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The main objective of this paper is to examine the impact of economic growth on coefficient of cardinal welfare in Iran's economy. Hence, we employ the Bayesian approach and the estimation of forward and backward density functions in order to measure the effect of economic growth spillovers on the social welfare. The paper has applied the Gibbs sampling algorithm which is a rigorous tool for forward simulation so as the results rising from this simulation indicate that there is a positive relationship between economic growth and welfare variables in Iran. It means that the flow of economic growth has had a positive impact on the rise of welfare in the country, such that the average of Bayesian coefficient is near to 0.17 per cent for the change of welfare during the period 19852011. Accordingly, it is recommended that: 1-the policy makers should follow the growth-based strategies 2-the respective officials should identify the effective variables on growth in order to increase growth rate for the economy and eventually, 3-design more efficient institutions for the poor so as they enjoy greater gaining from the growth. [ABSTRACT FROM AUTHOR]

Hub location problem is further used in transportation and telecommunication networks (airlines, post delivery services, etc.) so origin-destination pairs, receive or send commodities via special facilities called Hub. Hub median problem with multiple allocation is an NP-hard problem which includes both locating hub facilities and allocating non-hub nodes to hubs as minimizes total transportation and location costs. In this paper, the hub median problem is considered in an environment which network flow varies during the time periods and the capacities of hubs and arcs are unlimited. Also opening and closing hubs in different periods of planning horizon are permitted. The model and the proposed algorithm for this problem were considered to Iran airlines network using real passenger flows data. Computational results state that the dynamic network compared with static model has lower cost and whatever the number of time periods in dynamic case increases, the cost will be reduced as well. [ABSTRACT FROM AUTHOR]

Economic vulnerability, is a country's structural feature, making it exposed by out-of-control economic exogenous variables. On the other hand, resilience stems from how macroeconomic policies are adopted. The purpose of this article is to analyze the relationship between sustainable development, vulnerability and resilience in the Iran's economy in the time period of 1391-1398.1 this way, sustainable development consists of 5 Dimensions: Economic, Social, Environmental, Governance, Peripheral and also includes 44 variables as a sub-indicator of each development's dimension. It uses graph theory and Tarjan Algorithm for study the network structure of relationships between variables. The Algorithm identifies34 variables as the fundamental variables affecting economic resilience and vulnerability and introduces economic and governance Dimensions as control (major) Dimensions; Social, Environmental and Peripheral Dimensions as Contingent (minor) Dimensions. The results show that weakness of Iran's economy in this period was due to vulnerability and resilience in governance and economy Dimensions. Among the contingent Dimensions, the Peripheral dimension has the worst situation in terms of vulnerability and resilience. The innovation of this research is in studying the Dimensions of sustainable development and its effect on vulnerability and resilience, moreover graph theory has been used in order to study the influential variables for the first time in Iran. In this algorithm, without limiting the number of input variables, the phenomenon can be analyzed comprehensively. furthermore, a holistic table has been prepared, by focusing on the variables affecting the state of vulnerability and resilience in the theoretical foundations of the subject, that has not been shown in any other studies. [ABSTRACT FROM AUTHOR]

Background and Objectives Change in the age structure of the population affects many activities and processes, and most countries are expected to enter the old population phase by 2050. Today, for various reasons, the consumption of blood and blood products has increased. The aim of this study was to investigate the age change in donor population during the years 1390 to 1397 and compare it with the society's age change algorithm to determine if the latter affects the former. Materials and Methods In this cross-sectional descriptive study, demographic information of 329631 blood donors from 1390 to 1397 from Blood Transfusion Software (Negareh software version 5/9) was extracted and the latest demographic information of the province was achieved using the website of the Statistics Center of Iran. Results Of the population of Yazd and Ardakan cities, 64.7% and 65.38% are within the appropriate age range for blood donation. The donor population of 18-30 years decreased by 30.7% in 2016 and 32.3% in 2018 compared with the year 2011 while other age groups almost increased. Mean age of donors in 2014 and 2017 were 44.2 and 40.05 years, respectively. Conclusions Due to the aging population, and the reduction of the population under the age of 30, it is necessary to take effective programs to maintain and attract 18-30 year old population for blood donation. [ABSTRACT FROM AUTHOR]

Background and Aim Chronic Lymphocytic Leukemia (CLL) is the most commonly occurring leukemia in adults, accounting for about 30-25% of total leukemia. One of the important etiological causes of this leukemia is the disruption of the Nuclear Factor Kappa B (NF-kB) signaling pathway. The two proteins of Apoptosis-Inducing Ligand (APRIL) and B-Cell Activating Factor (BAFF) play a role in the pathogenesis of this leukemia by affecting the NF-kB signaling pathway. In this study, due to the effect of miRNAs in regulating many cellular processes, the prediction of the prominent miRNAs targeting APRIL and BAFF transcripts in B-cell CLL patients was evaluated using specific and different bioinformatics programs. Methods & Materials Afterwards retrieving the sequences of APRIL and BAFF proteins from the NCBI website, by using several programs including miRanda, TargetScan, miRWalk, DIANA and miRDB with different algorithms, the prediction of miRNAs targeting these genes was investigated. Ethical Considerations This study was approved by the Research Ethics Committee of Arak University of Medical Sciences. Results Based on the scoring system of bioinformatics programs, “hsa-miR-145-5p” and “hsa-miR-185-5p” were identified as miRNAs targeting APRIL gene, while “hsa-miR-424” and “hsa-miR-497”were miRNAs targeting BAFF gene. They were suggested for the practical studies in future. Conclusion Based on the important role of APRIL and BAFF genes in the normal process of cell death and B-cell evolution, it seems that the mi-RNAs predicted by bioinformatics programs using different algorithms can be used as a diagnostic molecular biomarker to identify B-cell CLL patients. [ABSTRACT FROM AUTHOR]

Background: Liver cirrhosis was one of the most important liver diseases. Other chronic liver diseases could be lead to liver cirrhosis. Liver cirrhosis could be lead one kind of liver cancers named hepatocellular carcinoma. Cirrhosis in the early stages just by laboratory and imaging testes could be diagnosed. In this study cirrhotic patients were classified based on laboratory symptoms. For this purpose data mining approach has been used in this research. Data mining was an interdisciplinary science that discovers the hidden knowledge in the data. Materials and Methods: We used K-Means algorithm to categorize the statues of cirrhotic patients. In order to determine the quality of clustering results and to find the best number of clusters, we have used silhouette indices. Results: Our data consists of 410 records which have been collected from Dr. Shariati hospital The number of features in this study are .1 items and sampling were divided into two main groups. Conclusion: At first, we have done clustering based on 21 attributes and the average silhouette was 41 percent. We improved the model, in order to reach a reasonable structure. Finally, based on 7 attributes, a reasonable clustering model was derived. The new model provides 64 percent average silhouette, and based on patients' status, patients are divided into 2 main categories. The risk of HCC in the first cluster is 23 percent and in the second cluster is 14 percent. [ABSTRACT FROM AUTHOR]