This study was conducted to determine the relationship between two most common diseases in Iraqis patients , which are Diabetic mellitus (DM) and Rheumatoid Arthritis (RA); seeking rheumatoid factor in hyperglycemic sera. The results revealed that ; 62.5% of hyperglycemic (HG) patients had positive rheumatoid factor (RF) . No difference in number between both gender of HG patients (20 males and 20 females ) , RF reaction was nearly similar in males and females of HG patients ( 12 &13 respectively ) . Only 40% out of patient controls had positive RF . None of the apparently healthy subjects had positive RF .

Background: Obesity represents a clear and
present danger to the health of children and
adolescents. Its prevalence among American
youth has doubled in the past 3 decades, and
there are now more overweight and obese
adults in the United States than adults of
normal weight.
Objectives of the study:
1- Finding whether screen watching among
adolescents has an effect on increasing
prevalence overweight and obesity.
2- The effect of other variables like physical
activity, eating in front of screen, eating under
stress on obesity and overweight among the
subjects sample.
Patients &Methods: During 3 months period a
cross sectional survey was conducted on 4
high schools at Baghdad with total

Purpose: In view of the trend toward using international financial reporting standards when generating financial statements, we looked at the interaction between audit services and non-audit services for auditors in the context of actuarial services for insurance firms. CPAs are authorized to work in banks and insurance businesses, but those with a practicing license obtained after earning a higher academic degree are not. Design/methodology/approach: A small number of auditing firms control the decisions issued by the Iraqi Accountants Association, monopolizing audit services in banks and insurance businesses. In the case of actuarial services used in reserve estimation, they are credited to an external party's account withou

With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

هدف ال الأسلوب المعرفيّ 􀇼 م الإد ا ركيّ 􀥽 اضة للبنات، والتعرّف على علاقة التنظ 􀈄 ة وعلوم الر 􀥽 ة البدنّ 􀥽􀈃 ة التر 􀥽 لّ 􀘗 ة في 􀥽 ات المرحلة الثانّ 􀥼 طال إنّه 􀇼 احثتان 􀥼 اضة للبنات، وأفترضت ال 􀈄 ة وعلوم الر 􀥽 ة البدنّ 􀥽􀈃 ة التر 􀥽 ل􀘗 ة في 􀥽 ات المرحلة الثان 􀥼 عض طال 􀇼 التأمّليّ الاندفاعيّ لدى اس الأسلوب المعرفيّ التأمّليّ الاندفاعيّ لدى عیّنة 􀥽 م الإد ا ركيّ ونتائج مق 􀥽 اس التنظ 􀥽 ة بین نتائج مق

      Faces of the individual in his life many stressful events, which includes expertise undesirable, and events may involve a lot of sources of tension and the risk factors and threats in all areas of life, and this would make the stressful events play a role in the genesis of many diseases physical.            

The high blood pressure is one of the most Actual manifestations of mental stress in the present scale physical disorders which may frequently in men relative to women, which may be caused by spasms in the blood vessels.      

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le