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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
Sat Sep 26 2026
Journal Name
Modern Sport
The effect of Developing special endurance using multiple round periods on some physical and functional indicators for elite boxers
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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Sat Jun 01 2013
Journal Name
Int. J. Nanoelectronics And Materials
Comparsion of the physical properties for CdS and CdS doped PVA thin films prepared by spray pyrolysis
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Study electron transport coefficients for Ar, O<sub>2</sub> and their mixtures by using EEDF program
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Publication Date
Wed Aug 20 2025
Journal Name
Aip Conference Proceedings
Study the physical properties of Se65Sn35-xTex alloys
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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Physical and Morphological Properties of Hard- Soft Ferrite Functionally Graded Materials
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  Functionally graded materials (FGMs), with ceramic –ceramic constituents are fabricated using powder technology techniques. In this work three different sets of FGMs samples were designed in to 3 layers, 5 layers and 7 layers. The ceramic constituents were represented by hard ferrite (Barium ferrite) and soft ferrite (lithium ferrite). All samples sintered at constant temperature at 1100oC for 2 hrs. and characterized by FESEM. Some physical properties were measured for fabricated FGMs include apparent density, bulk density, porosity, shrinkage and hardness. The results indicated that the density increase with the increase the number of layer. Lateral shrinkage is one of the important parameter f

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Engineering
hermo-Physical and Mechanical Properties of Unsaturated Polyester /Cobalt Ferrite Composites
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Unsaturated polyester was used as a matrix which was filled with different percentages of cobalt ferrite using hand lay-up method. Cobalt ferrite was synthesized using solid state ceramic method with reagent of CoO and Fe2O3. Mechanical properties such tensile strength, Young's modulus and shore D hardness of the composite have been studied. All these properties have increased by 10% with increasing cobalt ferrite contents. Also the thermal properties such thermal conductivity and specific heat capacity are highly increased as the ferrite content increased, while the thermal diffusivity increased by 22 %. On the other hand dielectric strength of composite has been measured which increased by 50% by increasing the cobalt ferrite content.&

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Publication Date
Fri Oct 25 2024
Journal Name
Infrastructures
Physical, Mechanical and Durability Properties of Eco-Friendly Engineered Geopolymer Composites
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Engineered geopolymer composite (EGC) is a high-performance material with enhanced mechanical and durability capabilities. Ground granulated blast furnace slag (GGBFS) and silica fume (SF) are common binder materials in producing EGC. However, due to the scarcity and high cost of these materials in some countries, sustainable alternatives are needed. This research focused on producing eco-friendly EGC made of cheaper and more common pozzolanic waste materials that are rich in aluminum and silicon. Rice husk ash (RHA), granite waste powder (GWP), and volcanic pumice powder (VPP) were used as partial substitutions (10–50%) of GGBFS in EGC. The effects of these wastes on workability, unit weight, compressive strength, tensile strengt

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