Ziziphora persica Bunge is recorded as a new Study in Iraq. This species has been collected from Jabal Sinjar in Nineveh province in the north western part of Iraq. The morphological characters, habitat and geographical distribution of the species with a key to Ziziphora L. species in Iraq have been provided.

the electron correlation effect for inter-shell can be described by evaluating the fermi hole and partial fermi hole for Li atom comparing with Be+ and B+2 ions

The graphic field invests the visual space then shows the shape by all means of expression that have a certain meaning. The research is interested in studying the iconic form in the modern graphic design through investing names and flags and the extent of their action in the social life and invest them from one to another looked at from viewpoint of trading and consumption and investing their wide popularity. The study problem is manifested in the following question:
1- Does the iconic form help in ad circulation?
The importance of the research lies in the following:
1- Reading the visual iconic form through deciphering its current symbols. The form combines a concept and a case or a form and meaning.

The theoretical fra

The importance of this research came through the question: Are there a privacy in the design in the ceramic arts, what are they? What are the basis of design for the ceramic art sculptures?The study refers to the design privacy in the contemporary ceramic arts, not as a serviceable art, but the art of being a dialectic collecting the arts across the craft and compositionThis research is the first study to look at the privacy of design and the connection with the formation of the large sizes ceramic art sculptures, and what they have as privacy of design and the way of formations.To highlight on the most prominent technical problems facing the ceramist in the production of so sculptural worksThe need for the study comes to help the worker

A mathematical model constructed to study the combined effects of the concentration and the thermodiffusion on the nanoparticles of a Jeffrey fluid with a magnetic field effect the process of containing waves in a three-dimensional rectangular porous medium canal. Using the HPM to solve the nonlinear and coupled partial differential equations. Numerical results were obtained for temperature distribution, nanoparticles concentration, velocity, pressure rise, pressure gradient, friction force and stream function. Through the graphs, it was found that the velocity of fluid rises with the increase of a mean rate of volume flow and a magnetic parameter, while the velocity goes down with the increasing a Darcy number and lateral walls. Also, t

Abstract: Microfluidic devices present unique advantages for the development of efficient drug assay and screening. The microfluidic platforms might offer a more rapid and cost-effective alternative. Fluids are confined in devices that have a significant dimension on the micrometer scale. Due to this extreme confinement, the volumes used for drug assays are tiny (milliliters to femtoliters).

 In this research, a microfluidic chip consists of micro-channels carved on substrate materials built by using Acrylic (Polymethyl Methacrylate, PMMA) chip was designed using a Carbon Dioxide (CO₂) laser machine. The CO2 parameters have influence on the width, depth, roughness of the chip. In order to have regular

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class