PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

              -convex sets and -convex functions, which are considered as an important class of generalized convex sets and convex functions, have been introduced and studied by Youness [5] and other researchers. This class has recently extended, by Youness, to strongly -convex sets and strongly -convex functions. In these generalized classes, the definitions of the classical convex sets and convex functions are relaxed and introduced with respect to a mapping . In this paper, new properties of strongly -convex sets are presented. We define strongly -convex hull, strongly -convex cone, and strongly -convex cone hull and we proof some of their properties.  Some examples to illustrate the aforementioned concepts and to cl

Abstract

Objectives: To assess patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention, and to find out the relationship between patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention

Methodology: A descriptive design was carried out at Al- Nasiriyah Heart Center in Thi-Qar Governorate for the period between May 19^th, 2022 to October 25^th, 2022. A non-probability sampling was used among (50) patients after their Percutaneous Coronary Intervention. The study instrument that used to collect data was composed of three parts namely: sociodemographic charac

The esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.