The study aims to biosynthesized of sliver nanoparticle from aqueous extract of olive leave and evaluate the effectiveness of the synthesis AgNPs against isolated fungi. The study mediating fifty samples were taken from various tools in laboratory from five hospitals in Baghdad. Four species of fungi were identified depending on the morphological and microscopic characteristics. The most common isolated fungi based on their frequency ratio were as follows Aspergillus niger 87.5%, Aspergillus flavus 62.5%, Aspergillus fumigatus 53.5% and Aspergillus nidulans 37.7%.The Biosynthesis of silver nanoparticle developed a rapid, eco-friendly and convenient green method for the stable silver nanoparticles (AgNPs) were synthesised with an average diameter of 30 ± 60 nm and like spherical in shape, using the aqueous solution of the Olive tree (Olea europaea) leaves extract.The reaction is carried out at 10-3M of silver nitrate. The AgNPs synthesized were confirmed by their change of color to (dark brown-grey). The characterization was studied using UV-Visible spectroscopy, Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Inhibition effect of AgNPs against fungi has been studied using well diffusion method by studying the effect of different concentration (100, 75, 50 and 25). The results revealed that the AgNPs have considerable antifungal activity comparison with alcohol. The obtained results indicate that the highest level of inhibition zone was detected at the concentration of 100 µg/ml of AgNPs, where the inhibition zones are (23.33 ± 4.41) for A. flavus and the lowest level of inhibition zone was detected at the concentration 25 µg/ml of AgNPs ,where the inhibition zones are (6.00 ± 1.15) for A.nidalus. While using alcohol the highest level of inhibition zone was detected at the concentration of 100 µg/ml of Alcohol, where the inhibition zones are (12.33 ± 1.45) for A.nidalus, and the lowest level of inhibition zone was detected at the concentration 25 µg/ml of Alcohol ,where the inhibition zones are (4.67± 0.33) for A.flavus.
Laser drilling is capable of producing small, precisely positioned holes with high degree of reproductively. In this paper , IR millisecond Nd:YAG single pulsed laser was used to determine the effect of laser parameters on the drilled hole of the glass - fiber reinforced epoxy composite FR-4 sample of 2 mm in thickness . The type of laser source was GSI lumonics JK760TR Series laser 1.064μm system in a CNC cabin. The JK760TR series has a 0.3-50ms pulse length and a maximum repetition rate 500Hz with an average power of 600W. The investigation of single pulse laser drilling in this paper was based on theoretical and experimental solutions. In single pulse technique, the investigation included focal plane position fpp, pulse shap
... Show MoreSeveral correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability
... Show MoreThis research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (dps). So that the depth of strands to overall depth of the section ratio (dps
... Show MoreBackground: pulmonary function can change with age for normal individual's .Spirometric measurement for the ratio of forced expiratory volume in one second (FEV1), the forced vital capacity and the ratio (FEV1/FVC) can reveal airway obstruction and the consequence change in pulmonary performance. These parameters can be different for different race /ethnic and gender.
Methods: Pulmonary function test were carried out on 29normal male and 37 normal female the test parameters were FEV1 and FVC from which the ratio of FEV1/FVC %was calculated in relation to age. Iraqi average for FEV1 and FVC and FEV1/FVC % has also been obtained
Results: results of these tests reveled that the ratio of FEV1/FVC % is almost th
In this study, a new technique is considered for solving linear fractional Volterra-Fredholm integro-differential equations (LFVFIDE's) with fractional derivative qualified in the Caputo sense. The method is established in three types of Lagrange polynomials (LP’s), Original Lagrange polynomial (OLP), Barycentric Lagrange polynomial (BLP), and Modified Lagrange polynomial (MLP). General Algorithm is suggested and examples are included to get the best effectiveness, and implementation of these types. Also, as special case fractional differential equation is taken to evaluate the validity of the proposed method. Finally, a comparison between the proposed method and other methods are taken to present the effectiveness of the proposal meth
... Show MoreFacial expressions are a term that expresses a group of movements of the facial fore muscles that is related to one's own human emotions. Human–computer interaction (HCI) has been considered as one of the most attractive and fastest-growing fields. Adding emotional expression’s recognition to expect the users’ feelings and emotional state can drastically improves HCI. This paper aims to demonstrate the three most important facial expressions (happiness, sadness, and surprise). It contains three stages; first, the preprocessing stage was performed to enhance the facial images. Second, the feature extraction stage depended on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) methods. Third, the recognition stage w
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
... Show MoreTwo unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.