فهرست مطالب haniyeh asadi

Surface-modifying biomaterials have the potential to improve both the performance and durability of dental implantable products that are currently in use. Dental implants' surfaces may be modified to improve their biocompatibility and other biologically significant characteristics using metal and metal oxide nanoparticle coatings. The toxicity of the materials used in the synthesis, the requirement for high temperature and energy, and the high cost are just a few of the factors that restrict the use of the various physical and chemical methods for the synthesis of metal nanoparticles. Though, these restrictions can be overcome by developing substitute synthetic approaches that are similar to Green Synthesis and have proven to be more eco-friendly and less toxic, including the use of algae, microorganisms, and plants. Metal ions can be readily reduced into nanoparticles by plants' biomolecules, secondary metabolites, and coenzymes. Although still in its infancy, the use of metal nanoparticles produced through green synthesis in dental implants has the potential to open up new avenues for enhancing the caliber of these goods.

In fact determine a reliable models and selection of inputs with proper temporal delay for river flow forecasting is a key topic for watershed managers, hydrologists, river engineers. In recent decades use of intelligent algorithms and fuzzy collection theories for modeling of hydrological phenomena that have complexity and uncertainly, has been noticed by researchers. In this regard, in the present study was used adaptive neuro-fuzzy inference system (ANFIS) and different input patterns of flow discharge (with daily time steps up to 7 days ago) in order to river flow forecast of Kasilian catchment. Then in order to further investigate of this process artificial neural network (ANN) model was used and the results were evaluated using quantitative statistics including coefficient of determination (R2) and root mean square error (RMSE). In ANFIS model the results of river flow prediction was improved up 4-day step and afterward decreased while in ANN up 5-day step improved. Evaluation of quantitative statistics values for the best patterns of two models applied during validation period indicated that ANFIS (R2 = 0.60, RMSE = 0.64) had high accuracy than ANN (R2 = 0.51, RMSE = 1.74) in river flow forecasting.

Accurate estimation of transported sediment by rivers plays an important role in water resources management. So the selection of proper methods for estimation of suspended sediment is an important objective. In this regard, application of intelligence models (e.g., ANN, SVR) have substantially improved the prediction of suspended sediment. An important step in suspended sediment modeling using these models is, the proper input selection because input vectors determine the structure of the model and, hence, can influence model results. In the most studies, only climatic and hydrological variables have been used as suspended sediment estimators using data-driven models. Therefore, this study was designed to determine effective and accessible geomorpholigical variables based on hydrologic understanding in suspended sediment estimation for the Tamar catchment. To accomplish this goal, the effect of an Index of Connectivity (IC) as a hydrogeomorphic input, in addition to the hydrologic inputs, using ANN and SVR models was investigated. Comparison of results indicated that using IC along with hydrological inputs improve models efficiency and this improvement is indicated by decrease in the root mean squared error (9.63% and 26.36%) and a noticeable increase in the Nash–Sutcliffe efficiency (25.80% and 21.85%) and in the coefficient of determination (13.20% and 45.94%) for ANN and SVR models, respectively. These results are valuable for water resources planning and management.

Estimation of runoff in ungauged catchments has been an important subject for experts in planning of various projects. Focus of this study was on comparison and evaluation of Clark’s model and time- area method in predicting output hydrograph in watersheds with lack of basic data. To this end, the time-area histogram was drawn by ArcGIS and the topographic map. Then, using rain gauge data and time-area method, the output hydrograph was estimated. In the next step, the obtained results were compared with the observed output hydrograph. Afterwards the Clark instantaneous unit hydrograph was also estimated using storage coefficient in order to simulate the unit hydrograph in Kasilian watershed. The storage coefficient was estimated using graphical, Clark, Linsley, Mitchell, Johnstone-Cross, Eaton, Hoyt-Langbein, Nash, Carter, Morgan-Johnson and Bell methods. Results were compared using quantitative statistics of root mean square of error, bias in peak discharge, coefficient of efficiency, and relative errors in peak discharge, time to peak and base time. The comparison of results showed that graphical method has had the highest accuracy in estimation of storage coefficient. Also The comparison of results showed that the Clark’s model had a good efficiency rather than time-area method and this showed effect of storage coefficient in flood routing in Kasilian watershed. So this method can be used with more accuracy to estimate output hydrograph in watershed with lack of basic data.

The present study was conducted to study the effect of storage coefficient on estimating the output hydrograph in a watershed which lacks basic data, using time- area method and Clark’s model. To this end, the time area histogram was determined by ArcGIS and the topographic map of the area. Then, using rain gauge data and time-area method, the output hydrograph was estimated. In the next step, the obtained results were compared with the observed output hydrograph. The Clark instantaneous unit hydrograph was also estimated by using storage coefficient in order to simulate the hydrograph in Kasilian watershed. As for the unit hydrograph, the statistical values of root mean square of error, bias in peak discharge, coefficient of efficiency, and relative errors in peak discharge, time to peak and base time were 1.64, 0.90, 0.76, 11.38, 33.33 and 15.38%, respectively. The results showed that Clark’s model was more efficient compared to time area method which is indicative of the effect of storage coefficient on flood routing in Kasilian forest watershed. Therefore, this method can be used to accurately estimate the output hydrograph in forest watershed when there is a lack of basic data.

The proper application of instantaneous unit hydrograph theory is very efficient for watershed with lack of rainfall data. Therefore، the present study has been conducted to evaluate the efficiency of Clark instantaneous unit hydrograph model with the help of geographical information system in regenerating flood unit hydrograph in Kasilian watershed in Mazandaran province. The comparative evaluation is conducted between the 3h-unit hydrographs simulated using Clark model and the one obtained from averaging the observed ones. This comparison is made with the help of statistical criteria viz. relative error، root mean square of error، coefficient of efficiency and bias. It verified high level of compatibility between two unit hydrographs using the Clark model and the hydrograph obtained by averaging the observed data.