The reaction paths of the C-C and C-H bond cleavage in the anthracene and phenanthrene aromatic molecules are studied by applying the ab-initio DFT method. It is found that the C-C bond cleavage proceeds via a singlet aromatic transition state, compelled through a disrotatoric ring opening reaction. A suprafacial H atom shift follows the transition state, leading to the formation of a methylene -CH2 and an acetylenic or allenic moiety. The calculated activation energies for anthracene range from 158.81-208.90 kcal/mol and the reaction energies from 96.106-156.976 kcal/mol. For phenanthrene, the energy values are 157.39-202.34 kcal/mol and 62.639-182.423 kcal/mol, respectively. For the C-H cleavage reactions, the calculated reaction energies

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

The five-a- Side Soccer for simple mental disability is as interesting and caring as many other sporting events. Therefore, the researchers believe that their basic skills tests are compatible with then level of the tested individuals in terms of age and mental ability. As a means of selecting those who are qualified to practice this game in a simple way, the problem of research has been identified in the design and standardization of two scoring skills that belong to this category and are approved by the training staff during the initial selection process. The research community is determined by people with mental disabilities who belong to the governmental and private institutes and the Special Olympics Union in Baghdad and for the year 2

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