In this study the most stable isobar for some isobaric families (light and  intermediate ) nuclei with mass number (A) equals to (15-30) & (101- 115) have been determined. This determination of stable nuclide can help to determine the suitable nuclide, which can be used in different fields.

Most stable isobar can be determined by two means. First: plot mass parabolas (plotting the binding energy (B.E) as a function of the atomic number (Z)) for these isobaric families, in this method most stable isobars represent the lowest point in mass parabola (the nuclide with the highest value of binding energy).

Second: calculated the atomic number for most stable isobar (Z_A) value.

Our results show that

Background: Endometriosis is defined as the presence or growth of ectopic endometrial tissue outside their usual site ( the uterus). It is a common condition in women. It may occur in the ovaries, fallopian tubes, vagina and rarely, endometriosis may occur in the abdomen and lungs. Endometriosis is common among women of reproductive age. It is either primary or secondary. The triad of diagnosis is a pain with menstruation, cesarean scar and a mass in the scar.                                           

The reaction of 2-amino-benzothiazole with bis [O,O-2,3,O,O – 5,6 – (chloro(carboxylic) methiylidene) ] – L – ascorbic acid (L-AsCl2) gave new product 3-(Benzo[d]Thaizole-2-Yl) – 9-Oxo-6,7,7a,9-Tertrahydro-2H-2,10:4,7-Diepoxyfuro [3,2-f][1,5,3] Dioxazonine – 2,4 (3H) – Dicarboxylic Acid, Hydro-chloride (L-as-am)), which has been insulated and identified by (C, H, N) elemental microanalysis (Ft-IR),(U.v–vis), mass spectroscopy and H-NMR techniques. The (L-as am) ligand complexes were obtained by the reaction of (L-as-am) with [M(II) = Co,Ni,Cu, and Zn] metal ions. The synthesized complexes are characterized by Uv–Visible (Ft –IR), mass spectroscopy molar ratio, molar conductivity, and Magnetic susceptibility techniques. (

Throughout this paper we introduce the notion of coextending module as a dual of the class of extending modules. Various properties of this class of modules are given, and some relationships between these modules and other related modules are introduced.

In this paper we introduce new class of open sets called weak N-open sets and we study the relation between N-open sets , weak N-open sets and some other open sets. We prove several results about them. 

Let R be a commutative ring with identity 1 and M be a unitary left R-module. A submodule N of an R-module M is said to be pure relative to submodule T of M (Simply T-pure) if for each ideal A of R, N?AM=AN+T?(N?AM). In this paper, the properties of the following concepts were studied: Pure essential submodules relative to submodule T of M (Simply T-pure essential),Pure closed submodules relative to submodule T of M (Simply T-pure closed) and relative pure complement submodule relative to submodule T of M (Simply T-pure complement) and T-purely extending. We prove that; Let M be a T-purely extending module and let N be a T-pure submodule of M. If M has the T-PIP, then N is T-purely extending.

The purpose of this paper is to introduce and study the concepts of fuzzy generalized open sets, fuzzy generalized closed sets, generalized continuous fuzzy proper functions and prove results about these concepts.

The main purpose of this paper is to introduce a some concepts in fibrewise bitopological spaces which are called fibrewise , fibrewise -closed, fibrewise −compact, fibrewise -perfect, fibrewise weakly -closed, fibrewise almost -perfect, fibrewise ∗-bitopological space respectively. In addition the concepts as - contact point, ij-adherent point, filter, filter base, ij-converges to a subset, ij-directed toward a set, -continuous, -closed functions, -rigid set, -continuous functions, weakly ijclosed, ij-H-set, almost ij-perfect, ∗-continuous, pairwise Urysohn space, locally ij-QHC bitopological space are introduced and the main concept in this paper is fibrewise -perfect bitopological spaces. Several theorems and characterizations c

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se