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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anastasopoulos, Markos P.; Tzanakaki, Anna; Simeonidou, Dimitra;

    This paper focuses on the design of service provisioning schemes suitable for mega data center (DC) infrastructures. A major issue linked with the operation of these infrastructures is scalability caused by the increased number of resources available in mega-size highly-dense DCs and the associated requirements for control and management information. To address this scalability issues, we propose for the first time to monitor and optimize the operation of mega DCs adopting graph factorization combined with compressive sensing theories. This approach takes advantage of the spatial and temporal correlation of compute, and network resource requests, to monitor and optimize metrics, such as delay and energy with reduced control and management information. Our modelling results indicate drastically reduced volume of traffic transferred from the data to control plane and number of optimization process variables.

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    Journal of Lightwave Technology
    Article . 2016 . Peer-reviewed
    License: IEEE Copyright
    Data sources: Sygma; Crossref
    https://doi.org/10.1109/JLT.20...
    Other literature type . Article . 2016 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Explore Bristol Rese...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Journal of Lightwave Technology
      Article . 2016 . Peer-reviewed
      License: IEEE Copyright
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      https://doi.org/10.1109/JLT.20...
      Other literature type . Article . 2016 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Santos, Susana; Eekhout, Iris; Voerman, Ellis; Gaillard, Romy; +76 Authors

    Figure S1. Flow chart of participating cohorts and individuals. Table S1. Cohort-specific methods of data collection for maternal anthropometrics and gestational age. Table S2. Box-Cox t model specifications for each maternal pre-pregnancy body mass index group. Table S3. Gestational weight measurements per participating cohort and maternal pre-pregnancy body mass index group. Figure S2. Sample size according to gestational age for each maternal pre-pregnancy body mass index group. Figure S3. Predicted z scores for the average weight gain according to gestational age for each maternal pre-pregnancy body mass index group. Table S4. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy underweight. Table S5. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy normal weight. Table S6. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy overweight. Table S7. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 1. Table S8. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 2. Table S9. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 3. Table S10. Local institutional ethical review boards per cohort. (DOCX 631 kb)

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    Authors: Ommer, Joy; Bucchignani, Edoardo; Leo, Laura S.; Kalas, Milan; +5 Authors

    Nature-based Solutions function as an umbrella concept for ecosystem-based approaches that are an alternative to traditional engineering solutions for Disaster Risk Reduction. Their rising popularity is explained partly by their entailing additional benefits (so called co-benefits) for the environment, society, and economy. The few existing frameworks for assessing co-benefits are lacking guidance on co-benefit pre-assessment that is required for the NBS selection and permission process. Going beyond these, this paper develops a comprehensive guidance on quantitative pre-assessment of potential co-benefits and disbenefits of NBS tackling Disaster Risk Reduction. It is based on methods and frameworks from existing literature around NBS and related disciplines. Furthermore, this paper discusses the evaluation of the quantified results of the pre-assessment. In particular, the evaluation focuses on the significance of change of the estimated co-benefits and disbenefits as well as the sustainability of the NBS. This paper will support decision-making in planning processes on suitability and sustainability of Nature-based Solutions and assist in the preparation of Environmental Impact Assessments of projects.

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    Article . 2022
    License: CC BY NC
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    International Journal of Disaster Risk Reduction
    Article . 2022 . Peer-reviewed
    License: Elsevier TDM
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CORE (RIOXX-UK Aggre...arrow_drop_down
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      Article . 2022
      License: CC BY NC
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      International Journal of Disaster Risk Reduction
      Article . 2022 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Sygma; Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Forth, Jan H.; Forth, Leonie F.; Lycett, Samantha; Bell-Sakyi, Lesley; +8 Authors

    Additional file 9: Table S7. SPAdes-assembled contigs from deep sequencing data from libraries AGL001 and MPA001, as generated from museum-stored ticks. Data from libraries from museum-stored tick were mapped against ASFLI-element-containing databases of Ornithoidoros moubata (AGL001) and Ornithodoros porcinus (MPA001) using Bowtie2 (v.2.3.4.3) with default parameters. Subsequently, mapped reads were assembled using SPAdes and aligned to the corresponding ASFLI- element-contigs using MAFFT (v. 7.388) in Geneious.

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    Dataset . 2020
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    Dataset . 2020
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      Dataset . 2020
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    Authors: Forth, Jan H.; Forth, Leonie F.; Lycett, Samantha; Bell-Sakyi, Lesley; +8 Authors

    Additional file 18: Figure S6. The reconstructed ASFV-like A104R protein is highly similar to its ASFV homologue (A) A rabbit antiserum raised against the reconstructed A104 gene recognised a flag-tagged and an untagged version of A104R protein (lanes A104-Flag and A104, respectively), but showed no specific reaction with extracts of tick cell lines OME/CTVM21, OME/CTVM22, OME/CTVM24, and OME/CTVM27. In extracts of WSL-HP cells infected with ASFV Kenya 1033, the serum reacted with a single band of 12 kDa which is similar to the calculated molecular weight of ASFV A104R (11.6 kDa). (B) The Coomassie stained gel confirms equal loading with proteins.

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    Authors: Emerton, R. E.; Stephens, E. M.; Pappenberger, F.; Pagano, T. C.; +8 Authors

    Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

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      Article . 2016
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    Authors: Emerton, Rebecca; Zsoter, Ervin; Arnal, Louise; Cloke, Hannah L.; +5 Authors

    Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks or even months in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global-scale seasonal hydrometeorological forecasting system: G1oFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (G1oFAS), G1oFAS-Seasonal couples seasonal meteorological forecasts from ECMWF with a hydrological model to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other forecasting system exists. We describe the key hydrometeorological components and computational framework of G1oFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.

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    Authors: Ana M. Queirós; Klaus B. Huebert; Friedemann Keyl; Jose A. Fernandes; +15 Authors

    AbstractThe Paris Conference of Parties (COP21) agreement renewed momentum for action against climate change, creating the space for solutions for conservation of the ocean addressing two of its largest threats: climate change and ocean acidification (CCOA). Recent arguments that ocean policies disregard a mature conservation research field and that protected areas cannot address climate change may be oversimplistic at this time when dynamic solutions for the management of changing oceans are needed. We propose a novel approach, based on spatial meta‐analysis of climate impact models, to improve the positioning of marine protected areas to limit CCOA impacts. We do this by estimating the vulnerability of ocean ecosystems to CCOA in a spatially explicit manner and then co‐mapping human activities such as the placement of renewable energy developments and the distribution of marine protected areas. We test this approach in the NE Atlantic considering also how CCOA impacts the base of the food web which supports protected species, an aspect often neglected in conservation studies. We found that, in this case, current regional conservation plans protect areas with low ecosystem‐level vulnerability to CCOA, but disregard how species may redistribute to new, suitable and productive habitats. Under current plans, these areas remain open to commercial extraction and other uses. Here, and worldwide, ocean conservation strategies under CCOA must recognize the long‐term importance of these habitat refuges, and studies such as this one are needed to identify them. Protecting these areas creates adaptive, climate‐ready and ecosystem‐level policy options for conservation, suitable for changing oceans.

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    Other literature type . Article . 2016
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    Global Change Biology
    Article . 2016 . Peer-reviewed
    License: Wiley Online Library User Agreement
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      Other literature type . Article . 2016
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      Global Change Biology
      Article . 2016 . Peer-reviewed
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    Authors: Manuel Dall'Osto; David C. S. Beddows; Peter Tunved; Roy M. Harrison; +11 Authors

    Aerosols are an integral part of the Arctic climate system due to their direct interaction with radiation and indirect interaction through cloud formation. Understanding aerosol size distributions and their dynamics is crucial for the ability to predict these climate relevant effects. When of favourable size and composition, both long-rangetransported-and locally formed particles-may serve as cloud condensation nuclei (CCN). Small changes of composition or size may have a large impact on the low CCN concentrations currently characteristic of the Arctic environment. We present a cluster analysis of particle size distributions (PSDs; size range 8-500 nm) simultaneously collected from three high Arctic sites during a 3-year period (2013-2015). Two sites are located in the Svalbard archipelago: Zeppelin research station (ZEP; 474 m above ground) and the nearby Gruvebadet Observatory (GRU; about 2 km distance from Zeppelin, 67 m above ground). The third site (Villum Research Station at Station Nord, VRS; 30 m above ground) is 600 km west-northwest of Zeppelin, at the tip of northeastern Greenland. The GRU site is included in an inter-site comparison for the first time. K-means cluster analysis provided eight specific aerosol categories, further combined into broad PSD classes with similar characteristics, namely pristine low concentrations (12 %-14 % occurrence), new particle formation (16 %-32 %), Aitken (21 %-35 %) and accumulation (20 %-50 %). Confined for longer time periods by consolidated pack sea ice regions, the Greenland site GRU shows PSDs with lower ultrafine-mode aerosol concentrations during summer but higher accumulation-mode aerosol concentrations during winter, relative to the Svalbard sites. By association with chemical composition and cloud condensation nuclei properties, further conclusions can be derived. Three distinct types of accumulation-mode aerosol are observed during winter months. These are associated with sea spray (largest detectable sizes, > 400 nm), Arctic haze (main mode at 150 nm) and aged accumulation-mode (main mode at 220 nm) aerosols. In contrast, locally produced particles, most likely of marine biogenic origin, exhibit size distributions dominated by the nucleation and Aitken mode during summer months. The obtained data and analysis point towards future studies, including apportioning the relative contribution of primary and secondary aerosol formation pro cesses and elucidating anthropogenic aerosol dynamics and transport and removal processes across the Greenland Sea. In order to address important research questions in the Arctic on scales beyond a singular station or measurement events, it is imperative to continue strengthening international scientific cooperation This research has been supported by the Spanish Ministry of Economy through project BIO-NUC (CGL2013-49020-R), PI-ICE (CTM2017-89117-R) and the Ramon y Cajal fellowship (RYC-2012-11922). The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109, the Danish Council for Independent Research (project NUMEN, DFF-FTP-4005-00485B) and previously from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254. The work at Villum Research Station, Station Nord, was financially supported by the Danish Environmental Protection Agency via the MIKA/DANCEA funds for Environmental Support to the Arctic Region. The Villum Foundation funded the construction of Villum Research Station, Station Nord. CCN measurements are supported by a KOPRI program (PN19081), funded by a National Research Foundation of Korea grant (NRF-2016M1A5A1901769). The authors acknowledge financial support (to David C. S. Beddows) from the Natural Environment Research Council's funding of the National Centre for Atmospheric Science (NCAS) (grant number R8/H12/83/011) 19 pages, 9 figures, 1 table Peer Reviewed

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    Atmospheric Chemistry and Physics (ACP)
    Other literature type . Article . 2019 . Peer-reviewed
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    Atmospheric Chemistry and Physics (ACP)
    Article
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      Atmospheric Chemistry and Physics (ACP)
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    Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

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    Remote Sensing
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    Authors: Anastasopoulos, Markos P.; Tzanakaki, Anna; Simeonidou, Dimitra;

    This paper focuses on the design of service provisioning schemes suitable for mega data center (DC) infrastructures. A major issue linked with the operation of these infrastructures is scalability caused by the increased number of resources available in mega-size highly-dense DCs and the associated requirements for control and management information. To address this scalability issues, we propose for the first time to monitor and optimize the operation of mega DCs adopting graph factorization combined with compressive sensing theories. This approach takes advantage of the spatial and temporal correlation of compute, and network resource requests, to monitor and optimize metrics, such as delay and energy with reduced control and management information. Our modelling results indicate drastically reduced volume of traffic transferred from the data to control plane and number of optimization process variables.

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    Journal of Lightwave Technology
    Article . 2016 . Peer-reviewed
    License: IEEE Copyright
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    https://doi.org/10.1109/JLT.20...
    Other literature type . Article . 2016 . Peer-reviewed
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      Journal of Lightwave Technology
      Article . 2016 . Peer-reviewed
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    Authors: Santos, Susana; Eekhout, Iris; Voerman, Ellis; Gaillard, Romy; +76 Authors

    Figure S1. Flow chart of participating cohorts and individuals. Table S1. Cohort-specific methods of data collection for maternal anthropometrics and gestational age. Table S2. Box-Cox t model specifications for each maternal pre-pregnancy body mass index group. Table S3. Gestational weight measurements per participating cohort and maternal pre-pregnancy body mass index group. Figure S2. Sample size according to gestational age for each maternal pre-pregnancy body mass index group. Figure S3. Predicted z scores for the average weight gain according to gestational age for each maternal pre-pregnancy body mass index group. Table S4. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy underweight. Table S5. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy normal weight. Table S6. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy overweight. Table S7. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 1. Table S8. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 2. Table S9. Week-specific Box-Cox t model parameters and selected percentiles of gestational weight gain for maternal pre-pregnancy obesity grade 3. Table S10. Local institutional ethical review boards per cohort. (DOCX 631 kb)

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    Authors: Ommer, Joy; Bucchignani, Edoardo; Leo, Laura S.; Kalas, Milan; +5 Authors

    Nature-based Solutions function as an umbrella concept for ecosystem-based approaches that are an alternative to traditional engineering solutions for Disaster Risk Reduction. Their rising popularity is explained partly by their entailing additional benefits (so called co-benefits) for the environment, society, and economy. The few existing frameworks for assessing co-benefits are lacking guidance on co-benefit pre-assessment that is required for the NBS selection and permission process. Going beyond these, this paper develops a comprehensive guidance on quantitative pre-assessment of potential co-benefits and disbenefits of NBS tackling Disaster Risk Reduction. It is based on methods and frameworks from existing literature around NBS and related disciplines. Furthermore, this paper discusses the evaluation of the quantified results of the pre-assessment. In particular, the evaluation focuses on the significance of change of the estimated co-benefits and disbenefits as well as the sustainability of the NBS. This paper will support decision-making in planning processes on suitability and sustainability of Nature-based Solutions and assist in the preparation of Environmental Impact Assessments of projects.

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    Article . 2022
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    International Journal of Disaster Risk Reduction
    Article . 2022 . Peer-reviewed
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      International Journal of Disaster Risk Reduction
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