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Augmenting solidification dynamics in double-pipe latent heat storage: Exploring optimized curved fin configurations
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This work is to examine the employment of curved fins to boost heat recovery in a double-pipe containment system filled with phase change material (PCM). The study utilizes CFD modeling, validated against experimental benchmarks, to evaluate how various geometric parameters of curved fins affect system performance. Findings demonstrate that adjusting the fin angular curvature from 60◦ to 180◦ yielded a 22.1 % decrease in the time required for solidification while simultaneously improving heat recovery efficiency by 32.0 %. When the fin base spacing was increased from 5 mm to 15 mm, the system showed a 14.5 % solidification time saving and a 20.9 % heat recovery improvement. Furthermore, modifying the joining angle between upper fins from 0◦ to 60◦ resulted in both a 25.9 % faster solidification rate and a 34.7 % boost in heat recovery capability. The study reveals that the optimized curved fin design significantly outperforms both traditional longitudinal fin configurations and systems without fins, demonstrating a 65.1 % faster solidification and a 190.5 % superior heat recovery rate compared to systems without fins. These results offer valuable design insights for developing more efficient thermal energy storage systems, with particular relevance for solar energy applications

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Fri May 16 2025
Journal Name
Journal Of Forensic Medicine And Toxicology
Exploring the Effect of Disruptive Behavioral Disorders on Quality of Learning Among School Children: Across-sectional Study
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Background: disruptive behavioral disorders among primary school children is oone of the most popular, which has  negative social, psychological, educational, and physical repercussions on children and families. Objective: This study sought to determine effect disruptive behavioral disorders quality of learning among school chil dren. Methods: A descriptive cross-sectional design study was conducted at Baquba primary schools in Diyala Governorate,  and the study period was extended from October 6th, 2024, to January 15th, 2025. A nonprobability purposive sample was  used to include 275 teachers working at selected Baquba primary schools, Iraq. Data were collected using a self-admin istered questionnaire, two components of the st

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Publication Date
Tue Oct 24 2023
Journal Name
Environmental Engineering Research
Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview
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Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

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Publication Date
Sat Jun 01 2024
Journal Name
Materials And Structures
Exploring the efficacy of sawdust ash as a mineral filler substitute for the production of asphalt mixtures
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Many waste materials can be repurposed effectively within asphalt concrete to enhance the performance and sustainability of pavement. One of these waste materials is sawdust ash (SDA). This study explores the beneficial use of SDA as a substitute for limestone dust (LD) mineral filler in asphalt concrete. The replacement rate was 0%, 15%, 30%, 45%, and 60% by weight of total mineral filler. Scanning electron microscopy (SEM) was employed to assess the surface morphology of Sawdust (SD), SDA, and LD. In addition, a series of tests, including Marshall stability and flow, indirect tensile strength,moisture susceptibility, and repeated uniaxial loading tests, were conducted to examine the performance characteristics of asphalt mixtures of diffe

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Publication Date
Thu Jun 01 2017
Journal Name
American Journal Of Pharmaceutical Education
Exploring Electronic Communication Modes Between Iraqi Faculty and Students of Pharmacy Schools Using the Technology Acceptance Model
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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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

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Publication Date
Sat Jun 01 2024
Journal Name
Partial Differential Equations In Applied Mathematics
Improving the hepatitis viral transmission model’s dynamics by vaccination and contrasting it with the fractional-order model
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We investigate mathematical models of the Hepatitis B and C viruses in the study, considering vaccination effects into account. By utilising fractional and ordinary differential equations, we prove the existence of equilibrium and the well-posedness of the solution. We prove worldwide stability with respect to the fundamental reproduction number. Our numerical techniques highlight the biological relevance and highlight the effect of fractional derivatives on temporal behaviour. We illustrate the relationships among susceptible, immunised, and infected populations in our epidemiological model. Using comprehensive numerical simulations, we analyse the effects of fractional derivatives and highlight solution behaviours. Subsequent investigatio

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Building a mathematical model of the transportation problem under the dynamics of demand restrictions with practical application
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Abstract\

In this research we built a mathematical model of the transportation problem  for data of General Company for Grain Under the environment of variable demand ,and situations of incapableness to determining the supply required quantities as a result of economic and commercial reasons, also restrict flow of grain amounts was specified to a known level by the decision makers to ensure that the stock of reserves for emergency situations that face the company from decrease, or non-arrival of the amount of grain to silos , also it took the capabilities of the tanker into consideration and the grain have been restricted to avoid shortages and lack of processing capability, Function has been adopted

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Publication Date
Wed Jun 11 2008
Journal Name
Journal Of Al-nahrain University
ANALYSIS OF A MOLECULAR DYNAMICS SIMULATION OF THE ACETYLCHOLINESTERASE ENZYME AND ITS COMPLEX WITH (AXILLARIDINE-A) INHIBITOR
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Molecular dynamics (MD) simulations were carried out in order to investigate the binding mode of axillaridine-A at the active site of human acetylcholinesterase (AChE) enzyme. 2.0 nanosecond of MD simulations was made for the protein and the complex to dynamically explore the active site and the behavior of the ligand at the peripheral AChE binding site. These calculations for the enzyme alone showed that the active site of AChE is located at the bottom of a deep and narrow cavity whose surface is lined with rings of aromatic residues and Tyr72 is almost perpendicular to the Trp286 ring and forms a stable - interaction. The size of the active site of the complex decreases with time due to increase the interaction. Axillaridine-A forms

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Theoretical Investigation of Charge Transfer Dynamics from Sensitized Molecule D35CPDT Dye to SnO_2 and TiO_2 Semiconductor
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In this research, the dynamics process of charge transfer from the sensitized  D35CPDT dye to tin(iv) oxide( ) or titanium dioxide (  ) semiconductors are carried out by using a quantum model for charge transfer. Different chemical solvents Pyridine, 2-Methoxyethanol. Ethanol, Acetonitrile, and Methanol have been used with both systems as polar media surrounded the systems. The rate for charge transfer from photo-excitation D35CPDTdye and injection into the conduction band of  or  semiconductors vary from a  to  for system and from a   to  for the system, depending on the charge transfer parameters strength coupling, free energy, potential of donor and acceptor in the system. The charge transfer rate in D35CPDT /  the syst

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