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Collision risk for six seabirds species in the first Belgian offshore wind farm zone
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RBINS Staff Publications 2020
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Colonization and diversification by the Chydorus sphaericus complex in the East African sky islands
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RBINS Staff Publications
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Color variations in Muricopsis principensis Rolán & Fernandes, 1991 (Gastropoda, Muricidae) from Príncipe Island
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RBINS Staff Publications
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Colourful rivers: archaeobotanical remains of dye plants from urban fluvial deposits in the southern Low Countries (Belgium)
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Although dye plants were a key element in the medieval cloth industry, their use has rarely been documented through archaeobotanical studies. This paper describes and discusses new archaeobotanical finds related to textile dyeing in the southern Low Countries, which was among the most important areas of cloth production and export in Europe during the late medieval period. Remains of weld, madder and woad, the three main medieval dye plant species, were identified via archaeobotanical analysis and high-performance liquid chromatography with photodiode array detection (HPLC-PDA). The remains were found in river deposits, dating between the 10th/12th and 15th century, from two medieval cloth-producing towns, Brussels and Mechelen. Most likely, the finds must be interpreted as waste discarded by textile dyers, which were often concentrated along the urban riverbanks. This study not only documents the use of dye plants in both cities, but also demonstrates the importance of archaeobotanical analyses of fluvial deposits for the reconstruction of artisanal activities within ancient towns. The assemblages are confronted with historic sources and mapped with other medieval remains of dye plants in the region.
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RBINS Staff Publications 2024
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Combined High-Throughput Imaging and Sequencing: Addressing the collections on demand requirement in SYNTHESYS+ project
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Imagine you are a scientist, working on collections. You have your pet taxon and you need information which is distributed in a number of books and publications but also in the specimens deposited in$~$Museums or Herbaria. Instead of paying visits to these establishments, around the world, you wish there was a means to transform all the information you need into a digitized form of the physical objects, you can reach from the screen of your laptop, tablet or cell phone. You dream you were able to watch, inspect and even dissect the type material you need online but also to compare it with others they way sequences are blasted against large databases, these days. You plan to make global research on this taxon and try to derive patterns from both the molecular and organismal level of the biological organization and to link the patterns resulting to the drivers of change for this taxon.$~$This is the vision of the Virtual Museum of Natural History and one of the ways to achieve this vision is to address the “collections on demand” requirement. One of the possible means to address this requirement is the digitization through the use of the micro-ct technology. The micro-CT virtual laboratory (vLab), developed by LifeWatchGreece research infrastructure (RI), makes it possible the online exploration and dissemination of micro-CT datasets, which are only rarely made available to the public due to their large size and a lack of dedicated online platforms for the interactive manipulation of 3D data. This presentation shows the development of such a “collections on demand” function, implemented by the SYNTHESYS+ project (DiSSCo RI), which combines such high-throughput technologies, that is micro-ct and genomics, to address the scientific communityʼs requirements. We show that this approach to combine patterns deriving from the application of novel techniques, which represent different kinds of observations is possible and we propose certain case studies as examples. The innovation aspects of this function include: Expansion and development of cost models for Collections on Demand; Development of standards and guidelines for exchange of collection-derived imaging data; Construction of new data pipelines and standard workflows, enabling access to complex digital content such as 3D scans; Development of novel molecular lab protocols, workflows and informatics pipelines, to enable large scale; DNA sequencing of NH collections.
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RBINS Staff Publications 2019
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Combined Hybridization Capture and Shotgun Sequencing for Ancient DNA Analysis of Extinct Wild and Domestic Dromedary Camel
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RBINS Staff Publications
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Combined land surface emissivity and temperature estimation from Landsat 8 OLI and TIRS
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Remote sensing of Land Surface Temperature (LST) generally requires atmospheric parameters and the emissivity (∊) of the target to be estimated. The atmospheric up- and downwelling radiances and transmittance can be accurately modelled using radiative transfer models and profiles of relative humidity and temperature, either measured by radiosonde probes or retrieved from assimilating weather models. The estimation of ∊ is a large source of uncertainty in the resulting LST product, and there are various approaches using multi-angle observations, multispectral optical or multispectral thermal infrared imagery. In this paper, the estimation of LST from the Thermal InfraRed Sensor (TIRS) on board Landsat 8 is evaluated using more than 6 years of in situ temperature measurements from a network of 14 Autonomous Weather Stations (AWS) in Belgium. ∊ is estimated from concomitant atmospherically corrected imagery from the Operational Land Imager (OLI) using two new neural network approaches trained on ECOSTRESS spectra, and an established NDVI based method. Results are compared to using ∊=1 and the ASTER Global Emissivity Dataset. LST retrievals from L8/TIRS perform well for all emissivity data sources for 500 matchups with AWS subsoil temperature measurements: Mean Differences 0.8–3.7 K and unbiased Root Mean Squared Differences of 2.9–3.5 K for both B10 and B11. The use of unity emissivity gives the best results in terms of MD (0.8 K) and unb-RMSD (3 K). Similar ranges of unb-RMSD are found for 500 matchups with broadband radiometer temperatures (2.6–3.1 K), that have lower absolute MD values (−2.2–0.6 K). For the radiometer temperatures, both the neural net approaches gave lowest MD, in the best case ±0.1 K. The present investigation can hence recommend the neural nets to derive ∊ for the retrieval of LST over the AWS in Belgium. Using published matchup results from other authors however, no single source of ∊ data performed better than ∊=1, but this could be due to their low number of matchups. Further efforts for estimating representative pixel average emissivities are needed, and establishing a denser in situ measurement network over varied land use, with rather homogeneous land cover within a TIRS pixel, may aid further validation of a per pixel and per scene ∊ estimates from multispectral imagery. AWS data seems valuable for evaluation of satellite LST, with the advantage of a much lower cost and higher potential matchup density compared to conventional radiometers.
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RBINS Staff Publications 2020
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Combining mitochondrial DNA and morphological data to delineate four new millipede species and provisional assignment to the genus Apeuthes Hoffman & Keeton (Diplopoda : Spirobolida : Pachybolidae : Trigoniulinae)
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RBINS Staff Publications 2022 OA
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Comfort op kantoor: temperatuur in tijden van energieschaarste - Le confort au bureau : la température en période de pénurie d'énergie
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RBINS Staff Publications 2022
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Comment caractériser un assemblage de termites: un test de la méthode des transects
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RBINS Staff Publications
