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This study aims to fabricate multiwalled carbon nanotubes (MWCNTs)-mediated polyvinyl alcohol (PVA) composite films using the solution casting approach.

The prepared films were evaluated for diverse structural, surface, optical and electrical attributes using advanced analytical techniques, i.e. electron microscopy for surface morphology, Fourier transform infrared spectroscopy for tracing chemical functionalities, x-ray diffraction (XRD) for crystal patterns, water contact angle (WCA) analysis for surface wettability and UV visible spectroscopy for optical absorption parameters. The specimens were also investigated for certain rheological, mechanical and electrical properties, where applicable.

The surface morphology results expressed a better dispersion of MWCNTs in the resultant PVA-based nanocomposite film. The XRD analysis exhibited that the nanocomposite film was crystalline. The surface wettability analysis indicated that with the inclusion of MWCNTs, the WCA of the resultant nanocomposite film improved to 89.4° from 44° with the pristine PVA film. The MWCNTs (1.00%, w/w) incorporated PVA-based film exhibited a tensile strength of 54.0 MPa as compared to that of native PVA as 25.3 MPa film. There observed a decreased bandgap (from 5.25 to 5.14 eV) on incorporating the MWCNTs in the PVA-based nanocomposite film.

The MWCNTs’ inclusion in the PVA matrix could enhance the AC conductivity of the resultant nanocomposite film. The prepared nanocomposite film might be useful in designing certain optoelectronic devices.

The results demonstrated the successful MWCNTs mediation in the PVA-based composite films expressed good intercalation of the precursors; this resulted in decreased bandgap, usually, desirable for optoelectronic applications.

This study aims to investigate the impact of authentic leaders on the performance of educational leaders in public and private universities in Pakistan. The study further examines the moderating role of social capital in this relationship.

The authors collected data from 259 academic heads of public and private universities and tested hypotheses using macro PROCESS.

The findings demonstrate that authentic leaders have a significant positive effect on team leader performance in both public and private universities. In addition, the authors establish that the positive impact of authentic leaders on team leader performance is stronger among employees with high social capital.

The education literature lacks evidence of the process through which authentic leaders influence team leader performance. The study is unprecedented in assessing whether social capital moderates the direct influence of authentic leaders on team leader performance.

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.

The purpose of this study is to fabricate a highly sensitive humidity sensor for observing the humidity effect on a robot’s body as an application of the Internet of Things. The sensor has been fabricated by depositing a thin sensing layer of nickel phthalocyanine (NiPc) between two silver electrodes.

The structure of the thin film was observed by X-ray diffraction, optical properties by UV Vis and surface morphology by scanning electron microscope. The capacitance and the resistance with respect to change in relative humidity from 0 to 100%RH have been measured by LCR meter at 1 kHz.

The sensor’s response time is 7.5 s and its recovery time is 3.7 s, with high sensitivity of 127,259 pF/%RH and 332.287 MΩ/%RH. The authors have also used a proposed sensor on a steel body and observed humidity values. The analysis of all measured values was performed through the classical and neutrosophic approaches. By comparing, the authors have observed that the neutrosophic approach is more efficient in analyzing the sensor data.

In this work, the authors will fabricate a capacitive and resistive-type humidity sensor using the thin film of NiPc. The structural, optical and morphological properties of NiPc thin film will be investigated with different characterization techniques. The electric properties, i.e. capacitance and resistance, will be measured at intervals with an LCR meter by changing relative humidity (%RH). Moreover, the measured data will be analyzed through different statistical approaches, as already used in [12].

Assistive technology has been developed to assist the visually impaired individuals in their social interactions. Specifically designed to enhance communication skills, facilitate social engagement and improve the overall quality of life, conversational assistive technologies include speech recognition APIs, text-to-speech APIs and various communication tools that are real. Enable real-time interaction. Using natural language processing (NLP) and machine learning algorithms, the technology analyzes spoken language and provides appropriate responses, offering an immersive experience through voice commands, audio feedback and vibration alerts.

These technologies have demonstrated their ability to promote self-confidence and self-reliance in visually impaired individuals during social interactions. Moreover, they promise to improve social competence and foster better relationships. In short, assistive technology in conversation stands as a promising tool that empowers the visually impaired individuals, elevating the quality of their social engagement.

The main benefit of assistive communication technology is that it will help visually impaired people overcome communication barriers in social contexts. This technology helps them communicate effectively with acquaintances, family, co-workers and even strangers in public places. By enabling smoother and more natural communication, it works to reduce feelings of isolation and increase overall quality of life.

Research findings include successful activity recognition, aligning with activities on which the VGG-16 model was trained, such as hugging, shaking hands, talking, walking, waving and more. The originality of this study lies in its approach to address the challenges faced by the visually impaired individuals in their social interactions through modern technology. Research adds to the body of knowledge in the area of assistive technologies, which contribute to the empowerment and social inclusion of the visually impaired individuals.

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 purpose of the study was to determine the relationship between personal mastery orientation and employee creativity through internalized extrinsic motivation (identified regulation) and intrinsic motivation while testing job complexity as a boundary condition.

The authors tested this study model using a cross-sectional design with a sample of (N = 361). The study population was software developers from across different cities of Pakistan. Respondents were asked to rate themselves on creative behavior. Partial least square structural equation (PLS-SEM) and PROCESS macro were used for data analysis.

The results of the study confirm that personal mastery orientation positively affects employee creativity. Furthermore, both identified regulation and intrinsic motivation mediate the relationship between personal mastery and employee creativity. Job complexity was shown to moderate the direct relationship between personal mastery, identified regulation and intrinsic motivation such that for higher job complexity levels, the relationship between personal mastery and both types of motivation (identified and intrinsic) becomes stronger. The authors confirm that the indirect relationship between personal mastery and employee creativity through identified regulation was contingent upon job complexity level. In comparison, the indirect relationship between personal mastery and employee creativity through intrinsic motivation is not contingent upon the level of job complexity.

There are a few limitations to the authors' study. The current study is based on a cross-sectional design; therefore, this is of limited causal value. The authors suggest the studies examining similar relations to this study model use a longitudinal design. The incumbent of the job reports creative behavior; therefore, this is susceptible to common method bias (CMB). A peer-reported or supervisor-reported creative behavior should be used to eliminate the CMB in future studies.

The authors' study provides valuable input in identifying the complex mechanism through which creative behavior is induced involving individual personality disposition, job attributes and various types of motivations. In this study, the authors tried to reveal the mechanism through which personal mastery orientation predicts creative behavior. In the authors' endeavor of testing the motivational paths through which personal mastery orientation predicts creative behavior, the authors confirmed the efficacy of autonomous-complex motivation based on the self-determination framework. The authors' findings add to the evidence of the importance of intrinsic motivation in inducing creative behavior and recommend that the researcher should not ignore intrinsic motivation when exploring the effectiveness of extrinsic motivation.

The study's findings strengthen the argument of the continuum-like structure of the motivation types under self-determination theory(SDT). The authors argued that intrinsic motivation is a relatively stable type of motivation when creative behavior is involved and is not contingent upon the job attributes. These findings add to the evidence that intrinsic motivation is stable compared to extrinsic motivation. Another important contribution of this study is that the authors identified a boundary condition for the internalized extrinsic motivation when serving as creativity predicting mechanism and ruled the presence of a conditional effect when intrinsic motivation is involved.

In this chapter, we outline the background to the present volume, including the history of the Emonet group and the origins of the book series. We argue that the volume subtitle “A coat of many colors” reflects the diversity of approaches to studying emotion in organizational settings. We then provide a summary of the 11 contributor chapters in the volume, which illustrates the wide range of emotion-related topics covered in the volume.

This chapter provides an overview of the chapters in the volume, and gives a brief summary of each chapter, explaining how each fits into the overall theme of the volume and listing the key contribution of each chapter.

The introduction concludes with a summary of main findings of the chapters, and how they shape the future of the field, concluding that, since emotion-related topics nowadays are so integrated into the mainstream literature in organizational behavior and organization theory, maybe there is no longer a need to address emotions as a stand-alone topic.

The chapters in this volume address a wide range of emotion-related topics in the fields of organizational behavior and organization theory and point to the future of research in this field.

This study aims to investigate the comparative importance of factors influencing the customer shift behavior from conventional to Islamic banking for consumer finance in Pakistan.

First, a comprehensive analysis of the existing literature was conducted to identify a broad range of factors related to customer shift behavior. Through an expert sampling, 14 essential factors were chosen for further investigation. Second, a questionnaire was developed using the analytical hierarchy process (AHP). This questionnaire was then distributed among customers who had previously been using conventional banking services but had made a shift toward Islamic banking. The purpose of this questionnaire was to gather data and insights regarding their motivations and decision-making process behind the shift, and a sample 215 customers are taken in the study.

The results of AHP depicts that the religiosity is a most important factor influencing customers to shift from conventional to Islamic banking, and the second most important factor is pricing. The other subsequent important factors are reputation of the bank, marketing and promotion, service quality, behavior of banks staff, Shariah compliance, management, convenience, fastness and charges/fees. Whereas documentation, ambiance and recommendation are found least important factors to patronize Islamic banking.

The study recommends Islamic banks to create awareness, concentrating on religious factor to have a greater impact on growth of Islamic banking and shrinking of conventional banking. Further, it suggests Islamic banks to apply Shariah-recommended approach of doing business, to help community in best possible way and to launch differentiated marketing techniques to attract customers. It also proposes regulatory authorities to provide facilitation to Islamic banking business by providing level playing field similar to conventional banking, tax equality and conversion of public financing from conventional banking to Islamic banking.

The originality of this study lies in its comprehensive analysis of factors influencing consumer shift behavior from conventional to Islamic banking in the context of consumer finance in Pakistan. By using the AHP, the study provides a structured approach to understanding the relative importance of these factors. This is the uniqueness of the paper that it applies the AHP for the analysis. Furthermore, the study offers practical implications for Islamic banks and regulatory authorities to effectively address and capitalize on this consumer shift trend.

This paper aims to meta-analyze the results of the prior studies related to the relationship of human capital and financial performance in Islamic banking.

To examine the relationship between human capital and financial of Islamic banks, 23 empirical studies having sample of 15,607 are considered for the meta-analysis. Moreover, different measures related to financial performance including return on assets (ROA), return of equity (ROE) and Tobin’s Q have been taken as moderating for further subgroup analysis.

The results of meta-analysis reveal a positive correlation between human capital and financial performance with an effect size of 0.268. The subgroup analyses showed significant positive associations of human capital with ROA and ROE, insignificant with Tobin’s Q.

This study suggests Islamic banking should prioritize human capital development, maintain consistency and adopt a long-term perspective. Future research should consider context-specific factors and harmonize human capital and financial performance measurements for consensus.