A method has been demonstrated to synthesise effective zeolite membranes from existing crystals without a hydrothermal synthesis step.

Purpose: to demonstrate the possibility of moving to electronic data exchange dimensions (regulatory requirements, technical requirements, human requirements, senior management support) to simplify the work procedures dimensions (modern procedures, clarity of procedures, short procedures, availability of information and means required. The simplicity of the models used because of its importance to keep abreast of recent developments in the service of municipal works through the application of electronic data interchange, which simplifies procedures and out of the routine in the performance of the work of municipal departments has developed. It was applied to Municipality (Hilla) so that the transformation

The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management

The current research aims to identify the time-management skills based on the post-test of the experimental group as well as to examine the effect of a training program on developing the skills of managing time among the study sample. To achieve the research objectives, the researcher designed a scale of time management skill included (30) paragraphs. The research reached that the training program is significantly effective in managing and organizing time. There are statistically significant differences in pre-posttest between the experimental and control groups.

Background: Generally, genetic disorders are a leading cause of spontaneous abortion, neonatal death, increased morbidity and mortality in children and adults as well. They a significant health care and psychosocial burden for the patient, the family, the healthcare system and the community as a whole. Chromosomal abnormalities occur much more frequently than is generally appreciated. It is estimated that approximately 1 of 200 newborn infants had some form of chromosomal abnormality. The figure is much higher in fetuses that do not survive to term. It is estimated that in 50% of first trimester abortions, the fetus has a chromosomal abnormality. Aim of the study: This study aims to shed some light on the results of chromosomal studies per

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise