Contextual word embedding models, such as BioBERT and Bio_ClinicalBERT, have achieved state-of-the-art results in biomedical natural language processing tasks by focusing their pre-training process on domain-specific corpora. However, such models do not take into consideration structured expert domain knowledge from a knowledge base.We introduce UmlsBERT, a contextual embedding model that integrates domain knowledge during the pre-training process via a novel knowledge augmentation strategy. More specifically, the augmentation on UmlsBERT with the Unified Medical Language System (UMLS) Metathesaurus is performed in two ways: (i) connecting words that have the same underlying 'concept' in UMLS and (ii) leveraging semantic type knowledge in UMLS to create clinically meaningful input embeddings. By applying these two strategies, Umls-BERT can encode clinical domain knowledge into word embeddings and outperform existing domain-specific models on common namedentity recognition (NER) and clinical natural language inference tasks.

(1) Background: Spain, Italy, and Greece are the world's top olive oil producers. In recent decades, these countries have gradually diversified their farming system in the olive groves. The element of innovation with respect to the state of the art is that this paper aims to compare the environmental performance of different farming systems in a European context by performing a simplified Life Cycle Assessment; (2) Methods: Environmental performance was calculated according to the methodology of Life Cycle Assessment and the "Guidance for the implementation of the Product Environmental Footprint (PEF)". Average data were considered in order to describe a system with a great degree of complexity and high spatial heterogeneity; (3) Results: The study highlights the difficulty of identifying the farming method that presents the best environmental performance in each of the impact categories considered. In Greece, the lowest use of diesel, electricity, and water brings about advantages for many impact categories, albeit with low yields. While the highest olive yield obtained in Italy has positive consequences in terms of global warming, the highest use of fertilisers, in many cases, entails higher environmental impacts. On the other hand, in Spain the highest use of organo-phosphorous pesticides entails the highest impacts of eco-toxicity; (4) Conclusion: the reduction of the use of fertilizers and pesticides, as well as water conservation, are important issues which require the optimization of timing and techniques in order to achieve environmental advantages.

Urban road networks are represented as directed graphs, accompanied by a metric which assigns cost functions (rather than scalars) to the arcs, e.g. representing time-dependent arc-traversal-times. In this work, we present oracles for providing time-dependent min-cost route plans, and conduct their experimental evaluation on a real-world data set (city of Berlin). Our oracles are based on precomputing all landmark-to-vertex shortest travel-time functions, for properly selected landmark sets. The core of this preprocessing phase is based on a novel, quite efficient and simple oneto-all approximation method for creating approximations of shortest travel-time functions. We then propose three query algorithms, including a PTAS, to efficiently provide mincost route plan responses to arbitrary queries. Apart from the purely algorithmic challenges, we deal also with several implementation details concerning the digestion of raw traffic data, and we provide heuristic improvements of both the preprocessing phase and the query algorithms. We conduct an extensive, comparative experimental study with all query algorithms and six landmark sets. Our results are quite encouraging, achieving remarkable speedups (at least by two orders of magnitude) and quite small approximation guarantees, over the time-dependent variant of Dijkstra's algorithm. * Partially supported by EU FP7/2007-2013 under grant agreements no. 288094 (eCOMPASS) and no. 609026 (MOVESMART), and partially done while S. Kontogiannis and C. Zaroliagis were visiting the Karlsruhe Institute of Technology (KIT).

We implement and experimentally evaluate landmarkbased oracles for min-cost paths in two different types of road networks with time-dependent arc-cost functions, based on distinct real-world historic traffic data: the road network for the metropolitan area of Berlin, and the national road network of Germany.Our first contribution is a significant improvement on the implementation of the FLAT oracle, which was proposed and experimentally tested in previous works. Regarding the implementation, we exploit parallelism to reduce preprocessing time and real-time responsiveness to live-traffic reports. We also adopt a lossless compression scheme that severely reduces preprocessing space and time requirements. As for the experimentation, apart from employing the new data set of Germany, we also construct several refinements and hybrids of the most prominent landmark sets for the city of Berlin. A significant improvement to the speedup of FLAT is observed: For Berlin, the average query time can now be as small as 83µsec, achieving a speedup (against the timedependent variant of Dijkstra's algorithm) of more than 1, 119 in absolute running times and more than 1, 570 in Dijkstra-ranks, with worst-case observed stretch less than 0.781%. For Germany, our experimental findings are analogous: The average query-response time can be 1.269msec, achieving a speedup of more than 902 in absolute running times, and 1, 531 in Dijkstra-ranks, with worst-case stretch less than 1.534%.Our (HORN). It is based on a hierarchy of landmarks, with a few "global" landmarks at the top level possessing travel-time information for all possible destinations, and many more "local" landmarks at lower levels possessing travel-time information only for a small neighborhood of destinations around them. As it was previously proved, the advantage of HORN over FLAT is that it achieves query times sublinear, not just in the size of the network, but in the Dijkstra-rank of the query at hand, while requiring asymptotically similar preprocessing space and time. Our experimentation of HORN in Berlin indeed demonstrates improvements in query times (more than 30.37%), Dijkstra-ranks (more than 39.66%), and also worst-case error (more than 35.89%), at the expense of a small blow-up in space.Finally, we implement and experimentally test a dynamic scheme to provide responsiveness to live-traffic reports of incidents with a small timelife (e.g., a temporary blockage of a road segment due to an accident). Our experiments also indicate that the traffic-related information can be updated in seconds.

As a part of the development of the Environmental Footprint (EF) guidelines, in June 2014 the European Commission started 11 pilot projects for the development of Product Environmental Footprint Category Rules (PEFCRs) for food, feed and beverage products. The PEFCRs are developed by technical secretariats involving various stakeholders from industries, academia, governments, trade unions and non-governmental organisations. This paper presents the state of the art of developing the PEFCR for the olive oil sector. The functional unit is defined as a litre of packed olive oil and the system boundaries cover the whole supply chain from cradle-to-grave. A screening study that estimated the EF of the average olive oil consumed in the European markets showed that olive production phase had the highest contribution to most environmental impact categories. The results of the screening study provide a benchmark that will be further adjusted after the current draft PEFCR will be tested in case studies for real products.