This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

The occurrence of two species of the genus Myxobolus Bütschli, 1882 (Myxozoa: Myxosporea) for the first time in Iraq from freshwater fishes.

The monogenean Gyrodactylus bychowskianus Bogolepova, 1950 is recorded in the present study for the first time in Iraq from the gills of the cyprinid fish Arabibarbus grypus (Heckel, 1843); which was collected from the Tigris River at Al-Taji Beach north of Baghdad Province during the period from July until November 2018.

Background: The gene encoding a disintegrin and metalloproteinase domain 33 (ADAM33) is known to be associated with asthma in different ethnic groups. In Iraq, among the Arab ethnic background, this association has not yet been highlighted. Methods: One hundred and ninety-two asthmatics were examined; 118 males and 74 females (mean age 38.23 ± 9.13 years). The control group was 183; 110 males and the rest were females. The SNP of rs2280091 A/G (T1) was studied here to determine adam33 genotyping status using polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP). The level of total IgE was measured using enzyme-linked immunosorbent assay (ELISA). Results: Significant differences (p = 0.004) in the frequencies of

Experiments were conducted to study the behavior of the solid particles (proppant) inside the hydraulic fracture during the formation stimulation, and study the effect of the proppant concentration on the hydraulic fracturing process, which lead to bridge and screen-out conditions inside the fractures across the fracture width that restricts fracturing fluid to flow into the hydraulic fracture. The research also studies the effect of the ratio between the fracture size and the average particles diameter “proppant", on fracture bridging. In this study two ratios were considered β= 2 and 3 ,where β=D_t / D_p where: D_t= hydraulic fracture size (width) and Dp=Average particles diameter.

This work pr

In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

Eleven hymenopterous species: two braconids, seven eulophids and two pteromalids
parasitized the larvae of Phytomyza horticola Goureau. The activity of the parasites began at
the end of April and evidently increased during May. The female of the parasites fed and
parasitized mostly on the second and third larval instars of P. horticola . Diglyphus iseae
Walker and Cirrospilus vittatus Walker were dominant larval parasites. Chrysocharis
pentheus Walker and Pediobius acantha Walker were main pupal parasites.

Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan