In each journal, the editorial board receives many articles but more than 70% of them are rejected. This happens because there is no real correlation among the variables in these articles or the variables and perceived relations are fake, which means playing with the variables nonexistent in reality. This rejection occurs mainly as a result of the researchers' misinterpretation of the interdisciplinary studies, their having no expertise in the subject, their paying no attention to co-authorship in different disciplines, and their being fond of the statistical outputs. Furthermore, these researchers have no real acceptable and sensible idea and no valid variable, think in isolate space, have few partners, lack the necessary motivation for research, and have hesitation in delivering their paper, and so on. To conclude, the researchers must concentrate more on the recognition of the differences between aim, necessity and profit, and the importance of prioritization.

ABSTRACTDuring the last century, ports of Persian Gulf become the most important storage, refining and transportation of crude oil, oil derivation, petrochemical products and also, business activities. Nowadays, due to functional diversity between ports, the impact of port activities on the development of urban spaces will be different, and this issue leads to structural differences of port cities. The purpose of this research is to identify the key variables affecting the relations and spatial structure of port-city in Dubai as the most thriving and successful port-city in the Persian Gulf. This research is based on deductive reasoning and carried out by analysis of cross effects with secondary data (results of other prominent articles) and also primary data (questionnaire). sampling method is based on purposive sampling and Micmac software was used to analyze the data. Output of Micmac software shows the position of the instability of the system. Therefore, the position of each variables in the conceptual model can be categorized to driver, linkage, dependent, and autonomous factors. The research findings indicate 4 variables (like as “income, cost and investmnets in port-city”) can be introduced as a driver factor, 5 variables (like as “advanced multimodal transportation in the port”) can be introduced as a linkage factor, 6 variables (like as “quality of living environment and desirable city”) can be introduced as a dependent factor, 3 variables (like as “environmental protection and sustainable development of the city-port”) can be introduced as an autonomous factor. The rapid development of Dubai can be explained by the purposeful distribution of revenues from trade and tourismExtended AbstractIntroductionDuring the last century, ports of Persian Gulf become the most important storage, refining and transportation of crude oil, oil derivation, petrochemical products and also, business activities. The global increase in oil demand since the 1950s led to the creation of discovery of new oil wells and large industrial areas. With the construction of new oil or gas facilities in the port areas, increasing oil revenues contributed to the countries of the Persian Gulf region and form a new geographical relationship between ports and coastal cities which had an impact on the spatial structure and relation of them. Nowadays, due to functional diversity between ports, the impact of port activities on the development of urban spaces will be different, and this issue leads to structural differences of port cities. In the 1950s, Containerization (container loading technology) was based in some of the world's ports and created a huge transformation in the shipping industry, which had a significant impact on the development of ports. Although the ports of the Persian Gulf have made a significant contribution to the economic growth and physical development of other ports in the world, but few researches have been done on the variables and factors affecting the development of the spatial structure of the important ports of the Persian Gulf. This region, due to its unique geographical location, has always been considered as a most important corridor in the field of economic and transportation throughout history. Some of the most important energy and commercial ports in this region are: Dubai, Manama, Kuwait, Dammam, Doha, Bushehr, Bandar-Abbas and Assaluyeh. In this regard, the purpose of this research is to identify the key variables affecting the relations and spatial structure of port-city in Dubai as the most thriving and successful port-city in the Persian Gulf. MethodologyThis research is based on deductive reasoning and carried out by analysis of cross effects with secondary data (results of other prominent articles) and also primary data (questionnaire). The method used in this research is quantitative and the sampling method is based on purposive sampling. the variables affecting the spatial structure of port-city relations were identified in the form of a review of 31 prominent articles. 25 experts (who had comprehensive knowledge and information about the development process of the city-port of Dubai) participated to determine the effectiveness or influence of variables. Finally, the output of data analysis was done by the Micmac software. Results and discussionOutput of Micmac software shows the position of the variables in the diagram that it indicates their status in the system and their role in the dynamics and changes of the system. The method of distribution and dispersion of the variables in the spatial structure of port-city relations indicates the instability of the system. Therefore, based on the output of the system, the position of each variables in the conceptual model can be identified in five categories (driver, linkage, dependent, autonomous and regulatory variables). According to the results, some variables such as “the changes in the strategic positions” and “geopolitics of port-city”, “the modification of the management method” and “regional planning of the ports”, “the promotion of local governance in the relations between port-city” and “the way of national and international management of ports have been introduced as driver variables. On the other hand, five variables consist of “advanced multimodal transportation in the port” and “income, cost and investment in the port-city”, “the contrast and physical integration of the port - city space”, “the development of various industrial and production activities in the ports and their local hinterland” and “their qualities Financial and commercial policies of ports” have been introduced as linkage variables. Findings of research also shows that some variables consist of “quality of living environment and desirable city”, “quantity and quality of transit corridors (rail, road and air) to hinterland”, “construction and launching the new port (sea port or dry port)”, “terminal facilities and infrastructure and warehousing”, “conflict or convergence between the city and the port” and “increase in population growth rate and migration to the port - city” categorized as dependent variables. Three variables including “cultural and historical background of ports”, “use of cheaper energy, Less-polluted, clean and renewable energies in the city-port” and “environmental protection and sustainable development of the city-port” categorized as autonomous variables. Finally, a variable with the title of “improvement in management and information technology and development in loading, unloading and storage of commodities” have been introduced as regulatory variables. The findings of this research have a remarkable similarity with other researches carried out in the field of city-port relation and clearly emphasize the direct impact of the "investment in port-city" in the development of them. For example, Grossmann (2008) emphasized that city-port of Hamburg has become one of the largest ports in Northern Europe during the last few decades due to huge domestic and foreign investment. ConclusionThis research carried out in order to introduce and explain the key variables affecting the development of the spatial structure of the port-city of Dubai. On this basis, 21 variables have been extracted by systematic reviews of prominent articles. In the following, 25 experts were selected with the purposive sampling method. Among the 21 variables extracted, 4 variables (like as “geopolitics of port-city”) introduced as a driver factor, 5 variables (like as “advanced multimodal transportation in the port”) introduced as a linkage factor, 6 variables (like as “quality of living environment and desirable city”) introduced as a dependent factor, 3 variables (like as “environmental protection and sustainable development of the city-port”) introduced as an autonomous factor. The rapid development of Dubai can be explained by the purposeful distribution of revenues from trade and tourism. A part of these revenues has been directed towards investment in important transportation infrastructures such as airports and ports of this city. These strategies have a wide impact on improving the economic growth of the city and the development of the port in order to adapt with the global trade and advanced technologies. FundingThere is no funding support. Authors’ ContributionAuthors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none. Conflict of InterestAuthors declared no conflict of interest. Acknowledgments We are grateful to all the scientific consultants of this paper.

News reporters are a special group in the jurisprudence and hadith of Shia Islam, whose way of thinking has cast a shadow over the people and seminaries for years. The founder of this sect was Mohammad Amin Esterabadi, who, by residing in Medina and writing the book "Fawaed al-Madaniyah, " spread his beliefs in Iraq and Iran. He considered deduction and ijtihad to be "innovation" and rejected them, believing that only the apparent meaning of hadith should be adhered to and that only the infallible Imams (AS) could interpret the Quran and hadith, which is beyond the capacity of ordinary people. He also disregarded reason and consensus. His opinions were similar to Sunni Ahl al-Hadith to some extent, although he differed from them in terms of belief. The thought of Esterabadi news reporting led to more attention being paid to hadith books, but it resulted in harmful effects such as regression, sectarianism, and superficiality, which hindered rational thinking. Of course, the thought of Esterabadi news reporting was limited and restricted by the efforts of scholars, but its effects can still be seen to some extent: the emergence of modern news reporting in today's world from Egypt to Iraq, Syria, Saudi Arabia, Afghanistan, etc., and cultural news reporting among elites and people are examples of this category.

Fake news presents a complex regulatory challenge in the increasingly democratized and intermediated on-line information ecosystem. Inaccurate information is readily created by actors with varying goals, rapidly distributed by platforms motivated more by financial incentives than by journalistic norms or the public interest, and eagerly consumed by users who wish to reinforce existing beliefs. Yet even as awareness of the problem grew after the 2016 U. S. presidential election, the meaning of the term “fake news” has become increasingly disputed and diffused. This Article first addresses that definitional challenge, offering a useful taxonomy that classifies species of fake news based on two variables: their creators’ motivation and intent to deceive. In particular, it differentiates four key categories of fake news: satire, hoax, propaganda, and trolling. This analytical framework can provide greater rigor to debates over the issue. Next, the Article identifies key structural problems that make each type of fake news difficult to address, albeit for different reasons. These include the ease with which authors can produce user generated content online and the financial stakes that platforms have in highlighting and disseminating that material. Authors often have a mixture of motives in creating content, making it less likely that a single solution will be effective. Consumers of fake news have limited incentives to invest in challenging or verifying its content, particularly when the material reinforces their existing beliefs and perspectives. Finally, fake news rarely appears alone: it is frequently mingled with more accurate stories, such that it becomes harder to categorically reject a source as irredeemably flawed. Then, the Article classifies existing and proposed interventions based upon the four regulatory modalities catalogued by Larry Lessig: law, architecture (code), social norms, and markets. It assesses the potential and shortcomings of extant solutions. Finally—and perhaps most importantly—the Article offers a set of model interventions, classified under the four regulatory modalities, that can reduce the harmful effects of fake news while protecting interests such as free expression, open debate, and cultural creativity. It closes by assessing these proposed interventions based upon data from the 2020 election cycle.

Objective: This paper aims to provide a detailed overview of the most recent methods and strategies used for detecting fake news, especially in the context of rapid advancements in artificial intelligence and machine learning. With the widespread reach of fake news across social media and other digital platforms, this review focuses on identifying and evaluating effective approaches that can help tackle this growing problem.Methods: Given the importance of detecting fake news, this paper reviews and compares various approaches utilized in this field. To this end, by studying articles published in online libraries and document repositories such as IEEE, Scopus, Elsevier, and others, we first explore different methods for detecting fake news. Then, we compare the various approaches of human-based detection with those of automated detection.Results: The review shows that while conventional techniques like feature extraction and rule-based systems offer a good starting point, they often fall short when dealing with the complexity of modern disinformation. Deep learning models trained on large datasets have demonstrated promising results in detecting fake news, yet they still struggle with the subtlety of human-generated content and real-time applications. This highlights the need for more comprehensive solutions that can address these challenges.Conclusions: The findings suggest that an integrated approach—one that combines language analysis, machine learning, and network-based methods—is essential for building effective fake news detection systems. As the field progresses, future research should focus on improving hybrid models, refining data quality, and incorporating user-centric insights to combat the spread of disinformation better. Combining large language models (LLMs) with context-aware systems offers a promising path for achieving higher precision in detecting both machine-generated and human-created fake news.

Dear Editor,Emerging infections are usually new considerations in infectious medicine, and today there are many new, problematic infections. Good examples are bird flu, MERS, and the Ebola virus. New infections are usually proven to be the result of new human pathogens, and the outbreak of disease usually occurs without previous knowledge of them. Nevertheless, there are some interesting situations surrounding new emerging infections that are not considered among the present problems in medicine. The first kind of emerging infection is the non-natural emerging infection. This means that the pathogen has been proven to be a human pathogen in experimental studies, but there has never been a natural case report of it.

Today, social networks have become a prominent source of news, significantly altering the way people obtain news from traditional media sources to social media. Alternatively, social media platforms have been plagued by unauthenticated and fake news in recent years. However, the rise of fake news on these platforms has become a challenging issue. Fake news dissemination, especially through visual content, poses a significant threat as people tend to share information in image format. Consequently, detecting and combating fake news has become crucial in the realm of social media. In this paper, we propose an approach to address the detection of fake image news. Our method incorporates the error level analysis (ELA) technique and the explicit convolutional neural network of the EfficientNet model. By converting the original image into an ELA image, it is possible to effectively highlight any manipulations or discrepancies within the image. The ELA image is further processed by the EfficientNet model, which captures distinctive features used to detect fake image news. Visual features extracted from the model are passed through a dense layer and a sigmoid function to predict the image type. To evaluate the efficacy of the proposed method, we conducted experiments using the CASIA 2. 0 dataset, a widely adopted benchmark dataset for fake image detection. The experimental results demonstrate an accuracy rate of 96. 11% for the CASIA dataset. The results outperform in terms of accuracy and computational efficiency, with a 6% increase in accuracy and a 5. 2% improvement in the F-score compared with other similar methods