87 research outputs found

    Constraint satisfaction problems for reducts of homogeneous graphs

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    For n >= 3, let (Hn, E) denote the n-th Henson graph, i.e., the unique countable homogeneous graph with exactly those finite graphs as induced subgraphs that do not embed the complete graph on n vertices. We show that for all structures Gamma with domain Hn whose relations are first-order definable in (Hn, E) the constraint satisfaction problem for Gamma is either in P or is NP-complete. We moreover show a similar complexity dichotomy for all structures whose relations are first-order definable in a homogeneous graph whose reflexive closure is an equivalence relation. Together with earlier results, in particular for the random graph, this completes the complexity classification of constraint satisfaction problems of structures first-order definable in countably infinite homogeneous graphs: all such problems are either in P or NP-complete

    Bio-IGCC with CCS as a long-term mitigation option in a coupled energy-system and land-use model

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    This study analyses the impact of techno-economic performance of the BIGCC process and the effect of different biomass feedstocks on the technology's long term deployment in climate change mitigation scenarios. As the BIGCC technology demands high amounts of biomass raw material it also affects the land-use sector and is dependent on conditions and constraints on the land-use side. To represent the interaction of biomass demand and supply side the global energy-economy-climate model ReMIND is linked to the global land-use model MAgPIE. The link integrates biomass demand and price as well as emission prices and land-use emissions. Results indicate that BIGCC with CCS could serve as an important mitigation option and that it could even be the main bioenergy conversion technology sharing 33% of overall mitigation in 2100. The contribution of BIGCC technology to long-term climate change mitigation is much higher if grass is used as fuel instead of wood, provided that the grass-based process is highly efficient. The capture rate has to significantly exceed 60 % otherwise the technology is not applied. The overall primary energy consumption of biomass reacts much more sensitive to price changes of the biomass than to technoeconomic performance of the BIGCC process. As biomass is mainly used with CCS technologies high amounts of carbon are captured ranging from 130 GtC to 240 GtC (cumulated from 2005-2100) in different scenarios

    The STAR MAPS-based PiXeL detector

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    The PiXeL detector (PXL) for the Heavy Flavor Tracker (HFT) of the STAR experiment at RHIC is the first application of the state-of-the-art thin Monolithic Active Pixel Sensors (MAPS) technology in a collider environment. Custom built pixel sensors, their readout electronics and the detector mechanical structure are described in detail. Selected detector design aspects and production steps are presented. The detector operations during the three years of data taking (2014-2016) and the overall performance exceeding the design specifications are discussed in the conclusive sections of this paper

    Constraint satisfaction problems for reducts of homogeneous graphs

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    For n >= 3, let (H-n, E) denote the nth Henson graph, i.e., the unique countable homogeneous graph with exactly those finite graphs as induced subgraphs that do not embed the complete graph on n vertices. We show that for all structures Gamma with domain H-n whose relations are first-order definable in (H-n, E) the constraint satisfaction problem for F either is in P or is NP-complete. We moreover show a similar complexity dichotomy for all structures whose relations are first-order definable in a homogeneous graph whose reflexive closure is an equivalence relation. Together with earlier results, in particular for the random graph, this completes the complexity classification of constraint satisfaction problems of structures first-order definable in countably infinite homogeneous graphs: all such problems are either in P or NP-complete

    Complexity of Existential Positive First-Order Logic

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    Achieving Zero Hunger by 2030 A Review of Quantitative Assessments of Synergies and Tradeoffs amongst the UN Sustainable Development Goals

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    The Sustainable Development Goal 2 “Zero hunger” (SDG2) sets clear global targets for ensuring access to sufficient food and healthy nutrition for all by 2030, while keeping food systems within sustainable boundaries and protecting livelihoods. Yet, the current trends show the level of challenge ahead, especially as the COVID-19 pandemic worsens the global development prospects. Intrinsically, SDG2 presents some points of tension between its internal targets and brings some synergies but also strong trade-offs with other sustainable development goals. \textlessbr /\textgreater We summarize in this paper the main relations between SDG2 targets and the other development goals and explain how the modelling literature has analyzed the SDG interactions around “Zero hunger”. SDG2 integrates four ambitious objectives – adequate food, no malnutrition, in increased incomes for smallholders, greater sustainability – that will require careful implementation to be conducted in synergy. We show that the compatibility of these objectives will depend on the interplay of future food demand drivers and the contribution of productivity gains across the food system. \textlessbr /\textgreater Analyzing the SDGs’ interrelations reveals the strong synergies between SDG2 and some other basic subsistence goals, in particular, Goal 1 “No poverty” and Goal 3 “Good health and well- being”. These goals need to be jointly addressed in order to succeed in “Zero hunger”. Several other SDGs have been shown to be key enablers for SDG2, in particular on the socio-economic side. On the other hand, agricultural production substantially contributes to the risks of exceeding critical global sustainability thresholds. We illustrate how recent modelling work has shed light on the interface between future food and nutrition needs, and the various environmental dimensions. Specifically, several important SDGs have been shown to compete directly with SDG2 through their common demands for scarce natural resources – including land for climate (SDG13), for biodiversity (SDG15) and for cities (SDG11), as well as the provision of water, both for the environment and for human needs (SDG6). Quantitative assessments show that more efficient production systems and technologies, pricing of externalities, and integrated resource management can mitigate some of these tradeoffs, but are unlikely to succeed in resolving these altogether. \textlessbr /\textgreater The success of achieving SDG2 in the face of these challenges will require new investments, smoothly functioning trade and effective markets, as well as changes in consumption patterns. Forward-looking analyses of global food systems indicate that deep transformations combining various measures will be needed to simultaneously achieve SDG2 targets while remaining within the planetary boundaries. These require fundamental changes, both on the supply side and on the demand side, and highlight the importance of SDG12 on “responsible production and consumption”

    The impact of high-end climate change on agricultural welfare

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    Climate change threatens agricultural productivity worldwide, resulting in higher food prices. Associated economic gains and losses differ not only by region but also between producers and consumers and are affected by market dynamics. On the basis of an impact modeling chain, starting with 19 different climate projections that drive plant biophysical process simulations and ending with agro-economic decisions, this analysis focuses on distributional effects of high-end climate change impacts across geographic regions and across economic agents. By estimating the changes in surpluses of consumers and producers, we find that climate change can have detrimental impacts on global agricultural welfare, especially after 2050, because losses in consumer surplus generally outweigh gains in producer surplus. Damage in agriculture may reach the annual loss of 0.3% of future total gross domestic product at the end of the century globally, assuming further opening of trade in agricultural products, which typically leads to interregional production shifts to higher latitudes. Those estimated global losses could increase substantially if international trade is more restricted. If beneficial effects of atmospheric carbon dioxide fertilization can be realized in agricultural production, much of the damage could be avoided. Although trade policy reforms toward further liberalization help alleviate climate change impacts, additional compensation mechanisms for associated environmental and development concerns have to be considered

    Focus on reactive nitrogen and the UN sustainable development goals

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    The scientific evidence assembled in this Focus Collection on 'Reactive nitrogen and the UN sustainable development goals' emphasizes the relevance of agriculture as a key sector for nitrogen application as well as its release to the environment and the observed impacts. Published work proves the multiple connections and their causality, and presents pathways to mitigate negative effects while maintaining the benefits, foremost the production of food to sustain humanity. Providing intersections from field to laboratory studies and to modelling approaches, across multiple scales and for all continents, the Collection displays an overview of the state of nitrogen science in the early 21st century. Extending science to allow for policy-relevant messages renders the evidence provided a valuable basis for a global assessment of reactive nitrogen

    Global consequences of afforestation and bioenergy cultivation on ecosystem service indicators

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    Land management for carbon storage is discussed as being indispensable for climate change mitigation because of its large potential to remove carbon dioxide from the atmosphere, and to avoid further emissions from deforestation. However, the acceptance and feasibility of land-based mitigation projects depends on potential side effects on other important ecosystem functions and their services. Here, we use projections of future land use and land cover for different land-based mitigation options from two land-use models (IMAGE and MAgPIE) and evaluate their effects with a global dynamic vegetation model (LPJ-GUESS). In the land-use models, carbon removal was achieved either via growth of bioenergy crops combined with carbon capture and storage, via avoided deforestation and afforestation, or via a combination of both. We compare these scenarios to a reference scenario without land-based mitigation and analyse the LPJ-GUESS simulations with the aim of assessing synergies and trade-offs across a range of ecosystem service indicators: carbon storage, surface albedo, evapotranspiration, water runoff, crop production, nitrogen loss, and emissions of biogenic volatile organic compounds. In our mitigation simulations cumulative carbon storage by year 2099 ranged between 55 and 89 GtC. Other ecosystem service indicators were influenced heterogeneously both positively and negatively, with large variability across regions and land-use scenarios. Avoided deforestation and afforestation led to an increase in evapotranspiration and enhanced emissions of biogenic volatile organic compounds, and to a decrease in albedo, runoff, and nitrogen loss. Crop production could also decrease in the afforestation scenarios as a result of reduced crop area, especially for MAgPIE land-use patterns, if assumed increases in crop yields cannot be realized. Bioenergy-based climate change mitigation was projected to affect less area globally than in the forest expansion scenarios, and resulted in less pronounced changes in most ecosystem service indicators than forest-based mitigation, but included a possible decrease in nitrogen loss, crop production, and biogenic volatile organic compounds emissions

    SOWL QL: Querying Spatio - Temporal Ontologies in OWL

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    We introduce SOWL QL, a query language for spatio-temporal information in ontologies. Buildingupon SOWL (Spatio-Temporal OWL), an ontology for handling spatio-temporal information in OWL, SOWL QL supports querying over qualitative spatio-temporal information (expressed using natural language expressions such as “before”, “after”, “north of”, “south of”) rather than merely quantitative information (exact dates, times, locations). SOWL QL extends SPARQL with a powerful set of temporal and spatial operators, including temporal Allen topological, spatial directional and topological operations or combinations of the above. SOWL QL maintains simplicity of expression and also, upward and downward compatibility with SPARQL. Query translation in SOWL QL yields SPARQL queries implying that, querying spatio-temporal ontologies using SPARQL is still feasible but suffers from several drawbacks the most important of them being that, queries in SPARQL become particularly complicated and users must be familiar with the underlying spatio-temporal representation (the “N-ary relations” or the “4D-fluents” approach in this work). Finally, querying in SOWL QL is supported by the SOWL reasoner which is not part of the standard SPARQL translation. The run-time performance of SOWL QL has been assessed experimentally in a real data setting. A critical analysis of its performance is also presented
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