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.
This work studied the facilitation of the transportation of Sharqi Baghdad heavy crude oil characterized with high viscosity 51.6 cSt at 40 °C, low API 18.8, and high asphaltenes content 7.1 wt.%, by reducing its viscosity from break down asphaltene agglomerates using different types of hydrocarbon and oxygenated polar solvents such as toluene, methanol, mix xylenes, and reformate. The best results are obtained by using methanol because it owns a high efficiency to reduce viscosity of crude oil to 21.1 cSt at 40 °C. Toluene, xylenes and reformate decreased viscosity to 25.3, 27.5 and 28,4 cSt at 40 °C, respectively. Asphaltenes content decreased to 4.2 wt. % by using toluene at 110 °C. And best improvement in API of the heavy crude o
... Show MoreBackground: Menopause can bring oral health problems and also associated with significant adverse changes in the orofacial complex. After menopause, women become more susceptible to periodontal disease due to deficiency of estrogen hormone. Current study aimed to evaluate the periodontal health status in relation to salivary constituent including pH, flow rate and some elements (Magnesium, Calcium and inorganic phosphorus) of pre and post-menopause women. Materials and Methods: Periodontal health status of 52 women aged 48-50 years old (26 pre-menopause and 26 post-menopause) were examined including (gingival index, plaque index, calculus index, probing pocket depth and clinical attachment level). Salivary sample was collected for two women
... Show MoreIn this research, an enhancement in lubricating, rheological, and filtration properties of unweighted water-based mud is fundamentally investigated using XC polymer NPs with 0.2gm, 0.5gm, 1gm, 2gm, and 4gm concentrations. Bentonite, that had been used in the preparation of unweighted water-based mud, was characterized using XRF-1800 Sequential X-ray Fluorescence Spectrometer, XRD-6100/7000 X-ray Diffractometer, and Malvern Mastersizer 2000 particle size analyzer, respectively. Lubricating, rheology and filtration properties of unweighted water-based mud were measured at room temperature (35°C) using OFITE EP and Lubricity Tester, OFITE Model 900 Viscometer, and OFITE Low-Pressure Filter Press, respectively. XC Polymer N
... Show MoreBackground Microorganisms and fungal growth especially Candida albicans, on soft denture lining material are the most common problem which can lead to chronic mucosal inflammation. The aim of this study was to evaluate the effect of zirconium nanoparticles into acrylic-based heat cured soft denture lining material against Candida albicans, and the amount of zirconium ion release of soft liner/ZrNPs composite. Furthermore, evaluate shear bond strength after ZrNPs addition to soft liner. Materials and methods: Zirconium nanoparticles were added into acrylic-based soft denture liner in various percentages (1%, and 1.5% by weight). Two hundred and fifty specimens were arranged and isolated into four groups as per the test to be done The antifu
... Show MoreComputer models are used in the study of electrocardiography to provide insight into physiological phenomena that are difficult to measure in the lab or in a clinical environment.
The electrocardiogram is an important tool for the clinician in that it changes characteristically in a number of pathological conditions. Many illnesses can be detected by this measurement. By simulating the electrical activity of the heart one obtains a quantitative relationship between the electrocardiogram and different anomalies.
Because of the inhomogeneous fibrous structure of the heart and the irregular geometries of the body, finite element method is used for studying the electrical properties of the heart.
This work describes t
... Show MoreIn this paper Alx Ga1-x As:H films have been prepared by using new deposition method based on combination of flash- thermal evaporation technique. The thickness of our samples was about 300nm. The Al concentration was altered within the 0 x 40.
The results of X- ray diffraction analysis (XRD) confirmed the amorphous structure of all AlXGa1-x As:H films with x 40 and annealing temperature (Ta)<200°C. the temperature dependence of the DC conductivity GDC with various Al content has been measured for AlXGa1-x As:H films.
We have found that the thermal activation energy Ea depends of Al content and Ta, thus the value of Ea were approximately equal to half the value of optical gap.
General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
... Show MoreCryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The
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