Influence of chemical reaction on heat and mass transfer of non-Newtonian fluid with yield stress by free convection from vertical surface in porous medium considering Soret effect

The effect of chemical reaction on free convection heat and mass transfer for a non-Newtonian power law fluid over a vertical flat plate embedded in a fluid-saturated porous medium has been studied in the presence of the yield stress and the Soret effect. The governing boundary layer equations and boundary conditions are cast into a dimen- sionless form by similarity transformations, and the resulting system of equations is solved by a finite difference method. The results are preSented and discussed for concentration profiles, as well as the Nusselt number and the Sherwood number for various values of the parameters, which govern the problem. The results obtained show that the flow field is influenced appreciably by the presence of the chemical reaction parameter γ the order of.the chemical reaction parameter m, the Soret number St, the buoyancy ratio N, the Lewis number Le, and the dimensionless rheological parameter Ω.

Natural convection of non-Newtonian power-law fluid over axisymmetric and two-dimensional bodies of arbitrary shape in fluid-saturated porous media

Numerical analysis of the free convection coupled heat and mass transfer is presented for non-Newtonian power-law fluids with the yield stress flowing over a two-dimensional or axisymmetric body of an arbitrary shape in a fluid-saturated porous medium. The governing boundary layer equations and boundary conditions are cast into a dimensionless form by the similarity transformation. The resulting system of equations is solved by a finite difference method. The parameters studied are the rheological constants, the buoyancy ratio, and the Lewis number. Representative velocity, temperature, and concentration profiles are presented and discussed. It is found that the results depend strongly on the values of the yield stress parameter and the power-law index of the non-Newtonian fluid.

Toddy Palm (Borassus Flabellifer) Fruit Fibre Bundles as Reinforcement in Polylactide (PLA) Composites: An Overview About Fibre and Composite Characteristics

Toddy palm fruit have an apparent density below 0.8 g/cm³and offer an interesting lightweight construction potential in polylactide(PLA)composites reinforced with 37 mass-%fibres.Single fibre bundles show similar mechanical properties compared with coir:tensile strength of 240 MPa,Young´s modulus of 3.8 GPa and an elongation at break of 31%.However,density and diameter(~50μm)of fruit fibre bundles are significantly lower.The compression moulded composites have a density of 0.9 g/cm³and achieved an unnotched Charpy impact strength of 12 kJ/m^(2),a tensile strength of 25 MPa,Young’s modulus of 1.9 GPa and an elongation at break of 9%.Due to the high porosity of the composites and the different stress-strain behaviour of fibre and matrix the fibre-reinforcement potential could not be fully used.Maximum stress of the composite was reached at the elongation at break of the PLA-matrix(~2%)while the fibre achieved its maximum stress at an elongation of~31%.After reaching the maximum stress of the composite,the fibres were pulled out from the matrix with low energy absorption,resulting in a decrease in stress and a limited reinforcement potential.Additionally,the study investigates whether an insect attack by the Asian fruit fly on the mesocarp has a significant influence on the mechanical fibre characteristics.The results have shown that only the rough surface of the fibre bundles is smoothed by insect infestation.The mechanical properties were not significantly affected.For this reason insect-infested fruits of the toddy palm,which are no longer suitable for food production,can be used for the production of sustainable composite materials.

Potential of Thai Bast Fibers for Injection Molded PLA Composites

Thailand has a huge variability of bast fiber plants,some of which have been little researched regarding their applicability in composites.Bast fiber(bundle)s from different species were investigated and incorporated into a polylactide(PLA)matrix by injection molding.Hemp and kenaf were used as well-studied fibers,while roselle,Fryxell and paper mulberry are less extensively characterized.Tensile strength,tensile modulus and interfacial shear strength(IFSS)of single fiber(bundle)s were highest for hemp,followed by kenaf,roselle,Fryxell and paper mulberry.Despite the lower tensile strength and IFSS of paper mulberry,the highest tensile strength was achieved for the paper mulberry/PLA composite followed by hemp/PLA.Scanning electron microscope(SEM)analyses showed that the single cells in paper mulberry fiber bundles,in contrast to the other fiber types investigated,were only partially bonded to each other,which explains the lower strength of the fiber bundles.The higher aspect ratio of fiber(bundle)s of paper mulberry in the PLA composite can explain the good composite characteristics.Apart from hemp,paper mulberry shows the best reinforcing effect in the PLA matrix and offers interesting potential for composite applications.Compared to neat PLA,the tensile strength could be increased by 24%and the tensile modulus by 54%.

Stochastic Framework for Solving the Prey-Predator Delay Differential Model of Holling Type-Ⅲ

The current research aims to implement the numerical resultsfor the Holling third kind of functional response delay differential modelutilizing a stochastic framework based on Levenberg-Marquardt backpropagationneural networks (LVMBPNNs). The nonlinear model depends uponthree dynamics, prey, predator, and the impact of the recent past. Threedifferent cases based on the delay differential system with the Holling 3^(rd) type of the functional response have been used to solve through the proposedLVMBPNNs solver. The statistic computing framework is provided byselecting 12%, 11%, and 77% for training, testing, and verification. Thirteennumbers of neurons have been used based on the input, hidden, and outputlayers structure for solving the delay differential model with the Holling 3rdtype of functional response. The correctness of the proposed stochastic schemeis observed by using the comparison performances of the proposed and referencedata-based Adam numerical results. The authentication and precision ofthe proposed solver are approved by analyzing the state transitions, regressionperformances, correlation actions, mean square error, and error histograms.

Boundary-layer non-Newtonian flow over vertical plate in porous medium saturated with nanofluid

The free convective heat transfer to the power-law non-Newtonian flow from a vertical plate in a porous medium saturated with nanofluid under laminar conditions is investigated. It is considered that the non-Newtonian nanofluid obeys the mathematical model of power-law. The model used for the nanofluid incorporates the effects of Brown- ian motion and thermophoresis. The partial differential system governing the problem is transformed into an ordinary system via a usual similarity transformation. The numer- ical solutions of the resulting ordinary system are obtained. These solutions depend on the power-law index n, Lewis number Le, buoyancy-ratio number Nr, Brownian motion number Nb, and thermophoresis number Nt. For various values of n and Le, the effects of the influence parameters on the fluid behavior as well as the reduced Nusselt number are presented and discussed.

Medical Image Compression Based on Wavelets with Particle Swarm Optimization

This paper presents a novel method utilizing wavelets with particle swarm optimization(PSO)for medical image compression.Our method utilizes PSO to overcome the wavelets discontinuity which occurs when compressing images using thresholding.It transfers images into subband details and approximations using a modified Haar wavelet(MHW),and then applies a threshold.PSO is applied for selecting a particle assigned to the threshold values for the subbands.Nine positions assigned to particles values are used to represent population.Every particle updates its position depending on the global best position(gbest)(for all details subband)and local best position(pbest)(for a subband).The fitness value is developed to terminate PSO when the difference between two local best(pbest)successors is smaller than a prescribe value.The experiments are applied on five different medical image types,i.e.,MRI,CT,and X-ray.Results show that the proposed algorithm can be more preferably to compress medical images than other existing wavelets techniques from peak signal to noise ratio(PSNR)and compression ratio(CR)points of views.

Using Genetic Algorithm for Identification of Diabetic Retinal Exudates in Digital Color Images

Blood vessels in ophthalmoscope images play an important role in diagnosis of some serious pathology on retinal images. Hence, accurate extraction of vessels is becoming a main topic of this research area. In this paper, a new hybrid approach called the (Genetic algorithm and vertex chain code) for blood vessel detection. And this method uses geometrical parameters of retinal vascular tree for diagnosing of hypertension and identified retinal exudates automatically from color retinal images. The skeletons of the segmented trees are produced by thinning. Three types of landmarks in the skeleton must be detected: terminal points, bifurcation and crossing points, these points are labeled and stored as a chain code. Results of the proposed system can achieve a diagnostic accuracy with 96.0% sensitivity and 98.4% specificity for the identification of images containing any evidence of retinopathy.

Dynamics for a hybrid non-autonomous prey-predator system with generalist predator and impulsive conditions on time scales

In this paper,we investigate the dynamical behavior for a hybrid non-autonomous predator-prey system with Holling Type II functional response,impulsive effects and generalist predator on time scales,where our proposed model commutes between a continuous-time dynamical system and discrete-time dynamical system.By using com--parison theorems,we first study the permanence results of the proposed model.Also,we established the uniformly asymptotic stability for the almost periodic solution of the proposed model.Finally,in the last section,we provide some examples with numerical simulation.

Flexible Traceable Generic Genetic Algorithm

This document elaborates on the generic implementation one of the main heuristics algorithms verified through its quick application to a biology problem requiring to find out an optimal sequences tree topology. In order to solve this problem, categorized as Non-Polynomial Hard (NP-Hard), “to minimize differences between given (leaf) and/or derived (parent) sequences”, many popular methods are used. “The higher the number of given sequences is, the more advisable and efficient it would be to go towards heuristics as they would provide a close-enough solution faster, as for instance genetic algorithms amongst others do. Thus, as part of a larger research in Heuristics and phylogenies, this paper aims to suggest a generic advanced flexible implementation of the Genetic Algorithm verified by a “general way to encode the problem into instances of different heuristic algorithms” as mentioned in our first reference below. The proposed algorithm will also present a chronology traceability feature for further analysis and potential improvements.

Generic Simulated Annealing

One of the many problems that are considered to be NP-Hard is the Multiple Sequence Alignment one that initially requires, as for any other of its siblings, a specific encoding schema and design of the main functionalities of the heuristics algorithm being implemented and executed. This paper intends to discuss our proposed generic implementation of the Simulated Annealing, inspired for the procedure of cooling and shaping methods of metals. In our algorithm, we attempted to add some executions tracing functionalities in order to help later analysis for initial parameters tuning. On another hand, we also tried to get closer in our attempt to mimic the cooling of metals, but giving it an option to run under different cooling schedules. We proposed a few schedules that seemed to be studied and/or used in many algorithm implementations.

Generic Tabu Search

The Multiple Sequence Alignment problem is considered to be an NP-Hard problem, requiring initially a specific encoding schema and design, as for any other of its siblings, to implement and run any of the main categories of heuristic. This paper intends to discuss our proposed generic implementation of the Tabu Search algorithm, a heuristic procedure proposed by Fred Glover to solve discrete combinatorial optimization problems. In this research, we try to coordinate and synchronize different designs/implementations discussed in many literatures, with some of the references mentioned in this paper. The basic idea is to avoid that the search for best solutions stops when a local optimum is found, by maintaining a list of non-acceptable or forbidden (taboo) solutions/costs, called Tabu list or Short-Term Memory (STM). In our algorithm, we attempt to add some executions tracing functionalities in order to help later analysis for initial parameters tuning. On the other hand, we propose to include the concept of a list called Long-Term Memory (LTM), so that some of the best solutions found so far can be saved, for search diversification.

Polynomial Decay and Blow Up of Solutions for Variable Coefficients Viscoelastic Wave Equation with Acoustic Boundary Conditions

A variable coefficient viscoelastic wave equation with acoustic boundary conditions and nonlinear source term is considered. Under suitable conditions on the initial data and the relaxation function g, we show the polynomial decay of the energy solution and the blow up of solutions by energy methods. The estimates for the lifespan of solutions are also given.

Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication

Understanding individual decisions in a world where communications and information move instantly via cell phones and the internet,contributes to the development and implementation of policies aimed at stopping or ameliorating the spread of diseases.In this manuscript,the role of official social network perturbations generated by public health officials to slow down or stop a disease outbreak are studied over distinct classes of static social networks.The dynamics are stochastic in nature with individuals(nodes)being assigned fixed levels of education or wealth.Nodes may change their epidemiological status from susceptible,to infected and to recovered.Most importantly,it is assumed that when the prevalence reaches a pre-determined threshold level,P*,information,called awareness in our framework,starts to spread,a process triggered by public health authorities.Information is assumed to spread over the same static network and whether or not one becomes a temporary informer,is a function of his/her level of education or wealth and epidemiological status.Stochastic simulations show that threshold selection Pand the value of the average basic reproduction number impact the final epidemic size differentially.For the ErdÖos-Rényi and Small-world networks,an optimal choice for Pthat minimize the final epidemic size can be identified under some conditions while for Scalefree networks this is not case.

A DNA sensor based on upconversion nanoparticles and two-dimensional dichalcogenide materials

We demonstrate the fabrication of a new DNA sensor that is based on the optical interactions occurring between oligonucleotide-coated NaYF4:Yb^(3+);Er^(3+) upconversion nanoparticles and the two-dimensional dichalcogenide materials,MoS_(2) and WS_(2).Monodisperse upconversion nanoparticles were functionalized with single-stranded DNA endowing the nanoparticles with the ability to interact with the surface of the two-dimensional materials via van der Waals interactions leading to subsequent quenching of the upconversion fluorescence.By contrast,in the presence of a complementary oligonucleotide target and the formation of double-stranded DNA,the upconversion nanoparticles could not interact with MoS_(2) and WS_(2),thus retaining their inherent fluorescence properties.Utilizing this sensor we were able to detect target oligonucleotides with high sensitivity and specificity whilst reaching a concentration detection limit as low as 5 mol·L^(-1),within minutes.

Physicochemical and toxicological characteristics of nanoparticles in aerosols in southern Thailand during recent haze episodes in lower southeast Asia

Transboundary haze from biomass burning is one of the most important air pollutions in Southeast Asia.The most recent serious haze episode occurred in 2015.Southern Thailand was affected by the haze during September to October when the particulate matter concentration hit a record high.We investigated physical and chemical characteristics of aerosols,including concentration and aerosol size distribution down to sub-micron sizes during haze episodes in 2013 and 2015 and,for reference,an insignificant haze period in 2017.The highest total suspended particulates and PM 10 levels in Hat Yai city were 340.1 and 322.5μg/m^3.The mass fractions were nanoparticles(<100 nm)3.1%-14.8%and fine particles(<1μm)54.6%-59.1%.Polycyclic aromatic hydrocarbon size distributions in haze periods peaked at 0.75μm and the concentrations are 2-30 times higher than the normal period.High molecular weight(4-6 ring)PAHs during the haze episode contribute to about 56.7%-88.0%for nanoparticles.The average values of benzo(a)pyrene toxic equivalency quotient were 3.34±2.54ng/m^3 in the 2015 haze period but only 0.89±0.17 ng/m^3 in 2017.It is clear that particles smaller than 1μm,were highly toxic.Nanoparticles contributed 19.4%-26.0%of total BaP-TEQ,whereas the mass fraction is 13.1%-14.8%.Thus the nanoparticles were more carcinogenic and can cause greater health effect than larger particles.The fraction of BaP-TEQ for nanoparticles during 2017 non-haze period was nearly the same,while the mass fraction was lower.This indicates that nanoparticles are the significant source of carcinogenic aerosols both during haze and non-haze periods.

Mathematical Validation of Proposed Machine Learning Classifier for Heterogeneous Traffic and Anomaly Detection

The modeling of an efficient classifier is a fundamental issue in automatic training involving a large volume of representative data.Hence,automatic classification is a major task that entails the use of training methods capable of assigning classes to data objects by using the input activities presented to learn classes.The recognition of new elements is possible based on predefined classes.Intrusion detection systems suffer from numerous vulnerabilities during analysis and classification of data activities.To overcome this problem,new analysis methods should be derived so as to implement a relevant system to monitor circulated traffic.The main objective of this study is to model and validate a heterogeneous traffic classifier capable of categorizing collected events within networks.The new model is based on a proposed machine learning algorithm that comprises an input layer,a hidden layer,and an output layer.A reliable training algorithm is proposed to optimize the weights,and a recognition algorithm is used to validate the model.Preprocessing is applied to the collected traffic prior to the analysis step.This work aims to describe the mathematical validation of a new machine learning classifier for heterogeneous traffic and anomaly detection.

Complex dynamics of COVID-19 mathematical model on Erdos-Rényi network

In this study,a conformable fractional order Lotka-Volterra predator-prey model that describes the COVID-19 dynamics is considered.By using a piecewise constant approximation,a discretization method,which transforms the conformable fractional-order differential equation into a difference equation,is introduced.Algebraic conditions for ensuring the stability of the equilibrium points of the discrete system are determined by using Schur-Cohn criterion.Bifurcation analysis shows that the discrete system exhibits Neimark-Sacker bifurcation around the positive equilibrium point with respect to changing the parameter d and e.Maximum Lyapunov exponents show the complex dynamics of the discrete model.In addition,the COVID-19 mathematical model consisting of healthy and infected populations is also studied on the Erdos Rényi network.If the coupling strength reaches the critical value,then transition from nonchaotic to chaotic state is observed in complex dynamical networks.Finally,it has been observed that the dynamical network tends to exhibit chaotic behavior earlier when the number of nodes and edges increases.All these theoretical results are interpreted biologically and supported by numerical simulations.

A nonautonomous mat hematical model to assess the impact of algae on the abatement of atmospheric carbon dioxide

The world's oceans have played an important role in sequestering atmospheric carbon dioxide through solubility and the action of algae.Fixation of atmospheric carbon dioxide by photoautotrophic algal cultures has the potential to diminish the release of carbon dioxide into the atmosphere,thereby helping to alleviate the trend toward global warming.This work investigates the role of algae in controlling the level of atmospheric carbon dioxide.Partial Rank Correlation Coefficients(PRCCs)technique is used to address how the concentration of atmospheric carbon dioxide is affected by changes in a specific parameter disregarding the uncertainty over the rest of the model parameters.Parameters related to algal growth are shown to significantly reduce the level of atmospheric CO_(2).Further,we explore the dynamics of nonautonomous system by incorporating the seasonal variations of sonic ecologically important model parameters.Our nonautonomous system exhibits globally attractive positive periodic solution,and also the appearance of double periodic solution is observed.Moreover,by letting the seasonally forced parameters as almost periodic functions of time,we show almost periodic behavior of the system.Our findings suggest that the policy makers should focus on continuous addition of nutrients in the ocean to accelerate the algal growth thereby reducing the level of carbon dioxide in the atmosphere.