Determination and evaluation of principal minerals in Negella sativa by atomic absorption technical methods were showed, using wet ashing method. This work was done on Negella sativa because of wide using of this plant in many formulations ( in food or medicine ).two types of atomic absorptions were used : first, flame atomic absorption spectroscopy, for minerals of high concentrations such as, Na, Mg, K, Fe, Ca, Li, Ni, Zn, Mn, Cu. Second, flameless atomic absorption spectroscopy, for minerals of low concentrations such as, Al, Si, V, B, Pb, Co, Cd, Cr ,Si, Hg, Sn .The results showed the existence of many minerals in Negella sativa useful to human sanity with acceptable dietary allowance. On other side, the presence of harmful m

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

Blood samples were collected from (31) pregnant women infected with cytomegalovirus , also (15) blood samples were collected from congenitally infected infants, and (20),(15),(15) blood samples were collected from pregnant women ,non pregnant and infants, respectively, all of them were as control groups. CMV infection identified by using ELISA assay to detect specific CMV IgM & IgG in sera. The results of lymphocyte transformation showed a significant decrease when phytoheamagglutinin (PHA) used as stimulator, lymphocytes response in infected pregnant women was lower than that of non infected pregnant women as well as non pregnant women. Result also showed a significant decrease in the ability of lymphocyte division in healthy pregnant w

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.