Grapes and grape seeds are important samples employed for environmental medical studies . The air of this work was to identify and concentration calculation of the elements in grapes fruit and thier seeds by using X-Ray fluoresces technique (XRF) . Samples were collected from Abo Ghraib of Baghdad city ,the grape seeds were obtained from those samples . Both samples were taken under experimental procedure to obtain the sample which were ready for analysis . The samples were then submitted to experimental conditions using a radiation source and then samples were applied for counting analysis shows the elements Na , Mg , Al , Si , P , S , Cl , K , Ca , and Sr as major components of the samples. Fe , Sr , I , Ba and V were

Let R be a commutative ring with identity and M be a unitary R- module. We shall say that M is a primary multiplication module if every primary submodule of M is a multiplication submodule of M. Some of the properties of this concept will be investigated. The main results of this paper are, for modules M and N, we have M N and HomR (M, N) are primary multiplications R-modules under certain assumptions.

      In this paper, we introduce and study the notation of approximaitly quasi-primary submodules of a unitary left -module  over a commutative ring  with identity. This concept is a generalization of prime and primary submodules, where a proper submodule  of an -module  is called an approximaitly quasi-primary (for short App-qp) submodule of , if , for , , implies that either  or , for some . Many basic properties, examples and characterizations of this concept are introduced.

Let  be a commutative ring with an identity and be a unitary -module. We say that a non-zero submodule  of  is  primary if for each with en either or  and an -module  is a small primary if   =  for each proper submodule  small in. We provided and demonstrated some of the characterizations and features of these types of submodules (modules).  

     In this work, plasma system that operates at vacuum was designed and built using a sheet of cobalt metal for the purpose of diagnosing plasma and measuring its parameters, as it is very important to know the processes that accompany plasma generation and are closely related to them, including the electron density in the plasma and its temperature. The spectroscopic diagnosis was done by optical emission spectroscopy (OES) which relies on the calculation of the optical radiation emitted by the plasma to describe plasma parameters in the chemical, molecular, and ionic radiator's near environment, and applied to cobalt metal at vacuum D.C high voltage power supply. The results showed the rise of spectral lines intensity with increa

Fumonisin B1 is toxic secondary metabolites compound produced by Fusarium spp. on maize and maize products causes health problems to human and animal. Therefore, this research is planned to study the effect of FB1 on the expression of TLR-2 & 4 in liver and kidney cells of mice. Four group of male mice were orally administrated with single dose of FB1 toxin as the following: 0 ppb, 800 ppb, 1200 ppb and 1600 ppb. After two weeks all animals were sacrificed, liver and kidney autopsies were taken and the level of TLR-2 & 4 detected in each four group by immunohistochemistry technique (IHC). According to the IHC examination of groups (1, 2, 3 and 4) strong expression of TLR2 in liver and kidney were (0%, 33.3%, 100%, 100%), respectively. This

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio