Objective: The study aims to evaluate nurses' knowledge toward care of unconscious adult patients and identify the relationship between nurses’ knowledge toward care of unconscious adult patient and their demographic characteristics of age, gender, Marital Status, level of qualification and years of experience. Methodology: A descriptive study (quantitative design) was carried out by using quasi experimental design to study nurses' knowledge, attitudes and practices toward care of unconscious adult patients at teaching hospitals in Al-Hilla City from September 2018 up to June 2019. A purposively sample has been chosen in which included 60 nurses who work in ICUs within two hospitals (Imam Al-Sadiq teaching hospital and Al-Hilla general teaching hospital). The sample has been collected by using the tool that involves four parts. The first part is demographical data for a study sample which consists of 10 items, the second part is multiple choice questions related to nurses' knowledge which consists of 32 items, The tool has been validated by 11 experts, all of them have experience more than 10 years, a reliability is determined by Crohn Bach correlation where r= 0.92 . The analyzed data have been stated during using of descriptive statistics (frequencies, percentages, mean of scores, Standard deviation) and inferential statistics (Coefficient alpha correlation and ANOVA). Results: The study showed that the majority of the participants in the study were males aged between 20-29 years of bachelor's degree in nursing. More than half of them were single and had years of experience in hospital and in intensive care unit (1-5) years, and half of the participants were doing their work in the morning and evening, within 24 hours, and the majority did not participate in training sessions on the intensive care unit. The study also showed that nurses' knowledge toward care of unconscious adult patients was enough. Recommendations: Advanced video programs, specific meetings, programs, workshops, training activities and seminars, and Booklet are should be provided for nurses on how to care of unconscious adult patients to increase their knowledge, it's recommended to the Ministry of Health to provide the necessary advanced supplies and equipment for use in intensive care units (ICUs) and It is recommended for future studies conduction.
In the present study, magnet silica-coated Ag2WO4/Ag2S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag2WO4 and pure Ag2S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the heterojunction be
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
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In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin
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This investigation reports application of a mesoporous nanomaterial based on dicationic ionic liquid bonded to amorphous silica, namely nano-N,N,N′,N′-tetramethyl-N-(silican-propyl)-N′-sulfo-ethane-1,2-diaminium chloride (nano-[TSPSED][Cl]2), as an extremely effectual and recoverable catalyst for the generation of bis(pyrazolyl)methanes and pyrazolopyranopyrimidines in solvent-free conditions. In both synthetic protocols, the performance of this catalyst was very useful and general and presented attractive features including short reaction times with high yields, reasonable turnover frequency and turnover number values, easy workup, high performance under mild conditions, recoverability and reusability in 5 consecutive runs without lo
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In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin
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This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
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