The paper aims to build a model that supports organizational sustainability by analyzing the correlations and revealing the impact between the two main variables (entrepreneurial leadership) with its dimensions of proactive outlook, risk, and creativity (Van Zyl & Mathur-Helm, 2007), and (organizational sustainability) with its economic, environmental, and societal dimensions (Hansmann et al., 2012). As well as identifying the level of awareness and informing managers in the General Company for the Automotive and Equipment Industry, of the theoretical implications and performance, and its vital importance to society and the surrounding ecological environment, and drawing attention to that and improving performance, and indicatin

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: A quick and easy method was developed for extraction of DNA of eukaryotes from different samples, which are bone marrow and sperms in white mice Mus musculus strain (Balb/c).
Patients and Methods: this method using high salt buffer, Ethylene diemine tetracetec acid (EDTA), Trypsine,Sodium Dodecyl Sulfate(SDS), and urea without using Proteinase-K digestion or ultracentrifugation.
Results: This method was successful in extracting DNA from different samples in eukaryotic and this DNA is suitable for Hind III digestion.
Conclusion: Without further clean-up, the extracted DNA can be used for restriction endonuclease digestion or for numerous applications.

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

Cognitive-behavioral therapy is one of the most important relatively recent; treatment programs that attempt to modify behavior and control psychological disorders by modifying the individual's thinking style and awareness of himself and his environment, and cognitive reconstruction by replacing negative thoughts with positive ones. The current study aimed to know the effectiveness of a cognitive behavioral treatment program in reducing nervous fatigue among mothers of children with cerebral palsy. The sample on which the nervous fatigue scale was applied consisted of (30) mothers whose son suffers from cerebral palsy, and the results indicated that (24) mothers suffer from nervous fatigue. This sample was divided