SURFsara (Netherlands)

The Horizon Europe SELINA project (project-selina.eu) supports evidence-based decision-making for the sustainable use of natural capital by advancing the integration of information on biodiversity, ecosystem condition, and ecosystem services across Europe, contributing to the EU Biodiversity Strategy for 2030, the European Green Deal, and national ecosystem reporting.As part of SELINA’s demonstration phase, advanced methods were tested to improve the spatial and temporal resolution of the three key ecosystem accounting components—extent, condition, and services — focusing on the capacity of forests, heathlands and peatlands to capture and store carbon on two test sites: São Miguel Island (Azores, Portugal) and Peloponnese, Greece.Ecosystem extent mapping employed a dual approach: (i) national-centric, enhancing existing datasets with Copernicus Land Monitoring Service (CLMS) data; and (ii) vegetation-centric, classifying EUNIS habitats from remote-sensing-derived features. Forest condition was assessed using the PEOPLE-EA index, integrating multiple indicators relative to an optimal reference state. Carbon accounting also followed a dual approach: (i) a remote sensing–based method (GEDI, LiDAR, Sentinel-1) to map above-ground biomass, estimate carbon stock/fluxes, and detect deforestation; (ii) a GPP-based approach applying a Light Use Efficiency (LUE) model with Sentinel-2 and climate data, subsequently converted to biome-specific NPP.These methods produced wall-to-wall 10 m resolution maps harmonized with the European ecosystem typology, enabling scalable, cost-effective, and policy-relevant ecosystem monitoring, particularly in typically underrepresented small-medium islands from the European outermost regions.

ABSTRACT Recent work has successfully achieved subarcsecond wide-field imaging with high-band observations from the LOw Frequency ARray (LOFAR). However, the scalability of this work remains limited due to the need for manual intervention, poor calibration solutions for the Dutch LOFAR stations, and high computational costs. We address these issues by: (1) improving automated self-calibration using a signal-to-noise metric and a neural network for image artefact detection; (2) implementing a refined calibration strategy for the Dutch LOFAR stations; and (3) cutting computational costs by optimizing the data processing strategy. We demonstrate the effectiveness of our automated processing strategy by reprocessing one previously reduced data set and a new data set from the European Large Area ISO Survey North 1 (ELAIS-N1) deep field, which features more severe ionospheric conditions. We find calibration artefacts across facet boundaries to be reduced with our improved automated calibration strategy and achieve a computational cost reduction of about a factor of 4–6 compared to previous work, where the exact factor depends on whether a single observation is processed or multiple observations of the same sky area are combined. Further optimization and improved handling of data with baseline-dependent averaging could reduce this in the near future by another factor of two, bringing the total cost for an 8-h observation below 30 000 CPU core hours. This work enables ultradeep imaging at sensitivities on the order of a few $\mu$Jy beam$^{-1}$. Furthermore, it also lays the foundation for a fully automated survey pipeline for subarcsecond wide-field imaging of the northern sky with LOFAR.

We present the deepest wide-field 115–166 MHz image at sub-arcsecond resolution spanning an area of 2.5° × 2.5° centred at the ELAIS-N1 deep field. To achieve this, we improved the direction-independent (DI) and direction-dependent (DD) calibrations for the International LOw Frequency ARray (LOFAR) Telescope. This enhancement enabled us to efficiently process 32 h of data from four different 8-h observations using the high-band antennas (HBAs) of all 52 stations, covering baselines up to approximately 2000 km across Europe. The DI calibration was improved by using an accurate sky model and refining the series of calibration steps on the in-field calibrator, while the DD calibration was improved by adopting a more automated approach for selecting the DD calibrators and inspecting the self-calibration on these sources. For our brightest calibrators, we also added an additional round of self-calibration for the Dutch core and remote stations in order to refine the solutions for shorter baselines. To complement our highest resolution at 0.3″, we also made intermediate resolution wide-field images at 0.6″ and 1.2″. Our resulting wide-field images achieve a central noise level of 14 μJy beam−1 at 0.3″, doubling the depth and uncovering four times more objects than the Lockman Hole deep field image at comparable resolution but with only 8 h of data. Compared to LOFAR imaging without the international stations, we note that due to the increased collecting area and the absence of confusion noise, we reached a point-source sensitivity comparable to a 500-h ELAIS-N1 6″ image with 16 times less observing time. Importantly, we have found that the computing costs for the same amount of data are almost halved (to about 139 000 CPU h per 8 h of data) compared to previous efforts, though they remain high. Our work underscores the value and feasibility of exploiting all Dutch and international LOFAR stations to make deep wide-field images at sub-arcsecond resolution.

Abstract As many of the chapters in this volume have illustrated, there are no single or easy answers to the question of ‘what is transdisciplinarity?’ and ‘how can I, through research or everyday inquiry, contribute to transformation?’. Everyone who was involved in this book project went on their own quest, their own journey, sometimes together with others, sometimes alone. In this concluding chapter, we loosely tie things together, ask ourselves what is next for Transdisciplinarity for Transformation by drafting an agenda for action, learning and research, and remind ourselves of the importance of diving into the unknown with curiosity and humility, without losing one’s ideals to make the world a more just, sustainable and safe place for all.

Interleukin-4 (IL-4) is a hematopoietic cytokine composed by a four-helix bundle stabilized by an antiparallel beta-sheet and three disulfide bonds: Cys3-Cys127, Cys24-Cys65, and Cys46-Cys99. IL-4 is involved in several immune responses associated to infection, allergy, autoimmunity, and cancer. Besides its physiological relevance, IL-4 is often used as a "model" for protein design and engineering. Hence, to understand the role of each disulfide in the structure and dynamics of IL-4, we carried out several spectroscopic analyses (circular dichroism [CD], fluorescence, nuclear magnetic resonance [NMR]), and molecular dynamics (MD) simulations on wild-type IL-4 and four IL-4 disulfide mutants. All disulfide mutants showed loss of structure, altered interhelical angles, and looser core packings, showing that all disulfides are relevant for maintaining the overall fold and stability of the four-helix bundle motif, even at very low pH. In the absence of the disulfide connecting both protein termini Cys3-Cys127, C3T-IL4 showed a less packed protein core, loss of secondary structure (~9%) and fast motions on the sub-nanosecond time scale (lower S2 order parameters and larger τc correlation time), especially at the two protein termini, loops, beginning of helix A and end of helix D. In the absence of Cys24-Cys65, C24T-IL4 presented shorter alpha-helices (14% loss in helical content), altered interhelical angles, less propensity to form the small anti-parallel beta-sheet and increased dynamics. Simultaneously deprived of two disulfides (Cys3-Cys127 and Cys24-Cys65), IL-4 formed a partially folded "molten globule" with high 8-anilino-1-naphtalenesulphonic acid-binding affinity and considerable loss of secondary structure (~50%decrease), as shown by the far UV-CD, NMR, and MD data.

The wealth of available global datasets at high spatial and temporal resolutions opens many opportunities for hydrological modelling and forecasting. It is now possible to provide high-resolution hydrological simulations for a river basin anywhere in the world, even in basins without in situ observations. Combined with the strength of global parameter estimations of the wflow_sbm concept (Imhoff et al, 2021), this allows us to build and run hydrological models without calibration. These models can ultimately be used to provide discharge forecasts for the seasonal time scale. Here we present a workflow that tests the interoperability, scalability, and performance of combining cloud and high-throughput compute and data resources. The workflow combines open source technologies, including containerization, to provide automated monthly river discharge forecasts for practically every basin on the globe on cloud, HTC and in the future HPC platforms. We leverage the global ERA5 and SEAS5 products from the Copernicus Climate Data store as input for the wflow hydrological model. The workflow automatically downloads the required input data for the model domain, resamples the data to the required model grids, and runs the simulations. The workflow is automatically triggered every month when new SEA5 forecasts become available. Prior to running the forecasts, the ERA5 files are used to update the hindcast model states in preparation for the forecast. Next, 50 wflow ensemble members, forced using the SEAS5 forecasts, are run in parallel to provide estimates on the probability of discharge events. The workflow is currently set up and running for the Rhine basin on SURF’s high-throughput computing platform, but can easily be deployed on different infrastructures and for different river basins. 

Context. Diffuse synchrotron emission pervades numerous galaxy clusters, indicating the existence of cosmic rays and magnetic fields throughout the intra-cluster medium. The general consensus is that this emission is generated by shocks and turbulence that are activated during cluster merger events and cause a (re-)acceleration of particles to highly relativistic energies. Similar emission has recently been detected in megaparsec-scale filaments connecting pairs of premerging clusters. These instances are the first in which diffuse emission has been found outside of the main cluster regions. Aims. We aim to examine the particle acceleration mechanism in the megaparsec-scale bridge between Abell 399 and Abell 401 and assess in particular whether the synchrotron emission originates from first- or second-order Fermi reacceleration. We also consider the possible influence of active galactic nuclei (AGNs). Methods. To examine the diffuse emission and the AGNs in Abell 399 and Abell 401, we used deep (∼40 h) LOw-Frequency ARray (LOFAR) observations with an improved direction-dependent calibration to produce radio images at 144 MHz with a sensitivity of σ = 79 μJy beam−1 at a 5.9″ × 10.5″ resolution. Using a point-to-point analysis, we searched for a correlation between the radio and X-ray brightness from which we would be able to constrain the particle reacceleration mechanism. Results. Our radio images show the radio bridge between the radio halos at high significance. We find a trend between the radio and X-ray emission in the bridge. We also measured the correlation between the radio and X-ray emission in the radio halos and find a strong correlation for Abell 401 and a weaker correlation for Abell 399. On the other hand, we measure a strong correlation for the radio halo extension from A399 in the northwest direction. With our deep images, we also find evidence for AGN particle injection and reenergized fossil plasma in the radio bridge and halos. Conclusions. We argue that second-order Fermi reacceleration is currently the most favored process to explain the radio bridge. In addition, we find indications for a scenario in which past AGN particle injection might introduce significant scatter in the relation between the radio and X-ray emission in the bridge, but may also supply the fossil plasma needed for in situ reacceleration. The results for Abell 401 are also clearly consistent with a second-order Fermi reacceleration model. The relation between the thermal and nonthermal components in the radio halo in Abell 399 is affected by a recent merger. However, a strong correlation toward its northwest extension and the steep spectrum in the radio halo support an origin of the radio emission in a second-order Fermi reacceleration model as well. The evidence that we find for reenergized fossil plasma near Abell 399 and in the radio bridge supports the reacceleration of the fossil plasma scenario.

The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer diagnosis. However, the availability of medical specialists to annotate digitized images and free-text diagnostic reports does not scale with the need for large datasets required to train robust computer-aided diagnosis methods that can target the high variability of clinical cases and data produced. This work proposes and evaluates an approach to eliminate the need for manual annotations to train computer-aided diagnosis tools in digital pathology. The approach includes two components, to automatically extract semantically meaningful concepts from diagnostic reports and use them as weak labels to train convolutional neural networks (CNNs) for histopathology diagnosis. The approach is trained (through 10-fold cross-validation) on 3’769 clinical images and reports, provided by two hospitals and tested on over 11’000 images from private and publicly available datasets. The CNN, trained with automatically generated labels, is compared with the same architecture trained with manual labels. Results show that combining text analysis and end-to-end deep neural networks allows building computer-aided diagnosis tools that reach solid performance (micro-accuracy = 0.908 at image-level) based only on existing clinical data without the need for manual annotations.

ABSTRACT The nearby face-on spiral galaxy NGC 2617 underwent an unambiguous ‘inside–out’ multiwavelength outburst in Spring 2013, and a dramatic Seyfert-type change probably between 2010 and 2012, with the emergence of broad optical emission lines. To search for the jet activity associated with this variable accretion activity, we carried out multiresolution and multiwavelength radio observations. Using the very long baseline interferometric (VLBI) observations with the European VLBI Network at 1.7 and 5.0 GHz, we find that NGC 2617 shows a partially synchrotron self-absorbed compact radio core with a significant core shift, and an optically thin steep-spectrum jet extending towards the north up to about 2 pc in projection. We also observed NGC 2617 with the electronic Multi-Element Remotely Linked Interferometer Network at 1.5 and 5.5 GHz, and revisited the archival data of the Very Large Array (VLA) and the Very Long Baseline Array (VLBA). The radio core had a stable flux density of ∼1.4 mJy at 5.0 GHz between 2013 June and 2014 January, in agreement with the expectation of a supermassive black hole in the low accretion rate state. The northern jet component is unlikely to be associated with the ‘inside–out’ outburst of 2013. Moreover, we report that most optically selected changing-look active galactic nuclei (AGN) at z < 0.83 are sub-mJy radio sources in the existing VLA surveys at 1.4 GHz, and it is unlikely that they are more active than normal AGN at radio frequencies.