. In 2019, studies were focused on the topics of COVID-19 virus identification and ways to deal with it; in 2020, studies focused on the topics of COVID-19 and vaccines, whereas in 2021, they focused on the topics of COVID-19 vaccines and their effects, vaccines hesitancy, the role of healthcare workers in COVID-19, as well as discussions about these vaccines in the social media. Conclusions: Recognition of the most important actors (countries, institutes, researchers, and channels for the release of COVID-19 vaccine studies), research trends, and fields of study on the COVID-19 vaccine can be useful for researchers, countries, and policy makers in the field of science and health to make decisions and better understand these vaccines

Analyzing the legacy and scientific impact of Saeed-Ul Hassan: A Pakistani scientometrician, data scientist and winner of the Eugene Garfield Award 2017 and 2022

This study highlights the scientific legacy and impact of Dr Saeed-Ul Hassan’s research on the world of science. He was a remarkable researcher in the fields of scientometrics, altmetrics, artificial intelligence, and data science, as evidenced by the Eugene Garfield Awards he received for innovation in citation analysis in 2017 and 2022. Based on datasets retrieved from the Scopus database for the years 2009–2022, he collaborated with 157 researchers from 22 different nations and his research findings are published in reputable journals and conferences. In the last five years of his life, his scholarly publications and scientific impact significantly increased. His significant attention to Open Access publications and high levels of worldwide collaboration have greatly contributed to his impact in the world of science. The results of altmetric studies indicate that Dr SU Hassan’s scientific publications are widely accepted by researchers on Twitter and Mendeley. The majority of individuals that tweeted and read his publications were from European and American nations. His research had the greatest impact on experts in the fields of scientometrics, computer science and social sciences, according to the classification of the readers of his research articles

Analyzing the legacy and scientific impact of Saeed-Ul Hassan: a Pakistani scientometrician, data scientist and winner of the Eugene Garfield Award 2017 and 2022

This study highlights the scientific legacy and impact of Dr Saeed-Ul Hassan’s research on the world of science. He was a remarkable researcher in the fields of scientometrics, altmetrics, artificial intelligence, and data science, as evidenced by the Eugene Garfield Awards he received for innovation in citation analysis in 2017 and 2022. Based on datasets retrieved from the Scopus database for the years 2009–2022, he collaborated with 157 researchers from 22 different nations and his research findings are published in reputable journals and conferences. In the last five years of his life, his scholarly publications and scientific impact significantly increased. His significant attention to Open Access publications and high levels of worldwide collaboration have greatly contributed to his impact in the world of science. The results of altmetric studies indicate that Dr SU Hassan’s scientific publications are widely accepted by researchers on Twitter and Mendeley. The majority of individuals that tweeted and read his publications were from European and American nations. His research had the greatest impact on experts in the fields of scientometrics, computer science and social sciences, according to the classification of the readers of his research articles

From mega-events hosting to scientific leadership: A seven-decade scientometric analysis of pioneer countries

Mega-events have always been an attractive topic for sports management academics. We used scientometric software packages to look at the studies on this topic that have been added to the Web of Science database in the last 68 years. Not only did we give an overview of the background information of the researchers, the status of their collaborations, and the countries and institutions they represented, but we also pointed out active and influential publication sources on this topic. We focused on the Olympic Games and other sports mega-events like the FIFA World Cups, as well as the environmental, tourism, economic, social, political, and cultural aspects of these events. We also made a list of the countries, organizations, and scholars who have made important contributions to the field. Researchers in sports management and sporting event hosts can both use this study as a guide for their own work

New implicit method for analysis of problems in nonlinear structural dynamics

In this paper a new method is proposed for direct time integration of nonlinear structural dynamics problems. In the proposed method the order of time integration scheme is higher than the conventional Newmark’s family of methods. This method assumes second order variation of the acceleration at each time step. Two variable parameters are used to increase the stability and accuracy of the method. The result obtained from this new higher order method is compared with two implicit methods; namely the Wilson- and the Newmark’s average acceleration methods

Application of imputation methods for missing values of PM10 and O3 data: Interpolation, moving average and K-nearest neighbor methods

Background: PIn air quality studies, it is very often to have missing data due to reasons such as machine failure or human error. The approach used in dealing with such missing data can affect the results of the analysis. The main aim of this study was to review the types of missing mechanism, imputation methods, application of some of them in imputation of missing of PM10 and O3 in Tabriz, and compare their efficiency. Methods: Methods of mean, EM algorithm, regression, classification and regression tree, predictive mean matching (PMM), interpolation, moving average, and K-nearest neighbor (KNN) were used. PMM was investigated by considering the spatial and temporal dependencies in the model. Missing data were randomly simulated with 10, 20, and 30% missing values. The efficiency of methods was compared using coefficient of determination (R2), mean absolute error (MAE) and root mean square error (RMSE). Results: Based on the results for all indicators, interpolation, moving average, and KNN had the best performance, respectively. PMM did not perform well with and without spatio-temporal information. Conclusion: Given that the nature of pollution data always depends on next and previous information, methods that their computational nature is based on before and after information indicated better performance than others, so in the case of pollutant data, it is recommended to use these methods. Keywords: Air pollution, Algorithms, Environmental pollutants, Spatio-temporal analysis, Human

Numerical Evaluation of the Extended Endplate Moment Connection Subjected to Cyclic Loading

In this paper, the seismic behaviour of extended endplate moment connection is analysed using finite element method (FEM). First, an existing test setup is modelled and analysed using ANSYS computer program. The model is validated by comparing the results from the finite element with the experimental ones. Afterwards, by changing the dimensions of members of the connection, their effect on the overall seismic performance of connection is investigated. The results show that by enlarging the column depth and stiffening the connection, the seismic performance is improved and the thickness of endplate should be chosen in a way that its moment capacity is larger than the plastic moment of beam