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Do low back pain changes correlate with sagittal lumbar alignment changes after total hip replacement arthroplasty?
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Abstract Background: The hip joint and lumbar spine are both anatomically and functionally closely related as had shown by many authors. So the abnormality in one area can affect the other e.g. hip joint osteoarthritis can cause lumbar sagittal malalignment and backache. Objectives: is to see if there is significant improvement in backache after total hip replacement? And which degree of backache improvement is associated with significant changes in lumbar lordosis? Methods and patients: a prospective open trial study was performed on 30 patients who had severe hip osteoarthritis and chronic low back pain. Total hip replacement was performed to all patients. Backache and lumbar lordosis were measured by visual analogue scale and Cobb’s angle respectively both before and 6 months after surgery. Patients were divided into 3 groups according to grade of improvement in backache after surgery. Results: The improvement in low back pain after surgery was statistically significant for all patients and for each group separately, while the changes in lumbar lordosis were not statistically significant neither for all patients nor for any group separately. Conclusions: total hip replacement surgery has significant positive effect on backache. There is no significant correlation between improvement in backache and changes in lumbar lordosis.

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Publication Date
Sat Sep 01 2018
Journal Name
Food Chemistry
Rapid determination of thiabendazole in juice by SERS coupled with novel gold nanosubstrates
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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Quantitative Determination of Fluoroquinolones in Contaminated Soils by HPLC with Solid-Phase Extraction
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This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Wed Apr 07 2021
Journal Name
Egyptian Journal Of Chemistry
Copolymers of Castor and Corn Oils with Lauryl Methacrylate as Green Lubricating Additives
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During the last few years, the greener additives prepared from bio-raw materials with low-cost and multifunctional applications have attracted considerable attention in the field of lubricant industry. In the present work, copolymers derived from sunflower and linseed oils with decyl methacrylate were synthesized by a thermal method using benzoyl peroxide (BPO) as a radical initiator. Direct polymerization of fatty acid double bonds in the presence of a free radical initiator results in the development of environmentally friendly copolymeric additives (Co-1 and Co-2). Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (1H-NMR) were used to characterize the resulting copolymers. Thermal decomposition of copolymers was de

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Publication Date
Wed Jun 01 2022
Journal Name
Results In Engineering
Behavioral nonlinear modeling of prestressed concrete flexural members with internally unbonded steel strands
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Publication Date
Mon Feb 01 2010
Journal Name
Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, And Endodontology
Oral Candida flora in a group of Jordanian patients with β-thalassemia major
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Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Experimental Evaluation of PV Panel Efficiency Using Evaporative Cooling Integrated with Water Spraying
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In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Thu Apr 01 2021
Journal Name
Basra Journal Of Science
Preparation and Characterization of Polyvinylpyrrolidone/Multi-walled Carbon Nanotubes Nanocomposite hybrid with Graphene
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In this work, polyvinylpyrrolidone (PVP), Multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybrid with Graphene (Gr) by casting method. The morphological and optical properties were investigated. Fourier Transformer-Infrared (FT-IR) indicates the presence of primary distinctive peaks belonging to vibration groups that describe the prepared samples. Scanning Electron Microscopy (SEM) images showed a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The results of the optical study show decrease in the energy gap with increasing MWCNT and graphene concentration. The absorption coefficient spectra indicate the presence of two absorption peaks at 282 and 287 nm attributed to the π-π* electronic tr

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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