The aim of the present investigation was to develop a microsponge delivery system of acyclovir to control its release when applied topically thereby reducing dosing frequency and enhancement patient compliance. The microsponges were produced by the oil in oil emulsion solvent diffusion method. The effect of different formulation and process variables such as internal phase volume, polymer type, drug-polymer ratio, stirring speed and stirring duration on microsponge production yield, loading efficiency, particle size and in-vitro drug release was evaluated. The result showed that the microsponge F2 prepared from Eudrajet RS polymer had optimum physical properties regarding the loading efficiency of 99.71_+ 0.7% and product

The aim of this work is to study the effect of mud compositions on it’s rheological behavior under high temperature conditions. Seventeen samples of five types of water base mud in which (fresh water bentonite mud. Lignosulphonate mud, gypsum mud, polymer mud, and salt saturated mud) were tested with different temperatures using the fann viscometer model 50-c. All the tested samples, except the fresh water bentonite mud, have the same trend reduction in both plastic viscosity and yield point with increasing temperature. Six rheological models has been adapted: Bingham plastic, power law, Casson model represent the laboratory data accurately  

In this research we have tackled the role of Talent management (as a private variable) within (the Talent attraction, the Talent management performance, Talent development and Talent retention) on strategic performance reinforcement ( accredited variable) within its dimensions ( financial perspective, costumer perspective, internal operations perspective and learning and development perspective). The research conducted on sample of some college teachers from two of Sumer's colleges. The research problem represented by the broad organization's competition as well as universities; which led these colleges to investigate it's skillful human staff to meet it's strategic performance. 

To meet the aims of

The importance of the research lies in preparing exercises using a proposed device to learn the skill of thehuman wheel on a machine rug of ground movements of the artistic gymnastics. As for the research problem:Through the presence of the two researchers as teachers and observers of this sport in the gymnastics hall,they noticed that there is difficulty in the students’ performance of the skill of the round off on the machineof the mat of ground movements, according to the researchers’ opinion, the reason for this is that skillsare taught with the limited availability of assistive devices, as well as the lack of use of these devices inexercises according to biomechanical variables, although they facilitate the learning process

Quantum key distribution (QKD) provides unconditional security in theory. However, practical QKD systems face challenges in maximizing the secure key rate and extending transmission distances. In this paper, we introduce a comparative study of the BB84 protocol using coincidence detection with two different quantum channels: a free space and underwater quantum channels. A simulated seawater was used as an example for underwater quantum channel. Different single photon detection modules were used on Bob’s side to capture the coincidence counts. Results showed that increasing the mean photon number generally leads to a higher rate of coincidence detection and therefore higher possibility of increasing the secure key rate. The secure key rat

The objective of the research is to measure the impact of social responsibility on the financial performance of the Bank of Baghdad for the period from 2014 to 2016 (3 years) through discussing and analyzing the level of practice of the Bank of Baghdad for social responsibility and the impact on their financial performance during the period. To measure the independent variable (CSR), the researcher used the CSR Disclosure Index and relied on the ROA as an indicator to measure the dependent variable (financial performance).The results of the research showed the main hypothesis of the research, which states that the social responsibility of the banks has no significant impact on the financial performance. In relation to the disclosure of s

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims