The present paper discusses morphological and syntactic structures of time in Russian language. The morphological and syntactic structures are considered part component of time category in Russian language.

The morphological categories of time are formed through a various types of expressions .Tenses generally express time relative to the moment of speaking. In some contexts, however, their meaning may be relativized to a point in the past ,present or future which is established in the discourse .Some languages have different verb forms or constructions and that are opposed in meaning not in syntactic category. Hence, the present study traces and compares the syntacti

  An experiment was carried out by using pots in kalar horticulture station/ Sulaimani province on soil which is talken form on once region field in the seasoning growth(20062007). The objective was to study interaction of different levels from urea fertilizer (zero, 0.20, 0.40, 0.80 gm / 4 kg soil in pot). These levels were equal to (zero, 25, 50, 100, kg uera / D) and super phosphate levels (zero, 0.24, 0.48, gm / 4 kg soil in pot).These levels were equal to(zero, 30, 60, kg / D) in morphological and physiological characteristies (ex. dry weight, leaf area, absolute growth rate, protein percentage, and chlorophyll content) of Ipa (95) wheat variety. This experiment was carried out by completely Randomized Design (C. R. D.). Re

  Alloys of Bi2[Te1-x Sex]3 were prepared by melting technique with different values of  Se percentage (x=0,0.1,0.3,0.5,0.7,0.9  and 1). Thin films of these alloys were prepared by using thermal evaporation technique under vacuum of 10-5 Torr on glass substrates, deposited at room temperature with a deposition rate (12nm/min) and a constant thickness (450±30 nm). The concentrations of the initial elements Bi, Te and Se in the Bi2 [Te1-x Sex]3 alloys with different values of Se percentage (x), were determined by XRF,The morphological and structural properties were determined by AFM and XRD techniques.  AFM images of Bi2[Te1-x Sex]3 thin films  show that the average diameter and the average surface roughness inc

ABSTRACT: Thin film of CdS has been deposited onto clean glass substrate by using Spray pyrolysis technique. Results of Morphological (AFM) studied; electrical properties and optical conductivity studied are analysis. AFM results show a crystalline nature of the films. From the conductivity measurement at different temperatures, the activation energy of the films was calculated and found to be between 0.188 - 0.124 eV for low temperature regions, and between 1.67-1.19eV for high temperature regions. Hall measurements of electrical properties at room temperature show that the resistivity and mobility of CdS polycrystalline films deposited at 400 C0, were 3.878x103 . cm and 1.302x104cm2/ (V.s), respectively. The electrical conductivity of th

  Functionally graded materials (FGMs), with ceramic –ceramic constituents are fabricated using powder technology techniques. In this work three different sets of FGMs samples were designed in to 3 layers, 5 layers and 7 layers. The ceramic constituents were represented by hard ferrite (Barium ferrite) and soft ferrite (lithium ferrite). All samples sintered at constant temperature at 1100^oC for 2 hrs. and characterized by FESEM. Some physical properties were measured for fabricated FGMs include apparent density, bulk density, porosity, shrinkage and hardness. The results indicated that the density increase with the increase the number of layer. Lateral shrinkage is one of the important parameter f

Poly [2-methoxy-5-(2-ethylhexyloxy)-1, 4-phenylenevinyl] (MEH-PPV) thin films were created in this study using both spin coating and drop casting processes. MEH-PPV thin films generated by Ferric Chloride (FeCl3) doping (0.03, 0.06, 0.09, and 0.12 wt%) were studied for some physical features using Fourier-Transform Infrared Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FE-SEM), and Energy Dispersive X-ray Spectroscopy (EDX). An FTIR test showed that there was no chemical reaction that occurred between Ferric Chloride (FeCl3) and MEH-PPV, but rather a physical one, that is, an organic material composite occurred. As for FE-SEM, the pure sample MEH-PPV formed uniformly, but when FeCl3 was added by weight, we have differ

Sludge worm samples were collected from the Tigers River sediment during the period from November 2018 to June 2019 in Al Sarafiya District/ Baghdad- Iraq. Biometric morphological measurements focusing on the form of penis sheath and chaetal morphology were used for species identification, in addition to molecular analysis by amplification of conserved 18s rRNA encoding gene using ITS1 and ITS4 universal primers.According to the morphological measurement records, the results revealed the existence of Limnodrilus hoffmeisteri Claparede 1862, L. claparedeianus Ratzel, 1868 and L. cervix Brinkhurst 1963. Other two groups of specimens, with short penis sheath, were identified by molecular technology as L

Leuciscidae species are the abundant and widely distributed fish species in Iraq's inland waters. They are complex species, and morphology makes them difficult to identify. Molecular analysis achieved and confirmed the morphological characters. Twenty specimens of Acanthobrama marmid were collected from two localities at Tigris River, in the middle of Iraq; 15 specimens from the Al-Zubaydia sub-district and five specimens from Al-Tharthar Lake. We used the mitochondrial DNA cytochrome b (cytb) gene to sequence the DNA of A. marmid. The following analysis are compared the sequences with those of other fish genera and species found in the Gene Bank. The barcoding result (DNA sequencing) in fishes found in the same family (Leuciscidae) showed

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet