Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.

In this paper we define and study new concepts of fibrewise topological spaces over B namely, fibrewise closure topological spaces, fibrewise wake topological spaces, fibrewise strong topological spaces over B. Also, we introduce the concepts of fibrewise w-closed (resp., w-coclosed, w-biclosed) and w-open (resp., w-coopen, w-biopen) topological spaces over B; Furthermore we state and prove several Propositions concerning with these concepts.

Throughout this paper R represents commutative ring with identity and M is a unitary left R-module. The purpose of this paper is to investigate some new results (up to our knowledge) on the concept of weak essential submodules which introduced by Muna A. Ahmed, where a submodule N of an R-module M is called weak essential, if N ? P ? (0) for each nonzero semiprime submodule P of M. In this paper we rewrite this definition in another formula. Some new definitions are introduced and various properties of weak essential submodules are considered.

Czerwi’nski et al. introduced Lucky labeling in 2009 and Akbari et al and A.Nellai Murugan et al studied it further. Czerwi’nski defined Lucky Number of graph as follows: A labeling of vertices of a graph G is called a Lucky labeling if  for every pair of adjacent vertices u and v in G where . A graph G may admit any number of lucky labelings. The least integer k for which a graph G has a lucky labeling from the set 1, 2, k is the lucky number of G denoted by η(G). This paper aims to determine the lucky number of Complete graph K_n, Complete bipartite graph K_m,n and Complete tripartite graph K_l,m,n. It has also been studied how the lucky number changes whi

The present work is qualitative descriptive. It aims to examine the idiosyncratic schema when deciphering the selected violence-based panel from Nasser Ibrahim’s caricatures. The researchers accordingly adopted part of Sharifian’s (2011) Cultural Schema model, particularly that part that is concerned with the examining the micro/idiosyncratic level of understanding. The study has revealed that the participants have not only differed among themselves regarding the way a figure is being denotatively conceptualized, they also highlighted different exact conceptualizations for the same figure, such as: using various adjectives that reflect various levels of intensity, emphasizing the behavioral aspect or the appearance of the figure, ado

This study was conducted in an orchard pomegranate's Department of Horticulture College of Agriculture, University of Baghdad for two seasons 1999-2000 on cultivars pomegranate Salimi and narrators seedless to study the effect spraying Nizant growth in sex ratio of flowers and recipes flowering and winning was selected 27 trees per class 15 years old planted

The drug promethazine hydrochloride (PRZH) forms with rhodium (II) a colored chelate (?max = 472 nm) complex at (pH = 2.1) which is extractable with benzyl alcohol as organic solvent. Under the appropriate experimental conditions a calibration plot was set up from which some analytical parameter were derived and deduced by regression. Standard addition procedure was also adopted. It has been estimated that the concentration of the drug PRZH to be 24.89 mg per unit and 24.19 mg per unit for both calibrations. Under optimal conditions, the developed method has been achieved the following characteristics: LDR (30 – 150 µg ml-1 ) PRZH , RSD % ( 0.6 – 2.47 ) , sandell sensitivity( 0.0844 µg. cm -2 ) , LOD ( 1.66 µgml-1 ) , recovery

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted