Mishrif Formation is the most important succession in the southern part of Iraq and has extensive distribution in the Arabian Plate. The present study  focuses upon the sequence stratigraphy and development of Mishrif Formation basin in four oil fields within the eastern part of the Mesopotamian Zone are:-  Halfaya (Hf-1), Noor (No-1) and Abu Ghirab (AG-3) and Fauqi oil fields (Fq-1).

     There are several types of microfacies were distinguished in the succession of the Mishrif Formation. Their characteristic of the grain types and carbonate texture enabled to interpret of five facies associations (depositional environments) were observed in this formation, they are: deep ma

Aqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Background: The skull base and the hard palate contain many anatomical features that make them rich in information which are useful in sex differentiation; in addition to that they have the ability to resist the hardest environmental conditions that support them in making sex differentiation. Three dimensional computed tomographic techniques has important role in differentiation between sex since it offers images with very accurate data and details of all anatomical structures with high resolution. This study was made to study sex variations among Iraqi sample by craniometric linear measurements of the hard palate and the skull base using 3D reconstructed Computed Tomographic scan. Materials and methods: This study composed of 100 Iraqi su

Plumbago (Plumbaginaceae) is a genus of 10-20 species of flowering plants used in traditional Indian medicine, native to warm temperature to tropical regions of the world. The roots of Plumbago europaea, the Iraqi species of Plumbago, have been used for the treatment of cancer, rheumatoid arthritis, and dysmenorrhea. The main active constituents from dried powdered leaves and roots of Plumbago europaea were extracted by Soxhlet apparatus using ethyl acetate, the main active constituent was characterized by spectroscopic analysis (IR, ¹H NMR, and ¹³C NMR)   as plumbagin. Quantitative and qualitative study of plumbagin in the roots and leaves extracts was carried out by HP

A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.