Titanium dioxide nanoparticles (TiO₂ NPs) are generally used in different types of applications such as the industry of plastics, paper industry, paints, toothpaste, cosmetics, sunscreens, and in various lifestyles, because of the vast range of applications and our daily exposure to these nanoparticles and a lack of information on animal and human health this study was designed to reveal dose and time-dependent effects of TiO₂-NPs on the thyroid gland and kidney functions in male rats.

For this study 54, Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided i

Three groups of subjects have been divided (25/group): healthy normotensive non-pregnant women (Group A), normal normotensive pregnant women (Group B), and women with preeclampsia (Group C).The levels of serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin , creatinine , blood urea nitrogen, triglyceride , total cholesterol and glucose have been estimated in all subjects. All measured parameters were determined by spectrophotometric analysis. The results showed a significant(P<0.05) increase in serum ALT, AST, blood urea nitrogen, triglyceride and total cholesterol levels in group B as compared to group A. However creatinine, total bilirubin and glucose levels did not show any statistical significant alt

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

This paper discusses reliability R of the (2+1) Cascade model of inverse Weibull distribution. Reliability is to be found when strength-stress distributed is inverse Weibull random variables with unknown scale parameter and known shape parameter. Six estimation methods (Maximum likelihood, Moment, Least Square, Weighted Least Square, Regression and Percentile) are used to estimate reliability. There is a comparison between six different estimation methods by the simulation study by MATLAB 2016, using two statistical criteria Mean square error and Mean Absolute Percentage Error, where it is found that best estimator between the six estimators is Maximum likelihood estimation method.

Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.

The interest of this paper is that

Time and space are indispensable basics in cinematic art. They contain the characters, their actions and the nature of events, as well as their expressive abilities to express many ideas and information. However, the process of collecting space and time in one term is space-time, and it is one of Einstein’s theoretical propositions, who sees that Time is an added dimension within the place, so the study here differs from the previous one, and this is what the researcher determined in the topic of his research, which was titled (The Dramatic Function of Space-Time Variables in the Narrative Film), Which included the following: The research problem, which crystallized in the following question: What is the dramatic function of the tempor

Playing is the only common language among children in every place and time, to the fact that what distinguishes the children is their quest to play and fun way innate, not acquired, which is expressed with the child really is one of the rights. And play a key entrance to the growth of the child mentally, intellectually and cognitively and not for the child emotionally and socially just. In the play the child begins to identify and classify objects and learn concepts and circulate among themselves on a linguistic basis. Activity here and play a major role in leading the linguistic development of the child in the composition has the communication skills.

The Games (especially intellectual ones) Whatever the cause of the development

Critical buckling temperature of laminated plate under thermal load varied linearly along the thickness, is developed using a higher-order shape function which depends on a parameter ‘‘m’’, which is improved to obtain results for thin and thick plates. Laminated plates’ equations of motion are obtained using virtual work principle and solved for simply supported boundary conditions. Angle and cross laminates thermal buckled mode shapes with different E1/E2 proportion, number of plies, (α2/α1) proportion, aspect ratios, are investigated. It is observed that this shape function gives thermal buckling for thin and thick plates but with m = 0.05 that agree well with other theories and linear distribution of temperature giv

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of