This paper aims to deal with the understanding of the properties of the molecular gas hydrogen in the extragalactic spirals sample. It is critical to make observations of CO (J = 1-0) line emission for spiral galaxies, particularly those with an energetic nucleus.  In the sample of spiral galaxies compiled, a carbon monoxide CO (1-0) emission line can be observed. This sample of galaxies' gas kinematics and star-forming should be analyzed statistically utilizing appropriate atomic gas HI, molecular gas H₂, infrared (1μm-1000μm), visual (at λ_blue-optical=4400A⁰), and radio spectrum (at ν_radio=1.4 GHz and 5GHz) databases. STATISTICA is software that allows us to perform this statistical

Ocular drug delivery is challenging due to the presence of anatomical and physiological barriers. These barriers can affect drug entry into the eye following multiple routes of administration (e.g., topical, systemic, and injectable). Topical administration in the form of eye drops is preferred for treating anterior segment diseases, as it is convenient and provides local delivery of drugs. Major concerns with topical delivery include poor drug absorption and low bioavailability. To improve the bioavailability of topically administered drugs, novel drug delivery systems are being investigated. Nanocarrier delivery systems demonstrate enhanced drug permeation and prolonged drug release. This review provides an overview of ocular barr

In this work, a simple and very sensitive cloud point extraction (CPE) process was developed for the determination of trace amount of metoclopramide hydrochloride (MTH) in pharmaceutical dosage forms. The method is based on the extraction of the azo-dye results from the coupling reaction of diazotized MTH with p-coumaric acid (p-CA) using nonionic surfactant (Triton X114). The extracted azo-dye in the surfactant rich phase was dissolved in ethanol and detected spectrophotometrically at λmax 480 nm. The reaction was studied using both batch and CPE methods (with and without extraction) and a simple comparison between the two methods was performed. The conditions that may be affected by the extraction process and the sensitivity of m

Abstract: In recent times, global attention has increasingly focused on the critical issue of environmental sustainability, owing to escalating environmental degradation exacerbated by the utilization of green spaces and technological innovation. This phenomenon necessitates thorough examination, prompting the present study to scrutinize the impact of various factors, namely green spaces, technological innovation, environmental taxes, renewable energy consumption (REC), inflation, and economic growth (EG), on environmental sustainability within the context of Iraq. Secondary data extracted from the World Development Indicators (WDI) spanning the period from 1991 to 2022 served as the foundation for this investigation. Methodologically, the

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp