The Fountain of poetry Canot be suddenly flow or flood from emptiness. but it is streams and motives drive it to move . Forward tat Calmness and latent in depth of poet ,and try to Chang it in to high wives , go in to details inside the seas of poetry ,to sail threw it on the ships of poetry in creative styel to reach to the point from imaginary meaning , so every poet has direction to competein poetry poetsin Lament of Imam Hussain, There versification of poetry didn’t come from emptiness , but there was clashes motive them threw Calling the personality of Imam Hussain to learn lesson in avery beautiful and greative styel ,to be the expression poem from many sides in the personality of Imam Hussain from that events and facts that happen in that time , The poet discover and repyouduce the battle (Altaf) , Altaf battle whichis absent from ore eves but its never absent from our maind in present time .
To specify this studing to detect the most important motives and clashes in lamentation of Imam Hussain , scince 1945 – 2010 , and out of coancern on that clashes to impact statement guide in lament of Imam Hussain , they have formend one of the pillars for the lamentation , to high light and constrat on to have it from researcher in modern eayes , Required research plant to divideol this study ing on three chapter , the first chapter concern on the intcnt function, the cecond chapter concern in conspt function while the third chapter concern in au thority function starting from couutinuation function of laurguage that mention by Gakbson .
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Periodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.
The
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طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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Background. Dental implantation has become a standard procedure with high success rates, relying on achieving osseointegration between the implant surface and surrounding bone tissue. Polyether ether ketone (PEEK) is a promising alternative to traditional dental implant materials like titanium, but its osseointegration capabilities are limited due to its hydrophobic nature and reduced surface roughness. Objective. The aim of the study is to increase the surface roughness and hydrophilicity of PEEK by treating the surface with piranha solution and then coating the surface with epigallocatechin-3-gallate (EGCG) by electrospraying technique. Materials and Methods. The study includes four groups intended to investigate the effect of pir
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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