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The role of nitrogen in achieving sustainable food systems for healthy diets

2020, Leip, Adrian, Bodirsky, Benjamin Leon, Kugelberg, Susanna

The ‘food system’ urgently needs a sustainable transformation. Two major challenges have to be solved: the food system has to provide food security with healthy, accessible, affordable, safe and diverse food for all, and it has to do so within the safe operating space of the planetary boundaries, where the pollution from reactive nitrogen turned out to be the largest bottleneck. Here we argue that thinking strategically about how to balance nitrogen flows throughout the food system will make current food systems more resilient and robust. Looking from a material and a governance perspective on the food system, we highlight major nitrogen losses and policy blind spots originating from a compartmentalization of food system spheres. We conclude that a participatory and integrated approach to manage nitrogen flows throughout the food system is necessary to stay within regional and global nitrogen boundaries, and will additionally provide synergies with a sustainable and healthy diet for all. © 2020 The Authors

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Raman LIDAR for UHECR experiments: an overview of the L'Aquila (Italy) lidar station experience for the retrieval of quality-assured data

2017, Iarlori, Marco, Rizi, Vincenzo, D’Amico, Giuseppe, Freudenthaler, Volker, Wandinger, Ulla, Grillo, Aurelio, Trávníček, P., Prouza, M., Gaug, M., Keilhauer, B.

L'Aquila (Italy) lidar station is part of the EARLINET (European Aerosol Research Lidar Network) since its beginning in the 2000. In the EARLINET community great efforts are devoted to the quality-assurance of the aerosol optical properties inserted in the database. To this end, each lidar station performed intercomparisons with reference instruments, a series of internal hardware checks in order to assess the quality of their instruments and exercises to test the algorithms used to retrieve the aerosol optical parameters. In this paper we give an overview of our experience within EARLINET qualityassurance (QA) program, which was adopted for the Raman lidar (RL) operated in the AUGER Observatory. This program could be systematically adopted for the lidar systems needed for the current and upcoming UHECR experiments, like CTA (Cherenkov Telescope Array).

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Open Research Knowledge Graph

2024-05-07, Auer, Sören, Ilangovan, Vinodh, Stocker, Markus, Tiwari, Sanju, Vogt, Lars, Bernard-Verdier, Maud, D'Souza, Jennifer, Fadel , Kamel, Farfar, Kheir Eddine, Göpfert , Jan, Haris , Muhammad, Heger, Tina, Hussein, Hassan, Jaradeh, Yaser, Jeschke, Jonathan M., Jiomekong , Azanzi, Kabongo, Salomon, Karras, Oliver, Kuckertz, Patrick, Kullamann, Felix, Martin, Emily A., Oelen, Allard, Perez-Alvarez, Ricardo, Prinz, Manuel, Snyder, Lauren D., Stolten, Detlef, Weinand, Jann M.

As we mark the fifth anniversary of the alpha release of the Open Research Knowledge Graph (ORKG), it is both timely and exhilarating to celebrate the significant strides made in this pioneering project. We designed this book as a tribute to the evolution and achievements of the ORKG and as a practical guide encapsulating its essence in a form that resonates with both the general reader and the specialist. The ORKG has opened a new era in the way scholarly knowledge is curated, managed, and disseminated. By transforming vast arrays of unstructured narrative text into structured, machine-processable knowledge, the ORKG has emerged as an essential service with sophisticated functionalities. Over the past five years, our team has developed the ORKG into a vibrant platform that enhances the accessibility and visibility of scientific research. This book serves as a non-technical guide and a comprehensive reference for new and existing users that outlines the ORKG’s approach, technologies, and its role in revolutionizing scholarly communication. By elucidating how the ORKG facilitates the collection, enhancement, and sharing of knowledge, we invite readers to appreciate the value and potential of this groundbreaking digital tool presented in a tangible form. Looking ahead, we are thrilled to announce the upcoming unveiling of promising new features and tools at the fifth-year celebration of the ORKG’s alpha release. These innovations are set to redefine the boundaries of machine assistance enabled by research knowledge graphs. Among these enhancements, you can expect more intuitive interfaces that simplify the user experience, and enhanced machine learning models that improve the automation and accuracy of data curation. We also included a glossary tailored to clarifying key terms and concepts associated with the ORKG to ensure that all readers, regardless of their technical background, can fully engage with and understand the content presented. This book transcends the boundaries of a typical technical report. We crafted this as an inspiration for future applications, a testament to the ongoing evolution in scholarly communication that invites further collaboration and innovation. Let this book serve as both your guide and invitation to explore the ORKG as it continues to grow and shape the landscape of scientific inquiry and communication.