In this article, the casting method was used to prepare poly(methyl methacrylate)/hydroxyapatite (PMMA/HA) nanocomposite films incorporated with different contents (0.5, 1, and 1.5 wt%) of graphene nanoplatelets (Gnp). The chemical properties and surface morphology of the PMMA/HA blend and PMMA/HA/Gnp nanocomposite were characterized using FTIR, and SEM analysis. Besides, the thermal conductivity, dielectric and electrical properties at (1–107 Hz) of the PMMA/HA blend and PMMA/HA/Gnp composites were investigated. The structural analysis showed that the synthesized composites had a low agglomerated state, with multiple wrinkles of graphene flakes in the PMMA/HA blend. The thermal conductivity was improved by more than 35-fold its value for

KE Sharquie, AA Noaimi, WK Al-Janabi, The Iraqi Postgraduate Medical Journal, 2013 - Cited by 3

chloride or poluacrulic acid with different primary amines to mesuring==================================638one hundred three patinents with rheumatic symptoms were include in this study and their sera tested for

Ruthenium-Ruthenium and Ruthenium–ligand interactions in the triruthenium "[Ru₃(μ-H)(μ₃-κ²-Hamphox-N,N)(CO)₉]" cluster are studied at DFT level of theory. The topological indices are evaluated in term of QTAIM (quantum theory of atoms in molecule). The computed topological parameters are in agreement with related transition metal complexes documented in the research papers. The QTAIM analysis of the bridged core part, i.e., Ru₃H, analysis shows that there is no bond path and bond critical point (chemical bonding) between Ru(2) and Ru(3). Nevertheless, a non-negligible delocalization index for this non-bonding interaction is calculated

At atmospheric pressure and at a frequency of 9.1 kHz, a constructed magnetically stabilized tornado gliding arc discharge (MSGAD) system was utilized in this study to generate a non-thermal plasma with an alternating voltage source from 2,4,6,8 to 10 kV. Argon gas was used to generate the arc plasma with an adjustable flow rate using a flow meter regulator to stabilize the gas flow rate to 2 L/min. A gliding plasma discharge is achieved by a magnetic field for the purpose of a planned investigation. The influence of the magnetically stabilized tornado gliding arc discharge parameters such as magnetic field and applied voltage on microscopic tornado plasma parameters was studied. The electron temperature1was measured using a Boltzmann plot

The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September,

In this paper, a construction microwave induced plasma jet(MIPJ) system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate using flow meter regulator. The influence of the MIPJ parameters such as applied voltage and argon gas flow rate on macroscopic microwave plasma parameters were studied. The macroscopic parameters results show increasing of microwave plasma jet length with increasing of applied voltage, argon gas flow rate where the plasma jet length exceed 12 cm as maximum value. While the increasing of argon gas flow rate will cause increasing into the ar

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati