In recent years, the need for Machine Translation (MT) has grown, especially for translating legal contracts between languages like Arabic and English. This study primarily investigates whether Google Translator can adequately replace human translation for legal documents. Utilizing a widely popular free web-based tool, Google Translate, the research method involved translating six segments from various legal contracts into Arabic and assessing the translations for lexical and syntactic accuracy. The findings show that although Google Translate can quickly produce English-Arabic translations, it falls short compared to professional translators, especially with complex legal terms and syntax. Errors can be categorized into: polysemy, homonymy, legal doublets, and adverbs at the linguistic level, and morphological parsing, concord, and modality at the syntactic level. The study concludes with recommendations for enhancing machine translation systems and suggests caution in using Google Translate for legal purposes, advocating for continued reliance on human expertise in legal settings.
This research deals with the most important indicators used to measure the phenomenon of financial depth, beyond the traditional indicators, which are called quantitative indicators, which is shown to be inadequate to show the facts accurately, but it may come in the results of a counterfactual, although reliable in econometric studies done in this regard.
Therefore, this research has sought to put forward alternative indicators, is the structural indicators, and financial prices, and availability of financial instruments, and cost of transactions concluded, in order to measure the phenomenon of financial depth.
After using and analyzing data collected from countries the research
... Show MoreAbstract:
Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .
power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.
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... Show MoreBackground: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome.
Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews.
Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative
... Show MoreNumerical study is adapted to combine between piezoelectric fan as a turbulent air flow generator and perforated finned heat sinks. A single piezoelectric fan with different tip amplitudes placed eccentrically at the duct entrance. The problem of solid and perforated finned heat sinks is solved and analyzed numerically by using Ansys 17.2 fluent, and solving three dimensional energy and Navier–Stokes equations that set with RNG based k−ε scalable wall function turbulent model. Finite volume algorithm is used to solve both phases of solid and fluid. Calculations are done for three values of piezoelectric fan amplitudes 25 mm, 30 mm, and 40 mm, respectively. Results of this numerical study are compared with previous b
... Show MoreFibroblast growth factor-23, play an important role in atherosclerosis, endothelial dysfunction and vascular calcification. Sevelamer can improve vascular calcification, serum uric acid, low-density lipoprotein-cholesterol and Fibroblast growth factor-23. Aim of study Assessment the effect of sevelamer as phosphate binder against calcium carbonate on Fibroblast growth factor-23. Methods A prospective open-labelled study that included patients on hemodialysis. A total of 72 patients were screened, only 53 patients completed the 10 week period. Adults patients with serum phosphate as> 5.5 mg/dl were included. There were Group1: Includes 28 patients (19 males and 9 females receiving sevelamer carbonate (Renvela) tablet. Group 2: Include 25pati
... Show MoreBackground: Oral Lichen Planus (OLP) is a chronic inflammatory mucosal disease, presenting in various clinical forms WHO had regarded OLP as a precancerous conditions in 1978 because of its potential with cancer. Both antigen-specific and nonspecific mechanisms involved in the pathogenesis of OLP. Oral Squamous Cell Carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity representing more than 94% of oral cancer. It occurs in different sites and has many etiological factors. Cyclin Dl is a proto-oncogene which consider as the key protein in the regulation of cell proliferation and its overexpression led to the occurrence and progression of malignant tumors.NF-KB p65 is a member ofNF-kB family of transcription factors that
... Show MoreNewly 4-amino-1,2,4-triazole-3-thione ring 2 was formed at position six of 2-methylphenol from the reaction of 6-(5-thio1,3,4-oxadiazol-2-yl)-2-methylphenol 1 with hydrazine hydrochloride in the presence of anhydrase sodium acetate. Seven newly fused heterocyclic compounds were synthesized from compound 2. First fused heterocyclic was 6-(6-(3,5-di-tertbutyl-4-hydroxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazol-3-yl)-2-methylphenol 3 synthesized from reaction compound 2 with 3,5-di-tert-butyl-4-hydroxybenzoic acid in POCl3. Reaction compound 2 with bromophencylbromide afford 6-(6-(4-bromophenyl)-5H-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazin-3-yl)-2-methylphenol 4. 6-(6-thio-1,7a-dihydro-[1,2,4] triazolo[3,4-b][1,3,4]-thiadiazol-3-yl)-2
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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