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This dataset includes the annotated metabarcoding Amplicon Sequence Variants (ASVs) resulting from the analysis of environmental DNA (eDNA) collected as water samples in the area of Marina di Camerota (Campania region, Italy) and filtered in loco by citizens. The first sheet includes sequence information, relative abundance and taxonomic annotation of the organisms identified using the hypervariable region V4 of the nuclear 18S rRNA; the second sheet includes the same information but for organisms (metazoans) identified using a fragment of the mitochondrial COI gene. Data were sequenced at the Sequencing facility of the SZN (RIMAR Dept.) using the GeneStudio S5 and processed through the dada2 pipeline. The dataset was produced during the Citizen Science Initiative Integrating biodiversity monitoring and awareness-raising in coastal peripheries, by engaging citizen-science sailors as focal nodes in the process of local community empowerment (Acronym: BIOMARCS; Nickname: Reknotting Marine Biodiversity) funded by the European project IMPETUS (https://impetus4cs.eu/; Grant agreement ID: 101058677; DOI: 10.3030/101058677). IMPETUS is funded by the European Union's Horizon Europe research and innovation programme under grant agreement number 101058677. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

This is the December 2023 edition of the OCEAN:ICE Newsletter. The original newsletter is posted on the OCEAN:ICE LinkedIn. For those who do not have access to LinkedIn, we upload the newsletter to Zenodo and the website.

The KM3NeT Collaboration is building and operating two deep sea neutrino telescopes at the bottom of the Mediterranean Sea. The telescopes consist of latices of photomultiplier tubes housed in pressure-resistant glass spheres, called digital optical modules and arranged in vertical detection units. The two main scientific goals are the determination of the neutrino mass ordering and the discovery and observation of high-energy neutrino sources in the Universe. Neutrinos are detected via the Cherenkov light, which is induced by charged particles originated in neutrino interactions. The photomultiplier tubes convert the Cherenkov light into electrical signals that are acquired and timestamped by the acquisition electronics. Each optical module houses the acquisition electronics for collecting and timestamping the photomultiplier signals with one nanosecond accuracy. Once finished, the two telescopes will have installed more than six thousand optical acquisition nodes, completing one of the more complex networks in the world in terms of operation and synchronization. The embedded software running in the acquisition nodes has been designed to provide a framework that will operate with different hardware versions and functionalities. The hardware will not be accessible once in operation, which complicates the embedded software architecture. The embedded software provides a set of tools to facilitate remote manageability of the deployed hardware, including safe reconfiguration of the firmware. This paper presents the architecture and the techniques, methods and implementation of the embedded software running in the acquisition nodes of the KM3NeT neutrino telescopes. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Questo riassunto visuale, disegnato da Jacopo Sacquegno, riassume l'iniziativa di citizen science, o scienza partecipativa "Riannodiamo la biodiversità marina" (Titolo esteso: Integrating biodiversity monitoring and awareness-raising in coastal peripheries, by engaging citizen-science sailors as focal nodes in the process of local community empowerment; acronimo: BIOMARCS; nome alternativo: Reknotting Marine Biodiversity), finanziata dal progetto europeo IMPETUS* (https://impetus4cs.eu/; Grant agreement ID: 101058677; DOI: 10.3030/101058677) L'iniziativa coinvolge i velisti delle aree costiere periferiche nella co-progettazione, creazione e gestione di un monitoraggio opportunistico dell'ecosistema marino e della sua biodiversità attraverso tecniche di analisi del DNA ambientale (eDNA). Gli stessi velisti contribuiscono a diffondere e comunicare i dati acquisiti sulla biodiversità tra più parti interessate (ad esempio, studenti delle scuole superiori e gestori di AMP), per rendere "visibile" il patrimonio di biodiversità e rafforzare il senso del luogo e la consapevolezza dell'importanza della salute degli oceani per il benessere delle società umane. *IMPETUS is funded by the European Union's Horizon Europe research and innovation programme under grant agreement number 101058677. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

Computational fluid dynamics (CFD) is an important tool for the simulation of the cardiovascular function and dysfunction. Due to the complexity of the anatomy, the transitional regime of blood flow in the heart, and the strong mutual influence between the flow and the physical processes involved in the heart function, the development of accurate and efficient CFD solvers for cardiovascular flows is still a challenging task. In this paper we present lifex-cfd, an open-source CFD solver for cardiovascular simulations based on the lifex finite element library, written in modern C++ and exploiting distributed memory parallelism. We model blood flow in both physiological and pathological conditions via the incompressible Navier-Stokes equations, accounting for moving cardiac valves, moving domains, and transition-to-turbulence regimes. In this paper, we provide an overview of the underlying mathematical formulation, numerical discretization, implementation details and examples on how to use lifex-cfd. We verify the code through rigorous convergence analyses, and we show its almost ideal parallel speedup. We demonstrate the accuracy and reliability of the numerical methods implemented through a series of idealized and patient-specific vascular and cardiac simulations, in different physiological flow regimes. The lifex-cfd source code is available under the LGPLv3 license, to ensure its accessibility and transparency to the scientific community, and to facilitate collaboration and further developments. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

EAT is a flexible and extensible software package that enables data assimilation of physical and biogeochemical variables in a one-dimensional water column. EAT builds on established open-source components for hydrodynamics (GOTM), biogeochemistry (FABM) and data assimilation (PDAF). It is easy to install and operate, and flexible through support for user-written plugins. EAT is well suited to explore and advance the state-of-the-art in DA in natural waters thanks to its support for: strongly and weakly coupled data assimilation observations describing any prognostic and diagnostic element of the physical-biogeochemical model estimation of biogeochemical parameters. On Windows, Mac and Linux systems with Anaconda or Miniconda, EAT can be installed with conda create -n eat -c bolding-bruggeman -c conda-forge eatpy. It is then not necessary to download and compile the source code. This record contains the EAT source code. It can be compiled and installed as described on the wiki.

Surface ocean fugacity of CO2 (fCO2) and air-sea CO2 flux data from individual Global Ocean Biogeochemistry Models (GOBMs) and surface ocean fCO2-based data-products (fCO2-products).There are three types of files: (1) one file per fCO2-product with gridded fields and regionally-integrated CO2 flux time-series, (2) one file per GOBM with gridded fields, and (3) one file with the regionally-integrated time-series for the GOBMs. Note: These provided gridded outputs from fCO2-based data-products and GOBMs are regridded datasets, without adjustments. The best estimates of the annual global ocean carbon sink, based on the native grids of fCO2-products and GOBMs and with the adjustments described in the Global Carbon Budget 2023 (https://doi.org/10.5194/essd-15-5301-2023), are available in the Global Carbon Budget 2023 spreadsheet. The regionally-integrated time-series are as provided by the contributing groups, i.e. integrated from their native grids. In order to reproduce Figure 13 of the Global Carbon Budget 2023 paper (https://doi.org/10.5194/essd-15-5301-2023), the river flux adjustment needs to be added to the CO2 flux estimated from the data-products (North: 0.14 GtC yr-1, Tropics: 0.42 GtC yr-1, South: 0.09 GtC yr-1, see GCB 2023 paper, section 2.5.1). The sum of the regional fluxes may differ from the global estimates as reported in the GCB spreadsheet, because some adjustments were applied only for global fluxes. What is in the files? (1) The files for the fCO2-based data-products contain the following variables (temporal resolution: monthly):fgco2_reg: Regionally integrated air-sea CO2 flux (positive downward), monthly, for regions: north, tropics, southfgco2: Flux density of the total air-sea CO2 flux (positive downward), dimensions: time, latitude, longitudesfco2: Surface ocean fCO2, dimensions: time, latitude, longitudearea: Area per pixel, dimensions: latitude, longitudearea_reg: Total surface ocean area covered by native grid, for global, north, tropics, south (2) The files for the GOBMs contain the following fields, for simulation A ('contemporary simulation', including effects of rising CO2, climate change and variability) and simulation B ('control simulation', constant CO2, no climate change and variability). Temporal resolution: monthly fgco2: Flux density of the total air-sea CO2 flux (positive downward), dimensions: time, latitude, longitudesfco2: Surface ocean fCO2, dimensions: time, latitude, longitudearea: Area per pixel, dimensions: latitude, longitude(3) One file 'GCB-2023_OceanModel_RegionalBreakdown_1959-2022.nc' with the regionally-integrated CO2 flux time-series for all individual GOBMs, and for simulations A and B. Temporal resolution: annual. Fair data use statement:The data and model output provided on this site are freely available and were furnished by individual scientists who encourage their use.Citation: Please cite the Global Carbon Budget 2023 (Friedlingstein et al., 2023, ESSD, https://doi.org/10.5194/essd-15-5301-2023) for all data. In addition, please also cite the corresponding original reference for each dataset that has been used - see Table 4 in Global Carbon Budget 2023 for references of all the individual Global Ocean Biogeochemical Models and fCO2-based data-products. Further, for an overview of the Global Ocean Biogeochemical Model output, you may find it useful to cite Hauck et al. (2020, Frontiers, doi:10.3389/fmars.2020.571720).Acknowledgement: Please add the following text in the acknowledgement of your paper: "We acknowledge the Global Carbon Project, which is responsible for the Global Carbon Budget and we thank the ocean modeling and fCO2-mapping groups for producing and making available their model and fCO2-product output."Co-authorship: An invitation of co-authorship to the contributing groups is encouraged if these data are the central data set of the publication. Besides the surface fCO2 and air-sea CO2 flux data that is made available open access, we make additional 3D output from the Global Ocean Biogeochemical models (GCB-ocean) available upon request and with its own data policy. Please refer to the Global Carbon Budget website for these additional data: https://globalcarbonbudgetdata.org/closed-access-requests.html