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Ternary glycerol-based deep eutectic solvents: Physicochemical properties and enzymatic activity
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The present study investigates deep eutectic solvents (DESs) as potential media for enzymatic hydrolysis. A series of ternary ammonium and phosphonium-based DESs were prepared at different molar ratios by mixing with aqueous glycerol (85%). The physicochemical properties including surface tension, conductivity, density, and viscosity were measured at a temperature range of 298.15 K – 363.15 K. The eutectic points were highly influenced by the variation of temperature. The eutectic point of the choline chloride: glycerol: water (ratio of 1: 2.55: 2.28) and methyltriphenylphosphonium bromide:glycerol:water (ratio of 1: 4.25: 3.75) is 213.4 K and 255.8 K, respectively. The stability of the lipase enzyme isolated from porcine pancreas (PPL) and Rhizopus niveus (RNL) toward hydrolysis in ternary DESs medium was investigated. The PPL showed higher activity compared to the RNL in DESs. Molecular docking simulation of the selected DES with the substrate (p-nitrophenyl palmitate) toward PPL was also reported. It is worth noting that ternary DES systems would be viable lipase activators in hydrolysis reactions.

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Fri Jan 10 2020
Journal Name
Polymers
Influence of Polyphosphates on the Physicochemical Properties of Poly (Vinyl Chloride) after Irradiation with Ultraviolet Light
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Three new polyphosphates were synthesized in good yields by reacting diethylenetriamine with the appropriate phosphate ester in ethanol under acidic conditions. The polyphosphate structures were determined using FT-IR and 1H-NMR spectroscopies, and their elemental compositions were confirmed by EDX spectroscopy. Polyphosphates were added to poly(vinyl chloride) (PVC) at low concentrations to fabricate thin films. The PVC films were irradiated with ultraviolet light for long periods, and the effect of polyphosphates as the photostabilizer was investigated by determining changes in the infrared spectra (intensity of specific functional group peaks), reduction in molecular weight, weight loss, and surface morphology. Minimal changes we

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Publication Date
Fri May 01 2026
Journal Name
Microchemical Journal
Modification of screen-printed carbon electrode through nanocomposite ZIF-67/MoO3 in Deep eutectic solvent water mixtures to enhance fentanyl sensitivity
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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
Sun Sep 01 2024
Journal Name
Chemistry Of Heterocyclic Compounds
Synthesis of polyaniline, polypyrrole, and poly(aniline-co-pyrrole) in deep eutectic solvent: a comparative experimental and computational investigation of their structural, spectral, thermal, and morphological characteristics
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In this investigation, deep eutectic solvent based on propionic acid and choline chloride was used to prepare polyaniline, polypyrrole, and poly(aniline-co-pyrrole) samples using chemical oxidation and polymerization. Quantum mechanical calculations were conducted using time-dependent density functional theory to determine the electronic, spectroscopic properties and structure of homopolymers and the copolymer which were compared with the respective experimental data. Furthermore, the synthesized materials were characterized using Fourier transform IR spectroscopy, scanning electron microscopy (SEM), UV-visible spectroscopy, and thermogravimetric analysis. IR and UV-visible spectra confirmed copolymerization, and SEM revealed that the copol

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Publication Date
Mon Apr 10 2023
Journal Name
The European Physical Journal Plus
Improved performance of D149 dye-sensitized ZnO-based solar cell under solvents activation effect
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Publication Date
Wed Jun 01 2022
Journal Name
International Journal Of Nanoscience
Zinc Oxide Nanoparticle Properties and Antimicrobial Activity
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In this study, zinc oxide was prepared by pulsed laser ablation method (PLAL), which is an easy-to-use and inexpensive physical method. The optical properties were studied using UV-Vis spectrometers, structure properties by (XRD) to calculate the crystalline size, and particle size determination by Field emission scanning electron microscopy (FE-SEM) and (EDS), transmission electron microscopy (TEM) assays and it was proved that they are within the ideal nanoscale for biological application. These ZnO NPs were employed on the inhibitory activity of different types of Gram-positive and Gram-negative bacteria, as well as on fungi, and it was noted their ability to penetrate the bacterial cell wall and inhibit its action.

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Entry cost based on activity-based cost specifications and comparative study
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Several recent approaches focused on the developing of traditional systems to measure the costs to meet the new environmental requirements, including Attributes Based Costing (ABCII). It is method of accounting is based on measuring the costs according to the Attributes that the product is designed on this basis and according to achievement levels of all the Attribute of the product attributes. This research provides the knowledge foundations of this approach and its role in the market-oriented compared to the Activity based costing as shown in steps to be followed to apply for this Approach. The research problem in the attempt to reach the most accurate Approach in the measurement of the cost of products from th

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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