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This scoring sheet was developed to collect data on the larval rearing methodology which is followed by commercial finfish hatcheries. It was used by Kourkouta et al. [Sci Rep. 2022 Oct 25;12(1):17896. doi: 10.1038/s41598-022-23008-z] to examine the link between the variability in the rearing conditions, and the variability in skeletal abnormalities incidence.

Computer Vision has played a major role in Intelligent Transportation Systems (ITS) and traffic surveillance. Along with the rapidly growing automated vehicles and crowded cities, the automated and advanced traffic management systems (ATMS) using video surveillance infrastructures have been evolved by the implementation of Deep Neural Networks. In this research, we provide a practical platform for real-time traffic monitoring, including 3D vehicle/pedestrian detection, speed detection, trajectory estimation, congestion detection, as well as monitoring of the interaction of vehicles and pedestrians, all using a single CCTV traffic camera. We adapt a custom YOLOv5 deep neural network model for vehicle/pedestrian detection and an enhanced SORT tracking algorithm. For the first time, a hybrid satellite-ground based inverse perspective mapping (SG-IPM) method for camera auto-calibration is also developed which leads to an accurate 3D object detection and visualisation. We also develop a hierarchical traffic modelling solution based on short- and long-term temporal video data streams to understand the traffic flow, bottlenecks, and risky spots for vulnerable road users. Several experiments on real-world scenarios and comparisons with state-of-the-art are conducted using various traffic monitoring datasets, including MIO-TCD, UA-DETRAC and GRAM-RTM collected from highways, intersections, and urban areas under different lighting and weather conditions.Computer Vision has played a major role in Intelligent Transportation Systems (ITS) and traffic surveillance. Along with the rapidly growing automated vehicles and crowded cities, the automated and advanced traffic management systems (ATMS) using video surveillance infrastructures have been evolved by the implementation of Deep Neural Networks. In this research, we provide a practical platform for real-time traffic monitoring, including 3D vehicle/pedestrian detection, speed detection, trajectory estimation, congestion detection, as well as monitoring the interaction of vehicles and pedestrians, all using a single CCTV traffic camera. We adapt a custom YOLOv5 deep neural network model for vehicle/pedestrian detection and an enhanced SORT tracking algorithm. For the first time, a hybrid satellite-ground based inverse perspective mapping (SG-IPM) method for camera auto-calibration is also developed which leads to an accurate 3D object detection and visualisation. We also develop a hierarchical traffic modelling solution based on short- and long-term temporal video data streams to understand the traffic flow, bottlenecks, and risky spots for vulnerable road users. Several experiments on real-world scenarios and comparisons with state-of-the-art are conducted using various traffic monitoring datasets, including MIO-TCD, UA-DETRAC and GRAM-RTM collected from highways, intersections, and urban areas under different lighting and weather conditions.

The documents in these folders represent part of the qualitative data collection documentation. Research has been performed in Flanders (Belgium) in 2016 and 2017. Involved stakehodlers were flemish sugar beet farmers, processors as well as other value chain members. Though, the main stakeholders involved were farmers. The raw data cannot be published. Anonymized interview transcripts and focus group transcripts exist. However, as indicated in the informed consent, farmers did not agree to the raw data being published. The codes that resulted from data analysis are in this folder. Interview questions differed slightly from farmer to farmer as follow up questions may have been posed if needed. First interviews were performed, then focus groups were conducted and finally a workshop was organized. The qualitative reserach followed the research strategy and plan determined by the SUFISA project. On the project webpage (https://www.sufisa.eu/) more information can be found.

This is the English version of the informed consent that has been used for staekholder interactions. Similar forms have been used for focus groups and workshops.

This dataset contains the genotyping data obtained from RAD-sequencing of a panel of 223 Lupinus mutabilis accessions and the marker selection used to perform the genome-wide association study described in the publication "Investigating the potential of Andean lupin as a lignocellulosic feedstock for Europe: first genome-wide association study on L. mutabilis biomass quality".

Il software VITA OLEI consente di stimare il termine minimo di conservazione dell’olio extra vergine di oliva sulla base di parametri compositivi del prodotto determinati mediante analisi chimiche e strumentali. Il software VITA OLEI può essere utile in particolare per produttori ed imbottigliatori di olio extra vergine di oliva allo scopo di stimarne la shelf-life. I dati, ovvero i risultati delle analisi di oli di oliva sottoposti ad uno studio di shelf-life, impiegati per la creazione del software, sono stati prodotti nell’ambito del progetto OLEUM nel task coordinato dall’Università degli Studi di Perugia. Requisiti tecnici: PC; Windows (64 bit) 7, 8, 10, 11; licenza software.

Evaluación de alternativas agrícolas con especies de gramíneas perennes para biomasa en tierras marginales

Solutions to current complex environmental challenges demand the consultation and involvement of various groups in society. In light of the WFD’s requirements of public participation, this paper presents an analysis of the establishment and development of nine different multi-actor platforms (MAPs) across Europe set up as arenas for long-term engagements to solve water quality challenges in relation to agriculture. The MAPs represent different histories and legacies of engagement some are recent initiatives and some are affiliated with previous government-initiated projects, while other MAPs are long-term engagement platforms. A case study approach rawing on insights from the nine engagement processes is used to discuss conditions for enabling long-term multi-actor engagement. The perceived pressure for change and preferred prioritization in complying with mitigating water quality problems vary within and among the MAPs. The results show that governmental and local actors’ concern for water quality improvements and focusing on pressure for change are important for establishing meaningful multi-actor engagement when concerns translate into a clear mandate of the MAP. Furthermore, the degree to which the MAPs have been able to establish relationships and networks with other institutions such as water companies, agricultural and environmental authorities, farmers, and civil society organizations influences possibilities for long-term meaningful engagement.

Ten innovative EU projects to build ocean observation systems that provide input for evidence-based management of the ocean and the Blue Economy, have joined forces in the strong cluster ‘Nourishing Blue Economy and Sharing Ocean Knowledge’. Under the lead of the EuroSea project, the group published a joint policy brief listing recommendations for sustainable ocean observation and management. The cooperation is supported by the EU Horizon Results Booster and enables the group to achieve a higher societal impact. The policy brief will be presented to the European Commission on 15 October 2021. The ocean covers 70% of the Earth’s surface and provides us with a diverse set of ecosystem services that we cannot live without or that significantly improve our quality of life. It is the primary controller of our climate, plays a critical role in providing the air we breathe and the fresh water we drink, supplies us with a large range of exploitable resources (from inorganic resources such as sand and minerals to biotic resources such as seafood), allows us to generate renewable energy, is an important pathway for world transport, an important source of income for tourism, etc. The Organisation for Economic Cooperation and Development (OECD) evaluates the Blue Economy to currently represent 2.5% of the world economic value of goods and services produced, with the potential to further double in size by 2030 (seabed mining, shipping, fishing, tourism, renewable energy systems and aquaculture will intensify). However, the overall consequences of the intensification of human activities on marine ecosystems and their services (such as ocean warming, acidification, deoxygenation, sea level rise, changing distribution and abundance of fish etc.) are still poorly quantified. In addition, on larger geographic and temporal scales, marine data currently appear fragmented, are inhomogeneous, contain data gaps and are difficult to access. This limits our capacity to understand the ocean variability and sustainably manage the ocean and its resources. Consequently, there is a need to develop a framework for more in-depth understanding of marine ecosystems, that links reliable, timely and fit-for-purpose ocean observations to the design and implementation of evidence-based decisions on the management of the ocean. To adequately serve governments, societies, the sustainable Blue Economy and citizens, ocean data need to be collected and delivered in line with the Value Chain of Ocean Information: 1) identification of required data; 2) deployment and maintenance of instruments that collect the data; 3) delivery of data and derived information products; and 4) impact assessment of services to end users. To provide input to the possible future establishment of such a framework, ten innovative EU projects to build user-focused, interdisciplinary, responsive and sustained ocean information systems and increase the sustainability of the Blue Economy, joined forces in a strong cluster to better address key global marine challenges. Under the lead of the EuroSea project, the group translated its common concerns to recommendations and listed these in the joint policy brief ‘Nourishing Blue Economy and Sharing Ocean Knowledge. Ocean Information for Sustainable Management.’. Following up on these recommendations will strengthen the entire Value Chain of Ocean Information and ensure sound sustainable ocean management. In this way, the 10 projects jointly strive to achieve goals set out in the EU Green Deal, the Paris Agreement (United Nations Framework Convention on Climate Change) and the United Nations 2021-2030 Decade of Ocean Science for Sustainable Ocean Development. Toste Tanhua (GEOMAR), EuroSea coordinator: “It was great to collaborate with these other innovative projects and make joint recommendations based on different perspectives and expertise.”