The peculiarity of the theater does not lie in its dramatic content because many literary genres and other artistic styles share with it in this content. The peculiarity of the theater lies in contemplating the drama through what is architectural, and this architectural axis is what distinguishes its character. It is a spatial poetry which is composed by the laws of physics and chemistry, (Weight, height, distance, rhythm, gravity, impulses and chemical excretions). i.e., what cannot be expressed in words. This is a game of space to exchange and organize energy and communicate in space by the living body, which contains the possibilities of the living drawing in space: in the time and place. This research deals with the importance of the

That the main feature of  the economics many countries in general is a tendency towards defining the role of the public sector in economic activity and the tendency towards encourage the private sector to investment in public projects especially in countries those tendency towards market economy actually.

That increased economic development proven failure in achieving more economic growth both individually in many countries especially developing countries socialist, by researchers this led one way or another to direction of corrective reforms in their economic was one of them in Transformation of public companies into Shareholding companies contributes to the public sector in resources and expertise

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

In this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.

It is a moral presumption that includes the object for its sake, and it is called the object for it or the object for its sake, which is the present tense after (lam, ki, fa, willn, and then), and it is not an excuse for the occurrence of the matter (1), and it requires a connection between the two sides of (a cause with a cause) united by a reason for a specific purpose (2). The object has a reason or an excuse, because it is an explanation of what came before it, of the cause. The reason for the occurrence of the action, being the motive for causing the action and the bearer of it (3), indicates that the infinitive is restricted to a special reason. So if I said: (I came to you with the hope of honoring you), then I attributed the coming

A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.

n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.

In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot