In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

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

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

KE Sharquie, SA Al-Mashhadani, AA Noaimi, AA Hasan, Journal of Cutaneous and Aesthetic Surgery, 2012 - Cited by 19

Two compounds,[2-amino-4-(4-nitro phenyl) 1,3-thiazole],(4) and [2-amino-4-(4-bromo phenyl) 1,3-thiazole],(5), were synthesized by refluxing thiourea (1) with each of  para-ntiro and para-bomophanacyl bromides(2) and (3) respectively, in absolute methanol. Then, by reaction of [5] with 3,5-dinitrobenzoyl chloride in dimethylformamide (DMF) yielded  (6) .On the other hand, reaction of (4) with chloroacetyl chloride in dry benzene afforded (7), which is  upon treatment with thiourea in absolute methanol, af

: Cigarette smoking is a lifestyle behavior that causes significant adverse health effects. Cigarette smoke contains chemicals, many of which are lead to the production of reactive oxygen species (ROS), which can lead to apoptosis and autophagy. To estimate the association of Cigarette smoking with the autophagy and immunity, technology of real time polymerase chain reaction (RTPCR) for gene expression of (LC3A, LC3B, LC3C, myd88) was used. Enzyme-linked immunosorbent assay (ELISA) technique was utilized to measurement the amount of TNF-α protein. The ratios of LC3A/LC3B and LC3B/LC3C were calculated to estimate the autophagy flux. The results indicate the expression of LC3B, LC3C and Myd88 genes in smokers is increased significantly (p

To determine the association between cigarette smoking and oxidative stress, a study was conducted in the period from January 2020 to April 2021, at College of Medicine, Al-Nahrain University, Baghdad, Iraq. The Enzyme-linked immunosorbent assay (ELISA) technique was utilized for measurement the antioxidant enzymes including: Glutathione superoxide (GPX) and catalase (CAT) and the biomarker of lipid peroxidation Malondialdehyde (MDA). Also, the gene expression of Nrf2 and HO-1were determined by using RT-PCR technique. The results indicate lower level of both GPX and CAT (p ≤ 0.001) in smokers compared with non-smokers. While the result of MDA indicate higher level in smokers (p≤0.001) compared with nonsmokers. The Nrf2 and HO-1 gene exp

Therapeutic contact lenses TCLs is an approach used to enhance corneal residence time and reduce frequent instillation, which is a problem with eye drops.  The problem with CLs is loading of hydrophobic drugs. In this research the CLs were prepared with molecular imprinting MI to enhance the loading of itraconazole, which is used as antifungal drug for fungal keratitis. CLs using different  concentration of hydroxyethyl methacrylate HEMA and methacrylic acid MAA were prepared with and without MI using PEGDA (25 μL) and AIBN (37 mg) as crosslinker and initiator respectively. All the prepared CLs were clear and have good folding endurance. MICLs had significantly higher drug loading compared to conventional CLs. The release of i