Cloud computing is a rapidly evolving computational technology. It is a distributed computational system that offers dynamically scaled computational resources, such as processing power, storage, and applications, delivered as a service through the Internet. Virtual machines (VMs) allocation is known as one of the most significant problems in cloud computing. It aims to find a suitable location for VMs on physical machines (PMs) to attain predefined aims. So, the main purpose is to reduce energy consumption and improve resource utilization. Because the VM allocation issue is NP‐hard, meta‐heuristic and heuristic methods are frequently utilized to address it. This paper presents an energy‐aware VM allocation method using the improved grey wolf optimization (IGWO) algorithm. Our key goals are to decrease both energy consumption and allocation time. The simulation outcomes from the MATLAB simulator approve the excellence of the algorithm compared to previous works.

In blockchain technology, all registered information, from the place of production of the product to its point of sale, is recorded as permanent and unchangeable, and no intermediary has the ability to change the data of other members and even the data registered by them without public consensus. In this way, users can trust the accuracy of the data. Blockchain systems have a wide range of applications in the medical and health sectors, from creating an integrated system for recording and tracking patients’ medical records to creating transparency in the drug supply chain and medical supplies. However, implementing blockchain technology in the supply chain has limitations and sometimes has risks. In this study, BWM methods and VIKORSort have been used to classify the risks of implementing blockchain in the drug supply chain. The results show that cyberattacks, double spending, and immutability are very dangerous risks for implementation of blockchain technology in the drug supply chain. Therefore, the risks of blockchain technology implementation in the drug supply chain have been classified based on a literature review and opinions of the experts. The risks of blockchain technology implementation in the supply chain were determined from the literature review.

Purpose: – The current study aims to investigate the existing relationship between knowledge management (KM) infrastructures, KM process capabilities, creative organizational learning (OL) and organizational performance.Design/methodology/approach: – Statistical population includes executives of knowledge-based companies in Tehran Science and Technology Park of Iran. The 68 questionnaires were distributed among the census, of which 60 questionnaires were completed correctly. The research data were analyzed by SPSS and PLS software. The unit of analysis is a company that has adopted a knowledge management system (KMS). Target population of the research consisted of 85 top managers of knowledge-based companies in Tehran Science and Technology Park of Iran (N= 85). Random sampling method was applied in this study, and 71 top managers were considered as the statistical sample based on the “Morgan Table”. One standard five-point Likert questionnaire was adopted and distributed between top managers in the park; 62 questionnaires were returned, among which 60 were statistically investigated. The structural relations among variables were tested using the partial least squares method.Findings: – This study shows that the KM processes can mediate between creative OL and factors in the KM infrastructure. The results of the study demonstrate that KM process capabilities have the most crucial role in creative OL. The results indicate a significant influence of the infrastructure capabilities on the process capabilities, also the impacts of KM process capabilities on creative OL and the impacts of creative OL on organizational performance was confirmed.Research limitations/implications: – Using a holistic view of the KM performance framework, this study has provided insights to KM for researchers because it explains the integrated aspects of KM performance by examining the relationships between the KM infrastructure, knowledge process capabilities, and organizational outcomes. Previous studies on KM have been fragmented because they only consider some aspects of KM performance rather than using a holistic view of the KM performance framework: they have examined the relationship between one or two facets of KM enablers and process capability, or between KM process capabilities and organizational performance.Practical implications: – In order to manage rapid change and global competition in business environments, knowledge workers should create new business opportunities and continuously question what and how they can contribute to these chances. Organizational KMS should support the learning processes of their knowledge workers.Social implications: – The continuous learning and experiments are necessary in order to produce new ideas and products: it is critical to emphasize the importance of a KM infrastructure that supports and encourages learning in organizations. The creative learning in turn affects organizational performance indicating that without learning, organizations cannot overcome the boundary of old business practices and adjust to change in environments.Originality/value: – Previous researches did not appraise the effect of KM and its capabilities on organizational performance, and the specific influence of creative OL was disregarded. The present study demonstrates the mechanism of KM effect on organizational performance and describes the comprehensive dimensions of KM performance.

These days, with the development of advanced space, rising innovations, for example, the blockchain has made a decent open door for organizations to additionally improve the productivity of their supply arranges. Going with and orchestrating the supply chain with computerized advancements can prompt a huge increment in mechanical proficiency. At present, there is a crucial open door for the supply that binds the world over to amplify their profitability and productivity by utilizing and abusing blockchain innovation, man-made consciousness, and keen gear. In this research we proposed a hybrid method based on hesitant fuzzy made for ranking the barriers of implementation of blockchain on supply chain management in perishable goods. The result shows that Technological and security barriers are the most important barriers.

Background Hepatitis A (HAV) and Hepatitis E viruses (HEV) are endemic in Iran and are known major causes of acute viral hepatitis. Also, during pregnancy, they are associated with severe outcomes. Therefore, it is vital to evaluate the antibody levels against HAV and HEV in pregnant women to avoid severe outcomes incidence. Study design and methods A total of 247 pregnant women were enrolled in this prospective cross-sectional study. In addition to completing the questionnaire and interviewing all participants, the serum samples were tested for anti-HAV and anti-HEV IgG using the enzyme-linked immunosorbent assay (ELISA). The association between anti-HAV and anti-HEV antibodies status and risk factors was evaluated. Results The mean age of patients was 28.06 ± 5.29 years. Anti-HAV antibody was found in 111 patients (44.9%), while anti-HEV antibody was detected in only two pregnant women (0.8%). The seroprevalence of HAV was inversely related to the level of education. There was no significant correlation between HAV antibody levels and age, marital status, residence location, and pregnancy trimesters. Conclusion Considering many complications of these diseases in pregnancy, the detection of enteroviral hepatitis, especially HAV in pregnant women, is necessary, and therefore, proactive measures, such as promoting education, improving people awareness, and vaccination, are recommended

The journal retracts the article titled “Evaluation and Classification Risks of Implementing Blockchain in the Drug Supply Chain with a New Hybrid Sorting Method”