An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and

Source, sedimentation, coagulation, flocculation, filter, and tank are parts of a water treatment plant. As a result, some issues threaten the process and affect the drinking water quality, which is required to provide clean drinking water according to special standards and international and local specifications, determined by laboratory results from physical, chemical, and biological tests. In order to keep the water safe for drinking, it is necessary to analyze the risks and assess the pollution that occurs in every part of the plant. The method is carried out in a common way, which is monitoring through laboratory tests, and it is among the standards of the global and local health regulators

Source, sedimentation, coagulation, flocculation, filter, and tank are parts of a water treatment plant. As a result, some issues threaten the process and affect the drinking water quality, which is required to provide clean drinking water according to special standards and international and local specifications, determined by laboratory results from physical, chemical, and biological tests. In order to keep the water safe for drinking, it is necessary to analyze the risks and assess the pollution that occurs in every part of the plant. The method is carried out in a common way, which is monitoring through laboratory tests, and it is among the standards of the global and local health regulators

This study aimed to obtain a local isolation of Aspergillus niger and then studied its ability to produce citric acid from raw materials available locally using solid state fermentation. Six local isolates were collected from different sources including some samples of the damaged fruits such as grapefruit, oranges and sindi. Wheat bran was used as a raw material or as culture medium for the production of citric acid from the collected isolates. The conditions for citric acid production were determined by humidity percentage of 1: 1 (water: culture medium), temperature of 28 C, pH 4 and inoculum dose with 5× 106 spore/ml and for 3 days of incubation. The orange was the best model for citric acid production with a concentration of 12.8 mg/m

Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

Background: Diabetes is defined by the World Health Organization as a metabolic disorder characterized by chronic hyperglycemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action, or both. Families are co-regulating systems in which the stresses and strains of one family member affect the well-being of another member of the family. Caregivers of children with chronic illness report experiencing more parental stress than parents of healthy children.

Objective: A descriptive cross-sectional study had been conducted in four centers of endocrine diseases in Baghdad city and data was collected by using self-administered questionnaire regarding qua

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

   This study includes Estimating scale parameter, location parameter  and reliability function  for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).

 Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (R_P=1000)