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This paper aims to examine the Dufour and Soret combined effects on the study of two-dimensional squeezed flow of copper water nanofluid between parallel plates along with applied (external) magnetic field. Impact of higher order chemical reaction is also considered.

The nonlinear partial differential equations (PDEs) are changed into system of ordinary differential equations (ODEs) by employing suitable similarity transformations. These transformed ODEs are then solved by means of a semianalytical method called differential transform method (DTM). Effects of several changing physical parameters on fluid flow, temperature and concentration have been deliberated through graphs.

It is observed that Dufour and Soret numbers are directly related to temperature profile and a reverse trend was observed in the concentration profile. Temperature enhancement is perceived for the enhanced Dufour number. Enhancement in Dufour number shows a direct association with Sh and Nu for all values of squeezing parameter.

The combined Dufour and Soret effects are used in separation of isotopes in mixture of gases, oil reservoirs and binary alloys solidification. The squeeze nanoliquid flow can be used in the field of composite material joining, rheological testing and welding engineering.

This study is mainly useful for geosciences and chemical engineering.

The uniqueness in this research is the study of the impact of cross diffusion on chemically reacting squeezed nanoliquid flow with the chemical reaction order more than one in the presence of applied magnetic force using a semianalytical procedure, named DTM.

This study aims to investigate numerically the impact of the three-dimensional convective nanoliquid flow on a rotating frame embedded in the non-Darcy porous medium in the presence of activation energy. The cross-diffusion effects, i.e. Soret and Dufour effects, and heat generation are included in the study. The convective heating condition is applied on the bounding surface.

The control model consisted of a system of partial differential equations (PDE) with boundary constraints. Using suitable similarity transformation, the PDE transformed into an ordinary differential equation and solved numerically by the Runge–Kutta–Fehlberg method. The obtained results of velocity, temperature and solute concentration characteristics plotted to show the impact of the pertinent parameters. The heat and mass transfer rate and skin friction are also calculated.

It is found that both Biot numbers enhance the heat and mass distribution inside the boundary layer region. The temperature increases by increasing the Dufour number, while concentration decreases by increasing the Dufour number. The heat transfer is increased up to 8.1% in the presence of activation energy parameter (E). But, mass transfer rate declines up to 16.6% in the presence of E.

The applications of combined Dufour and Soret effects are in separation of isotopes in mixture of gases, oil reservoirs and binary alloys solidification. The nanofluid with porous medium can be used in chemical engineering, heat exchangers and nuclear reactor.

This study is mainly useful for thermal sciences and chemical engineering.

The uniqueness in this research is the study of the impact of activation energy and cross-diffusion on rotating nanoliquid flow with heat generation and convective heating condition. The obtained results are unique and valuable, and it can be used in various fields of science and technology.

In order to explore a new estimation approach of hyperspectral estimation, this paper aims to establish a hyperspectral estimation model of soil organic matter content with the principal gradient grey information based on the grey information theory.

Firstly, the estimation factors are selected by transforming the spectral data. The eigenvalue matrix of the modelling samples is converted into grey information matrix by using the method of increasing information and taking large, and the principal gradient grey information of modelling samples is calculated by using the method of pro-information interpolation and straight-line interpolation, respectively, and the hyperspectral estimation model of soil organic matter content is established. Then, the positive and inverse grey relational degree are used to identify the principal gradient information quantity of the test samples corresponding to the known patterns, and the cubic polynomial method is used to optimize the principal gradient information quantity for improving estimation accuracy. Finally, the established model is used to estimate the soil organic matter content of Zhangqiu and Jiyang District of Jinan City, Shandong Province.

The results show that the model has the higher estimation accuracy, among the average relative error of 23 test samples is 5.7524%, and the determination coefficient is 0.9002. Compared with the commonly used methods such as multiple linear regression, support vector machine and BP neural network, the hyperspectral estimation accuracy of soil organic matter content is significantly improved. The application example shows that the estimation model proposed in this paper is feasible and effective.

The estimation model in this paper not only fully excavates and utilizes the internal grey information of known samples with “insufficient and incomplete information”, but also effectively overcomes the randomness and grey uncertainty in the spectral estimation. The research results not only enrich the grey system theory and methods, but also provide a new approach for hyperspectral estimation of soil properties such as soil organic matter content, water content and so on.

The paper succeeds in realizing both a new hyperspectral estimation model of soil organic matter content based on the principal gradient grey information and effectively dealing with the randomness and grey uncertainty in spectral estimation.

This study explores the immobilisation of enzymes within porous catalysts of various geometries, including spheres, cylinders and flat pellets. The objective is to understand the irreversible Michaelis-Menten kinetic process within immobilised enzymes through advanced mathematical modelling.

Mathematical models were developed based on reaction-diffusion equations incorporating nonlinear variables associated with Michaelis-Menten kinetics. This research introduces fractional derivatives to investigate enzyme reaction kinetics, addressing a significant gap in the existing literature. A novel approximation method, based on the independent polynomials of the complete bipartite graph, is employed to explore solutions for substrate concentration and effectiveness factor across a spectrum of parameter values. The analytical solutions generated through the bipartite polynomial approximation method (BPAM) are rigorously tested against established methods, including the Bernoulli wavelet method (BWM), Taylor series method (TSM), Adomian decomposition method (ADM) and fourth-order Runge-Kutta method (RKM).

The study identifies two main findings. Firstly, the behaviour of dimensionless substrate concentration with distance is analysed for planar, cylindrical and spherical catalysts using both integer and fractional order Michaelis-Menten modelling. Secondly, the research investigates the variability of the dimensionless effectiveness factor with the Thiele modulus.

The study primarily focuses on mathematical modelling and theoretical analysis, with limited experimental validation. Future research should involve more extensive experimental verification to corroborate the findings. Additionally, the study assumes ideal conditions and uniform catalyst properties, which may not fully reflect real-world complexities. Incorporating factors such as mass transfer limitations, non-uniform catalyst structures and enzyme deactivation kinetics could enhance the model’s accuracy and broaden its applicability. Furthermore, extending the analysis to include multi-enzyme systems and complex reaction networks would provide a more comprehensive understanding of biocatalytic processes.

The validated bipartite polynomial approximation method presents a practical tool for optimizing enzyme reactor design and operation in industrial settings. By accurately predicting substrate concentration and effectiveness factor, this approach enables efficient utilization of immobilised enzymes within porous catalysts. Implementation of these findings can lead to enhanced process efficiency, reduced operating costs and improved product yields in various biocatalytic applications such as pharmaceuticals, food processing and biofuel production. Additionally, this research fosters innovation in enzyme immobilisation techniques, offering practical insights for engineers and researchers striving to develop sustainable and economically viable bioprocesses.

The advancement of enzyme immobilisation techniques holds promise for addressing societal challenges such as sustainable production, environmental protection and healthcare. By enabling more efficient biocatalytic processes, this research contributes to reducing industrial waste, minimizing energy consumption and enhancing access to pharmaceuticals and bio-based products. Moreover, the development of eco-friendly manufacturing practices through biocatalysis aligns with global efforts towards sustainability and mitigating climate change. The widespread adoption of these technologies can foster a more environmentally conscious society while stimulating economic growth and innovation in biotechnology and related industries.

This study offers a pioneering approximation method using the independent polynomials of the complete bipartite graph to investigate enzyme reaction kinetics. The comprehensive validation of this method through comparison with established solution techniques ensures its reliability and accuracy. The findings hold promise for advancing the field of biocatalysts and provide valuable insights for designing efficient enzyme reactors.

The purpose of this study is to reduce the residual stress in welded workpieces, optimize the vibratory stress relief treatment process through the use of a vibration generator and enhance the durability and longevity of the workpiece by developing a vibratory stress relief robot that incorporates a multi-manipulator system.

The multi-manipulator combination work is designed so that each manipulator is deployed according to the requirements of vibration stress relief work. Each manipulator works independently and coordinates with others to achieve multi-dimensional vibratory stress relief of the workpiece. A two-degree-of-freedom mobile platform is designed to enable the transverse and longitudinal movement of the manipulator, expanding the working space of the robot. A small electromagnetic superharmonic vibration generator is designed to produce directional vibrations in any orientation. This design addresses the technical challenge of traditional vibration generators being bulky and unable to achieve directional vibrations.

The residual stress relief experiment demonstrates that the residual stress of the workpiece is reduced by approximately 73% through three-degree-of-freedom vibration. The multi-dimensional vibration effectively enhances the relief effect of residual stress, which is beneficial for improving the strength and service life of the workpiece.

A new multi-manipulator robot is proposed to alleviate the residual stress generated by workpiece welding by integrating vibratory stress relief with robotics. It is beneficial to reduce material and energy consumption while enhancing the strength and service life of the workpiece.

A finite element computational methodology on a curved boundary using an efficient subparametric point transformation is presented. The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions.

Our proposed method builds upon the domain discretization into linear, quadratic and cubic-order elements using subparametric spaces and such a discretization greatly reduces the computational complexity. A unique subparametric transformation for each triangle is derived from the unique parabolic arcs via a one-of-a-kind relationship between the nodal points.

The novel transformation derived in this paper is shown to increase the accuracy of the finite element approximation of the boundary value problem (BVP). Our overall strategy is shown to perform well for the BVP considered in this work. The accuracy of the finite element approximate solution increases with higher-order parabolic arcs.

The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions.

The purpose of this article is to present a mathematical model for the fully developed flow of Bi-viscous Bingham nanofluid through a uniform-width anisotropic porous channel. The model incorporates a generalized Brinkman-Darcy formulation for the porous layers while considering the motion of nanoparticles influenced by both Brownian diffusion and thermophoresis effects.

The similarity transformations derived through Lie group analysis are used to reduce the system from nonlinear partial differential equations to nonlinear ordinary differential equations. The finite difference method-based numerical routine bvp4c is employed to collect and graphically present the outcomes for velocity, temperature, and nanoparticle concentration profiles. The flow pattern is analyzed through streamlined plots. Furthermore, skin friction, heat, and mass transmission rates are investigated and presented via line plots.

It is observed that in anisotropic porous media, the temperature profile is stronger than in isotropic porous media. The thermal anisotropic parameter enhances the concentration profile while reducing the temperature.

Anisotropy arises in various industrial and natural systems due to factors such as preferred orientation or asymmetric geometry of fibers or grains. Hence, this study has applications in oil extraction processes, certain fibrous and biological materials, geological formations, and dendritic zones formed during the solidification of binary alloys.

1. The permeability and thermal conductivity are not constant; instead, they have different values in the x and y directions. 2. This study considers the dependency of thermophoresis on nanoparticle volume fraction and Brownian diffusion on the temperature in both the fluid flow equations and boundary conditions. 3. A novel similarity transformation is derived using Lie group analysis instead of using an existing transformation already available in the literature.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

For survival and prosperity, enterprises need to simultaneously engage in exploitation and exploration. Digital transformation is of great significance to enterprise innovation. However, the impacts of digital transformation on exploitation and exploration remain unclear. Moreover, the impacts of technological diversity on the relationships between digital transformation and exploitation and exploration are also unknown.

Based on an integrated perspective of dynamic capability theory and organizational inertia theory and using data from Chinese listed enterprises from 2007 to 2020, this study clarifies the effects of digital transformation on exploitation and exploration and assesses the moderating effect of technological diversity.

The results show that digital transformation improves exploitation, but negatively impacts exploration. Technological diversity mitigates the negative effect of digital transformation on exploration, but the moderating effect on the relationship between digital transformation and exploitation is not significant.

This study contributes to the existing literature on the digital paradox and provides guidance for enterprises to clarify the direction of digital transformation.

The literature review explores how multidisciplinary approaches based on critical pedagogy and participatory research can provide frameworks for equitable partnerships and genuine participation in educational design and research practices. Additionally, the essay aims to expand understandings of equitable engagement within educational research and design based on principles from critical pedagogy.

The essay draws from diverse literature in the learning sciences, health informatics, industrial design, disability studies, ethnic studies, rehabilitation science, and to a lesser extent HCI research to understand how critical pedagogy and participatory research methods can provide useful frameworks for disabled peoples' equitable engagement and genuine participation in educational research and design. The literature reviewed in the paper concern topics such as participatory approaches to community development with disabled adults, the implementation of university-initiated community partnerships, participatory research with students and disabled people, and the importance of culturally-responsive research practices. The design literature in this review explores various arenas such as the co-design of assistive technologies with disabled children and adults and the design of curricula for students with and without disabilities. This review focuses on research practices that engender disabled peoples' participation in educational research and design, with focus on developing multidisciplinary frameworks for such research.

The literature review concludes that participatory research methods and critical pedagogy provide useful frameworks for disabled peoples’ participation in educational design and research practices. Critical pedagogy and participatory design allow for the genuine participation of disabled people in the research process.

Emphases on collaboration and collective knowledge-building in social transformation are present in scholarship concerning critical pedagogy, participatory research, and disability studies. However, these connections have been routinely underexplored in the literature. This paper aims to underscore these integral connections as a means to build solidarity between disabled and other marginalized people.

The connections between participatory research methods, critical pedagogy, and disability studies have been previously underexplored. The literature review proposes a combined approach, which has the potential to radically transform multiple realms of research beyond the learning and information sciences.