A statistical optical potential has been used to analyze and
evaluate the neutron interaction with heavy nuclei 197Au at the
neutron energy range (1-20 MeV). Empirical formulae of the optical
potentials parameters are predicted by using ABAREX Code with
minimize accuracy compared with experimental bench work data.
The total elastic, absorption, shape elastic and total compound crosssections are calculated for different target nuclei and different
incident neutron energies to predict the appropriate optical
parameters that suit the present interaction. Also the dispersion
relation linking between real and imaginary potential is analyzed
with more accuracy. The results indicate the behavior of the
dispersion c

The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd+2, Nickel Ni+2, and Vanadium V+5) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir model with correlation coefficients (R2)

Results of charge, neutron and matter densities and related form factors for one- proton halo nucleus ⁸B are presented using a two- frequency shell model approach. We choose a model space for the core of ⁷Be different from that of the extra one valence proton. One configuration is assumed for the outer proton to be in 1p_1/2 - shell. The results of the matter density distributions are compared with those fitted to the experimental data. The calculated proton and matter density distributions of this exotic nucleus exhibit a long tail behavior, which is considered as a distinctive feature of halo nuclei. Elastic electron scattering form factors of this exotic nucleus are also studied. The effects of

In this work, electron number density calculated using Matlab program code with the writing algorithm of the program. Electron density was calculated using Anisimov model in a vacuum environment. The effect of spatial coordinates on the electron density was investigated in this study. It was found that the Z axis distance direction affects the electron number density (n_e). There are many processes such as excitation; ionization and recombination within the plasma that possible affect the density of electrons. The results show that as Z axis distance increases electron number density decreases because of the recombination of electrons and ions at large distances from the target and the loss of thermal energy of the electrons in

The main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate

The aim of the research is to identify the impact of the dimensions of the European Excellence Model in evaluating the performance of the bank of the research sample, as well as to interpret which dimensions are more important to the banks of the research sample. Based on the dimensions of this model, the United Bank for Investment and Finance has chosen a research community, and has met with officials of the United Bank for Investment and Finance at various administrative levels to measure the practices of excellence management in the European model, and the analytical approach has been the case study and the construction of the checklist as a tool to collect information. The research has reached the most important results There is a discr

The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

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