Transition metal complexes of Co(II), Ni(II), Cu(II), and Zn(II) with 2-(4-antipyrine azo)-4-nitroaniline derived from 4-aminoantipyrine and 4-nitroaniline were synthesized. Characterization of these compounds has been done on the basis of elemental analysis, electronic data, FT-IR, UV-Vis and 1HNMR, as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). High molar absorbtivity of the complex solutions were observed. From the analytical data, the stoichiometry of the complexes has been found to be 1:2 (metal:ligand). On the basis of physicochemical data octa

Background The application of nanotechnology to biomedical surfaces is explained by the ability of cells to interact with nanometric features. The aim of this study was to consider the role of nanoscale topographic modification of CPTi dental implant using chemical etching method for the purpose of improving osseointegration. Materials and methods: Commercial pure titanium rod was machined into 20 dental implants. Each implant was machined in diameter about 3mm, length of 8mm (5mm was threaded part and 3mm was flat part). Implants were prepared and divided into 2 groups according to the types of surface modification method used: 1st group (10 implant) remained without nano surface modification (control), 2nd group include (10 implant) etche

Structural and optical properties of CdO and CdO0.99Cu0.01 thin
films were prepared in this work. Cadmium Oxide (CdO) and
CdO0.99Cu0.01semiconducting films are deposited on glass substrates
by using pulsed laser deposition method (PLD) using SHG with Qswitched
Nd:YAG pulsed laser operation at 1064nm in 6x10-2 mbar
vacuum condition and frequency 6 Hz. CdO and CdO0.99Cu0.01 thin
films annealed at 550 C̊ for 12 min. The crystalline structure was
studied by X-ray diffraction (XRD) method and atomic force
microscope (AFM). It shows that the films are polycrystalline.
Optical properties of thin films were analyzed. The direct band gap
energy of CdO and CdO0.99Cu0.01 thin films were determined from
(αhυ)1/2 v

We present a simple model of charge transfer current through sensitizer N3 molecule contact to TiO2 and ZnO semiconductors to calculate the charge transfer current. The model underlying depends on the fundamental parameters of the charge transfer reaction and it is based on the quantum transition theory approach. A transition energy, driving energy and potential barrier have been taken into account charge transfer current at N3 / TiO2 and N3 / ZnO devices with wide polarity solvents Acetic acid, 2-Methoxyethanol, 1-Butanol, Methyl alcohol, chloroform, N,N-Dimethylacetamide and Ethyl alcohol via the quantum donor-acceptor system.The effects of the transition energy and potential barrier are computed and discussion on charge transfer current.

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The Schiff base (E)-2-(((2-(1H-benzo[d]imidazol-2-yl) phenyl) imino) methyl)-4-methylphenol (Lb) ligand with some metals(II) ion such as; Co, Cu, Cd, and Hg, were synthesis and characterized by the mass and 1 HNMR spectrometry for ligand Schiff base, the fourier-transform infrared spectroscop (FTIR), UV- visible and the flame atomic absorption (AA) spectrum, the CHN analysis, and the chlorine content, in addition to measuring the magnetic sensitivity of the complexes. All the complexes had octahedral geometry. The bioactivity activity for compounds against; Rhizopodium, Staphylococcus aureus, and Escherichia coli showed different efficacy towards these microorganisms

(3) (PDF) Theoretical investigation of charge transfer at N3 sensitized molecule dye contact with TiO2 and ZnO semiconductor. Available from: https://www.researchgate.net/publication/362773606_Theoretical_investigation_of_charge_transfer_at_N3_sensitized_molecule_dye_contact_with_TiO2_and_ZnO_semiconductor [accessed May 01 2023].

New bidentate dithiocarbamate ligand (NaL) namely [Sodium-2-(((3-methyl -4- “(2,2,2-tri fluoro ethoxy) pyridin-2”-yl) methyl) sulfinyl)-1H-benzoimidazole -1-carbodithioate] was prepared. This free ligand was synthesized from the reaction of a (RS)-2-([3-methyl -4-(2,2,2-tri fluoroethoxy) pyridin-2-yl] methyl sulfinyl)-1H benzoimidazole, CS2 and NaOH in methanol as solvent. From reaction of dithiocarbamate salt (NaL) with metal ions (M); Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Pd(II)”, have obtained the DTC complexes at general molecular formula [M(L)2(H2O)2] and [Pd(L)2]. To characterize the ligand and its complexes, used different analyses methods such FTIR, UV-Vis, elemental microanalysis, atomic absoreption, magnetic susceptibil

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T