This study was carried out to prepare and characterize domperidone nanoparticles to enhance solubility and the release rate. Domperidone is practically insoluble in water and has low and an erratic bioavailability range from 13%-17%. The domperidone nanoparticles were prepared by solvent/antisolvent precipitation method at different polymer:drug ratios of 1:1 and 2:1 using different polymers and grades of poly vinyl pyrolidone, hydroxy propyl methyl cellulose and sodium carboxymethyl cellulose as stabilizers. The effect of polymer type, ratio of polymer:drug, solvent:antisolvent ratio, stirring rate and stirring time on the particle size, were investigated and found to have a significant (p? 0.05) effect on particle size. The best formul

Isradipine belong to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used in the treatment of hypertension, angina pectoris, in addition to Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, therefore, oral bio-availability will be approximately15 to 24 %.

 The aim of this study was to formulate and optimize a stable  nanoparticles of a highly hydrophobic drug, isradipine by anti-solvent microprecipitation Method to achieve the higher in vitro dissolution rate, so that it will be absorbed by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism&nbs

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

In light of accelerating environmental degradation, the transition to a green economy is an imperative for achieving sustainable development. This study provides a critical analysis of the international legal and institutional framework governing this transition, revealing a significant gap between normative developments and the institutional framework on one hand, and their practical implementation on the other. The transition faces legal obstacles, including reliance on non-binding voluntary commitments and conflicts between environmental obligations and global trade and investment rules. It also reveals a significant financing gap, as financial flows to developing countries continue to lag behind commitments, in add

This research introduces a developed analytical method to determine the nominal and maximum tensile stress and investigate the stress concentration factor. The required tooth fillets parametric equations and gears dimensions have been reformulated to take into account the asymmetric fillets radiuses, asymmetric pressure angle, and profile shifting non-standard modifications. An analytical technique has been developed for the determination of tooth weakest section location for standard, asymmetric fillet radiuses, asymmetric pressure angle and profile shifted involute helical and spur gears. Moreover, an analytical equation to evaluate gear tooth-loading angle at any radial distance on the involute profile of spur and hel

Background: Radioactive iodine-131 therapy is highly effective in treating patients with hyperthyroidism. An ablative dose is preferred by a number of endocrinologists, and, a fixed dose protocol seems to be better than a calculated dose in real practice.

Objective: To check for hypothyroidism in hyperthyroid patients one year after RAI therapy, comparing between the results of high ablative versus usual dosages of RAI-131.

 Methods:  This study included 174 hyperthyroid patients, 101 males and 73 females, divided into 2 groups, the first consisted of 162 patients given a usual fixed dose of RAI while the second consisted of 12 patients given a high fixed ablati

Objective: To assess the functional outcome, time to union, shoulder pain, blood loss, operative time, iatrogenic radial nerve injury, hospitalization, and infection. Methodology: It is a prospective randomized study on 30 patients with mid-shaft humerus fracture according to AO classification (1.2A1, 2, 3 and 1,2B) with functioning radial nerve. They were randomly dividing into two groups. Group A were treated by a closed antegrade interlocking nail, and group B treated by open reduction and locked compression plate fixation. The follow-up was up to 6 months, including time to union, shoulder pain, intraoperative blood loss, operative time and iatrogenic radial nerve injury. Functional outcome was assessed by quick DASH score. Resu

True random number generators are essential components for communications to be conconfidentially secured. In this paper a new method is proposed to generate random sequences of numbers based on the difference of the arrival times of photons detected in a coincidence window between two single-photon counting modules

The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the resear

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod