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This study aims to evaluate blockchain as an e-government governance model. It assesses its alignment with legal frameworks, emphasizing robustness against disruptions and adherence to existing laws.

The paper explores blockchain’s potential in e-government, focusing on legal, ethical and governance aspects. It conducts an in-depth analysis of blockchain’s integration into data governance, emphasizing legal compliance and resilient security protocols.

The study comprehensively evaluates blockchain’s implementation, covering privacy, interoperability, consensus mechanisms, scalability and regulatory alignment. It highlights governance’s critical role in ensuring legal compliance within blockchain paradigms.

Ethical and legal concerns arising from blockchain adoption remain unresolved. The study underscores how blockchain challenges its core principles of anonymity and decentralization in e-government settings.

The framework outlined offers potential for diverse technological environments, albeit raising ethical and legal queries. It emphasizes governance’s pivotal role in achieving legal compliance in blockchain adoption.

Blockchain’s impact on legal and ethical facets necessitates further exploration to align with its core principles while addressing governance in e-government settings.

This study presents a robust framework for assessing blockchain’s viability in e-government, emphasizing legal compliance, despite ethical and legal intricacies that challenge its fundamental principles.

Entropy generation in nanofluids with peristaltic scheme occupies a primary consideration in the sense of its application in clinical, as well as the industrial field in terms of improved thermal conductivity of the original fluid. Three-dimensional cylindrical configurations are the most realistic and commonly used geometries which incorporate most of the experimental equipment. In the current study, three-dimensional cylindrical enclosures have been assumed to receive the results of entropy generation occurring due to viscous dissipation, heat transfer of nanofluid and mass concentration of nanoparticles through peristaltic pumping. Applications of the study can be found in peristaltic micro-pumps and novel drug delivery mechanism in pharmacological engineering.

The equations of interest have been structured under physical constraints of lubrication theory and dimensionless strategy. Finalized relations involve highly complicated partial differential equations whose solutions are tabulated through some perturbation procedure and expression of pressure rise is manipulated by a numerical technique through built-in command NIntegrate on Mathematical tool “Mathematica.”

It is evaluated that entropy production goes linear with the greater magnitudes of Brownian motion but inverse characteristics have been sorted against thermophoresis factor.

To the best of authors’ knowledge, this study does not exist in literature yet and it contains a new innovative idea.

The purpose of this paper is to fabricate and investigate sensing properties of a novel, flexible resistive tensile load cells based on multi-walled carbon nano-tubes (MWCNTs)/rubber composites. The use of carbon nanotubes makes it very attractive for being used as sensors.

On thin rubber substrate, MWCNTs powder was deposited and pressed at elevated temperature. Two types of samples were prepared: first sample was made by depositing MWCNTs suspension in water on the substrate, then the sample was dried at room temperature; the second sample was prepared by applying dry MWCNTs powder directly on the substrate.

The resistances of the cells made from wet MWCNT powder are much lower than those made with dry powder. It was found that the fabricated load cells were highly sensitive to the force and showed good repeatability. The resistance of the flexible resistive tensile MWCNTs/rubber composite load cells increased 1.37 times, on average, with the increasing force (up to 0.045 N). The sensitivity of the cells was equal to 142 N-1.

The device fabrication method used here provides a simple, less expensive and effective approach for preparing resistive tensile load cells.

A novel, flexible resistive tensile load cells using MWCNTs/rubber composites have been successfully fabricated and investigated. MWCNTs, in dry and wet form, have been deposited on thin rubber substrates by adopting a very simple and inexpensive technique.

This study aims to present a unique hybrid metaheuristic approach to solving the nonlinear analysis of hall currents and electric double layer (EDL) effects in multiphase wavy flow by merging the firefly algorithm (FA) and the water cycle algorithm (WCA).

Nonlinear Hall currents and EDL effects in multiphase wavy flow are originally described by partial differential equations, which are then translated into an ordinary differential equation model. The hybrid FA-WCA technique is used to take on the optimization challenge and find the best possible design weights for artificial neural networks. The fitness function is efficiently optimized by this hybrid approach, allowing the optimal design weights to be determined.

The proposed strategy is shown to be effective by taking into account multiple variables to arrive at a single answer. The numerical results obtained from the proposed method exhibit good agreement with the reference solution within finite intervals, showcasing the accuracy of the approach used in this study. Furthermore, a comparison is made between the presented results and the reference numerical solutions of the Hall Currents and electroosmotic effects in multiphase wavy flow problem.

This comparative analysis includes various performance indices, providing a statistical assessment of the precision, efficiency and reliability of the proposed approach. Moreover, to the best of the authors’ knowledge, this is a new work which has not been explored in existing literature and will add new directions to the field of fluid flows to predict most accurate results.

This study aims to explore the evolving field of physics-informed neural networks (PINNs) through an analysis of 996 records retrieved from the Web of Science (WoS) database from 2019 to 2022.

WoS database was analyzed for PINNs using an inhouse python code. The author’s collaborations, most contributing institutes, countries and journals were identified. The trends and application categories were also analyzed.

The papers were classified into seven key domains: Fluid Dynamics and computational fluid dynamics (CFD); Mechanics and Material Science; Electromagnetism and Wave Propagation; Biomedical Engineering and Biophysics; Quantum Mechanics and Physics; Renewable Energy and Power Systems; and Astrophysics and Cosmology. Fluid Dynamics and CFD emerged as the primary focus, accounting for 69.3% of total publications and witnessing exponential growth from 22 papers in 2019 to 366 in 2022. Mechanics and Material Science followed, with an impressive growth trajectory from 3 to 65 papers within the same period. The study also underscored the rising interest in PINNs across diverse fields such as Biomedical Engineering and Biophysics, and Renewable Energy and Power Systems. Furthermore, the focus of the most active countries within each application category was examined, revealing, for instance, the USA’s significant contribution to Fluid Dynamics and CFD with 319 papers and to Mechanics and Material Science with 66 papers.

This analysis illuminates the rapidly expanding role of PINNs in tackling complex scientific problems and highlights its potential for future research across diverse domains.

This paper aims to examine the impact of various economic, social and environmental issues on the sustainable development of Pakistan, both directly and indirectly through the sustainability dimensions of China–Pakistan Economic Corridor (CPEC), a multi-billion-dollar megaproject.

Using a quantitative (deductive) methodological approach, data were collected using a strategy of an online questionnaire survey from diverse stakeholders of CPEC in Pakistan. Partial least squares-based structural equation modeling technique was used to test the relationship between observed and latent variables.

The results confirmed the positive impact of various economic, social and environmental issues on the sustainable development of Pakistan directly and indirectly through the partial mediation of sustainability dimensions of CPEC.

Sustainability perceptions of stakeholders about CPEC and its relationship with sustainable development are critical issues for governments and policymakers. This paper suggest how economic, social and environmental dimensions of CPEC can enhance the positive perception which is necessary for stakeholder involvement and support for megaprojects such as CPEC.

This study evaluated the megaprojects of CPEC from a sustainability perspective through stakeholders’ perceptions by proposing and testing a parsimonious research model that has never been examined in the existing literature.

This study aims to model the important flow response quantities over a shrinking wedge with the help of response surface methodology (RSM) and an artificial neural network (ANN). An ANN simulation for optimal thermal transport of incompressible viscous fluid under the impact of the magnetic effect (MHD) over a shrinking wedge with sensitivity analysis and optimization with RSM has yet not been investigated. This effort is devoted to filling the gap in existing literature.

A statistical experimental design is a setup with RSM using a central composite design (CCD). This setup involves the combination of values of input parameters such as porosity, shrinking and magnetic effect. The responses of skin friction coefficient and Nusselt number are required against each parameter combination of the experimental design, which is computed by solving the simplified form of the governing equations using bvp4c (a built-in technique in MATLAB). An empirical model for Cf_x and Nu_x using RSM and ANN adopting the Levenberg–Marquardt algorithm based on trained neural networks (LMA-TNN) is attained. The empirical model for skin friction coefficient and Nusselt number using RSM has 99.96% and 99.99% coefficients of determination, respectively.

The values of these matrices show the goodness of fit for these quantities. The authors compared the results obtained from bvp4c, RSM and ANN and found them all to be in good agreement. A sensitivity analysis is performed, which shows that Cf_x as well as Nu_x are most affected by porosity. However, they are least affected by magnetic parameters.

This study aims to simulate ANN and sensitivity analysis for optimal thermal transport of magnetic viscous fluid over shrinking wedge.

This study aims to test the Kuznets curve between economic growth and child labor, along with the influence of exports, household size and rural population in the context of Pakistan.

To achieve the research objective, this study applied the unit root test, bound co-integration test, and autoregressive distributive lags (ARDL) method for the period of 1972–2021.

The findings show an inverted U-shaped relationship between economic growth and child labor indicating that at the beginning stage of economic development, child labor increases due to lower per capita household and subsequently, in the long-run of economic development, child labor decreases due to the higher per capita households. Moreover, the results also show that exports, household size and rural population have a positive influence on increasing child labor.

The policymakers and government of Pakistan need to focus on long-term economic growth policies, ensure free quality education and cheap equipment which practices minimum manpower to reduce the threat of child labor.

Having long-run economic growth, the government of Pakistan need to equally benefit the households and the poor population to reduce child labor and enhance the social welfare of society.

To the best of the authors’ knowledge, this is the first study that investigates the Kuznets curve relationship between economic growth and child labor in the context of Pakistan. Moreover, this study contributes to the reduction in child labor through long-term economic growth in the context of Pakistan.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0387

The coronavirus disease 2019 (COVID-19) epidemic has given an upsurge to online retailing in Pakistan. This shift has escalated the issues about privacy concerns among consumers. Keeping in view the growing concerns, the objective of this study is to investigate customer patronage in online shopping and the role of privacy concerns in this relationship.

To generalize the relationship between antecedents and outcomes of privacy concerns, a cross-disciplinary macro model was used. Data were collected through a survey method from the consumers who used credit and debit cards during online shopping.

Results show that government regulations have a significant positive relationship with privacy concerns and customer patronage. Privacy concerns are found to have a significant negative relationship with organizational ethical care while customer patronage was found to have a significant positive relationship with organizational ethical care. Customer patronage was also found to have a significant negative relationship with privacy concerns. Privacy concerns mediated the relationship between government regulations and customer patronage, whereas privacy concerns does not mediate the relationship between organizational ethical care and customer patronage.

The research adds to the existing literature and highlights the customer behavior toward online shopping/e-commerce in developing economies. The research gives a direction to stakeholders to counter privacy concerns and ensure safer e-commerce practices.

This paper aims to deal with the heat transmission of Sutterby fluid-containing gyrotactic microorganism by incorporating non-Darcy resistance law. The mathematical modeling is based on nanoparticle concentration, energy, momentum and motile microorganism equations.

The governing nonlinear coupled equations are first rendered into nonlinear ordinary equations using appropriate transformation and are then solved analytically by using the optimal homotopy.

Graphical illustration of results depict the behavior of flow involved physical parameters on temperature, gyrotactic microorganism, concentration and velocity. Additionally, local Nusselt number and skin friction coefficient are computed numerically and validated through comparison with existing literature as a special case of proposed model. It is found that the temperature profile decreases by increasing values of Brownian-motion parameter and Prandtl number. An increase in thermophoresis parameter and Schmidt number results in decrease in concentration of nanoparticles. Bioconvection Peclet number corresponds to decreasing behavior of nondimensional gyrotactic microorganism field is observed. Finally, a comparison with the existing literature is made, and an excellent agreement is seen.

To the best of the authors’ knowledge, this study is reported for the first time.