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Plain Language Movement and Legal Translation : An Analytical Study of Two Translations of a Contract of Lease from Arabic into English
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The present paper addresses one of the most challenging topics in translation; namely legal translation in the framework of two different approaches; the classical (formal) and the more recent (functional). The latter approach is the outcome of the process of simplifying legal language known technically as Plain Language Movement. The advent of this movement dates back to the 1950s, in response to the widely-held complain about the awkwardness of the legal register. Within this framework, the salient features of legal language, at the various linguistic and textual levels, underwent reconsideration in favor of more publicly digested expressions. The paper then subjects two translations of a lease contract to analysis in the light of the formal/functional dichotomy. These two texts are taken from textbooks widely accredited to train students legal translation at the Iraqi universities. The analysis revealed that the translators did not adhere to one specific approach; rather they moved smoothly from one approach to another. This is a promising change in attitude towards the rather flexible approach, and departing from the rather static one. The paper finally suggests some guidelines for investing this new tendency in training translators who have been complaining about the rigorous nature of legal translation.

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Publication Date
Fri Jan 02 2026
Journal Name
Iraqi Journal Of Science
Elastic Electron Scattering From Unstable Neutron-Rich P19PC Exotic Nucleus
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The ground state proton, neutron, and matter density distributions and corresponding root-mean-square (rms) of P19PC exotic nucleus are studied in terms of two-frequency shell model (TFSM) approach. The single-particle wave functions of harmonic-oscillator (HO) potential are used with two different oscillator parameters bRcoreR and bRhaloR. According to this model, the core nucleons of P18PC nucleus are assumed to move in the model space of spsdpf. The shell model calculations are carried out for core nucleons with w)20(+ truncations using the realistic WBPinteraction. The outer (halo) neutron in P19PC is assumed to move in the pure 2sR1/2R-orbit. The halo structure in P19PC is confirmed with 2sR1/2R-dominant configuration.Elastic electr

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Pulmonary CT findings in Patients Recovered from COVID-19 Pneumonia
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Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
New algorithms to Enhanced Fused Images from Auto-Focus Images
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Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras

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Publication Date
Wed Jan 08 2025
Journal Name
Interventional Cardiology
Intravascular Foreign Bodies Retrieval: Navigating Differences From Childhood to Adulthood
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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Reducing endotoxin from dialysis water by using different disinfection processes
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Publication Date
Sat Jun 01 2024
Journal Name
Ecological Engineering & Environmental Technology
Employing Phytoremediation Methods to Extract Heavy Metals from Polluted Soils
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The phytoremediation technique has become very efficient for treating soil contaminated with heavy metals. In this study, a pot experiment was conducted where the Dodonaea plant (known as hops) was grown, and soil previously contaminated with metals (Zn, Ni, Cd) was added at concentrations 100, 50, 0 mg·kg-1 for Ni and Zn, and at concentrations of 0, 5, 10 mg·kg-1 for cadmium. Irrigation was done within the limits of the field capacity of the soil. Cadmium, nickel and zinc was estimated in the soil to find out the capacity of plants to the absorption of heavy and contaminated metals by using bioconcentration factors (BCFs), bioaccumulation coefficient (BAC) and translocation factor (TF). Additionally, BCF values of both Ni and Zn were l

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Publication Date
Wed Jan 01 2020
Journal Name
Akkadica
Some Ur III Texts from Irisagrig in the Iraq Museum
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This article publishes seven cuneiform tablets in the collection of the Iraq Museum Baghdad. Six of the tablets have an Irisagrig/Al Sarraki provenance, the seventh is of uncertain origin. They are dated to the reigns of Amar-Suen (AS) and Ibbi-Suen (IS) of the Ur III Dynasty. The texts represent administrative texts of the governing institutions and account for economic activities including the assignment of female workers for wool plucking, the remuneration of canal work with barley and the selection of wool for textiles. Three tablets record offerings in respect of cultic observances, two of which describe the disbursement of foodstuffs for the king's monthly 83-63 offerings to the new moon.

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Publication Date
Fri Dec 01 2017
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
RESEARCH NOTES ON RECORDING SOME RARE VERTEBRATES FROM KURDISTAN, IRAQ
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    A mounted specimen of a mustelid animal deposited in the Kurdistan Museum of Natural History, Salahaddin University, Erbil proved to be Mustela erminea (Linnaeus, 1758) and represents a new record for the mammalian fauna of Iraq. Its measurements and some biological noted are provided. Also, two passerine birds; the Red-headed bunting, Emberiza bruniceps Brandt, 1841(Family, Emberizidae) and the Variable wheatear, Oenanthe picata (Blyth, 1847) (Family, Muscicapidae) were recorded for the first time in Iraq. Furthermore, the tree frog Hyla savignyi Audouin, 1829 was found in two locations north east of Iraq with spotted dorsum and having interesting behavior in having the capabil

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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