h. nazari

Azadegan field is one of Iran's oil fields, which is located in an area of 1500 km2 in the southwest of Iran in the northern Dezful region. According to the geological survey of the region, in the anticlines excavated in Azadegan field after the Aghajari formation, the Gachsaran, Asmari, Pabdeh, Jahrom, Gurpi, Tabor, Sarvak and Fahlian formations, are placed in the usual geological sequence. At present, in the Azadegan oil field, production is carried out from four oil formations, including Kazhdami, Gadvan, Fahlian andSarvak, although the main reservoir of this field is the Sarvak formation and it is composed of carbonate rocks. On the other hand, permeability is the most important factor for accurate description and modeling of hydrocarbon reservoir rocks. Usually, the standard methods for determining permeability are core analysis and well testing. These methods are very expensive, also the wells of a field do not have a core. As a result, because well logs are usually available in all the wells of a field, it will be very important to provide a method or methods that can provide the petrophysical properties of the reservoir, including permeability, using well logs. Smart methods are new, low-cost and accurate methods that can indirectly estimate reservoir permeability in the shortest possible time using well drilling data. Therefore, by using different well logs and the method of adaptive neural-fuzzy inference system (ANFIS), the permeability in Sarvak Formation, one of the hydrocarbon reservoirs in southwestern Iran, has been indirectly estimated. In order to use this intelligent method, the database was divided into two parts: training data (1754 data) and test data for evaluating the models (752 data). The results show the very appropriate performance of the intelligent method in permeability estimation. Therefore, the smart model can be used as a powerful, fast and accurate method for indirect estimation of permeability in reservoirs where permeability has not been measured through core.

Degree of water saturation is one of the key parameters in petroleum geological engineering to calculate the volume of reservoir hydrocarbons and also reduce economic risk in the development of oil fields. The first attempts to estimate the degree of water saturation of the formation were made by Archi in the data of well drilling diagrams in clean sandstone reservoirs, the results of which were generalized as an experimental relation for carbonate reservoirs. In carbonate reservoirs, assuming these parameters to be constant due to severe heterogeneity is associated with a large error. On the other hand, it is not possible to calculate these parameters due to the time and cost and loss of part of the core for the entire length of the well. Artificial intelligence methods are new, low-cost and accurate methods that can indirectly estimate the degree of saturation of the reservoir water in the shortest possible time using well data. Therefore, in this study, using different wells and intelligent method of adaptive neural-fuzzy inference system (ANFIS-FCM), the degree of water saturation in one of the hydrocarbon reservoirs in southwestern Iran (North Azadegan Square) has been indirectly estimated. To use this artificial intelligence method, the database consisted of 2511 well data, which were divided into two parts: training data (1758 data) and test data to evaluate the models (753 data). The results show the very good performance of the adaptive neural-fuzzy inference system (ANFIS-FCM) method of estimating the degree of water saturation. Therefore, the adaptive neural-fuzzy inference system (ANFIS-FCM) model can be used as a powerful, fast and accurate method for indirectly estimating the degree of water saturation in reservoirs where the degree of water saturation is not measured through the core.

The efficiency of ovine in vitro embryo production remains low yet.

The present study evaluated the effect of different concentrations of gamma (γ)-oryzanol in maturation or culture media on in vitro ovine oocytes and embryo developments.

Morphologically normal COCs were aspirated from ovine ovaries, subjected to maturation media supplemented with 0, 2.5, 5, 10, 20, 50, and 100 μM γ-oryzanol, then processed for conventional in vitro fertilization and culture to assess their potential to cleave and develop to blastocyst. Another group of COCs was matured and fertilized. Presumptive zygotes were subjected to culture in drops of media supplemented with 0, 2.5, 10, 20, and 50 μM γ-oryzanol, and the developments of embryos were assessed under 7% and 20% O2 levels. A control group of no supplementation was included in each experiment.

The expansion of cumulus cover and survival rate tended to decrease with concentrations of 20, 50, and 100 μM in maturation media, suggesting an overdose effect. The cleavage and total blastocyst rates were significantly higher for oocytes matured at 5 μM γ-oryzanol. The presumptive zygotes cultured in supplemented media showed significantly higher cleavage and total blastocyst rates with concentrations of 5 and 10 μM γ-oryzanol (P<0.04) in both 7% and 20% O2 levels.

These results represent the first study showing a significant positive effect of the γ-oryzanol supplement on in vitro ovine oocyte and embryo development, at optimal concentrations of 5 μM in maturation, and 5 and 10 μM in embryo culture media.

managed care is an example of modern health care systems whose task is to control the cost of services in a cost-effective manner through managed care organizations. Considering that several factors such as inadequate budget, unnecessary prescriptions and tests, incorrect payment system are observed in Iran. Therefore, the purpose of the present study was to determine and explain the model of managed care for emerging respiratory infectious diseases in Iran's healthcare system.

The present case study and semi-structured interview was conducted on 12 experts and professors in 2019 leading to the development of research model criteria. For emerging respiratory infectious diseases, based on content analysis technique, these factors and indicators are categorized. Considering that the purpose of this research is an exploratory combination of the sequential type and the tooling model, designing and editing the model based on the criteria of the model design. The collected data were analyzed using statistical tests of generalized linear models, Hotelling's t and Bonferroni's post-test.

Based on the conducted interviews and review of previous researches, Factors affecting the managed care pattern for emerging respiratory infectious diseases were identified and divided into five separate dimensions and placed into 13 categories based on axial coding. In this model, 5 main categories of financing, providing resources, information and research, servicing and equipping, as well as government agents were identified as the main categories. Also, the managed care status of emerging respiratory infectious disease (Corona) was ranked first and other diseases were ranked next. The managed care of rural centers was significantly better than urban centers.

In general, planning to establish these organizations as a private sector of insurance alongside the treatment sector is inevitable, so a model that could facilitate the traditional system and move towards the new system is essential.

The aim of this study was to investigate the electrical conductivity of groundwater due to physical and chemical parameters of water using ANFIS-FCM method in Azarshahr, Ajabshir and Maragheh study areas of Urmia Lake catchment area. To achieve this goal, 82 water samples were taken from wells and springs in the plains and the data were chemically analyzed in the laboratory. Descriptive statistical data and correlation matrix of the studied parameters were obtained using SPSS software. By forming the correlation matrix, it was found that the four salinity parameters, soluble oxygen (DO), total soluble solids (TDS) and pH, have the highest correlation with electrical conductivity (EC) compared to other existing parameters. Therefore, the inputs of the model included the four mentioned parameters and the output was selected according to the purpose of the research, electrical conductivity.  After standardization, the data entered the MATLAB environment and using ANFIS-FCM method, the electrical conductivity of groundwater was predicted. In this method, 80% of the data (66 samples) were randomly selected for the training data set and 20% of the data (16 samples) were randomly selected for the test data set. For ANFIS-FCM training data set, R2, RMSE and VAF values were 0.9999, 0.0032399 and 0.99993, respectively, and also for ANFIS-FCM test data set, R2, RMSE and VAF values were 0.9998, respectively, 0.0029949 and 0.99972 were obtained. Using the results of this model, it was found that the estimated electrical conductivity in the studied areas had a very good accuracy and high correlation with the measured values. As a result, the ANFIS-FCM intelligent method is an effective, efficient and accurate way to estimate the physical and chemical parameters of water.

Electrical conductivity increases in groundwater around the gypsum mines because of ions dissolution. this is a useful indicator in gypsum mines exploration, but not enough to that aim, so the elements with high concentrations involved in increasing EC should be identified. This study aims to investigate the efficiency of ANFIS-FCM method to exploration of salty gypsum mines using hydrogeochemical changes of groundwater, which was tested on a case: Anar salty gypsum mine. to this aim, 21 water samples were taken from wells across the plain and chemical analysis of samples was performed in the laboratory. Then, the resulted data were statistically analyzed and descriptive statistics of the data and correlation matrix of the studied parameters were obtained using SPSS software. Forming a data correlation matrix, it was found that in samples near the salty gypsum mine, some ions had the highest correlation with electrical conductivity (EC) including sodium, magnesium, calcium, manganese, selenium and lead, while the mentioned parameters had the highest correlation. The 6 mentioned elements selected as the model inputs and the electrical conductivity was the output according to purpose of the current research. After standardization, the data were entered into MATLAB and the electrical conductivity was predicted using ANFIS-FCM method. The measured electrical conductivity was used directly to compare with the electrical conductivity of the intelligent method. Based on the model results, the estimated electrical conductivity in the study area had very good accuracy and high correlation with the measured values. As a result, ANFIS-FCM intelligent method is an effective method to diagnose the salty gypsum mine. If this method is used in groundwater around other salty gypsum mines in Iran and a similar result be observed, its efficiency in diagnosing the salty gypsum mines is confirmed.

In recent years, recovery of rare earth elements (REEs) from coal reserves as by products, in many countries has helped to alleviate the current raw material crisis. Due to the variety of research done in this field and the lack of a review article, doing this research is necessary. The purpose of this article is to review the geochemical distribution of rare earth elements in coal with an overview on Iranian coal. The results of this research show that the amount of heavy rare earth elements is usually higher than light coal rare earth elements than shales and chondrites. The proportion of Ce/Yb ratio in conventional shales is 4 to 6 and in coal and coal shales is about 7 to 8. Four sources for this enrichment have been proposed: 1. Organic origin, 2. Surface absorption by clay minerals in coal basins, 3. Mineral origin and 4. Sedimentation with organic matter during coal formation. Studies have also shown that the concentration of elements on the ash from coal combustion is much higher than coal itself. Extraction of these elements from the ash is easier than coal mining, which significantly reduces the environmental problems caused by the resulting ashes by combustion. The study of Alborz coal (Karmzad, Loshan, and Shahrood) and Central Iran (Tabas, Heshuni, Pabdana, Pudnee Springs, Hajdak) has shown that the grade of rare earth elements in Iranian coal is higher than the average grade of these elements in the upper crust and coal of the world such as China and America.

Due to the importance of food environment of the public dining places in promoting sustainable diets, the present study was carried out to analyze canteen menu of the School of Nutrition Sciences and Food Technology sustainability and to develop a sustainable lunch menus.

First, nutrition information and quantity per capita of foods served within the last 20 days were asked from the food service manager of the canteen during the second semester of 2019–2020. The frequency of each food served, as well as food waste durung their preparation and consumption were recorded. Quantities of carbon, water and land footprints, costs and nutrient-rich food (NRF) index of the foods in the  two menus  were calculated. Then, a sustainable food menu for each two menus was designed in order to minimize water, carbon and land footprints and cost, as well as maxmizing NRF  through goal programming method.

Foods served in Menu 1, had higher mean water (P=0.011), carbon (P=0.001) and land footprints (P=0.022) and higher costs (P=0.001) but lower NRF (P=0.001), compared to those served in Menu 2. The average daily non-compostable, compostable and recyclable wastes included 19660, 6320 and 9010 g, respectively. Replacing the sustainable food menu designed for Menu 1 could decrease carbon, total water and land footprints and costs by 10, 13, 22 and 6%, respectively, and increased the NRF profile by 8%. Furthermore, replacing the sustainable menu designed for Menu 2 could result in 25, 23, 27 and 28% decreases in carbon, total water and land footprints and costs, respectively, and increased the NRF profile by 23%.

Replacement of the current menus with sustainable ones and planning to decrease food wastes are recommended to achieve national targets of resistive economy and sustainable development and to promote sustainable diets.

Localization by the received signal Strength (RSS) measurement is inexpensive and has low computational complexity, thus extending the lifetime of the sensors in the wireless sensor network. The conventional propagation model for RSS has a log-normal distribution and since the probability density function is known, the best estimator for localization is Maximum Likelihood Estimator (MLE). The ML estimator is nonlinear and nonconvex and Gauss-Newton and convex optimization methods are presented in the papers. These methods impose a lot of complexity on the system and reduce the energy of the battery. In this paper, a two-step linear estimator is employed to solve the nonlinear ML estimator. In the first step, a new DRSS model is presented and nonlinear terms of ML cost function are replaced with linear variables. Also, in contrast to the estimators based on the conventional DRSS model, the performance of this estimator doesn't reduce by the random selection of the number 1 reference node. In the second step, the error of approximation of the first step is minimized, thus increasing the accuracy of the location estimation. Simulations show that in both the first and second steps, the accuracy is improved and the average error root error is reduced by up to 13% compared to the existing estimators.

Ophiolite outcrops and ophiolite clusters have spread widely in Iran. Ophiolite is referred to as a collection of mafic and voltramaphic rocks, which may be ordered or layered or interconnected by tensile stresses. Ophiolite; ophiolite complex, ophiolite series, was finally told that the color combination of the words' color combination (Kalrd melange) more applications. Due to the variety of research done in this field and the lack of a review article, a new research work has been done. The purpose of this article is to review the geochemistry and tectonic environment of the formation of ophiolitic zones of Iran. The results of this research show that in terms of dispersion, Iranian ophiolites are a type of melange that can be distinguished in the two groups of Zagros radiolarite ophiolite strips and Central Iranian tape. In the southwest of Zagros, there are two separate parts, called Ophiolite, Kermanshah and Nayriz. Central ophiolites, which are named after the submarine strips of central central (Sabzevar, north of Torbat Heydarieh, south of Birjand) and east of central Iran (Mako-Khoy, northern Makran and northern Nain) due to subduction, part of the upper mantle and the crust The ocean is left in the form of an ophiolite melange. Also, the results of many geochemical studies on Iranian ophiolites have shown the dependence of Mid-ocean ridge basalts (MORB) and island arc tholeiitic (IAT. Both groups of subalkaline and alkaline basalts have been identified in the ophiolites of Kermanshah. In the ophiolites of Neyriz and Babak, several types of basalt that have IAT attributes have been identified and reported. The chemical composition of Sabzevar ophiolite also shows the geochemical characteristics of the IAT type. Two types of basaltic lava have also been identified in the Ophiolite of the Ziarat (Bakhtar Makran).

This study aimed to examine the political culture, the Shiite women contribution in politics and its effect on Iranian women’s political culture. The research was carried out using a descriptive-analytical approach. The underlying assumption was that, although the political culture components in Iran such as authoritarian culture has been responsible for the decline of women participation in politics, due to the influence of the Iranian Shiite women’s political culture, the women political participation in certain periods of history has increased. For example, during the Islamic revolution under the supervision of Imam Khomeini (ra) the political participation of women has reached its peak. During the revolution, the role and contribution of women in politics for the first time became equal to that of men. The revolution was a manifestation of the political participation of women in Iran.

The main purpose of this research was to examine the model of evaluating efficiency of electronic learning strategies on students’ academic achievement. The methodology of research was correlation. Statistical community included all of the virtual universities’ students of Iran in 1390-91. The statistical sample was randomly selected (n=363). The data were gathered by three questionnaires (efficiency electronic learning strategies) ، = (0.94), α (academic interest) ، (α= 0.92) and comparing students’ score mean for two semesters. The validity of questionnaires has been prepared by specialist. The fundamental theory of this research was research community model of picciano and predicted that students cooperated with each other by social, teaching and cognitive presence and at last this cooperation results in their progress. The total results indicated that there was relationship between electronic learning strategies based on cognitive presence, social presence, teaching presence and students’ academic achievement. They have direct effects of the variables, such as cognitive presence (0.789), social presence (0.078), and teaching presence (0.695). The CFA shows that the measurement model fit the data very well with a goodness of fit index (AGFI) of 0.91 and adjusted goodness of fit index (GFI) of 0.95, RMSEA (0.214).

Today the quality of health service is determined by providing the service by appropriate operators (people)، within the shortest time and with minimum resonances. The aim of the study is to find the path of information and the errors in Hospital information system.

this study is done by the analytics method in which the hospital information system of Urmia Shahid Motahari Education center was analyzed، in doing so the technical errors also the human errors in the path of information from deferens parts of the hospital in the HIS system were found by using a prepared cheek list. Finely t he algorithm of errors or in other words، the path in which there was a high technical and human error were reported.

the finding show us that there is a great gap between the human errors and the education level of operators (P=0/000). In contrast there was a signatures difference between the human errors and different working times (P>0/05). Also there wasn’t a significant difference between the human errors and various parts of the hospital working with HIS (P<0/05). By analyzing the path of information in the system of HIS it was seen that maximum error occurs in the time shifts of nights and Holidays.

By paying attention to the changes in the needs of the Health area as time goes on، the information system should adapt itself to the changes also these changes should be in parallel with the changes in the structure and the missions so that it would fulfill the needs of operators and prevent errors.

One of the most important and complicated problems in medical ethics is to disclose the full truth about diagnosis of incurable diseases which leads to death، and each therapist may be encountered with it during the years of medical profession. The aim of this study was to survey on attitude of professors and residents of clinical wards to disclose the diagnosis for incurable patients leading to death.

In this descriptive study، sampling was carried out by a survey. All faculty members and their residents of teaching hospitals of Urmia University of Medical Sciences، Urmia، Iran، were surveyed as sample in 2007. Of 145 subjects، 138 responded to the questionnaire. The collected data were analyzed using Pearson and Spearman correlation tests with a p≤0. 05 being considered as significant.

In this study، the tendency to disclose the diagnosis among faculty members and residents was 64. 63%. Also، there was no significant relation between age، sex، university degree، educational field، years of service of the faculty members and residents of clinical wards with the tendency for telling the truth to incurable patients.

Final analyses revealed that the faculty members and clinical residents of different fields in terms of diagnosis disclosure do not have a definite idea. However، the majority of them agree to disclose the full truth about diagnoses.

Research is one of the most influential tools for developing students’ potential talents. This study aimed to assess students’ awareness, attitude, and performance regarding researching activities in the Urmia University of Medical Sciences.

Totally, in this descriptive-analytic study, we randomly selected 70 male and female students of medicine. They were (35 male and 35 female) between 21 and 36 years old. Likert question type inventories were used to determine students’ awareness and attitude toward the importance of research and their performance in this case. Findings were presented based on descriptive data analysis and tests.

The sum of positive responses to the question: “Are you interested in researching activities?” were 52 (74.3%) and the rest 18 students (25.7% of all test subjects) responded negatively. When they were asked: “Do you have enough time for researching activities?” the answer of 16 students (22.8%) was positive versus 54 (77.2%) of negative responses. Totally 8 students (11.4% of all test subjects) believed that there are enough lab equipment and facilities available. However, 48 students (68.6% of all test subjects) believed otherwise, and 14 students (20%) had no idea in this case. The research performance of students was evaluated as follows: poor for 35 students (50%); moderate for 28 students (40%); good for 5 students (7.1%) and excellent for 2 students (2.9%). The total average of attitude appraisal value was 77.85% for all 70 students.

The majority of students has plenty of time for doing research and do not have living and occupational difficulties. The lack of proper informing policy and integrated motivating programs are the cause for the lack of interest toward researching activities among students.