An Integrated, Virtualized Joint Edge and Fog Computing System with Multi-RAT Convergence

Notably, developing an innovative architectural network paradigm is essential to address the technical challenging of 5G applications' requirements in a unified platform. Forthcoming applications will provide a wide range ofnetworking, computing and storage capabilities closer to the endusers.In this context, the 5G-PPP Phase two project named "5GCORAL:A 5G Convergent Virtualized Radio Access Network Living at the Edge" aims at identifying and experimentally validating which are the key technology innovations allowing for the development of a convergent 5G multi-RAT access based on a virtualized Edge and Fog architecture being scalable, flexible and interoperable with other domains including transport, core network and distant Clouds. In 5G-CORAL, an architecture is proposed based on ETSI MEC and ETSI NFV frameworks in a unified platform. Then, a set of exemplary use cases benefiting from Edge and Fog networks in near proximity of the end-user are proposed for demonstration on top of connected car, shopping mall and high-speed train platforms.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant num. 761586

COVID-19 Infection in Children and Infants: Current Status on Therapies and Vaccines

Since the beginning in December 2019, the SARS-CoV-2 outbreak appeared to affect mostly the adult population, sparing the vast majority of children who only showed mild symptoms. The purpose of this investigation is to assess the status on the mechanisms that give children and infants this variation in epidemiology compared to the adult population and its impact on therapies and vaccines that are aimed towards them. A literature review, including in vitro studies, reviews, published guidelines and clinical trials was performed. Clinical trials concerned topics that allowed a descriptive synthesis to be produced. Four underlying mechanisms were found that may play a key role in providing COVID-19 protection in babies. No guidelines are available yet for therapy due to insufficient data; support therapy remains the most used. Only two vaccines are approved by the World Health Organization to be used in children from 12 years of age, and there are currently no efficacy or safety data for children below the age of 12 years. The COVID-19 clinical frame infection is milder in children and adolescents. This section of the population can act as vectors and reservoirs and play a key role in the transmission of the infection; therefore, vaccines are paramount. More evidence is required to guide safely the vaccination campaign

Federated Learning of Explainable AI Models in 6G Systems: Towards Secure and Automated Vehicle Networking

This article presents the concept of federated learning (FL) of eXplainable Artificial Intelligence (XAI) models as an enabling technology in advanced 5G towards 6G systems and discusses its applicability to the automated vehicle networking use case. Although the FL of neural networks has been widely investigated exploiting variants of stochastic gradient descent as the optimization method, it has not yet been adequately studied in the context of inherently explainable models. On the one side, XAI permits improving user experience of the offered communication services by helping end users trust (by design) that in-network AI functionality issues appropriate action recommendations. On the other side, FL ensures security and privacy of both vehicular and user data across the whole system. These desiderata are often ignored in existing AI-based solutions for wireless network planning, design and operation. In this perspective, the article provides a detailed description of relevant 6G use cases, with a focus on vehicle-to-everything (V2X) environments: we describe a framework to evaluate the proposed approach involving online training based on real data from live networks. FL of XAI models is expected to bring benefits as a methodology for achieving seamless availability of decentralized, lightweight and communication efficient intelligence. Impacts of the proposed approach (including standardization perspectives) consist in a better trustworthiness of operations, e.g., via explainability of quality of experience (QoE) predictions, along with security and privacy-preserving management of data from sensors, terminals, users and applications

Federated Learning of Explainable AI Models in 6G Systems: Towards Secure and Automated Vehicle Networking

This article presents the concept of federated learning (FL) of eXplainable Artificial Intelligence (XAI) models as an enabling technology in advanced 5G towards 6G systems and discusses its applicability to the automated vehicle networking use case. Although the FL of neural networks has been widely investigated exploiting variants of stochastic gradient descent as the optimization method, it has not yet been adequately studied in the context of inherently explainable models. On the one side, XAI permits improving user experience of the offered communication services by helping end users trust (by design) that in-network AI functionality issues appropriate action recommendations. On the other side, FL ensures security and privacy of both vehicular and user data across the whole system. These desiderata are often ignored in existing AI-based solutions for wireless network planning, design and operation. In this perspective, the article provides a detailed description of relevant 6G use cases, with a focus on vehicle-to-everything (V2X) environments: we describe a framework to evaluate the proposed approach involving online training based on real data from live networks. FL of XAI models is expected to bring benefits as a methodology for achieving seamless availability of decentralized, lightweight and communication efficient intelligence. Impacts of the proposed approach (including standardization perspectives) consist in a better trustworthiness of operations, e.g., via explainability of quality of experience (QoE) predictions, along with security and privacy-preserving management of data from sensors, terminals, users and applications

Setting 6G Architecture in Motion - the Hexa-X Approach

The most recent cellular generation, 5G, is being deployed on a large scale globally. The capabilities of 5G surpass all previous generations of cellular networks and support many new services compared to 4G. Despite this, at the same time, preparations for 6G have begun since user demands and technical development continuously push the boundaries of what is possible. Demands come not only from users. Also, society sets requirements, e.g., sustainability, coverage, and privacy. To support the necessary features in the network needed to meet the requirements, a new generation of the architecture is needed; one based on the most forward-looking design principles together with trends in networks, use cases, and whatnot. To show that the proposed new features will allow the future network to meet the set requirements, key performance indicators (KPIs) have to be defined. In this paper, we present six of the KPIs that the European 6G flagship project Hexa-X has identified as the fundamental ones to measure the most important aspects of a new 6G architecture

Use of CGF in Oral and Implant Surgery: From Laboratory Evidence to Clinical Evaluation

Edentulism is the condition of having lost natural teeth, and has serious social, psychological, and emotional consequences. The need for implant services in edentulous patients has dramatically increased during the last decades. In this study, the effects of concentrated growth factor (CGF), an autologous blood-derived biomaterial, in improving the process of osseointegration of dental implants have been evaluated. Here, permeation of dental implants with CGF has been obtained by using a Round up device. These CGF-coated dental implants retained a complex internal structure capable of releasing growth factors (VEGF, TGF-β1, and BMP-2) and matrix metalloproteinases (MMP-2 and MMP-9) over time. The CGF-permeated implants induced the osteogenic differentiation of human bone marrow stem cells (hBMSC) as confirmed by matrix mineralization and the expression of osteogenic differentiation markers. Moreover, CGF provided dental implants with a biocompatible and biologically active surface that significantly improved adhesion of endothelial cells on CGF-coated implants compared to control implants (without CGF). Finally, data obtained from surgical interventions with CGF-permeated dental implants presented better results in terms of optimal osseointegration and reduced post-surgical complications. These data, taken together, highlight new and interesting perspectives in the use of CGF in the dental implantology field to improve osseointegration and promote the healing process

6G E2E Architecture Framework with Sustainability and Security Considerations

The research on 6G in the EU-funded flagship project Hexa-X started with the investigation of the most important technology enablers and the evaluation of relevant 6G use cases. The next step is to integrate these enablers in a 6G E2E architecture that fulfills all use case-based Key Performance (KPI) and Key Value Indicators (KVI) and that follows the guidelines of general architectural principles. In addition, the main focus of an E2E 6G architecture must be on security and sustainability which both will have increased importance for future communication networks and society

Rapid Maxillary Expansion on the Adolescent Patient: Systematic Review and Case Report

Aim: In the literature, many studies and articles are investigating new devices and approaches to achieve rapid palate expansion through the opening of the palatal suture, and evaluating the skeletal, dental, and soft tissue effects. The purpose of this review was to assess how palatal expansion is performed in adolescent patients with permanent dentition. Furthermore, it was reported as an example of successful orthodontic treatment of an 11-year-old female patient affected by maxillary skeletal transverse deficiency, in permanent dentition. Methods: A search of the literature was conducted on PubMed, Cochrane, Scopus, Embase, and Web of Science databases. Inclusion criteria were the year of publication between 2017 and 2022, patients aged 10 to 16 years in permanent dentition, with transversal discrepancy, treated with tooth-borne, bone-borne, hybrid palatal expanders. Results: A total of 619 articles were identified by the electronic search, and finally, a total of 16 papers were included in the qualitative analysis. Conclusions: From this study, it was assessed that MARPE is more predictable, and it determines a more significant expansion of the suture than the Hyrax expander, with fewer side effects