Loss of drilling fluid in the Nasiriyah oil field can be considered as a big,
serious, and expensive problem at the same time, therefore accurate and integrated
program must be prepared before start drilling in layers that are likely to get loss
circulation. From the available data of well Ns-13, the area of loss was detected in
five layers, which are Dammam, Um- radoma, Tayarat, Shiranish and Hartha since
these layers contain natural cracks and high porosity represented by vugs.
Methods of prevention have been identified by specifying the minimum values
of drilling parameters to reduce hydrostatic pressure, thus reducing equivalent
density of drilling mud during the circulation, depths of casing shoes is
deter

With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

In this research we investigated the corrosion behavior of the commertialy pure titanium and Ti-6Al-4V alloy that coated with hydroxyapatite by electrochemical deposition with applied voltage (6,9,12) Volt from aqueous solution containing Ca(NO3)2.H2O =7.0 gm/l , (NH4)2HPO4 =3.5 gm/l , Na(NO3)2 = 8.5 gm/l in order to improve the bonding strength of hydroxyapetite and medical metals and alloys and increasing the biocompatibility. The coating layer morphology was investigated by XRD, Optical microscope , and SEM tests, the corrosio tests was made by use senthesys simulated body fluid (SBF) , and we found that the propreate voltage for coatint on Ti was 9 Volt and for Ti-6Al-4Vwas12Volt.

 BACKGROUND: Vascular tumors are a heterogeneous group of diseases with biological behavior ranging from a hamartomatous growth to frank malignant. The pathophysiology of lymphangioma, vascular malformation and hemangioma is interconnected, blood vessels known to be the site of origin of hamartomas, venous malformations and some neoplasms as benign, tumor-like growth of vessels (hemangiomas). Angiogenesis is the process of formation of new blood vessels from an existing structure.

Aims of study Assessment of angiogenic potential in benign vascular lesions (hemangioma, lymphangioma and lobular capillary hemangioma) of head and neck region.

 Materials and Methods: Twenty-two formalin-fixed paraffin-embedd

A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these

The formation of a Schiff-base with N2O2 donor atoms derived from the hydrazine segment and its metal complexes are reported. The Schiff-base ligand; N’-((1R,2S,4R,5S,Z)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-ylidene)furan-2-carbohydrazide (HL) was prepared from the reaction of furan-2-carbohydrazide with (1R, 2R, 4R, 5S)-2,4-diphenyl-3-azabicyclo[3.3.1]nonan-9-one (M1) in ethanol medium. The reaction of the title ligand with selected metal ions Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II) gave complexes with the general formula [M(L)Cl2], (where: M = Cr(III), Mn(II), Ni(II), Cu(II), Zn(II) and Cd(II)). Spectroscopic analyses Fourier transform infrared (FT-IR), Nuclear Magnetic Resonance (NMR) Carbon-13 nuclear magnetic res

Objective(s): The study aims to identify the role of sociodemographic factors in predicting the level of psychological hardiness of nurses.

Methodology: A descriptive correlational study conducted in the Medical City hospitals in the city of Baghdad during the period from November 1, 2022 to May 1, 2023 on a sample of 156 male and female nurses.  The validity of the quest

Three cohesionless free flowing materials of different density were mixed in an air fluidized bed to study the mixing process by calculating performance of mixing index according to Rose equation (1959) and to study the effect of four variables (air velocity, mixing time, particle size of trace component and concentration of trace component) on the mixing index and as well as on mixing performance. It was found that mixing index increases with increasing the air velocity, mixing time and concentration of trace component until the optimum value. Mixing index depends on the magnitude of difference in particle size The first set of experiments (salt then sand then cast iron) give higher mixing index and better performance of mixing than the

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay