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The purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane.

To achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer.

The finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique.

This paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced.

Although extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

The authors examined how employee led exchange benefits the organizations. Specifically, the authors aim at investigating the mediating role of family supportive supervision between employee performance and taking charge behavior. The authors further examined leader-member exchange (LMX) as a boundary condition between employee performance and family supportive supervision.

The authors collected data from 295 employees and their supervisors working in various public sector organizations of Pakistan on a convenience basis. Specifically, data on family supportive supervision and LMX was collected from employees; whereas, data on employee performance and taking charge was collected from their supervisors between June–September 2021.

The statistical analysis reveals that high-performing employees are reciprocated by the high family-supportive supervision which increases their work-life balance and they further reciprocate by showing a propensity to take charge. In addition, LMX is noted to strengthen the association between employees' performance and family supportive supervision.

This study explains how managers can extend the stream of employees' performance by highlighting the role of family-supportive supervision and LMX. The managers through high LMX and provision of family-supportive supervision can boost the employees' outcomes from job performance to extra-role performance (i.e. taking charge).

This study adds value to the existing body of knowledge by considering performance as a predictor of various organizational-level consequences. Recent studies have considered the negative consequences of employees' performance, while the positive aspect has been called for an investigation.

In this digital age, the rapid technological innovation and adoption, with the increasing use of big data analytics, has raised concerns about the ability of small and medium enterprises (SMEs) to sustain the competition and innovation performance (IP). To narrow the research gap, this paper investigates the role of big data analytics capability (BDAC) in moderating the relationship between digital innovation (DI) and SME innovation performance.

This research has been carried forward through a detailed theory and literature analysis. Data were analyzed through confirmatory factor analysis and structural equation models using a two-stage approach in smartPLS-4.

Results highlight that digital service capability (DSC) significantly mediates the relationship between DI and IP. Additionally, value co-creation (VCC) directly affects digital transformation (DT), while DI has a stronger effect on DSC than IP. Furthermore, BDAC significantly moderates the relation between DSC → IP and DT → IP, whereas it has a detrimental effect on the relation between DI and IP. In addition to that, VCC, DSC, DT, DI and BDAC have a direct, significant and positive effect on IP.

This research was motivated by the practical relevance of supporting SMEs in adopting DT and the resource-based view (RBV) and technology acceptance model (TAM). This study shows that all direct and indirect measures significantly affect innovation performance, including BDAC as moderator. These findings refresh the perspective on what DT, DI, VCC, DSC and BDAC can bring to a firm's innovation performance.

This paper has contributed to DT by empirically validating a theoretical argument that suggests the acceptance and adoption of new technology. This paper aims to fill theoretical gaps in understanding BDAC and DT by incorporating the RBV and TAM theories on BDAC and DT.

This study aims to focus on second grade fluid flow over a rotating disk in the presence of chemical reaction. Uniform magnetic field is also taken into account. Because of the smaller magnetic Reynolds number, induced magnetic field is negligible. Heat equation is constructed by considering heat source/sink.

Suitable variables are used to transform nonlinear partial differential equations to ordinary ones. Convergent series solutions are attained by applying homotopy analysis method.

Trends of different parameters on concentration, velocity and temperature are shown graphically. Skin friction coefficient and local Nusselt number are calculated and investigated under the effect of elaborated parameters. An elevation in the value of magnetic field parameter causes collapse in the velocity distributions. Velocity distribution in increasing function of viscoelastic parameter. Temperature and concentration profiles are decreasing functions of viscoelastic parameter. Concentration distribution reduces by increasing the chemical reaction parameter. There is more surface drag force for larger M, while opposite behavior is noted for β.

To the best of the authors’ knowledge, such consideration is yet to be published in the literature.

Nonlinear mixed-convective entropy optimized the flow of hyperbolic-tangent nanofluid (HTN) with magnetohydrodynamics (MHD) process is considered over a vertical slendering surface. The impression of activation energy is incorporated in the modeling with the significance of nonlinear radiation, dissipative-function, heat generation/consumption connection and Joule heating. Research in this area has practical applications in the design of efficient heat exchangers, thermal management systems or nanomaterial-based devices.

Suitable set of variables is introduced to transform the PDEs (Partial differential equations) system into required ODEs (Ordinary differential equations) system. The transformed ODEs system is then solved numerically via finite difference method. Graphical artworks are made to predict the control of applicable transport parameters on surface entropy, Bejan number, Sherwood number, skin-friction, Nusselt number, temperature, velocity and concentration fields.

It is noticed from present numerical examination that Bejan number aggravates for improved estimations of concentration-difference parameter a_2, Eckert number E_c, thermal ratio parameter ?_w and radiation parameter R_d, whereas surface entropy condenses for flow performance index n, temperature-difference parameter a_1, thermodiffusion parameter N_t and mixed convection parameter ?. Sherwood number is enriched with the amplification of pedesis-motion parameter N_b, while opposite development is perceived for thermodiffusion parameter. Lastly, outcomes are matched with formerly published data to authenticate the present numerical investigation.

To the best of the authors' knowledge, no investigation has been reported yet that explains the entropic behavior with activation energy in the flowing of hyperbolic-tangent mixed-convective nanomaterial due to a vertical slendering surface.

The knowledge management (KM) sharing process plays an essential role in manufacturing under Green Implementation Network (GIN). This study aims to analyze the KM process of adopting a GIN to determine the relative importance of technical risk minimization. The proposed conceptual model was tested by considering two interrelated concepts (GIN and KM process).

Primary data from manufacturing companies in Henan province, China, were collected through 276 questionnaires. PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA) were applied to investigate the configurational path of minimizing the technical risk in the manufacturing process.

The findings showed that the GIN and KM processes minimize the technical risk. The fsQCA reported multiple configurational of GIN and KM processes validated toward technical risk reduction. The study's findings contribute to the existing body of knowledge on technical risk reduction in manufacturing concerns by investigating the complex intersection between GIN and KM process.

This research adds to current GIN and KM literature by focusing on the green process using a resource-based view (RBV) and socio-technical theories. The current study provides practical and theoretical justification for explaining the relationship between GIN and KM processes. Moreover, this study adds to the literature by providing evidence that KM is an essential manufacturing industry enabler in minimizing technical risk.

This study aims to investigate the effectiveness of two types of social media videos used for destination image development: induced/commercial-oriented content and organic content (where content is made without commercial interest, such as vlogs classified as user-generated content).

Experimental research using “Emotive EEG” (electroencephalogram) in a controlled environment was conducted with 30 participants (20 males, 10 females), age range 18 to 26. Emotive EEG recording was performed while the participants watched both types of video clips. Test results for both groups indicate that induced content is preferred over organic content.

This study opens up future research avenues where neuromarketing’s “Marketer Friendly” EEG equipment can be applied to the customer selection process.

Marketing analysts can gauge the interest and response of customers on different types of social media video content for destination marketing based on the findings of this study.

In the era of knowledge economy, the significance of intellectual capital has been increasing globally. Similarly, recent studies have focused on the importance of green intellectual capital in mitigating environmental degradation. However, only a few studies have analysed green intellectual capital and its impacts in the specific case of Pakistan. Hence, this study aims to investigate the effects of green intellectual capital on green innovation adoption in Pakistan’s manufacturing small and medium-size enterprises (SMEs).

We used a data sample of 235 SMEs, gathered from the four manufacturing sectors of Pakistan including: textile, chemical, pharmaceutical and steel and analysed using a multiple regression analysis approach.

The empirical results of this research indicate that green human capital and green structural capital significantly increase green innovation adoption. However, it must be noted that green relational capital has a positive but insignificant impact on green innovation adoption in manufacturing SMEs in Pakistan.

The findings and recommended policy measures of this study are important for the managers of manufacturing SMEs and policymakers to mitigate environmental destruction and achieve sustainable development through green intellectual capital.

The purpose of this study is to analyze the transportation of heat and mass in three-dimensional (3D) shear rate-dependent viscous fluid. Thermal enhancement plays a significant role in industrial and engineering applications. For this, the authors dispersed trihybrid nanoparticles into the fluid to enhance the working fluid’s thermal enhancement.

The finite element method is a numerical scheme and is powerful in achieving convergent and grid-independent solutions compared with other numerical techniques. This method was initially assigned to structural problems. However, it is equally successful for computational fluid dynamics problems.

Wall shear stress has shown an increasing behavior as the intensity of the magnetic field is increased. Simulations have predicted that Ohmic heat in the case of trihybrid nanofluid (MoS₂–Al₂O₃–Cu/C₂H₆O₂) has the greatest value in comparison with mono and hybrid nanofluids. The most significant influence of chemical reaction on the concentration in tri-nanofluid is noted. This observation is pointed out for both types of chemical reaction (destructive or generative) parameters.

Through a literature survey, the authors analyzed that no one has yet to work on a 3D magnetohydrodynamics Carreau–Yasuda trihybrid nanofluid over a stretched sheet for improving heat and mass transfer over hybrid nanofluids. Herein, molybdenum disulfide (MoS₂), aluminum oxide (Al₂O₃) and copper (Cu) nanoparticles are mixed in ethylene glycol (C₂H₆O₂) to study the thermal enhancement and mass transport of their corresponding resultant mono (Cu/C₂H₆O₂), hybrid (Al₂O₃–Cu/C₂H₆O₂) and trihybrid (MoS₂–Al₂O₃–Cu/C₂H₆O₂) nanofluids.