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Computational methods to leverage topological features occurring in signals and images are currently one of the most innovative trends in applied mathematics. In this paper a pipeline of topological machine learning is applied to the challenging task of classifying four specific marine mesoscale patterns from remote sensing data, i.e., Sea Surface Temperature maps of the southwestern region of the Iberian Peninsula. Our preliminary study achieves an accuracy of 56% in the 4-label classification. Such results are encouraging, especially considering that the data are affected by noise and that there are low-quality/missing data. Also, the paper devises directions for future improvements.

The Pomo (or Jabuka) Pits area is one of the main fishing ground for Norway Lobster Nephrops norvegicus and European hake Merluccius merluccius within the GFCM Geographical Sub Areas 17 (Northern and Central Adriatic Sea) and it is shared by the Italian and the Croatian fleets. Furthermore, this represents a well-known nursery area for M. merluccius and hosts a distinct population of N. norvegicus, characterized by small-sized mature individuals. Due to a decline in landing of both species for the Adriatic Sea, since 2015 the Italian and the Croatian governments implemented some protection measures in that area. Eventually in 2018, the GFCM established a Fishery Restricted Area. Since 2009 the area is yearly monitored by CNR IRBIM in collaboration with IOF Split. From 2009 to 2019 (except 2011 and 2018), a spring UWTV survey was conducted in the Pomo Pits area jointly by CNR-IRBIM Ancona and IOF Split, on board the CNR R/V Dallaporta; the Pomo Pits UWTV time series has been recently included, as a tuning index, in new modeling approaches tested for the Adriatic N. norvegicus stock assessment. Trials on automatic burrow tracking and counting have also been recently conducted on the Adriatic UWTV footage in the framework of the EU H2020 NAUTILOS project.

The Working Group on Nephrops Surveys (WGNEPS) is the international coordination group for Nephrops underwater television and trawl surveys within ICES. This report summarizes the national contributions on the results of the surveys conducted in 2022 together with time series covering all survey years, problems encountered, data quality checks and technological improvements as well as the planning for survey activities for 2023. In total, 21 surveys covering 26 functional units (FU’s) in the ICES area and 1 geographical subarea (GSA) in the Adriatic Sea were discussed and further improvements in respect to survey design and data analysis standardization and the use of most recent technology were reviewed. The first exploratory UWTV survey on the FU 25 Nephrops grounds was also presented to the group. The results of the evaluation of reference sets for FU3&4 Skagerrak/Kattegat were accepted following the process set down by the 2018 workshop (WKNEPS). An alternative method estimate Nephrops abundance was shown to the group using the recently published R package sdmTMB. The group agreed to hold a workshop in 2025 to address burrow size estimations to update correction factors and terms of reference for this to be agreed at next meeting. Automatic burrow detection based on deep learning methods continues to show promising results where datasets from multiple institutes were used. Plans are being progressed for an international Nephrops UWTV database to be established at the ICES data centre with a sub-group.

The oceans play a crucial role in the global ecosystem for shaping climate and weather trends, water management and health, and the biogeochemical cycles, representing valuable sources of oil, food, minerals and renewable energy. Although increasingly mature marine observation technologies have been developed during recent decades for a better understanding of the oceans, the new advances of existing operational observing systems have been constrained by limited cooperation and interaction between the managers of existing ocean networks on earth as well as between the observing units. Furthermore, the development of smart in situ marine sensors to be integrated into existing fixed units (such as landers and mooring buoys) as well as in mobile units (such as AUVs, ROVs, ships of opportunity, marine drones, Argo floats and gliders) are under development in the frame of various European and international projects. In recent years, a lot of progress has been made for the Ocean Observation Technologies and Information Systems by developing cost effective and miniaturized sensing devices with very low power consumption that would be directly integrated as a "plug and play" operational mode in existing sensor networks. Additionally, a lot of effort has been made to develop acoustic communication methods and modules to transmit the data from the deep ocean as well as cellular systems for transmitting the data of the marine sensors in near real-time mode using 4G/5G protocols (especially in coastal areas). In order to improve the processes that take place globally in the oceans (such as weather monitoring and forecasting, climate variability, sea level rise, natural hazards, ocean acidification, health of the ocean, pollution and ecosystem functioning, energy, economic development and coastal management, public safety, security, training and education), new research is ongoing to improve and optimize infrastructures and updated models at the international level. The state-of-the-art in situ marine sensors with the capability to be easily integrated into ocean platforms combined with innovative communication and information systems for real-time data transmission will emerge as new features of both forecasting methods and smart emergency systems to protect humans.

Background and aims: In patients with hepatocellular carcinoma (HCC), macrovascular invasion (MaVI) limits treatment options and decreases survival. Detailed data on the relationship between MaVI extension and patients' characteristics, and its impact on patients' outcome are limited. We evaluated the prevalence and extension of MaVI in a large cohort of consecutive HCC patients, analysing its association with liver disease and tumour characteristics, as well as with treatments performed and patients' survival. Methods: We analysed data of 4774 patients diagnosed with HCC recorded in the Italian Liver Cancer (ITA.LI.CA) database (2008-2018). Recursive partition analysis (RPA) was performed to evaluate interactions between MaVI, clinical variables and treatment, exploring the inter-relationship determining overall survival. Results: MaVI prevalence was 11.1%, and median survival of these patients was 6.0months (95% CI, 5.1-7.1). MaVI was associated with younger age at diagnosis, presence of symptoms, worse Performance Status (PS) and liver function, high alphafetoprotein levels and large HCCs. MaVI extension was associated with worse PS, ascites and greater impairment in liver function. RPA identified patients' categories with different treatment indications and survival, ranging from 2.4months in those with PS>1 and ascites, regardless of MaVI extension (receiving best supportive care in 90.3% of cases), to 14.1months in patients with PS 0-1, no ascites and Vp1-Vp2 MaVI (treated with surgery in 19.1% of cases). Conclusions: MaVI presence and extension, together with PS and ascites, significantly affect patients' survival and treatment selection. The decision tree based on these parameters may help assess patients' prognosis and inform therapeutic decisions.

Questo rapporto tecnico di progetto è il risultato del contributo fornito dal Laboratorio Segnali e Immagini dell'ISTI-CNR per il documento di progetto RTOD-SYS-SDD-010-INT per il progetto RTOD (Real-Time Object Detection mediante Machine Learning basato su tecnologia Low-Power GPU). In particolare, il rapporto studia e discute delle varie possibilità di architetture di reti convolutive che sono state valutate e che potranno essere utilizzate nel contesto del progetto per effettuare delle categorizzazioni di immagini mediante algoritmi di machine learning.

D13.7 deliverable is relative to Ethics Requirement No. 10 as a General requirement to submit a report by the Ethics Board as a deliverable at the end of each reporting period. This document represents the first report of such type. Describing the activities and updates of the NAUTILOS Ethics Advisory Board for this first period of the project from M1 till M18.

In this deliverable, an update of the DMP at M18 will be reported.

This deliverable consist of the deployment of the project's web portal through which the storage and management of the integrated data regarding NAUTILOS, and the services defined and implemented during Task 8.4 have been organised. The implemented tools and services for data management and visualisation, designed in close connection with end-users requirements, are described.

An annual report and evaluation provided by the External Advisory Board provides their overall assessment of NAUTILOS and advice on the project's future direction. The following deliverable is the report following the EAB at the end of the project's second year in M24.

Remote sensing technologies allow for continuous and valuable monitoring of the Earth's various environments. In particular, coastal and ocean monitoring presents an intrinsic complexity that makes such monitoring the main source of information available. Oceans, being the largest but least observed habitat, have many different factors affecting theirs faunal variations. Enhancing the capabilities to monitor and understand the changes occurring allows us to perform predictions and adopt proper decisions. This paper proposes an automated classification tool to recognise specific marine mesoscale events. Typically, human experts monitor and analyse these events visually through remote sensing imagery, specifically addressing Sea Surface Temperature data. The extended availability of this kind of remote sensing data transforms this activity into a time-consuming and subjective interpretation of the information. For this reason, there is an increased need for automated or at least semi-automated tools to perform this task. The results presented in this work have been obtained by applying the proposed approach to images captured over the southwestern region of the Iberian Peninsula.

With the intention of extending knowledge about the ocean and the maritime environment, this Special Issue focuses on all the many intelligent systems and applications that, through technologies integrated on observational platforms, can provide tools and services for increasing the availability of data regarding all ocean environmental variables. Among the already existing platforms and technologies for ocean observation, this Special Issue aims to expand the possible application of intelligent systems and tools that operate in this context. Contributions can vary from tools for automatic collection and dispatching of information to systems for management and processing of environmental data through to methods applied to new or well-established technologies for performing consistent and standardised intelligent processing of collected data. The intended coverage for this Special Issue concerns systems, applications, and models that aim to improve the current observation tools and services and expand the availability of data in terms of higher spatial resolution, temporal regularity, and length than what is currently available at the European scale. The Special Issue also aims to democratise monitoring of the marine environment for traditional and non-traditional data users such as citizen scientists. All articles from academia, the industry, or environmental stakeholders are welcome.

The Signal & Images Laboratory is an interdisciplinary research group in computer vision, signal analysis, intelligent vision systems and multimedia data understanding. It is part of the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR). This report accounts for the research activities of the Signal and Images Laboratory of the Institute of Information Science and Technologies during the year 2021.

Introduction and Objective The H2020 NAUTILOS project aims to fill existing gaps in marine observation and modelling through the development of innovative and cost-effective technologies and observational methodologies for use in a wide range of crucial environmental contexts and sectors that can further support EU policies. The H2020 NAUTILOS project fills marine observation and modelling gaps by developing and deploying new technologies, promoting innovative and cost-effective methods in a wide range of crucial environmental settings and EU policy-related applications. Material and Methods NAUTILOS is developing innovative and cost-effective sensors and samplers for physical, chemical, and biological essential ocean variables in addition to micro-/nano-plastics. Newly developed technologies are integrated into diverse observing platforms, i.e. ships of opportunity, research vessels, surface and autonomous underwater vehicles, landers, fixed observatories, Argo floats, and Animal-borne instrumentation modules, to be deployed in key environmental settings. Results and Data relevance NAUTILOS will contribute to improving future ocean observation and forecasting capabilities through its holistic approach, which includes new sensors, new data to feed metocean forecast models, and the assessment of the forecasting capabilities, i.e. (OSSE) NAUTILOS data products FAIRness includes adopting standard vocabularies and open data publishing systems interoperable with European and international Ocean Data integrators. Moreover, synergies with relevant initiatives, Citizen Science campaigns and capacity building courses are also planned to reach out to all relevant stakeholders and users and promote free access and exchange of scientific data and knowledge. Conclusion The project will improve our understanding of environmental fluctuations and anthropogenic impacts in the oceans, relevant to aquaculture, fisheries and marine litter. Moreover, it will also complement and contribute to expanding European observation tools and services to obtain data collection at a much higher spatial resolution, temporal regularity and length than currently available at the European scale, and further democratise the marine environment's monitoring.

This deliverable will consist of the specific tools and interface for supporting the Citizen Science Campaigns, to integrate the data produced during these activities (see Task 12.2) within the web portal. The interface, realised in Task 8.4, will be based on geo-referenced maps indicating, for instance, plastic litter data. An accompanying report with the guidelines for the usage of these tools and interface will be produced.

This deliverable will consist of the implementation of image analysis tools based on methods and algorithms designed explicitly to perform different automatic classifications. These tools will be used and applied both on already available and acquired images during the project. An accompanying report describing the tools will be produced.

In this document, following the details on the dual-use items in the sense of Regulation (EC) 428/2009, or other items for which an authorisation is needed, which has been included in the Grant Agreement, further details regarding the use of Unmanned Aerial Vehicle and Underwater Autonomous Vehicles that will be used in demonstrations, and their required authorisations is reported.

Existing European observation tools and services have the potential to take advantage of cutting-edge technologies to obtain a wide range of data at a much higher spatial resolution and temporal regularity and duration. The EU-funded NAUTILOS project will develop a new generation of sensors and samplers for physical, chemical, and biological essential ocean variables in addition to micro- and nano-plastics. The project will improve our understanding of environmental variations and anthropogenic impacts connected with aquaculture, fisheries, and marine litter. The project will integrate recently advanced marine technologies into different observing platforms and deploy them through innovative and cost-effective methods in a wide range of key environmental settings and EU policy-related applications. The project aims to complement and expand existing European observation instruments and services and further enable and democratise the monitoring of the marine environment for both traditional and non-traditional data users.

This document is intended to provide recommendation on the procedures of the Information Systems and is inspired by the principles of correctness and diligence and is adopted in compliance with the provisions contained in the Privacy code and in the General Data Protection Regulation of the European Union.

In this deliverable the Data Management Plan (DMP) of the project will be written, in compliance with the H2020 Data Management Guidelines, also based on inputs from WP8. It will outline a data management policy, including data to be generated by the project, their potential exploitation, curation and storage. Additionally, in line with the principles of Open Access to research data and publications generated through H2020 programmes, NAUTILOS will participate in the Open Research Data Pilot carried out by the European Commission.

This deliverable describes the general nature of the experiments with animals and the procedures that will be performed within NAUTILOS, in order to ensure animal welfare and adherence to EU Directive 2010/63/EU and the Three Rs guidelines principle. Moreover, information about existing expertise and experiences of the involved partners are reported.

The objective of our work is to detect and classify mesoscale patterns in an upwelling ecosystem by analysing Sea Surface Temperature (SST) maps coming from satellite data. The poster shows how we organize this information in a "spaghetti plot", a tool that we use to analyse different trends of the SST in a target area for a period of time, and how we can associate those trends with different mesoscale patterns.

The deliverable presents and discusses the procedures and measures to mitigate environmental risks happening during the Project. Moreover, the application of health and safety procedures, conforming to the relevant guidelines and legislations are described, together with the measures minimising impact on endangered species or protected areas involved in the project activities.

Remote sensing plays a crucial role in the supervision of extended maritime areas. In particular, multisensor multisource imagery is collected daily through satellite platforms moving on earth-centered orbits. This massive amount of data, including optical images and radar maps, can be exploited for relevant purposes, such as the implementation of maritime surveillance tasks. These tasks typically address security and safety issues (vessel traffic monitoring, search and rescue) as well as environmental sustainability aspects (fishery, pollution). Satellite missions also serve the purpose of remotely measuring meaningful properties of the water column (e.g., salinity, turbidity, pollutants concentration), enabling chemophysical surveys of maritime areas of interest. Publications in this Special Issue will aim at composing a comprehensive overview of the several aspects that emerge in the implementation of maritime observation platforms through data processing. With these topics in mind, among various other subjects, the authors are invited to discuss theoretical issues and methods concerning remote sensing and data processing over the marine and maritime environment (such as software platforms for surveillance or monitoring, processing algorithms for radar or optical imagery, sea-level assessment through satellite altimetry, integrated methods for the observation of the maritime environment, etc.), not excluding application case studies focused on remote sensing within the maritime context. To this purpose, authors are invited to submit contributions that take into consideration the following topics: Maritime data representation, analysis, and learning, Ocean observation applied to fishing sustainability or biodiversity, Techniques for data processing applied to maritime observation, Target detection, classification, and identification in maritime data, Marine pollution monitoring along with sea environment monitoring issues, Open water analysis and trends based on remote sensing.

The procedures and criteria that will be used to identify/recruit research participants, as well as the informed consent procedures that will be implemented for the participation of humans external to NAUTILOS to the project activities and in regard to their data processing are presented in this document. Templates of the informed consent/assent forms and information sheets covering the voluntary participation and data protection issues, in the English version are provided.

This deliverable is relative to the Ethics Requirement n. 13 as a General requirement to keep copies of relevant authorisations for the usage of both Unmanned Aerial Vehicles (UAVs) and Underwater Autonomous Vehicles (AUVs). Those authorisations will be kept on file and made available to the EC Agency upon request.

This deliverable describes the ethical issues concerning the research performed outside the EU, both in terms of ethical compliance with EU standards, and in terms of the detail of the materials that will be imported/exported from and to non-EU countries to a member state.

An annual report and evaluation provided by the External Advisory Board providing their overall assessment of NAUTILOS and advice on the future direction of the project. The following deliverable will be the report following their meeting after MM3 in M12.