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

The isolation and characterization of Escherichia coli O157:H7 strains from 22 out of 174 fecal samples from petting zoo animals representing twenty‐two different species (camel, lion, goats, zebra, bear, baboon monkey, Siberian monkey, deer, elk, llama, pony, horses, fox, kangaroo, wolf, porcupine, chickens, tiger, ostrich, hyena, dogs, and wildcats) were investigated. One petting Al‐Zawraa zoological society of Baghdad was investigated for E. coli O157:H7 over a 16‐month period that spanned two summer and two autumn seasons. Variation in the occurrence of E. coli O157:H7‐positive petting zoo animals was observed, with animals being culture pos

Hydroxide upon the chemical composition and dry matter(DM) and organic matter(OM) digestibility . Rice straw was treated with 4% sodium hydroxide using 30% of DM basis moisture, and incubated at 40 ºC for 40 days., DM digestibility (DMD) was significantly affected (P<0.01) by the treatment , where DMD increased The objective of this experiment was to study the effect of physical form (long ,chopped and ground ) and washing rice straw treated with sodium from 42.32 to 45.41% , OM digestibility (OMD) and total digestible nutrient (TDN) increased(P<0.05) from 47.38 and 49.33 to 49.67 and 52.83% ,respectively. While hemicellulose content increased (P<0.05 ) from 261.71 to 268.17 gm/kg DM ,and metabolizable energy (ME) from 7.11 to 7.48 MJ/

Background: Propolis has received great interest because of its wide range antimicrobial activity. Propolis also called (bee glue) due to its collection by (Apismellifera) honeybees from various plants resinous substance. The aim of this study was to determine the antibacterial effect of propolis extracts (aqueous and alcoholic) on anaerobic periodontal pathogen namely Aggregatibacteractinomycetemcomitans. Materials and Methods: Strains of Aggregatibacter actinomycetemcomitans wasisolated from pockets of systemically healthy patients aged between 35-55 years old suffering from chronic periodontitis with pocket depths of 5-6 mm, the bacteria cultured on special blood Agar plates solid media. Propolis was extracted by using water and alcohol.

Background: Herbs are being widely explored to discover alternatives to synthetic antibacterial agents.Small Cardamom often referred to as queen of spices because of its very pleasant aroma and taste, have a history as old as human race. Most people use cardamom as a spice and are largely unaware of its numerous health benefits. The purpose of this study was to evaluate the effect of different concentrations of water and alcoholic cardamom extracts on sensitivities, growth, and adherence of Mutans streptococci in vitro. Materials and Methods: In this study, saliva was collected from ten volunteers (College students 18-22 years). Agar well technique was used to study the sensitivities of Mutans streptococci to different concentrations of s

Background: Multi- drug resistant (MDR) Staphylococcus aureus infections have become a major public health concern in both hospital and community settings.Objective: to investigate the antibacterial activity of T. Foenum- groecum essential oil against skin infection with S. aureus and to study probable synergistic activity in combination with Clindamycin.Type of the study: Cross-sectional study.

Methods: Antibacterial activity of T. Foenum- groecum essential oil extract (1.2gm/100 µl) was investigated in multi- drug resistance (MDR) Staphylococcus aureus specimen isolated from patients with skin infection in Baghdad. T. Foenum- groecum use externally for cellulites and skin inflammation due to the presence of diosgenin .fast liq

Background: Spices and herbs have been used by many cultures to enhance the flavor and aroma of food and for their medicinal value. Black cardamom is one of these spices widely used in cooking because of its unique taste and powerful flavor. The aim of study was to test the effect of black cardamom on Mutans Streptococci in comparison to chlorhexidine gluconate (0.2%) and de-ionized water. Materials and methods: Dried fruits of black cardamom were extracted by using alcohol (70% ethanol). Saliva was collected from seven volunteers. Agar well technique with different concentrations of black cardamom extracts was used to test the sensitivities of Mutans Streptococci, as well black cardamom extracts effect on viable counts of Mutans Streptococ

Stimulative effect of 10 mW He-Ne laser on the phagocytic activity of human polymorphonuclear leukocytes( PMNs) has been studied in vitro. Normal polymorphonuclear leucocytes were isolated from the human peripheral blood. A mixture of 0.25 ml of Hanks solution, 0.25 ml of serum, 0.25 ml of Candida albicans suspension and 0.25 ml of PMNs suspension was prepared. The samples of mixture of PMNs and Candida were subdivided in 1 ml ependrof tubes and irradiated to He-Ne laser for 1, 3, 5, 10 and 20 min. The diameter of the irradiated area was 0.8 cm. For calculation of Phagocytic index before and after irradiation, the samples were incubated (37°C) at 5, 15, 30, 60 min. The slides of samples were prepared and stained using Giemsa stain. The

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.