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Nesting Technique : It’s Effects on Preterm Cardiorespiratory Indicators
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Background: Premature infant born with immature body system, their organs are not ready for extra uterine life, and they are unable to deal with external stress, which could alter body functions such as cardio-respiratory function. In addition, poor muscle tone increases the chance of developing an abnormal posture. To reduce this instability, applying developmental care such as nesting is vital to promote cardio-respiratory stability, maintain position, and reduce stress in preterm.      Objectives: The study aims to assess the impact of the nesting technique on preterm cardio-respiratory parameters in various positions (supine, prone, and right lateral).       Methodology: The research used randomized controlled trial design. By simple random sampling technique was choose 60 preterm infant, and they were divided into four groups equally (supine, prone, right lateral, and control group). The cardio-respiratory parameters (heart rate, respiratory rate, and oxygen saturation) were measured before and after applying the nesting and positioning techniques for 3 consecutive days. Data were analyzed by Statistical Package for Social Sciences (SPSS) program.                                                                                  Results: The study results showed a significant difference in the mean score of cardio-respiratory after three days of nesting technique with lateral, supine, and prone position groups at p= 0.000. While the control group showed there was non-significant change in the mean score of HR, RR, and Spo2 at p > 0.05.          Conclusion: The Study concluded that the nesting technique was effective for stabilizing the cardio-respiratory parameters of preterm infants. The authors recommended routinely using nesting with the ideal position technique in preterm as a part of  developmental care at the neonatal intensive care unit

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Pathological And Immunological Study On Infection With Escherichia Coli In ale BALB/c mice
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Publication Date
Sun Oct 01 2017
Journal Name
Fuel
Effect of temperature and SiO2 nanoparticle size on wettability alteration of oil-wet calcite
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Nanofluid treatment of oil reservoirs is being developed to enhance oil recovery and increase residual trapping capacities of CO2 at the reservoir scale. Recent studies have demonstrated good potential for silica nanoparticles for enhanced oil recovery (EOR) at ambient conditions. Nanofluid composition and exposure time have shown significant effects on the efficiency of EOR. However, there is a serious lack of information regarding the influence of temperature on nanofluid performance; thus the effects of temperature, exposure time and particle size on wettability alteration of oil-wet calcite surface were comprehensively investigated; moreover, the stability of the nanofluids was examined. We found that nanofluid treatment is more efficie

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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Engineering Software
System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Mon Oct 01 2018
Journal Name
Chemical Physics Letters
Effect of heat treatment on photoelectrochemical performance of hydrothermally synthesised Ag2S/ZnO nanorods arrays
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Wed Dec 27 2023
Journal Name
Biomed Research International
Efficacy of Autogenous Dentin Biomaterial on Alveolar Ridge Preservation: A Randomized Controlled Clinical Trial
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Background. After tooth extraction, alveolar bone resorption is inevitable. This clinical phenomenon challenges dental surgeons aiming to restore esthetic and function. Alveolar ridge preservation can be applied to minimize dimensional changes with a new socket grafting material, an autogenous dentin graft, produced by mechanically and chemically processing natural teeth. This study assessed the safety and efficacy of using autogenous dentin biomaterial in alveolar ridge preservation. Materials and Methods. Patients with nonrestorable maxillary anterior teeth bounded by natural sound teeth were included in this study. After a detailed clinical and tomographic examination, eligible participants were randomly allocated into two groups

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Publication Date
Fri Feb 01 2019
Journal Name
Iraqi Journal Of Information & Communications Technology
Evaluation of DDoS attacks Detection in a New Intrusion Dataset Based on Classification Algorithms
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Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Influence of Silver and Copper Nanoparticles on the Enzymatic Activity of Soil-Borne Microorganisms
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Influence of metal nanoparticles synthesized by microorganisms upon soil-borne microscopic fungus Aspergillus terreus K-8 was studied. It was established that the metal nanoparticles synthesized by microorganisms affect the enzymatic activity of the studied culture. Silver nanoparticles lead to a decrease in cellulase activity and completely suppress the amylase activity of the fungus, while copper nanoparticles completely inhibit the activity of both the cellulase complex and amylase. The obtained results imply that the large-scale use of silver and copper nanoparticles may disrupt biological processes in the soil and cause change in the physiological and biochemical state of soil-borne microorganisms as well.

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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