The extraction of Eucalyptus oil from Iraqi Eucalyptus Camadulensis leaves was studded using water distillation methods. The amount of Eucalyptus oil has been determined in a variety of extraction temperature and agitation speed. The effect of water to Eucalyptus leaves (solvent to solid) ratio and particle size of Eucalyptus leaves has been studied in order to evaluate the amount of Eucalyptus oil. The optimum experimental condition for the Eucalyptus oil extraction was established as follows: 100 C extraction temperature, 200 rpm agitation speed; 0.5 cm leave particle size and 6: 1 ml: g amount of water to eucalyptus leaves Ratio.

     This work is devoted to define new generalized gamma and beta functions involving the recently suggested seven-parameter Mittag-Leffler function, followed by a review of all related special cases. In addition, necessary investigations are affirmed for the new generalized beta function, including, Mellin transform, differential formulas, integral representations, and essential summation relations. Furthermore, crucial statistical application has been realized for the new generalized beta function.  

The effect of applied current on protection of carbon steel in 0.1N NaCl solution (pH=7) was investigated under flow conditions (0-0.262 m/s) for a range of temperatures (35-55°C) using rotating cylinder electrode. Various values of currents were applied to protect steel from corrosion, these were Iapp.=Icorr., Iapp.=2Icorr. and Iapp.=2.4Icorr. under stationary and flow conditions. Corrosion current was measured by weight loss method. The variation of protection potential with time and rotation velocity at various applied currents was assessed. It is found that the corrosion rate of carbon steel increases with rotation velocity and
has unstable trend with temperature. The protection current required varies with temperature and it inc

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

Natural fractures provide an important reservoir space and migration channels for oil and gas reservoirs and control the reservoir potential. Therefore, it is essential to understand the methods for identifying accurate reservoir permeability and characterizing reservoir fractures. In particular, using conventional measurements to identify permeability and characterize fractures is very expensive. While using conventional logging data is very challenging, and an efficient characterization correlation method is urgently needed. In this paper, we have evaluated reservoir potential based on the sensitivity of sonic scanner tools to fluid mobility, maximum stress direction, and fractures presence. This tool provides a continuous estimat

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

The present work provides theoretical investigation of laser photoacoustic one dimensional imaging to detect a blood vessel or tumor embedded within normal tissue. The key task in photoacoustic imaging is to have acoustic signal that help to determine the size and location of the target object inside normal tissue. The analytical simulation used a spherical wave model representing target object (blood vessel or tumor) inside normal tissue. A computer program in MATLAB environment has been written to realize this simulation. This model generates time resolved acoustic wave signal that include both expansion and contraction parts of the wave. The photoacoustic signal from the target object is simulated for a range of laser pulse duration 1

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

This paper demonstrates the construction of a modern generalized Exponential Rayleigh distribution by merging two distributions with a single parameter. The "New generalized Exponential-Rayleigh distribution" specifies joining the Reliability function of exponential pdf with the Reliability function of Rayleigh pdf, and then adding a shape parameter for this distribution. Finally, the mathematical and statistical characteristics of such a distribution are accomplished

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep