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We consider the effect that an upstream cylinder has on the effective inertial collection efficiency of a downstream cylinder. We consider an initially uniform distribution of particles moving past a cylindrical fiber in a potential crossflow and numerically calculate the resulting particle distribution far downstream of the fiber using finite differences. We then investigate the effect that the downstream distribution of particles has on the effective inertial collision efficiency of a downstream test cylinder oriented parallel to the first. We show that the effective collision efficiency of the test cylinder depends on its relative offset in the transverse direction (normal to the flow) with respect to the upstream cylinder. For relatively small offsets there is complete shielding, and no particles collide with the test cylinder. As the offset increases, a growing effective collision efficiency is observed leading to a significant enhancement relative to the collision efficiency of an isolated cylinder for intermediate offsets and Stokes numbers close to unity. Importantly, we observe relative gains in effective collision efficiency above 100% for a range of Stokes number and offset values. For larger offsets and Stokes numbers, the effect of the upstream cylinder on the effective collision efficiency of the test cylinder decreases and eventually becomes negligible. Detailed results are provided for Stokes drag acting on the particles and we also show that a non-linear drag has negligible effect on the observed trends for the conditions relevant to filtration systems. These results suggest that the arrangement of fibers has a substantial effect on inertial particle impaction even when neighboring fibers do not alter the flow field around each individual collector. Moreover, periodic arrangements with specific orientations with respect of the flow could lead to a significant enhancement of the inertial collision of particles on an array of collectors, thus contributing towards a better filtration performance.

In a life testing experiments, accelerated life tests (ALTs) model has provided a significant decrease for the cost and time. The problem of statistical inference of constant-stress ALTs based on censored data is discussed in this paper. So, we implement partially constant-stress ALTs model to test units have two parameter Kumaraswamy lifetime population under adaptive Type-II progressive censoring scheme. The population parameters as well as acceleration factor are estimated by using maximum likelihood method for point and interval estimation. Two different confidence intervals are obtained under bootstrap technique. Also, Bayesian approach under different loss functions is used to contract the point and interval estimates of the model parameters with the help of Markov chain Monte Carlo method (MCMC). For illustrative purpose a simulate data set are analyzed. Different developed results discussed in this paper are compared through Monte Carlo simulation study.

In this study, we will discuss numerical solutions of conformable fractional systems of second-order integrodifferential equations concerning couple types Volterra and Fredholm. These conformable fractional systems will be considered in the sense of periodic boundary conditions in two points. The reproducing kernel Hilbert space method is used with the help of Mathematica 11 to utilize different tabulated data and graphical results. Series representation and required theorems are utilized and proved in the constructed Hilbert spaces. Several applications of linear and nonlinear function types have been studied and solved to ensure the applicability and power of the method. From the gained results, one can note that the approach algorithm is accurate and provides numerical results in a faster time and with less effort. Several notes and highlights with the latest references are discussed and presented at the end of the article.

The linear stability analysis has been analyzed for an electrified liquid sheet confined between two symmetric dielectric movable ambient gas. The present study aims to estimate the planer jet systems response when applying a tangential electric field. The dispersion relations for varicose and sinuous modes have been formulated. The electrical Euler number and some flow parameters have been tested for their influence on the electrified liquid sheet instability. In other words, the effects of electric field on the dominant wave number, and instability range (cutoff wave number) are discussed. The results clarify that the tangential electric field has a stabilizing effect for sinuous mode over the whole range of gas velocity ratio. On the other hand, for varicose mode, the electric field slightly improves the system stability to a certain limit, but it has a great role in stability for higher values of gas velocity ratio.

In order to improve the effect of intelligent sports prediction and analysis, this paper analyzes the traditional high-speed model and proposes a reliable sports action recognition algorithm on this basis. With this algorithm as the core algorithm, sports action recognition can be performed. The paper mainly constructs a standard database structure, inputs a reliable standardized movement model into the database structure, and compares the identified sports movement model with the standard movement model to judge the accuracy of the sports movement. Moreover, this paper uses statistical analysis to study sports training and sports competitions, and obtains prediction results through multi-factor analysis and comparison. In addition, this paper uses statistical methods to process experimental data to draw graphs and tables that can visually observe the results of sports predictive analysis. From the experimental analysis, it can be seen that the algorithm model constructed in this paper has a significant effect.

In recent years, utilization of nano-technology in drugs and cancer growth treatment has produced a great deal of temptation in thermal properties of biological nanofluid, for example, blood with nanoparticles suspension. The objective of this research is to discover a MHD naturally bio-convective flow of non-Newtonian bio-nano-fluid containing blood as base fluid with ( A l 2 O 3 ) alumina nanoparticles suspension carrying effect of buoyancy, chemical reaction, moving microorganism and heat generation near stagnation region. The Buongiorno along Tiwari and Das nanofluid model is employed whereas Oldroyd-B model is capitalized for depicting the viscoelastic behavior of blood. The non-similarity transformations are exercised on governing nonlinear partial differential system (PDE’s) to transform them into system of non-dimensional PDE’s. After applying appropriate transformations the local non-similarity method via bvp4c algorithm is adopted to numerically deal with the problem. The significance of parameters such as Grashof numbers, magnetic field, Brownian motion, thermophoresis, Deborah numbers, Prandtl number, Schmidt number, Peclet number, heat generation/absorption number and chemical reaction on velocity, temperature, concentration and density of moving microorganism are computed in the graphical profiles to explain the physical state of problem. Physical quantities i.e. local Nusselt number, local Sherwood number and local microorganism density number are also calculated.

The coronavirus infectious disease (COVID-19) is a novel respiratory disease reported in 2019 in China. The infection is very destructive to human lives and caused millions of deaths. Various approaches have been made recently to understand the complex dynamics of COVID-19. The mathematical modeling approach is one of the considerable tools to study the disease spreading pattern. In this article, we develop a fractional order epidemic model for COVID-19 in the sense of Caputo operator. The model is based on the effective contacts among the population and environmental impact to analyze the disease dynamics. The fractional models are comparatively better in understanding the disease outbreak and providing deeper insights into the infectious disease dynamics. We first consider the classical integer model studied in recent literature and then we generalize it by introducing the Caputo fractional derivative. Furthermore, we explore some fundamental mathematical analysis of the fractional model, including the basic reproductive number R 0 and equilibria stability utilizing the Routh-Hurwitz and the Lyapunov function approaches. Besides theoretical analysis, we also focused on the numerical solution. To simulate the model, we use the well-known generalized Adams–Bashforth Moulton Scheme. Finally, the influence of some of the model essential parameters on the dynamics of the disease is demonstrated graphically.

With the historical review, it can determine that plasma scientists devolved many numerical schemes in literature to solve the kinetic plasma models such as Vlasov- Maxwell system, but the fatal problem is that most of the designed algorithms violate the conservation laws. This issue is significant and cannot disregard because the Vlasov Maxwell system is connected with conservations properties and can evaluate after performing some effective mathematical operations. In this prospective, we formulated the Atangana-Baleanu fractional derivative with Caputo concepts based fractional-order plasma model to study the fractional performance of the plasma particles and further suggested a higher-order conservative numerical algorithm that follows the conservation laws, based on operational matrices theory which is evaluated by using the concepts of Shifted Gegenbauer estimations. The numerical convergence of the designed algorithm is also inspected to validate the competency and compatibility. The comprehensive analysis of the fractional performance of the plasma particles is also part of the study. Moreover, this concept can extend to the variable order and multi-dimensional problems for Vlasov and Boltzmann system.

In this work, the effect of using baffles and vortex generators on the cooling performance of a gas turbine combustion chamber is numerically investigated. The RNG k-ɛ model is utilized in order to simulate the flow turbulence. The effects of baffles and vortex generator pitch, hydraulic diameter and bypass ratio on the Nusselt number and friction coefficient at different Reynolds number are studied. The cooling performance of applying baffles and vortex generators are also evaluated and compared based on the Performance Evaluation Criterion (PEC). The numerical results are verified with available experimental data. The results show that the pitch increment results in the decrement of the Nusselt number and the wall friction coefficient due to the lower vortices generation and the turbulence kinetic energy dissipation. Also, the Nusselt number is increased by increasing both the bypass ratio and the hydraulic diameter. It is also found that vortex generators and baffles improve the cooling performance of the gas turbine combustion chamber by 18.8% and 26% respectively through decreasing the external wall temperature.

Prey refuge from predators can play an important role in stabilising an ecological system by reducing interactions between species, while Allee effects can arise from a range of biological phenomena, such as anti-predator vigilance, genetic trends and feeding deficiencies. We develop a predator–prey model that combines these phenomena, considering variable prey refuge with additive Allee effect on the prey species, with a Holling type II response function for the prey growth function. We use the predator and prey nullclines to determine the existence and stability of interior equilibria. We also investigate all possible local and global bifurcations that the system could undergo, showing that prey refuge and a strong Allee effect can lead to saddle-node bifurcations, Hopf bifurcations or Bogdanov–Takens bifurcation. We have investigated the appearance of Hopf bifurcations in a neighborhood of the unique interior equilibrium point of the dynamical system. The rich behaviour of the dynamics suggests that both prey refuge and a strong Allee affect are important factors in ecological complexity.

At present, electrospinning technology is a versatile and simple method for generating nano-scale membranes, and it provides attractive solutions in solving environmental problems and many energy problems. However, such films generally have low mechanical properties which limit their use in industry. Nanocellulose with excellent mechanical properties, high specific surface area, and renewable nature is an ideal green reinforcing material. In this paper, the cellulose nanocrystals (CNC) coatings on electrospun polyamide 6 (PA6) were prepared via coating method and explored as potential high-performance reinforced materials. The extraction of CNC and the performance of the composite membranes were studied by calculating the yield, scanning electron microscopy, 3D imaging, mechanical testing, and thermogravimetric analysis. Results show that the yield of CNC is impacted by various factors among which acid concentration is the most important. The CNC/PA6 composite film shows lower porosity and higher surface roughness than the pure PA6 membrane. With the increase of CNC concentration, lower porosity and higher surface roughness are obtained. With CNC coatings, tensile strength and Young s modulus of PA6 increase dramatically, while the tensile strain decreases obviously. The Young s modulus of the composite film has been increased by 250%. The composite membranes reveal high mechanical strength and low porosity, which can be applied infiltration and packaging.

Convection differential equations that include momentum, energy and mass balance equations are used for the simulations of boundary layer (BL) flows. In convection analysis, it is in execution to dimensionless the BL system through similarity variable. However, a wide range of convection differential equations cannot be non-dimensionalized using similarity variable therefore the intent of this manuscript is to develop non-similar model for the forced convective magnetic flow of a viscous fluid above an exponentially expanding surface saturated by nano-fluid. The non-similarity is due to the exponential stretching of the surface and viscous dissipation. Influences of chemical reaction and heat generation are also incorporated. The non-similarity transformation is applied to the nonlinear partial differential system (PDE’s) to transform them into dimensionless PDE’s. Non-similar system is analytically approximated by adapting local non-similarity (LNS) and then it is numerically simulated by finite difference based bvp4c algorithm to explore the influences of significant numbers named as Prandlt number, chemical reaction, magnetic field, Brownian motion, heat generation, Eckert number, thermophoresis on concentration, velocity and temperature distribution. Auxiliary consequences presume that the heat penetration in fluid rises with enhancements in Brownian motion and Prandtl number, while it can be perceived here that for positive estimations of heat generation causes the thicker temperature field. Increasing non-similarity variable and magnetic number become reason for the reduction of temperature profile and chemical reaction is reason of reduced concentration profile.

The discharged volatile organic compounds (VOCs) have aroused more and more attention because of increasing serious air pollution. Accurate prediction of the emission is very important for the industry. Therefore, two kinds of model were developed to predict the VOCs removal efficiency in the RPB, including empirical model and artificial neural network (ANN) models. The empirical model was mainly including gas and liquid mass transfer, effective contact area and liquid holdup. The ANN models were including Cascade-forward back propagation neural network, Feed-forward distributed time delay neural network, Feed-forward back propagation neural network and Elman-forward back propagation neural network. The input parameters were dimensionless numbers, such as high gravity factor, liquid Reynolds number, gas Reynolds number and dimensionless Henry coefficient. The output parameter was removal efficiency. The outlet concentrations of different VOCs predicted by the ANN model were much better than those of the empirical model. And the disadvantages and the advantages were also analyzed. The effects of high gravity factor, gas flow rate and liquid flow rate on the removal efficiency in the RPB were simulated by ANN model with high precision. And then, operation conditions could be timely adjusted to meet the emission standards.

Nature of carbon nanotubes (CNT’s) mechanical characteristics can only be disclosed through advanced studies. Carbon nanotubes show diverse features in radial and axial directions when studied geometrically. Since CNT’s have two dimensional symmetrical behavior and they are in cylindrical shape, they show strong electrical and thermal conductivity in base fluid. In order to develop energy equation, such characteristics must be kept in view, we nominate the heat flux model of Catteneo-Christov. Carbon nanotubes of singlewall and multiwall are analyzed and compared in base fluid of water. Cylindrical coordinates are used in mathematical formulation and modeling for the flow equations to be converted to partial differential equations. For solution and study of fluid equations shooting method and Keller box scheme are used. Our computations resulted in an increase in fluid temperature due to thermal relaxation time, while fluid temperature decreases with an increases in Prandtl number. Further more, porosity also has fluid velocity as its decreasing function. The results are displayed through tables and graphs.

This paper aims to numerically investigate the effects of turbulence-inducing elements with various geometries in a double pipe Heat Exchanger (HEX). The water is considered as a working fluid and the flow is turbulent. Also, CFD simulation has been carried out by finite volume method within commercial software. In the first section, the various geometries, including smooth tube, corrugated tube, tube with spherical elements, and a tube with axial fins, are evaluated. Subsequently, the heat transfer characteristics of two various hybrid nanoparticles comprise Ag-MoS2 and Fe3O4-SiO2, are compared. Ultimately, the optimized geometry has been selected for adding hybrid nanoparticles of Ag-MoS2 to enhancing heat transfer performance. The obtain results indicate that the double tube heat exchanger with the spherical elements has the best thermal performance. In addition, with changing the Reynolds number from 4000 to 13,000 in the optimized model with Ag-MoS2 1%, the convective heat transfer coefficient enhances 62.21%.

The demand of energy saving and loss mitigation in modern industry gives rise to drag reduction techniques such as micro groove/riblet ever since the last century. Plenty of studies are conducted under straight flow condition showing relevance between drag reduction and flow features. However, the same issue has not been studied adequately for rotational flows, which is typical in turbopumps. In this paper, two-dimensional numerical simulations of rotating disks are performed together with verification experiments to investigate drag reduction effect of micro riblet under rotational flow condition. The numerical results show that riblets with certain dimensions can lessen the resistant torque by a maximum of 8.46% and the drag reduction efficiency depends on rotational Reynolds number and riblet dimensions. Meanwhile, the distributions of static pressure and swirl velocity on surfaces are changed and near-wall turbulence intensity is tranquilized by riblets which are considered as the main reasons to the diminish of drag. Finally, the relevance of vortexes inside riblets to swirl wall shear stress and torque is demonstrated revealing that the configuration of riblets plays an important role in cutting resistance. The results of this paper can be a supplement for the investigation of micro groove/riblet drag reduction mechanism.

In the current study, a mathematical model is developed to visualize the mixed convection boundary layer flow of a nanofluid containing gyrotactic microorganisms past a permeable vertical surface saturated in a porous medium with variable viscosity and velocity slip effects. Suction/injection impact is taken into detail through the flow with heat and mass transfer analysis. Appropriate transformations are applied to transform the governing partial differential equations into non-linear ordinary differential equations, before being solved numerically using Runge-Kutta procedure is used with shooting technique. A parametric study focusing the influence of involved parameters on various fields such as the local skin friction coefficient, local Nusselt number are graphed via plots along with the local Sherwood number and motile microorganisms density number. The present results indicate that the motile microorganism number is enhanced for increasing Peclet number estimations. Moreover, the growing in the thermophoresis parameter leads to sufficient enhancement in the skin friction coefficient, Sherwood number and the density of the motile microorganism number for injection case, while the opposite behavior occurred with suction case.

Physical quantities such as skin friction coefficient, local Nusselt number, and local Sherwood number for Casson fluid flow in an irregular channel are determined in this article. Casson fluid properties are primarily enhanced in this flow due to the effects of magnetohydrodynamic (MHD), porous medium, thermal radiation, viscous dissipation, and chemical reaction. Because of the pressure gradient, oscillatory waves formed at the ends of the walls, which are also kept at constant temperatures and concentrations. The Lie group method is used to convert partial differential equations (PDEs) to ordinary differential equations (ODEs). Analytical solutions are provided for the momentum, energy, and concentration equations with benchmark solutions. Dimensionless numbers are computed to interpret physical quantities for this type of flow via graphs and tables. According to the variations of the emerging parameters, physical quantities exhibited reverse behaviour between the upper and lower walls. The velocity profile has an increasing attitude toward the Casson fluid parameter, the Darcy parameter, the wavelength, and the Reynolds number, but a decreasing attitude toward the Hartmann number. The concentration profile is decreasing due to the oscillation effect, but the Schmidt number has a growing influence.

The point of this paper is to analyze and investigate the analytic-approximate solutions for fractional system of Volterra integro-differential equations in framework of Caputo-Fabrizio operator. The methodology relies on creating the reproducing kernel functions to gain analytical solutions in a uniform form of a rapidly convergent series in the Hilbert space. Using the Gram-Schmidt orthonomalization process, the orthonormal basis system is constructed in a dense compact domain to encompass the Fourier series expansion in view of reproducing kernel properties. Besides, convergence and error analysis of the proposed technique are discussed. For this purpose, several numerical examples are tested to demonstrate the great feasibility and efficiency of the present method and to support theoretical aspect as well. From a numerical point of view, the acquired solutions simulation indicates that the methodology used is sound, straightforward, and appropriate to deal with many physical issues in light of Caputo-Fabrizio derivatives.

In this study, a stochastic differential equation capable of describing (using the motion function) the automatic manufacturing process of a lithium battery with a sleeve shell is introduced. The boundary-condition modeling method for this type of motion is an ordinary differential equation. The nonlinear equation is found using a dynamic method. The equations of the motions for the assembly process are derived by reducing the order of terms and separating the variables. Both the derivatives and integrals of the motion functions are derived and applied to describe the assembly process for a lithium battery. By using a characteristic constitutive assembly model, a new method to calculate the nonlinear terms is proposed. The main advantage of this method is that it can simplify the problem, which is done by finding the algebraic error in the region space of the motion function. The reliability and the applicability of the method were confirmed using a real-life example. Finally, by solving and improving the Euler model, the fourth-order Kutta method and Taylor series are applied to verify the correctness of the algorithm, and the convergence order of the function and the optimization of the assembly model are discussed. Through a one-dimensional search of the convergence domain, a method is found to make the analytical solution approximate the exact solution and reduce the calculation cost. This method in dynamics and mathematical engineering.

Nanofluids are expected to be utilized in more efficient based processes. Such nanofluids are employed in cancer therapy, computer electronics, food packaging, and physical sciences, etc. The study focuses on the influence of bioconvection Carreau nanoliquid transport passing via a moving surface. Furthermore, the major properties of the Lorentz force and the magnetic field in Carreau nanoliquid transport are explored. The system of governing PDEs is turned into ODEs by using the appropriate transformation method and then solved by employing the bvp4c technique in computational MATLAB software (Lobatto IIIa formula). The contribution of several key numbers against the velocity profile, concentration profile, temperature profile, and microorganisms’ profile are monitored, and the findings are represented by graphs and numerical data.

Backgroud/purpose Bloodstream infections (BSI) are common in patients with major burns, but its effect on mortality remains controversial. This study was aimed to investigate if BSI is significant risk factor of mortality? Methods This is a retrospective chart review study included 266 adult patients admitted to our burn center from 2000 to 2019. Age, sex, inhalation injuries, total burn surface area (TBSA), duration of stay in intensive care unit, BSI and mortality were variables studied. Fisher exact test, Mann-Whitney test and logistic regression was used for statistical analysis. Results There were 234 survivors and 32 non-survivors. Male was predominant. The overall incidence of BSI was 18.8%, and the overall crude mortality was 12%. Burns ≥ 30% TBSA and BSI were significant risk factors. A predictive function based on 30% TBSA and BSI within 14 days after the onset of burns (BSI-14) was derived. The function has a sensitivity of 0.97, specificity of 0.42 and achieved a maximum Youden Index at functional value ≥ 0.05727. The mortality probability of BSI-14 in burns ≥ 30% TBSA was 40.8%. Conclusions BSI and burns ≥ 30% TBSA were significant risk factors of mortality. Early detection of BSI-14 is critical in burn care as its probability of mortality can be as high as 40% in patients ≥ 30% TBSA of burns. To reduce the risk of mortality, early in ventilator withdrawal, invasive lines and tubes removal, and early grafting should be emphasized besides infection control and appropriate use of antibiotics.

The absence of satisfactory results that address the stability analysis of nonlinear incommensurate Fractional-order Difference Systems (FoDSs) as well as the impossibility of establishing a proper Lyapunov function that helps us to reveal any stability outcome for those systems, are considered some significant nonlinear problems that should be taken into account. To overcome such dilemmas, the present work provides some novel convenient conditions that can be utilized to ensure the asymptotic stability of those systems. In particular, through utilizing some features of the Z-transform scheme, we intend to propose certain results that aim to reveal the stability of the nonlinear incommensurate fractional-order difference system formulated in the sense of the Caputo difference operator. These novel results are completely confirmed by demonstrating the stability of the numerical solutions for two nonlinear difference systems with incommensurate fractional-orders.

Arrival processes to service systems often display (i) larger than anticipated fluctuations, (ii) a time-varying rate, and (iii) temporal correlation. Motivated by this, we introduce a specific non-homogeneous Poisson process that incorporates these three features. The objective is to develop a staffing rule for a many-server system facing such an arrival process. So as to obtain approximations for its performance, we first consider the situation of the arrival process being fed into the corresponding infinite-server system. Using the square-root staffing principle leads to a staffing rule that acknowledges the three features. After a slight rearrangement of servers over the time slots, we succeed to stabilize system performance even under highly varying and strongly correlated conditions. We fit the arrival stream model to real data from an emergency department and demonstrate (by simulation) the performance of the novel staffing rule.

In the current investigation, a triazole, namely 1-Amino-2-mercapto-5-(4-(pyrrol-1-yl)phenyl)-1,3,4-triazole (AMPPT), was synthesized and characterized using ¹H and ¹³C nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectroscopies in addition to CHN micro elemental analysis. A preliminary study of the title compound as corrosion inhibitor for mild steel in 1 M hydrochloric acid solution was evaluated by performing gravimetrical, electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization measurements in addition to scanning electronic microscope (SEM). The obtained experimental results indicated that AMPPT works perfectly as a corrosion inhibitor for mild steel in 1 M HCl solution and its effectiveness is up to 96.3% at 500 ppm and corrosion inhibition efficiency increase with increasing the concentration of tested inhibitor, suggests that the adsorption of AMPPT molecules on the mild steel surface obeyed the Langmuir adsorption model. Polarization measurements show that the studied inhibitor is a mixed type. EIS measurements revealed that the charge transfer resistance increases with increasing concentration of AMPPT. The free energy (ΔGoads) value showed that the adsorption of AMPPT molecules suggesting a mixed-mode of physisorption and chemisorption. Density functional theory (DFT) calculations were performed on AMPPT molecules to determine the quantum parameters and the relationship between the inhibitor structure and inhibiting efficiency. The molecular parameters, such as energy gap and frontier molecular orbitals (HOMO and LUMO), the absolute electronegativity (χ) value, and the fraction transfer of electrons (∆N) were also calculated and correlated with inhibition activity. The theoretical outcomes showed that the inhibition efficiency of AMPPT increased with the increase the energy of HOMO, and the nitrogen and sulphur atoms are the most likely sites for bonding by giving electrons to the unoccupied 3d-orbitals of Fe atoms on the mild steel surface.

A volumetric dispersion model (VDM) with inhibitory kinetics was proposed to describe the biogas production from the acetolastic methanogenesis of the acetate medium process in modeling aspects of the operating capacity and stability. The influence of axial mixing promoted by ultrasonic disruption had been investigated during the methane conversion under a progressive inhibition of substrate in the up-flow anaerobic sludge blanket (UASB) reactor. Increasing the organic loading rates was conducted for the model calibration and prediction to indicate when the process instability occurs due to a potent inhibition and suggest a proper axial mixing. For this simplified substrate characteristics investigation with controlled hydraulic retention time, the results showed that the flow and transfer system with a Peclet number of 1.254 could prevent the system failure. The process instability due to a potent inhibition could be manipulated by using suitable axial mixing to eliminate the inhibitory effect within the reactor.

The main contribution of this paper is proposing a new approach for retrieving the five parameters of the single diode equivalent model (SDM) of photovoltaic cells/modules including the series and shunt resistances. The least square method is used as an error minimization technique for fitting the non-linear transcendental model equation of the solar panel to the measured I–V characteristics. Newton Raphson method is applied to solve the system of five non-linear equations which represent the error of each parameter. Initial guess values are calculated with an optimised algorithm depending on information extracted from the same measured data. MATLAB programming script was used in all implementation steps. This approach is useful for a wide variety of applications where the five SDM parameters have to be determined from the measured curves, particularly, for self-fabricated cells/modules or in case of no available datasheet. One of the strengths of this method is the higher level of accuracy because of the absence of mathematical simplifications and physical assumptions. The method was validated on different types of PV devices, including a crystalline silicon cell, a polycrystalline module, and an amorphous module by using measurement data obtained at a wide range of solar irradiance conditions and temperatures.

In this study, composites containing undoped and barium-doped Bi2WO6:Ba2+were investigated for their shielding against diagnostic X-ray. At first, Bi2WO6 and barium-doped Bi2WO6 were synthesized with different weight percentages of barium oxide through a hydrothermal process. The as-synthesized nanostructures were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and Raman spectroscopy (RS). After that, some shields were generated with undoped and barium-doped Bi2WO6:Ba2+ nanostructure particles incorporated into polyvinyl chloride (PVC) polymer with different thicknesses and 15% weight of the nanostructure. Finally, the prepared samples were exposed to an X-ray tube at 40, 80, and 120 kV voltages, 10 mAs and, 44.5 cm SID (i.e. the distance from the X-ray beam source to the specimen). Linear and mass attenuation coefficients were also calculated for different samples. The results indicated that, among the samples, the one with 7.5 mmol barium-doped Bi2WO6 had the most attenuation at the voltage of 40kV, and the attenuation coefficients would increase with an increase in the amount of barium. The samples with 15 and 17.5 mmol barium-doped Bi2WO6 had higher attenuation than the others at 80 and 120 kV. Moreover, the half-value layer (HVL), tenth-value layer (TVL) and 0.25 mm lead equivalent thickness were calculated for all the samples. The lowest HVL value was for the sample with 7.5 mmol barium-doped Bi2WO6. As the result clearly show, an increment in the barium-doping content leads to a decrease in both HVL and TVL. In every three voltages, 0.25 mm lead equivalent thickness of the barium-doped composites (7.5 mmol and 15 mmol) had less than the other composites. The lowest value of 0.25 mm lead equivalent thickness was 7.5 barium-doped in 40 kV voltage and 15 mmol barium-doped in 80 kV and 120 kV voltages. These results were obtained only for 15% weight of the nanostructure.

This paper considers an optimal pricing problem for the black box producer-consumer Stackelberg game. A producer sets price over a set of goods to maximize profit (the difference in revenue and cost function). The consumer buys a quantity to maximize the difference between the value of the quantity consumed and the cost. The value function of the consumer and the cost function of the producer are ‘black box’ functions (unknown functions with limited or costly evaluations). Using Gaussian processes, Bayesian optimization and Bayesian quadrature we derive an algorithm for learning the optimal price. The method has the following significant advantages: (i) the method is efficient and scales well compared to existing techniques, (ii) the cost function of the producer could be non-convex, (iii) the value function and/or cost function can be time varying. We illustrate, using a real dataset, optimal pricing in electricity markets.

This chapter presents Gaussian elimination and Gauss-Jordan row reduction that are important techniques for solving linear systems. Attempts to solve systems of linear equations inspired much of the development of linear algebra. The study of linear systems leads to the examination of further properties of matrices including row equivalence, rank, and the row space of a matrix. A linear equation is an equation involving one or more variables in which only the operations of multiplication by real numbers and summing of terms are allowed. When several linear equations involving the same variables are considered together, a system of linear equations is obtained. Many methods are available for finding the complete solution set for a given linear system in which the Gaussian elimination is most important that begins with the augmented matrix for the given system and examines each column in turn from left to right. There are three operations that we are allowed to use on the augmented matrix in the Gaussian elimination method: (1) multiplying a row by a nonzero scalar, (2) adding a scalar multiple of one row to another row, and (3) switching the positions of two rows in the matrix.

Publisher Summary With image enhancement, the visibility of selected features in an image can be improved, but the inherent information content cannot be increased. The design of a good image enhancement algorithm should consider the specific features of interest in the microscopic image and the imaging process itself. The image enhancement algorithms can be classified into two categories: spatial domain methods and transform domain methods. The spatial domain methods include operations carried out on a whole image or on a local region selected on the basis of image statistics. Techniques that belong to this category include histogram equalization, image averaging, sharpening of important features such as edges or contours, and nonlinear filtering. The transform domain enhancement methods manipulate image information in transform domains, such as Fourier and wavelet transforms. Often, interesting image information cannot be separated out in the spatial domain but can be isolated in the transform domain. For example, one can amplify certain coefficients in the Fourier domain and then recover the image in the spatial domain to highlight interesting image content. The wavelet transform is another powerful tool that has been developed in recent years and used for image enhancement.

Publisher Summary This chapter discusses the process of object classification with the very useful maximum-likelihood method. One straightforward and quite powerful approach is the use of the Bayes maximum-likelihood classifier. It generates second-order surfaces that partition the color space into disjoint regions, one for each object type (i.e., for each color of pixel). Assuming Gaussian distributions for the clusters of points in color space, the Bayes classifier maximizes the probability that each pixel will be assigned correctly. The first step is to train the classifier to recognize the three types of pixels. This requires a training set containing pixels that are known to fall in the background, inside normal cells, and inside abnormal cells. It is the statistics of these training set pixels that constitute the knowledge the classifier has about the problem. Estimating these statistics is the process of classifier training.

This chapter introduces the theory and applications of calculus of variation. We introduce the Euler equation, which is vital in solving the functional problem. We examine the solution methods in one-dimensional and in both higher dimensions and functions of multiple variables. This theory plays a vital part in the derivation of the variational-based data assimilation theory.

Secretory and membrane proteins traffic from the ER to the Golgi via COPII-coated vesicles that form via the action of five conserved coat proteins. This process is further regulated to respond to cellular and environmental conditions that permit traffic of the large diversity in form and function of cargo molecules.

The membrane potential is a key aspect of cellular function and cell-to-cell signaling, and thereby ultimately body functions. This article describes the basic principles regarding electrical and chemical properties of ions and membranes, how these forces combine to determine electrochemical gradients that, when combined with membrane permeability give rise to membrane potentials. The article quantifies these principles using a range of simple equations such as Ohm’s Law, the Nernst equation, and the Goldman–Hodgkin–Katz (GHK) equation, and illustrates how to calculate the number of ions flowing in or out of a cell during typical membrane potential changes. The role of active and passive transporters in generating membrane potentials is briefly described, with a focus on the important role of a channel’s selectivity filter and gating mechanism. The final section discusses ways to experimentally measure membrane potentials and some caveats to be aware of when using these approaches. The challenges associated with an accurate measurement of membrane potential is illustrated by the range of absolute values reported for the resting membrane potential in hippocampal pyramidal neurons, and it may be a little misleading to consider a membrane as ever at ‘rest.’ Changes in membrane potential are a major cellular unit of organ and body function. It is hoped this article provides a simple and clear outline of the membrane potential and its underlying principles and mechanisms to assist students and researchers in cell biology.

Investigates aging and lifetime reduction of transformers and induction machines due to elevated temperatures caused by harmonics. The additional temperature rise caused by harmonics is defined by a weighted-harmonic factor function which has not yet been published in a textbook. The Arrhenius reaction rate equation is relied on to estimate the reduction in lifetime of motors and transformers due to harmonic voltage magnitudes. Harmonic limits within single- and three-phase power systems are proposed and rigid harmonic spectra are not recommended. The probabilistic and time-varying nature of harmonics and their incurred cost are reviewed. Various operating regimes of electric machines are investigated from a lifetime reduction point of view. Heat flow relations due to radiation and convection are given with their associated thermal equivalent circuits. 11 application examples with solutions and 11 application-oriented problems are included.

The concepts of population genetics and evolution seem simple from an abstract, academic perspective, but in reality, nature is too heterogeneous and dynamic to allow science to be so easy. To provide a reference scenario, we describe evolution by natural selection in patchy landscapes without consideration of pest density. Complications involving a variety of ecological processes are discussed. We describe random genetic drift and demographic Allee effects on evolution. We explore the complexities of genetic architecture for arthropods that evolve resistance. The roles of selection intensity, gene interaction, fitness costs, and dominance (expression of resistance) are presented. Even though most research has been on diploid arthropods, many species can be haplo-diploid (males are haploid, females are diploid). The relationship between generation time and resistance evolution is evaluated. We emphasize the importance of temporal and spatial scales for hypotheses and recommendations regarding evolution of resistance.

In this chapter we extend the theory from univariate distributions to multivariate formulations for a select few distributions: the Gaussian, lognormal, and gamma distributions. We shall also introduce mixed distribution, which is a combination of Gaussian and lognormal random variables. We shall highlight that not all of the desired properties of the univariate descriptive statistics carry over to the multivariate formulation, but start to lay the foundations for the derivation of many of the data assimilation schemes in later chapters.

Publisher Summary This chapter discusses various functions of the gastrointestinal tract that is essential for the orderly digestion, absorption, and transportation of food and residue. The motor activity of the gut is one of the integrated functions that are essential for the normal assimilation of food. Gut motility facilitates the transportation of nutrients, brings together digestive enzymes and their substrates, temporarily stores content, particularly in the distal small bowel and right colon, for optimal absorption, and finally, excretes nondigestible residue by defecation in a well-coordinated function under voluntary control. The extrinsic autonomic nervous system (ANS) is critically important for almost all secretory and motor functions in the digestive tract. The function of the gastrointestinal smooth muscle is intimately controlled by the release of peptides and transmitters by the intrinsic (or enteric) nervous system; the modulation of the latter input arises in the extrinsic autonomic nerves, the craniospinal parasympathetic excitatory input, and the thoracolumbar sympathetic outflow, which is predominantly inhibitory to the gut but excitatory to the sphincter. Gastrointestinal smooth muscle forms an electrical syncytium whereby the impulse that induces the contraction of the first muscle cell results in efficient transmission to a sheet of sequentially linked cells in the transverse and longitudinal axes of the intestine. The pacemaker of the intestinal muscle syncytium is the network of interstitial cells of Cajal that serve to coordinate contraction circumferentially and longitudinally along the gut.

The chapter reviews fundamental theories, formulas, solution methods, and a set (toolbox) of MATLAB functions for static analysis of Euler–Bernoulli beams. The system requirements for the MATLAB toolbox—a PC with Win 98SE/NT/2000 and XP or Mac with OS 9.x and up, and the software MATLAB (version 5.x and up) installed on the computer. A fundamental problem in the static analysis of Euler-Bernoulli beams is stated as the given external loads and boundary disturbances that determines the beam response (displacement, rotation, bending moment, and shear force), which is governed by a given equation and boundary conditions. There are many solution methods available for the static analysis of Euler-Bernoulli beams. The chapter presents three analytical solution methods for the beam problem—method of singularity functions, the boundary value approach, and distributed transfer function method (DTFM). The MATLAB functions are developed based on the distributed transfer function method, which is an exact analytical modeling and solution method for many one-dimensional distributed systems including bars, shafts, strings, and beams.

Because of the heavy metal content and other toxic chemicals, used lubricating oil remains one of the most serious environmental concerns. The target of this work is the synthesis of γ-Al2O3 from waste aluminum foil and re-refining waste lubricating oils using solvent extraction pursued by hydrotreatment. The trimetallic CoNiMo/γ-Al2O3 catalyst was prepared via a co-impregnation method. The support and tri-metallic supported alumina are characterized by N2 adsorption–desorption techniques, X-ray diffraction (XRD), Raman spectroscopy, HRTEM, and EDX. The catalyst was evaluated in the hydrotreating of extracted waste lubricating oils. The results confirmed that the solvent to oil ratio of 3 gave the higher performance with the highest percent of sludge elimination at room temperature. Hydrotreating of extracted lube oil was investigated to determine the effect of variables such as temperature, pressure, liquid hour space velocity, and hydrogen to oil feed ratio. The results indicated that the optimum conditions are (temperature 400 °C, Pressure 60 bar, 0.75 h−1 LHSV). The results showed improvement of the hydrotreated waste lubricating oils properties by decreasing the refractive index from 1.480 to 1.460, the total acid number decreased from 8.164 to 0. 459, the Viscosity Index increase from 78 to 129, and the Sulfur content decreased from 6752 ppm to 543 ppm.

Owing to the improved thermophysical properties of nano-materials, the nanofluid convey novel applications in industries, engineering as well as bio-medicals. With high efficiency performances, the nanoparticles include applications in various cooling and heating systems, energy production, aerospace engineering, thermal extrusion, bio-medical applications like treatment of diseases, brain tumour, surgical applications and many more. Moreover, the magneto-nanofluids have the characteristics in the flow of blood in the human artery. The current analysis deals with the free convective unsteady flow of viscous nanofluid subject to the magnetic force over a vertical plate in presence of porous space. The heat transfer phenomenon is accessed by utilizing the additional features like Joule heating, viscous dissipation and absorption coefficients. In addition to the volume fraction of the nanofluid, the effect of the chemical reaction is also introduced. The solution procedure for the modified time-dependent boundary value problem is performed by using the code in-build MATLAB namely Built-in-Shooting method. The change in velocity, temperature and concentration of nano-materials is examined through various graphs. The physical consequences of flow parameters like porosity parameter K p 1 ⩽ K p ⩽ 3 , thermal Grashoff number Gr 1 ⩽ G r ⩽ 3 , solutal Grashoff number Gc 1 ⩽ G c ⩽ 3 , magnetic field parameter M 1 ⩽ M ⩽ 3 , thermal radiation parameter Nr 0.1 ⩽ N r ⩽ 1 , radiation absorption parameter Q 0 ⩽ Q ⩽ 0.5 , Prandtl number Pr 2 ⩽ Pr ⩽ 21 , Eckert number Ec 0 ⩽ E c ⩽ 0.4 , heat source S - 0.2 ⩽ S ⩽ 0.2 , chemical reaction parameter Kc 1 ⩽ K c ⩽ 4 , nanoparticles volume fraction ϕ 0.0 ⩽ ϕ ⩽ 0.1 , Lewis number Le 1 ⩽ L e ⩽ 10 on velocity, temperature and concentration distributions is graphically analyzed. The results show that skin friction coefficients decline with buoyant forces. A lower numerical variation in Nusselt number is resulted with heat source parameter. Moreover, a sharp fall in nanofluid concentration is noticed with increment of chemical reactants and Lewis number.

The authors propose the side information-free low-computational complexity Time Domain Sequence Superposition-Selected Mapping (TDSS-SLM) scheme for PAPR suppression. We adopt IFFT point reduction for transmitter and reception technique using pilot subcarriers for side information estimation. The simulation results show the TDSS-SLM transmitter achieves PAPR reduction of 2.3 dB which corresponds to the 1.5 times larger PAE than that in the conventional transmitter. In addition, the proposed receiver shows loss-less BER performances for both AWGN channel and two types of fading channels, while the computational complexity of the proposed receiver is nearly the same as the conventional OFDM receiver, which is less than 1/10 of the ML receiver.

An analysis related to the transport of nanofluid that is confined in a channel between two orthogonal permeable walls will be investigated with the help of two numerical techniques. With the aid of the reasonable similarity changeover; the said model will be shaped into the desired non-linear equation whose behavior will be explained analytically as well as graphically where the functioning of three disparate variables such as magnetic parameter, permeable Reynold number, and channel permeable ratio will be explained precisely. The said model has been controlled by the homotopy analysis method (HAM) and then, compared through an efficient numerical method named shooting method (ShM). The profiles show that increases in the magnetic parameter decline the nanofluid flow velocity, whereas magnitude-wise raise is shown in each axial velocity profile. The radial profile raises while getting variation in wall expansion parameter from negative to positive. For the entire domain, the rate of change in velocity description enhances at the center while reduces at the surfaces. And the outcomes disclose that the wall permeable ratio has a significant impact on the solutions. Since the zero value of wall ratio refers to the particular type that Terrill has discussed.

In this paper, we present a convergence proof for an iterative procedure of local mode filtering. We formulate the local mode filtering as a quadratic optimization problem based on the Legendre transform of convex function, from which two closed-form expressions at each iteration step are derived for variables to be optimized. Those analytical solutions ensure that the value of objective function increases monotonically with the progress of the iterative procedure. We also show experimental results using a grayscale image, which support our theoretical results practically.

In this research article, two Haar wavelet collocation methods (HWCMs) (namely one dimensional HWCM and two dimensional HWCM) are adapted to approximate linear homogeneous and linear non-homogeneous Klein–Gordon equations. The results obtained from both methods are compared with exact solutions. Moreover, both of the methods are also compared together, that indicates much better performance of two dimensional Haar wavelet collocation method (2D HWCM) in a small number of collocation points.

In this paper, we study a Susceptible-Vaccinated-Infected-Recovered (SVIR) epidemic model in a spatially heterogeneous environment under the Dirichlet boundary condition. We define the basic reproduction number ℜ 0 by the spectral radius of the next generation operator, and show that it is a threshold parameter. The disease extinction and persistence in the case of a bounded domain are considered. More precisely, we show that the disease-free equilibrium is globally asymptotically stable if ℜ 0 1 ; the system is uniformly persistent and an endemic equilibrium exists if ℜ 0 > 1 . To verify our theoretical results, we perform some numerical simulations, using the Fredholm discretization method to identify ℜ 0 .

In sample surveys, when we need information regarding rare sensitive issues which people often do not prefer to share with others. In such situations this is also awkward for interviewers to ask the direct questions related to confidential and private matters of interviewees. An approach towards the open queries about sensitive issues generally results in the high non-response rates or misleading answers. The aim of this paper is to develop an effective randomized response model to overcome with these types of challenges arising due to sensitive nature of characteristic under study. In this paper we have proposed three-stage randomized response model for estimating mean number of individuals who possessed rare sensitive attribute which makes use of Poisson distribution. The properties of the proposed estimation procedures have been deeply examined when the parameter of a rare unrelated attribute is known as well as unknown. Privacy protection of respondents is also an equally important matter of concern. So measure of privacy protection for the proposed randomized response model has also been examined. Empirical studies are performed to support the theoretical results, which show the dominance of the proposed estimators over well-known contemporary estimators. From the findings of this study we may conclude that proposed randomized response model is rewarding in terms of percent relative efficiencies and privacy protection and may be recommended to survey practitioners for real life applications.