Search results

Using a generalized translation operator, this study aims to obtain a generalization of Titchmarsh's theorem for the Laguerre–Bessel transform for functions satisfying the ψ-Laguerre–Bessel–Lipschitz condition in the space L²_α (K), where K=0,+∞×0,+∞[.

The author has employed the results developed by Titchmarsh, of reference number [1].

In this paper, an analogous of Titchmarsh's theorem is established for Laguerre–Bessel transform.

To the best of the authors’ findings, at the time of submission of this paper, the results reported are new and interesting.

In this paper, the authors prove that the Douglas space of second kind with a generalised form of special (α, β)-metric F, is conformally invariant.

For, the authors have used the notion of conformal transformation and Douglas space.

The authors found some results to show that the Douglas space of second kind with certain (α, β)-metrics such as Randers metric, first approximate Matsumoto metric along with some special (α, β)-metrics, is invariant under a conformal change.

The authors introduced Douglas space of second kind and established conditions under which it can be transformed to a Douglas space of second kind.

Capacitive six-axis force/torque (F/T) sensors require various configurations to fulfill diverse performance requirements; however, a systematic method to assess the feasibility of any new configuration is lacking. This study aims to propose three criteria for evaluating the rationality of these configurations, enabling a quick determination of the feasibility of the initial structure of the sensor.

This study used sensitivity isotropy as a performance metric. By examining the signal conversion process from F/T to displacement using the compliance transformation matrix, the authors identified Criterion 1: the symmetry condition. By analyzing the decoupling process of the sensor, the authors discovered Criterion 2: the capacitor arrangement condition. Through the optimization of analog sensors, this study derived Criterion 3: the range and structural parameters conditions. Ultimately, this study designed and fabricated a sensor that fulfills these criteria, thereby demonstrating the feasibility of the approach through its performance.

By analogy with capacitive six-axis F/T sensors that have demonstrated exceptional performance in recent years, the authors have found that they all meet the criteria proposed in this paper. Furthermore, the sensor designed and fabricated in this study achieves an accuracy of 0.64% FS, surpassing both the accuracy and sensitivity of the commercially available high-performance ATI industrial automation (Gamma) sensor. This underscores the feasibility of this study’s criteria.

By following the configuration guidelines presented in this paper, designers can quickly assess whether a new configuration will perform well at the early stages of the design process. This makes it easier to consider other requirements while meeting the basic performance needs, thereby significantly enhancing design efficiency.

Developing countries are characterized by gender wage inequality that can be largely attributed to gender-based disparities in education. Education subsidy can be an effective tool for reducing the inequality in human capital formation. However, the parents’ decision in response to the subsidy is a crucial determinant of gendered inequality in schooling and earnings. The paper aims to examine the effects of gender-neutral and gender-specific education subsidy policies on the gendered differences in schooling and earnings.

A three-sector full employment general equilibrium model is developed, where the amount of schooling of children is determined by the intertemporal utility maximizing behaviour of the parents over two periods.

The results indicate that higher gender-neutral education subsidy may raise the amount of schooling of boys more than girls and aggravate the schooling inequality in a society with traditional gender norms; the effect on earning inequality depends on the relative gendered returns to education and the marginal effects of the subsidy on relative schooling levels. However, gender-specific subsidy policies raise female schooling, thereby narrowing gender-based schooling and are likely to favourably affect the earning inequality.

The paper tries to analyse the linkage between education and labour market within a gender dimension. On the one hand, it tries to explain parental schooling decision due to gender-neutral and gender-specific education subsidies, and on the other, it examines the effects of these two subsidy policies on gendered schooling inequality and gender earnings inequality in a dynamic model.

This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point. Key considerations include the presence of Ohmic dissipation, linear thermal radiation, second-order chemical reaction with the multiple slips. With these factors, this study aims to provide insights for practical applications where thermal management and energy efficiency are paramount.

Lie group transformation is used to revert the leading partial differential equations into nonlinear ODE form. Hence, the solutions are attained analytically through differential transformation method-Padé and numerically using the Runge–Kutta–Fehlberg method with shooting procedure, to ensure the precise and reliable determination of the solution. This dual approach highlights the robustness and versatility of the methods.

The system’s entropy generation is enhanced by incrementing the magnetic field parameter (M), while the electric field (E) and velocity slip parameters (ξ) control its growth. Mass transportation irreversibility and the Bejan number (Be) are significantly increased by the chemical reaction rate (C_r). In addition, there is a boost in the rate of heat transportation by 3.66% while 0.05⩽ξ⩽0.2; meanwhile for 0.2⩽ξ⩽1.1, the rate of mass transportation gets enhanced by 12.87%.

This paper presents a novel approach to analyzing the entropy optimization in a radiative, chemically reactive EMHD nanofluid flow near a stagnation point. Moreover, this research represents a significant advancement in the application of analytical techniques, complemented by numerical approaches to study boundary layer equations.

The paper aims to study the constraint solutions of the periodic coupled operator matrix equations by the biconjugate residual algorithm. The new algorithm can solve a lot of constraint solutions including Hamiltonian solutions and symmetric solutions, as special cases. At the end of this paper, the new algorithm is applied to the pole assignment problem.

When the studied periodic coupled operator matrix equations are consistent, it is proved that constraint solutions can converge to exact solutions. It is demonstrated that the solutions of the equations can be obtained by the new algorithm with any arbitrary initial matrices without rounding error in a finite number of iterative steps. In addition, the least norm-constrained solutions can also be calculated by selecting any initial matrices when the equations of the periodic coupled operator matrix are inconsistent.

Numerical examples show that compared with some existing algorithms, the proposed method has higher convergence efficiency because less data are used in each iteration and the data is sufficient to complete an update. It not only has the best convergence accuracy but also requires the least running time for iteration, which greatly saves memory space.

Compared with previous algorithms, the main feature of this algorithm is that it can synthesize these equations together to get a coupled operator matrix equation. Although the equation of this paper contains multiple submatrix equations, the algorithm in this paper only needs to use the information of one submatrix equation in the equation of this paper in each iteration so that different constraint solutions of different (coupled) matrix equations can be studied for this class of equations. However, previous articles need to iterate on a specific constraint solution of a matrix equation separately.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

This study aims to optimize heat transfer efficiency and minimize friction factor and entropy generation in hybrid nanofluid flows through porous media. By incorporating factors such as melting effect, buoyancy, viscous dissipation and no-slip velocity on a stretchable surface, the aim is to enhance overall performance. Additionally, sensitivity analysis using response surface methodology is used to evaluate the influence of key parameters on response functions.

After deriving suitable Lie-group transformations, the modeled equations are solved numerically using the “spectral local linearization method.” This approach is validated through rigorous numerical comparisons and error estimations, demonstrating strong alignment with prior studies.

The findings reveal that higher Darcy numbers and melting parameters are associated with decreased entropy (35.86% and 35.93%, respectively) and shear stress, increased heat transmission (16.4% and 30.41%, respectively) in hybrid nanofluids. Moreover, response surface methodology uses key factors, concerning the Nusselt number and shear stress as response variables in a quadratic model. Notably, the model exhibits exceptional accuracy with $R^2$ values of 99.99% for the Nusselt number and 100.00% for skin friction. Additionally, optimization results demonstrate a notable sensitivity to the key parameters.

Lubrication is a vital method to minimize friction and wear in the automobile sector, contributing significantly to energy efficiency, environmental conservation and carbon reduction. The incorporation of nickel and manganese zinc ferrites into SAE 20 W-40 motor oil lubricants, as defined by the Society of Automotive Engineers, significantly improves their performance, particularly in terms of tribological attributes.

This work stands out for its focus on applications such as hybrid electromagnetic fuel cells and nano-magnetic material processing. While these applications are gaining interest, there is still a research gap regarding the effects of melting on heat transfer in a NiZnFe_2O_4-MnZnFe_2O_4/20W40 motor oil hybrid nanofluid over a stretchable surface, necessitating a thorough investigation that includes both numerical simulations and statistical analysis.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

The sustainable development of the platform economy has been hindered by the absence and alienation of platform corporate social responsibility. Previous studies have mainly focused on the contents and governance models for platform corporate social responsibility. This study seeks to explore which strategy participants choose in the governance of platform corporate social responsibility and their influencing factors.

Using a platform ecosystem approach, a quadrilateral evolutionary game model was developed, and the stabilities of subjects’ behavioral strategies and their combinations in various scenarios were analyzed. Additionally, the effects of key parameters on the system’s evolutionary path were simulated.

The ideal steady state system is achieved when platform enterprises, complementors and consumers adopt positive strategies while the government adopts lax regulation. Moreover, the evolutionary strategies of the subjects are influenced by several factors, including the participation costs of governance, the rewards and punishments imposed by platform enterprises, as well as the reputational losses of platform enterprises and complementors due to media coverage.

This study offers insights into improving the governance effectiveness of platform corporate social responsibility for managers and practitioners.

This study contributes to existing literature by considering the rational orientation of platform ecosystem members and revealing the interaction mechanisms among members. Furthermore, this study combines collective action theory and reputation theory to clarify the influencing factors on members’ behaviors.