The rapid increase in the number of older people with Alzheimer’s disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems because of a large number of people affected. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available, and to plan for the future. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage caused to the brain due to AD leads t

Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so

     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

In this study, concentrations of radon were measured for seventeen samples of soil distributed in three Sulphuric Spring, in addition to other regions as a background in Hit City in AL-Anbar Governorate. The radon concentrations in soil samples measured by using alpha-emitters registration that emits from radon (222Rn) in (CR-39) track detector. The concentrations values were calculated by a comparison with standard samples. The results show that the radon concentrations in first spring varies from (258.253- 347.762 Bq/m3), second spring (230.374-305.209 Bq/m3), third spring (292.002-336.023 Bq/m3) and the average radon concentration in other regions (187.821 Bq/m3). As a conclusion of the study radon concentration in Sulphuric Spring is r

      Strong and ∆-convergence for a two-step iteration process utilizing asymptotically nonexpansive and total asymptotically nonexpansive noneslf mappings in the CAT(0) spaces have been studied. As well, several strong convergence theorems under semi-compact and condition (M) have been proved. Our results improve and extend numerous familiar results from the existing literature.

Biological samples of mother's milk were collected from Iraqi southern provinces(Basrah,Messan,al-Muthana,Thikar)and Baghdad province to measure uranium concentration of the samples by using track technique of fission fragments as a result from uranium atom fission with thermal neutrons from neutrons source 24 I Am-Be with activity 16Ci and neutron flux of 5000 n/cm2.s on using nuclear track detector CR-39 It was found that the high percentage of depleted uranium concentration on the samples from Muthana province , which accounted as 4.183ppm therefore the samples was taken from the provinces (Thikar,Basrah,Baghdad),which was accounted the depleted uranium concentration as following (1.243,2.172,2.875) ppm respectively, with appear a small

Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne