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Variants of Hybrid Genetic Algorithms for Optimizing Likelihood ARMA Model Function and Many of Problems
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Publication Date
Tue Jan 01 2019
Journal Name
Spe/aapg/seg Asia Pacific Unconventional Resources Technology Conference
Optimizing the dispersion of coal fines using Sodium Dodecyl Benzene Sulfonate
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Coal fines are highly prone to be generated in all stages of Coal Seam Gas (CSG) production and development. These detached fines tend to aggregate, contributing to pore throat blockage and permeability reduction. Thus, this work explores the dispersion stability of coal fines in CSG reservoirs and proposes a new additive to be used in the formulation of the hydraulic fracturing fluid to keep the fines dispersed in the fluid. In this work, bituminous coal fines were tested in various suspensions in order to study their dispersion stability. The aggregation behavior of coal fines (dispersed phase) was analyzed in different dispersion mediums, including deionized-water, low and high sodium chloride solutions. Furthermore, the effect of Sodium

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Publication Date
Thu Dec 25 2025
Journal Name
Sultan Qaboos University Medical Journal
Clinical and Molecular Analysis of ATP7B Variants Identified by Next-Generation Sequencing in Iraqi Adults With Wilson Disease
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Objectives: This study aimed to identify and analyse ATP7B variants in Iraqi adults with Wilson disease (WD) by long-read next-generation sequencing. Methods: This cross-sectional study was conducted at the Poisoning Consultation Center at Ghazy Al-Hariri Hospital for Surgical Specialties and the Gastroenterology Consultation Clinic at Baghdad Teaching Hospital, Medical City in Baghdad, Iraq. Unrelated patients with clinical and biochemical features suggestive of WD were recruited between October 2022 and October 2023. DNA was extracted from peripheral blood samples. Variants in the ATP7B gene were identified using long-read next-generation sequencing and then analysed by in-silico tools. Results: A total of 45 patients were recruited in

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Publication Date
Thu Jun 13 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Association of the MDR1 Variants (rs2032582 and rs2032583) with Steroid Response in Iraqi Children with Idiopathic Nephrotic Syndrome
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Background: Several studies linked the development of steroid-resistant nephrotic syndrome (SRNS) to genetic variations in the multidrug resistance 1 (MDR1) gene, though a disparity in findings was underlined among children with different ethnic origins. Objective: This study examined the relationship between MDR1 variants (rs2032582 and rs2032583) and the risk of developing SRNS in Iraqi patients with idiopathic nephrotic syndrome (INS). Methods: This case-control study included children with steroid-sensitive INS (SSNS; n=30) and SRNS (n=30) from the Babylon Hospital for Maternity and Pediatrics. Sanger sequencing was used to determine the participants’ genotypes. Results: The rs2032582 genotypes and alleles were not associated

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Publication Date
Wed Jan 02 2019
Journal Name
Pramana
The description of quantum dielectric function for insulators over Bethe surface
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Publication Date
Wed Jul 01 2026
Journal Name
Nature Communications
Structural basis for independent pore function of Vpb4 from Bacillus thuringiensis
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Abstract<p> The Bacterial_Exotoxin_B family constitutes translocating pore-forming proteins that function as the binding (B) component in the binary AB Toxin mechanism. While the two-component system of the family is consistent among well-characterised members, the single-component Vpb4 subclass from entomopathogenic <italic>Bacillus thuringiensis</italic> challenges this dogma. Here, through single-particle cryo-electron microscopy, we elucidate the inserted pore structure of a Vpb4 member, Vpb4Aa2, at 2.2 Å resolution. The structure reveals distinguishing features from other family members: missing molecular bottleneck</p> ... Show More
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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
A Parallel Adaptive Genetic Algorithm for Job Shop Scheduling Problem
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Publication Date
Fri Apr 01 2011
Journal Name
Al-mustansiriyah Journal Of Science
A Genetic Algorithm Based Approach For Generating Unit Maintenance Scheduling
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Publication Date
Fri Sep 18 2020
Journal Name
Hal Open Science
Adaptive Approximation Control of Robotic Manipulators: Centralized and Decentralized Control Algorithms
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The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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