Industrial dyes are major pollutants in wastewater and river water with an initial visible concentration of 1 mg/L. Recent studies have shown the possibility of using polyphenol oxidase in catalytic biological treatment due to its ability to oxidize a large number of dyes and pollutants in wastewater and the flexibility to work in wide ranges of temperature, pH and salinity. It is easy availability as well as the low economic cost resulting from its use in biological treatments, this enzyme polyphenol oxidase was used. The findings in this study showed that the extraction of polyphenol oxidase (PPO) from potato peel was homogenized with potassium phosphate buffer (0.1 M, pH 7) at a ratio of 1:10 (weight: volume) for two min. The res

Zinc, Copper, Selenium, Magnesium, Manganese, Chromium, Iron, Nickel, Cobalt, Vanadium and Germanium were determined by atomic absorption spectrophotometer (AAS) in blood serum of patients with rheumatoid arthritis, (30) patients (14male and 16female) with age range (37-60) years compared with normal tensive control. The analysis of results showed that the mean value of concentration (Magnesium,  Manganese and Nickel) were significantly higher in patients with rheumatoid arthritis compared to that of healthy, while the mean levels of serum (Zinc, Copper, Selenium, Chromium, Iron, Cobalt and Germanium) were significantly lower than controls. There were no significant changes in overall mean concentration of serum Vanadium in patients

Coconut milk is considered as a natural drink that enhances the immunity and it is enriched by calcium, iron, magnesium and vitamin (C) and it is also safe drink for kids and bacterial anti-oxdant, and it may be used in the natural juices instead of the whole milk (cow milk) which is added to some juices. This study aimed to determine the nutritrnal value and the sensory evaluation properties of the natural orange juice enriched by canned coconut milk                                                 &nb

In this study, the effect of design parameters such as pipe diameter, pipe wall thickness, pipe material and the effect of fluid velocity on the natural frequency of fluid-structure interaction in straight pipe conveying fully developed turbulent flow were investigate numerically,analytically and experimentally. Also the effect of support conditions, simply-simply and clamped-clamped was investigated. Experimentally, pipe vibrations were characterized by accelerometer mounted on the pipe wall. The natural frequencies of vibration were analyzed by using Fast Fourier Transformer (FFT). Five test sections of two different pipe diameters of 76.2
mm and 50.8 mm with two pipe thicknesses of 3.7 mm and 2.4 mm and two pipe materials,stainles

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Ebastine (EBS) is a poorly water-soluble antihistaminic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS). The aim of the present work was to enhance the solubility, dissolution rate and micromeritic properties of the drug, by formulating it as spherical crystal agglomerates by Quasi Emulsion Solvent Diffusion (QESD) method.

Spherical crystal agglomerates (SCAs) were prepared in presence of three solvents dichloromethane (DCM), water and chloroform as a good solvent, poor solvent and bridging solvent respectively.  Agglomeration of EBS involved the use of some hydrophilic polymers like polyethylene glycol 4000 (PEG 4000), polyvinyl pyrrolidine K30 (PVP K30), D-?-tocopheryl

Iron oxide (Fe3O4) nanoparticles were synthesized via an eco-friendly green approach by adding Phoenix dactylifera extract to the aqueous solution of ferric chloride. The effect of annealing temperature (Ta) (100-150) °C on particle size was studied. X-ray diffraction (XRD), UV-visible spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM) were used to evaluate the produced nanoparticles. According to XRD spectra, the crystallite size of the samples was determined using the Scherrer formula. AFM and FE-SEM were used to determine surface morphology. A UV-Vis optical spectroscopic examination was carried out to determine the band gap energy of the iron oxide nanoparticles. It was found th

As an important resource, entanglement light source has been used in developing quantum information technologies, such as quantum key distribution(QKD). There are few experiments implementing entanglement-based deterministic QKD protocols since the security of existing protocols may be compromised in lossy channels. In this work, we report on a loss-tolerant deterministic QKD experiment which follows a modified “Ping-Pong”(PP) protocol. The experiment results demonstrate for the first time that a secure deterministic QKD session can be fulfilled in a channel with an optical loss of 9 dB, based on a telecom-band entangled photon source. This exhibits a conceivable prospect of ultilizing entanglement light source in real-life fiber-based

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa