Background The study covered thirty-three species which grown wildly in Iraq and a comparative study for all kinds of morphological characters were done. Principal Findings The most stable and important taxonomic characters were pointed out, diagrams, illustrations, scheduals, micrographs were also documented. Stamens, nutlets, basal leaves, bracts, bracteoles, calyces, corollas and their trichomes were very important taxanomic characters. The trichomes were variable in variable species therefore used as a diagnostic characters for the species. Conclusions New species Salvia margasurica Al-Musawi & Al-Hussaini was suggested to be new record for science. Keywords: Salvia, Morphology, Spec. Nov.

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

תקציר :

 המחקר הזה הוא ניסיון לשפוך אור על נושא מרכזי וחשוב בחייהם של היהודים, "הממד הדתי" אצל היהודים, מחקרי הנקרא "הממד הדתי בסיפור העברי המודרני" גם מתייחס להשפעת התרבות הדתית של המספר והחוג המשפחתי שחי בו, ואיך שיקף המספר את כל הדברים האלה ביצירותיו הסיפורית .

המספר בוחר במילים ובמונחים בעלי משמעויות דתיות או מביא את הסיפור הזה אשר קרוב אל נושא הסיפור ההולך באותה מגמה .גם כן השפעת התיאולג

Background: Although they are not life threatening, dental caries and periodontal disease are the most predominant and widely spread oral diseases throughout the world. Another most common dental problem seen in children is dental trauma. The aims of the study included the investigation of the prevalence and severity of dental caries, gingivitis and dental plaque in relation to gender, furthermore, the prevalence and severity of the traumatized anterior teeth were assessed. Materials and Methods: This oral health survey was conducted among primary school children aged 9 years old in Al-Diwaniyah city in Iraq. The total sample composed of 600 child (320 males and 280 females) selected randomly from different school in Al-Diwaniyah city. Dia

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ r

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe