This study was aimed to evaluate the effect of spraying nano chitosan loaded with NPK fertilizer and nettle leaf and green tea extracts on the growth and productivity of potato for the spring and fall seasons of 2021.It was conducted at private farm in Wasit Governorate, Iraq, as a factorial experiment (5 × 5) within randomized complete block design using three replicates. The first factor included spraying with four concentrations of chitosan nanoparticles loaded with NPK fertilizer 0, 10. 15 and 20% in addition to chemical fertilization treatment, the second factor was spraying nettle leaf extract 25 and 35 gL-1 and green tea extract with 2 and 4 g.L-1, in addition to the control treatment, spraying with distilled water only. The

The problem of non-Darcian-Bènard double diffusive magneto-Marangoni convection   is considered in a horizontal infinite two layer system. The system consists of a two-component fluid layer placed above a porous layer, saturated with the same fluid with a constant heat sources/sink in both the layers, in the presence of a vertical magnetic field.   The lower porous layer is bounded by rigid boundary, while the upper boundary of the fluid region is free with the presence of Marangoni effects.  The system of ordinary differential equations obtained after normal mode analysis is solved in a closed form for the eigenvalue and the Thermal Marangoni Number (TMN) for two cases of Thermal Boundary Combinations (TBC); th

In the present study, free convection heat and mass transfer of fluid in a square packed bed enclosure is numerically investigated. For the considered geometrical shape, the left vertical wall of enclosure was assumed to be kept at high temperature and concentration while the opposite wall was kept at low temperature and concentration with insulating both the top and bottom walls of enclosure. The Brinkman– Forchheimer extended Darcy model was used to solve the momentum equations, while the energy equations for fluid and solid phases were solved by using the local thermal non-equilibrium (LTNE) model.Computations are performed for a range of the Darcy number from 10-5 to 10-1, the porosity from 0.5 to 0.9, and buoyancy ratio from -15 t

Background: H1N1 influenza pandemic or swine flu was an influenza pandemic first described in Iraq in October 2009 .The virus appeared to be anew strain of H1N1 causes wide range of morbidity and mortality among different genders and age groups as part of worldwide pandemics.Seasonal flu is a contagious respiratory illness caused by influenza viruses that infect the nose, throat, and lungs. It can cause mild to severe illness, and at times can lead to death. The best way to prevent the flu is by getting a flu vaccine each year.

Objectives: Is to determine the morbidity and mortality in different age groups in patients with H1N1 influenza versus those patients with seasonal influenza who were admitted at the same time to AL-kindy

• Islamic art is applied art that searches for everything that is useful and beneficial and Both are properties of Islamic art. Islamic art has many well-established elements and styles and pictures that distinguish it from the rest of the arts among those elements and methods that were used in the architectural cladding artwork Or mosaic murals and mosaic was known in its first form in Babylon in a primitive style similar to it, but the Muslim artist in the era of the Caliphs made the art of mosaic In mosques and palaces.
  Chapter one: This chapter is concerned with introducing the art of mosaic historically and focusing on it.
  Chapter Two: This chapter deals with contemporary Islamic mosaics, especially in Mecca

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

Inelastic longitudinal electron scattering C2 form factor in 48Ca has been utilized
to study the effects of fitting parameters on the sigma meson exchange type
potentials as a residual interaction. By coupling the core particles with model space
particle, where the latter used as an active part of residual interaction in the so called
core polarization process, it is included as a correction with first order perturbation
theory to the main calculation of model space, and the excitation energy has been
carried out with ( ). A model space wave vectors are generated in full fp shell
model with FPD6 as effective interaction with mixing configuration technique and
harmonic oscillator as a single particle wave function.

The present study was performed on 80 female subjects between (30-60) years, who attended the Specialized Center for Endocrinology and Diabetes during the period from April to July; 2011. The subjects were divided into 3 groups : controls , non diabetic autoimmune thyroid patients , and non diabetic autoimmune thyroid patient with renal diseases as complication The results showed a significant increase in serum T 3 T4 levels in hyperthyroidism patients, and significant decrease in serum T3,T4 levels in hypothyroidism patients ,while a significant difference in serum TSH levels in hyperthyroidism and hypothyroidism patients when compared to control group The results show also a significant increase in serum antibodies to thyroid peroxidas

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an