Reutilization of thermostable polyester wastes by means of agglomeration with phenolic resins
In: Waste management: international journal of integrated waste management, science and technology, Band 30, Heft 11, S. 2305-2311
ISSN: 1879-2456
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In: Waste management: international journal of integrated waste management, science and technology, Band 30, Heft 11, S. 2305-2311
ISSN: 1879-2456
Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β-galactosidase data set ; The authors would like to acknowledge financial support from The Spanish Ministry of Economy and Competitiveness through the BIO2016-76400-R (AEI/FEDER, UE) grant, the Comunidad Auto´noma de Madrid through grant S2017/BMD3817, the Instituto de Salud Carlos III (PT17/0009/0010), the European Union (EU) and Horizon 2020 through the CORBEL grant (INFRADEV-1-2014-1, Proposal 654248), the 'la Caixa' Foundation (ID 100010434, Fellow LCF/BQ/ IN18/11660021), Elixir–EXCELERATE (INFRADEV-3- 2015, Proposal 676559), iNEXT (INFRAIA-1-2014-2015, Proposal 653706), EOSCpilot (INFRADEV-04-2016, Proposal 739563) and INSTRUCT–ULTRA (INFRADEV03-2016-2017, Proposal 731005)
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Three dimensional electron microscopy is becoming a very data-intensive field in which vast amounts of experimental images are acquired at high speed. To manage such large-scale projects, we had previously developed a modular workflow system called Scipion (de la Rosa-Trevín et al., 2016). We present here a major extension of Scipion that allows processing of EM images while the data is being acquired. This approach helps to detect problems at early stages, saves computing time and provides users with a detailed evaluation of the data quality before the acquisition is finished. At present, Scipion has been deployed and is in production mode in seven Cryo-EM facilities throughout the world. ; Spanish Ministry of Economy and Competitiveness through Grants BIO2016-76400R(AEI/FEDER, UE) and AEI/FEDER BFU 2016 74868P, the Comunidad Autónoma de Madrid through Grant: S2017/BMD-3817, European Union (EU) and Horizon 2020 through grant Corbel (INFRADEV-1-2014-1, Proposal: 654248). The "Knut & Alice Wallenberg Foundation", and "A Pilot Facility development grant from Science for Life Laboratory". European Union (EU) and Horizon 2020 through grant EOSCpilot (INFRADEV-04-2016, Proposal: 739563).This work used the EGI Infrastructure and is co-funded by the EGIEngage project (Horizon 2020) under Grant No. 654142. European Union (EU) and Horizon 2020 through grant West-Life (EINFRA-2015-1, Proposal: 675858) European Union (EU) and Horizon 2020 through grant Elixir - EXCELERATE (INFRADEV-3-2015, Proposal: 676559) European Union (EU) and Horizon 2020 through grant iNEXT (INFRAIA-1-2014-2015, Proposal: 653706). ; Peer reviewed
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