This research aims to develop transdermal patches of Ondansetron hydrochloride (OSH) with different types of polymers, ethyl cellulose and, polyvinyl pyrrolidone k30 in a ratio (3:0.5,3:1,3:2,2:1,1:1) with propylene glycol 20%w/w as a plasticizer. Prepared transdermal patches were evaluated for physical properties. The compatibility between the drug and excipients was studied by Differential scanning calorimetry (DSC), where there is no interaction between the drug and polymers. From the statistical study, there is a statistical difference between all the prepared formulations p<0.05. In-vitro Release study of transdermal patches was performed by using a paddle over the disc. The release profile of OSH follow

This paper numerically and theoretically investigates the optical and thermal performance of a parabolic trough collector PTC system. Many numerical simulations and theoretical analyses are conducted to demonstrate the influence of the receiver geometry and shifting from the focal position on the optical performance. The examined receiver geometries are circular, square, triangular, elliptical, and the new circular–square combined geometry is named as channel receiver. The thermal performance of PTC is examined for different volume flow rates theoretically in the range of (0.36 to 2.4 lpm). The results show that the best optical design is the channel receiver with an intercept factor of 84%, while the worst is the elliptical receiver with

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

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas

Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

The non static chain is always the problem of static analysis so that explained some of theoretical work, the properties of statistical regression analysis to lose when using strings in statistic and gives the slope of an imaginary relation under consideration.  chain is not static can become static by adding variable time to the multivariate analysis the factors to remove the general trend as well as variable placebo seasons to remove the effect of seasonal .convert the data to form exponential or logarithmic , in addition to using the difference repeated d is said in this case it integrated class d. Where the research contained in the theoretical side in parts in the first part the research methodology ha