In this article, we developed a new higher-order implicit finite difference iterative scheme (FDIS) for the solution of the two dimension (2-D) time fractional Cable equation (FCE). In the new proposed FDIS, the time fractional and space derivatives are discretized using the Caputo fractional derivative and fourth-order implicit scheme, respectively. Moreover, the proposed scheme theoretical analysis (convergence and stability) is also discussed using the Fourier analysis method. Finally, some numerical test problems are presented to show the effectiveness of the proposed method.
Given the importance and use of electrically conducted nanofluids, this work aims to examine an engine-oil-based nanofluid including various nanoparticles. In the current study, a fractional model for inspecting the thermal aspect of a Brinkman-type nanofluid, composed of (molybdenum disulfide (MOS2) and graphene oxide (GO) nanoparticles flows on an oscillating infinite inclined plate, which characterizes an asymmetrical fluid flow, heat, and mass transfer. Furthermore, the Newtonian heating effect, magnetic field, and slip boundary conditions were taken into account. The objectives for implementing the Prabhakar-like fractional model are justified because this fractional algorithm has contemporary definitions with no singularity restrictions. Furthermore, the guided fractional model was solved using the Laplace transform and several inverse methods. The obtained symmetrical solutions have been visually analyzed to investigate the physics of several relevant flow parameters on the governed equations. Some exceptional cases for the momentum field are compiled to see the physical analysis of the flowing fluid symmetry. The results show that the thermal enhancement can be progressively improved with the interaction of the molybdenum disulfide-engine oil-based nanofluid suspension, rather than with the graphene oxide mixed nanoparticle fluid. Furthermore, the temperature and momentum profiles enhance due to the factional parameters for molybdenum disulfide and the graphene oxide-engine oil-based nanofluid suspension. This study's graphical and numerical comparison with the existing literature has shown a very close resemblance with the present work, which provides confidence that the unavailable results are accurate. The results show that an increase improved the heat transmission in the solid nanoparticle volume fractions. In addition, the increment in the mass and heat transfer was analyzed in the numerical evaluation, while the shear stress was enhanced with the enhancement in the Prabhakar fractional parameter α.
This communication elaborates the irreversibility analysis of the flow of Prandtl nanofluid along with thermal radiation past a permeable stretched surface embedded in a Darcy-Forchheimer medium. The activation and chemical impressions along with effects of thermophoretic and Brownian motion are as well examined. The flow symmetry of the problem is modeled mathematically and leading equations are rehabilitated into nonlinear ordinary differential equations (ODEs) through the assistance of suitable similarity variables. The Keller-box technique in MATLAB is employed to draw the impacts of the contributing elements on the velocity field, temperature distribution, and concentration. The impact of the Prandtl fluid parameter has mounting performance for the velocity whereas conflicting behavior is examined in the temperature profile. The achieved numerical results are matched correspondingly with the present symmetrical solutions in restrictive cases and fantastic agreement is scrutinized. In addition, the entropy generation uplifts for the growing values of the Prandtl fluid parameter, thermal radiation, and Brinkman number and decreases for growing numbers of the inertia coefficient parameter. It is also discovered that the coefficient of friction decreases for all parameters involved in the momentum equation. Features of nanofluids can be found in a variety of real-world fields, including microfluidics, industry, transportation, the military, and medicine.
Cooling and heating are two critical processes in the transportation and manufacturing industries. Fluid solutions containing metal nanoparticles have higher thermal conductivity than conventional fluids, allowing for more effective cooling. Thus, the current paper is a comparative exploration of the time-independent buoyancy opposing and heat transfer flow of alumina nanoparticles scattered in water as a regular fluid induced via a vertical cylinder with mutual effect of stagnation-point and radiation. Based on some reasonable assumptions, the model of nonlinear equations is developed and then tackled numerically employing the built-in bvp4c MATLAB solver. The impacts of assorted control parameters on gradients are investigated. The outcomes divulge that the aspect of friction factor and heat transport upsurge by incorporating alumina nanoparticles. The involvement of the radiation parameter shows an increasing tendency in the heat transfer rate, resulting in an enhancement in thermal flow efficacy. In addition, the temperature distribution uplifts due to radiation and curvature parameters. It is discerned that the branch of dual outcomes exists in the opposing flow case. Moreover, for higher values of the nanoparticle volume fraction, the reduced shear stress and the reduced heat transfer rate increased respectively by almost 1.30% and 0.0031% for the solution of the first branch, while nearly 1.24%, and 3.13% for the lower branch solution.
Cellulose nanocrystals (CNCs) are typically extracted from plants and present a range of opto-mechanical properties that warrant their use for the fabrication of sustainable materials. While their commercialization is ongoing, their sustainable extraction at large scale is still being optimized. Ultrasonication is a well-established and routinely used technology for (re-) dispersing and/or isolating plant-based CNCs without the need for additional reagents or chemical processes. Several critical ultrasonication parameters, such as time, amplitude, and energy input, play dominant roles in reducing the particle size and altering the morphology of CNCs. Interestingly, this technology can be coupled with other methods to generate moderate and high yields of CNCs. Besides, the ultrasonics treatment also has a significant impact on the dispersion state and the surface chemistry of CNCs. Accordingly, their ability to self-assemble into liquid crystals and subsequent superstructures can, for example, imbue materials with finely tuned structural colors. This article gives an overview of the primary functions arising from the ultrasonication parameters for stabilizing CNCs, producing CNCs in combination with other promising methods, and highlighting examples where the design of photonic materials using nanocrystal-based celluloses is substantially impacted.
Exhaust gases from the smelting furnace have high temperature and mass flow rate, and there is huge potential to use them for energy-related purposes such as electricity generation, cooling and heating. Utilization of the gases for energy-related purposes would lead to fuel savings and emissions reduction. To use this potential, it is necessary to design proper systems and cycles and apply a heat recovery unit. Several technologies are useable for heat recovery depending on the characteristics of exhaust gases, such as their mass flow rate, temperature and compositions. Due to the higher potential of combined heating, cooling and power (CCHP) generation systems compared with the systems with a single output, a CCHP is designed and investigated in the present study by consideration of the specifications of the exhaust gases. The applied system in this study comprises a Supercritical CO2 (SCO2) cycle, heat exchanger and single-stage absorption chiller for simultaneous heating, cooling and power production. Engineering Equation Solver (EES) is employed to model the proposed system by considering the properties of the flows and characteristics of the components. To get deep insight into the effective parameters on the outputs of the designed system, the impact of three factors, namely the mass flow rate of the gases, the effectiveness of heat exchanger and temperature of exhaust gases, are analyzed and investigated by the implementation of sensitivity analysis. As one of the main conclusions, it is found that an increment in the mass flow rate of exhaust gases from 30 kg/s to 70 kg/s causes augmentation in the power generation from 2037 kW to 4754 kW. Furthermore, exergy analysis is carried out, and it is found that an increase in the temperature or mass flow rate of exhaust gases or a decrease in the effectiveness of heat exchangers would lead to decrement in the exergy efficiency of the system. According to the performed sensitivity analysis, the mass flow rate of exhaust gases has the most remarkable influence on the heating and cycle-generated power among the considered factors.
The formation of entropy in a mixed convection Casson nanofluid model with Arhenius activation energy is examined in this paper using magnetohydrodynamics (MHD). The expanding sheet, whose function of sheet velocity is nonlinear, confines the Casson nanofluid. The final equations, which are obtained from the first mathematical formulations, are solved using the MATLAB built-in solver bvp4c. Utilizing similarity conversion, ODEs are converted in their ultimate form. A number of graphs and tabulations are also provided to show the effects of important flow parameters on the results distribution. Slip parameter was shown to increase fluid temperature and decrease entropy formation. On the production of entropy, the Brinkman number and concentration gradient have opposing effects. In the presence of nanoparticles, the Eckert number effect's augmentation of fluid temperature is more significant. Furthermore, a satisfactory agreement is reached when the findings of the current study are compared to those of studies that have been published in the past.
This research aims to establish the MHD radiating convective nanofluid flow properties with the viscous dissipation across an exponentially accelerating vertical plate. As the plate accelerates, its temperature progressively increases. There are two separate types of water-based nanofluids that include copper ([Formula: see text]) and titanium dioxide ([Formula: see text]) nanoparticles, respectively. The most crucial aspect of this investigation is finding a closed-form solution to a nonlinear coupled partial differential equations scheme. Galerkin finite element method (G-FEM) is used to figure out the initial managing equations. Utilizing graphs, the effect of the flow phenomenon's contributing variables as well as the influence of other factors is determined and depicted. In the part dedicated to the findings and discussion, the properties of these emergent parameters are described in more depth. Nonetheless, the thermal radiation and heat sink factors increase the thermal profile. In addition, the greater density of the copper nanoparticles cause the nanoparticle volume fraction to lessen the velocity delineation.
Objective: hybrid nanofluids have superior thermal efficiency and physical durability in contrast to regular nanofluids. The stagnation point flow of MHD micropolar hybrid nanofluids over a deformable sheet with viscous dissipation is investigated. Methodology: the controlling partial differential equations are converted to nonlinear ordinary differential equations using the transmuted similarity, and are subsequently solved using the bvp4c solver in MATLAB. The hybrid nanofluids consist of aluminum and copper nanoparticles, dispersed in a base fluid of water. Results: multiple solutions are obtained in the given problem for the case of shrinking as well as for the stretching sheet due to the variation in several influential parameters. Non-unique solutions, generally, exist for the case of shrinking sheets. In addition, the first branch solution is physically stable and acceptable according to the stability analysis. The friction factor is higher for the branch of the first solution and lower in the second branch due to the higher magnetic parameters, while the opposite behavior is seen in the case of the local heat transfer rate. Originality: the novelty of this model is that it finds multiple solutions in the presence of Cu and Al2O3 nanoparticles and also performs the stability analysis. In general, non-unique solutions exist for the phenomenon of shrinking sheets.
The customization of hybrid nanofluids to achieve a particular and controlled growth rate of thermal transport is done to meet the needs of applications in heating and cooling systems, aerospace and automotive industries, etc. Due to the extensive applications, the aim of the current paper is to derive a numerical solution to a wall jet flow problem through a stretching surface. To study the flow problem, authors have considered a non-Newtonian Eyring-Powell hybrid nanofluid with water and CoFe2O4and TiO2nanoparticles. Furthermore, the impact of a magnetic field and irregular heat sink/source are studied. To comply with the applications of the wall jet flow, the authors have presented the numerical solution for two cases; with and without a magnetic field. The numerical solution is derived with a similarity transformation and MATLAB-based bvp4c solver. The value of skin friction for wall jet flow at the surface decreases by more than 50% when the magnetic fieldMA=0.2is present. The stream function value is higher for the wall jet flow without the magnetic field. The temperature of the flow rises with the dominant strength of the heat source parameters. The results of this investigation will be beneficial to various applications that utilize the applications of a wall jet, such as in car defrosters, spray paint drying for vehicles or houses, cooling structures for the CPU of high-processor laptops, sluice gate flows, and cooling jets over turbo-machinery components, etc.
Solar radiation, which is emitted by the sun, is required to properly operate photovoltaic cells and solar water pumps (SWP). A parabolic trough surface collector (PTSC) installation model was created to investigate the efficacy of SWP. The thermal transfer performance in SWP is evaluated thru the presence of warmth radiation and heat cause besides viscid dissipation. This evaluation is performed by measuring the thermal transmission proportion of the selected warmth transmission liquid in the PTSC, known as a hybrid nano-fluid. Entropy analysis of Oldroyd-B hybrid nano-fluid via modified Buongiorno's model was also tested. The functions of regulating parameters are quantitatively observed by using the Keller-box approach in MATLAB coding. Short terms define various parameters for tables in velocity, shear pressure and temperature, gravity, and Nusselt numbers. In the condition of thermal radiation and thermal conductivity at room temperature, the competence of SWP is proven to be enhanced. Unlike basic nano-fluids, hybrid nano-fluids are an excellent source of heat transfer. Additionally, with at least 22.56% and 35.01% magnitude, the thermal efficiency of AA7075-Ti-6Al-4 V/EO is higher than AA7075-EO.
Human skin diseases have become increasingly prevalent in recent decades, with millions of individuals in developed countries experiencing monkeypox. Such conditions often carry less obvious but no less devastating risks, including increased vulnerability to monkeypox, cancer, and low self-esteem. Due to the low visual resolution of monkeypox disease images, medical specialists with high-level tools are typically required for a proper diagnosis. The manual diagnosis of monkeypox disease is subjective, time-consuming, and labor-intensive. Therefore, it is necessary to create a computer-aided approach for the automated diagnosis of monkeypox disease. Most research articles on monkeypox disease relied on convolutional neural networks (CNNs) and using classical loss functions, allowing them to pick up discriminative elements in monkeypox images. To enhance this, a novel framework using Al-Biruni Earth radius (BER) optimization-based stochastic fractal search (BERSFS) is proposed to fine-tune the deep CNN layers for classifying monkeypox disease from images. As a first step in the proposed approach, we use deep CNN-based models to learn the embedding of input images in Euclidean space. In the second step, we use an optimized classification model based on the triplet loss function to calculate the distance between pairs of images in Euclidean space and learn features that may be used to distinguish between different cases, including monkeypox cases. The proposed approach uses images of human skin diseases obtained from an African hospital. The experimental results of the study demonstrate the proposed framework's efficacy, as it outperforms numerous examples of prior research on skin disease problems. On the other hand, statistical experiments with Wilcoxon and analysis of variance (ANOVA) tests are conducted to evaluate the proposed approach in terms of effectiveness and stability. The recorded results confirm the superiority of the proposed method when compared with other optimization algorithms and machine learning models.
Expression levels of the NAC gene family were studied in rice infected with Rice dwarf virus (RDV), Rice black-streaked dwarf virus (RBSDV), Rice grassy stunt virus (RGSV), Rice ragged stunt virus (RRSV), and Rice transitory yellowing virus (RTYV). Microarray analysis showed that 75 (68%) OsNAC genes were differentially regulated during infection with RDV, RBSDV, RGSV, and RRSV compared with the control. The number of OsNAC genes up-regulated was highest during RGSV infection, while the lowest number was found during RTYV infection. These phenomena correlate with the severity of the syndromes induced by the virus infections. Most of the genes in the NAC subgroups NAC22, SND, ONAC2, ANAC34, and ONAC3 were down-regulated for all virus infections. These OsNAC genes might be related to the health stage maintenance of the host plants. Interestingly, most of the genes in the subgroups TIP and SNAC were more highly expressed during RBSDV and RGSV infections. These results suggested that OsNAC genes might be related to the responses induced by the virus infection. All of the genes assigned to the TIP subgroups were highly expressed during RGSV infection when compared with the control. For RDV infection, the number of activated genes was greatest during infection with the S-strain, followed by the D84-strain and the O-strain, with seven OsNAC genes up-regulated during infection by all three strains. The Os12g03050 and Os11g05614 genes showed higher expression during infection with four of the five viruses, and Os11g03310, Os11g03370, and Os07g37920 genes showed high expression during at least three viral infections. We identified some duplicate genes that are classified as neofunctional and subfunctional according to their expression levels in different viral infections. A number of putative cis-elements were identified, which may help to clarify the function of these key genes in network pathways.
The goal of this research is to investigate the effects of Ohmic heating, heat generation, and viscous dissipative flow on magneto (MHD) boundary-layer heat transmission flowing of Jeffrey nanofluid across a stretchable surface using the Koo-Kleinstreuer-Li (KKL) model. Engine oil serves as the primary fluid and is suspended with copper oxide nanomolecules. The governing equations that regulate the flowing and heat transmission fields are partial-differential equations (PDEs) that are then converted to a model of non-linear ordinary differential equations (ODEs) via similarity transformation. The resultant ODEs are numerically resolved using a Keller box technique via MATLAB software that is suggested. Diagrams and tables are used to express the effects of various normal liquids, nanomolecule sizes, magneto parameters, Prandtl, Deborah, and Eckert numbers on the velocity field and temperature field. The outcomes display that the copper oxide-engine oil nanofluid has a lower velocity, drag force, and Nusselt number than the plain liquid, although the introduction of nanoparticles raises the heat. The heat transference rate is reduced by Eckert number, size of nanomolecules, and magneto parameter rising. Whilst, Deborah number is shown to enhance both the drag-force factor and the heat transfer rate. Furthermore, the discoveries reported are advantageous to upgrading incandescent lighting bulbs, heating, and cooling equipment, filament-generating light, energy generation, multiple heating devices, and other similar devices.
The paper focuses on the hepatitis C virus (HCV) infection in Egypt, which has one of the highest rates of HCV in the world. The high prevalence is linked to several factors, including the use of injection drugs, poor sterilization practices in medical facilities, and low public awareness. This paper introduces a hyOPTGB model, which employs an optimized gradient boosting (GB) classifier to predict HCV disease in Egypt. The model's accuracy is enhanced by optimizing hyperparameters with the OPTUNA framework. Min-Max normalization is used as a preprocessing step for scaling the dataset values and using the forward selection (FS) wrapped method to identify essential features. The dataset used in the study contains 1385 instances and 29 features and is available at the UCI machine learning repository. The authors compare the performance of five machine learning models, including decision tree (DT), support vector machine (SVM), dummy classifier (DC), ridge classifier (RC), and bagging classifier (BC), with the hyOPTGB model. The system's efficacy is assessed using various metrics, including accuracy, recall, precision, and F1-score. The hyOPTGB model outperformed the other machine learning models, achieving a 95.3% accuracy rate. The authors also compared the hyOPTGB model against other models proposed by authors who used the same dataset.
Electrical conductivity is very important property of nanomaterials for using wide range of applications especially energy applications. Metal-organic frameworks (MOFs) are notorious for their low electrical conductivity and less considered for usage in pristine forms. However, the advantages of high surface area, porosity and confined catalytic active sites motivated researchers to improve the conductivity of MOFs. Therefore, 2D electrical conductive MOFs (ECMOF) have been widely synthesized by developing the effective synthetic strategies. In this article, we have summarized the recent trends in developing the 2D ECMOFs, following the summary of potential applications in the various fields with future perspectives.
Tobacco products are widely recognized as a major contributor to death. Cigarette smoke contains several toxic chemicals including heavy metals particulate causing high health risks. However, limited information has been available on the health risks associated with the heavy metals in cigarettes commonly sold in the Bangladeshi market. This study evaluated the concentrations and potential health risks posed by ten concerned heavy metals in ten widely consumed cigarette brands in Bangladesh using an atomic absorption spectrometer. The concentration (mg/kg) ranges of heavy metals Pb, Cd, Cr, As, Co, Ni, Mn, Fe, Cu, and Zn vary between 0.46-1.05, 0.55-1.03, 0.80-1.2, 0.22-0.40, 0.46-0.78, 2.59-3.03, 436.8-762.7, 115.8-184.4, 146.6-217.7, and 34.0-42.7, respectively. We assume that the heavy metals content among cigarette brands is varied due to the differences in the source of tobacco they use for cigarette preparation. The carcinogenic risks posed by heavy metals follow the order of Cr > Co > Cd > As > Ni > Pb, while the non-carcinogenic risks for Cu, Zn, Fe, and Mn were greater than unity (HQ > 1), except for Fe. The existence of toxic heavy metals in cigarette tobacco may thus introduce noticeable non-carcinogenic and carcinogenic health impacts accompanying inhalation exposure. This study provides the first comprehensive report so far on heavy metal concentration and associated health risks in branded cigarettes commonly sold in Bangladesh. Hence, this data and the information provided can serve as a baseline as well as a reference for future research and have potential implications for policy and legislation in Bangladesh.