Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

In this research, the Williamson-Hall method and of size-strain plot method was employed to analyze X- ray lines for evaluating the crystallite size and lattice strain and of cadmium oxide nanoparticles. the crystallite size value is (15.2 nm) and (93.1 nm) and lattice strain (4.2 x10−4 ) and (21x10−4) respectively. Also, other methods have been employed to evaluate the crystallite size. The current methods are (Sherrer and modified Sherrer methods ) and their results are (14.8 nm) and (13.9nm) respectively. Each method of analysis has a different result because the alteration in the crystallite size and lattice strain calculated according to the Williamson-Hall and size-strain plot methods shows that the non-uniform strain in nan

Background: Odontogenic cysts are characterized by their sluggish growth and ability to enlarge, primarily affecting the oral and maxillofacial tissues. Timely diagnosis and treatment are crucial to prevent potentially serious consequences. The present study aimed to evaluate and compare the immunohistochemical expression of cytokeratin 19 in the epithelium of odontogenic keratocyst, dentigerous, and radicular cysts.

Methods: This study analyzed forty-five formalin-fixed, paraffin-embedded tissue blocks containing odontogenic cysts. The sample consisted of fifteen odontogenic keratocysts, fifteen dentigerous cysts, and

Background: In young adults, multiple sclerosis is a prevalent chronic inflammatory demyelinating condition. It is characterized by white matter affection, but many individuals also have significant gray matter involvement. A double-inversion recovery pulse (DIR) pattern was recently proposed to improve the visibility of multiple sclerosis lesions. Objective: To find out how well a DIR sequence, FLAIR, and T2-weighted pulse sequences can find MS lesions in the supratentorial and infratentorial regions. Methods: A total of 37 patients with established diagnoses of multiple sclerosis were included in this cross-sectional study. Brain MRI was done using double inversion recovery, T2, and FLAIR sequences. The number of lesions was count

Background: Heterocyclic compounds and its derivatives have biological activities and used as analgesic, anti-helminthic, antituberculer, antifungal, antiviral, anticancer and inhibitor of some enzymes. Oxazepine (benzodiazepine) derivative used in relief of psychoneuroses characterized by anxiety and tension. Alkaline phosphatase (ALP) hydrolyzes phosphate monoesters, while Lactate dehydrogenase (LDH) catalyses oxidation of L-lactate to pyruvate utilizing NAD+Objective: The study was carried out to know of the impact of 1,3-oxazepine derivative on the ALP and LDH enzyme activity on human serum in vitro.Methods: The study included the effect of synthesized 1,3-oxazepine divertive [(Z)-3-(5-mercapto-1-3,4-Thiadizol-2-yl)-2-(4-nitroph

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin