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This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.

In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.

This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.

According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.

The COVID-19 pandemic has caused widespread disruptions to global industries, with the textile sector in South Asia being particularly hard hit. While previous studies have focused on the performance of textile sectors in individual countries, there is a gap in the literature on the comparative impact of the pandemic on the textile industry in South Asian nations. This study aims to fill this gap by investigating the performance of the textile sector in South Asian countries and identifying best practices for overcoming the pandemic’s adverse effects.

Using a comparative approach, this study analyzes the impact of COVID-19 on the performance of the textile sector in Pakistan, India and Bangladesh.

Our findings reveal that COVID-19 significantly negatively impacts the textile industry in Pakistan and India. However, Bangladesh has shown effective practices to support the textile industry and mitigate the pandemic’s adverse effects.

The findings of this study hold considerable implications for legislators, leaders, investors and supply chain management professionals operating within the South Asian textile sector. This research has the potential to inform policymakers in formulating strategies to facilitate the textile sector’s resilience during emergencies like the COVID-19 pandemic.

This paper provides significant theoretical additions to the current body of literature regarding the impact of COVID-19 on the textile sector in South Asia. The research uses the global value chain (GVC) theory as a theoretical framework to enhance understanding of the impact of global supply chains and interdependencies on the textile sector in the region.

This paper aims to explore the role of perceived organizational injustice (POI) leading to workplace conflict in determining organizational performance (OP) among healthcare employees. This paper also examines the serial mediating effects of moral disengagement (MD) and knowledge hiding (KH).

In all, 244 public and private hospital employees in Pakistan provided the data set.

According to partial least squares-structural equation modeling findings, the negative association between POI and OP was serially mediated by KH and MD. The recovery process underlying the linkage between POI and OP is tested and highlighted in this paper as a first step in unraveling it.

The findings highlight the significance of taking moral and KH models into account when attempting to understand the moral cognitive processes that employees go through when they see injustice. Organizations should guarantee the equitable distribution of incentives and resources, as distributive and procedural justices are concerned with organizations.

By directing actions meant to prevent MD and KH, the findings may potentially inspire new, more focused treatments to safeguard patient safety and avoid losses in the healthcare industry. One way to reduce unethical conduct and MD is to have people declare or agree to a code of ethics.

The halal cosmetics industry continues to grow significantly. Furthermore, using halal cosmetics is a must for Muslims. This study aims to analyze the factors influencing the switching intention to halal cosmetics in Indonesia.

This quantitative study uses a Partial Least Square-Structural Equation Modelling (PLS-SEM) on 214 respondents. The variables include halal certification, halal awareness, product image, perceived behavioral control, subjective norm, attitude, advertisement and switching intention.

The product image plays the most influential role in deriving the attitude toward switching intention to halal cosmetics, following perceived behavioral control, halal awareness and subjective norm, but not halal certification and advertisement. The result indicates that the image of halal cosmetics influences customers’ attitudes toward switching to using halal cosmetics. Indonesian customers know the obligation to use halal products because they are Muslim. However, the existence of halal certification does not derive the switching intention to halal cosmetics.

This study conducts research only in Indonesia. As a recommendation, further studies might conduct a comparative test using multicultural respondents in several countries. Other studies also suggested examining factors of switching intention through different generational, especially in countries with high individualism traits.

This study will encourage the halal industry, especially the halal cosmetics industry, to pay more attention to the product image. Meanwhile, the government can provide incentives or rewards to promote industry participation in halal cosmetics. The findings provide a more detailed understanding of how product image can influence someone to switch to halal cosmetics.

Research on switching intention to halal cosmetics is still limited. This study uses halal variables, while previous studies only used religiosity. This study also introduced the product images motivating customers’ switching intention to use halal cosmetics.

This paper aims to examine female entrepreneurship perceptions at the nexus of understandings of Muslim behaviour in Pakistan, the “formula” of Shapero for considering entrepreneurial intentions and the viewpoints of young Pakistani women.

Data collected from 555 women between 18 and 30 years of age, undertaking tertiary-level business studies in Pakistan constitute the sample of the study, and structural equation modelling was used to test the hypotheses.

This study finds that the respondents’ perceptions of Islam positively impact the formula at the feasibility component, whilst also inverting the desirability component, therefore, resulting in a “does not equal” outcome for intentions.

To the best of the authors’ knowledge, this work is one of the first to empirically examine the role of Islamic perception in shaping entrepreneurial intentions through the individual components of desirability, feasibility and propensity to act. It puts forth contextual deliberations for a meaningful heterodoxy in light of female entrepreneurship in an Islamic country.

The particle distribution in a fluid is mostly not homogeneous. The inhomogeneous dispersion of solid particles affects the velocity profile as well as the heat transfer of fluid. This study aims to highlight the effects of varying density of particles in a fluid. The fluid flows through a wavy curved passage under an applied magnetic field. Heat transfer is discussed with variable thermal conductivity.

The mathematical model of the problem consists of coupled differential equations, simplified using stream functions. The results of the time flow rate for fluid and solid granules have been derived numerically.

The fluid and dust particle velocity profiles are being presented graphically to analyze the effects of density of solid particles, magnetohydrodynamics, curvature and slip parameters. Heat transfer analysis is also performed for magnetic parameter, density of dust particles, variable thermal conductivity, slip parameter and curvature. As the number of particles in the fluid increases, heat conduction becomes slow through the fluid. Increase in temperature distribution is noticed as variable thermal conductivity parameter grows. The discussion of variable thermal conductivity is of great concern as many biological treatments and optimization of thermal energy storage system’s performance require precise measurement of a heat transfer fluid’s thermal conductivity.

This study of heat transfer with inhomogeneous distribution of the particles in a fluid has not yet been reported.

This study explores how titanium oxide (TiO₂) filler influences the specific wear rate (SWR) in flax fiber-reinforced epoxy composites (FFRCs) through a Taguchi approach. It aims to boost abrasive wear resistance by incorporating TiO₂ filler, promoting sustainable and eco-friendly materials.

This study fabricates epoxy/flax composites with TiO₂ particles (0–8 wt%) using hand layup. Composites were tested for wear following American Society for Testing and Materials (ASTM) G99-05. Statistical analysis used Taguchi design of experiments (DOE), with ANOVA identifying key factors affecting SWR in abrasive sliding conditions.

The study illuminates how integrating TiO2 filler particles into epoxy/flax composites enhances abrasive wear properties. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, wt% of TiO₂ and sliding distance. Grit size has the highest effect at 43.78%, and wt% TiO₂ filler contributes 15.61% to SWR according to ANOVA. Notably, the Taguchi predictive model closely aligns with experimental results, validating its reliability.

This paper integrates TiO₂ filler and flax fibers to form a novel hybrid composite with enhanced tribological properties in epoxy composites. The use of Taguchi DOE and ANOVA offers valuable insights for optimizing control variables, particularly in natural fiber-reinforced composites (NFRCs).

Several graphs, streamlines, isotherms and 3D plots are illustrated to enlighten the noteworthy fallouts of the investigation. Embedding flow factors for velocity, induced magnetic field and temperature have been determined using parametric analysis.

Ternary hybrid nanofluids has outstanding hydrothermal performance compared to classical mono nanofluids and hybrid nanofluids owing to the presence of triple tiny metallic particles. Ternary hybrid nanofluids are considered as most promising candidates in solar energy, heat exchangers, electronics cooling, automotive cooling, nuclear reactors, automobile, aerospace, biomedical devices, food processing etc. In this work, a ternary hybrid nanofluid flow that contains metallic nanoparticles over a wedge under the prevalence of solar radiating heat, induced magnetic field and the shape factor of nanoparticles is considered. A ternary hybrid nanofluid is synthesized by dispersing iron oxide (Fe3O4), silver (Ag) and magnesium oxide (MgO) nanoparticles in a water (H₂O) base fluid. By employing similarity transformations, we can convert the governing equations into ordinary differential equations and then solve numerically by using the Runge–Kutta–Fehlberg approach.

There is no fund for the research work.

This kind of study may be used to improve the performance of solar collectors, solar energy and solar cells.

This investigation unfolds the hydrothermal changes of radiative water-based Fe₃O₄-Ag-MgO-H₂O ternary hybrid nanofluidic transport past a static and moving wedge in the presence of solar radiating heating and induced magnetic fields. The shape factor of nanoparticles has been considered in this study.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

A novel type of heat transfer fluid known as hybrid nanofluids is used to improve the efficiency of heat exchangers. It is observed from literature evidence that hybrid nanofluids outperform single nanofluids in terms of thermal performance. This study aims to address the stagnation point flow induced by Williamson hybrid nanofluids across a vertical plate. This fluid is drenched under the influence of mixed convection in a Darcy–Forchheimer porous medium with heat source/sink and entropy generation.

By applying the proper similarity transformation, the partial differential equations that represent the leading model of the flow problem are reduced to ordinary differential equations. For the boundary value problem of the fourth-order code (bvp4c), a built-in MATLAB finite difference code is used to tackle the flow problem and carry out the dual numerical solutions.

The shear stress decreases, but the rate of heat transfer increases because of their greater influence on the permeability parameter and Weissenberg number for both solutions. The ability of hybrid nanofluids to strengthen heat transfer with the incorporation of a porous medium is demonstrated in this study.

The findings may be highly beneficial in raising the energy efficiency of thermal systems.

The originality of the research lies in the investigation of the Darcy–Forchheimer stagnation point flow of a Williamson hybrid nanofluid across a vertical plate, considering buoyancy forces, which introduces another layer of complexity to the flow problem. This aspect has not been extensively studied before. The results are verified and offer a very favorable balance with the acknowledged papers.