Objective: The study aims to determine the effectiveness of the continuing nursing education
program on nursing staffs knowledge in kidney transplantation unit and to find out the relationship
between nursing staffs knowledge and demographic characteristics (age, gender, education level, and
years of experiences in kidney transplantation unit).
Methodology: A quasiexperemental design (One-group Pretest - Posttest design) was carried out in
kidney transplantation units at Baghdad Teaching Hospitals, from December 2011 to July 2012. A nonprobability
(purposive sample) of (16) nurses were selected from kidney transplant units at Baghdad
teaching hospitals, the choice was based on the study criteria. The data were collected through the
use of constructed questionnaire and consist from two major parts, part one consist of demographic
characteristics contain (9) and part two consist of (58) items of a multiple choice questions
distributed in (8) major sections. Validity of the instrument was determined through a panel of (8)
experts, and reliability through a pilot study. The data were analyzed through the application of
descriptive and inferential statistical analysis procedures.
Results: The findings of the present study indicate that the continuing nursing education program
was effective on knowledge improvement of the participant’s nurses. The total percent of the
improvements resulted by the effects of applying the continuing nursing education program was
(43.31%). And there was a non-significant relationship between nurse’s knowledge and demographic
characteristics (age, gender, education level, and years of experiences in kidney transplantation unit).
Recommendation: Based on the result of the present study the researcher recommends to carrying
out additional studies on application of nursing education programs about nurses practice on kidney
transplantation in kidney transplant units, and nurses should be encouraged to participate in
continuing education programs and training sessions about kidney transplantation.
The pilgrimage takes place in several countries around the world. The pilgrimage includes the simultaneous movement of a huge crowd of pilgrims which leads to many challenges for the pilgrimage authorities to track, monitor, and manage the crowd to minimize the chance of overcrowding’s accidents. Therefore, there is a need for an efficient monitoring and tracking system for pilgrims. This paper proposes powerful pilgrims tracking and monitoring system based on three Internet of Things (IoT) technologies; namely: Radio Frequency Identification (RFID), ZigBee, and Internet Protocol version 6 (IPv6). In addition, it requires low-cost, low-power-consumption implementation. The proposed
CuO-ZnO-Al2O3 catalyst was prepared in the ratios of 20:30:50 respectively, using the coprecipitation method of Cu, Zn and Al carbonates from their nitrate solutions dissolved in distilled water by adding sodium bicarbonate as precipitant.The catalyst was identified by XRD and quantitatively analysis to determine the percentages of its components using flame atomic absorption technique. Also the surface area was measured by BET method. The activity of this prepared catalyst was examined through the oxidation of ethanol to acetaldehyde which was evaluated by gas chromatography.
Understanding the compatibility between spider silk and conducting materials is essential to advance the use of spider silk in electronic applications. Spider silk is tough, but becomes soft when exposed to water. Here we report a strong affinity of amine-functionalised multi-walled carbon nanotubes for spider silk, with coating assisted by a water and mechanical shear method. The nanotubes adhere uniformly and bond to the silk fibre surface to produce tough, custom-shaped, flexible and electrically conducting fibres after drying and contraction. The conductivity of coated silk fibres is reversibly sensitive to strain and humidity, leading to proof-of-concept sensor and actuator demonstrations.
In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.
This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti
... Show MoreThe notion of a Tˉ-pure sub-act and so Tˉ-pure sub-act relative to sub-act are introduced. Some properties of these concepts have been studied.
Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor
... Show More