In this work, the effect of preparing a composite of copper oxide nanoparticles with carbon on some of its optical properties was studied. The composite preparing process was carried out by exploding graphite electrodes in an aqueous suspension of copper oxide. The properties of the plasma which is formed during the explosion were studied using emission spectroscopy in order to determine the most important elements that are present in the media. The electron’s density and their energy, which is the main factor in the composite process, were determined. The particle properties were studied before and after the exploding process. The XRD showed an additional peak in the copper oxides pattern corresponding to the hexagonal graphite struct

The shape dimensions and characteristics of pollen grains and seeds have importance in distinguish among species. Therefore, the present study included morphological characteristics of pollen grains and seeds for eight species belonging to eight genera of the family Brassicaceae and these species are: Alliaria petiolata (M.Bieb) Cavara et Grand, Aubrieta parviflora Boiss, Cardamine hirsuta L., Crambe orientalis L., Eromobium aegyptiacum (Spreng.) Schweinf.et Asch.ex Boiss., Parlatoria cakiloidea Boiss., Sterigmostemum sulphureum (Banksetsol.) Bornm. Neotorularia torulosa (Desf.) Hedge & J. Leonard. The pollen grains were studied in morphological and full measurements were taken, the study showed that the majority of the pollen grai

The aim of this work is to study the correlation between the electrons for Li atom in ground state through the calculation of the inter-particle distribution function f (r12) and inter-particle expectation values . By using the f(r12) function for KL shell in both singlet and triplet state .The Fermi hole have been evaluated .In this work the Hartree-Fock wave function (1993) have been used.

The study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical test

Rheumatoid arthritis is an inflammatory chronic disease with an autoimmune pathogenesis. To determine the role of Helicobacter pylori as a trigger agent, twenty five patients with rheumatoid arthritis of ages (15-47) years have been investigated and compared with twenty healthy individuals. All the studied groups were carried out to measure the rheumatoid arthritis (RA) IgM, anti-CCP antibody IgG and IgA by ELISA test and by measured anti-IgG antibody level of H. pylori by using ELISA and IFAT techniques. The present study showed significant differences (P< 0.05) of anti-H. Pylori in sera of RA patients than control group, this lead to suggest that H. pylori had a role in pathogenesis of RA.

     This work demonstrated a simple and environmentally friendly method for synthesizing silica-supported copper nanocubes (CuNCs/SiO2). The copper nanocubes, with a size of 15 ± 5 nm, were synthesized using green reagents and conditions. Ascorbic acid, water, and di-n-butyl sulfide were employed as reducing agent, solvent, and stabilizing ligand, respectively. The designed nanoscale catalyst was utilized for the esterification of acetic acid to methyl acetate at room temperature. The catalyst exhibited high efficiency, converting 80% of the reactant to the desired product (methyl acetate) after 24 hours of reaction at room temperature. The size and shape of copper nanocubes were characterized by transmission electron microsco

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti