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Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterification reaction and showed considerable activity even after four consecutive recycling runs. The produced biodiesel after acid esterification and alkaline transesterification met the EN14214 international biodiesel standard specifications. To our best knowledge, this is the first study to introduce an acidic catalyst in capsule form. This method presents a new route for the safe storage of new materials to be used for biofuel production. Conductor-like screening model for real solvents (COSMO-RS) representation of the DES using σ-profile and σ-potential graphs indicated that MTPB and PTSA is a compatible combination due to the balanced presence and affinity towards hydrogen bond donor and hydrogen bond acceptor in each constituent.

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Publication Date
Fri Jan 01 2016
Journal Name
5th Iet International Conference On Renewable Power Generation (rpg), 2016, London, Uk
Electrical Machine Design for use in an External Combustion Free Piston Engine
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Publication Date
Sat Mar 30 2019
Journal Name
Studia Universitatis Babeș-bolyai Chemia
"Excess and deviations properties for the binary solvent mixtures of tetrahydrofurfuryl alcohol with some aromatic hydrocarbons at 298.15K "
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Publication Date
Sat Mar 30 2019
Journal Name
Studia Universitatis Babeș-bolyai Chemia
"Excess and deviations properties for the binary solvent mixtures of tetrahydrofurfuryl alcohol with some aromatic hydrocarbons at 298.15K "
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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering &amp; Technology
Modified Strut Effectiveness Factor for FRP-Reinforced Concrete Deep Beams
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A few examinations have endeavored to assess a definitive shear quality of a fiber fortified polymer (FRP)- strengthened solid shallow shafts. Be that as it may, need data announced for examining the solid profound pillars strengthened with FRP bars. The majority of these investigations don't think about the blend of the rigidity of both FRP support and cement. This examination builds up a basic swagger adequacy factor model to evaluate the referenced issue. Two sorts of disappointment modes; concrete part and pulverizing disappointment modes were examined. Protection from corner to corner part is chiefly given by the longitudinal FRP support, steel shear fortification, and cement rigidity. The proposed model has been confirmed util

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
A study of the solvent effect on the low temperature spectra of benzoanthracene molecules
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been taken at room temperature down to liquid nitrogen temperature (77K). Polar and nonpolar solvents have been used to study the solvent effect on the absorption and fluorescence spectra of solute molecules. Some of the spectroscopic parameters have been determined as functions of solvent polarity and temperature. The results indicate that the band width FWHM increases with increasing the solvent polarity and temperature, while the peak emission cross section decreases with increasing of solvent polarity and decreases with increasing the temperatures. Clear vibrational structure spectra of benzoanthracene molecules have been observed in Nonane and Hexane solvents at 77K.

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Publication Date
Sat Aug 01 2020
Journal Name
Proceedings Of International Structural Engineering And Construction
ARCHITECTURAL POTENTIALITY OF FREE-FORM STRUCTURES
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Contemporary architecture has witnessed a new innovative trend in design characterized by the creation of interesting free-flowing structures that reflect expressiveness of form and design, as well as the uniqueness of structure and approaches of construction. These fascinating structures are often perceived as landmarks that blend harmoniously into their surroundings. In the last two decades, parametric design and advanced computational tools, with prefabrication and construction techniques, enabled architects and engineers to explore new materials and methods to create such impressive structures, breaking the obsolete ways of thinking. Several examples of free-form structures lack obviously to explore architectural potentialities,

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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