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Particle-Hole State Density Calculations with Non-Equidistant Spacing Model: I. Basic Derivation

The basic analytical formula for particle-hole state densities is derived based on the non-Equidistant Spacing Model (non-ESM) for the single-particle level density (s.p.l.d.) dependence on particle excitation energy u. Two methods are illustrated in this work, the first depends on Taylor series expansion of the s.p.l.d. about u, while the second uses direct analytical derivation of the state density formula. This treatment is applied for a system composing from one kind of fermions and for uncorrected physical system. The important corrections due to Pauli blocking was added to the present formula. Analytical comparisons with the standard formulae for ESM are made and it is shown that the solution reduces to earlier formulae providing more general way to calculate state density. Numerical calculations then are made and the results show that state density behavior with excitation energy deviates from Ericson’s and Williams’ formulae types, especially at higher excitation energies

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Preparation and Characterization of Prednisolone Acetate Microemulsion for Ophthalmic Use

Background: Prednisolone acetate is an ester form of prednisolone. It is used topically as an ophthalmic suspension to treat many inflammatory ocular conditions, where its absorption from suspension is highly variable and has poor dose accuracy.

Objectives: The main objective of this research is to formulate and evaluate prednisolone acetate microemulsion for ophthalmic use to increase solubility, residence time, and corneal permeability of the drug to enhance patient compliance and treatment efficacy.

Methods: Twenty-four prednisolone acetate-loaded microemulsion (0.5%w/w)  formulas were prepared using

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Method Development of Nested Allele-Specific Multiplex Polymerase Chain Reaction (NASM-PCR) for the Irritable Bowel Syndrome (IBS)-related Gene Polymorphisms

Polymorphisms in the genes of G-protein subunit beta 3 (GNB3); rs5443, tryptophan hydroxylase 1 (TPH1); rs211105 and rs4537731, tryptophan hydroxylase 2 (TPH2); rs4570625 and sodium voltage-gated channel alpha subunit 5 (SCN5A); rs1805124, have known to cause the abnormalities in the gastrointestinal tract that are implicated to irritable bowel syndrome (IBS) predisposition. Upfront genetic polymorphism genotyping in IBS-related gene polymorphisms will help to intervene and guide the decision-making in the management of IBS patients. This study aimed to develop a genotyping method to detect the respective polymorphisms using nested allele-specific multiplex polymerase chain reaction (NASM-PCR). A combi

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Publication Date
Sat Feb 01 2020
Journal Name
Meta Gene
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Publication Date
Tue Feb 13 2024
Journal Name
Iraqi Journal Of Science
Parameters Estimation for Modified Weibull Distribution Based on Type One Censored Samplest

The three parameters distribution called modified weibull distribution (MWD) was introduced first by Sarhan and Zaindin (2009)[1]. In theis paper, we deal with interval estimation to estimate the parameters of modified weibull distribution based on singly type one censored data, using Maximum likelihood method and fisher information to obtain the estimates of the parameters for modified weibull distribution, after that applying this technique to asset of real data which taken for Leukemia disease in the hospital of central child teaching .

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Replacement of Line Loads acting on slabs to equivalent uniformly Distributed Loads

This study aims to derive a general relation between line loads that acting on two-way slab system and the equivalent uniformly distributed loads. This relation will be so useful to structural designer that are used to working with a uniformly distributed load and enable them to use the traditional methods for analysis of two-way systems (e.g. Direct Design Method). Two types of slab systems, Slab System with Beams and Flat Slab Systems, have been considered in this study to include the effect of aspect ratio and type of slab on the proposed relation. Five aspect ratios, l2/l1 of 0.5, 0.75, 1.0, 1.5 and 2.0, have been considered for both types of two-way systems.
All necessary finite element analyses have been executed with SAFE Soft

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition β€ŽAccuracy

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Comparison study of CC and CH vibration frequencies and eelectronic properties for mono, Di, Tri, and tetra-rings layer of arm chair (SWCNTs)

Semi-empirical methods were applied for calculating the vibration frequencies and IR absorption intensities for normal coordinates of the {mono (C56H28), di (C84H28), tri (C112H28) and tetra (C140H28)} -rings layer for (7,7) armchair single wall carbon nanotube at their equilibrium geometries which were all found to have D7d symmetry point group.

Assignment of the modes of vibration (3N-6) was done depending on the pictures of their modes by applying (Gaussian 03) program. Comparison of the vibration frequencies of (mono, di, tri and tetra) rings layer which are active in IR, and inactive in Ramman spectra. For C-H stretching vibrat

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Research - Granthaalayah
CALCULATION OF MULTIPLE MIXING RATIOS OF GAMMA RAYS FROM 𝑡𝒅(𝒏,𝒏)πŸ”πŸŽ πŸπŸ’πŸβˆ’πŸπŸ“πŸŽ ) πŸ”πŸŽπ‘΅π’… πŸπŸ’πŸβˆ’πŸπŸ“πŸŽ INTERACTION

In the current research, multiple mixing ratios of gamma -transitions of the energy levels 60𝑁𝑑 142−150 isotopes populated in 𝑁𝑑(𝑛, 𝑛 ˊ 60 142−150 ) 60𝑁𝑑 142−150 interaction are calculated using the constant statistical tensor (CST) method. The results obtained are, in general, in good agreement or consistent, within the experimental error, with the results published in the previously researches. Existing discrepancies result from inaccuracies in the experimental results of previous works. The current results confirm the validity of the constant statistical tenser method of calculating the values of mixing ratios and its predictability of errors in experimental results

Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
PFDINN: Comparison between Three Back-propagation Algorithms for Pear Fruit Disease Identification

     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

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