The research aims to evaluate Evaluation of the investments Iraqi fund for External development through the application of financial tools to a number of companies of the Iraqi Fund for External Development, and from the point of view to achieve the best returns from investment and the feasibility of the investments of the Iraqi Fund for External Development and the research community represents the Iraqi Fund for External Development and the amount of (28) A company, while the research sample is (4) companies (the Arab Petroleum Transportation Services Company, the Arab Iraqi Company for Livestock Development, the Bauhaus Company for prefabricated buildings and mineral installations, the Arab Fisheries Company) that were chosen

Background: Fast dissolving oral drug delivery system is solid dosage form which disintegrates or dissolves within second when placed in the mouth without need of water or chewing. In present investigation, an attempt has been made to develop oral fast dissolving film of calcium channel blocker lacidipine. Method: Five formulas were prepared by solvent casting method using HPMC (METOLOSE)® as a film forming polymer and evaluated for their physical characteristics such as thickness, weight variation, folding endurance, drug content, disintegration time and in vitro drug release. The compatibility of the drug in the formulation was confirmed by FTIR and DSC studies. Result and Conclusion: The optimized formula F1 showed minimum in vitr

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

There are many factors effect on the spread of infectious disease or control it,
some of these factors are (immigration and vaccination). The main objective of this
paper is to study the effect of those factors on the dynamical behavior of an SVIR
model. It is assumed that the disease is spread by contact between members of
populations individuals. While the recovered individuals gain permanent immunity
against the disease. The existence, uniqueness and boundedness of the solution of
this model are investigated. The local and global dynamical behaviors of the model
are studied. The local bifurcations and Hopf bifurcation of the model are
investigated. Finally, in order to confirm our obtained results and specify t

Inclination Of The Lumbosacral Angle In Normal Individuals: An Mri Study,GJRA - Global Journal For Research Analysis(GJRA) GJRA is a double reviewed monthly print journal that accepts research works. 36572+ Manuscript submission, 9855+ Research Paper Published, 100+ Articles from over 100 Countries

In this paper a mathematical model that analytically as well as numerically
the flow of infection disease in a population is proposed and studied. It is
assumed that the disease divided the population into five classes: immature
susceptible individuals (S1) , mature individuals (S2 ) , infectious individual
(I ), removal individuals (R) and vaccine population (V) . The existence,
uniqueness and boundedness of the solution of the model are discussed. The
local and global stability of the model is studied. Finally the global dynamics of
the proposed model is studied numerically.

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

kinetic studies were carried out the uterine homogenate time course of the association of with LH in benign and malignant uterine