raisin on mice in comparison with negative (phosphate buffer saline (PBS) and positive Mitomycin-C (MMC) controls. Moreover, the effect on fertility hormones (follicles stimulation hormone/FSH, lutenising hormone/LH) was also measured. The effect of the extracted samples were measured by employing cytogenetic analysis which included (the mitotic index (MI), chromosomal aberrations (CAs) and micronucleus (MN)) parameters. Results showed that significant increase in MI and significant reduction in both CAs and MN percentage were seen after treatment with both alcoholic and water extracts of the two raisins and alcoholic extracts was more effective than water extracts. On the other hand both the gold and black raisin enhanced the levels of the

This study was designed to test the effect of the treatment with aqueous extract of carrot seeds( Daucus carota) on fertility of male albino mice by effected on Body weight , testis weight ,secondary sex organs (prostate , seminal vesicle) and sperms properties .This experiment used (24) albino male mice aged(8-10)weeks. these animals were randomly divided into three groups contain two doses (200,400mgkg) were used from both extracts ,they were daily and orally given for (35)days ,and control group was given physiological saline. After the end of the experiment the animals were sacrificed after taken their body weights. The results were show: 1. A significant (p<0.05) increase in body weight and reproductive organs. 2

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Vapor-liquid equilibrium data are presented for the binary systems n-hexane - 1-propanol, benzene - 1-propanol and n-hexane – benzene at 760 mm of mercury pressure. In addition ternary data are presented at selected compositions with respect to the 1-propanol in the 1-propanol, benzene, n-hexane system at 760 mmHg. The results indicate the relative volatility of n-hexane relative to benzene increases appreciably with addition of 1-propanol.