The study of the motor gasoline blended with superior kerosene (SK) and high speed diesel, HSD (mixture of hydrocarbon with high aromatic content) revealed that distillation parameter gives the basic idea or significant role of adulteration. The motor gasoline laboratory blends give an idea that about 4% of SK and 2% of HSD can be adulterated based on the EURO-III specification and parameter does not show the control point of adulteration. The distillation test attempt to realize that whether the Motor gasoline is adulterated with Superior Kerosene. The Motor gasoline laboratory blends analysis has made finger print region with deviation of+1% and correlated with the data.

This research studies the model reference adaptive control strategy based on the fuzzy theory to control a wind turbine with a doubly-fed induction generator (DFIG). The model reference adaptive control method, incorporating Takagi-Sugeno (T-S) fuzzy logic, is proposed to control the turbine rotor speed using a pitch angle control. The aim of the proposed control system is to address the shortcomings of the traditional wind turbine controllers, such as unknown dynamics and system nonlinearities. The proposed hybrid adaptive-fuzzy structure provides an effective tool for controlling the wind turbine system, which exhibits complex nonlinear dynamics. The superiority of the proposed method over the traditional model reference adaptive control lies in modeling the nonlinear system with multiple fuzzy linear models instead of a single linear model. Additionally, the use of the fuzzy method enhances the adaptability of this control method, resulting in more accurate outcomes. Stability analysis of the closed-loop system with the proposed fuzzy model reference adaptive control (FMRAC) is conducted using the Lyapunov method. The proposed FMRAC method is simulated for a 0.2 Mw variable speed wind Turbine and compared with the traditional model reference adaptive control. The simulation results of the proposed method demonstrate higher performance and an accurate response despite the unknown dynamics and nonlinearities of the model.

Introduction: The expected values of hematologic and serum biochemical parameters in domestic animal species can be affected by breed, age, environment, and nutrition. Established breed-specific reference intervals (RI) are an important tool for monitoring the health of sheep. There is a lack of published data on biochemical RI for Sngsari sheep. Thus, the aims of this study were to establish RI for select of serum biochemical parameters for Sangsari sheep by reference Value Advisor (RVA) method and provide information on the studied parameters for both sex of this breed in order to form a basis for clinical interpretation. Materials and Methods: Sixty healthy Sangsari sheep including 26 ewes and 34 rams (2– 4 years old) were chosen from the breeding station of Sangsari sheep among 150 sheep in Damghan, Semnan, Iran. The type of feeding, all the animals had free access to water and to good-quality alfalfa hay (90. 0 % DM, 15. 8 CP % DM, 50. 4NDF%DM, 31. 6ADF%DM, 5. 8 lignin% DM, and 2. 2 EE % DM). Concentrate (23 % oats, 36 % corn, 38 % barley, and 3%mineral and vitamin supplements) was provided once daily (200 g per animal per day). In the sampling day, breeder signed a subscription form and completed a primary questionnaire consisting of specific questions about past and current health status, sexual status, medications used, and familial and reproductive medical history. Complete physical examinations were performed by the same experienced veterinarian on each sheep. In order to reduce stress, blood samples were taken in the station with minimal changes in the usual schedule of the sheep. Blood samples (taken from the jugular vein) were collected in simple tubes in order to separate the serum (centrifuged at 3000 rpm for 10 min) for biochemical analysis. Samples transported at +4 ° C to the laboratory department of the Faculty of Veterinary Medicine, Semnan, Iran. Biochemical parameters were measured by a autoanalyzer. These parameters included alkaline phosphatase (ALP), gamma glutamyletransferase (GGT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), total protein (TP) and albumin (Alb). For statistical analysis, data were analyzed by reference Value Advisor and outliers were deleted if detected according to Tukey or Dixon. RIs, according to sample size, were determined using a robust method and following Box-Cox transformation of data. The data were normally distributed, and differences between sexes in biochemical parameters were analyzed using independent sample T test. A value of P<0. 05 was considered as significant. Results and Discussion: The RI of biochemical parameters obtained from adult healthy Sangsari sheep includes the following: ALP 49. 24-564. 84 u/l; GGT 24. 14-62. 23 u/l; AST 10. 86-338. 40 u/l; BUN 6. 91-26. 43 mg/dl; TP 5. 19-13. 95 gr/dl and Alb 0. 92-3. 63 gr/dl. Established RI of biochemical parameters for ewes and rams, respectively including: ALP 29. 98-702. 89 u/l; GGT 22. 41-54. 49 u/l; AST 1. 36-279. 89 u/l; BUN 5. 9526. 86 mg/dl; TP 5. 75-12. 83 gr/dl; Alb 0. 84-2. 77 gr/dl and ALP 106. 08-568. 55 u/l; GGT 20. 80-58. 30 u/l; AST 360. 12 u/l; BUN 8. 15-26. 04 mg/dl; TP 4. 66-15. 59 g/dl and Alb 0. 74-3. 77 g/dl. Interpretation of the biochemical results in different breeds of sheep, with regard to RI for each parameter, in conjunction with history, clinical findings and other paraclinical tests helps the clinician to reach a definitive diagnosis. A unique feature of Sangsari sheep is that they are highly adaptable with desert and mountain ranges with high tolerance of drought conditions. This breed is also relatively small size and light weight, and most studies have focused on genetic characteristics associated with this trait. In view of the characteristics mentioned above and considering the lack of reference range for biochemical parameters, it is necessary to determine reference intervals in Sangsari sheep. In order to establish a comprehensive reference interval in Sangsari sheep, a select biochemical parameters were evaluated in the present study. Almost most of the established RI for biochemical parameters in this study differed from previously published RI, so that the lower and upper limits of RI of theses parameters (with the exception of BUN) were lower and higher than the values previously reported. Differences between obtained RI for the Sangsari sheep and previously reported RI for other breeds may be attributed to variations in hormonal influences, hydration status, dietary differences, or adaptations to a desert environment, age, breed, season of study and analytic method. Conclusion: The obtained data provided reference interval for biochemical parameters in Sangsari sheep for the first time. Present study demonstrates significant differences in most of the biochemical parameters. reference intervals determined in this study provide a baseline for interpreting biochemical results in Sangsari sheep, and contribute to optimization of the management of this species.

Background & Objective: In addition to pyramidal neurons and interneurons, the hippocampus contains Astrocytes that play important roles in regulating ion flux currents, energy production, neurotransmitter release and memory. Learning needs some instrument for information storage and information maintenances mechanisms resemble to memory. The aim of this study was determination of spatial memory effect on the number of astrocytes in rat’s hippocampus.Materials & Methods: In this experimental study, with usage of Morris Water Maze and reference memory technique, we used 10 male albino wistar rats. 5 rats were in control group and 5 rats in reference memory group. After histological preparation, the slides were stained with PTAH staining for showing the Astrocytes. Results: The findings of this study showed significant difference in astrocytes number in CA1, CA2 and CA3 area of hippocampus between control and reference memory group. The mean and SD of astrocytes in CA1, CA2 and CA3 of reference memory group were 118.57±25.29, 58.91±23.59 and 116.6±31.14, that they are more than control group with 49±17.29 in CA1, 48.8±25.21 in CA2 and 41.95±11.22 in CA3. Conclusion: We concluded that the number of astrocytes increased due to spatial learning (e.g. reference memory method).

AbstractBackground and Objectives: Evapotranspiration is considered as the water requirement for plants. Therefore, its measurement is necessary for all agricultural and irrigation projects. Evapotranspiration is one of the main components of the hydrological cycle associated with agricultural systems. Usually, evapotranspiration can be obtained using reference evapotranspiration (ET0). Accurate estimation and prediction of ET0 is essential in managing water resources, planning irrigation, and determining the water requirement of plants. Prediction of the ET0 by providing information about the future state in different time scales can help to make appropriate decisions, plan, and apply water resources management methods. Also, assessing agricultural drought conditions by well-known indices such as the Standardized Precipitation-Evaporation Index (SPEI) and Palmer Drought Severity Index (PDSI) directly requires ET0 of the region. The sharp decrease in the level of Lake Urmia and the threat to the region's ecosystem have also made the need for accurate calculation of ET0 more significant than in the past. One of the solutions to calculate ET0 is to use the FAO-56 Penman-Mantis equation (FAO-56 PM), an acceptable alternative for the scarce lysimeter data. However, the Penman-Mantis equation is highly dependent on the wind speed parameter, so a small error in the wind speed measurement causes a significant error. Therefore, this study aims to provide an innovative and reliable model for estimating ET0 without the need for wind speed parameters in Tabriz and Urmia stations.Methodology: In this study, to predict daily ET0 different intelligent models including multi-layer perceptron neural network (ANN-MLP), support vector regression (SVR), and support vector regression combined with firefly algorithm (SVR-FFA) were used in Urmia and Tabriz stations during 2002-2022 period. The input parameters of the models included minimum relative humidity (RHmin), maximum relative humidity (RHmax), average relative humidity (RHavg), sunshine hours (SSH), minimum temperature (Tmin), maximum temperature (Tmax), average temperature (Tavg), and average soil temperature (Tsoil) which were obtained from Iran Meteorological Organization (IRIMO). Also, four different scenarios were used to run the models. The selection of different input combinations was based on the correlation coefficient, so the first combination had the lowest correlation and the last combination had the highest correlation concerning ET0. Also, data from 2002-2015 for 14 years were considered for model training and from 2016-2022 for 6 years for model testing. Correlation coefficient (R), mean absolute error (MAE), root mean square error (RMSE), and normalized root mean square error (NRMSE) indices were used to evaluate the used models.Findings: The comparison and evaluation of the models used in Tabriz station showed that the SVR-FFA-4 model was chosen as the best model in this station with the root mean square error of 1.23 mm day-1. Among the SVR models, the SVR-4 model showed a good performance with the root mean square error of 1.95 mm day-1 after the combined model. Finally, the ANN-4 model also obtained an acceptable accuracy compared to other ANN combinations by having the root mean square error of 1.99 mm day-1. Finally, the evaluation of the results used for the Urmia station shows that the SVR-FFA-3 model has made the best predictions compared to other models with a root mean square error of 1.16mm day-1. The SVR-3 and SVR-4 models had a higher accuracy than other SVR combinations with a root mean square error of 1.78 mm day-1, but the third scenario was chosen as the appropriate model in the SVR model due to having less input. Among the ANN combinations, the ANN-3 model has a good performance compared to the other combinations of this model with the root mean square error of 1.81 mm day-1.Conclusion: The results of this study showed that in both studied stations, the hybrid model showed higher accuracy than the individual models. So, in Tabriz station, the SVR-FFA-4 model had the best performance with an error rate of 1.23 mm day-1. In the Urmia station, the SVR-FFA-3 model showed good accuracy with an error rate of 1.16 mm day-1. Finally, it is suggested to use the hybrid model to predict the daily reference evapotranspiration in the northwest of the country. One of the limitations of this research is the lack of access to the parameters of dew point temperature and solar radiation. Therefore, it is suggested to use these parameters in the subsequent studies.

In this study, the effectiveness of these measures in reduction of vehicles speed has been considered, considering the extensive use of speed humps and humps as physical traffic calming measures in Iran, especially in the northern provinces (due to high accesses, interference of social roles and displacement of road, and the significant difference between speed of vehicles and speed limit). This study was carried out to determine the relationship between geometric characteristics of humps and vehicles speed in 90 different areas of roads in eastern part of Mazandaran province. Since the studied sample consisted of all types of humps, including arches and beds and they performed in different functional classes of roads, they were categorized for better examination and Separately, each geometric feature was identified. and the speed of vehicles were determined individually around them. The speed of the vehicle was recorded at a few points before, on the humps and then it was recorded using a speedometer camera, and their dimensions were surveyed accurately by using the Total Station camera. Finally, data was evaluated using linear regression model in SPSS software and has been presented the main factors affecting vehicle speed reduction and models related to speed reduction. Considering the high number of selected humps in the study, the results of this research showed that it is possible to use these models to design and implement humps for passage speed and different specific speeds; in addition, these models could evaluate the effectiveness of the humps in speed reduction, and determine the speed profile at different distances from the humps in a high level of confidence.

Background: Determination of the correct working length is one of the main factors that lead to success in root canal therapy. This laboratory study aimed to compare the accuracy of conventional (F, E-speed) radiography and Complementary Metal Oxide Semiconductor (CMOS) digital radiography in working length measurement.Materials and Methods: In this laboratory study, access cavities were prepared in 40 extracted maxillary central incisors with straight and single canals. Size 15 K-file was introduced into the each canal until it was appeared through the apical foramen. The file was then removed and measured by a digital caliper with precision of 0.01 mm. Actual working length was considered 1 mm less than the measurement showed by the caliper (Gold standard). At the next stage, each tooth together with its related K-file was positioned in a dried skull and then, periapical conventional and digital radiographies were taken with parallel technique. All the radiographs were measured by two radiologists. Statistical analysis was performed using repeated measures ANOVA and paired t-test.Results: No statistically significant difference was observed between conventional and digital radiographies regarding working length measurement (P>0.05). Conventional and digital radiographies demonstrated significantly higher scores of working length measurement compared to the Gold standard (P<0.001).Conclusion: Although CMOS had no significant superiority over conventional radiography, if both techniques are available, using CMOS is recommended due to significant reduction of radiation dose.