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Synergistic improvement of UHPC mechanical properties through nano-engineering and thermal curing
No full textYesAdvancing material performance is pivotal for improving resource efficiency and reducing environmental footprint. Despite its superior performance over conventional concrete, the development of ultra-high- performance concrete (UHPC) is fundamentally constrained by difficult-to-reduce porosity from imperfect particle packing, and the inherent mechanical limitations of the C-S-H gel phase. To address these challenges, this study proposes an innovative synergistic strategy that integrates thermal curing with the incorporation of nano- silica (NS), without the use of any special dispersion techniques. The investigation evaluates the mechanical performance and microstructural evolution of UHPC incorporating 1 %, 2 %, and 3 % NS dosages under three distinct curing regimes: standard curing, steam curing, and a high-temperature gradient curing regime that integrates controlled steam curing (90 ◦ C for 48 h) followed by gradient hot air curing (150 ◦ C–200 ◦ C for 48 h). Compared with standard curing and steam curing, the compressive strength of the resulting UHPC was increased from 144.1 MPa and 165.9 MPa to 255.0 MPa, while the flexural strength improved from 48.0 MPa and 51.9 MPa to 76.7 MPa, respectively. The porosity was decreased from 7.78 % to 4.27 %, and was further reduced to 3.01 % with NS incorporation. In addition, relative to the traditional methods, the strength-normalized carbon emissions and cost of UHPC prepared using this synergistic strategy were reduced by 27.87 %-38.18 % and 26.00 %- 39.25 %, respectively. The study found that the capillary pore range of 5–70 nm was filled as a result of the thermal activation effect, by consuming free water within these pores and promoting the formation of a large amount of highly polymerized C-S-H, which was further transformed into high hardness and modulus crosslinked tobermorite and xonotlite. This is the key to improving the nano-scale heterogeneity and the steel fiber-matrix bonding. These findings suggest that the integration of combined curing with the nano-engineering method outperforms their individual effects, significantly optimizing its microstructural evolution, improving the mechanical properties of UHPC, and achieving high strength-to-density ratios, while also offering environmental and economic benefits.National Science Foundation of China (52578268,52308236 and 52368031), Major Science and Technology Research Project of the China Building Materials Federation (2023JBGS10–02), Natural Science Joint Founda tion of Liaoning Province (2023-BSBA-077), Fundamental Research Funds for the Central Universities (DUT24GJ202), the Fundamental Research Funds for the Central Universities (DUT25XQLP07).The full-text of this article will be released for public view at the end of the publisher embargo on 3 Feb 2028
Predictors and correlates of loneliness and social isolation in people with dementia: longitudinal findings from the IDEAL Programme
No full textYesObjective: To identify predictors of loneliness and social isolation experienced by people with dementia at baseline and over time.
Methods: Using data from the Improving the experience of Dementia and Enhancing Active Life (IDEAL) cohort study (2014–2018), we examined the prevalence and predictors of loneliness and social isolation in 1547 people with mild-to-moderate dementia over 24 months. Loneliness was measured using the six-item De Jong Gierveld Scale at baseline and 24 months and social isolation by the six-item Lubben Social Network Scale at baseline, 12 and 24 months. Generalised linear mixed effects models examined possible predictors of loneliness and social isolation including individual characteristics, depression, cognition, cultural participation, and neighbourhood characteristics.
Results: At baseline 35.4% of people with dementia were categorised as being lonely and 28.8% as socially isolated, increasing to 39.3% and 32.0% 2 years later. Over the 24-month follow-up none of these predictors were associated with changes in social isolation scores. Only perceived neighbourhood trust was associated with change in loneliness longitudinally. At baseline, depressive symptoms, living alone, smaller social networks and lower neighbourhood trust were associated with greater loneliness. Cross-sectionally, loneliness and lower cognitive ability were associated with greater social isolation, and greater cultural participation, more green and blue spaces nearby and higher neighbourhood trust were associated with lower social isolation scores.
Conclusions: The findings highlight the importance of the local environment and cultural participation for people with dementia. Enhancing interactions with the local neighbourhood through initiatives such as dementia friendly communities may help to reduce loneliness and social isolation.Economic and Social Research Council. Grant Number: ES/L001853/2. National Institute for Health and Care Research. Grant Number: ES/L001853/2. Alzheimer's Society. Grant Number: AS-PR2-16–00
The Effect of the Chinese One-Child Policy as Imposed Scarcity on Spouse Hunting
No full textYesChina’s one-child policy (1979–2015) has created a significant gender imbalance, leaving 34 million more men than women and intensifying competition in the marriage market. This study examines how imposed scarcity affects spouse-seeking behaviours through the lens of attachment theory and reactance theory. While attachment anxiety is expected to heighten desperation for romantic relationships, attachment avoidance may lead to greater reluctance in spouse-seeking. Meanwhile, reactance theory suggests that men—especially onelings (only children)—may experience heightened urgency due to limited partner availability and social pressure to marry. This study employs a quantitative survey-based approach to analyse attachment styles, desperation, family influence, and spouse-seeking methods among Chinese adults born during the one-child policy era. A structured online questionnaire will be distributed to a representative sample (ages 25–45, various marital statuses) using quota and snowball sampling via Chinese social media platforms and dating forums. Structural Equation Modelling (SEM) and multigroup analysis will assess the relationships between attachment styles, desperation, and spouse-seeking behaviours, while also examining gender and agebased differences. Findings will contribute to theoretical and practical discussions on romantic consumption by: 1. Extending attachment theory to explain how scarcity-driven desperation influences spouse-hunting behaviours. 2. Applying reactance theory to romantic decision-making, providing insights into how individuals react to imposed limitations in the dating market. 3. Examining traditional vs. digital matchmaking trends, offering implications for consumer behaviour, marketing strategies, and matchmaking industries. By bridging relationship psychology and consumer behaviour, this study provides new perspectives on the impact of demographic policies on romantic consumption. The insights are relevant for academics, policymakers, and the dating industry, particularly as China navigates post-one-child policy demographic shifts
AI-driven zero trust and blockchain framework for secure electric vehicle infrastructure
No full textYesElectric vehicle (EV) charging infrastructures are increasingly exposed to sophisticated cyber threats, including replay, spoofing, privilege escalation, and geolocation-based attacks. While standards such as ISO 15118 and OCPP 2.0.1 provide interoperability and cryptographic guarantees, they rely on static policies or isolated detection mechanisms, leaving gaps against adaptive adversaries. This paper presents an AI-driven Zero Trust Blockchain (AI-ZTB) framework whose novelty lies in the system-level integration of identity and access management, AI-based risk assessment, and blockchain-backed decentralized auditability with IPFS-based evidence storage, while operational governance remains centrally managed by the service provider. Unlike prior AI-only or blockchain-only frameworks, AI-ZTB introduces a fully integrated and enforceable Zero Trust control loop in which AI-generated risk scores are operationally bound to access enforcement decisions through smart contracts, enabling adaptive, auditable, and context-aware security governance in real time. The framework was implemented in Python with Solidity smart contracts and evaluated through a large-scale network simulation involving batches of 10,000 EV-charging sessions, trained on a dataset of 50,000 legitimate and adversarial behaviours using Random Forest, Autoencoder, and Isolation Forest models. Results demonstrate that AI-ZTB achieves access-decision accuracy above 95%, reducing false acceptance and rejection rates to approximately 3%. A comparative analysis evaluates AI-ZTB against industry standards (ISO 15,118 and OCPP 2.0.1) as secure communication baselines, and against prior integrated frameworks from the literature, highlighting differences in architectural scope, policy enforceability, and auditability rather than protocol-level performance. Despite modest inference and logging overheads, performance remained within real-time operational tolerances. The framework establishes a robust foundation for securing EV infrastructures, with extensibility to smart grids and other cyber-physical environments
Enhancing supply chain resilience and economic performance through Industry 4.0 and ESG integration: the mediating role of sustainable practices
Full text linkYesPurpose – The study aims to investigate the antecedents and outcomes of firms’ supply chain resilience, focusing on technology and sustainability capabilities. The study examines Industry 4.0 and the firms’ commitment to environmental, social and governance (ESG) as key resources for reshaping supply chains. Sustainability capabilities such as circular economy and sustainable supply chain design are also investigated to analyse their impact on supply chain resilience. The study measures the effect of supply chain resilience on a firm’s economic performance as its competitive advantage outcome.
Design/methodology/approach – The dynamic capabilities view and the information processing view are utilised as theoretical backgrounds. A partial least squares structural equation model is implemented to test the model using data gathered from 261 enterprises.
Findings – The results indicate that sustainable supply chain design and circular economy contribute to supply chain resilience, which in turn enhances a firm’s economic performance. Our results also demonstrate that Industry 4.0 and firms’ ESG commitment affect both sustainable supply chain design and the circular economy. Still, the contribution of ESG commitment to circular economy practices only exists through full mediation of sustainable supply chain design.
Originality/value – The study contributes to the operations and sustainable supply chain management literature by enhancing our understanding of the impact of Industry 4.0 and ESG commitment on sustainable supply chain practices, as well as the influence of these capabilities on enhancing supply chain resilience and environmental performance. In particular, the study reinforces the power of supply chain resilience as a dynamic capability that can help supply chains respond effectively to disruptions, thereby significantly improving economic performance by reducing overall operational and material costs, as well as energy consumption, while enhancing profitability and revenue
Internet of Things: Innovation, Threats, and Consequences
Full text linkYesThe Internet of Things (IoT), a paradigm driven by the integration of artificial intelligence and the convergence of the physical and digital domains, has ushered in a new era of hyperconnectivity and intelligent automation. While its innovations offer vast societal and economic benefits, IoT adoption faces significant challenges, including high deployment costs, integration complexity, and critical threats to security, privacy, and safety. This article critically examines these issues by exploring current advancements, highlighting economic and operational barriers, and analysing the evolving threat landscape. It emphasises the often-overlooked risks of rapid IoT expansion and presents balanced, forward-looking recommendations to support safer, more resilient, and sustainable IoT adoption and governance
Leveraging Parasocial Interaction to Drive the Bandwagon Effect in Online Retail
No full textYesPurpose: The primary objective of this study is to examine the role of parasocial interactions in generating the bandwagon effect. It is necessary to note that the bandwagon effect plays a crucial role in shaping the demand for brands, making it a principal area of interest for marketers.
Design/methodology/approach: This study investigates the influence of parasocial interaction (PSI) between the viewers and tech YouTubers in generating the bandwagon effect by incorporating the lens of parasocial relationship theory. Furthermore, the authors collected responses from 488 social media users who followed at least one tech YouTuber influencer and one brand fan page on a social media platform when considering the online retail sector. The authors analysed the obtained data using partial least square structural equation modelling (PLS-SEM) with SmartPLS software.
Findings: The results revealed that PSI is positively influencing vicarious expression (VE) and social networking site (SNS)-based electronic word-of-mouth (eWOM). Furthermore, VE also positively impacted the attitude toward the product category and the bandwagon effects.
Practical implications: The results of this study have direct managerial implications for PSI with tech YouTubers that can effectively redirect viewers to SNS brand fan pages, generating more user traffic for social media pages. It is particularly beneficial for newly launched brands with limited brand identification to leverage the authenticity and trustworthiness of tech YouTubers.
Originality: This study becomes essential as it offers valuable insights into the usability of PSI shared by viewers with YouTube-based tech influencers and its potential to be leveraged for the vicarious expression of products and associated brands through YouTube videos
The Use of a Smartphone to Assess the Two-Minute Step Test: Validity of Machine Learning Compared to Analytical Data Processing
No full textYesThe 2-Minute Step Test (2MST) is commonly scored by step count, which overlooks how the task is performed. This study tested whether a smartphone held to the thigh can be used to quantify thigh kinematics to determine 2MST outcome parameters, and whether a machine learning (ML) data analysis approach of the smartphone signal yields better agreement with motion capture (ground truth) compared to a more typical analytical data analysis approach (AA). Eighty-four healthy adults completed the 2MST while holding a smartphone against the right thigh. A thigh angular velocity ‘ground truth’ reference was obtained by simultaneous recording via motion capture (Vicon). Smartphone signals were resampled and processed using analytical (i.e., adaptive Butterworth filtering) and machine-learning data processing approaches (i.e., a stacked regression model trained to identify peak angular velocities). Step cycles and cycle duration were identical across equipment modalities and data analysis pipelines (mean 143 ± 18 cycles; 0.84 ± 0.11 s). However, the mean and variability of peak thigh angular velocity differed across the different modalities/pipelines (motion capture: 303 ± 39°·s−1; AA: 280 ± 47°·s−1; ML: 304 ± 37°·s−1). Bland–Altman agreement, compared to the ground truth measure, showed larger bias and limits of agreement for AA (bias 25.5°·s−1; −49.8–100.8) compared to ML (bias 1.0°·s−1; −15.4–17.5). These findings support using a smartphone held to the thigh to assess how the 2MST is performed, including providing the number and timing of steps completed and the average and variability in thigh angular velocity across cycles. Findings also suggest that a machine learning data analysis approach provides thigh angular velocity measures that are nearly identical to motion capture techniques, whereas a typical analytical data analysis approach has errors of around 8%
Global Tax Fraud Controversies Contextualized in A Dynamic Framework of Corporate Fraud Pyramid
No full textYesPurpose:
This study explores the determinants of corporate tax fraud utilizing a ‘dynamic framework of the corporate fraud pyramid.’ The debate regarding firm-specific and governance-related attributes explaining corporate tax fraud remains inconclusive, particularly during financial crises. Furthermore, few studies have utilized panel data to examine tax aggressiveness and tax evasion. Additionally, while some studies have investigated the effect of corporate governance on firm performance during a financial crisis, its impact on corporate tax fraud remains unknown. We aim to bridge these gaps by examining the effects of these attributes on corporate tax fraud, including in the pre-, during, and post-2007-2009 financial crisis.
Design/Methodology:
We use a sample of 198 matched pairs of tax fraud and non-tax fraud firms from 30 global jurisdictions for the period 2005-2017. The main source for our data is the Refinitiv (Thomson EIKON) databases. We use a quantitative research design employing Probit regression analysis to explore the immediate environment related to corporate tax fraud and the contextual, governance, and regulatory aspects of the sample firms. We employ an instrumental variable (IV) approach to control for endogeneity and an alternative specification to ensure the robustness of the results.
Findings:
We find that strong internal corporate governance mechanisms decrease the probability of tax fraud controversies. However, a strong regulatory environment, large audit fees, Big4 auditors and firm size were positively associated with the probability of tax fraud controversies. Moreover, higher executive compensation tends to curb the incidence of tax fraud controversies. These results were generally consistent for the pre-crisis, crisis, and post-crisis periods of the financial crisis of 2008.
Research / Practical Implications:
The research extends the contours of academic literature on corporate tax fraud and fraud theories, besides having implications for firm, industry, and country-level tax authorities, regulators, and policymakers, leading to greater transparency and accountability. Regulators will need to pay special attention to corporate board structures and ensure the inception of regulatory policies that can guarantee the existence of effective boards at the firm level. Tax authorities in different countries will be expected to make further efforts in detecting tax fraud, even if firms are operating in strong regulatory environments and are being audited by large audit firms.
Social Implications:
The colossal economic loss perpetrated by corporate tax fraud and its effect on societies across the world are some of the key motivators for pursuing this research. This study's findings help us understand the diverse occurrence of tax fraud in both developed and developing countries, especially in times of financial crises. The policy makers and regulators can pursue mitigating strategies, in the light of the knowledge thus obtained, which can have useful social implications in terms of reduced occurrence of corporate tax fraud.
Originality / Value:
First, we claim the ideation of a ‘dynamic framework of corporate fraud pyramid’ as a theoretical research contribution. We focus on four conceptual determinants: internal corporate governance mechanisms, firm-specific attributes, managerial aspects, and an external regulatory environment. Second, this study contributes to the literature in the context of the 2007-09 financial crisis and shows that strong internal corporate governance mechanisms and firm-specific attributes moderate the relationship between the crisis and corporate tax fraud incidence.The full-text of this article will be released for public view as soon as possible after the publisher's release date.” to this field. Remove it when full-text file released for public view
Community Norms, Peer Influence, and Women’s Digital Financial Inclusion: Evidence from India
Full text linkYesDespite rapid advances in digital finance, significant gender gaps persist, especially in South Asia. Using nationally representative data from India’s NFHS-5 survey (n = 84,213), this study explores how community norms and peer behavior shape women’s adoption of digital financial services. Employing a 2–2–1 multilevel moderated mediation model, we find that women are significantly more likely to engage in digital finance when embedded in communities with high peer usage, aligning with behavioral diffusion theory. However, this peer influence is curtailed in communities with restrictive gendered mobility norms. Our findings underscore the layered interaction between individual agency and community-level social structures. The study reveals that women’s employment and relative income foster digital adoption both directly and via increased peer exposure. Yet, this pathway weakens in socially restrictive environments. These insights highlight the necessity of norm-sensitive, community-level interventions to promote inclusive digital finance for women in low- and middle-income countries