A restrictive relative clause (RRC hereafter), which is also known as a defining relative clause, gives essential information about a noun that comes before it: without this clause the sentence wouldn’t make much sense. A RRC can be introduced by that, which, whose, who, or whom. Givon (1993, 1995), Fox (1987), Fox and Thompson (1990) state that a RCC is used for two main functions: grounding and description. When a RRC serves the function of linking the current referent to the preceding utterance in the discourse, it does a grounding function; and when the information coded in a RRC is associated with the prior proposition frame, the RRC does a proposition-linking grounding function. Furthermore, when a RRC is not used to ground a new discourse entity, the purpose of it is to provide new information for its newly-introduced head NP. RRC of this kind perform a description function. Based on empirical analyses of 10 letters to editors, the present study investigates the use of RRCs in written text. The study draws on Givon (1993, 1995), Fox (1987), Fox and Thompson (1990) classification of RRCs' functions as outlined above. The analysis of data reveals that the use of RRCs as performing the grounding function is intuitively clear in letters to the editors. By comparison, the description function of RRCs is less than the grounding function and it varies between makes assertion about its head NPs and provides information for the newly-introduced NP. That is, in some cases RRC only makes assertion about its head NP without necessarily provides information for the newly-introduced NP and vice versa. The study further finds out that the third kind of grounding, which is done by the main clause instead of relative clauses, is impossible function of RRCs in letters to the editors
Thin films ZrO2: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and 10)% percentage to be used as the gas sensor for nitrogen dioxide NO2. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the
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A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthio- benzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L/)as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar const
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A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthiobenzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L/ )as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar construction is propo
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff
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الصيغة العامة للمعقدات الجديدة [M2(BDS)Cl4] الناتجة من تفاعل الليكاند الجديد] ن1,ن4-ثنائي(1أ –بنزو]د[ اميدازول-2-يل)-ن1,ن4-ثنائي(4-ثنائي مثيل امينو) بنزيل) سكسنمايد[ (BDS) مع الايونات الفلزية الكادميوم, الكوبلت, الزئبق, النحاس والنيكل. تم اشتقاق هذا الليكاند من تفاعل المواد الثلاث 4-(ثنائي ميثيل أمينو) بنزالدهيد، 2-أمينو بنزيميدازول، وكلوريد السكسينيل. تم تشخيص المركبات باستخدام مطيافية طيف الاشعة تحت الحمراء وطيف الرن
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The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag
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