Abstract The relative pronoun in Hebrew language is an important pronoun use anciently and recently, it developed and it's usage and meanings differed so, it was not confined to the particle "אֲשֶׁר" as a relative pronoun, but beside it appeared other pronouns giving the relative meaning. Hence, the topic of this research was on this basis through studying the relative pronouns in old and modern Hebrew, the way of using them and their connection with preposition particles, as well as studying the relative clause.

Background/Aim: Psoriasis is a persistent systemic disorder characterised by chronic inflammation and linked to multiple comorbidities, including arthritis, cardiometabolic disorders, obesity and hyperlipidaemia. Objective of this study was to identify the relationship of abnormal lipid profiles and psoriasis, as well as to pinpoint factors that correlate with disease severity. Methods: A cross-sectional study was carried out at the dermatology clinic over 6 months from the 1 August 2024 to the 1 February 2025. Patients aged 15 years and above with a diagnosis of psoriasis were enrolled. For each patient two sets of data were collected, demographical characteristics (age, sex, disease duration and the body mass index (BMI)) and the

إن النجاح في أداء المتطلبات الفنية والخططية في أي من الألعاب ألرياضيه يستوجب امتلاك العناصر الاساسيه المتعلقة بطبيعة الاداء ونوع الفعالية الرياضية الممارسة , لذا فان اغلب الألعاب الرياضية تعتمد على مكونات ألقدره التوافقيه والادراكيه الحسيه بوصفها احد العناصر الاساسيه في المستويات العليا لما توفره من قاعدة اقتران للصفات البدنيه والحر كيه وقدرات أجهزة الجسم الوظيفية , وفقا للأسس المعتمدة في بناء مهاراته, وع

Background: This study aimed to determine whether there is a relationship among the bite force with facial dimensions and dental arches in a sample of Iraqi adults with Class I skeletal and dental relations. Materials and methods: Forty dental students (20 males and 20 females) were selected under certain criteria. For those individuals, dental impressions, frontal facial photographs and maximum bite force at molar and incisor regions were taken. The dental arches widths and facial dimensions were measured using the AutoCAD program 2007, while the bite force was determined using special device. Descriptive statistics for the measured variables were performed and gender difference was determined using independent sample t-test, while the rel

The Yemen Kings and gaverners allered notable services to the pilgrims, who
were in their way to perform the pilgrimage to Mecca. Among them Al-Hysen Ibn
Salama (dead 384, Aih). The governer of Al- Zeadiea state, who concern about
pilgrimage route from its beginning at Hudrumot to its end at Mecca Al Makruma, the
distant was estimated by 60th days to pass the way he also eastablished asystem of
water “artesian wells” as long as the pilgrimage way also setting up large Mosqeses
and Marking out the way of the caravans of pilgrimage to save these caravans from
lossing the right way, he setting up under ground water chanal started from Arafat to
holy Mecca in order to ensure water supplies for the erea. This proje

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c