Let R be a commutative ring with identity 1 ¹ 0, and let M be a unitary left module over R. A submodule N of an R-module M is called essential, if whenever N ⋂ L = (0), then L = (0) for every submodule L of M. In this case, we write N ≤e M. An R-module M is called extending, if every submodule of M is an essential in a direct summand of M. A submodule N of an R-module M is called semi-essential (denoted by N ≤sem M), if N ∩ P ≠ (0) for each nonzero prime submodule P of M. The main purpose of this work is to determine and study two new concepts (up to our knowledge) which are St-closed submodules and semi-extending modules. St-closed submodules is contained properly in the class of closed submodules, where a submodule N of M is called St-closed in M, if N has no proper semi-essential extension in M, i.e if there exists a submodule K of M such that N is a semi-essential submodule of K, then N = K. We investigate the main properties of this type of submodules, and discuss some results that are useful in our work. The class of semi-extending modules is a generalization to the notion of extending modules, where an R-module M is called semi-extending, if every submodule of M is a semi-essential in a direct summand of M. Various properties of semi-extending modules are obtained, and we study the relationships between this class of modules and other related concepts.
Modern asphalt technology has adopted nanomaterials as an alternative option to assert that asphalt pavement can survive harsh climates and repeated heavy axle loading during service life and prolong pavement life. This work aims to elucidate the behavior of the modified asphalt mixture fracture model and assess the fatigue and Rutting performance of Hot Mix Asphalt (HMA) mixes using the outcomes of indirect Tensile Strength (IDT), Semicircular bend (SCB) and rutting resistance; for this, a single PG (64−16) nanomodified asphalt binder with 5 % SiO2 and TiO2 have been investigated through a series of laboratory tests, including: Resilient modulus, Creep compliance, and tensile strength, SCB, and Flow Number (FN) to study their potential
... Show MoreBoth religions have urged (honoring parents and kin) through the texts that came in their original sources, as honoring parents means showing respect to them In word and deed, and carrying in our hearts an appreciation for their status, and God commands to honor parents; Becausee this is Important in the eyes of God that he includeincludeed it in the Ten Commandmen.
The study aims to identify the bargaining differences between the governmental and private kindergarteners; the rivalry differences between the governmental and private kindergarteners; the rivalry and bargaining differences among private kindergarteners; and the rivalry and bargaining differences among governmental kindergarteners. The researchers had raised a question; is there any difference of rivalry and bargaining between governmental and private kindergarteners?. A total of (150) kindergarteners ranged from 5 to 6 years old, (90) student from governmental kindergarten and (60) student from private kindergarten, were selected as a sample of this study. Fifteen governmental and private kindergarten were chosen from al-rasafa directo
... Show MoreThe new media scene reveals that the unprecedented overlap of a number of technical, economic, and political factors has made the new media a very complicated issue; and the focus of specialized and public debates about its impact on traditional means of communication and forms of social media and social relations. Then, the same scene discloses the reality of the relationship between the new and the traditional. These are the axes that will be will be discussed in this study.
MS Elias, RGM AL-helfy, Plant Archives, 2019
1-[4-(4-Acetyl-2-hydroxy-phenylazo)-phenyl]-ethanone (L1) and 1-[3-Hydroxy-4(4-nitro-phenylazo)-phenyl]-ethanone (L2) were readied by combination the diazonium salts of amines with 3-hydroxyacetophenone. (C.H.N) analyses, infrared spectra, UV–vis electronic absorption spectra, 1H and 13CNMR spectral mechanisms are use to identified of the ligands. Complexes of Ni+2 and Cu+2 were performed as well depicted. The formation of complexes has been identified by using atomic absorption of flame, elemental analysis, infrared spectra and UV-Vis spectral process as well conductivity and magnetic quantifications. Nature of compounds produced have been studied obeyed the mole ratio and continuous contrast methods, Beer's law followed during a concent
... Show MoreThermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.
This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.
Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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