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Shedding Light on Thermodynamics and Physical Properties of Deep Eutectic Solvents for Separating Toluene-Heptane Mixtures Using COSMO-RS
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A total of 150 deep eutectic solvents (DESs) with varying salt, hydrogen bond donor, and molar ratios were studied to develop a screening tool for separating toluene-heptane mixtures. The activity coefficient at infinite dilution (γ∞) of each DES was predicted using COSMO-RS, and selectivity (S∞), capacity (C∞), and performance index (PI) were calculated. Key DES properties, including density, viscosity, melting/freezing point, surface tension, and conductivity, were compiled from the literature to create a DES property library. A comprehensive screening tool with four evaluation criteria was developed, which identified ethyl triphenylphosphonium bromide:ZnCl2 (1:4) as the optimal solvent for toluene-heptane separation. Tetrabutyl- based DESs exhibited higher S∞, while phenyl phosphonium-based DESs showed higher C∞. DESs with Cl- anions provided higher selectivity, whereas those with Br- anions had higher capacity. Generally, DESs with high S∞ also showed high PI, indicating superior separation performance.

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A study of the effect of silica particles addition on some physical properties of PVC as a packaging material
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In this work, varying compositions of SiO2 micro filler were added
with the Polyvinyl Chloride (PVC) and samples have been prepared
using film casting technique. The results have been analyzed and
compared for PVC samples with (1 wt%, 3 wt%, 5 wt% and 10 wt%)
SiO2 micro filler. Mechanical characteristics such as tensile strength,
elongation at break and Young`s modulus were measured for all the
samples, where the tensile strength was increased from 8.39 Mpa for
purified PVC to 16 Mpa for 3% SiO2/PVC composite. Also, thermal
conductivity measurement values illustrated that composite materials
have a good thermal insulation at 10 wt. %, thermal conductivity was
decreased from 0.1684 W/m.

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Publication Date
Sun May 24 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of silanized alumina nano -fillers addition on some physical and mechanical properties of heat cured polymethyl methacrylate denture base material
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Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements. Midline fracture; poor thermal conductivity and water sorption, are common problem in this material. The purpose of this study was to evaluate the effect of addition of surface treated Aluminum oxide nano fillers on some properties of heat cured (PMMA). Materials and methods: In addition to controlled group of heat cured PMMA the silanized (Al2O3) nanoparticles was added to PMMA powder by weight in three different percentages 1wt%, 2wt% and 3wt%, mixed by probe ultra-sonication machine. 200 specimens were constructed and divided into 5 groups according to the test (e

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Publication Date
Sun May 24 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Zirconium Silicate Nanopowder Reinforcement on Some Mechanical and Physical Properties of Heat Cured Poly (Methyl Methacrylate) Denture Base Materials
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Background: Polymethylmethacrylate (PMMA) has relatively unsatisfactory mechanical properties such as low flexural strength and impact strength also dimensional instability. Material and method: Zirconium silicate nanoparticles were coated with a layer of trimethoxysilylpropylmethacrylate (TMSPM) before sonication in monomer (MMA) with the percentages 1% and 1.5% by weight then mixed with powder using conventional procedure, (150) samples were prepared and divided into three groups, each group consisted of (50) samples, the first group prepared from PMMA without addition (control), another group with the addition of 1% wt Zrsio4 nanoparticles (experimental) and the third one with 1.5% wt Zrsio4 nanoparticles (experimental). Each group

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
Study of deposited spray quality of spraying agents with different physical properties
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The spray quality of two spraying agents with different physical properties was investigated under laboratory conditions to find whether the measurement of deposited drops could be affected by spraying those agents. The first spraying agent Moddus, which is a plant growth regulator, has a surface tension of 28 mN m-1 with almost half the value of the second spraying agent Kelpak (58 mN m-1). A mini boom sprayer containing three flat fan nozzles (XR 11003) was used in the test with three traveling speeds (4.74, 5.42 and 8.13 km. h-1). The test was performed to evaluate the quality of spray drops (spray coverage, spray density and stains diameter) after they were deposited on water sensitive papers (WSP). The results showed a higher ability o

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Unmasking Deepfakes Based on Deep Learning and Noise Residuals
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The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Mechanical and physical properties of carbon nano tubes with kevlar fiber reinforced with polyester resin
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In this research study Hardness (shore D), Water absorption,
Flexural, Impact Test, and Fracture Toughness of polymer nano
composites. The polymer nano composites based on unsaturated
polyester resin reinforced with Kevlar fibers (K.F). The samples are
attended by hand lay – up method according to (Rule mixture) for
various volume fractions of unsaturated polyester resin, fiber and
carbon nanotube. The polyester resin was matrix strengthened with
3% volume fraction from Kevlar fiber and (0.5%, 1%, 1.5%, 2%)
volume fractions of carbon nanotube. The water absorption, hardness
(shore D), flexural test, impact test and toughness fracture properties
were studied. Results showed that the water absorption increas

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Publication Date
Sun Nov 01 2020
Journal Name
Physics Of Atomic Nuclei
Study of the Halo Structure for Some Light Neutron-Rich Nuclei Using the Cosh Potential
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The radial wave functions of the cosh potential within the three-body model of (Core+ 2n) have been employed to investigate the ground state properties such as the proton, neutron and matter densities and the associated rms radii of neutron-rich 6He, 11Li, 14Be, and 17B exotic nuclei. The density distributions of the core and two valence (halo) neutrons are described by the radial wave functions of the cosh potential. The obtained results provide the halo structure of the above exotic nuclei. Elastic electron scattering form factors of these halo nuclei are studied by the plane-wave Born approximation.

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