The research aims to determine the role of Entrepreneur decision-making in its dimensions in improving the activities of Ambidexterity performance in its dimensions in the researched company. The importance of the research is also evidenced by assisting the oil products distribution company/session in directing the interest of the researched company because it has a prominent role in the Iraqi industrial community for the Entrepreneur decision-making variable that Contributes to building sustainable competitive advantage. This will happen when the company has an Entrepreneur orientation and a good strategic plan is built by the smart leaders in the researched company The researcher adopted the method of the analyti

Abstract
Dame Ngaio Edith Marsh (1899-1982), a writer of detective fiction, was born
at Christchurch, New Zealand. Her hero, Chief Detective Inspector Roderick Alleyn,
appears in her first novel, A Man Lay Dead (1934), and in subsequent novels
including Death and the Dancing Footman (1942). She wrote twenty detective novels.
The Dancing Footman, Thomas, listening to a playful song from the smokingroom's
radio where William lay dead after being killed by his brother, Nicholas,
provides the most suspected guest at Highfold with badly needed alibi. The murderer,
Nicholas, plans an almost perfect crime, but the dance of this footman spoils his
scheme. When Alleyn and his group of policemen stage a show in which the

Water is necessary for sustainable development and healthy society.  Groundwater, often, is not sufficient and protected for direct human consumption. Due to increase in the density of population the requirement of water is increasing.  In this work, the assessment of groundwater quality was conducted in the south-west part of Basrah province. Spatial variations in the quality of groundwater in the study area have been analyzed utilizing GIS technique. The geochemical parameters of groundwater samples including pH, EC, TDS, Ca, Mg, Na, Cl, HCO₃, SO₄, and NO₃ were assessed in this study. Information maps of the study area have been actually prepared to make use of the GIS spatial

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This