Motion Parameters Research Articles

Automated External Bone Fixation Robot Design and Orthopedic Analysis

Background: Bone external fixation technology is an important therapeutic approach for limb correction, primarily involving a class of external fixation correction mechanisms. It has achieved good results in limb lengthening and correcting deformities to restore limb function. In clinical practice, existing correction mechanisms face challenges such as high resistance between components, complex installation procedures, and high precision requirements for installation, requiring manual adjustment by physicians, which limits precise control and quantification of correction parameters. Objective: To address these issues, an automated correction bone external fixation robot was designed based on traditional Ilizarov external fixation devices(TIEFD). Methods: By increasing the number of unidirectional hinge connections, the robot can effectively reduce motion resistance. Subsequently, the robot was combined with the tibia for correction motion simulation, obtaining the motion parameters θ of the deformed bones during the correction process based on the trajectory of the tibia's point mass. Finally, correction motion experiments and finite element analysis(FEA) were conducted on the robot combined with a control system. Results: The results showed that the robot could precisely control correction parameters, with the error range for rotational correction not exceeding 0.5 radians and the error range for traction correction not exceeding 0.2 mm. FAE, based on corrective force data, concluded that compared to (TIEFD), the robot could reduce bone stress by 16 MPa during the correction process. Conclusion: The robot effectively reduces patient discomfort, this provides a reliable theoretical basis for bone external fixation technology and holds positive significance for the treatment of skeletal deformities.

Impact of viscous dissipation on MHD flow of Maxwell nanofluid across a linear stretching sheet

The viscous dissipation of Maxwell nanofluid movement on a stretching sheet is examined in the present article. Constructed the modelling equalities with assumptions and emerging parameters such as Magnetic parameters, thermophoresis, Brownian motion, and Biot number etc. Convert those equation to simple third-order ODEs by applying stream functions, MATHEMATICA software used to solve ODE by applying the RK method approach with shooting technique. Presented our outcomes graphically by incorporating the parameters. The elasticity of the Maxwell fluid is directly proportional to temperature, resulting in a reduction in its velocity. The factors that affect fluid flow include viscous dissipation, Lewis number, Brownian motion, and the reversibility of temperature and velocity. Increasing the parameters of Brownian motion leads to significant movement of the nanofluid particles, which in turn increases their kinetic energy and enhances heat generation in the boundary layer. The Lorentz force, which hinders the movement of fluid, leads to a decrease in velocity profiles. This is determined by the magnetic parameter. The heat transfer rate, the velocity decay rate, and the occurrence of viscous dissipation are all occurring in close proximity to the sheet. Also, the model tabular validation presented and current results align well with previously published studies. Cancer treatment and the cooling process in industries, polymer processing, biotechnology and medicine, food industry, cosmetics, oil and gas, textiles, aerospace and automotive, and construction are just a few of the technical and biological uses for it. Industries may enhance material performance, process efficiency, and product quality in a variety of applications by using Maxwell fluid models.

Potential dynamic corneal response parameters for myopia: relationships between axial length with whole eye movement at the first and second applanations and the highest concavity

PurposeTo investigate the correlation between whole eye movement (WEM) parameters measured using Corvis ST and axial length (AL) to explore whether AL affects WEMs.MethodsThis single-center, cross-sectional study included data from healthy subjects and patients preparing for refractive surgery at the Qingdao Eye Hospital of Shandong First Medical University. Data were collected from July 2021 to April 2022. We first determined the correlations of WEMs at the time of corneal first applanation (A1_WEM), highest concavity (HC_WEM), and second applanation (A2_WEM), as well as the maximum value of WEM (WEM_Max) with AL. Subsequently, we established a series of regression models to analyze the relationships between different WEM values and AL.ResultsAL was negatively correlated with HC_WEM, A2_WEM, and WEM_Max (r = − 0.28, − 0.23, and − 0.22, respectively; P < 0.001). The correlation between AL and A1_WEM was not significant (P = 0.77). According to the adjusted regression models, AL was negatively associated with HC_WEM (Model 2: β = −7.39, P < 0.001) and WEM_Max (Model 4: β = −3.52, P = 0.02), while the associations of AL with A1_WEM (Model 1: P = 0.61) and A2_WEM (Model 3: P = 0.23) were not significant.ConclusionsAL is an independent negative influencing factor for HC_WEM. WEM is a potentially useful parameter that reflects the biomechanical properties of the eye behind the cornea in myopia.

Task-Specific Perceived Harmfulness Predicts Protective Movement Behaviour in Chronic Low Back Pain.

Background/Objectives: There is emerging evidence that task-specific pain-related psychological measures may better predict movement behaviour in chronic low back pain (CLBP) than general pain-related psychological measures. Currently, little is known regarding the prediction of movement duration and movement velocity. Methods: Baseline data from a previously published randomized controlled trial were used (clinicaltrials.gov NCT02773160). Fifty-five patients with CLBP and 54 pain-free persons performed a lifting task while kinematic measurements were obtained to calculate movement velocity of the L1 vertebra, S1 vertebra, and the lumbar spine, as well as the time to complete the lifting task. Scores on the Photograph Daily Activities Series-Short Electronic Version (PHODA-SeV), Tampa Scale for Kinesiophobia (TSK), and its Activity Avoidance and Somatic Focus subscales were used as general pain-related psychological measures. The score on a picture of the PHODA-SeV, showing a person lifting an object with a bent back (PHODA-Lift), was used as task-specific measure of perceived harmfulness. Results: The task-specific measure best predicted movement duration and movement velocity of L1 and the lumbar spine, and explained 35%, 19%, and 25% of the respective movement parameters. Although general perceived harmfulness predicted S1 velocity and movement duration, it only explained 6% and 8% of the respective movement parameters. General measures of pain-related fear were not predictive for any of the movement parameters. It took patients with CLBP significantly longer to complete the lifting task when compared to the pain-free participants (ES = 1.01, p < 0.0001), and patients with CLBP also moved significantly slower at L1 (ES = 0.85, p < 0.0001) and the lumbar spine (ES = 1.01, p < 0.0001). These between-groups differences were larger for CLBP subgroups with higher scores on the PHODA-Lift, and to some extent for subgroups with higher total scores on the PHODA-SeV. Conclusions: Task-specific perceived harmfulness best predicts movement velocity. General pain-related fear measures (i.e., TSK and its subscales) do not predict these movement parameters.

The role of innovations in the development of modern sports games and its impact on physical activity and sports achievements

Scientific and technical progress is rapidly accelerating, therefore innovative technologies penetrate into all aspects of human life, in particular, into the sports sphere. They open new horizons, allow you to achieve positive results and offer high-tech equipment and equipment. The purpose of the article was to analyze the impact of innovations on physical activity in modern society and sports achievements. In the course of the study, it was found that innovations are innovative methods, technologies and approaches that are implemented to achieve new results, improve processes or solve problems in a certain field. Technological innovations such as virtual reality, innovative materials for sports equipment, artificial intelligence, digital technologies have affected all sports. The main examples of these technologies and their advantages of implementation in the sports industry were analyzed. So, for example, it is determined that the use of synthetic materials in poles for athletics increases their catapulting properties and sports achievements of athletes. Virtual reality technologies contribute to the effective training of cyclists, providing the opportunity to reproduce different weather conditions and types of routes, to test different strategies of speed and intensity of riding without any risks. Modern technologies, which allow to objectively evaluate the biomechanical parameters of the athlete's movements and to correct and improve them, contribute to a significant increase in the effectiveness of the athlete training system. The main groups of modern biomechanical technologies implemented in sports are analyzed. Significant technological updates in the field of sports are caused by the active implementation of digital technologies. Digital technologies help improve the national health care system by facilitating the collection, analysis and dissemination of data on health and physical activity. A key innovation in sports is also the use of fitness trackers and mobile applications that provide personalized training programs and nutritional recommendations.

Diffusion-thermo and thermo-diffusion impacts on MHD natural convection flow of maxwell nanofluids over a stretching sheet

The present study carried out significant importance in its magnetic field and crosswise diffusion influenced the Maxwell nanofluid flow past a nonlinear stretching sheet. This investigation aimed to shed light on the behavior of critical parameters, particularly in the presence of thermophoresis and Brownian motion. The primary aim is to investigate the impact of thermal diffusion, diffusion-thermo, and various influencing factors on a Maxwell nanofluid near a stretching sheet in the magnetic field, and the impact of three distinct slip conditions (velocity, thermal, and solutal). The partial differential equations by the nonlinear coefficients are utilized in obtaining the most important equations. These equations are distorting to beneficial nonlinear ordinary differential equations making use of the appropriate transformations variables and transformation coefficients. To investigating the computational solutions for the reducing sets of the nonlinear ordinary differential equations, these were developing and utilized the Keller box methodology. The simulations are carried out the nanofluids velocity, temperature, concentration, skin friction coefficients, the rate of temperature transport, in addition to the rate of mass transportation, amongst previous variables. The validations of this methodology are displayed via the comparison of the present outputs through the preceding judgments into the literatures. The major conclusions drawn from this study are the concentration profiles exhibited opposing behaviours as concentration slip parameter increased. However, the temperature profile increases for Brownian motion parameter and thermophoresis parameter parameters. Secondly, concentration displayed an increasing behavior as the Soret number increased.

Motion Planning for Dynamic Three-Dimensional Manipulation for Unknown Flexible Linear Object

Generally, deformable objects have large and nonlinear deformations. Because of these characteristics, recognition and estimation of their movement are difficult. Many studies have been conducted aimed at manipulating deformable objects at will. However, they have been focused on situations wherein a rope’s properties are already known from prior experiments. In our previous work, we proposed a motion planning algorithm to manipulate unknown ropes using a robot arm. Our approach considered three steps: motion generation, manipulation, and parameter estimation. By repeating these three steps, a parameterized flexible linear object model that can express the actual rope movements was estimated, and manipulation was realized. However, our previous work was limited to 2D space manipulation. In this paper, we extend our previously proposed method to address casting manipulation in a 3D space. Casting manipulation involves targeting the flexible linear object tips at the desired object. While our previous studies focused solely on two-dimensional manipulation, this work examines the applicability of the same approach in 3D space. Moreover, 3D manipulation using an unknown flexible linear object has never been reported for dynamic manipulation with flexible linear objects. In this work, we show that our proposed method can be used for 3D manipulation.

Ground motion parameters and damage correlation in plan irregular L-shape steel structure with BRB

Irregularly designed structures frequently experience greater damage compared to regular buildings as a result of elevated torsional reactions and stress concentration, as indicated by evaluations of damage carried out subsequent to past seismic events. The irregularities in the plan configuration provide significant issues for building seismic design. One example of an irregularity is the re-entrant corners found in L-shaped structures, which can lead to early collapse by causing stress concentration from abrupt changes in stiffness and torsional response amplification. More than ever, a thorough investigation into the relationship between the issue of ground motion parameters (GMPs) and Damage is required because of the complex way that L-shaped buildings respond to earthquakes. The current study examines the relationship between a large number of commonly used GMPs and the associated damage for three-, six-, nine-, and twelve-story 3D buildings—that is, low-, mid, and high-rise structures—with asymmetric L-shaped plan layouts. The system of lateral load resistance that was used was Buckling Restrained Brace Frames (BRBFs). To assess a building's seismic performance, 15 bidirectional earthquake ground motions were applied using Nonlinear Time History Analysis (NTHA) for incident angles of 0°, 45°, 135°, 225°, and 315°. The structural response is reported in terms of the average and maximum inter-story drift as well as the total Park-Ang damage index. The relationship between GMPs and structural damage was then investigated using Pearson's correlation coefficient. The results indicate that the highest link with damage measurements is found for 3- and 6-story structures when looking at the spectral acceleration at the fundamental period, Sa(T1). However, PGD and SMV exhibit a stronger correlation than other GMPs for structures with nine and twelve stories. Additionally, Classification and Regression Trees (CART) is a decision tree algorithm used for predictive modeling. In this study suggested using CART (Classification and Regression Trees) algorithms to estimate the link between GMPs and Damage Indices. The findings demonstrate the ability of CART algorithms to extract the rules and correlations governing earthquake damage.

A non-parametric model of ground motion parameters for shallow crustal earthquakes in Europe

The current study focuses on deriving ground motion models (GMMs) for 21 ground motion parameters derived from data sourced from the Engineering Strong Motion (ESM) database. These parameters include Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), Peak Ground Displacement (PGD), PGV-to-PGA ratio, (V/H) PGA ratio Predominant Frequency (Fp), Central Frequency (Ω), Spectral Parameter (q), Significant Duration (TSig), Root Mean Square Acceleration (Arms), Arias Intensity (Ia), Cumulative Absolute Velocity (CAV), Characteristic Intensity (IC), Acceleration Spectrum Intensity (ASI), Velocity Spectrum Intensity (VSI), Total Energy (Eacc), Spectral Centroid (Ew), Spectral Standard Deviation (Sw), Temporal Centroid (Et), Temporal Standard Deviation (St), and Correlation between time and frequency [ρ(t,ω)]. Both horizontal and vertical components are considered in this study. The inherent random effects within ground motion regression, encompassing inter-event, inter-site, inter-locality, and inter-region variabilities, are addressed using cross-nested mixed effect regression utilizing a non-parametric GMM approach employing Artificial Neural Network (ANN). Quantitative assessment of the models involves correlation coefficients for regression through the origin and error measures like mean squared error and mean absolute error. These findings of the assessment confirm reliable estimates of Ground Motion Parameters (GMPs). A comparison of GMPs computed using the proposed model and those reported in the literature indicated model's superior performance. Furthermore, satisfactory performance of the proposed GMM in ground motion simulation for the ESM region is demonstrated.

Reach-dependent reorientation of rotational dynamics in motor cortex

During reaching, neurons in motor cortex exhibit complex, time-varying activity patterns. Though single-neuron activity correlates with movement parameters, movement correlations explain neural activity only partially. Neural responses also reflect population-level dynamics thought to generate outputs. These dynamics have previously been described as “rotational,” such that activity orbits in neural state space. Here, we reanalyze reaching datasets from male Rhesus macaques and find two essential features that cannot be accounted for with standard dynamics models. First, the planes in which rotations occur differ for different reaches. Second, this variation in planes reflects the overall location of activity in neural state space. Our “location-dependent rotations” model fits nearly all motor cortex activity during reaching, and high-quality decoding of reach kinematics reveals a quasilinear relationship with spiking. Varying rotational planes allows motor cortex to produce richer outputs than possible under previous models. Finally, our model links representational and dynamical ideas: representation is present in the state space location, which dynamics then convert into time-varying command signals.

Trajectory Recognition and Working Condition Analysis of Rod Pumping Systems Based on Pose Estimation Method with Heatmap-Free Joint Detection

Summary Rod pump systems are the primary production tools in oilfield development. Analyzing their working conditions provides a theoretical foundation for formulating production optimization plans and adjusting equipment parameters. Existing machine learning–based condition analysis methods rely on dynamometer cards and cannot capture the actual operational trajectory of the pumping unit. To address this issue, this paper proposes a keypoint detection method for pumping units based on pose estimation of heatmap-free joint detection from video data. A data annotation scheme suitable for the task of detecting pumping unit keypoints was developed, and the learning criteria for this task were optimized. An end-to-end heatmap-free pose estimation algorithm was used to process images of the pumping unit, yielding predicted keypoint positions, thereby enabling the identification of the keypoint motion trajectories of the pumping unit. Experiments validated the proposed method and compared it with general learning criteria. Results show that this method accurately captures the keypoint positions of the pumping unit, with the optimized learning criteria model improving by more than 5% compared with general methods and increasing the keypoint object keypoint similarity (OKS) by more than 30%. The model’s results can be used for the actual operational trajectory recognition of the pumping unit, automatically calculating the motion parameters of the polished rod, and intelligently assessing the balance and working condition analysis of the pumping unit. This realizes the intelligent application of video surveillance data, significantly contributing to the dynamic study of rod pump systems.

The effects of bioconvection, non‐Fourier heat flux, and thermal radiations on Williamson nanofluids and Maxwell nanofluids transportation with prescribed thermal conditions

AbstractThe utilization of nanoentities in common fluids has opened new opportunities in the area of heat transportation. The rising requirements to enhance the efficiency of compact heat exchangers can be achieved by using various nanofluids. In this article, the thermal output of Maxwell and Williamson nanofluids transport over a prolonging sheet with bioconvection of self‐motivated organisms is scrutinized. A magnetic flux and the porous effects of a medium influence the flow of fluids. The fundamental principles for conservation of mass, concentration, momentum, and energy yield a nonlinear set of partial differential equations that can then be altered into ordinary differential form. A heat transfer flux is presented along with temperature boundary conditions, PST, and PHF (prescribed surface temperature and prescribed heat flux). The numerical results are acquired by executing the Runge–Kutta method with a shooting procedure in MATLAB coding. By fluctuating the inputs of influential variables of the dependent functions, a precise overview of the scheme is acquired. It can be seen that velocity decreases with the rising values of buoyancy ratio, magnetic force, Raleigh number, and porosity. Also, the temperature of the fluids begins to rise directly with the rising values of thermophoresis and Brownian motion parameters. The present study addresses bioconvection, non‐Fourier heat flow, and thermal radiations while combining the special properties of Williamson and Maxwell nanofluids. The field of biomedical engineering may benefit from this study, particularly with regard to therapies for hyperthermia and drug delivery systems. This study can be useful in cutting‐edge cooling systems, bioengineering, solar energy conversion and biotechnology.

Empirical approaches for non-linear site response: results for the ESG6-blind test

As a contribution to step 3 of the ESG6 blind prediction exercise, we present an application of two different, purely empirical approaches to estimate the strong ground motion at a soft site ("KUMA") from the observed ground motion at a reference rock site ("SEVO") for the two largest shocks of the Kumamoto 2016 sequence. The two methods estimate the non-linear transfer function between a reference rock and a sedimentary site by modifying the linear transfer function derived from weak motion recordings. The modification is based either on a machine learning tool based on a wide collection of Japanese weak and strong motion recordings and the associated site metadata (method 1), or on an estimate of a site-specific parameter related to an average non-linear site response (method 2). The acceleration time series are then derived at the sedimentary site of interest using an estimation of the time delay between wave arrivals at the rock and site stations, and a minimum phase assumption for the site transfer function. These predictions were made blindly, but after the ESG6 conference they could be compared both with the actual ground motion recorded at KUMA during the two shocks, and the average and range of all other predictions preformed for this benchmark. Both of these purely empirical methods provide an honorable prediction of usual engineering ground motion parameters of the two target events. The performance of these two purely empirical approaches is at least comparable to those of the numerical simulation methods for the foreshock—if not better—and slightly worse for the (largest) mainshock. As the methods required only recordings of weak motions at the target and a referent sites and very simple description of the soil profile. The use of moderate motions to constrain the frequency shift prediction for the second method and the consideration of an alternative phase modification are possible ways to improvement.Graphical

Unsteady magnetohydrodynamic bioconvection Casson fluid flow in presence of gyrotactic microorganisms over a vertically stretched sheet

The free convective, unsteady, two-dimensional (2D) magnetohydrodynamic (MHD) Darcy–Forchheimer Casson fluid flow via a vertical stretching sheet containing gyrotactic microorganisms was the novel aspect of this investigation. We rewrote the collection of partial differential equations (PDEs) as nonlinear ordinary differential equations (ODEs) by considering an appropriate similarity variable. We solved the overhaul of nonlinear ODEs using MATLAB’s bvp4c approach. This study rigorously investigates the significance of gyrotactic microorganisms for Casson fluid motility. Additionally, this work investigates the impact of various parameters, including magnetic parameters, thermophoresis, Brownian motion, and radiation parameters, on temperature, motile microorganisms, velocity, and concentration profiles. We use graphs to illustrate the outcomes of various fluid flow parameters. Numerical tables display the effects of different parameters on skin friction, Sherwood number, Nusselt number, and the quantity of motile microorganisms. The unsteady parameter causes a drop in the velocity, temperature, concentration, and the density profile of microorganisms. Additionally, the Casson parameter leads to a decrease in the flow profile, while simultaneously increasing the heat, concentration, and microorganism density profiles. The microorganism density profile decreases as the bioconvection Schmidt number, Peclet number, and motile microbe parameter increase. We deem the new results extremely satisfactory when compared to earlier research. The fields of environmental remediation, biomedical sciences, and engineering may find this examination useful.

Influence of ground motion parameters on seismic response of a large-longitudinal-slope and small-radius curved girder bridge.

The mechanical performance of curved bridges under the action of an earthquake is complex. To obtain the influence of seismic parameters on the seismic response of curved girder bridges, this paper relies on a large slope small-radius curved steel box girder bridge (LSCGB) and selects seismic wave incidence angle, vertical component of ground motion, and site category as seismic parameters to carry out nonlinear time history analysis. Based on the analysis results of the case bridge, it is shown that the torsional vibration of the first 10 modes of LSCGB is significant, the modes are dispersed, and the contribution of high-order modes of vibration cannot be ignored. The most unfavorable seismic wave incidence angle is in the direction of 45°∼60° counterclockwise Angle from the central connection line of Pier No. 1 and Pier No. 4 of the bridge. The seismic response of the curved bridge components increases with the vertical seismic intensity, and the influence on displacement responses is more significant. The basic vibration period of curved girder bridges built on soft soil sites is extended by approximately 18.23%, and the seismic response of key components increases with the softening of the site soil. Therefore, when analyzing the seismic response of LSCGBs, the influence of vertical component of ground motion and site category should not be ignored.

A COMPARATIVE ANALYSIS OF LUMBAR INTERVERTEBRAL MOTION BETWEEN LOW BACK PAIN SUBGROUPS AND HEALTHY CONTROLS USING QUANTITATIVE FLUOROSCOPY

Study purpose and backgroundKinematic variables have been identified as potential biomarkers for low back pain patients; however, an in-depth comparison between chronic (n=22), acute (n=15), and healthy controls (n=136) has not been done. This retrospective data analysis compared intervertebral lumbar motion parameters, angular range of motion, translation, maximum disc height, motion share inequality (MSI) and variability (MSV), and laxity, between these groups.Methods and resultsKinematic parameters were determined using video tracking techniques utilising quantitative fluoroscopy (QF), during both weight-bearing and recumbent controlled sagittal bending tasks. Data was analysed for normality, and appropriate statistical tests were applied to determine differences between groups. There were no significant differences between the groups for age, height, weight and sex. Whilst few differences were found between acute and healthy groups, differences were shown between both chronic and healthy, and acute and chronic groups for all six parameters. Of particular note were examples of differences in the motion share parameters between the acute and chronic populations, with an increased MSI in the chronic group during recumbent flexion, and MSV during recumbent extension, and inversely an increase in MSV in the acute group during weight-bearing flexion.ConclusionAnalysis of intervertebral lumbar motion provides valuable insights into kinematic differences between chronic, acute, and healthy control populations. These findings suggest that there is variation between the groups which is knowledge that may benefit management strategies. Further exploration of the time varying data is warranted to explore how such differences may relate to the motion share inequalities and variability shown.Conflicts of InterestNo conflicts of interestSources of FundingNo funding obtained

Simulation of Ship Berthing Operation at Luojing Container Terminal Under Extreme Sea Conditions

The Luojing Port Area of the Port of Shanghai, specifically the coal terminal and ore terminal, used to be the main port area for coal and ore bulk cargo transportation services in the Port of Shanghai.To enhance the container handling capacity at Shanghai port, this study conducted a series of simulation tests at Luojing Container Terminal. The tests were designed according to the terminal&amp;apos;s specifications, taking into account the limit berthing wind direction and wind speed (levels 6 and 7). This study selected an appropriate representative ship type for the comprehensive simulation tests, and it thoroughly tested the berthing limits under various extreme conditions using an advanced navigation simulator. The experiment obtained the motion parameters and trajectory of the simulated ship. Based on these results, this study analyzed and evaluated the safety of the rotary waters and berthing operations, ensuring they met the safety assessment requirements for wharf engineering. The study examined the berthing time window, berthing mode, boundary conditions, and safety guarantee measures under extreme sea conditions at Luojing Container Terminal. Finally, By analyzing the berthing simulation trajectory diagrams, tugboat usage, and vessel maneuvering data under the eight extreme berthing conditions, this study formulated a safe berthing plan for ships.

Applications of neural networking in Eyring-Powell nanofluid dynamics on a rotating surface in a porous medium

One of the fundamental aspects of solving difficult and nonlinear mathematical ideas is the use of Artificial Neural Networks due to their exceptional efficiency in handling such problems. In many complex fields such as computational fluid system, biological computation, and biotechnology, a distinct computing structure is provided by Artificial Neural Networks, which is extremely valuable. The main purpose of this article is to dig out the abilities of the Levenberg-Marquardt technique using back-propagation artificial neural networks regarding the fluid mechanics and the heat transport assessment in nanoparticles. This interdisciplinary field explores heat and mass transfer through objects and fluids, and their impacts on temperature as well as concentration distributions. With the help of mathematical modelling and numerical solution methodologies, researchers can simulate and analyze these processes. The present analysis communicates the Eyring-Powell fluid flow caused by a rotating disk placed in the horizontal direction. The fluid flow over a rotating disk through non-linear partial differential equations is modeled. After converting the partial differential equations to ordinary ones, they are tackled numerically through shooting technique. The Levenberg-Marquardt algorithm using back-propagation artificial neural networks technique is used with reference datasets, having 70 % training, 15 % testing, and 15 % to validation. The method is validated with the help of mean squared error, error histogram and comprehensive regression analysis. These figures show the accuracy of the proposed method for solving nonlinear problems. Flow features such as velocity, temperature as well as the concentration profiles are exemplified quantitatively and have been graphically discussed. Velocity of the fluid decreases for porosity and increases for fluid parameter while temperature increases for thermophoresis and Brownian motion parameters. Consistency is shown by getting a minimum absolute error approaching zero, showing the strength of the proposed approach.

ASEAN-5 Stock Indexes Predictions using Geometric Brownian Motion

Even though the ASEAN-5 region has recently experienced enormous economic growth and advancement, this expansion has been associated with increased market volatility. Analysing historical data to assess stock market performance is crucial to comprehending these markets' dynamics and spotting potential hazards and opportunities. This study seeks to determine the mean and volatility parameters of the Geometric Brownian Motion (GBM) model for stock indexes to see trends and patterns in the ASEAN-5 stock market from 2017 to 2022. Once these parameters are determined, they are used in the GBM model to forecast the stock market indexes. Consequently, this research intends to highlight the value of incorporating GBM into stock indexes and assist investors in making short-term price predictions. The geometric Brownian motion involving randomness, volatility, and drift that might aid investors in making sensible investment decisions will be elaborated on in this research.

A comprehensive analysis of magnetized Non-Newtonian nanofluids ' peristaltic mechanism for optimized fluid flow and heat transfer

Magnetized non-Newtonian models nowadays have attracted many researchers because it is an exciting field in the collaboration of material science, fluid dynamics, and applied physics. Their unique properties and adaptability render them invaluable across various technological and industrial applications, promising further innovations as research advances. This research unveils the intricate rheological and thermal behavior of magnetized non-Newtonian nanofluids undergoing peristaltic motion. The study aims to enhance engineering design techniques for optimal biophysiological performance by incorporating second-order slip, convective conditions, and temperature-dependent thermal conductivity. The Buongiorno nanofluid model is adopted to investigate heat and mass transfer phenomena, while the Prandtl non-Newtonian fluid model is employed to comprehend the complex rheological characteristics of the fluid. A long-wavelength approximation with a low Reynolds number was employed to simplify the governing equations. Analytical solutions have been obtained by solving the nonlinear transformed equations using the Homotopy perturbation technique. The findings are validated with previous literature and indicate that magnetic fields play a key role in controlling peristaltic flow behavior and nanofluid pumping rates. Moreover, the interplay between non-Newtonian rheology and nanofluid parameters significantly affects temperature distribution patterns. An increase in the species Biot number and thermophoresis parameter leads to improved concentration behavior. Conversely, a reversible trend is noted with the augmentation of the Prandtl number, Eckart number, variable thermal conductivity, and Brownian motion parameters. This research provides new insights into magnetohydrodynamic transport mechanisms in peristaltic systems. The modeling approach, coupled with analysis, lays the background for improved fluid circulation, oxygen delivery, waste removal, and nutrient transport in biomedical applications. Specifically, the findings are important for advancing the design of peristaltic pumps tailored for targeted drug delivery and optimizing fluid flow within gastrointestinal tracts.