This paper aims to propose a hybrid approach of two powerful methods, namely the differential transform and finite difference methods, to obtain the solution of the coupled Whitham-Broer-Kaup-Like equations which arises in shallow-water wave theory. The capability of the method to such problems is verified by taking different parameters and initial conditions. The numerical simulations are depicted in 2D and 3D graphs. It is shown that the used approach returns accurate solutions for this type of problems in comparison with the analytic ones.

Dust storms are a common ecological occurrence in many world‘s countries, mainly in dry and semi-dry parts. Dust storms tremendously influence human health, the environment, the climate, and numerous social aspects. In this paper, spatial and temporal analysis, metrological triggers, and trajectory, dust exporting areas of a severe dust storm that occurred in Iraq on May 16, 2022, were investigated. The dust storm's backward trajectory was determined using HYSPLIT model, which is then compared with MODIS and Meteosat satellite images. The weather is then analyzed using the NCEP/NCAR Reanalysis model, and the approximate area of these sources was determined using Landsat 8 satellite image classification method. The results revealed

A Modified version of the Generlized standard addition method ( GSAM) was developed. This modified version was used for the quantitative determination of arginine   (Arg) and glycine ( Gly) in arginine  acetyl salicylate – glycine complex . According to this method two linear equations were solved to obtain the amounts of (Arg) and (Gly). The first equation was obtained by spectrophotometic measurement of the total absorbance of (Arg) and (Gly) colored complex with ninhydrin . The second equation was obtained by measuring the total acid consumed by total amino groups of (Arg) and ( Gly). The titration was carried out in non- aqueous media using perchloric acid in glacial acetic acid as a titrant. The developed metho

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

Background: Bone mineral density (BMD) has been assessed using Dual-Energy X-ray absorptiometry (DEXA). This procedure is considered to be of vital importance in assessing the general condition of individuals concerning their skeletal mineralization. BMD is measured according to the results of the DEXA examination of the vertebral column and pelvis. Although diabetes mellitus (D.M.)is known to affect BMD, the information regarding this relationship is not currently particularly clear. Objective: This study concentrates on the point that the assessment of BMD for the vertebral column is insuffi-cient to give a realistic and correct picture of the mineralization of the remaining part of the skeleton. Besides, this study elicited a gen

Background: Oral pyogenic granuloma (PG) is a clinicopathological entity that could develop due to the reaction to a variety of stimuli, such as low-grade local irritation, traumatic damage, and hormonal stimulation. There are two histopathological types of pyogenic granuloma; lobular type -capillary hemangioma (LCH) and non-lobular type; with PG,LCH has highly vascular, diffuse capillary growth while non- lobular variant mimicking granulation tissue with heavily inflammated stroma. The study aims were to review the clinical  and histopathological spectrum of an oral pyogenic granuloma from different intraoral sites in order to avoid diagnostic pitfalls associated with similar morphological lesions and to determine