The induced photodegradation of methyl cellulose (MC) films in air was investigated in the absence and presence of aromatic carbonyl compounds(photosenssitizers): 1,4-naphthaquinone (NQ) and benzophenone (BPH) by accelerated weathering tester. The addition of (0.01 wt %) of low molecular weight aromatic carbonyl compounds to cellulose derivatives films(25µm in thickness) enhanced the photodegradation of the polymer films.The photodegradation rate was measured by the increase in carbonyl absorbance. Decreases in solution viscosity and reduction of molecular weight were also observed in the irradiated samples. Changes in the number-average chain scission, the degree of deterioration and in the quantum yield of chain scission values are als

The enhancement of ZnSe/Si Heterojunction by adding some elements (V, In and Cu) as impurities is the main goal because they contribute to the manufacturing of renewable energy equipment, such as solar cells. This paper describes the preparation of thin films ZnSe with V, In and Cu doped using thermal evaporation method with a vacuum of 10–5 Torr. The thin film was obtained from this work could be applied in heterojunction solar cell because of several advantages including high absorption coefficient value and direct band gap. The samples prepared on a glass and n-type Si wafer substrate. These films have been annealed for 1 h in 450 K. X-ray diffraction XRD results indicated that ZnSe thin film possesses poly-crystalline structure after

Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm arises from Bcr-Abl gene translocation (called Ph chromosome) in hematopoietic stem cells (HSCs). This genetic abnormality results in constitutive activation of tyrosine kinase and subsequent uncontrol growth and multiplication of granulocytes. The cornerstone in treatment of CML are tyrosine kinase inhibitors, of which imatinib is the most effectively used. JAK2V617F mutation is an acquired single nucleotide polymorphism (SNP) occurs in JAK2 gene and is associated with many hematological malignancy other than CML. It was thought that the two genetic abnormalities (Bcr-Abl and JAK2V617F) occur mutually; however, growing body of evidences suggested the reverse. This study a

New complexes of the [M(Ura)(Phen)(OH2)Cl2]Cl.2H2O type, where (Ura) uracil ; (Phen) 1,10-phenanthroline hydrate; M (Cr+3 , Fe+3 and La+3) were synthesized from mix ligand and characterized . These complexes have been characterized by the elemental micro analysis, spectral (FT-IR., UV-Vis, 1HNMR, 13CNMR and Mass) and magnetic susceptibility as well the molar conductive mensuration. Cr+3, Fe+3 and La+3- complexes of six–coordinated were proposed for the insulated for three metal(III) complexes for molecular formulas following into uracil property and 1,10-phenanthroline hydrate present . The proposed molecular structure for all metal (III) complexes is octahedral geometries .The biological activity was tested of metal(III) salts, ligands

Objectives To compare the clinical efficacy of microvascular decompression surgery (MVD) and gamma knife radiosurgery (GKR) as a treatment for patients with primary trigeminal neuralgia (TN) and evaluate the outcome regarding pain relief, recurrence, and complications with both modalities of treatment. Patients and Methods A randomized prospective study conducted in SaadAlwitry Neurosciences Hospital, Baghdad, Iraq. Eighty-four patients with TN from January 2016 to January 2018, 45 patients had GKR while 39 patients treated with MVD. The pain evaluated pre-and post-operatively using the Barrow Neurological Institute Pain Intensity scale (BNIPI), visual analog scale (VAS) and Brief Pain Inventory Facial (BPI-Facial) scoring systems. In GKR p

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet