The aim of this study was to evaluate the effect and safety of N‐acetylcysteine (NAC) inhalation spray in the treatment of patients with coronavirus disease 2019 (COVID‐19). This randomized controlled clinical trial study was conducted on patients with COVID‐19. Eligible patients (n = 250) were randomly allocated into the intervention group (routine treatment + NAC inhaler spray one puff per 12 h, for 7 days) or the control group who received routine treatment alone. Clinical features, hemodynamic, hematological, biochemical parameters and patient outcomes were assessed and compared before and after treatment. The mortality rate was significantly higher in the control group than in the intervention group (39.2% vs. 3.2%, p < 0.001). Significant differences were found between the two groups (intervention and control, respectively) for white blood cell count (6.2 vs. 7.8, p < 0.001), hemoglobin (12.3 vs. 13.3, p = 0.002), C‐reactive protein (CRP: 6 vs. 11.5, p < 0.0001) and aspartate aminotransferase (AST: 32 vs. 25.5, p < 0.0001). No differences were seen for hospital length of stay (11.98 ± 3.61 vs. 11.81 ± 3.52, p = 0.814) or the requirement for intensive care unit (ICU) admission (7.2% vs. 11.2%, p = 0.274). NAC was beneficial in reducing the mortality rate in patients with COVID‐19 and inflammatory parameters, and a reduction in the development of severe respiratory failure; however, it did not affect the length of hospital stay or the need for ICU admission. Data on the effectiveness of NAC for Severe Acute Respiratory Syndrome Coronavirus‐2 is limited and further research is required.
PurposeThis paper follows a systematic literature review (SLR) method covering the published studies until March 2021. The authors have extracted the related studies from different online databases utilizing quality-assessment-criteria. In order to review high-quality studies, 32 papers have been chosen through the paper selection process. The selected papers have been categorized into three main groups, decision-making methods (17 papers), meta-heuristic methods (8 papers) and fuzzy-based methods (7 papers). The existing methods in each group have been examined based on important qualitative parameters, namely, time, cost, scalability, efficiency, availability and reliability.Design/methodology/approachCloud computing is known as one of the superior technologies to perform large-scale and complex computing. With the growing tendency of network service users to utilize cloud computing, web service providers are encouraged to provide services with various functional and non-functional features and supply them in a service pool. In this regard, choosing the most appropriate services to fulfill users' requirements becomes a challenging problem. Since the problem of service selection in a cloud environment is known as a nondeterministic polynomial time (NP)-hard problem, many efforts have been made in recent years. Therefore, this paper aims to study and assess the existing service selection approaches in cloud computing.FindingsThe obtained results indicate that in decision-making methods, the assignment of proper weights to the criteria has a high impact on service ranking accuracy. Also, since service selection in cloud computing is known as an NP-hard problem, utilizing meta-heuristic algorithms to solve this problem offers interesting advantages compared to other approaches in discovering better solutions with less computational effort and moving quickly toward very good solutions. On the other hand, since fuzzy-based service selection approaches offer search results visually and cover quality of service (QoS) requirements of users, this kind of method is able to facilitate enhanced user experience.Research limitations/implicationsAlthough the current paper aimed to provide a comprehensive study, there were some limitations. Since the authors have applied some filters to select the studies, some effective works may have been ignored. Generally, this paper has focused on journal papers and some effective works published in conferences. Moreover, the works published in non-English formats have been excluded. To discover relevant studies, the authors have chosen Google Scholar as a popular electronic database. Although Google Scholar can offer the most valid approaches, some suitable papers may not be observed during the process of article selection.Practical implicationsThe outcome of the current paper will be useful and valuable for scholars, and it can be a roadmap to help future researchers enrich and improve their innovations. By assessing the recent efforts in service selection in cloud computing and offering an up-to-date comparison of the discussed works, this paper can be a solid foundation for understanding the different aspects of service selection.Originality/valueAlthough service selection approaches have essential impacts on cloud computing, there is still a lack of a detailed and comprehensive study about reviewing and assessing existing mechanisms in this field. Therefore, the current paper adopts a systematic method to cover this gap. The obtained results in this paper can help the researchers interested in the field of service selection. Generally, the authors have aimed to specify existing challenges, characterize the efficient efforts and suggest some directions for upcoming studies.
Over the last decade, the landscape of cloud computing has been significantly changed. It has been known as a paradigm in which a shared pool of computing resources is accessible for users. The rapid growth of the healthcare environment provides better medical services to reduce costs and increase competition among healthcare providers. Despite its crucial role in the cloud, no thorough study exists in this domain. This article presents a systematic study for healthcare services in the cloud environment. A well‐organized overview of all the databases has been explored. By clustering the research goals of the found papers, we have derived four main research groups. We have further evaluated the papers concerning the background of the paper, QoS parameters, application area, or methods used for applying and formulating the main ideas presented in the works. This survey emphasizes the challenges, needs, benefits of using cloud computing in healthcare systems and provides a comprehensive and detailed study on cloud healthcare services, strengths, and weaknesses of the existing methods. Highlighting cloud health services can be the major focus of research for developing the urban healthcare system.
To identify a vehicle, License Plate identification technology is the key technology of intelligent transport system, finding a stolen vehicle, monitoring traffic flow, in town management, highway tolls etc. The major issue in such applications is to detect the exact location of plate, because finding the location of number plate could vary and as well as its size and color; many of the vehicles have an uncertain difference in License plate position, location and unclean License Plate. In this paper we have conducted a very fresh survey of most authentic techniques of license plate detection from a car, we studied different techniques and compared them; we figured out every technique has its own limitations, every method gives best results under some certain conditions so do bad results, we figured out all we need to do is to have locus of control, we shall control theenvironment we are working in, some techniques works good in dark light, some for bright light etc; every technique has its own parameters to identify license plate; this paper will lead you to choose the best technique for detection just according to your circumstance.
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