The purpose of this study is to develop and assess the effectiveness of exercises using heavy and hanging ropes for handball players, focusing on enhancing specific physical abilities and shooting accuracy. The research addresses the gap in training methodologies by comparing the effects of heavy rope exercises versus hanging rope exercises. An experimental design was used in two equal groups, besides pre-testing and post-testing. The study involved 16 players from the School of Handball for the season 2022–2023. The sample included 14 players, who were then randomly divided into two experimental groups of 7 each. The first group performed heavy rope exercises, while hanging rope exercises were included in the plan of the second group. Th

Background: This study aimed to compare the surface microhardness (MH) and mineral content of white spot lesions(WSLs) after using bioactive glass (BAG)casein phosphopep-tides-amorphous calcium phosphate(CPP-ACP),and nanohydroxyapatite(Nano-HAP) under pHcycling. Material and method:18 sound maxillary first premolar were used for the study.10 were selected for the vickers microhardness test, For Energy-dispersive X-ray spectroscopy analysis (EDX), the remaining 8 premolar teeth were used, 40 sections of enamel blocks (Four from each tooth) were produced from the middle part of the buccal and palatal surfaces of teeth for MH test while 48 sections of enamel blocks (Six from each tooth) were produced for EDX analysis. Enamel slabs were

Background: This study aimed to compare the surface microhardness (MH) and mineral content of white spot lesions(WSLs) after using bioactive glass (BAG)casein phosphopep-tides-amorphous calcium phosphate(CPP-ACP),and nanohydroxyapatite(Nano-HAP) under pHcycling. Material and method:18 sound maxillary first premolar were used for the study.10 were selected for the vickers microhardness test, For Energy-dispersive X-ray spectroscopy analysis (EDX), the remaining 8 premolar teeth were used, 40 sections of enamel blocks (Four from each tooth) were produced from the middle part of the buccal and palatal surfaces of teeth for MH test while 48 sections of enamel blocks (Six from each tooth) were produced for EDX analysis. Enamel slabs were divi

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

with an organized propaganda campaign. This military campaign was helped to formulate its speech by many institutions, research centers, and knowledge and intelligence circles in order to mobilize public opinion gain supporters and face the opponents by different means depending on a variety of styles to achieve its required effects. 
          After the US occupation of Iraq, US media fighters sought to influence the Iraqi public opinion and making them convinced them of the important presence of US military forces in Iraq which necessitated finding its justification through the use of persuasive techniques in its intensive propaganda campaigns. 
  This research discusses the most important

In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the