انسان با تهذیب نفس و علم حضوری می تواند حضور علت هستی بخش را درک نماید؛ لذا در فلسفه اسلامی خداوند حاضر علی الاطلاق است. اما پرسش از چرایی عدم انکشاف حضور الهی به طور گسترده برای بشر از طریق روش هایی مانند تجربه دینی ذهن فیلسوفان دین را به خود مشغول داشته است و تقریرات شلنبرگ در استدلال به اختفای الهی برای الحاد، در این میان نقش محوری دارد. عمده پاسخ ها به علت اختفای الهی از منظر وجودی، فلسفی، عرفانی و کلامی است. اما در پژوهش حاضر به روش تحلیل محتوایی سعی شده است رویکردهای انسانی تراویس دامزدی مورد ارزیابی قرار گیرد. وی با بیان مواردی مانند شاخص انزجار آسیب دیده، شاخص انزجار محدودیت وجودی، شاخص ترس و امید و شاخص از خود بیگانگی سعی در طرح دلایل اختفای الهی نموده است. در این مقاله عمده نقدهای این رویکرد انسانی مواردی چون نسبی گرایی و استقرای ناقص، بی نیاز نبودن از رویکردهای کلامی مانند تدبیر، حکمت و لطف الهی، ارائه تصویری منفعل از خداوند و عدم توجه به بعد اجتماعی دین، دانسته شده است.

Purpose: The main objective of this research is to rank Iranian-indexed journals in the Journal Citation Reports (JCR) 2020 based on the Journal Citation Index (JCI). Additionally, the study aims to investigate the significant correlation between the JCI and other metrics such as Eigenfactor, Article Influence Score (AIS), Quartile, and Journal Impact Factor (JIF). Among them, forty Iranian journals are indexed in three main citation indexes and have received Journal Impact Factor (JIF) and Quartile rankings for the first time, which also reported their Journal Citation Index (JCI). However, the ranking of these Iranian journals based on the new JCI is not specified. More importantly, the study does not examine the significant correlation between JCI and other indices such as Eigenfactor, AIS, Quartile, and JIF. Therefore, this research aims to rank Iranian journals indexed in JCR 2020 based on the Journal Citation Indicator (JCI) and investigate the significant correlation of this index with Eigenfactor, Article Influence Score (AIS), Quartile, and Journal Impact Factor (JIF). The main focus of this research is to determine whether changes in the value of the new index (JCI) will correspond to changes in the old indices (Eigenfactor, AIS, Quartile, and JIF). Therefore, this article aims to investigate the mentioned issues and provide scientific and accurate answers. Methodology: The present research is applied and has been conducted using scientometric indices and an analytical approach. The required data for the research was extracted from JCR 2020. All Iranian journals in JCR 2020 with an Impact Factor (IF) and Quartile, totaling forty journals, formed the research population. In this article, five research questions have been posed. Iranian journals and their corresponding indices were extracted from JCR 2020. They were then ranked and reported in a table based on JCI to address the first question. To address the second to fifth research questions, which investigate the significant relationship between JCI and Eigenfactor, AIS, Quartile, and JIF, the Shapiro-Wilk test was initially used to assess the normality of the distribution of the relevant data for Eigenfactor, AIS, Quartile, and JIF. The results of the Shapiro-Wilk test indicated that the data related to Eigenfactor and AIS followed a normal distribution, while the data related to JIF did not. Therefore, to investigate the significant relationship between JCI and Eigenfactor and AIS, the Pearson correlation coefficient was used. Additionally, to study the significant relationship between JCI and JIF, Spearman's rho correlation coefficient was employed. Additionally, when examining the relationship between JCI and Quartile, it is important to note that Quartile only has four levels (Q1, Q2, Q3, and Q4). Therefore, the Kendall's tau b test was used. This test is used when the data under investigation is on an ordinal scale. Findings: "Iranian Journal of Fuzzy Systems, " "International Journal of Health Policy and Management, " and "BioImpacts" ranked first, second, and third, respectively, in JCI with scores of 65. 1, 15. 1, and 99. 0. A positive and significant correlation between JCI and Eigenfactor (R=44. 0, P<0. 006) indicates a statistical relationship. There is a positive and significant correlation between JCI and Article Influence Score (AIS) (R=73. 0, P<0. 0001), suggesting that an increase in JCI is associated with an increase in AIS. There is a negative and significant correlation between JCI and Q (R=-64. 0, P<0. 0001), implying that an increase in JCI is associated with a decrease in Q. In summary, the results suggest that JCI is positively related to Eigenfactor and AIS but negatively related to Q. These findings can have implications for evaluating the impact and influence of academic journals. Conclusion: The JCI can be a complementary indicator with the JIF. Many indicators have been introduced to cover JIF's weaknesses, but JIF is still the most famous indicator. The passage of time will show that the JCI will also suffer the fate of the previous indicators or, as a new and unique indicator, will remove the authority and acceptance of the JIF after half a century.

This study was conducted to investigate the health status of the Haraz River ecosystem as one of the most important protected rivers in Iran. Sampling was done in 2020 and 2021 from 14 stations along the river. Identification of macrobenthos and calculation of Z index was performed along with Quality status, determination of toxicity, measurement of PAHs and statistical analysis of data. Based on the results, IRWQIsc was decreasing towards the downstream, except for the branches. IRWQIst fluctuated and generally decreased from upstream to downstream. The Z index had the highest value (4) in the downstream stations. In terms of self-purification, the river was in oligosaprobe, betamzosaprobe, alphamzosaprobe and polysaprobe classes. Upstream was more favorable than downstream and the cold season was more suitable than the warm season. Maps were prepared based on saprobe, integration of self-purification, BOD and land use of the region. The results of the analysis showed the important role of human activities, especially rural and garden uses, and in the next stage, roads, in the quality of river water. From upstream to downstream, the number of polluting sources has increased and they have shown their role. The increase in the density of rural areas, gardens, and fish farms has caused an increase in BOD and Z index. Therefore, it is necessary to follow up and carry out the treatment of sewage, development of agricultural system standards and supervision of the use of underground water along with dealing with the violators in order to protect the river.

Background and Aim: In this study, in order to increase the visibility of articles in Scopus journals of Tehran University of Medical Sciences (TUMS), selective dissemination of information (SDI) service was presented and its impact on some citation indices was investigated. Materials and Methods: This is a semi-experimental study of two groups (pretest-posttest design with a control group). In this study, TUMS Scopus indexed journals (20 titles) were randomly divided into test and control groups and their citation indices were assessed. Then, the SDI services for test group journals were designed based on PubMed's Alert system and presented to the university's top researchers for one year. Finally, the citation indices of the journals of test and control groups were reassessed and compared. For data analysis, independent t-test, paired t-test and, covariance analysis were used. Results: Comparison of mean citations as well as SJR, SNIP and CiteScore indices before and after the intervention showed no significant difference between the test and control groups. But the average CiteScore in both groups after the intervention was significantly higher than the average before the intervention. Conclusion: The results showed that the provision of the aformentioned services in the time period defined in this study had no significant effect on the citation indices. However, the valuable experiences gained in this study will undoubtedly be applicable to future research as well as services to researchers, librarians, and journal managers.

The present study aimed to investigate the value of Iranian papers in chemistry in 2010 from the viewpoint of their citation quality. The citation value was calculated based on text citation frequency and text citation potential. The latter is defined based on the text citation frequency of the cited papers, divided by text citation potential of the citing papers.The research was carried out using a citation analysis method. The data were analyzed by descriptive and inferential statistics, including Spearman correlation test.955 papers referring to 517 Iranian papers were examined. These papers gave 1434 text citations to Iranian papers, of which 213 (22 percent) were self-citations. Only a minority (17.02 percent) of the Iranian papers performed higher than the expected level and the rest (82.97 percent) performed below the expected level, regarding their text citation portions. The results also indicated that citations can properly predict text citation frequencies but have no significant correlation with text citation portions.Despite the recent growth in Iran’s scientific outputs in chemistry, the citation value of the papers was revealed to be considerably low. This implies that in order to have a more objective evaluation, Iranian science system requires more qualitative indicators instead of the crude count of citations.

Background and aim: Today, the extraction of scientometric indicators has been widely used in prediction of the scientific status of researchers, organizations and countries in various national and international fields. The aim of this study was to determine the participation in the production of science and partnership pattern of researchers in Hamedan University of Medical Sciences based on the databases of Web of Science (WoS), Scopus and Google Scholar.Material and methods: This applied and scientometric study was conducted on 100 top researchers of ISI in terms of the number of articles in 2014. The number of articles, citations and h-index were extracted from WoS, Scopus and Google Scholar from 2012 to 2014. Data were analyzed using SPSS, Stata and R.Findings: The number of publications and citations has increased over three years in three databases. The correlation between the number of publications in Google Scholar and the number of citations in WoS and Scopus was weak but significant. Negative binomial regression model indicated that the number of publications would be enhanced 7% in WoS and Scopus through the increase of one article in Google Scholar. Zero-inflation negative binomial model illustrated that odds of zero of the citation number in Scopus and WoS will be 0.66 and 0.27 times with increasing one article in Google Scholar and the citation number of Scopus and WOS is increased 2% and 3% with the increase of one article in Google Scholar, respectively.Conclusion: The results show that there is a direct and strong relationship among the number of publications, citations and h-index in three databases. Negative binomial model can be used as a proper model for the number of publications and zero-inflation negative binomial model can be applied as an appropriate model for the number of citations in WoS and Scopus, too.

Purpose: Quantitative citation analysis fails to take into account different citation motivations which may be neutral, confirmative, or negational. It necessitates devising new methods or techniques to evaluate cited documents based on the attitudes of their citing articles, to increase the accuracy of the results of the quantitative approach. The challenge is believed to be partially answered by content analysis of citations, including citation opinion mining. It is based on extracting and analyzing the sentiment words occurring in citations, or citation contexts, i. e., a word window surrounding any given citation within a citing paper. However, there exist few pieces of evidence on the degree of divergence or convergence of the results of the quantitative and content-based approaches. To provide further research evidence, the present study investigated the correlation between the results of these two citation-analysis approaches. Methodology: Using a citation analysis method with the quantitative and opinion-mining approaches, this communication explored a sample consisting of 524 medical papers. Their bibliographic information and citations were extracted from PubMed and CoLil, respectively. 3663 citations were identified, of which 3639 contexts were available through CoLil. The citations were processed using the KNIME data mining platform. The opinion scores of the words were extracted from SentiWords. The citations opinions were measured in terms of the polarity and strength of the average opinion scores of their words. The data were then analyzed by Spearman Correlation. Findings: The citations were revealed to carry numerous sentiment words. They were mostly positive in their polarity, however, the number of citations with negative polarity was also considerable. The citation counts were found to be directly and strongly correlated to the absolute count of the opinionated citations. However, they were revealed to be indirectly and weakly correlated to the relative count of opinionated citations, i. e., the number of opinionated citations normalized by the total count of the citations. Furthermore, the citation counts had an insignificant correlation with the relative frequency of positive citations, while displaying significant direct relationships with negative and neutral ones. Moreover, they were indirectly associated with the average opinion scores. Conclusion: In general, the findings of this research showed that as the number of citations increases, the relative number of opinionated contexts decreases. They were dominated by a positive polarity which is in line with previous studies revealing a confirmative motivation in citation behavior. The predominance of positive opinions implied explicit and implicit confirmation motives of researchers reflected in the citing works: the citer may explicitly express her opinion about the cited article and its features, or implicitly express her approval by citing it (i. e., using algorithms, methods, tools, findings and etc. ). According to the findings, as citation counts increase, the cited papers witness a reduction in their opinionated contexts’ relative numbers, while experiencing an increase in their negative and neutral ones. Consequently, the content-based citation analysis with an opinion-mining approach may be able to adjust the results of the quantitative approach. However, this finding and its generalizability should be treated with caution. Because the sample of the current research was not selected randomly. Given the differences between disciplines and scientific communities in their citation behavior, it is necessary to replicate the research in various contexts to support the results. Moreover, in the dictionary-based opinion mining method applied in the present study, the big challenge is precisely detecting negative opinions. As in negative citations, the negative opinions of citers may be mingled with their reports of negative objective findings. In other words, the method cannot precisely distinguish these two types of opinion contexts, i. e., the negative attitudes of the citers and their narration of negative findings. Moreover, citations are of social nature. Therefore, negative citations are mostly hidden and indirect, and their lexical identification is hence quite difficult. Thus, advanced methods using, for example, machine learning algorithms, are required to detect and analyze any possible implicit and indirect negative opinions which the direct natural language method may fail to capture.