COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.
Methotrexate (MTX) is widely used chemotherapeutic agent with different side effects including germ cells toxicities. Silibinin is one of the structural isomers of silymarin, with different phytotherapeutic applications, and its possible protective effects against MTX induced germ cells damage were investigated in this work. Twenty five male mice were divided into five groups (n=5) allocated as follows: Group 1 received buffer for five days given by single intraperitoneal (IP) injection per day; Group 2 in addition to buffer for five days, animals received at day five single dose of 20mg/kg of MTX IP. Groups (3, 4, and 5) received respectively, (50, 100, or 150mg/kg body weight) of silibinin IP single daily dose for five days then at day fi
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The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of
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This research was conducted in order to monitor and measure the dimensions of media policy in satellite channels directed from the point of view of the communicator, and this research is classified among the descriptive studies, as the researcher used the survey method to answer the questions that were formulated in light of the research problem represented by the main question: What are the dimensions of media policy in Directed satellite channels? .
To achieve the objectives of the study, the researcher used the following tools:
The questionnaire, in order to survey the attitudes of communicators about the extent to which the media policy during crises reflects on their professional standards. The research community is represente
Abstract
Objectives: The main objective of this study is to find the influence level of nursing incivility on psychological well-being among nurses in southeastern Iraq.
Methods: In this descriptive correlational study, a convenience sample of 250 nurses working in three government hospitals in Missan province in the south of Iraq were surveyed using the nursing incivility scale (NIS) and Ryff's psychological well-being scale (PWB) from November 2021, to July 2022. A multivariate multiple regression analysis was done to analyze the multivariate effect of workplace incivility on the psychological well-being of nurses.
Results: The study results show a
... Show MoreThere are many studies that discussed the famous museum's graveyards in the Islamic worlds, to study the lives of these figures, there are many difficulties for their studies because the first we need the regularity and history information, and many sciences support, such as in language, geography information.
I am studying the research from Maraqid Al-Maaraf book by Harz Aldeen, the book has large members about the persons have graved in Persian Country in the middle ages, there are more than (30) figures in my study, I have studied every figure in this research depending on the sources and references books.
Background: Neonatal macrosomia is defined as a birth weight of more than 4000 g. Significant maternal and neonatal complications can result from the birth of macrosomic infants like hypoglycemia and birth injuries.Objectives: To determine the frequency of hypoglycemia in neonates with macrosomia in Amarah, IraqMethods: The study involved 146 macrosomic newborn neonates delivered in 2 maternity hospitals in Amarah, Iraq during a period from June 2011 to June 2014.Results: Hypoglycemia was observed in 16% of neonates affected by macrosomia. Maternal diabetes was the most common cause of fetal macrosomia (28%).Our results were compared with those from other parts of the world.Conclusion Macrosomia is associated with increase rate ofneonata
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