فهرست مطالب fahimeh hosseinzadeh

Nursing Known as a stressful and overwhelming profession. Due to the stressful nature of the nursing job, nurses experience burnout more than any other occupation, which may affect the quality of health care. Emotional intelligence is one of the important predictors of psychological well-being and it plays an important role as a distinguishing factor for organizational performance and achievement of job success. The purpose of this study was to determine the relationship between emotional intelligence and nurseschr('39') personal and occupational characteristics. 

 In this cross-sectional analytical study, 135 nursing staff working in Gonabad hospitals was selected through a census sampling method. Written informed consent of nurses and working in hospitals of Gonabad city were the inclusion criteria and Failure to complete the questionnaires or the questionnaire being confounded or withdrawal from the study was considered as the exclusion criteria. They were evaluated by Shirring Emotional Intelligence Questionnaire and Demographic Information Form. The research data were analyzed using SPSS software version 16, Chi-square test, one-way ANOVA and Pearson correlation coefficient. The significance level was less than 0.05.

In this study72.6% of participants were women. The majority of nurses were married (81.5%) and 87.4% of nursing staff had high emotional intelligence. In this study, there was no significant relationship between individual characteristics and emotional intelligence, but there was a significant association between job characteristics, job shift (P = 0.03) and employment status (P = 0.03) with total emotional intelligence. The results showed that there was a significant relationship between social consciousness with education level (p = 0.019) and employment status (p = 0.001) and there was a significant relationship between social skills with work shift (p = 0.003) and nurseschr('39') marital status (p = 0.007)

According to the findings, considering the appropriate job shifts for nurses and formalizing them to create a strong organizational commitment to take benefit of nurses with higher emotional intelligence and this leads to improved performance of nurses.

Vitamin D deficiency is prevalent in heart failure (HF) and the anti-inflammatory impacts of vitamin D may affect the pathogenesis of HF. Therefore, the present study aimed to investigate the effect of vitamin D supplementation on echocardiographic and biochemical factors in vitamin D-deficient HF patients. To this end, 39 HF patients with 25(OH)D ≤20 ng/mL participated in the current double-blind, randomized, and placebo-controlled trial, who belonged to class III, New York Heart Association classification. About 50 000 IU vitamin D3 (group D+) or placebo (group D-) were prescribed within 2 months. Then, the ejection fraction (EF%), tumor necrosis factor alpha (TNF-α), B-type natriuretic peptide (BNP), and high sensitive C-reactive protein (hs-CRP) were assessed before and after supplementation. The mean serum level of 25(OH)D increased markedly in D+ group (P < 0.001). The mean increase of EF% was 5.3±9.03% (P = 0.03) and the decrease of TNF-α (-0.09 pg/mL, P < 0.001) and BNP (-3.14 ng/mL, P = 0.04) were statistically significant in D+ group after supplementation. In addition, the blood concentration of BNP declined significantly in D+ group compared to placebo while hs-CRP and TNF-α levels failed to differ between the two groups. The results revealed that vitamin D could be effective against inflammation and thus its supplementation may reduce the severity of HF by improving the serum level of BNP and EF%. However, more clinical trials are required to approve the beneficial role of vitamin D in HF patients.

Surface waters play a significant role in supplying water for different demands such as agriculture, domestic and industrial. Due to the variation of river discharges and the non-compatibility of this resource with the water demands, water supply reliability reduces and some damages are inflicted. Therefore, for appropriate use of water in the reservoir, the reservoir operation should be considered. Reservoir operation is performed using different optimization methods. Heuristic algorithms showed a suitable performance during the last two decades. In this study optimized water releases are determined in the Pishin reservoir using Imperialist Competitive Algorithm (ICA) which is based on the social-political evolution. Modeling is done for a 12-month period that is the mean of a 41-years period of hydrological parameters. Objective function is defined as the square of summation between water releases and water demand in each sub-period. Results are compared with the Particle Swarm Optimization (PSO) and Standard Operation Policy (SOP) methods. The mean of the objective function with PSO and ICA is obtained as 3.9804 and 3.9808 respectively, which shows a close estimation of the two methods. The results also show that the content of unmet demand by these two algorithms is 31.1 percent less than SOP method.