The history of civilizations in the past centuries is a rich source for creativity and inspiration in all areas of art and design, especially in the field of fashion design. Many designers draw their designs from previous eras; which is the aim of this research as we propose designing fashion the mannequin for the category of young girls aged between (10-18). The costumes were inspired by Victorian women's costumes during the time period (1860-1890) and were subdivided into three time periods (1860-1870), (1870-1880), (1880-1890) forming three designs for each time period , analyzing the nine designs to achieve the creative , functional and aesthetic aspects that are appropriate for the age group (research sample). The importance of the

Background:Amino acid disorders are a major group of inborn error metabolism (IEM) with variable clinical presentation; its diagnosis constitutes a real challenge in a community with high consanguinity rate and no systematic newborn screening.

Objectives: to provide data about amino acid disorders detected in high-risk Iraqi children by using quantitative amino acid fluorescent high performance liquid chromatography (HPLC) analysis.

Type of the study: Cross-sectional study.

Methods: a descriptive cross sectional study from 1st February to 1st December 2014, at Neurological ward and clinic of the Children Welfare teaching Hospital, in Baghdad - Ira

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

Absitract

This research was interested in studying the phrase “I don’t know” in the Lisan al-Arab dictionary, and Lisan al-Arab was based on collecting its material from five dictionaries, including: Tahdhib al-Lugha, al-Muqamah, al-Sahih, and the footnotes of Ibn Berri, al-Nihaya and Gharib al-Hadith. The objection to this phrase, and the discussion of its various implications among linguists and the clarification of the closest and most famous content to it according to the data presented to the researcher in his research journey, and to reach this goal, the research division into a preface, five demands and a conclusion and followed the list of sources and references. To define the lexicon of Lisan al-Ar

Three stations were chosen on the water treatment plan of al- madaan .The Samples collected from the (Raw water) and the Sedimentation, filtration and storage water and the drinking water of outlet. Coliform densities T.S and F.C and TS and F.S and total bacterial count as bacteriological pollution indicators, as moste probable number (MPN) method was studied in test. Also some of the chemical characteristics of the water like pH , total suspended solid T.S.S, T.D.D.and S04 , T.Hardness , Ca++ , Mg++ . From the results it were indicated . The study showed the drinking water of outlet (distriputed in system) was agree with WHO criteria and Iraqi limits standards .

Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %Hb_AIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.

A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow