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This study aims to fabricate a multifunctional electromagnetic interference (EMI) shielding composite fabric with simultaneous high-efficiency photothermal conversion and Joule heating performances.

A multifunctional polypyrrole (PPy) hydrogel/multiwalled carbon nanotube (MWCNT)/cotton EMI shielding composite fabric (hereafter denoted as PHMC) was prepared by loading MWCNT onto tannin-treated cotton fabric, followed by in situ crosslinking-polymerization to synthesize three-dimensional (3D) conductive networked PPy hydrogel on the surface of MWCNT-coated cotton fabric.

Benefiting from the unique interconnected 3D networked conductive structure of PPy hydrogel, the obtained PHMC exhibited a high EMI-shielding effectiveness vale of 48 dB (the absorbing electromagnetic wave accounted for 84%) within a large frequency range (8.2–12.4 GHz). Moreover, the temperature of the laminated fabric reached 54°C within 900 s under 15 V, and it required more than 100 s to return to room temperature (28.7°C). When the light intensity was adjusted to 150 mW/cm², the PHMC temperature was about 38.2°C after lighting for 900 s, indicating high-efficiency electro-photothermal effect function.

This paper provides a novel strategy for designing a type of multifunctional EMI shielding composite fabric with great promise for wearable smart garments, EMI shielding and personal heating applications.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

The existing technology adoption model (TAM) has ignored the importance of social proof of credibility such as risk, security and privacy. Also, this study aims to provide understanding how the issues of usability such as interactivity, compatibility and credibility can influence the mobile banking (MB) adoption of commercial and Islamic banks. This study has offered two theoretical models which may be helpful to understand the importance of social proof of credibility during MB adoption.

It is exploratory study therefore the researcher used triangulation of qualitative methods such as online banking app reviews, focused group and semi structured interviews are used to understand the behavior of customers toward MB adoption.

Consumers are actively involved to take recommendations from close sources, experts, customers and crowd opinion using interactive social media platforms (SMPs). The purpose to gather information is to save from usability, risk, security and privacy issues, especially when customers share their personal and financial information with the purpose to use MB. Results reveal that people with disabilities require MB app that has adjustable size, color, text and functions. The usability issues such as system design, response time, aesthetics, personalization, installation and service quality influenced the use of MB in Islamic banks.

Present study has offered social proof as TAM which highlights usefulness and credibility as important factors that can create social proof on SMPs. This study provides rich insights regarding what initiatives are required to resolve the issues of usability such as interactivity, compatibility and credibility that can influence the MB adoption of commercial and Islamic banks. Another major contribution of this study is to explore the issues of MB for people with disabilities and suggest how they can improve the service quality of MB for people with disabilities.

The purpose of this paper is to establish a two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem with three-parameter interval grey number to evaluation of agricultural drought resistance grade of 18 cities in Henan Province.

The clustering process is divided into two stages. In the first stage: Combining variance and time degree, the time weight optimization model is established. Applying the prospect theory, the index weight optimization model is established. Then, with the help of grey possibility function, the first stage of grey cloud clustering evaluation is carried out. In the second stage: the weight vector group of kernel clustering is constructed, and the grey class of the object is determined. A two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem is proposed.

This paper indicates that 18 cities in Henan Province are divided into four categories. The drought capacity in Henan province is high in the east and low in the west, high in the south and low in the north and the central region is relatively stable. The drought is greatly affected by natural factors. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical method for drought resistance assessment, and provides theoretical support for farmers to grasp the drought information timely and improve the drought resistance ability.

The model in this paper solves the situation of ambiguity and randomness to some extent with the help of grey cloud possibility function. Moreover, the time weight of time degree and variance are used to reduce the volatility and the degree of subjective empowerment. Considering the risk attitude of the decision makers, the prospect theory is applied to make the index weight more objective. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

Through a theoretical lens of psychological ownership, this study aims to investigate how technology mindfulness may stimulate metaverse tourism users’ feelings of individual psychological ownership, aesthetic value and conversational value, which in turn fosters intention to engage in prosocial behaviors.

The study used a scenario-based survey that allowed U.S.-based participants to create their own avatars and imagine using their avatars to explore heritage sites in the metaverse. Structural equality modeling was applied for data analysis.

The results from 357 valid responses indicate that technology mindfulness arouses tourists’ individual psychological ownership, aesthetic value, conversational value and prosocial behavioral intentions. The moderating role of biospheric value orientation on willingness to donate and intention to volunteer is investigated.

The research sheds light on the significance of technology mindfulness, conversational value and psychological ownership perspectives in the metaverse, which have been previously overlooked. The authors used a scenario-based survey for mental stimulation due to current metaverse technology limitations.

The study is one of the first to explore the possibility of encouraging prosocial behaviors using metaverse-facilitated technology. The research offers guidelines to engage hospitality and tourism customers in the metaverse that can blend their virtual experiences into the real world.

This study represents one of the pioneering efforts to gain an in-depth understanding of the application of metaverse in triggering prosocial behavior toward heritage sites, explained via a technology mindfulness-driven model with a psychological ownership perspective.

Drawing on the socially embedded model of thriving and the idiosyncrasy credit model of leadership, this study aims to develop a moderated mediation model to investigate the roles that are thriving at work and leader competency play in the link between leader humility and creative service performance (CSP) of hospitality frontline service employees (FSEs).

To test the moderated mediation model, the authors applied a time-lagged research design and collected multi-source data from locally owned, star-rated hotels headquartered in the capital city of Pakistan. The authors collected the multi-source data at three different points in time from employees and their respective supervisors (N = 52 managers and their 312 immediate employees).

The results denote that leader humility positively impacts CSP, thriving at work mediates this impact and leader competency not only moderates the connection between leader humility and thriving at work but also magnifies the indirect association between leader humility and CSP via thriving at work.

The moderated mediation framework based on the socially embedded model of thriving and the idiosyncrasy credit model of leadership will benefit future researchers and practitioners while exploring the impact of leader humility (LH) on FSEs’ CSP in the hospitality context.

The fundamental contribution of this study is developing and testing a research model that concentrates on the effects of leader humility on FSEs’ CSP. Moreover, by receiving support on the mediating role of thriving, this research further sheds light on how subordinates under the leader with humility demonstrate high CSP. In addition, the moderating role of leader competency found in this study further highlights that leader effectiveness depends on the degree to which employees perceive their leader as competent.

This paper aims to study the breather, lump-kink and interaction solutions of a (3 + 1)-dimensional generalized shallow water waves (GSWW) equation, which describes water waves propagating in the ocean or is used for simulating weather.

Hirota bilinear form and the direct method are used to construct breather and lump-kink solutions of the GSWW equation. The “rational-cosh-cos-type” test function is applied to obtain three kinds of interaction solutions.

The fusion and fission of the interaction solutions between a lump wave and a 1-kink soliton of the GSWW equation are studied. The dynamics of three kinds of interaction solutions between lump, kink and periodic waves are discussed graphically.

This paper studies the breather, lump-kink and interaction solutions of the GSWW equation by using various approaches and provides some phenomena that have not been studied.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

This paper aims to examine the impact of carbon emissions (carbon dioxide [CO₂]) reduction on tax evasion behaviour.

This study uses data from 200 countries from 2000 to 2017. The empirical analysis is based on various methodological tools, including ordinary least-squares model, fixed- and random-effects models. In addition, GMM and linear mixed model has been used for robustness purposes.

The results show that carbon emissions reduction significantly affects tax evasion behaviour; when carbon emissions decrease, tax evasion behaviour increases. This indicates that the reduction of CO₂ emissions is linked to significant costs, placing a financial burden on companies and leading them to evade taxes to counterbalance these costs.

This study has important implications, as it highlights that the efforts made by countries to minimize CO₂ emissions are associated with high costs and may lead to increased tax evasion, potentially contributing to countries’ budget deficits. The results provide valuable insights for policymakers and stakeholders to implement effective environmental and fiscal regulations that contribute to a sustainable and eco-friendly future. These regulations can help maintain a balance between improving economic growth and ensuring the protection of the environment.

To the best of the authors’ knowledge, this is the first paper to test the impact of carbon emissions on tax evasion using macro-level data.