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Advancing sustainable pavements: a review of low-carbon construction materials and practices
Full text linkThis review comprehensively explores low-carbon construction materials for pavements, emphasizing their role in advancing sustainable infrastructure. It examines various material types—including recycled, industrial by-products, and bio-based alternatives—highlighting their properties, availability, and suitability for pavement applications. Performance metrics such as mechanical strength, durability, environmental impact, and life cycle assessments are discussed in detail. Real-world case studies demonstrate successful implementations, underscoring practical benefits. The review also identifies key challenges—including technological, economic, and regulatory barriers—and proposes directions for future research. Overall, the findings affirm that integrating low-carbon materials in pavement construction offers significant potential for reducing carbon emissions and promoting sustainable development
Educational Psychology Research and Practice (EPRaP); A Ten-Year Anniversary Retrospective
Full text linkMMF-Gait: A Multi-Model Fusion-Enhanced Gait Recognition Framework Integrating Convolutional and Attention Networks
Full text linkGait recognition is a reliable biometric approach that uniquely identifies individuals based on their natural walking patterns. It is widely used to recognize individuals who are challenging to camouflage and do not require a person’s cooperation. The general face-based person recognition system often fails to determine the offender’s identity when they conceal their face by wearing helmets and masks to evade identification. In such cases, gait-based recognition is ideal for identifying offenders, and most existing work leverages a deep learning (DL) model. However, a single model often fails to capture a comprehensive selection of refined patterns in input data when external factors are present, such as variation in viewing angle, clothing, and carrying conditions. In response to this, this paper introduces a fusion-based multi-model gait recognition framework that leverages the potential of convolutional neural networks (CNNs) and a vision transformer (ViT) in an ensemble manner to enhance gait recognition performance. Here, CNNs capture spatiotemporal features, and ViT features multiple attention layers that focus on a particular region of the gait image. The first step in this framework is to obtain the Gait Energy Image (GEI) by averaging a height-normalized gait silhouette sequence over a gait cycle, which can handle the left–right gait symmetry of the gait. After that, the GEI image is fed through multiple pre-trained models and fine-tuned precisely to extract the depth spatiotemporal feature. Later, three separate fusion strategies are conducted, and the first one is decision-level fusion (DLF), which takes each model’s decision and employs majority voting for the final decision. The second is feature-level fusion (FLF), which combines the features from individual models through pointwise addition before performing gait recognition. Finally, a hybrid fusion combines DLF and FLF for gait recognition. The performance of the multi-model fusion-based framework was evaluated on three publicly available gait databases: CASIA-B, OU-ISIR D, and the OU-ISIR Large Population dataset. The experimental results demonstrate that the fusion-enhanced framework achieves superior performance
Antiracism in Early Childhood Education: Theory and Practice
No full textThis book explores racism and antiracist practice in early childhood education (ECE), exploring how different theoretical lenses can enable students and practitioners to consider the complexity of race and racism in early childhood and education and the impact it has on young children's lives. Written by academics and practitioners based in the USA and the UK, the chapters cover a range of Issues and theories including, race and play, decolonial approaches in ECE, Marxism, critical pedagogy, child-centered pedagogy, pro-Black pedagogies, Black feminist perspectives, critical race theory and immigration. Throughout the book, new conceptualisations of race and anti-racist praxis emerge that have the potential to transform children's lives not only in day to day practice but also one's way of being in the world
What's the Hidden Cost of Leaders’ Cyberloafing? Uncovering Its Impact on Employees’ Innovative Behavior and the Mechanisms Involved
Full text linkThe widespread application of network technology in the workplace has given rise to the issue of leaders’ cyberloafing, which refers to leaders engaging in non-work-related online activities during working hours. Previous studies have revealed the trickle-down effect of leaders’ cyberloafing, but a comprehensive exploration of its impact on employees’ innovative behavior is still lacking. Considering this, we developed a moderated mediation model based on the cognitive appraisal theory of emotions to investigate how leaders’ cyberloafing affects employees’ innovative behavior. This study used hierarchical regression analysis to analyze a sample of 357 employees collected at three time points. The results indicate that leaders’ cyberloafing has a negative impact on employees’ innovative behavior. Workplace anxiety mediates the relationship between leaders’ cyberloafing and employees’ innovative behavior. Power dependence positively moderates the relationship between leaders’ cyberloafing and workplace anxiety, as well as the indirect effect of leaders’ cyberloafing on employees’ innovative behavior via workplace anxiety. This study identifies the detrimental effect of leaders’ cyberloafing on employees’ innovative behavior and its underlying mechanisms. It also inspires organizations to promote employees’ innovative behavior by regulating leaders’ cyberloafing and the exercise of power
The Battle for Search: United States v. Google LLC and Its Implications for Antitrust Law
Full text linkIn the ongoing antitrust case United States v. Google LLC, the central question is whether Google’s agreements to secure default status for its search engine with device manufacturers like Apple, browser developers and mobile carriers are part of a strategy to maintain its monopoly position. Google is accused of using this strategy to effectively block competitors from reaching a sufficient user base to achieve minimum efficient scale. A central question in the case is what role substantial payments to secure default status can play in such a foreclosure strategy. This theory looks at first sight like a standard foreclosure theory of harm for an exclusive dealing arrangement along the lines of the US Microsoft case, which the court explicitly refers to. We show in this paper that this is only superficially the case and that the issues are in fact significantly more complicated in this case than in either the US or EU Microsoft cases. This does not become clear in the judgement because of an insufficiently precise analysis of market definition and a limited use of the cited evidence. Furthermore, the lack of counterfactual analysis leads to a mistaken assessment of default payments necessarily being anticompetitive for a dominant company. We show that these flaws complicate the assessment of adequate remedies that address actual anticompetitive behaviour while not distorting the efficient operation of the market
Data-driven approaches in concrete science: applications, challenges and future prospects
Full text linkThis review paper provides a comprehensive exploration of integrating data-driven approaches in the domain of concrete science. The paper commences with an introduction elucidating the background and context of data-driven concrete science, outlining objectives and scope, and underscoring the importance of data-driven methodologies. Subsequently, it delves into the traditional analytical approaches and the potential for data-driven methods. The paper elucidates data collection and pre-processing techniques tailored to the domain, encompassing concrete-related data types, collection methodologies, and data pre-processing strategies. Moreover, it extensively covers data-driven modelling and prediction in concrete science, presenting an overview of data-driven models, machine learning techniques deep learning approaches and integration of big data analytics. The review consolidates insights into diverse applications, including concrete strength prediction, durability analysis and concrete microstructure characterisation, employing data-driven approaches. Furthermore, it highlights challenges and opportunities in this burgeoning field, encompassing data quality and availability, interpretability and explainability of models, and ethical consideration. The paper concludes with recommendations for researchers and practitioners aiming to harness the full potential of data-driven methodologies
Metaverse Innovation: Technological, Financial, and Legal Perspectives
No full textThe Metaverse can be defined as an immersive 3-D simulated digital environment that deploys technologies like augmented reality, virtual reality, blockchain, and artificial intelligence to imitate the real world and allow people to conduct daily activities through digital versions of themselves (avatars). The opportunities brought by the metaverse for the economy and the society are wide in scope from business models to equitable education possibilities. This prompts regulators and policymakers around the world to assess the crucial legal and regulatory issues that arise in the process of metaverse development. This book offers a comprehensive understanding of metaverse innovation from technological, financial, and legal perspectives. It offers the basics of the metaverse, such as its enabling technologies, main characteristics and the global trends that shape its development. It also reviews the positive and negative impact of the metaverse on different sectors of the economy as well as the implications for policy and law
Pharmabiome analyses in tandem with chemometrics can help trace the provenance of falsified medicines: A proof-of-concept study
Full text linkA lack of robust analytical approaches limits our ability to investigate the clandestine manufacturing origins of falsified medicines. We conducted a proof-of-concept study to test the feasibility of geolocating the production sites of falsified medicines, based on the identification of site-specific biological and chemo-isotopic features using a combination of environmental DNA metabarcoding, Direct Analysis in Real Time - Mass Spectrometry and Isotope Ratio Mass Spectrometry as profiling techniques. We produced tablets at two distant locations (England vs. Thailand), using controlled manufacturing methods, excipient composition and environmental conditions. Sets of tablets produced at separate locations showed distinct bacterial and eukaryotic diversity, particularly influenced by the incorporation of water used during tableting and the background environmental biosignatures of the production site. Tablets showed corresponding site-specific chemometric profiles, but the factors contributing to the observed chemical differences were unclear. When reference samples of known origin are available, our study suggests that site-specific biological and chemical features can be used in modelling approaches to successfully predict product origin. We developed a new mapping approach to exploit the geographic information within the eukaryotic pharmabiome of the falsifications; based on eDNA-derived species identification and the integration of publicly available species distribution data. In the absence of reference samples of known origin, the application of this workflow to our dataset provided partial clues about the product’s origin, with limitations likely due to taxonomic resolution and the presence of species with wide distribution ranges. Collectively, our research provides experimental support for the development of integrated, multifaceted tools for tracing the origin of falsified medicines, advancing efforts to combat this pervasive but neglected global health problem
Platformization in operations and supply chain management: A bibliometric-systematic literature review with content analyses
Full text linkPlatformization, the integration of Internet-driven platforms into the fabric of an application ecosystem, has gained substantial momentum across economic, governance, and infrastructure domains. However, research topics and directions in platformization are scattered and lack a systematic framework, which hinders the progress of platformization research in an era of rapid technological innovation. This paper comprehensively reviews the platformization literature in operations and supply chain management (OSCM), identifying research gaps, addressing the fragmented state of platformization literature, and promoting platformization innovation. Using bibliometric knowledge mapping, we analyze 402 journal articles and identify 13 key research areas. An in-depth content analysis based on 168 papers is conducted to identify five research themes: platformization in collaborative manufacturing, platformization in operational decisions, platformization in sustainability in supply chains, platformization in e-commerce supply chains, and platformization in technology innovation in supply chains. Using CiteSpace, we conduct author analysis, institution analysis, keyword co-occurrence network-based cluster analysis, and trend analysis to reveal keywords at the forefront of platform research. The study reveals the temporal evolution of keywords and emerging research trends and concludes with actionable directions for future exploration. This research establishes a robust roadmap for the evolving field and provides a foundational bibliometric knowledge structure map for platformization in OSCM