The current paper studied the concept of right n-derivation satisfying certified conditions on semigroup ideals of near-rings and some related properties. Interesting results have been reached, the most prominent of which are the following: Let M be a 3-prime left near-ring and A_1,A_2,…,A_n are nonzero semigroup ideals of M, if d is a right n-derivation of M satisfies on of the following conditions,
d(u_1,u_2,…,(u_j,v_j ),…,u_n )=0 ∀ 〖 u〗_1 〖ϵA〗_1 ,u_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n ϵA〗_u;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=0 ∀u_1,v_1 〖ϵA〗_1,u_2,v_2 〖ϵA〗_2,…,u_j,v_j ϵ A_j,…,〖u_n,v_n ϵA〗_u ;
d((u_1,v_1 ),(u_2,v_2 ),…,(u_j,v_j ),…,(u_n,v_n ))=(u_

A mathematical eco-epidemiological model consisting of harvested prey–predator system involving fear and disease in the prey population is formulated and studied. The prey population is supposed to be separated into two groups: susceptible and infected. The susceptible prey grows logistically, whereas the infected prey cannot reproduce and instead competes for the environment’s carrying capacity. Furthermore, the disease is transferred through contact from infected to susceptible individuals, and there is no inherited transmission. The existence, positivity, and boundedness of the model’s solution are discussed. The local stability analysis is carried out. The persistence requirements are established. The global behavior of th

     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an

This study aimed to know the impact of the capital structure measured by the ratio of financing to short-term capital and the ratio of financing to long-term capital on the profitability of companies, as measured by the rate of return on assets and the rate of return on equity. The study was applied to industrial sector companies listed in the Iraq Stock Exchange. The financial number of (14) companies, and (4) companies were selected that met the conditions for selecting the study sample. The study methodology relies on the analytical method as it is more appropriate to the nature, scope and objectives of the study, and the ready-made statistical program "SPSS" will be used to analyze the relationships and influence between the

Background: Non-traumatic Intracerebral Hemorrhage (ICH) results from rupture of blood vessels in the brain. ICH categories can also be considered as being either lobar in location or within the deep white matter. Although hypertension is a major risk factor for ICH in general[11], it is commonly considered to be associated more with patients having deep than with those having lobar haemorrhage.
Objectives: We investigate the relationship between hypertension and deep versus lobar intracerebral hemorrhage (ICH).
Methods: a retrospective review of records of 163 patients aged 18-89 years admitted to Al-Kadhimiya Teaching Hospital (January 2008 - October 2010) and diagnosed with ICH.
Results: There was no significant relationship

Objective:
This study aims to asses the patients' compliance with essential hypertension in respect to antihypertensive
medications, follow-up, dietary pattern and health habits, to identify the associated long-term complications, and
to find out the relationship between patient's compliance, and demographic characteristics such as age, gender,
level of education, and duration of disease.
Methodology:
A descriptive study was carried out in Nasiriyah Teaching Hospital to achieve presented objectives .
Results:
The results of the study revealed that there were a significant association between educational level and total
patient's compliance, a significant association was found between the duration of disease and

Objective:
This study aims to asses the patients' compliance with essential hypertension in respect to antihypertensive
medications, follow-up, dietary pattern and health habits, to identify the associated long-term complications, and
to find out the relationship between patient's compliance, and demographic characteristics such as age, gender,
level of education, and duration of disease.
Methodology:
A descriptive study was carried out in Nasiriyah Teaching Hospital to achieve presented objectives .
Results:
The results of the study revealed that there were a significant association between educational level and total
patient's compliance, a significant association was found between the duration of disease and

Background: Chronic obstructive pulmonary disease (COPD) is a common disease and it accounts for over 10% of all hospital medical admission. Cigarette smoking is the most important risk factor. Pulmonary arterial hypertension (PHT) is a common complication of COPD and the increase in pulmonary artery pressure is often mild to moderate. The presence of pulmonary arterial pressure and its severity is readily and reliably determined by transthoracic echocardiography in majority of COPD patients.
Patients and Methods: This study included 55 patients with mean age 65.6 ±8.2 years .The mean duration of symptoms was 18 ±10 months. 32 patients (58%) were current smoker, 18 patients (33%) were exsmoker and 5 pat

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D