This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.

This study aims to explore the impact of the interaction of the university leadership and the university organizational environment on the performance level of the staff at Al-Maaqal university. This university was chosen as a field of study because it is a new university and needs studies that develops and contributes to improve its overall performance. The problem defined by the following question: to what extent does the interaction of the university leadership and the university organizational environment affect the performance level of the teaching staff at AlMaaqal University?). The method of this study adopted a major hypothesis in which there is a statistically significant effect of university leadership and university environment o

Pots experiment was conducted at the greenhouse of botanical garden belong to Department of Biology, College of Education for Pure Science, Ibn-AL-Haithum, University of Baghdad, for growth season 2018-2019. The aim of the experiment was to study the effects of foliar application of a-tocopherol concentrations (0, 50, 100, 150, 200 mg.L-1) on growth parameters and the activity of some antioxidant enzymes of wheat plant irrigated with sodium chloride concentrations (0, 75, 150, 225) mM.L-1. Salinity reduced plant growth parameter, plant height, flag leaf area, flag leaf chlorophyll content and increased the activity of antioxidant enzymes, superoxide dismutase and peroxidase. Plant growth parameters were enhanced by foliar application of a-t

Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti