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The purpose of this paper is to examine the impact of urbanicity on rural–urban migrants' dietary diversity and nutrition intake and whether its effect differs across various urban environments of migrants.

Using the individual- and time-invariant fixed effects (two-way FE) model and five-year panel data from the China Health and Nutrition Survey (CHNS), this paper estimates a linear and nonlinear relationship between urbanicity and nutrition. The paper also explores the spatial heterogeneity between rural–urban migrants and rural–suburban migrants. Dietary diversity, total energy intake and the shares of energy obtained from protein and fat, respectively, are used to measure rural–urban migrants' nutrition on both quality and quantity aspects.

The study shows that rural–urban migrants have experienced access to more diverse, convenient and prepared foods, and the food variety consumed is positively associated with community urbanicity. Energy intake is positively and significantly affected by community urbanicity, and it also varies with per capita household income. The obvious inverse U-shaped relationship reveals that improving community urbanicity promotes an increase in the shares of energy obtained from protein and fat at a decreasing rate, until reaching the urbanicity index threshold of 66.69 and 54.26, respectively.

This paper focuses on the nutritional status of rural–urban migrants, an important pillar for China's development, which is often neglected in the research. It examines the urbanicity and the nutrition of migrants in China, which provides a new perspective to understand the dietary and nutritional intake among migrants in the economic and social development. Moreover, the urbanicity index performs better at measuring urban feathers rather than the traditional rural/urban dichotomous classification.

This study aims to undertake a comprehensive analysis of innovation models, tracing their evolution from Innovation 1.0 to Innovation 4.0 and introducing the concept of Innovation 5.0. It explores the intersection between innovation models and the principles of sustainability, resilience and human-centeredness, providing insights into their implications for Industry 5.0, and their potential to foster a resilient ecosystem amidst challenges and multiple crisis.

To achieve this objective, the authors used a systematic literature review approach, considering academic articles on Innovation 4.0, Industry 5.0 (specifically in the context of innovation) and helix models of innovation. The authors conducted thematic analysis and content analysis, followed by keyword co-occurrence analysis, enabling us to systematically synthesize and interpret the relevant literature.

The results conclude that Innovation 5.0 is a new paradigm for innovation that fosters broader societal engagement, and emphasizes sustainability, resilience and human-centeredness. Innovation 5.0 is evolving, but it has the potential to transform the way we produce, consume and live. Using insights from the sextuple helix model, this research leverages media and ICT as sixth helix vital role of knowledge sharing, digital transformation, innovation ecosystem and next industrial revolution in this process.

This study contributes to the ongoing discourse on exploring Innovation 5.0 through the sextuple helix model, offering a fresh perspective on innovation models and their collaborative potential. Its contribution lies in providing practical insights into the transition to Innovation 5.0, emphasizing the need for sustainability, regulatory support and awareness while also offering clear recommendations for future research.

To facilitate the reception and care of discharged patients, streamlining processes at the University Hospital and promoting a seamless transition to continuity of care services post-discharge.

Hospitalised patients undergo the Blaylock risk assessment screening score (BRASS), a screening tool identifying those at risk of complex discharge.

Pre-pandemic, patients with a medium-to-high risk of complex discharge were predominantly discharged to their residence or long-term care facilities. During the pandemic, coinciding with an overall reduction in hospitalisation rates, there was a decrease in patients being discharged to their residence.

The analysis of discharges, with the classification of patients into risk groups, revealed a coherence between the BRASS score and the characteristics of the studied sample. This tool aids physicians in decision-making by identifying the need for a planned discharge in a systematic and organised manner, preventing the loss of crucial information.

We propose in this paper a novel reliable detection method to recognize forged inpainting images. Detecting potential forgeries and authenticating the content of digital images is extremely challenging and important for many applications. The proposed approach involves developing new probabilistic support vector machines (SVMs) kernels from a flexible generative statistical model named “bounded generalized Gaussian mixture model”. The developed learning framework has the advantage to combine properly the benefits of both discriminative and generative models and to include prior knowledge about the nature of data. It can effectively recognize if an image is a tampered one and also to identify both forged and authentic images. The obtained results confirmed that the developed framework has good performance under numerous inpainted images.

This study aims to explore the enhancement of mechanical properties in epoxy resin composites through the incorporation of graphene nanoparticles, focusing on their impact and wear resistance. It investigates the role of graphene, both treated and untreated, as a reinforcing agent in composites, highlighting the significance of nanoparticle dispersion and surfactant treatment in optimizing mechanical performance.

Employing a novel dispersion technique using a drawing brush, this research contrasts with traditional methods by examining the effects of graphene nanoparticle concentrations treated with surfactants – Polyvinylpyrrolidone (PVP) and Sulphonated Naphthalene Formaldehyde (SNF) – on the mechanical properties of epoxy resin composites. The methodology includes conducting a series of impact and wear tests to assess the influence of graphene reinforcement on the composites' performance.

The findings reveal a marked enhancement in the composites impact resistance and energy absorption capabilities, which escalate with an increase in graphene content. Additionally, the study demonstrates a significant improvement in wear resistance, attributed to the superior mechanical properties, robust interface adhesion and effective dispersion of graphene. The use of surfactants for graphene treatment is identified as a crucial factor in these advancements, offering profound insights into the development of advanced composite materials for diverse industrial uses.

This study introduces a unique dispersion technique for graphene in epoxy composites, setting it apart from conventional methods. By focusing on the critical role of surfactant treatment in enhancing the mechanical properties of graphene-reinforced composites, it provides a novel insight into the optimization of impact and wear resistance.

Honeycombs enjoy wide use in various engineering applications. The emergence of additive manufacturing (AM) as a method of customisable of parts has enabled the reinvention of the honeycomb structure. However, research on in-plane compressive performance of both classical and new types of honeycombs fabricated via AM is still ongoing. Several important findings have emerged over the past years, with significance for the AM community and a review is considered necessary and timely. This paper aims to review the in-plane compressive performance of AM honeycomb structures.

This paper provides a state-of-the-art review focussing on the in-plane compressive performance of AM honeycomb structures, covering both polymers and metals. Recently published studies, over the past six years, have been reviewed under the specific theme of in-plane compression properties.

The key factors influencing the AM honeycombs' in-plane compressive performance are identified, namely the geometrical features, such as topology shape, cell wall thickness, cell size and manufacturing parameters. Moreover, the techniques and configurations commonly used for geometry optimisation toward improving mechanical performance are discussed in detail. Current AM limitations applicable to AM honeycomb structures are identified and potential future directions are also discussed in this paper.

This work evaluates critically the primary results and findings from the published research literature associated with the in-plane compressive mechanical performance of AM honeycombs.

This paper aims to investigate the feasibility of adding macro-textures to triangle meshes for additive manufacturing (AM) focusing on possible time and quality issues in both software processing and part fabrication.

A demonstrative software tool was developed to apply user-selected textures to existing meshes. The computational procedure is a three-dimensional extension of the solid texturing method used in computer graphics. The tool was tested for speed and quality of results, considering also the pre- and post-processing operations required. Some textured meshes were printed by different processes to test build speed and quality.

The tool can handle models with realistic complexity in acceptable computation times. Parts are built without difficulties or extra-costs achieving a good aesthetic yield of the texture.

The tool cannot reproduce sample patterns but requires the development of a generation algorithm for different type of textures. Mesh processing operations may take a long time when very fine textures are added to large parts.

Direct texturing can help obtain parts with aesthetic or functional textures without the need for surface post-treatments, which can be especially difficult and expensive for plastic parts.

The proposed method improves the uniformity and consistency of textures compared to existing approaches, and can support future systematic studies on the detail resolution of AM processes.

In the crowd intelligence networking era, the smart connections of human, machines and things enable point-to-point trustable transactions and distributed efficient collaboration; the smart connections among government, enterprises, organizations and the public would enable active participation of the public in society management and decision-making and improve the efficiency of government management and services. All interactions among various agents can be viewed as the transaction activity. The social division of labor system drives the evolution of transaction. The transaction mode also differentiated into different patterns with the development of human society. What will be the intelligent transaction in the crowd intelligence networking era? What will be the transactions modes and rules in the crowd intelligence networking era? The answers to these questions are of great importance to the future development of transactions.

The authors review the evolution of traditional transaction and transaction modes and analyze the driving forces of it. They attempt to give the definitions of intelligent transaction and intelligent transaction mode. They also review the traditional transaction modes and rules, analyze the characteristics of the intelligent transaction and classify the intelligent transaction modes.

The authors find the intelligent transaction is mainly reflected in the intellectualization of transaction subject, transaction object and transaction process. They summarize the characteristics of intelligent transaction and develop four modes for the intelligent transactions based on the modularization level of the transaction objects and the quantity of transaction subjects, including the demand side and the supply side. The authors also show representative examples to further illustrate rules and features of these transaction modes and point out the potential research directions.

This study is among the first to analyze the characteristics of the intelligent transaction, and the proposed division framework of the intelligent transaction modes could not only add value to the future research of intelligent transaction modes and rules but also help to guide the transactions in the crowd intelligence network.