The taxonomy of Ficus L., 1753 species is confusing because of the intense morphological variability and the ambiguity of the taxa. This study handled 36 macro-morphological characteristics to clarify the taxonomic identity of the taxa. The study revealed that Ficus is represented in the Egyptian gardens with forty-one taxa; 33 species, 4 subspecies and 4 varieties, and classified into five subgenera: Ficus Corner, 1960; Terega Raf., 1838; Sycomorus Raf., 1838; Synoecia (Miq.) Miq., 1867, and Spherosuke Raf.,1838; out of them seven were misidentified. Amongst, four new Ficus taxa were recently introduced to Egypt namely: F. lingua subsp. lingua Warb. ex De Wild. & T. Durand, 1901; F. pumila L., 1753; F. rumphii Blume, 1825, and F. su

        In current study, the dye from flowers petals of Strelitzia reginae used for the first time to prepare natural photosensitizer for DSSC fabrication. Among five different solvents used to extract the natural dye from S. reginae flowers, the ethanol extract of anthocyanin dye revealed higher absorption spectrum of 0.757a.u. at wavelength of 454nm.  A major effect of temperature was studied to increase the extraction yield. The results show that the optimal temperature was 70 °C and there was a sharp decrease of dye concentration from 0.827 at temperature of 70 °C to 0.521 at temperature of 90°C. The extract solution of flowers of S. reginae showed higher concentration in acidic media, especially at pH 4 (0.902). The

Background: Extracorporeal Shock wave lithotripsy (ESWL) is widely used in treating patients with ureteralstones because it is effective, safe, and noninvasive. Based on factors such as size and the location of stones,there is a significant variation in the overall stone-free rate (SFR).Aim of the study: To evaluate the effect of ureteral wall thickness (UWT), stone attenuation, the time fromfirst attack of pain till first session of ESWL and stone/ rib density on the outcome of SWL in the treatmentof upper ureteral stones (UUS).Patient and methods: A prospective study when 127 patients with radio-opaque UUS ranging from 7 to 20mm and treated by ESWL were included in this study. The effect of (stone/ 12th rib) density by KUB, ureter

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Among a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species  to  the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl