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The complex behavior of viscoelastic fluids and its flow analysis under the impact of transverse magnetic field are becoming increasingly important in numerous emerging applications including biomedical engineering, aerospace engineering, geophysics and industrial applications. Additionally, the thermal analysis and fluid flow driven by propagating membranes will aid significant applications for microscale transport in bio-thermal systems. This study aims to investigate the thermal effects of viscoelastic fluids driven by membrane-induced propagation and transverse magnetic field.

The propagation of the membranes will work as pump which pushes the fluids from bottom to top against the gravitation force; however, there is backflow due to compression and expansion phases of membrane propagation. The Jeffrey fluid model is employed to analyze the viscoelastic fluid flow, with entropy generation examined and equations solved analytically under low Reynolds number and long-wavelength assumptions.

The findings reveal that an increase in magnetic field strength impedes fluid flow, while higher values of the Grashof number, heat source parameter and Jeffrey fluid parameter enhance fluid motion. The study’s findings have significant implications for optimizing magnetohydrodynamic systems in various emerging applications, including biomedical engineering, aerospace, geophysics and industrial processes.

This study aims to investigate the impact of a transverse magnetic field on the flow and heat transfer characteristics of viscoelastic fluids driven by membrane propagation.

This study aims to investigate the factors influencing service employee work and personal well-being affecting their intention to leave the organization. This research explored the effects of service climate, resilience and workplace well-being (WWB) on service employee perceptions of subjective well-being and turnover intention. PERMA framework of individual flourishing and well-being (Seligman, 2011) was used to measure employee WWB and reflected their positive emotions, engagement, relationships, meaning and accomplishment.

Service employees (n = 250) completed an online self-administered survey. partial least squares structural equation (PLS-SEM) modeling and multi-group analysis (PLS-MGA) were utilized to test how gender differences influenced personal and organizational factors, and their impacts on PERMA dimensions and outcomes.

Results revealed a significant effect of service climate and resilience on PERMA. Only service employee work-meaning positively influenced SWB and negatively turnover intention. Examining each dimension of employee engagement showed similar impacts of service climate and resilience for both men and women, while absorption increased turnover intention for men.

To the best of the authors’ knowledge, this study is one of the first to test the PERMA framework as service employee WWB. The study advances the employee well-being line of research by exploring the impacts of service climate and resilience on PERMA dimensions. The PERMA framework was extended to examine three sub-dimensions of employee engagement as unique PERMA dimensions. This study advances the limited knowledge of how work and personal factors affect service employees’ work and subjective well-being from a gender perspective.

Since the COVID-19 pandemic had a significant impact on all facets of civilisation around the world, including food safety, this study aimed to determine and compare the pre-COVID and post-COVID food safety knowledge of Bangladeshi consumers and their association with sociodemographic variables.

The current study performed a cross-sectional survey of 503 consumers who prepared food at least 2–4 times per week through a validated questionnaire, selected through convenience sampling from two metropolitan cities and two rural districts in Bangladesh. The non-parametric Wilcoxon signed-rank test, Mann–Whitney U tests, Kruskal–Wallis H and binary logistic regression were used for statistical analysis.

Although an increased percentage of consumers showed a better level of overall food safety knowledge in the post-pandemic (38.2%) than the pre-pandemic (28.8%), there is a low level of awareness of the appropriate duration of handwashing, foodborne pathogens, consuming raw milk or eggs, safe storage and temperature control of food. University graduates, families with few children and urban consumers had a good understanding of food safety both pre- and post-pandemic.

This study compares consumers’ pre- and post-COVID-19 food safety knowledge previously unknown in Bangladesh. The findings have significantly contributed to existing food safety knowledge in Bangladesh to adopt policies and structure training programmes for consumers in the country.

Recently, manipulative techniques, such as dark patterns, are widely applied. However, there is a need for clarification regarding these techniques and related phenomena. In particular, there is still no clarity about the terminology and conceptual basis of consumer manipulation. This paper aims to address this shortcoming by introducing a definition and classification of consumer manipulation.

This paper takes a conceptual approach, drawing on existing literature and established theories to comprehend the phenomenon of consumer manipulation.

The paper proposes that consumer manipulation comprises three dimensions: limited transparency, perceived restriction of autonomy and the feeling of being tricked. This paper presents a classification of different types of consumer manipulation and demonstrates how these types can lead to varying outcomes based on the source of manipulation, changeability, reasons for perception and perception timing. Based on this classification, research propositions informed by established theories and concepts are presented.

To the best of the author’s knowledge, this work represents a first attempt to address the concept of consumer manipulation through a clear definition and classification. It is relevant for academics, policymakers and practitioners since it facilitates informed discussions and analyses of this concept. It benefits companies by raising awareness of potentially overlooked consequences of manipulative tactics, while also benefiting consumers by reducing their exposure to manipulation.

Ohmic heating generates temperature with the help of electrical current and resists the flow of electricity. Also, it generates heat rapidly and uniformly in the liquid matrix. Electrically conducting biofluid flows with Ohmic heating have many biomedical and industrial applications. The purpose of this study is to provide the significance of the effects of Ohmic heating and viscous dissipation on electrically conducting Casson nanofluid flow driven by peristaltic pumping through a vertical porous channel.

In this analysis, the non-Newtonian properties of fluid will be characterized by the Casson fluid model. The long wavelength approach reduces the complexity of the governing system of coupled partial differential equations with non-linear components. Using a regular perturbation approach, the solutions for the flow quantities are established. The fascinating and essential characteristics of flow parameters such as the thermal Grashof number, nanoparticle Grashof number, magnetic parameter, Brinkmann number, permeability parameter, Reynolds number, Casson fluid parameter, thermophoresis parameter and Brownian movement parameter on the convective peristaltic pumping are presented and thoroughly addressed. Furthermore, the phenomenon of trapping is illustrated visually.

The findings indicate that intensifying the permeability and Casson fluid parameters boosts the temperature distribution. It is observed that the velocity profile is elevated by enhancing the thermal Grashof number and perturbation parameter, whereas it reduces as a function of the magnetic parameter and Reynolds number. Moreover, trapped bolus size upsurges for greater values of nanoparticle Grashof number and magnetic parameter.

There are some interesting studies in the literature to explain the nature of the peristaltic flow of non-Newtonian nanofluids under various assumptions. It is observed that there is no study in the literature as investigated in this paper.

This study aims to analyze research trends in civil engineering education accreditation, focusing on influential authors, top journals, leading institutions and countries and frequently cited articles. It also explores key research themes and proposes potential directions for future research in civil engineering education accreditation domain.

Data were retrieved from the Scopus database for the period 1985–2024, targeting articles referencing accreditation in civil engineering education. Performance analysis was conducted using Microsoft Excel, OpenRefine and biblioMagika, while science mapping was performed with the Bibliometrix R Package and VOSviewer.

The analysis demonstrates a consistent growth in publications on civil engineering education accreditation since 2000, with the United States leading contributions and Malaysia emerging as a notable contributor among developing countries. Contributions from 226 authors across worldwide institutions were identified. Six key research clusters were uncovered: (1) curricula and accreditation, (2) analytical and problem-solving skills, (3) construction practices and safety engineering, (4) undergraduate civil engineering programs, (5) professional standards in civil engineering and (6) research activities and development.

The findings provide valuable insights for institutions offering civil engineering programs, highlighting the need to align curricula with accreditation frameworks to ensure educational quality. Emphasis is placed on integrating elements such as outcome-based education, competency development and continuous quality improvement to prepare graduates for industry demands and global professional standards.

By offering a foundational framework for understanding the evolving landscape of accreditation, this study provides valuable guidance for institutions aiming to enhance educational quality and achieve alignment with international standards.

This study aims to explore the strategies for implementing research data management (RDM) services in Tanzania’s higher education institutions (HEIs).

The study drew upon the technology, organization, people and environment (TOPE) framework. Using a qualitative case study approach, data was collected through semistructured interviews with librarians, lecturers, information and communication technologies (ICT) and research and innovation staff. Data was thematically analyzed.

Numerous participants recognized the importance of RDM services, such as creating data management plans, enhancing the retrieval and reuse of research data and offering support for data curation and preservation. The study also identified organizational support, including developing policies and guidelines, providing financial assistance and ensuring data security. Furthermore, the study highlighted the importance of ICT infrastructure, including servers, software and hardware. A lack of ICT infrastructure and limited skills and knowledge among those responsible for implementing RDM services were among the challenges identified.

This study used the TOPE framework, along with relevant literature, to guide the formulation of research objectives and questions. While the TOPE framework offers a comprehensive view through its four dimensions, there is a need to integrate additional models, such as data curation, to achieve a more holistic understanding.

This study provides valuable insights into strategies for implementing RDM services in HEIs. It highlights the importance of professional development for stakeholders, enabling them to develop and enforce effective strategies supporting a data-driven research agenda.

This study contributes original insights by outlining the necessary strategies for HEIs to consider when implementing RDM services. The study adds value to understanding effective RDM implementation requirements in an academic setting by identifying various strategies for developing RDM activities.

Housing provision is a fundamental driver of national development and economic prosperity. However, housing affordability remains a critical problem worldwide, affecting countries regardless of their level of development, whether developed, developing or underdeveloped. The housing price index (HPI) measures trends in residential property prices and provides valuable insights into market dynamics. This study aims to model and forecast the HPI in Malaysia. Accurate HPI predictions are essential for informing policy decisions, guiding investment strategies and ensuring sustainable housing market development.

The autoregressive integrated moving average (ARIMA) model was used to analyse historical housing price data for modelling and forecasting housing prices for different types. The accuracy and reliability of the models and forecasts were assessed using key statistical metrics, including variance (s²), log-likelihood, Akaike information criterion, corrected Akaike information criterion and Bayesian information criterion.

The findings demonstrate that the ARIMA model improves accuracy in capturing seasonal and trend components in the Malaysian housing market, offering actionable insights for strategic decision-making. In addition, this research presents point and annual changes across different housing types that seek to offer a detailed view of price movements. By providing a reliable five-year forecast of the HPI, this study enables more informed decision-making in housing policy, investment strategy and financial planning.

Policymakers can use these insights to stabilise housing markets, whereas investors and developers can anticipate market movements for better capital allocation. Homeowners and prospective buyers will benefit from understanding future price trends, allowing for more strategic decisions regarding property purchases or sales.

The originality of the study lies in its ability to empirically forecast housing prices for various types of housing for the next five years. This provides valuable guidance for housing-related decisions. This research contributes to the growing literature on real estate forecasting in emerging markets and underscores the relevance of advanced time series models in navigating the complexities of dynamic housing markets.