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Improving asphalt concrete durability through soda lignin powder
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Lignin has emerged as a promising asphalt binder modifier due to its sustainable and renewable nature, with the potential to improve flexible pavement performance. This study investigates the use of Soda Lignin Powder (SLP), derived from Pinus wood sawdust via alkaline treatment, as an asphalt modifier to enhance mixture durability. SLP was characterized using Fourier Transformation Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy with Energy Dispersive X-ray Analysis (SEM/EDX), revealing significant changes in its chemical structure post-extraction. These analyses showed the presence of phenolic units, including hydroxyphenyl propane, syringyl, and guaiacyl units. The morphology of SLP was identified as irregular and spherical particles consisting of carbon, oxygen, nitrogen, and sulfur. Experimental evaluations involved three SLP dosages (2%, 4%, and 6% by weight of asphalt binder), with tests for penetration, softening point, ductility and rotational viscosity. Additionally, the asphalt mixtures were tested for their performance in terms of moisture susceptibility, resilient modulus, permanent deformation, and fatigue resistance. Results indicated that SLP effectively reduces the temperature susceptibility of asphalt by increasing its stiffness and rotational viscosity. Furthermore, mixtures with 6% SLP showed enhanced moisture resistance, with a Tensile Strength Ratio (TSR) of 86.98%, a 74.1% reduction in accumulated permanent deformation at 10,000 cycles, and a 38.1% increase in the Cracking Tolerance Index (CT index) compared to the control mix (0% SLP content). These findings confirm that SLP has the potential to be an effective additive in the design of asphalt mixture. Moreover, it allows producing endurable mixtures with higher resistance to distress.

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Publication Date
Thu Nov 27 2025
Journal Name
Frontiers In Robotics And Ai
Design of modified fractional-order PID controller for lower limb rehabilitation exoskeleton robot based on an improved elk herd hybridized with grey wolf and multi-verse optimization algorithms
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Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

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Publication Date
Mon Apr 15 2013
Journal Name
Eng. & Tech. Journal,
Assessment the Impact of Different Hydrated Lime Addition Methods on Fatigue Life Characteristic
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The purpose of this study is to evaluate the effect of hydrated lime addition methods as filler replacement on fatigue performance of Hot Mix Asphalt (HMA). Three types of addition methods of hydrated lime were introduced namely dry HL on dry aggregate and saturated surface aggregate above 3% and slurry HL on dry aggregate, ordinary Lime stone powder was reduced by three HL percentage (1.0, 2.0 and 3.0 %). The effect of different methods were investigated on the fatigue properties of HMA using, third-point flexural fatigue bending Test. Pneumatic Repeated Load System (PRLS) was carried out to establish the effect of hydrated lime on the fatigue failure criteria and to select the proper hydrated lime application methods on fatigue behavior o

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluated the level density for proton induced nuclear resonances in (P+48Ti) reaction using different models
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The experimental proton resonance data for the reaction P+48Ti have been used to calculate and evaluate the level density by employed the Gaussian Orthogonal Ensemble, GOE version of RMT, Constant Temperature, CT and Back Shifted Fermi Gas, BSFG models at certain spin-parity and at different proton energies. The results of GOE model are found in agreement with other, while the level density calculated using the BSFG Model showed less values with spin dependence more than parity, due the limitation in the parameters (level density parameter, a, Energy shift parameter, E1and spin cut off parameter, σc). Also, in the CT Model the level density results depend mainly on two parameters (T and ground state back shift energy, E0), which are app

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Effect of Amoxicillin and Azithromycin Suspensions on Microhardness of Sliver Reinforced and Nano Resin-Modified Glass Ionomers: An In Vitro Study
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We aimed to examine the effect of amoxicillin and azithromycin suspensions on the microhardness of sliver-reinforced glass ionomer and nano-resin modified glass ionomer (GI). Method: Thirty discs (2mm height x 4mm diameter) of each type of GI were prepared, which were randomly assigned to amoxicillin, azithromycin, and artificial saliva groups. Microhardness was evaluated by Vickers hardness test before and after three immersion cycles. Results: The overall model (P < 0.001), before/after intervention (P < 0.001), intervention group (type of antibiotic) (P=0.013), and type of glass ionomer (P < 0.001) showed significant differences among study groups (P < 0.001). Post hoc test showed only non-significant before/after difference for Azithrom

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
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In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Approximate Analytical Solutions of Bright Optical Soliton for Nonlinear Schrödinger Equation of Power Law Nonlinearity
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This paper introduces the Multistep Modified Reduced Differential Transform Method (MMRDTM). It is applied to approximate the solution for Nonlinear Schrodinger Equations (NLSEs) of power law nonlinearity. The proposed method has some advantages. An analytical approximation can be generated in a fast converging series by applying the proposed approach. On top of that, the number of computed terms is also significantly reduced. Compared to the RDTM, the nonlinear term in this method is replaced by related Adomian polynomials prior to the implementation of a multistep approach. As a consequence, only a smaller number of NLSE computed terms are required in the attained approximation. Moreover, the approximation also converges rapidly over a

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Mon Apr 01 2019
Journal Name
Dental Materials
An integrated multifunctional hybrid cement (pRMGIC) for dental applications
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Objective. Glass-ionomer and resin-modified glass-ionomer cements are versatile materials with the ability to form a direct bond with tooth tissues. The aim of this study was to formulate a novel class of dental bio-interactive restorative material (pRMGIC) based on resin-modified glass-ionomer cements via the inclusion of an organophosphorus monomer, ethylene glycol methacrylate phosphate, with a potential to improve the mechanical properties and also function as a reparative restorative material. Methods. pRMGIC was formulated with modification of the resin phase by forming mixes of ethylene glycol methacrylate phosphate (EGMP; 0–40%wt) and 2-hydroxyethyl methacrylate monomer into the liquid phase of a RMGIC (Fuji II LC, GC Corp.).

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Publication Date
Mon Jun 01 2026
Journal Name
Wasit Journal Of Engineering Sciences
Engineering Perspectives on Rehabilitation Robotics: An Integrative Review of Control Strategies, Optimization Methods, and IoT-Enabled Platforms
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Rehabilitation robotics has developed into an interdisciplinary field which uses mechanical design and control theory and optimization techniques together with information technologies to create better recovery results for people who suffer from motor disabilities. The present review assesses rehabilitation robotics research through engineering application studies which use more than 120 peer-reviewed articles published between 2014 and 2024. The discussion covers four main areas which include control strategies that start from basic PID methods and extend to sophisticated adaptive and intelligent control systems. The study utilizes bio-inspired and metaheuristic optimization methods to enhance system functionality and develop control paths

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Modified Weighted Pareto Distribution Type I (MWPDTI)
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In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distrib

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