EFFECTIVENESS OF OUT SOURCING ACTIVITIES AT NATIONAL IRANIAN OIL REFINING &DISTRIBUTION COMPANY IN ARDABIL REGION

Abstract This study has done to evaluating the effectiveness ofoutsourcingactivities at National Iranian Oil Refining &Distribution Company in Ardabil region with four hypotheses. We used financialaspects, customeraspects, internal processes aspects and learning andgrowth aspects of outsourcingactivities as conceptual model variables. The population of this study is National Iranian Oil Refining & Distribution Company in Ardabil region. We determined the amount of the sample size with the used of Cochran sampling method which the statistical sample is 60 of National Iranian Oil Refining & Distribution Company employees which have been selected through the simple random sampling method. To gathering of data, we used questionnaire. Questionnaires reliability was estimated by calculating Cronbach's Alpha that is 0.89. In order to analyze the data, we used deductive and descriptive statistical methods. The results K-S Test for Financial aspects, Customer aspects, internal processes aspects and Learning and growth aspects show the test distribution is Normal, so we can use One-Sample T Test to test the hypothesis of the research. Findings show that Outsourcingactivities at National Iranian Oil Refining &Distribution Company has impact on financialaspects, Customeraspects, internal processes aspects and learning and growth aspects

Sonographic Optic Nerve Sheath Diameter as a Screening Tool for Detection of Elevated Intracranial Pressure

Introduction: Timely diagnosis and treatment of post traumatic, elevated intracranial pressure (EICP), could reduce morbidity and mortality, as well as improve patients’ outcome. This study is trying to evaluate the diagnostic accuracy of sonographic optic nerve sheath diameter (ONSD) in detection of EICP. Methods: Sonographic ONSD of patients with head trauma or cerebrovascular accident suspicious for EICP were evaluated by a trained chief resident of emergency medicine, who was blind to the clinical and brain computed tomography scan (BCT) findings of patients. Immediately after ultrasonography, BCT was performed and reported by an expert radiologist without awareness from other results of the patients. Finally, ultrasonographic and BCT findings regarding EICP were compared. To evaluate the ability of sonographic ONSD in predicting the BCT findings and obtain best cut-off level, receiver operating characteristic (ROC) curve were used. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) of sonographic ONSD in determining of EICP was calculated. P < 0.05 was considered to be statistically significant. Results: There were 222 patients (65.3% male), with mean age of 42.2±19.5 years (range: 16-90 years). BCT showed signs of EICP, in 28 cases (12.6%). The means of the ONSD in the patients with EICP and normal ICP were 5.5 ± 0.56 and 3.93 ± 0.53 mm, respectively (P<0.0001). ROC curve demonstrated that the best cut off was 4.85 mm. Sensitivity, specificity, PPV, NPV, PLR, and NLR of ONSD for prediction of EICP were 96.4%, 95.3%, 72.2%, 98.9%, 20.6, and 0.04, respectively. Conclusion: Sonographic diameter of optic nerve sheath could be considered as an available, accurate, and noninvasive screening tool in determining the elevated intracranial pressure in cases with head trauma or cerebrovascular accident.

Investigating the effect of perceived authenticity, destination image and memorable experience on the intention of visiting tourists again (Case study: Ardabil city)

urban destinations can achieve a sustainable competitive advantage by increasing the number of new tourist visits. Research has shown that in the long run, attracting re-visits costs less than visiting a destination for the first time. Therefore, the sustainable growth of the tourism sector relies more on tourists who repeat their visits. Such a factor has added to the importance of the concepts affecting the re-visit of urban tourism destinations. In this research, an attempt has been made to evaluate and analyze the effect of perceived originality, destination image and memorable experience on the intention of tourists to visit Ardabil again. The present study is applied in terms of purpose and descriptive-analytical in terms of method and the statistical population of this study is incoming tourists to Ardabil in 1398. The required sample size was considered using the Cochran's formula and 384 people. The questionnaire used in the research has been made by a researcher whose indicators have been obtained and localized from related studies and backgrounds. Validity and reliability of the research model and data analysis were performed using structural equation modeling and confirmatory factor analysis in SMART PLS software. Findings showed that the perceived authenticity of tourist attractions has a positive and significant effect on the image of destinations and memorable experience. The destination image also has a positive and significant effect on the memorable experience. Finally, the findings showed that a memorable experience has a positive and significant effect on the intention to visit again

A Model to Measure the Spread Power of Rumors

Nowadays, a significant portion of daily interacted posts in social media are infected by rumors. This study investigates the problem of rumor analysis in different areas from other researches. It tackles the unaddressed problem related to calculating the Spread Power of Rumor (SPR) for the first time and seeks to examine the spread power as the function of multi-contextual features. For this purpose, the theory of Allport and Postman will be adopted. In which it claims that there are two key factors determinant to the spread power of rumors, namely importance and ambiguity. The proposed Rumor Spread Power Measurement Model (RSPMM) computes SPR by utilizing a textual-based approach, which entails contextual features to compute the spread power of the rumors in two categories: False Rumor (FR) and True Rumor (TR). Totally 51 contextual features are introduced to measure SPR and their impact on classification are investigated, then 42 features in two categories "importance" (28 features) and "ambiguity" (14 features) are selected to compute SPR. The proposed RSPMM is verified on two labelled datasets, which are collected from Twitter and Telegram. The results show that (i) the proposed new features are effective and efficient to discriminate between FRs and TRs. (ii) the proposed RSPMM approach focused only on contextual features while existing techniques are based on Structure and Content features, but RSPMM achieves considerably outstanding results (F-measure=83%). (iii) The result of T-Test shows that SPR criteria can significantly distinguish between FR and TR, besides it can be useful as a new method to verify the trueness of rumors

Automatic Personality Prediction; an Enhanced Method Using Ensemble Modeling

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end, we suggest five new APP methods including term frequency vector-based, ontology-based, enriched ontology-based, latent semantic analysis (LSA)-based, and deep learning-based (BiLSTM) methods. These methods as the base ones, contribute to each other to enhance the APP accuracy through ensemble modeling (stacking) based on a hierarchical attention network (HAN) as the meta-model. The results show that ensemble modeling enhances the accuracy of APP

Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction

Reverse engineering of gene regulatory networks (GRNs) is the process of estimating genetic interactions of a cellular system from gene expression data. In this paper, we propose a novel hybrid systematic algorithm based on neurofuzzy network for reconstructing GRNs from observational gene expression data when only a medium-small number of measurements are available. The approach uses fuzzy logic to transform gene expression values into qualitative descriptors that can be evaluated by using a set of defined rules. The algorithm uses neurofuzzy network to model genes effects on other genes followed by four stages of decision making to extract gene interactions. One of the main features of the proposed algorithm is that an optimal number of fuzzy rules can be easily and rapidly extracted without overparameterizing. Data analysis and simulation are conducted on microarray expression profiles of S. cerevisiae cell cycle and demonstrate that the proposed algorithm not only selects the patterns of the time series gene expression data accurately, but also provides models with better reconstruction accuracy when compared with four published algorithms: DBNs, VBEM, time delay ARACNE, and PF subjected to LASSO. The accuracy of the proposed approach is evaluated in terms of recall and F-score for the network reconstruction task

Alendronate improves fasting plasma glucose and insulin sensitivity and decreases insulin resistance in prediabetic osteopenic postmenopausal women: a randomized triple-blind clinical trial

Aims Postmenopausal women receive bisphosphonates for osteoporosis treatment. The effect of these medications on developing diabetes mellitus (DM) in prediabetic patients is yet to be investigated. We aimed to determine the effect of alendronate on plasma glucose, insulin indices of postmenopausal women with prediabetes and osteopenia. Methods This triple‐blind randomized controlled clinical trial included 60 postmenopausal women, aged 45–60 years. All patients were vitamin D sufficient. They were randomly enrolled in intervention (70 mg/week alendronate for 12 week) and control (placebo tablet per week for 12 weeks) groups. The morning 8 hour fasting blood samples were collected at the baseline and follow–up visits to measure the fasting plasma glucose (FPG) (mg/dl), insulin and hemoglobin A1c (HbA1c). Plasma glucose and insulin concentration were measured 30, 60, and 120 minutes after glucose tolerance test. Matsuda index, homeostasis model assessment of insulin resistance (HOMA–IR), homeostasis model assessment of beta–cell function (HOMA–B) and the area under the curves (AUC) of glucose and insulin were calculated. Results Mean (SD) FPG (102.43 (1.46) mg/dl vs. 94.23)1.17) mg/dl, P=0.001), 120‐minutes insulin concentration (101.86)15.70) mU/l vs. 72.60 (11.36), P=0.026), HbA1c (5.60 (0.06) % vs. 5.40 (0.05)%, P=0.001), HOMA‐IR (3.57 (0.45) vs. 2.62 (0.24), P=0.021) and Matsuda index (7.7 (0.41) vs. 9.2 (0.4), P=0.001) significantly improved in the alendronate‐treated group. There was statistically significant more reductions in FPG (‐8.2 (8.63) mg/dl vs. ‐2.5 (14.26) mg/dl, P=0.002) and HbA1c (‐0.2 (0.23) % vs. ‐0.09 (0.26) %, P=0.015) were observed in alendronate‐treated group than placebo group during the study course, respectively. Conclusions Administration of 70 mg/week alendronate improves fasting plasma glucose, HbA1c and insulin indices in postmenopausal women

The Investigation of WRAP53 rs2287499 Association with Thyroid Cancer Risk and Prognosis among the Azeri Population in Northwest Iran

Background: TP53 and the oncogene WRAP53 are adjoining genes, producing p53-WRAP53α sense-antisense RNA couples. WRAP53α is indispensable for p53 mRNA regulation and p53 induction following DNA damage. Up-regulated WRAP53β can induce neoplastic transformation and cancer cell survival. All these, along with the associations of WRAP53 single nucleotide polymorphisms with tumor incidence and prognosis, highlighted an impact in human cancers. Considering the importance of WRAP53 in modulating p53, and the frequent occurrence of thyroid cancer, we examined the association of a WRAP53 SNP (rs2287499) with thyroid cancer risk and prognosis among Iranian-Azeri population. Methods: This research was done in Tabriz-IRAN in 2014. DNA samples obtained from 106 patients and 196 controls were subjected to polymerase chain-reaction-based single-strand conformational polymorphism (PCR-SSCP) analysis. Genotypes were characterized by sequencing. Correlations of desired SNP with thyroid cancer as well as age, gender, involved thyroid lobe, lymph node metastasis, tumor type, stage, and size were estimated using Chi-square (χ2) or Fisher's exact tests with a P-value less than 0.05 as significant. Results: rs2287499 is not associated with thyroid cancer predisposition. Except for gender, none of the clinicopathologic factors were significantly linked to the examined genotypes. Conclusions: rs2287499 is not a genetic risk factor for thyroid cancer. Although rs2287499 is not assessable as a biomarker to predict prognosis based on clinicopathologic parameters, the considerable association with gender suggests that this SNP may indirectly be relevant to gender-associated disease manifestation. Further investigations on distinct types of thyroid tumors are needed to fully characterize the rs2287499 status in thyroid malignancies