The main objective of the study is to discuss the application of a participatory approach that involves the community of a small rural area in Italy to develop and maintain a sustainable local food system based on a very ancient and high-quality typical local bean. The efficacy of the approach in terms of the active involvement of local actors (farming communities, local administration, social associations, and civil society) and knowledge transfer for preserving the local food culture has been demonstrated. Possible improvements to the approach through digital technologies for stimulating the effective engagement of teenagers have also been discussed.

Heat removal has become an increasingly crucial issue for microelectronic chips due to increasingly high speed and high performance. One solution is to increase the thermal conductivity of the corresponding dielectrics. However, traditional approach to adding solid heat conductive nanoparticles to polymer dielectrics led to a significant weight increase. Here we propose a dielectric polymer filled with heat conductive hollow nanoparticles to mitigate the weight gain. Our mesoscale simulation of heat conduction through this dielectric polymer composite microstructure using the phase-field spectral iterative perturbation method demonstrates the simultaneous achievement of enhanced effective thermal conductivity and the low density. It is shown that additional heat conductivity enhancement can be achieved by wrapping the hollow nanoparticles with graphene layers. The underlying mesoscale mechanism of such a microstructure design and the quantitative effect of interfacial thermal resistance will be discussed. This work is expected to stimulate future efforts to develop light-weight thermal conductive polymer nanocomposites.

Increasing populations in cities have created challenges for the urban environment and also public health. Today, lacking sport participation opportunities in urban settings is a global concern. This study conceptualizes and develops a theoretical framework that identifies factors associated with effective urban built environments that help shape and reshape residents’ attitude toward sport activities and enhances their participation. Based on a comprehensive review of literature and by following the Stimulus-Organism-Response (SOR) theory and attitude change theory, a four-factor measurement model is proposed for studying urban built environment, including Availability, Accessibility, Design, and Safety. Further examinations are made on how these factors are channeled to transform residents’ attitudes and behavior associated with participating in sport activities, with Affordability as a moderator. Discussions are centered around the viability of the developed framework and its application for future research investigations.

This study explores the marginalization of a poor fishing community in Gwadar, Pakistan. The study provides an insight into how different levels of power, such as hidden, visible/pluralist, and invisible ideological powers, are used in policy arenas to hinder fishers’ access to participatory spaces, decision-making, and resource use. By employing Gaventa’s power cubes analytical model, we analyze fishers’ experiences and prevailing scenarios. Qualitative research methods were used to collect data, including in-depth interviews and participant observation. The finding shows that the interests of the fishing community in fishery policies and ongoing development projects are excluded both with intention and unintentionally. The exclusion of the local fisher community from key spaces brings interruptions and transformations that influence their lives. Due to this, they are induced to join insurgent groups to confront exclusion-based policies in Gwadar, Pakistan.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

Oil spill clean-up is a long-standing challenge for researchers to prevent serious environmental pollution. A new kind of oil-absorbent based on silicon-containing polymers (e.g., poly(dimethylsiloxane) (PDMS)) with high absorption capacity and excellent reusability was prepared and used for oil-water separation. The PDMS-based oil absorbents have highly interconnected pores with swellable skeletons, combining the advantages of porous materials and gels. On the other hand, polymer/silica composites have been extensively studied as high-performance functional coatings since, as an organic/inorganic composite material, they are expected to combine polymer flexibility and ease of processing with mechanical properties. Polymer composites with increased impact resistance and tensile strength without decreasing the flexibility of the polymer matrix can be achieved by incorporating silica nanoparticles, nanosand, or sand particles into the polymeric matrices. Therefore, polymer/silica composites have attracted great interest in many industries. Some potential applications, including high-performance coatings, electronics and optical applications, membranes, sensors, materials for metal uptake, etc., were comprehensively reviewed. In the first part of the review, we will cover the recent progress of oil absorbents based on silicon-containing polymers (PDMS). In the later details of the review, we will discuss the recent developments of functional materials based on polymer/silica composites, sand, and nanosand systems.