The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Previous data indicated the effectiveness of silibinin as intraocular pressure (IOP) - lowering agent.  The present study was performed to evaluate the interaction of silibinin with pilocarpine or cyclopentolate in lowering IOP in normotensive rabbits. The effects of topically instilled silibinin hemisuccinate solution (0.75%) alone or adjunctly combined with 2% pilocarpine or 1% cyclopentolate on the IOP of normotensive rabbits were evaluated using indentation tonometry. The results showed that 0.75% solution of silibinin was found more potent than pilocarpine (2% drops) in lowering IOP of normotensive rabbits, while their combination results in longer duration of action. Moreover, the elevated IOP values produced by cyclopentolate

Previous data indicated the effectiveness of silibinin as intraocular pressure (IOP) - lowering agent. The present study was performed to evaluate the interaction of silibinin with pilocarpine or cyclopentolate in lowering IOP in normotensive rabbits. The effects of topically instilled silibinin hemisuccinate solution (0.75%) alone or adjunctly combined with 2% pilocarpine or 1% cyclopentolate on the IOP of normotensive rabbits were evaluated using indentation tonometry. The results showed that 0.75% solution of silibinin was found more potent than pilocarpine (2% drops) in lowering IOP of normotensive rabbits, while their combination results in longer duration of action. Moreover, the elevated IOP values produced by cyclopentolate (1%drops

Background: It is well-known that silicon oil (SO) injection into the vitreous cavity after pars plana vitrectomy is usually associated with high intraocular pressure.

Objectives: To determine the influence of silicon oil (SO) removal on IOP level after pars plana vitrectomy for spontaneous rhegmatogenous retinal detachment (RRD)

Subjects and Methods: A prospective study was conducted at Ibn Al-Haitham eye teaching hospital, Baghdad- Iraq. Intraocular pressure (IOP) was measured pre and post SO removal in patients who have underwent retinal detachment surgery with SO injection of 1000 centistokes (cSt) viscosity. Baseline IOP was measured for all the patient before the SO