The present study investigates the notion of untranslatability where the concept of equivalence is reconsidered since the misconceptions, related to the said concept, inevitably lead to the emergence of untranslatability. Identifying equivalence as relative, approximate and necessary identity makes the notion of untranslatability a mere theorization. The objectives of the present study are (1) to investigate the notion of untranslatability in terms of the misconceptions associated with the concept of equivalence (2) to examine the possibility of translatability from Arabic into English focusing on culture-bound euphemistic expressions in the Quran as an area of challenge in translation. Data on the translation of culture-bound euphemistic expressions were purposively selected from the Quran and its four identified English translations. Ten examples were randomly selected and the criterion for their selection is that they are culture bound and therefore translation-resistant. Qualitative content analysis was used to examine the source data by referring to traditional exegetical books to determine the source text intentionality. Additionally, the translated data were analyzed according to the functional equivalence proposed by Nida (1993; 2001).Findings of this study revealed that translatability is always possible and, accordingly, untranslatability is no more valid.
Studies were conducted to screen eight sunflower (Helianthus annuus L.) genotypes for their allelopathic potential against weeds and wheat crop, which customarily follows sunflower in Iraq. All sunflower genotypes significantly inhibited the total number and biomass of companion weeds and the magnitude of inhibition was genotype dependent. Among the eight genotypes tested, Sin-Altheeb and Coupon were the most weed-suppressing cultivars, and Euroflor and Shumoos were the least. A subsequent field experiment indicated that sunflower residues incorporated into the field soil significantly inhibited the total number and biomass of weeds growing in the wheat field. Sunflower genotypes Sin-Altheeb and Coupon appeared to inhibit total weed number
... Show MoreEnvironmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant
... Show MoreThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
Phosphorus‐based Schiff base were synthesized by treating bis{3‐[2‐(4‐amino‐1.5‐dimethyl‐2‐phenyl‐pyrazol‐3‐ylideneamino)ethyl]‐indol‐1‐ylmethyl}‐phosphinic acid with paraformaldehyde and characterized as a novel antioxidant. Its corresponding complexes [(VO)2L(SO4)2], [Ni2LCl4], [Co2LCl4], [Cu2LCl4], [Zn2LCl4], [Cd2LCl4], [Hg2LCl4], [Pd2LCl4], and [PtL
... Show MoreThe 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
... Show MoreAlpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images