Four electrodes were synthesized based on molecularly imprinted polymers (MIPs). Two MIPs were prepared by using the diclofenac sodium (DFS) as the template, 2-hydroxy ethyl metha acrylate(2-HEMA) and 2-vinyl pyridine(2-VP) as monomers as well as divinyl benzene and benzoyl peroxide as cross linker and initiator respectively. The same composition used for prepared non-imprinted polymers (NIPs) but without the template (diclofenac sodium). To prepared the membranes electrodes used different plasticizers in PVC matrix such as: tris(2-ethyl hexyl) phosphate (TEHP), tri butyl phosphate (TBP), bis(2-ethyl hexyl) adipate (BEHA) and tritolyl phosphate (TTP). The characteristics studied the slop, detection limit, life time and linearity range of DF

Periodontitis is a chronic inflammatory disease resulted from aggravated immune response to a dysbiotic subgingival microbiota of a susceptible host. Consequences of periodontitis are not only limited to the devastating effect on the oral cavity but extends to affect general health of the individual and also exerts economic burdens on the health systems worldwide. Despite these serious outcomes of periodontitis; however, they are avoidable by early diagnosis with proper preventive measures or non-invasive interventions at earlier stages of the disease. Clinically, diagnosis of periodontitis could be overlooked due to certain limitations of the conventional diagnostic methods such as periodontal charting and radiographs. Utilization of re

Polymer films of PEG and PVA and their blend with different
concentrations of MnCl2 (0, 2, 4, 6 and 10 %.wt) were study using
casting technique. The X-ray spectra of pure PEG, PVA and
PVA:PEG films and with addition of 2% concentrations from
(MnCl2) show amorphous structures. The results for FTIR show the
interaction between the filler and polymer blend results in
decreasing crystallinity with rich amorphous phase. This
amorphous nature confirms the complexation between the filler and
the polymer blend. The optical properties of (PVA:PEG/MnCl2)
contain the recording of absorbance (A) and explain that the
absorption coefficient (α), refractive index (n), extinction coefficient
(ko) and the dielectric cons

Short Multi-Walled Carbon Nanotubes functionalized with OH group (MWCNTs-OH) were used to synthesize flexible MWCNTs networks. The MWCNTs suspension was synthesized using Benzoquinone (BQ) and N, N Dimethylformamide alcohol (DMF) in specific values and then deposited on filter paper by filtration from suspension (FFS) method. Polypyrrole (PPy) conductive polymer doped with metallic nanoparticles (MNPs) prepared using in-situ chemical polymerization method. To improve the properties of the MWCNTs networks, a coating layer of (PPy) conductive polymer, PPy:Ag nanoparticles, and PPy: Cu nanoparticles were applied to the network. The fabricated networks were characterized using an X-ray diffractometer (XRD), UV-Vis. spectrometer, and Ato

To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

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