The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

Numerical simulations have been carried out on the solar chimney power plant systems. This paper gives the flow field analysis for a solar chimney power generation project located in Baghdad. The continuity, Naver-stockes, energy and radiation transfer equations have been solved and carried out by Fluent software. The governing equations are solved for incompressible, 3-D, steady state, turbulent is approximated by a standard k -  model with Boussiuesq approximation to study and evaluate the performance of solar chimney power plant in Baghdad city of Iraq. The different geometric parameters of project are assumed such as collector diameter and chimney height at different working conditions of solar radiation intensity (300,450,600,750

Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image

This work predicts the effect of thermal load distribution in polymer melt inside a mold and a die during injection and extrusion processes respectively on the structure properties of final product. Transient thermal and structure models of solidification process for polycarbonate polymer melt in a steel mold and die are studied in this research. Thermal solution obtained according to solidify the melt from 300 to 30Cand Biot number of 16 and 112 respectively for the mold and from 300 to 30 Cand Biot number of 16 for die. Thermal conductivity, and shear and Young Modulus of polycarbonate are temperature depending. Bonded contact between the polycarbonate and the steel surfaces is suggested to transfer the thermal load. The temperat

This research includes structure interpretation of the Yamama Formation (Lower Cretaceous) and the Naokelekan Formation (Jurassic) using 2D seismic reflection data of the Tuba oil field region, Basrah, southern Iraq. The two reflectors (Yamama and Naokelekan) were defined and picked as peak and tough depending on the 2D seismic reflection interpretation process, based on the synthetic seismogram and well log data. In order to obtain structural settings, these horizons were followed over all the regions. Two-way travel-time maps, depth maps, and velocity maps have been produced for top Yamama and top Naokelekan formations. The study concluded that certain longitudinal enclosures reflect anticlines in the east and west of the study ar

Gas compressibility factor or z-factor plays an important role in many engineering applications related to oil and gas exploration and production, such as gas production, gas metering, pipeline design, estimation of gas initially in place (GIIP), and ultimate recovery (UR) of gas from a reservoir. There are many z-factor correlations which are either derived from Equation of State or empirically based on certain observation through regression analysis. However, the results of the z-factor obtained from different correlations have high level of variance for the same gas sample under the same pressure and temperature. It is quite challenging to determine the most accurate correlation which provides accurate estimate for a range of pressures,

With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the