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Evaluations of Intervention Program on Nurses` Practices about Care of Children with Diabetic Ketoacidosis
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Objective(s): To assess the adequacy of mediation program on medical attendants practice toward care of kids with diabetic's ketoacidosis. Methodology: A quasi-experimental design that applied at teaching hospitals for pediatric in AL Ramadi city to establish the Effectiveness of Intervention Program on Nurses` Practices about Care of Children with Diabetic Ketoacidosis from 3th of March 2022 till 20 of March 2023. Non-probability (purposive) sample of (50), likewise was alienated into the study (experimental) group. The study group included (50) nurses non-randomly selected from AL-Ramadi Teaching Hospital.

A preliminary study has conducted in AL-Ramadi Teaching Hospital The whole number of nurses was (20) for 4 days, by using questions of the open-ended answers. The validity of the questionnaire and educational program are tested by (25) experts from related fields.

Results: Reliability of survey and program tried through a pilot investigation of It included (10) medical caretakers, non-randomly selected from AL-Ramadi Teaching Hospital (this sample was excluded from the original study sample) by using test-retest technique and Cronbach's Alpha measurement, the results for practice was (0.933).

The study findings have proved the effectiveness of the program through high percent obtained between the pre-test and post-test1 and post-test 2. It was sample study group results in pre-test is 31.76% (19) with regard to them on a not acceptable level, but post-test 1 is 77.04% (26) through esteem to them on a good level, and also post-test 2 remains 80.98% (24) with esteem to them on a good level.

Conclusions: The study concluded that the intervention program has significant effect on nurses practice about diabetic's ketoacidosis. It is improving nurses practice from poor to good practice after implementation of the intervention program.

Recommendations: the study has recommended that Training courses and workshops for nurses of the hospital teaching of pediatric regarding Diabetics Ketoacidosis care, increasing nurses' numbers especially those who hold nursing Bachelor's degrees to work at pediatric teaching hospitals for their ability and background.

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Publication Date
Sat Jan 01 2022
Journal Name
Geminivirus : Detection, Diagnosis And Management
Geminiviruses occurrence in the middle east and their impact on agriculture in Iraq
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Tue Oct 01 2019
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A RE-SATURATION IMPACT ON SOIL RETENTION CURVE FOR FIVE DIFFERENT TEXTURED SOILS
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Soil water retention curves (SWRCs) are crucial for characterizing soil moisture dynamics and are particularly relevant in the context of irrigation management. A study was carried out to obtain the SWRC, inflection point, S index, pore size distribution curve, macro porosity, and air capacity from samples submitted to saturation and re-saturation processes. Five different-texture disturbed soil samples Sandy Loam, Loam, Sandy Clay Loam, Silt Loam, and Clay were collected. After obtaining SWRC, each air-dried soil samples were submitted to particle size distribution and clay dispersed in water analyses to verify the soil lost clay. The experimental design was completely randomized with three replications using two processes of SWRC (saturat

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Wed May 26 2021
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Rotational Piezoelectric Energy Harvesting: A Comprehensive Review on Excitation Elements, Designs, and Performances
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Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect

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Response surface methodology: A review on its applications and challenges in microbial cultures
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Wed Aug 28 2024
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A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Thu Jun 29 2017
Journal Name
College Of Islamic Sciences
Imam Yahya bin Saeed Al-Ansari and his jurisprudential views on fasting issues
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In The Name of Allah Most Gracious Most Merciful

 

The reason for choosing this topic was:

 

First: It is my great love for the Prophet Muhammad, may God’s prayers and peace be upon him, his family, his companions, his followers, the followers of their followers, and the scholars after them until the Day of Judgment.

 


Secondly: Showing a great jurisprudential figure who has contributed by speaking about important jurisprudential issues in the life of this nation, and bringing out this immortal book to put it in the hands of scholars, so I chose a figure from the followers (may God be pleased with them all).

 


Third: The study of the jurisprudence of the companions

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Publication Date
Mon May 30 2022
Journal Name
The Journal Of Infection In Developing Countries
SARS-CoV-2 viral shedding and susceptibility: perspectives on gender and asymptomatic patients
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Despite efforts to contain and manage the SARS-CoV-2 outbreak which was declared a public health emergency of international concern in January 2020 by the World Health Organization (WHO), the COVID-19 pandemic still remains a major global challenge. Patients who display the classical symptoms of the infection are easily identified, tested, isolated and monitored. However, many cases of infected asymptomatic patients have been documented. These patients are not easily identified even though many evidences suggest that they can spread the virus to others. How and why these COVID-19 asymptomatic presentations occur remain unclear. The many theories and views are conjectural, and supporting evidences are still needed. In this review, we

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Publication Date
Thu Jun 06 2024
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Journal Of Applied Engineering And Technological Science (jaets)
Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG)
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Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

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