Two oil wells were tested to find the abnormal pressure zones using sonic log technique. We found that well Abu-Jir-3 and Abu-Jir-5 had an abnormal pressure zones from depth 4340 to 4520 feet and 4200 to 4600 feet, respectively. The maximum difference between obtained results and the field measured results did not exceed 2.4%.
In this paper, the formation pressures were expressed in terms of pressure gradient which sometimes reached up to twice the normal pressure gradient.
Drilling and developing such formations were dangerous and expensive.
The plotted figures showed a clear derivation from the normal trend which confirmed the existence of abnormal pressure zones.

Objectives: The study aimed to assess the level of pediatric nurses' knowledge toward children with Guillain-Barre
syndrome (GBS) and to find out the relationships between nurses' knowledge and their demographic data.
Methodology: A purposive “non probability” sample of (30) nurses was selected from medical neurological wards and
Respiratory Care Units of Children Welfare Pediatric Teaching Hospital, Child’s Center Pediatric Teaching Hospital,
AL-Kadhemia Teaching Hospital, Baghdad Teaching Hospital, and Neurological Science Hospital which has started
from March 5
th 2009 to April 30th 2009. The study instrument consists of two parts. The first part is concerned with
nurses' demographical characteristic and the

The effect of superficial gas velocity within the range 0.01-0.164 m/s on gas holdup (overall, riser and down comer), volumetric oxygen mass transfer coefficient, liquid circulation velocity was studied in an internal loop concentric tubes airlift reactor (working volume 45 liters). It was shown that as the u_sg increases the gas holdup and also the liquid circulation velocity increase. Also it was found that increasing superficial gas velocity lead to increase the interfacial area that increases the overall oxygen mass transfer coefficient. The hydrodynamic experimental results were modeled with the available equations in the literature. The predicted data gave an acceptable accuracy with the empirical data.

The final

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

In this research, design of advanced material for sunlight conversion requires focused research to obtain efficient photocatalytic system. Nanostructured ZnO was synthesized using spin coating technique. The structural, morphological and optical properties of annealed nanostructured ZnO thin film at 390 Co for 3 hours were characterized by x-ray diffraction, atomic force microscope AFM and UV-VIS spectrophotometer. Nanostructured ZnO was applied for removal Methylene Blue (MB) dye from water using sunlight induced photocatalytic process. Overall degradation of MB/ZnO was achieved after 120 minutes of sunlight irradiation while it needs more time for MB alone. The reaction rate constant fit pseudo first order for MB/ZnO degradation was 0.

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl