When writing a text, such as a newspaper article, various types of discourse markers are frequently used to group sentences into paragraphs and parts in order to establish a discourse with certain functions, such as coordination, orientation, emphasizing the concepts presented, etc. It should also be noted that this type of mark exists in both written and spoken language. Therefore, it is convenient to dedicate a chapter to these linguistic elements to clarify their use and their classification, which is mainly based on Jose Portolés (2001), as well as the main features, specifically their features (prosodic, morphological, semantic and pragmatic).

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In this article we  study a single stochastic process model for the evaluate the assets pricing and stock.,On of the models le'vy . depending on the so –called Brownian subordinate as it has been depending on the so-called Normal Inverse Gaussian (NIG). this article aims as the estimate that the parameters of his model using my way (MME,MLE) and then employ those  estimate of the parameters is the study of stock returns and evaluate asset pricing for both the united Bank and Bank of North which their data were taken from the Iraq stock Exchange.

which showed the results to a preference MLE on MME based on the standard of comparison the average square e

The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used

         Free radical formation in heme proteins is recognized as a factor in mediating the toxicity of many chemicals. The present study was designed to evaluate the dose-response relationship of the free radical scavenging properties of pentoxifylline in nitrite-induced Hb oxidation. Different concentrations of pentoxifylline were added at different time intervals of Hb oxidation in erythrocytes lysate, and formation of methemoglobin (MetHb) was monitored spectrophotometrically. The results showed that in this model, pentoxifylline successfully attenuates Hb oxidation after challenge with sodium nitrite; this protective effect was found to be not related to the catalytic stage of Hb oxidation, th

The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which prove

In this work, radius of shock wave of plasma plume (R) and speed of plasma (U) have been calculated theoretically using Matlab program.

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea