Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.

Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the potential enhancement of HAR models through the fusion of biological signals with inertial signals. The classification of eight common low-, medium-, and high-intensity activities was assessed using machine learning (ML) algorithms, trained on accelerometer (ACC), blood volume pulse (BVP), and electrodermal activity (EDA) data obtained from a wrist-worn sensor. Two types of ML algorithms were employed: a random forest (RF) trained on features; and a pre-trained deep learning (DL) network (ResNet-18) trained on spectrogram images. Evaluation was conducted on both individual activities and more generalized activity groups, based on similar intensity. Results indicated that RF classifiers outperformed corresponding DL classifiers at both individual and grouped levels. However, the fusion of EDA and BVP signals with ACC data improved DL classifier performance compared to a baseline DL model with ACC-only data. The best performance was achieved by a classifier trained on a combination of ACC, EDA, and BVP images, yielding F1-scores of 69 and 87 for individual and grouped activity classifications, respectively. For DL models trained with additional biological signals, almost all individual activity classifications showed improvement (p-value < 0.05). In grouped activity classifications, DL model performance was enhanced for low- and medium-intensity activities. Exploring the classification of two specific activities, ascending/descending stairs and cycling, revealed significantly improved results using a DL model trained on combined ACC, BVP, and EDA spectrogram images (p-value < 0.05).

Experimental Exploration of Multilevel Human Pain Assessment Using Blood Volume Pulse (BVP) Signals.

Critically ill patients often lack cognitive or communicative functions, making it challenging to assess their pain levels using self-reporting mechanisms. There is an urgent need for an accurate system that can assess pain levels without relying on patient-reported information. Blood volume pulse (BVP) is a relatively unexplored physiological measure with the potential to assess pain levels. This study aims to develop an accurate pain intensity classification system based on BVP signals through comprehensive experimental analysis. Twenty-two healthy subjects participated in the study, in which we analyzed the classification performance of BVP signals for various pain intensities using time, frequency, and morphological features through fourteen different machine learning classifiers. Three experiments were conducted using leave-one-subject-out cross-validation to better examine the hidden signatures of BVP signals for pain level classification. The results of the experiments showed that BVP signals combined with machine learning can provide an objective and quantitative evaluation of pain levels in clinical settings. Specifically, no pain and high pain BVP signals were classified with 96.6% accuracy, 100% sensitivity, and 91.6% specificity using a combination of time, frequency, and morphological features with artificial neural networks (ANNs). The classification of no pain and low pain BVP signals yielded 83.3% accuracy using a combination of time and morphological features with the AdaBoost classifier. Finally, the multi-class experiment, which classified no pain, low pain, and high pain, achieved 69% overall accuracy using a combination of time and morphological features with ANN. In conclusion, the experimental results suggest that BVP signals combined with machine learning can offer an objective and reliable assessment of pain levels in clinical settings.

Numerical simulation of burn injuries with temperature-dependent thermal conductivity and metabolism under different surface heat sources.

In the present paper, the phenomena of heat transport inside human forearm tissue are studied through a one-dimensional nonlinear bioheat transfer model under the influence of various boundary and interface conditions. In this study, we considered temperature-dependent thermal conductivity and metabolic heat to predict temperature distribution inside the forearm tissue. We have studied the temperature distribution inside inner tissue and bone because it has been found that burn injuries are mostly affected by layer thickness. The temperature distribution inside human forearm tissue is analyzed using the finite difference and bvp4c numerical techniques. To examine the accuracy of present numerical code, we compare the obtained numerical result with the exact analytical result in a specific case and find an excellent agreement with the exact results. We also validated our present numerical code with a hybrid scheme based on Runge-Kutta (4,5) and finite difference technique and found it in good compliance. From the obtained results, we observed that the homogeneous heat flux has a greater impact on the temperature at the outer surface of the skin, but the sinusoidal heat flux has a greater impact on the temperature of the subcutaneous layer and inner tissue. It is found that there is no burn injury in the first type of heat source (Tw=44°C), but it may occur in the second and third types of heat sources. It has been observed that by raising the blood perfusion rate and reducing the values of reference metabolic heat, coefficient of thermal conductivity, and heat fluxes, we can manage and reduce burn injuries and achieve hyperthermia temperature.

Influence of bamboo vinegar powder (BVP) enriched diet on antioxidant status, immunity level, and pro-anti-inflammatory cytokines modulation in Asian sea bass, Lates calcarifer (Bloch 1790) against Vibrio anguillarum.

Effect of bamboo vinegar powder (BVP) on growth, immunity, disease resistance, and immune-related gene expressions in juvenile Asian sea bass (barramundi), Lates calcarifer against Vibrio anguillarum was investigated. V. anguillarum infected fish fed by 2g BVP kg-1 diet exhibited significant growth, albumin (AB), serum total protein (TP), and globulin (GB) levels. Similarly, enhanced lysozyme (LZM), phagocytic (PC), anti-protease (AP), respiratory burst (RB), bactericidal (BC) activities and total immunoglobulin (Ig) levels were observed in fish fed 2g BVP kg-1. In addition, use of 2g BVP kg-1 in diet modulated several immune related gene expressions against Vibrio disease. This study exhibited a positive effect of dietary 2g BVP kg-1 diet on hemato-biochemical and immunological responses, which enhance the immunocompetence and health status of L. calcarifer against V. anguillarum infection.

Assessment of ROI Selection for Facial Video-Based rPPG.

In general, facial image-based remote photoplethysmography (rPPG) methods use color-based and patch-based region-of-interest (ROI) selection methods to estimate the blood volume pulse (BVP) and beats per minute (BPM). Anatomically, the thickness of the skin is not uniform in all areas of the face, so the same diffuse reflection information cannot be obtained in each area. In recent years, various studies have presented experimental results for their ROIs but did not provide a valid rationale for the proposed regions. In this paper, to see the effect of skin thickness on the accuracy of the rPPG algorithm, we conducted an experiment on 39 anatomically divided facial regions. Experiments were performed with seven algorithms (CHROM, GREEN, ICA, PBV, POS, SSR, and LGI) using the UBFC-rPPG and LGI-PPGI datasets considering 29 selected regions and two adjusted regions out of 39 anatomically classified regions. We proposed a BVP similarity evaluation metric to find a region with high accuracy. We conducted additional experiments on the TOP-5 regions and BOT-5 regions and presented the validity of the proposed ROIs. The TOP-5 regions showed relatively high accuracy compared to the previous algorithm's ROI, suggesting that the anatomical characteristics of the ROI should be considered when developing a facial image-based rPPG algorithm.

Stability of Non-Linear Dirichlet Problems with ϕ-Laplacian.

We study the stability and the solvability of a family of problems -(ϕ(x'))'=g(t,x,x',u)+f* with Dirichlet boundary conditions, where ϕ, u, f* are allowed to vary as well. Applications for boundary value problems involving the p-Laplacian operator are highlighted.

Numerical simulation of heat transfer in blood flow altered by electroosmosis through tapered micro-vessels.

A numerical simulation is presented to study the heat and flow characteristics of blood flow altered by electroosmosis through the tapered micro-vessels. Blood is assumed as non-Newtonian (micropolar) nanofluids. The flow regime is considered as asymmetric diverging (tapered) microchannel for more realistic micro-vessels which is produced by choosing the peristaltic wave train on the walls to have different amplitudes and phase. The Rosseland approximation is employed to model the radiation heat transfer and temperatures of the walls are presumed constants. The mathematical formulation of the present problem is simplified under the long-wavelength, low-Reynolds number and Debye-Hückel linearization approximations. The influence of various dominant physical parameters are discussed for axial velocity, microrotation distribution, thermal temperature distribution and nanoparticle volume fraction field. However, our foremost emphasis is to determine the effects of thermal radiation and coupling number on the axial velocity and microrotation distribution beneath electroosmotic environment. This analysis places a significant observation on the thermal radiation and coupling number which plays an influential role in hearten fluid velocity. This study is encouraged by exploring the nanofluid-dynamics in peristaltic transport as symbolized by heat transport in biological flows and also in novel pharmacodynamics pumps and gastro-intestinal motility enhancement.

Profiles of law enforcement agency body armor policies-A latent class analysis of the LEMAS 2013 data.

The life-saving benefits of body armor have been well-documented, and law enforcement agency (LEA) body armor wear requirements have been cited by police officers as one of the most important reasons for them to wear body armor. However, research on LEAs' policies and practices regarding body armor is scarce. This study examined whether there are different agency-level profiles of various body armor-related policies, and related these body armor policy profiles to agency characteristics, size, location, etc. U.S. LEAs fell into four distinct profiles based on their body armor policies. Close to half of the LEAs had comprehensive coverage of body armor policies in all aspects. However, nearly one in five LEAs had very weak body armor policies in all aspects. The rest of the LEAs split into two groups, each with different strengths and weaknesses on selection, training, fitting, wearing, and inspection policies. Sheriff's offices and smaller LEAs were found to have weaker policies. In contrast, LEAs with a community policing emphasis and those with body armor grants were found to have stronger body armor polices, especially when it comes to mandatory wearing polices. Findings from the study provide a portrait of the current state of LEA body armor policies, and provide guidance for improving LEAs' body armor policies and practices.

LVSP and LBBP Result in Similar or Improved LV Synchrony and Hemodynamics Compared to BVP.

BACKGROUND: The effect of left ventricular septal myocardial pacing (LVSP) and left bundle branch pacing (LBBP) on ventricular synchrony and left ventricular (LV) hemodynamic status is poorly understood. OBJECTIVES: The aim of this study was to investigate the impact of LVSP and LBBP vs biventricular pacing (BVP) on ventricular electrical synchrony and hemodynamic status in cardiac resynchronization therapy patients. METHODS: In cardiac resynchronization therapy candidates with LV conduction disease, ventricular synchrony was assessed by measuring QRS duration (QRSd) and using ultra-high-frequency electrocardiography. LV electrical dyssynchrony was assessed as the difference between the first activation in leads V1 to V8 to the last from leads V4 to V8. LV hemodynamic status was estimated using invasive systolic blood pressure measurement during multiple transitions between LBBP, LVSP, and BVP. RESULTS: A total of 35 patients with a mean LV ejection fraction of 29% and a mean QRSd of 168 ± 24 ms were included. Thirteen had ischemic cardiomyopathy. QRSd during BVP, LVSP, and LBBP was the same, but LBBP provided shorter LV electrical dyssynchrony than BVP (-10 ms; 95% CI: -16 to -4 ms; P = 0.001); the difference between LVSP and BVP was not significant (-5 ms; 95% CI: -12 to 1 ms; P = 0.10). LBBP was associated with higher systolic blood pressure than BVP (4%; 95% CI: 2%-5%; P < 0.001), whereas LVSP was not (1%; 95% CI: 0%-2%; P = 0.10). Hemodynamic differences during LBBP and LVSP vs BVP were more pronounced in nonischemic than ischemic patients. CONCLUSIONS: Ultra-high-frequency electrocardiography allowed the documentation of differences in LV synchrony between LBBP, LVSP, and BVP, which were not observed by measuring QRSd. LVSP provided the same LV synchrony and hemodynamic status as BVP, while LBBP was better than BVP in both.

A numerical study of heat and mass transfer characteristic of three-dimensional thermally radiated bi-directional slip flow over a permeable stretching surface.

Within fluid mechanics, the flow of hybrid nanofluids over a stretching surface has been extensively researched due to their influence on the flow and heat transfer properties. Expanding on this concept by introducing porous media, the current study explore the flow and heat and mass transport characteristics of hybrid nanofluid. This investigation includes the effect of magnetohydrodynamic (MHD) with chemical reaction, thermal radiation, and slip effects. The nanoparticles, copper, and alumina are combined with water for the formation of a hybrid nanofluid. Using the self-similar method for the reduction of Partial differential equations (PDEs) to the system of Ordinary differential equations (ODEs). These nonlinear equation systems are solved numerically using the bvp4c (boundary value solver) technique. The effect of the different physical non-dimensional flow parameters on different flow profiles such as velocity, temperature, concentration, skin friction, Nusselt and mass transfer rate are depicted through graphs and tables. The velocity profiles diminish with the effect of magnetic and slip parameters. The temperature and concentration slip parameters reduce the temperature and concentration profile respectively. The higher values of magnetic factor lessened the skin friction coefficient for both slip and no-slip conditions. An elevation in the thermal slip parameter reduced the boundary layer thickness and the heat transfer from the surface to the fluid. The Nusselt number amplified with the climbing values of the radiation parameter. The mass transfer rate depressed with the solutal slip parameter. Comparison is made with the published work in the literature and there is excellent agreement between them.

Heat transfer innovation of engine oil conveying SWCNTs-MWCNTs-TiO2 nanoparticles embedded in a porous stretching cylinder.

The influence of boundary layer flow of heat transfer analysis on hybrid nanofluid across an extended cylinder is the main focus of the current research. In addition, the impressions of magnetohydrodynamic, porous medium and thermal radiation are part of this investigation. Arrogate similarity variables are employed to transform the governing modelled partial differential equations into a couple of highly nonlinear ordinary differential equations. A numerical approach based on the BVP Midrich scheme in MAPLE solver is employed for solution of the set of resulting ordinary differential equations and obtained results are compared with existing literature. The effect of active important physical parameters like Magnetic Field, Porosity parameter, Eckert number, Prandtl number and thermal radiation parameters on dimensionless velocity and energy fields are employed via graphs and tables. The velocity profile decreased by about 65% when the magnetic field parameter values increases from 0.5 to 1.5. On the other hand increased by 70% on energy profile. The energy profile enhanced by about 62% when the Radiation parameter values increases from 1.0 < Rd < 3.0. The current model may be applicable in real life practical implications of employing Engine oil-SWCNTs-MWCNTs-TiO2 nanofluids on cylinders encompass enhanced heat transfer efficiency, and extended component lifespan, energy savings, and environmental benefits. This kind of theoretical analysis may be used in daily life applications, such as engineering and automobile industries.

Non-similar bioconvective analysis of magnetized hybrid nanofluid (Ag + TiO2) flow over exponential stretching surface.

Scientists have studied fluid flow over a stretching sheet to explore its potential applications in industries. This study investigates the exponential stretching flow of a bioconvective magnetohydrodynamic (MHD) hybrid nanofluid in porous medium taking into consideration thermal radiations, heat generation, chemical reaction, porosity, and dissipation. Moreover, microorganisms are present in the fluid, so the fluid is more stable, which is crucial in biotechnology, biomicrosystems, and bio-nano coolant systems. Silver and titanium dioxide in a water-based medium are the prototypical nanoparticles. The present study involves a transformation of the governing system into a set of dimensionless, coupled and nonlinear partial differential equations (PDEs) using nonsimilar techniques. The local non-similarity (LNS) technique is used to truncate these equations to ordinary differential equations (ODEs). This technique is also used to estimate transformed equations numerically until the second level of truncation takes place via the bvp4c algorithm, which is a built-in MATLAB solver. Furthermore, tables are provided that presents the drag coefficients, Nusselt numbers, Sherwood numbers, and densities of motile microorganisms. Results show a negative correlation between the velocity and the magnetic field parameter as well as the porosity parameter, as evidenced by a decrease in velocity corresponds to rises in these parameters. The temperature distribution exhibits a positive correlation with the rising values of both radiation parameter and Eckert number. The concentration profiles also exhibit a negative correlation with the increasing values of Lewis and bioconvection Lewis number, chemical reaction parameter, Peclet number and the differences in microbial concentration. This study will improve the future research on hybrid nanofluid regarding industrial applications. There haven't been any previous publications that have investigated the use of this model with the local non-similarity method. The main objective of this article is to enhance the heat transfer performance in a hybrid nanofluid.

Numerical investigation of MHD flow of hyperbolic tangent nanofluid over a non-linear stretching sheet.

This research investigates two-dimensional MHD incompressible boundary layer Hyperbolic Tangent nanofluid flow across a non-linear stretching plate. Similarity transformations are employed to convert the governing non-linear partial differential equations (PDEs) into coupled non-linear ordinary differential equations (ODEs). The MATLAB built-in routine bvp4c has been used for finding the numerical solutions of the dimensionless velocity, temperature, and concentration profiles. The current findings are validated with already published results. The influence of some important parameters on the velocity, temperature, and concentration profiles are displayed through graphs and tables. It is observed that for increasing values of magnetic parameter M and hyperbolic Tangent parameter We, the boundary layer thickness of the velocity profile decreases while it increases for the temperature profile.

Analytical study on couple stress flow of GO-EG and GO-W nanofluid over an extending cylinder along with variable viscosity.

The main goal of this research is to present the concept of enhancing heat transfer within emerging technology. To achieve this, tiny metal and nonmetal particles ranging from 1 to 100 nm in size are introduced into base liquids. These nanoscale particles are utilized to improve the thermal performance of the liquids, leading to what are termed nanofluids. The utilization of these fluids and the examination of the flow of thin films have valuable implications across various sectors such as engineering, technology, and industries. This research focuses on analyzing the convective flow behavior of nanofluids, specifically, graphene oxide-ethylene glycol (GO-EG) and graphene oxide-water (GO-W) on a moving surface. The study investigates the impacts of magnetic fields and varying viscosity. By making use of the thermophysical characteristics of the base fluid and the nanofluid, as well as implementing a similarity transformation within the fundamental equations that govern energy and momentum, we formulate a 5th order nonlinear ordinary differential equation (NODE) to describe the velocity profile. This is combined with a second-order NODE that describes the distribution of temperature. To solve this derived NODE, we employ a method known as the Homotopy Analysis Method (HAM) for analytical solution. The impact of the relevant factors, Prandtl number, including magnetic field parameter, thickness of the liquid, couple stress parameter, temperature distribution, dynamic viscosity, and Eckert number, on the skin friction, velocity profile, and Nusselt's number are interrogated through graphical representation. The velocity field exhibits a decline as the couple stress parameter, magnetic field parameter, liquid thickness, and dynamic viscosity experience an increase. Conversely, the temperature field displays a rise as the Eckert number and dynamic viscosity experience an increase. To ensure the convergence of the issue, dual solutions of the problem are employed, and this is verified through the utilization graphs and tables. Due to the considerable challenge encountered in heat transfer applications for cooling diverse equipment and devices across industries like automotive, microelectronics, defense, and manufacturing, there is a strong expectation that this theoretical methodology could make a favorable contribution towards enhancing heat transfer efficiency. This improvement is sought to meet the requirements of the manufacturing and engineering sectors.

Virtual reality exposure aided-diagnosis system for anxiety disorders: Long short-term memory architecture for three levels of anxiety recognition.

BACKGROUND: The COVID-19 pandemic has resulted in increased psychological pressure on mental health since 2019. The resulting anxiety and stress have permeated every aspect of life during confinement. OBJECTIVE: To provide psychologists with an unbiased measure that can aid in the preliminary diagnosis of anxiety disorders and be used as an initial treatment in cognitive-behavioral therapy, this article introduces automated recognition of three levels of anxiety. METHODS: Anxiety was elicited by exposing participants to virtual environments inspired by social situations in reference to the Liebowitz social anxiety scale. Relevant parameters, such as heart rate variability and vasoconstriction were derived from the measurement of the blood volume pulse (BVP) signal. RESULTS: A long short-term memory architecture achieved an accuracy of approximately 98% on the training and test set. CONCLUSION: The generated model allowed for careful study of the state of seven phobic participants during virtual reality exposure (VRE).

Energy transmission through carreau yasuda fluid influenced by ethylene glycol with activation energy and ternary hybrid nanocomposites by using a mathematical model.

The current study aims to assess the augmentation of energy transmission in the presence of magnetic dipole through trihybrid Carreau Yasuda nanofluid flow across a vertical sheet. The rheological properties and thermal conductivity of the based fluids are improved by framing an accurate combination of nanoparticles (NPs). The trihybrid nanofluid (Thnf) has been synthesized by the addition of ternary nanocomposites (MWCNTs, Zn, Cu) to the ethylene glycol. The energy and velocity conveyance has been observed in the context of the Darcy Forchhemier effect, chemical reaction, heat source/sink, and activation energy. The trihybrid nanofluid flow across a vertical sheet has been accurately calculated for velocity, concentration, and thermal energy in the form of a system of nonlinear PDEs. The set of PDEs is reduced to dimensionless ODEs by using suitable similarity replacements. The obtained set of non-dimensional differential equations is numerically computed through the Matlab package bvp4c. It has been perceived that the energy curve enhances by the influence of heat generation factor and viscous dissipation. It is also noted that the magnetic dipole has a momentous contribution to raising the transmission of thermal energy of trihybrid nanofluid and declines the velocity curve. The inclusion of multi-wall carbon nanotubes (MWCNTs), zinc (Zn), and copper (Cu) nano particulates to the base fluid "ethylene glycol", augments the energy and velocity outlines.

Numerical investigation of chemically reacting jet flow of hybrid nanofluid under the significances of bio-active mixers and chemical reaction.

Jet flows are employed in a variety of applications. It can be found in daily life as well as in agriculture, for example, jet flow assists with irrigation and harvest protection. The current problem is related to the study of energy and mass transference on the hybrid nanoliquid flow with mixed convection effect due to the vertical stretching surface conveying the cobalt ferrite CoFe2O4 and titanium dioxide TiO2 nanoparticles (NPs) with the base fluid water H2O. Further, the role of the chemical reaction, heat source/sink, and activation energy are investigated. By exploiting the idea of the modified Buongiorno model, the thermophoretic and Brownian diffusivity effects have discoursed on the existing flow behavior. The existing mathematical problem is framed with the application of the nonlinear higher-order PDEs. Higher-order PDEs of the mathematical model are changed into highly nonlinear ODEs by using the concepts of suitable similarity transformations. The modified higher-order nonlinear ODEs are cracked by manipulating the bvp4c technique in MATLAB. The impacts of the numerous physical flow parameters on the velocity, energy, and concentration are computed in graphical forms. Key findings from the present problem revealed that the velocity of the nanoliquid and hybrid nanofluid decreased due to greater nanoparticles volume fraction. Furthermore, the heat transportation is greater for mixed convection and thermophoresis parameter.

Stability of magnetohydrodynamics free convective micropolar thermal liquid movement over an exponentially extended curved surface.

Micro polar fluids have a wide variety of applications in biomedical, manufacturing, and technical activities, such as nuclear structures, biosensors, electronic heating and cooling, etc. The aim of this study is to investigate the properties of heat transfer on a magnetohydrodynamic free convection movement of micro polar fluid over an exponentially stretchable curved surface. The flow is non-turbulent and steady. The effects of Joule heating, varying thermal conductivity, irregular heat reservoir, and non-linear radiation are anticipated. The modelled PDEs are converted to ODEs via transformation, and the integration problems are then addressed using ND-Solve method along with bvp4c package. It is observed that velocity is reduced and the micro rotation field is increased as the micro rotation parameter is increased. It is witnessed that the temperature of the fluid enhances as the Eckert number is augmented. The velocity is increasing function of the curvature parameter while the decreases with increasing magnetic factor. The distribution of temperature is improved by a rise in temperature-dependent thermal conductivity characteristic. It is investigated that as the values of temperature ratio, Prandtl number, and the Biot number are increased the temperature distribution is enhanced. For the stability of the numerical results, the mean square residue error (MSRE) and total mean square residue error (TMSRE) are computed. For the confirmation of the present analysis, a comparison is done with the published study and excellent settlement is found.

Numerical computation of the optimal vector field: Exemplified by a fishery model.

Numerous optimal control models analyzed in economics are formulated as discounted infinite time horizon problems, where the defining functions are nonlinear as well in the states as in the controls. As a consequence solutions can often only be found numerically. Moreover, the long run optimal solutions are mostly limit sets like equilibria or limit cycles. Using these specific solutions a BVP approach together with a continuation technique is used to calculate the parameter dependent dynamic structure of the optimal vector field. We use a one dimensional optimal control model of a fishery to exemplify the numerical techniques. But these methods are applicable to a much wider class of optimal control problems with a moderate number of state and control variables.

Numerical Case Study of Chemical Reaction Impact on MHD Micropolar Fluid Flow Past over a Vertical Riga Plate.

The purpose of this article is to investigate the mass and heat transport phenomena associated with micropolar fluid flow created by a vertically stretched Riga surface. This is constructed using an array of irregular electrodes and permanent magnets that are oriented spanwise. Additionally, we investigate the particles' micro rotational impacts. Furthermore, the flow behaviour of the modeled problem has been numerically calculated with bvp4c solver and the obtained results are presented graphically. Numerical data are used to illustrate physical parameters such as skin friction, Nusselt, and Sherwood numbers. For precise values of different flow parameters, the characteristics of fluid velocity, angular velocity, temperature, and concentration gradients are investigated graphically. The flowing parallel to the Riga plate in a positive x-path is aided by Lorentz forces introduced into the flowing simulation by the electro-magnetic poles of the Riga plate, which produces a rapidity greater than the inner speed. It is confirmed that the numerical calculations fit well with the results of earlier published investigations. Due to the participation of the Riga plate, the updated Hartmann number has a considerable effect on flow profiles.