A  new  Schiff base  ligand  [2,3,8,9–tetra -phenyl-1,4,5,7,10,12-hexa azo-5,12- dihydro -6,11- dione 1,3,7,10-dudec-tetra-ene]  [H2L]  and  its  complexes In general formula [M(H2L)]Cl2 (where : M= CoII, NiII, and PdII) were prepared. This ligand was prepared in two steps,in the first step a solution of  benzil in methanol was reacted  under  reflux   with    semicarbazidhydrochlorid  to give an (intermediate compound)[benzyl bis–(Semicarbazone)] which was  reacted  in the  second   step with  benzil giving  the  mentioned  ligand. The

This paper describes the development of a simple spectrophotometric determination of bismuth III with 4-(2-pyridylazo) resorcinol (PAR) in aqueous solution in the presence of cetypyridinium chloride surfactant at pH 5 which exhibits maximum absorption at 532 nm. Beer's law is obeyed over the range 5-200 µg/25 mL. i.e. 0.2-8 ppm with a molar absorptivity of 3×104 l.mol-1.cm-1 and Sandell's sensitivity index of 0.0069 µg.cm-2. The method has been applied successfully in the determination of Bi (III) in waters and veterinary preparation.

The aim of this paper is to identify Nano-particles that have been used in diagnosis and treatment of leishmaniasis in Iraq. All experiments conducted in this field were based on the following nanoparticles: gold nanoparticles, silver nanoparticles, zinc nanoparticles, and sodium chloride nanoparticles. Most of these experiments were reviewed in terms of differences in the concentrations of nanoparticles and the method that was used in the experiments whether it was in vivo or in vitro. These particles used in most experiments succeeded in inhibiting the growth of Leishmania parasites.

Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal

Avery large numbers of articles are made by powder metallurgical methods using electrolytically reduced metal powders. Iron powder is one of these powders which play an important role in this field. Its preparation by electrolytic method is economic in comparison with the traditional methods (Atomization and carbonyl processes).

An electrochemical cell consisting of two electrodes (stainless steel cathode and iron anode, 99.9%) was used to study the electrolytic preparation of iron powder with particle size less than 106µm directly as powde1y form. Ferrous sulphate electrolyte was used containing sodium chloride as a stabilizing agent. The produced powder was thoroughly washed with an acidified distilled water and absolute ethan

            In this study, pure SnO₂ Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl₂.2H₂O, CuCl₂.2H₂O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO₂ stage. As the average SnO₂ crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO₂ does not change with the introduction of Cu, and S

<span lang="EN-GB">This paper highlights the barriers that have led to a delay in the implementation of E-Health services in Iraq. A new framework is proposed to improve the E-Health sector using a SECI model which describes how explicit and tacit knowledge is generated, transferred, and recreated in organizations through main stages (socialization, externalization, combination and internalization). Class association rules (CARs) is integrated to mine the SECI model by extracting related rules which correspond to the medical advice. The proposed framework (SECICAR) can be done through a web portal to assemble healthcare professionals, patients in one environment. SECICAR will be applied to the hypertension community to show th

The gamma camera, along with SPECT and PET scanners, is one of the main imaging technologies in nuclear medicine. A collimator is typically constructed from tungsten to provide high absorption of gamma photon energies. It has a hole or holes for imaging. Gamma rays from a radioactive source within the body are emitted in all directions, while the photons required constructing an image travel through the hole. A scintillator is the most common material used to convert the high energy of gamma radiation into a lowenergy optical photon. These detectors are one of the primary secrets to radio-diagnosis in nuclear medicine. The photomultiplier tube (PMT) is a versatile device with extraordinarily highly sensitivity and response. A typical photom

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings