Abstract
Delivering information timely across the logistics network is a challenge considering the diversity of entities, technologies, IT maturity and legislation. A way to overcome those challenges is to bring all the parties to a common level by providing technology able to fast and easily connect every system and a common language to allow efficient communication between logistics stakeholders. When we apply the Synchromodality and the Digital twin concepts to logistics, significant improvements can be achieved. Shippers and Integrators can act more precisely, deciding in any step of the global operation by what mode should be selected or combined and following the strict regulations and issuing the mandatory documents timely to avoid bottlenecks. This work produced one real business scenario where the 4-corner model technology-based solution enables synchromodality across the logistics network of one industry unit and its providers and the Digital twin for the process and the VGM (Verified Gross Mass) formality documents. As a solution to this scenario we propose collaboration networks between logistics stakeholders that provide interoperable, low-cost, reliable and secure data exchange, without requiring significant IT developments. To this purpose we studied and developed a demonstrator and tested our solution that consists of the adoption of the 4-corner model as described by Connecting Europe Facility (CEF) eDelivery using access points and the adoption of the standard e-Freight to exchange data over the collaboration network. The widespread use of this solution will increase global efficiency, make the inclusion of every client and provider regardless of resources available, and avoid imponderables in the logistics network. © 2020 IEEE.

Abstract
Index structures were often used to optimise fetch operations to external storage devices (secondary memory). Nowadays, this also holds for increasingly large amounts of data residing in main-memory (primary memory). Within this scope, this work focuses on index structures that efficiently insert, query and delete valid-time data from very large datasets. This work performs a comparative study on the performance of the Interval B+ tree (IB+ tree) and the Improved Interval B+ tree (I2B+ tree): a variant that improves the time-efficiency of the deletion operation by reducing the number of traversed nodes to access siblings. We performed an extensive analysis of the performance of two operations: insertions and deletions, on both index structures, using multiple datasets with growing volumes of data, distinct temporal distributions and tree parameters (time-split alpha and node order). Results confirm that the I2B+ tree globally outperforms the IB+ tree, since, on average, deletion operations are 7% faster, despite insertions requiring 2% more time. Furthermore, results also allowed to determine the key factors that augment the performance difference on deletions between both trees. Copyright © 2021 by Author/s and Licensed by Veritas Publications Ltd., UK.

Abstract
iReceptor Plus will enable researchers around the world to share and analyse huge immunological distributed datasets, from multiple countries, containing sequencing data pertaining to both healthy and sick individuals. Most of the Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) data is currently stored and curated by individual labs, using a variety of tools and technologies.

Abstract
The Iliad Digital Twins of the Ocean is a European Green Deal Project which aims at the development of an architecture and set of components, tools and services for the creation of digital twins of the ocean. The approach aims to support the emerging European Digital Twins of the Ocean (EDITO) initative with associated projects like EDITO Infra and EDITO Model lab and the overall Destination Earth (DestinE) initiative and also taking advantage of the evolving European Common Data Spaces including the Green Deal Data Space, the Copernicus Data Space and the EOSC cross domain Data Space. The paper presents the final version of the Iliad digital twin interoperability architecture based on four steps of a digital twin pipeline from Data Acquisition/Collection to Digital Twin Data Representation to Digital Twin Hybrid and Cognitive/AI Analytics Models and further to Digital Twin Visualisation and Control, which are presented together with associated Digital twin components and services.

Abstract
Integrating citizen science with digital twin technology represents a significant development in oceanographic research and marine management. This paper examines how the Iliad project has successfully developed a comprehensive suite of digital twins of the ocean (DTOs) that leverage citizen science contributions to enhance data coverage, improve modelling accuracy, and foster public engagement with marine ecosystems. Through innovative technological solutions, including semantic interoperability frameworks, mobile applications, knowledge graphs, and gamification approaches, the project demonstrates the reciprocal benefits between citizen scientists, scientific research and digital twin ecosystems. The developments presented in this work illustrate how engaging the public in scientific research not only broadens the data foundation for digital twins but also creates pathways for citizens to gain valuable insights from these sophisticated digital representations of ocean environments.

Abstract
Developed within the Iliad Digital Twin of the Ocean (DTO) project, Coastal Crete provides advanced marine forecasting for oil spill detection and response. The system integrates satellite data, in-situ observations, and machine learning to predict oil spill trajectories and minimize environmental impacts. Using a multi-model approach, it combines WRF-DA, NEMO, and WAVEWATCH III models for high-resolution forecasts. Making use of Sentinel-1 SAR imagery, a deep learning approach was developed for near-real-time oil spill detection. The methodology is based on a U-net Neural Network, which is compared with the statistical methodology based on pythons' SNAPpy library. The operational forecasting system employs MEDSLIK-II for oil spill transport modeling and visualization via the GeoMachine platform, ensuring rapid decision-making for marine safety and environmental protection.