The present work determines the particle size based only on the number of tracks detected in a cluster created by a hot particle on the CR-39 solid state nuclear track detector and depending on the exposure time. The mathematical model of the cross section developed here gives the relationship between alpha particle emitting from the (n, α) reaction and the number of tracks created and distribution of tracks created on the surface of the track detector. In an experiment performed during this work, disc of boron compound (boric acid or sodium tetraborate) of different weights were prepared and exposed to thermal neutron from the source. Chemical etching is processes of path formation in the detector, during which a suitable etching solut

This study presents the results of atmospheric particulates sampling using high volume air sampler for selected places at Al Tuwaitha nuclear site. The collected samples were analyzed for gross alpha /beta radioactivity using Ludlum model 3030 and measurement particles activity in Al Tuwaitha nuclear site and the surrounding areas for the period from 28/12/2016 to 13/4/2017.The measurement of activity concentrations ranged from (0.42±0.03 to 4.18±0.13) Bq/m3 for alpha particles and from(0.93±0.06 to 9.21±0.26) Bq/m3for beta particles. The activity concentration of nuclides inversely proportional with air temperature and wind speed while humidity is directly proportional with it. Highest value of activity concentration has been found at(

Coupling reaction of 4-amino antipyrene with 4-amino benzoic acid gave bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]Cl2 . The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the complexes formed were studied following the mol

Four new complexes of Pd(II), Pt(II) and Pt(IV) with DMSO solution of the ligand 8-[(4-nitrophenyl)azo]guanine (L) have been synthesized. Reaction of the ligand with Pd(II) at different pH gave two new complexes, at pH=8, a complex of the formula [Pd(L)2]Cl2.DMSO (1) was formed, while at pH=4.5,the complex[Pd(L)3]Cl2.DMSO (2) was obtained. Meanwhile, the reaction of the ligand with Pt(II) and Pt(IV) revealed new complexes with the formulas[Pt(L)2]Cl2.DMSO (3)and [Pt(L)3]Cl4.DMSO (4) at pH 7.5 and 6 respectively.
All the preparations were performed after fixing the optimum pH and concentration. The effect of time on the stability of these complexes was checked. The stoichiometry of the complexes was determined by the mole ratio and Job

In the present study, activated carbon supported metal oxides was prepared for thiophene removal from model fuel (Thiophene in n-hexane) using adsorptive desulfurization technique. Commercial activated carbon was loaded individually with copper oxide in the form of Cu₂O/AC. A comparison of the kinetic and isotherm models of the sorption of thiophene from model fuel was made at different operating conditions including adsorbent dose, initial thiophene concentration and contact time. Various adsorption rate constants and isotherm parameters were calculated. Results indicated that the desulfurization was enhanced when copper was loaded onto activated carbon surface. The highest desulfurization percent for Cu₂O/AC and o

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an