This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

A method was developed that offers a rapid, simple and accurate technique for the determination of chlorophenols at trace levels in aqueous samples with very limited volumes of organic solvents. These compounds were acetylated, then preliminarily extracted with n-hexane. The enriched chlorophenols were directly analyzed using gas chromatography with an electron-capture detector. The detection limits were in the range of 0.001–0.005 mg/L, except for 2-chlorophenol, which was always above 0.013 mg/L. Relative standard deviation for the spiked water samples ranged from 2.2 to 6.1%, while relative recoveries were in the range of 67.1 to 101.3%.

Promoting the production of industrially important aromatic chloroamines over transition-metal nitrides catalysts has emerged as a prominent theme in catalysis. This contribution provides an insight into the reduction mechanism of p-chloronitrobenzene (p-CNB) to p-chloroaniline (p-CAN) over the γ-Mo2N(111) surface by means of density functional theory calculations. The adsorption energies of various molecularly adsorbed modes of p-CNB were computed. Our findings display that, p-CNB prefers to be adsorbed over two distinct adsorption sites, namely, Mo-hollow face-centered cubic (fcc) and N-hollow hexagonal close-packed (hcp) sites with adsorption energies of −32.1 and −38.5 kcal/mol, respectively. We establish that the activation of nit

In this work, we employ a new normalization Bernstein basis for solving linear Freadholm of fractional integro-differential equations  nonhomogeneous  of the second type (LFFIDE_s). We adopt Petrov-Galerkian method (PGM) to approximate solution of the (LFFIDE_s) via normalization Bernstein basis that yields linear system. Some examples are given and their results are shown in tables and figures, the Petrov-Galerkian method (PGM) is very effective and convenient and overcome the difficulty of traditional methods. We solve this problem (LFFIDE_s) by the assistance of Matlab10.   

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

This paper predicts the resilient modulus (Mr) for warm mix asphalt (WMA) mixtures prepared using aspha-min. Various predictor variables were analyzed, including asphalt cement types, asphalt contents, nominal maximum aggregate sizes (NMAS), filler content, test temperatures, and loading times. Univariate and multivariate analyses were conducted to examine the behavior of each predictor variable individually and collectively. Through univariate analysis, it was observed that Mr exhibited an inverse trend with asphalt cement grade, NMAS, test temperature, and load duration. Although Mr increased slightly with higher filler and asphalt content, the magnitude of this increase was minimal. Multivariate analysis revealed that the rate of change

Background: Hydatid disease also known as echinococcosis or hydatidosis , is caused by infection with larva (metacestoide) of tape worms of the genus Echinococcus.
Materials and methods: Twelve Rabbits were immunized with three types of antigens (Hydatid cyst fluid antigen; Protoscoleces antigen and Germinal and Laminated layer antigen) according to a specific immunization program and we used indirect hemagglutination test( IHAT) and Enzyme Linked Immuno Sorbent Assay(ELISA) for detecting the anti-Echinococcus antigens in the serum of these animals.
Results: The highest titter of antibodies were recorded in the Rabbit serum when use the first antigen (Hydatid cyst fluid) by using IHA method (1:64)after

     The worldwide pandemic Coronavirus (Covid-19) is a new viral disease that spreads mostly through nasal discharge and saliva from the lips while coughing or sneezing. This highly infectious disease spreads quickly and can overwhelm healthcare systems if not controlled. However, the employment of machine learning algorithms to monitor analytical data has a substantial influence on the speed of decision-making in some government entities.        ML algorithms trained on labeled patients’ symptoms cannot discriminate between diverse types of diseases such as COVID-19. Cough, fever, headache, sore throat, and shortness of breath were common symptoms of many bacterial and viral diseases.

This research focused on the nu