This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

The picture has taken a place that sometimes enables it to take precedence over media analysis، psychology، and political communication.
The image has the ability to influence to obtain persuasion، not only emotionally or
dramatically، but also on the level of commercial and political persuasion. In every
image، the intention of that persuasion is hidden.
It can be identified by a set of underlying dimensions such as vitality، social dominance، and confidence، for which a group of specific suggestions or movements، such
as a smile، the movement of hands، or the nature and way of looking with the eyes، is
established. The visual image often precedes its verbal counterpart in the proce

The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

Background:- Cholesterol is high in ascetic fluid due
to malignancy and other causes of exudates.
Objective:-To use cholesterol as a marker to
differentiate between exudative and transudative
ascetic fluid and to compare that with other routine
parameters.
Methods:-Twenty eight patients were included in this
study 17 females with mean age of 41.9 years, 11
males with mean age of 48.2 years. The patients were
divided in group I suspected transudate, and group II
suspected exudate according to history and clinical
examination.
Ascetic fluid samples were sent for total protein,
albumin, and cholesterol measurement blood samples
were sent for serum protein and albumin measurement.
Results:-In this

Human serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nan