The catalytic conversion of waste cooking oil (WCO) was carried out over a synthetic nano catalyst of cobalt aluminate (CoAl
O
) to produce biofuel range fractions. A precipitation method was used to ...create a nanoparticle catalyst, which was then examined using field-emission scanning electron microscopy, X-ray diffraction, energy dispersive X-ray, nitrogen adsorption measurements, high-resolution transmission electron Microscopy (HRTEM), infrared spectroscopy, while a gas chromatography-mass spectrometer (GC-MS) was used to analyze the chemical construction of the liquid biofuel. A range of experimental temperatures was looked at including 350, 375, 400, 425, and 450 °C; hydrogen pressure of 50, 2.5, and 5.0 MPa; and liquid hour space velocity (LHSV) of 1, 2.5, and 5 h
. As temperature, pressure, and liquid hourly space velocity increased, the amount of bio-jet and biodiesel fractional products decreased, while liquid light fraction hydrocarbons increased. 93% optimum conversion of waste cooking oil over CoAl
O
nano-particles was achieved at 400 °C, 50 bar, and 1 h
(LHSV) as 20% yield of bio-jet range,16% gasoline, and 53% biodiesel. According to the product analysis, catalytic hydrocracking of WCO resulted in fuels with chemical and physical characteristics that were on par with those required for fuels derived from petroleum. The study's findings demonstrated the nano cobalt aluminate catalyst's high performance in a catalytic cracking process, which resulted in a WCO to biofuel conversion ratio that was greater than 90%. In this study, we looked at cobalt aluminate nanoparticles as a less complex and expensive alternative to traditional zeolite catalysts for the catalytic cracking process used to produce biofuel and thus can be manufactured locally, which saves the cost of imports for us as a developing country.
In Egypt, water shortage has become a key limiting factor for agriculture. Water-deficit stress causes different morphological, physiological, and biochemical impacts on plants. Two field experiments ...were carried out at Etay El-Baroud Station, El-Beheira Governorate, Agriculture Research Center (ARC), Egypt, to evaluate the effect of potassium silicate (K-silicate) of maize productivity and water use efficiency (WUE). A split-plot system in the four replications was used under three irrigation intervals during the 2017 and 2018 seasons. Whereas 10, 15, and 20 days irrigation intervals were allocated in main plots, while the three foliar application treatments of K-silicate (one spray at 40 days after sowing; two sprays at 40 and 60 days; and three sprays at 40, 60, and 80 days, and a control (water spray) were distributed in the subplots. All the treatments were distributed in 4 replicates. The results indicated that irrigation every 15 days gave the highest yield in both components and quality. The highly significant of (WUE) under irrigation every 20 days. Foliar spraying of K-silicate three times resulted in the highest yield. Even under water-deficit stress, irrigation every fifteen days combined with foliar application of K-silicate three times achieved the highest values of grain yield and its components. These results show that K-silicate treatment can increase WUE and produce high grain yield requiring less irrigation.
Synovial fluid is an ultra-viscous plasma filtration that lubricates joint movement. During acute accidents or a cartilage repair surgical intervention, blood is introduced into the joint and mixed ...with variable amounts of synovial fluid. The hypothesis of this study was that mixing the blood with the synovial fluid, forming a mixture of them, can change the rheological properties of the blood and the mechanical properties of the stenosis formed.
In this work we have presented a theoretical study to a mixture of synovial and blood nanofluid with heat distribution, concentration and volume fraction effects through concentric tube when the outer tube contain stenosis. Two models of synovial fluid that depend on viscosity are debated, in model I the viscosity depend exponentially on the concentration while model II shear tensor is considered as a function of concentration. The mathematical model has been studied in cylindrical coordinates. The solution of mathematical model was also obtained numerically using finite difference method after using a domain transformation to transform the variable cross-section of the concentric tube to a uniform cross section. We approaches to the synovial fluid improves the velocity of blood in the areas of atherosclerosis due to the nature of synovial fluid, which has less friction forces. Also, the velocity of mixture blood and synovial for model I is higher than that for model II.
This problem with synovial lining is called synovitis.
To the authors’ information, no such research has been performed in the literature.
•The addition of trace metals in form of nanoparticles reduced the lag phase.•Nanoparticles reduced time to achieve the highest biogas and methane production.•Biogas and methane production were ...proportional to nanoparticles concentration.•Nanoparticles biostimulate the methanogenic bacteria and increase their activity.
Nanoparticles (NPs) were hypothesized to enhance the anaerobic process and to accelerate the slurry digestion, which increases the biogas and methane production. The effects of NPs on biogas and methane production were investigated using a specially designed batch anaerobic system. For this purpose, a series of 2L biodigesters were manufactured and implemented to study the effects of Cobalt (Co) and Nickel (Ni) nanoparticles with different concentrations on biogas and methane production. The best results of NPs additives were determined based on the statistical analysis (Least Significant Difference using M-Stat) of biogas and methane production, which were 1mg/L Co NPs and 2mg/L Ni NPs (p<0.05). These NPs additives delivered the highest biogas and methane yields in comparison with their other concentrations (0.5, 1, and 2mg/L), their salts (CoCl2, and NiCl2) and the control. Furthermore, the addition of 1mg/L Co NPs and 2mg/L Ni NPs significantly increased the biogas volume (p<0.05) by 1.64 and 1.74 times the biogas volume produced by the control, respectively. Moreover, the aforementioned additives significantly increased the methane volume (p<0.05) by 1.86 and 2.01 times the methane volume produced by the control, respectively. The highest specific biogas and methane production were attained with 2mg/L Ni NPs (p<0.05), and were 614.5mlBiogasg−1VS and 361.6mlCH4g−1VS, respectively compared with the control which yielded only 352.6mlBiogasg−1VS and 179.6mlCH4g−1VS.
Alzheimer's Disease (AD) is considered one of the most diseases that much prevalent among elderly people all over the world. AD is an incurable neurodegenerative disease affecting cognitive functions ...and were characterized by progressive and collective functions deteriorating. Remarkably, early detection of AD is essential for the development of new and invented treatment strategies. As Dementia causes irreversible damage to the brain neurons and leads to changes in its structure that can be described adequately within the framework of multifractals. Hence, the present work focus on developing a promising and efficient computing technique to pre-process and classify the AD disease especially in the early stages using multifractal geometry to extract the most changeable features due to AD. Then, A machine learning classification algorithm (K-Nearest Neighbor) has been implemented in order to classify and detect the main four early stages of AD. Two datasets have been used to ensure the validation of the proposed methodology. The proposed technique has achieved 99.4% accuracy and 100% sensitivity. The comparative results show that the proposed classification technique outperforms is recent techniques in terms of performance measures.
Diabetic Retinopathy (DR) is a complication of diabetes that affects the eyes. It is caused by blood vessel damage of the light-sensitive tissue at the back of the retina. Neovascularization are ...emerged and the small blood vessels are blocked. The prevention or delaying vision loss can be obtained by DR early detection. The retinal microvascular network as a biological system has its own multifractal features as generalized dimensions, lacunarity and singularity spectrum. In this study, a novel approach for DR early detection based on the multifractal geometry has been proposed in some details. Analyzing the macular optical coherence tomography angiography (OCTA) images for diagnosing early non-proliferative diabetic retinopathy (NPDR). Using a supervised machine learning method as a Support Vector Machine (SVM) algorithm to automate the diagnosis process and improving the resultant accuracy. The classification technique had achieved 98.5 % accuracy. This approach also can classify easily other diabetic retinopathy stages or other retinal diseases, which affect the vessels or neovascularization distribution.
Abstract
Alzheimer’s disease (AD) is a physical illness, which damages a person’s brain; it is the most common cause of dementia. AD can be characterized by the formation of amyloid-beta (Aβ) ...deposits. They exhibit diverse morphologies that range from diffuse to dense-core plaques. Most of the histological images cannot be described precisely by traditional geometry or methods. Therefore, this study aims to employ multifractal geometry in assessing and classifying amyloid plaque morphologies. The classification process is based on extracting the most descriptive features related to the amyloid-beta (Aβ) deposits using the Naive Bayes classifier. To eliminate the less important features, the Random Forest algorithm has been used. The proposed methodology has achieved an accuracy of 99%, sensitivity of 100%, and specificity of 98.5%. This study employed a new dataset that had not been widely used before.
Solar photovoltaic (PV) energy has witnessed double-digit growth in the past decade. The penetration of PV systems as distributed generators in low-voltage grids has also seen significant attention. ...In addition, the need for higher overall grid efficiency and reliability has boosted the interest in the microgrid concept. High-efficiency PV-based microgrids require maximum power point tracking (MPPT) controllers to maximize the harvested energy due to the nonlinearity in PV module characteristics. Perturb and observe (P&O) techniques, although thoroughly investigated in previous research, still suffer from several disadvantages, such as sustained oscillation around the MPP, fast tracking versus oscillation tradeoffs, and user predefined constants. In this paper, a modified P&O MPPT technique, applicable for PV systems, is presented. The proposed technique achieves: first, adaptive tracking; second, no steady-state oscillations around the MPP; and lastly, no need for predefined system-dependent constants, hence provides a generic design core. A design example is presented by experimental implementation of the proposed technique. Practical results for the implemented setup at different irradiance levels are illustrated to validate the proposed technique.
The present work is devoted to search for the optimum wind farm layout using binary real coded genetic algorithm (BRCGA) based local search (LS); gathering robust single wake model with suitable wake ...interaction modeling. The binary part of genetic algorithm (GA) is used to represent the location of turbines; while the real part is used to give the power generated by each turbine at its location. In addition, the solution quality is improved by implementing LS technique; where it intends to find the optimal solution near the approximated solution obtained by BRCGA. The Jensen wake model along with the sum of squares model are used to obtain the available power for each turbine; where it is considered one of the most common analytical models used for wind farm optimization. Siting improvement is achieved, as compared with earlier studies.
•The study focuses on wake interaction optimization for wind farm siting.•Genetic algorithm based local search approach is used.•Two cases, multiple wind direction with either single or multiple speed are tested.•Regular as well as irregular land spaces are adapted by the proposed methodology.•Siting improvement is achieved, compared to earlier studies.
In this study, nanoparticles (NPs) were hypothesized to enhance the anaerobic process and to accelerate the slurry digestion, which increases the biogas and methane production. The effects of NPs on ...biogas and methane production were investigated using a specially designed batch anaerobic system. For this purpose, a series of 2 L biodigesters were manufactured and implemented to study the effects of the nanoparticles of Iron (Fe) and Iron Oxide (Fe3O4) with different concentrations on biogas and methane production. The best results of NPs additives were selected based on the statistical analysis (Least Significant Difference using M-Stat) of biogas and methane production, which were 20 mg/L Fe NPs and 20 mg/L Fe3O4 magnetic NPs (p < 0.05). The aforementioned NPs additives delivered the highest biogas and methane yields in comparison with their other concentrations (5, 10 and 20 mg/L), their salt (FeCl3) and the control. Furthermore, the addition of 20 mg/L Fe NPs and 20 mg/L Fe3O4 magnetic NPs significantly increased the biogas volume (p < 0.05) by 1.45 and 1.66 times the biogas volume produced by the control, respectively. Moreover, the aforementioned additives significantly increased the methane volume (p < 0.05) by 1.59 and 1.96 times the methane volume produced by the control, respectively. The highest specific biogas and methane production were attained with 20 mg/L Fe3O4 magnetic NPs, and were 584 ml Biogas g−1 VS and 351.8 ml CH4 g−1 VS, respectively compared with the control which yielded only 352.6 ml Biogas g−1 VS and 179.6 ml CH4 g−1 VS.
•The addition of trace metals in form of nanoparticles reduced the lag phase.•Nanoparticles reduced time to achieve the highest biogas and methane production.•Biogas and methane production were proportional to nanoparticles concentration.•Nanoparticles biostimulate the methanogenic bacteria and increase their activity.
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