This work was conducted to study the extraction of pelletierine sulphate from Punica granatum L. roots by liquid membrane techniques. Pelletierine sulphate is used widely in medicine. The general behavior of extraction process indicates that pelletierine conversion increased with increasing the number of stages and the discs rotation speed but high rotation speed was not favored because of the increased risk of droplet formation during the operation. The pH of feed and acceptor solution was also important. The results exhibit that the highest pelletierine conversion was obtained when using two stages, (10 rpm) discs speed of stainless steel discs, (pH=9.5) of feed solution and (pH=2) of acceptor solution in n-decane. Assuming the existen

The geometric morphometric technique was used to study the variables in the shape and size wings of different populations of mosquitoes Culex quinquefasciatus from different Iraqi provinces Babylon, Baghdad and Wasit. The results showed that the average of centroid size were 366, 387.5 and 407.4 Micron in Babylon, Baghdad and Kut, respectively. The statistical analysis showed that there were no significant differences in the average of centroid size of all specimens and they belong to the same species.

Mishrif Formation regards one of the most important reservoirs in Iraq. Well logging represents one of the most important tool in the formation evaluation. According to the Petrophysical properties that have been gotten from well logging, Mishrif Formation in terms of reservoirs units, consist of several reservoirs units. Major reservoirs units divided into three reservoir units,MA,MB&MC. Each of these major units divided into minor reservoirs units (MB11,MB12,MC2&MC3).MB major reservoir units represent the best reservoir unit. These reservoirs units separated by cap rocks(mainly tight limestone)(CR1,CR2,CR3,CR4,CR5,CR6,and CR7).CPI were demonstrated for all wells.Hydrocarbon saturation vs.

     Disequilibrium compaction, sometimes referred to as under compaction, has been identified as a major mechanism of abnormal pore pressure buildup in sedimentary basins. This is attributed to the interplay between the rate at which sediments are deposited and the rate at which fluids associated with the sediments are expelled with respect to burial depth. The purpose of this research is to analyze the mechanisms associated with abnormal pore pressure regime in the sedimentary formation. The study area “Jay field” is an offshore Niger Delta susceptible to abnormal pore pressure regime in the Agbada –Akata formations of the basin. Well log analysis and cross plots were applied to determine the unde

The current research discusses the jurisprudence of the argumentative meaning in the Qur’an, and it is one of the general methods of responses in the Qur’an, as well as the argumentative approach to the recitations of the readers and directing their meanings. I have chosen a model for three verses from Surat Al-An’am, in which there are seven frequent recitations and seven odd ones, on a topic related to theology and faith; It forms the centerpiece of the argument verses in Surat Al-An'am; It contains the jurisprudence of dealing with infidels and dissenters, turning away and forbidding insulting what they claim besides God in the event of corruption, and God Almighty’s decree and wisdom in the occurrence of unbeli

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

     This paper presents an IoT smart building platform with fog and cloud computing capable of performing near real-time predictive analytics in fog nodes. The researchers explained thoroughly the internet of things in smart buildings, the big data analytics, and the fog and cloud computing technologies. They then presented the smart platform, its requirements, and its components. The datasets on which the analytics will be run will be displayed. The linear regression and the support vector regression data mining techniques are presented. Those two machine learning models are implemented with the appropriate techniques, starting by cleaning and preparing the data visualization and uncovering hidden information about the behavior of