Effect of microwave energy on dehydration of celery leaves

Celery leaves were dried in a microwave oven to determine the effects of microwave output power on drying rate, specific energy consumption, drying efficiency, leaves surface area and the color of dried product.  Five different microwave output powers ranging from 180 to 900 W were used in the drying experiments.  As the drying progressed, the loss of moisture caused a decrease in absorbing microwave power and resulted in a fall in the drying rate.  Rising microwave power could reduce the rate of energy efficiency from 45.0% to 11.4% and growth of specific energy consumption from 5.3 to 18.7 MJ kg-1 water.  Significant differences (p<0.01) were observed between the color’s variables of leaf in five microwave powers, but changing of color in microwave drying were less than oven drying

The evolution of the commercialization of Knowledge with New Approach of Referenced Publication Years Spectroscopy (RPYS)

The purpose of this study was to identify the most important historical works written in the field of commercialization of knowledge using Referenced Publication Years Spectroscopy (RPYS). Initial data were obtained from the Web of Science (WoS) database to investigate the historical roots of published works in the field of commercialization of knowledge. Then, the main roots of this filed, the amount of received citations, and influential works were identified using RPYS software. Next, with the help of the yearcr software, the extent of the effects of the works outside of the range of peaks were also introduced. The period under investigation is the publication in the years 1900-2015. by searching published works in the time period of 1900-2015, 1550 records related to commercialization of knowledge were retrieved. To exactly investigate the effects of this field, the timeframe was divided into five periods (four 25-year periods and one 15-year period) to allow peaks with a small number of citations in the early years. The total number of citations up to the time of the present research was 39817, which resulted in the emergence of five peaks in the years 1934, 1962, 1973, 1998, and 2003

Co-Concept Analysis in Bioinformatics Field by Yewno Based on Experts’ Viewpoints

In this paper, the opinions of bioinformatics experts were sought to examine the knowledge semantic maps. The research question was whether the mapping of bioinformatics field articles could contribute to the reflection of knowledge map in this field; can knowledge within articles be demonstrated through a knowledge map? The research type was applied and analytical. Data collection was performed in two ways. First, the data were collected from scientific databases by using semantic search software and drawing knowledge maps by the software. Second, Delphi technique was used in two stages in order to obtain the opinion of experts regarding these knowledge semantic maps and co-concepts in bioinformatics field. In this method, first, the co-concepts map of the articles exported by Yewno and the knowledge semantics map were presented to the experts to get their viewpoints. By implementing the Delphi approach, the opinions of experts in examining the application of knowledge semantic maps resulted in the phonological analysis of articles in this field. The analysis results demonstrated that the knowledge map of bioinformatics studies dynamically developed over time. The continuous conduction flow of scientific studies in this field brought continuous changes to the knowledge of this field

Developing a Prediction Model for Author Collaboration in Bioinformatics Research Using Graph Mining Techniques and Big Data Applications

Nowadays, scientific collaboration has dramatically increased due to web-based technologies, advanced communication systems, and information and scientific databases. The present study aims to provide a predictive model for author collaborations in bioinformatics research output using graph mining techniques and big data applications. The study is applied-developmental research adopting a mixed-method approach, i.e., a mix of quantitative and qualitative measures. The research population consisted of all bioinformatics research documents indexed in PubMed (n=699160). The correlations of bioinformatics articles were examined in terms of weight and strength based on article sections including title, abstract, keywords, journal title, and author affiliation using graph mining techniques and big data applications. Eventually, the prediction model of author collaboration in bioinformatics research was developed using the abovementioned tools and expert-assigned weights. The calculations and data analysis were carried out using Expert Choice, Excel, Spark, and Scala, and Python programming languages in a big data server. Accordingly, the research was conducted in three phases: 1) identifying and weighting the factors contributing to authors’ similarity measurement; 2) implementing co-authorship prediction model; and 3) integrating the first and second phases (i.e., integrating the weights obtained in the previous phases). The results showed that journal title, citation, article title, author affiliation, keywords, and abstract scored 0.374, 0.374, 0.091, 0.075, 0.055, and 0.031. Moreover, the journal title achieved the highest score in the model for the co-author recommender system. As the data in bibliometric information networks is static, it was proved remarkably effective to use content-based features for similarity measures. So that the recommender system can offer the most suitable collaboration suggestions. It is expected that the model works efficiently in other databases and provides suitable recommendations for author collaborations in other subject areas. By integrating expert opinion and systemic weights, the model can help alleviate the current information overload and facilitate collaborator lookup by authors.https://dorl.net/dor/20.1001.1.20088302.2021.19.2.1.

The Scientific Information Exchange General Model at Digital Library Context: Internet of Things

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model. Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is consist of 15 experts in “Internet of Things” and “digital library” domains. The Data gathering procedure is by applying a semi-structured interview. Appropriate software is applied for the analysis. Results: The findings showed that the 9 main classes of “End user”, “librarian”, “Microcomputer”, “Digital library server”, “Automated information services”, “Physical resources”, “Virtual resources”, “Information resources on the digital library server (virtual object)”, and “Security” in general model of scientific information exchange are very contributive. In general, 27 sub-classes and 38 attributes are identified for the main classes for this purpose. In this model, how the classes communicate and interact with one another is illustrated to justify this theme. Conclusion: Here it is deduced that focusing on data protection at two levels of user and server in the main class of security is very important. Focusing on information resources metadata in the entity class, and device to device communication in this model is of essence as well. This proposed model is contributive in information networking in Internet of things-based library systems in providing better services to users. Research value: This model has potential in offering a basic proposal as a startup for automated library services

The Scientific Information Exchange General Model at Digital Library Context: Internet of Things

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model. Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is consist of 15 experts in “Internet of Things” and “digital library” domains. The Data gathering procedure is by applying a semi-structured interview. Appropriate software is applied for the analysis. Results: The findings showed that the 9 main classes of “End user”, “librarian”, “Microcomputer”, “Digital library server”, “Automated information services”, “Physical resources”, “Virtual resources”, “Information resources on the digital library server (virtual object)”, and “Security” in general model of scientific information exchange are very contributive. In general, 27 sub-classes and 38 attributes are identified for the main classes for this purpose. In this model, how the classes communicate and interact with one another is illustrated to justify this theme. Conclusion: Here it is deduced that focusing on data protection at two levels of user and server in the main class of security is very important. Focusing on information resources metadata in the entity class, and device to device communication in this model is of essence as well. This proposed model is contributive in information networking in Internet of things-based library systems in providing better services to users. Research value: This model has potential in offering a basic proposal as a startup for automated library services

Age as moderated influence on the link of spiritual and emotional intelligence with mental health in high school students

This study examined whether, spiritual intelligence (SI) and emotional intelligence (EI) can be considered as predictor for mental health. The present investigation was also to test the moderating effects of age on the relationship of SI and EI with mental health among high school students. The participants in the study were 247 High school students (124 male and 123 female) in the age range of 14-17 years old, at the Gorgan City, north of Iran. Three valid and reliable instruments were used to assess SI, EI and mental health. Descriptive statistics, multiple and moderated regression analysis were used to analyses the data. The result demonstrated that mental health can be influences by SI and EI. In addition, the moderated effect of age on the relationship of SI and EI with mental health was not found

Designing a model to measure information intelligence based on the Indices and measures

Measuring information intelligence is especially important in information societies. The present study aimed to identify indices and measures effective and design a model for measuring information intelligence. The research used a mixed method to achieve objectives. Data collection tools included the study of scientific literature and interviews. The research population included related published literature related to scientific theories, information science experts, and psychology experts. Based on the research findings, 14 indices and 97 measures were identified as effective for measuring information intelligence in two dimensions of management and information retrieval. After weighing and prioritizing the indices, finally, a model is presented for measuring information intelligence. From the findings, it is concluded that in the information society, officials should first determine their information strategies and then address the strategic goals of the information society. One of these strategic goals can be to increase the level of information intelligence of individuals, organizations, and society. To do this, effective indices must be identified for measuring and strategies to increase the level of information intelligence of the target community. It is suggested that this be one of the priorities of an information society