Gold nanoparticles AuNPs have proven to be powerful tools in various nanomedicine applications, because of their photo-optical distinctiveness and biocompatibility. Noble metal gold nanoparticles was prepared by pulsed laser ablation method (1064-Nd: YAG with various Laser power from 200 to 800 mJ and 1 Hz frequency) in distil water. The process was characterized using UV-VIS absorption spectroscopy. Morphology and average size of nanoparticles were estimated using AFM and X-ray diffraction (XRD) analysis which show the nature of gold nanoparticles (AuNPs). Antibacterial activity of gold nanoparticles as a function of particles concentration against gram negative bacterium Escherichia coli and gram positive bacterial Staphylococcus aureu

     This research aims to study the suitability of the Fatha Formation clay deposits for the brick industry in the Zurbatiya area, Wasit Government. Two sites (Al-Salam police station and Al-Taff station) were selected. The clay deposits were subjected to particle size analysis, atterberg limits, chemical and mineralogical analyses. The samples have 31.45% clay, 52.91% silt, and 15.64% sand. Chemical analyses revealed that SiO₂ and CaO are the clay deposits' main components, indicating the high content of quartz and calcium carbonate. The mineralogical analysis by XRD techniques indicated that quartz, calcite, feldspar, gypsum, and dolomite are the non-clay minerals; Kaolinite, illite, palygorskite and chlorite are the mo

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

     Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, ​​precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi

Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and La

Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

The Bouguer gravity and magnetic RTP data were used to detect the depth of basement rocks in middle and south Diyala Province, east Iraq. The depth of the basement rocks was calculated by using the Source Parameter Imaging (SPI) method. New attempt is achieved to applied the SPI technique to the gravity values to estimate the depth of basement rocks. The depths of basement map derived from gravity data range 8-14 km, the depth of basement map derived from magnetic data range 9-13.5 km and the basement depth prepared by C.G.G, 1974 range 9-11 km. The derived maps from SPI method and that prepared by C.G.G, 1974 show good matching in the distribution of the depths of the study area. This study showed that basement’s depth range from

Water quality has become an important requirement in recent years, assumed the enormous pressure on water resources. As a result of the rapid population growth and climate change. Seven sampling stations were chosen along the river, specifically near the important cities. After analyzing the water samples, it was found that pH values range from (7.1 to 7.5). The values of total dissolved ions ranged from (730 to 1390) mg/l. It was found that the sodium percentage in the river water samples ranged from (36.8 to 51.3), which is acceptable for irrigation purposes. The water content of magnesium hazard ranges from (45.1 to 48.6), it is within the permissible limits for watering purposes. The residual sodium amounts range from (-4.01 to -2.86