Introduction: Urban green space is one of the land uses whose distribution and dispersion throughout cities is of paramount importance and constitutes an inextricable part of city structure. Thus, city green space is a sort of urban land use covering manmade vegetation and boasting both social and ecological output. City parks should be geographically distributed in ways that are easily accessible. Moreover, along with the rapid growth of urbanization and constructions in recent decades, the appearance of the city of Mashhad, the second metropolis in Iran, has changed in such way that a dire dearth is noticeable in terms of the land use of city parks.

In order to identify the CORRELATIONs and relationships between different traits in the bread wheat, 30 genotypes were investigated as sub-factors under the split plot experiment in the completely randomized design in greenhouse and the randomized complete block design in the field with three replications under the normal irrigation and post-anthesis water stress conditions. The results of the canonical CORRELATION ANALYSIS showed that at both normal and moisture stress levels, there was a significant CORRELATION between the pair of canonical variables obtained from the phenological traits and the yield components. Under the normal conditions in the greenhouse, to increase the spike density and length, the number of days to 50% flowering can be considered as a suitable selection criterion. According to the results of canonical CORRELATION ANALYSIS, under the stressed conditions in greenhouse, to increase the spike length, the number of days to the heading, maturity and 50% of flowering were among the important and effective factors. Under the optimum irrigation conditions in the field, the number of days to maturity was considered as one of the factors influencing the seed weight per spike. The results of canonical CORRELATION ANALYSIS under the field stress conditions showed that to increase the 1000-seed weight, the number of days to maturity can be considered an appropriate selection criterion.

Introduction: Tinnitus is a common disorder with a considerable amount of distress that affects the patient`s daily life. No objective tools were approved for measuring tinnitus distress. It can be estimated only by subjective scales and questionnaires, albeit, the Electroencephalography (EEG) studies have reported some alterations regarding tinnitus distress NETWORK. This study aimed to investigate the CORRELATION between Tinnitus Handicap Inventory (THI) and the recorded EEG data. Methods: A total of 33 chronic tinnitus cases (9 females) with the mean age of 42. 67 years were recruited. Their THI scores were collected, and a 3-minute EEG recorded with eye closed at resting-state. The CORRELATION ANALYSIS was performed on THI scores and the current density in the selected Region of Interests (ROIs) concerning the distress NETWORK for the eight frequency bands. The patients grouped depending on the THI cutoff point of 56 into low and high THI groups, and then the groups were compared for source ANALYSIS and functional connectivity between ROIs using standardized low-resolution brain electromagnetic tomography. Results: A significant positive CORRELATION was seen between THI scores and the electrical activity in the Anterior Cingulate Cortex (ACC), the prefrontal cortex, and the parahippocampus for an alpha band (P<0. 05) and in the ACC for beta (P<0. 01). Source ANALYSIS showed significant differences with increased activity in the high THI group for alpha, beta and gamma bands. Functional connectivity was also elevated in the high THI group between the ROIs in alpha and beta bands. Conclusion: THI can be a useful tool for measuring tinnitus distress, and it has a high CORRELATION with EEG data.

The tourism industry is becoming one of the world's largest economical sources, and is expected to become the world's first industry by 2020. Previous studies have focused on several aspects of this industry including sociology, geography, tourism management and development, but have paid less attention to analytical and quantitative approaches. This study introduces some NETWORK ANALYSIS techniques and measures aiming at studying the structural characteristics of tourism NETWORKs. More specifically, it presents a methodology to analyze tourism destinations NETWORK. We apply the methodology to analyze mazandaran’s Tourism destination NETWORK, one of the most famous tourism areas of Iran.

This research examines the association between co-authorship NETWORK centrality (degree, closeness, betweenness, eigenvector, Bonacich flow betweenness) and productivity of Information science researchers. The research population includes all those researchers who have published at least one record in one of the twenty journals of Information Science which has an impact factor of 0.635 as a minimum from the years 1996 to 2010. By using social NETWORK analyses, this study examines information science researchers’ outputs during 1996-2011 in ISI Web of Science database. In general co-authorship NETWORK of these researchers was analyzed by UCINET6 software. Results showed that there is a significant CORRELATION between Journal Impact Factor (JIF) and all centrality measures except closeness centrality at P=0.001. Results also showed that there is a significant CORRELATION between productivity of authors and all centrality measures scores at P≥ 0.001. Also, regression reports direct relationship of degree, closeness and flow betweenness and inverse relationship of betweenness as well as Eigen vector centrality on productivity of researchers.

Purpose: This study aims to analyze the scientific cooperation NETWORK of ontology researchers using social NETWORK indicators. It also investigates the CORRELATION between centrality indicators and the productivity and efficiency of researchers in this field. Methodology: The present study is an applied research project that utilizes scientometric techniques and indicators. The social NETWORK ANALYSIS method was employed to illustrate and analyze the scientific cooperation NETWORK in the field of ontology. In order to retrieve the outputs related to the field of ontology, a search was conducted for the term "Ontolog*" in the title and subject fields of the Web of Science database from 1990 to July 2, 2021. The search strategy used is TI=(Ontolog*) OR TS=(Ontolog*). In the next step, the recovered findings were limited to research conducted in the fields of computer science, information science, and librarianship. This is because ontology is a subject that is also used in other fields such as philosophy, religious studies, biology, and so on. Despite the fact that the concept of ontology in this research is "a tool that specifies the concepts of the related field, their characteristics, and the relationships between concepts and characteristics, thereby increasing the semantic interaction between documents and sources to process complex, advanced, and text-sensitive questions. " Among the retrieved data, original articles, conference articles, review articles, and editorials with more credibility were selected. In the end, 29, 611 research articles were obtained. The retrieved records were entered into VOSviewer version 16. 6. 1 software for matrix design and visual map design. To standardize the names, Gephi software was used. The matrix designed in Gephi software was then imported, and micro-indexes of social NETWORK ANALYSIS were calculated. These measures included degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. The calculation of macro indicators for the co-authorship NETWORK in the field of ontology outputs was also performed using the UCINET software. To test the research hypotheses, SPSS software Version 24 was utilized. Due to the non-normal distribution of the data, a non-parametric test (Spearman's CORRELATION) was used to test the hypotheses. Findings: Examination of the four measures of centrality, which include degree centrality, closeness centrality, betweenness centrality, and special vector centrality, revealed that Pascal Hitzler from Kansas State University, USA,Stefano Borgo from the Italian National Research Council,Jeff Z. Pan from the University of Edinburgh, Scotland,Stefan Schulz from the Medical University of Graz, Austria,Barry Smith from the University of Buffalo, USA,Nicola Guarino from the National Research Council of Italy,Ian Horrock from the University of Oxford, England,Bernardo Cuenca Grau from the University of Oxford, England,Heiner Stuckenschmidt from the University of Mannheim, Germany,and Jerome Euzenat from the Diderot University of Paris, France are the most influential researchers in the co-authorship NETWORK in the field of ontology. The ANALYSIS of the scientific cooperation NETWORK in the field of ontology using macro indicators of social NETWORK ANALYSIS revealed that the NETWORK is not cohesive. This is evident from the density value, which is less than one, and the high clustering coefficient of the NETWORK. Of course, the flow of information in this NETWORK is fast, based on the NETWORK's diameter and average distance. Additionally, the findings revealed a significant and positive CORRELATION between centrality measures (such as degree, closeness, betweenness, and special vector centrality) and both the number of scientific productions and the number of citations. However, it is worth noting that the relationship between closeness centrality and scientific productions was found to be not significant. Conclusion: The results showed that the cooperation between researchers who know each other has led to a decrease in the diameter of the NETWORK and the average distance in the web of ontology co-authorship. As a result, the information flow in this NETWORK has intensified, overcoming the weaknesses of low density and high clustering coefficient. According to the results, when authors collaborate with colleagues they know in the field of ontology, the NETWORK diameter and average distance decrease, resulting in increased information flow in the ontology co-authorship NETWORK. This holds true even when the density and clustering coefficient are high.