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The development of a scheme for the safety evaluation of mechanical recycling processes for polyethylene terephthalate (PET) is described. The starting point is the adoption of a threshold of toxicological concern such that migration from the recycled PET should not give rise to a dietary exposure exceeding 0.0025 μg kg(-1) bw day(-1), the exposure threshold value for chemicals with structural alerts raising concern for potential genotoxicity, below which the risk to human health would be negligible. It is practically impossible to test every batch of incoming recovered PET and every production batch of recycled PET for all the different chemical contaminants that could theoretically arise. Consequently, the principle of the safety evaluation is to measure the cleaning efficiency of a recycling process by using a challenge test with surrogate contaminants. This cleaning efficiency is then applied to reduce a reference contamination level for post-consumer PET, conservatively set at 3 mg kg(-1) PET for a contaminant resulting from possible misuse by consumers. The resulting residual concentration of each contaminant in recycled PET is used in conservative migration models to calculate migration levels, which are then used along with food consumption data to give estimates of potential dietary exposure. The default scenario, when the recycled PET is intended for general use, is that of an infant weighing 5 kg and consuming every day powdered infant formula reconstituted with 0.75 L of water coming from water bottles manufactured with 100% recycled PET. According to this scenario, it can be derived that the highest concentration of a substance in water that would ensure that the dietary exposure of 0.0025 µg kg(-1) bw day(-1) is not exceeded, is 0.017 μg kg(-1) food. The maximum residual content that would comply with this migration limit depends on molecular weight and is in the range 0.09-0.32 mg kg(-1) PET for the typical surrogate contaminants.

<p>The EFSA Panel on Food Additives, Flavourings, Processing Aids and Materials in Contact with Food (AFC Panel) and the subsequent Panel on Food Contact Materials, Enzymes, Flavourings and Processing Aids (CEF Panel) have undertaken evaluations of the safety of flavourings (both chemically defined substances and mixtures such as smoke flavourings) and food contact materials (FCM), as well as assessments on other substances used in food. The major progress in methodologies for the evaluation of the safety of these substances is highlighted in this article. By December 2011, scientific opinions had been adopted for 247 substances for food contact materials, mainly plastics. Adoption of a series of opinions on active and/or intelligent packaging substances and on recycling processes of plastics is planned between July 2012 and December 2013. Panel opinions, EFSA statements/reports and guidance documents were published on specific issues and on substances for which there was an urgent request for safety evaluation (for example isopropylthioxanthone (ITX), bisphenol A (BPA), phthalates, epoxidised soybean oil (ESBO), benzophenone and 4-methylbenzophenone). By 2009, the AFC and CEF Panels had completed the safety review of 2 067 flavourings substances used in the EU. Additional data, which were requested for 404 substances, are currently under evaluation or have been generated. Eleven smoke flavourings have been evaluated, and the CEF Panel has prepared a guidance document on the future data required for the evaluation of flavourings.</p>

The undergoing digital transformation of the aviation industry is driven by the rise of cyber-physical systems and sensors and their massive deployment in airplanes, the proliferation of autonomous drones and next-level interfaces in the airports, connected aircrafts-airports-aviation ecosystems and is acknowledged as one of the most significant step-function changes in the aviation history. The aviation industry as well as the industries that benefit and are highly dependent or linked to it (e.g. tourism, health, security, transport, public administration) are ripe for innovation in the form of Big Data analytics. Leveraging Big Data requires the effective and efficient analysis of huge amounts of unstructured data that are harnessed and processed towards revealing trends, unseen patterns, hidden correlations, and new information, and towards immediately extracting knowledgeable information that can enable prediction and decision making. Conceptually, the big data lifecycle can be divided into three main phases: i) the data acquisition, ii) the data storage and iii) the data analytics. For each phase, the number of available big data technologies and tools that exploit these technologies is constantly growing, while at the same time the existing tools are rapidly evolving and empowered with new features. However, the Big Data era comes with new challenges and one of the crucial challenges faced nowadays is how to effectively handle information security while managing massive and rapidly evolving data from heterogeneous data sources. While multiple technologies and techniques have emerged, there is a need to find a balance between multiple security requirements, privacy obligations, system performance and rapid dynamic analysis on diverse large data sets. The current paper aims to introduce the ICARUS Secure Experimentation Sandbox of the ICARUS platform. The ICARUS platform aims to provide a big data-enabled platform that aspires to become an "one-stop shop" for aviation data and intelligence marketplace that provides a trusted and secure "sandboxed" analytics workspace, allowing the exploration, curation, integration and deep analysis of original, synthesized and derivative data characterized by different velocity, variety and volume in a trusted and fair manner. Towards this end, a Secure

Over the last years, the impacts of the evolution of information integration, increased automation and new forms of information management are also evident in the aviation industry that is disrupted also by the latest advances in sensor technologies, IoT devices and cyber-physical systems and their adoption in aircrafts and other aviation-related products or services. The unprecedented volume, diversity and richness of aviation data that can be acquired, generated, stored, and managed provides unique capabilities for the aviation-related industries and pertains value that remains to be unlocked with the adoption of the innovative Big Data Analytics technologies. The big data technologies are focused on the data acquisition, the data storage and the data analytics phases of the big data lifecycle by employing a series of innovative techniques and tools that are constantly evolving with additional sophisticated features, while also new techniques and tools are frequently introduced as a result of the undergoing research activities. Nevertheless, despite the large efforts and investments on research and innovation, the Big Data technologies introduce also a number of challenges to its adopters. Besides the effective storage and access to the underlying big data, efficient data integration and data interoperability should be considered, while at the same time multiple data sources should be effectively combined by performing data exchange and data sharing between the different stakeholders that own the respective data. However, this reveals additional challenges related to the crucial preservation of the information security of the collected data, the trusted and secure data exchange and data sharing, as well as the robust access control on top of these data. The current paper aims to introduce the ICARUS big data-enabled platform that aims provide a multi-sided platform that offers a novel aviation data and intelligence marketplace accompanied by a trusted and secure "sandboxed" analytics workspace. It holistically handles the complete big data lifecycle from the data collection, data curation and data exploration to the data integration and data analysis of data originating from heterogeneous data sources with different velocity, variety and volume in a trusted and secure manner.

Open banking holds the potential of expanding traditional banking data flows, placing the customer at its core and in control of their banking data, including their personal information. Consent management enables the tracking, monitoring and managing the personal data lifecycle in a GDPR compliant manner, and improves customers’ control over their data, empowering them to manage their consent throughout its lifecycle. However, traditional technologies have failed to become a key enabler of trust, due to multiple security/data tampering incidents. This chapter introduces a blockchain-empowered Consent Management System (CMS). It aims at presenting the design and implementation of a robust CMS, enabling the sharing of customers’ consent, thus facilitating the exchange and the utilization of customer data, across different banking institutions. The proposed CMS implementation will enable the financial institutions to effectively manage and share their customers’ consents in a transparent and unambiguous manner, ensuring compliance to PSD2 and GDRP, while lowering the barriers of secure data sharing.