scholarly journals High Resolution Bottom-up Residential Electrical Model For Distribution Networks Planning

Author(s):  
Simon Sansregret ◽  
Karine Lavigne ◽  
Brice Le Lostec ◽  
Laurencelle Francois ◽  
Frederic Guay
Author(s):  
Diego Arnone ◽  
Marzia Mammina ◽  
Salvatore Favuzza ◽  
Mariano G. Ippolito ◽  
Eleonora Riva Sanseverino ◽  
...  

PROTEOMICS ◽  
2017 ◽  
Vol 17 (23-24) ◽  
pp. 1600321 ◽  
Author(s):  
Kira Vyatkina ◽  
Lennard J. M. Dekker ◽  
Si Wu ◽  
Martijn M. VanDuijn ◽  
Xiaowen Liu ◽  
...  

2020 ◽  
Author(s):  
Dominique Arrouays ◽  
Zamir Libohova ◽  
Budiman Minansny ◽  
Vera Leatitia Mulder ◽  
Laura Poggio ◽  
...  

<p>Soils have critical relevance to global issues, such as food and water security, climate regulation, sustainable energy, desertification and biodiversity protection. All these examples require accurate national soil property information and there is a need to scientific support to develop reliable baseline soil information and pathways for measuring and monitoring soils. Soil sustainable management is a global issue, but effective actions require high-resolution data about soil properties. Two projects, GlobalSoilMap and SoilGrids, aim at delivering the first generation of high-resolution soil property grids for the globe, the first one by a bottom-up approach (from country to globe), the latter by top-down (global). The GLobAl Digital SOIL MAP (GLADSOILMAP) consortium brings together world scientific leaders involved in both projects. The consortium aims at developing and transferring methods to improve the prediction accuracy of soil properties and their associated uncertainty, by using legacy soil data and ancillary spatial information. This approach brings together new technologies and methods, existing soil databases and expert knowledge. The consortium aims at transferring methods to achieve convergence between top-down and bottom-up approaches, and to generate methods for delivering maps of soil properties. These maps are essential for communities from climate and environmental modeling to decision making and sustainable resources management at a scale that is relevant to soil management. The consortium will ensure links with the numerous actors in geosciences of the world, and will contribute to improving their skills in digital mapping and their national and international legibility. The actions include 4 main Work Packages (WP) subdivided into several tasks that are summarized below:</p><p> </p><p>WP0 Management of the project</p><p>WP1 Legacy and ancillary data for Digital Soil Mapping (DSM)</p><p>Test the potential of new ancillary data for DSM</p><p>Explore methodologies to merge and/or harmonize different products</p><p>Propose methods for harmonizing products to a common date</p><p> </p><p>WP2 Methods for sampling, modelling and mapping soils in space and time</p><p>Testing and developing new methods/models for prediction</p><p>Testing methods for estimating complete probability distribution</p><p> </p><p>WP3 Methods for estimating model and map uncertainty</p><p>Develop methods of uncertainty spatial assessment</p><p>Develop methods do deal with censored data/soft data</p><p>Solve the question of influence on the age of the rescued soil data on predictions</p><p> </p><p>WP4 Scientific outreach and capacity building</p><p>Produce an exhaustive review of GlobalSoilMap initiatives and results all over the world</p><p>Revise and update the GlobalSoilMap specifications by keeping them at the state-of-the-art level</p><p>Show relevance of gridded, Global, DSM by use cases and communication to end users</p><p> </p><p>The added value of the consortium is to allow a direct scientific exchange between members that should result in synthesis papers, in the identification of the major knowledge gaps, and in extending, deepening and disseminating knowledge of DSM, with the final aim to contribute to the achievement of global soil maps. Another added value of the consortium will certainly be to foster the creation of new ideas.</p><p> </p><p>Acknowledgements: the Consortium GLADSOILMAP is supported by LE STUDIUM Loire Valley Institute for Advanced studies.</p>


2016 ◽  
Author(s):  
Daniel R. Garza ◽  
Marcel C. Van Verk ◽  
Martijn A. Huynen ◽  
Bas E. Dutilh

AbstractThe environmental metabolome is a dominant and essential factor shaping microbial communities. Thus, we hypothesized that metagenomic datasets could reveal the quantitative metabolic status of a given sample. Using a newly developed bottom-up ecology algorithm, we predicted high-resolution metabolomes of hundreds of metagenomic datasets from the human microbiome, revealing body-site specific metabolomes consistent with known metabolomics data, and suggesting that common cosmetics ingredients are some of the major metabolites shaping the human skin microbiome.


2013 ◽  
Author(s):  
Peter Trefonas ◽  
James W. Thackeray ◽  
Guorong Sun ◽  
Sangho Cho ◽  
Corrie Clark ◽  
...  

Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 98
Author(s):  
Athanasios V. Serafeim ◽  
George Kokosalakis ◽  
Roberto Deidda ◽  
Irene Karathanasi ◽  
Andreas Langousis

Quantification of water losses (WL) in water distribution networks (WDNs) is a crucial task towards the development of proper strategies to reduce them. Currently, WL estimation methods rely on semi-empirical assumptions and different implementation strategies that increase the uncertainty of the obtained estimates. In this work, we compare the effectiveness and robustness of two widely applied WL estimation approaches found in the international literature: (a) the water balance, or top-down, approach introduced by the International Water Association (IWA), and (b) the bottom-up or minimum night flow (MNF) approach, based on a recently proposed probabilistic MNF estimation method. In doing so, we use users’ consumption and flow-pressure data from the 4 largest pressure management areas (PMAs) of the WDN of the city of Patras (the third largest city in Greece), which consist of more than 200 km of pipeline, cover the entire city center of Patras, and serve approximately 58,000 consumers. The obtained results show that: (a) when MNF estimation is done in a rigorous statistical setting from high resolution flow-pressure timeseries, and (b) there is sufficient understanding of the consumption types and patterns during day and night hours, the two approaches effectively converge, allowing for more reliable estimation of the individual WL components. In addition, when high resolution flow-pressure timeseries are available at the inlets of PMAs, the suggested version of the bottom-up approach with probabilistic estimation of MNF should be preferred as less sensitive, while allowing for confidence interval estimation of the individual components of water losses and development of proper strategies to reduce them.


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