Multiple myeloma is hematological disease produces many complications in the bone, kidney, neural and other complications. The study aims to measure serum biomolecules like fetuin-A and resistin and determined the possibility to use these biomarkers as disease predictor. blood samples were isolated from 58 patients and 24 sex and age-matched control, serum then isolated, and proper ELISA kit then used to a determined level of B2 microglobulin, resistin, and fetuin-A. The result demonstrated significant increase in   B2 microglobulin, fetuin-A and resistin in patients compare to control (1.3470.714 vs. 0.9130.253), p = 0.000, (14.00310.352 vs. 9.2594.264), p= 0.005, (1.9673.595 vs. 0.6040.622), p = 0.009, respectively.   These di

In this work, novel copolymers of poly(adipic anhydride-co-mannitol) were synthesized by melting condensation polymerization of poly(adipic anhydride) with five percentages of mannitol sugar, 1 to 5 Wt.%. These copolymers were purified and then, characterized by FT-IR, which was proved that the cross-linking reaction was caused by nucleophilic attack of mannitol hydroxyl group to acidic anhydride groups of poly(adipic anhydride) backbone and new ester groups were formed and appeared. Also, modified organic-soluble chitosan, N-maleoyl-chitosan, were synthesized by grafting reaction of chitosan with maleic anhydride in DMF as solvent, and it was also purified and characterized by FT-IR. Biodegradation in vitro of the IPNs of poly(adipic anhyd

Cataract is an opacity in the normally transparent focusing lens of the eye which leads to blindness. The aim of current study is to investigate the possible protective and therapeutic effects of aqueous extract of Foeniculum vulgare seed eye drops (0.5%) against selenite induced cataract in rabbits. Aqueous extract of Foeniculum vulgare seed prepared then formulated as eye drops. Sodium selenite used to induce cataract in rabbits' right eye by single intravitreal injection. Thirty-six rabbits included in the study and divided into three equal groups (12 rabbits in each group): healthy control group, Cataract-Induced group and group treated by Foeniculum vulgare seed extract eye drops. Parameters include the score of lens opacity which was

The degradation of Toluidine Blue dye in aqueous solution under UV irradiation is investigated by using photo-Fenton oxidation (UV/H2O2/Fe+). The effect of initial dye concentration, initial ferrous ion concentration, pH, initial hydrogen peroxide dosage, and irradiation time are studied. It is found put that the removal rate increases as the initial concentration of H2O2 and ferrous ion increase to optimum value ,where in we get more than 99% removal efficiency of dye at pH = 4 when the [H2O2] = 500mg / L, [Fe + 2 = 150mg / L]. Complete degradation was achieved in the relatively short time of 75 minutes. Faster decolonization is achieved at low pH, with the optimal value at pH 4 .The concentrations of degradation dye are detected by spectr

Cr2O3 thin films have been prepared by spray pyrolysis on a glass substrate. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm before and after annealing. The effects of annealing temperature on absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity were expected. It was found that all these parameters increase as the annealing temperature increased to 550°C.

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

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d