Multi-objective integrated sustainable supply chain scheduling with environmentally friendly and time windows freight transportation

Integrated sustainable supply chain scheduling (ISSCS) is essential for minimizing distribution costs, reducing environmental impacts, and improving customer service. This study develops a bi-objective mixed-integer nonlinear programming (MINLP) model that simultaneously optimizes single-machine production scheduling, due-date assignment, batch delivery decisions, and heterogeneous-fleet vehicle routing with customer-specific time windows. The objectives are to reduce freight transportation and emission costs while minimizing delivery tardiness. Numerical experiments based on real operational data validate the model using the -constraint method, which produces Pareto-optimal solutions with relative gaps below 0.8%. For large-scale instances, two multi-objective metaheuristics, Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization (MOPSO), are designed, tuned using Taguchi analysis, and evaluated using generational distance, mean ideal distance, spacing, diversity, and computational time. Experimental results show that NSGA-II delivers superior convergence and solution quality: within 50 iterations, it reduces average distribution cost from 126.2 to 69.3 million LCU (a 45% reduction) and decreases tardiness from 23,950 to 858 h (a 96% reduction). MOPSO achieves 32% cost reduction (108.4–68.1 million LCU) and 96% tardiness reduction (29,595–1047 h), but with less diversity and slower convergence. Pareto-front and convergence analyses confirm that NSGA-II consistently provides better-distributed and more stable non-dominated solutions. Overall, the proposed integrated model effectively reduces transportation, emission, and customer-dissatisfaction costs; the batch-delivery formulation ensures timely service across multiple time windows; and the metaheuristic frameworks especially NSGA-II demonstrate strong capability for solving large-scale sustainable supply-chain scheduling and environmentally friendly freight transportation problems

Parental use of distraction and portioning to reduce snack intake by children with avid eating behaviour: An experimental laboratory study

Introduction Children's avid eating behaviour is characterised by frequent snacking and food responsiveness. Parents need evidence-based advice on specific feeding practices, such as distraction techniques and portioning, that can be used to reduce children's intake of high energy-dense snacks. This experimental laboratory study tested the effectiveness of these feeding practices. Methods Parents and children (3–5 years; N = 129) who were identified as having an avid or typical eating profile were recruited and randomly allocated to one of three conditions. Following a standardised meal, children's energy intake (kcal) in the absence of hunger was assessed. While children had access to a snack buffet, parents were asked to use one of the following feeding practices: (1) Distract – using distraction techniques to delay children's snack intake; (2) Portion – allowing children to have snacks from pre-portioned pots; or (3) Control – allowing children to eat the type and number of snacks that their child wanted to. Results Children in the distraction condition consumed significantly less energy from snacks (M = 54.44 kcal, SD = 73.30) compared to children in the portion (M = 103.89 kcal, SD = 91.33, p .05). Children with avid versus typical eating profiles did not differ significantly in energy intake (p > .05). Conclusion Parental use of distraction techniques may be effective for reducing children's intake of high energy-dense snacks and could be recommended for use to support the development of children's healthy eating. Research to examine the effectiveness of distraction in real-world settings is now needed

AI legitimacy in energy: A model to improve corporate narratives on sustainability and responsibility

CONTEXT: The integration of artificial intelligence (AI) in the energy sector is pivotal for achieving Sustainable Development Goal 7 (SDG7). Within the European Union, the regulatory landscape, particularly the proposed AI Act, influences how organisations navigate responsible AI (RAI) adoption while addressing societal expectations, creating a critical need to examine how they communicate their commitment to RAI and sustainability. OBJECTIVE: This study uncovers how narratives employed in the public communications of EU energy stakeholders legitimise corporate efforts and signal alignment with RAI principles. METHOD: A grey literature search of website pages, whitepapers, and reports was conducted. Thematic analysis, using inductive and deductive coding, was employed to identify emerging themes and evaluate how organisations frame their initiatives in response to regulatory and societal pressures. RESULT: Analysis of 28 reports reveals that EU energy stakeholders predominantly frame AI as an inevitable technological advancement while lacking concrete strategies for RAI implementation. Communications focus on aspirational commitments rather than measurable actions. To address these gaps, this study develops the Responsible AI (RAI) Communication Model. This framework guides stakeholders in structuring their communication around three core pillars: (1) aligning AI initiatives with measurable sustainability goals and governance, (2) developing trustworthy and accountable narratives backed by concrete evidence, and (3) establishing organisational legitimacy through active stakeholder engagement. CONCLUSION: By adopting this model, energy stakeholders can move beyond rhetorical narratives towards sharing demonstrable practices. This fosters greater trust, ensures effective communication of priorities like transparency and accountability, and promotes regulatory alignment

Advancing Theoretical Integration of Distrust: A Multilevel Examination of Its Theoretical Foundations, Dynamics, and Mechanisms

This paper addresses persistent gaps in distrust scholarship by systematically reviewing studies published from 1998 to 2024. We refine distrust as a construct distinct from trust, mistrust, and suspicion, shaped by unique cognitive, emotional, and behavioral mechanisms. Substantial evidence supports that distrust is not merely the absence of trust but an independent phenomenon. Our review synthesizes research on how distrust emerges, escalates, and spills over across market settings. We develop a comprehensive model illustrating key themes and propositions at individual, dyadic, organizational, and systemic levels. This analysis reveals the complex antecedents of distrust, its varied influences on decision‐making and market interactions, and the measurement challenges arising from conflating distrust with low trust. By offering a unified framework, this review promotes the theoretical integration of distrust and offers practical guidance for mitigating its impact

The emotional toll of referral rewards: uncovering the relationship between referral rewards, anticipated embarrassment, self-image-concern, and recommendation likelihood

Using four experiments (N=765), this research shows that a referral reward offered only to the recommender negatively affects recommendation likelihood via anticipated embarrassment, and this effect is stronger for customers with high self-image-concern but can be minimized by appropriate reward design (e.g., reward both scheme and choice of reward)

A Qualitative Assessment of Metro Operators’ Internal Operations and Organisational Settings

This article offers a Qualitative Assessment of Metro Operators’ Internal Operations and Organisational Settings. It focuses on the current operational structures of metro companies and elaborates on key aspects incl. maintenance of metro rolling stock and energy consumption. Envisaging future metro operations requires a collective and collaborative approach to understand an operator’s requirements. This study aims to gain an understanding of the current status of metro operators, as well as to identify areas of future innovation and further development. A special emphasis was given to the organisational settings – an underexplored aspect of metro operators in existing research - in addressing three designated areas of interest: predictive maintenance, cyber-security and energy consumption. Therefore, to achieve an insight into metro operator’s internal operations, the study sought to engage in dialogue with operators. A literature review was first conducted to provide a foundation for analysis, and based on it, an online self-completed questionnaire survey was designed and administered to gain responses and insights from an extensive range of real-world metro operators. Follow-up face-to-face and group-wide discussions were also undertaken to obtain further detail and more specific information relating to metro operations. Through a three-dimension analysis framework, current practices, areas of consensus and future innovative strategies of metro operators’ internal operations and organisational settings are highlighted. These insights collectively underscore the importance of adaptable strategies and cross-sector collaboration for advancing resilient, efficient, and secure metro systems. The outcome of the paper aspires to provide a strong foundation for future research as well as for future metro projects, providing an overview of the existing status of metro operators across the world

From symbolic violence to structural exclusion: The multidimensional nature of Islamophobia in Europe

Amid growing concerns over rising religious tensions and anti-Muslim sentiment in Europe, this study develops and validates a robust Islamophobia Index to systematically measure experiences of discrimination among Muslim communities. Leveraging survey data from 3598 respondents (including 466 Muslims) across Belgium, Germany, Spain, and Italy, confirmatory factor analysis validated a three-factor structure for the Islamophobia Index, comprising Experiential Violence, Perceived Negativity, and Global Event Impacts. The index demonstrated metric invariance across Belgium, Germany, and Spain (N = 444 analysis sample), supporting its utility for cross-national comparisons. Regression analyses indicate systemic exclusion; perceived global event impacts emerged as a significant statistical predictor of both experiential violence and perceived negativity. Experiences were also found to vary with demographic factors such as age and income in certain models. While specific hypothesised intersectional effects (e.g., gender with religious identification) were not statistically significant in the tested models, the research illustrates the value of considering compounded vulnerabilities. The validated three-factor Islamophobia Index provides a nuanced quantitative measure capable of capturing both overt prejudice and perceptions of structural discrimination. By bridging critical theory with empirical rigour, this research points to the need for transnational, intersectional policy frameworks to dismantle institutionalised religious marginalisation and foster inclusive societies across Europe

Robust multi-period blood inventory routing under multiple uncertainties

We study a multi-period blood inventory routing problem that integrates production, inventory, and distribution decisions under uncertainties in demand, donation supply, and travel times, all while accounting for the limited shelf life of blood products. Our model captures transportation efficiency through a disutility measure based on vehicles’ arrival times at hospitals, and addresses supply–demand imbalances by allowing selective rejection of service requests at a high penalty cost. We formulate a robust optimization model that simultaneously determines production quantities, inventory levels, hospital service selections, and vehicle routing for each period. The objective is to minimize the total cost over the planning horizon, which includes worst-case inventory holding, wastage, and transportation costs, unserved demand penalties, and overall transportation disutility. To obtain an exact solution,we propose an integrated algorithm within the L-shaped framework that combines Benders decomposition with a branch-and-price-and-cut (BPC) scheme. This approach decomposes the robust model into a master problem and period-specific subproblems. For a given master solution, we first use constraint programming to verify the feasibility of the subproblems, and then, if feasible, solve them with a tailored BPC algorithm to generate Benders cuts that eliminate suboptimal master solutions. Extensive numerical experiments, including a case study at the Blood Center in Chongqing, demonstrate the effectiveness of our approach. Our analysis quantifies the benefits of incorporating uncertainty and robustness while providing managerial insights through a systematic evaluation of various parameters

Parametric study and design optimization of finned tube heat exchangers for enhanced indirect evaporative cooling

This study presents a comprehensive computational analysis, parametric study and optimization of a finned-tube heat exchanger (FTHE) integrating with Multi-Directional Wind Tower (MDWT) in Indirect Evaporative Cooling (IEC) applications aimed at improving thermal performance while minimizing pressure drop..

7‐Keto Cholesterol as a Mediator in Alzheimer's Disease Pathogenesis

Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-beta (Aβ) plaque accumulation, tau hyperphosphorylation, and oxidative stress. Recent evidence suggests that oxysterols, particularly 7-ketocholesterol (7-KC) may play a pivotal role in AD pathology by exacerbating neuroinflammatory and oxidative damage. 7-KC, a major non-enzymatic oxidation product of cholesterol, is known to contribute to neurotoxicity through mitochondrial dysfunction, lipid peroxidation, and inflammation. Unlike other oxysterols, 7-KC is highly reactive and has been implicated in cell death pathways relevant to neurodegeneration, including ferroptosis and autophagy dysregulation. Sulphation of 7-KC alter its solubility, bioavailability, and interaction with cellular receptors, potentially amplifying its cytotoxic effects in neuronal and glial cells