dataesr/scientific-paragraphs-categorization huggingface dataset:
We chose this approach to reduce the confounding effects of evaporation and we were constrained by the computation limitations imposed by running HYDRUS-1D with many con gurations. The observation dataset from Brooks et al. 1  was used to calibrate our modeled soil properties, however our objective was not to exactly simulate the observed water isotope datasets. The simulated stable water isotopes in precipitation are not equal to the actual precipitation during the period and we did not know the initial soil water's isotopic concentration. Our focus was to test the dual-porosity approach across 650 representations of transport dynamics across soils and climates.
To facilitate inexperienced observers and at the same time achieve homogeneity in the results, we created data collection and validation protocols, educational material and easy to use interfaces, open to everyone. ExoClock was launched in September 2019 and now counts over 140 participants from more than 15 countries around the world. In this release, we report the results of observations obtained until the 15h of April 2020 for 119 Ariel candidate targets. In total, 632 observations were used to either verify or update the ephemerides of 83 planets. Additionally, we developed the Exoplanet Characterisation Catalogue (ECC), a catalogue built in a consistent way to assist the ephemeris refinement process. So far, the collaborative open framework of the ExoClock project has proven to be highly efficient in coordinating scientific efforts involving diverse audiences.
However, in the new era of characterising large numbers of planets, such an effort needs to be organised in a much more efficient way through an open and collaborative platform, in order to make the best use of all the currently available resources. In several fields of astronomy there are public and collaborative databases which contribute significantly to community building and sharing. Examples of such efforts in astronomical fields are: VESPA 1 [13], the Minor Planet Center 2 and Simbad 3. In this work, we present the ExoClock project (www. exoclock. space), an open, integrated platform with the scope of verifying the ephemerides of the planets that will be observed by Ariel, prior to the launch of the mission. ExoClock has been designed in a way to make the best use of all the available resources, including literature observations regardless of their purpose, and observations from any available ground-or space-based facilities, smaller or larger in size.
The ExoClock project has been designed to implement the above approach by: 1. integrating dedicated follow-up observations conducted by observers that have joined the project (forming the ExoClock network), literature observations, and observations conducted for other purposes, both from ground and space; 2. being open to contributions from a variety of audiences -professional and amateur astronomers, students, and industry partners; 3. interacting with the participants through a variety of user-friendly interfaces to efficiently coordinate their efforts and ensure the high quality of the data products. The diversity of the project requires strategies to ensure homogeneity and reliability in the results. To achieve this vision, we have planned and applied several strategies which will be discussed in detail later.
Hence, it is very important to plan and implement citizen science aspects carefully, considering a number of different parameters to ensure scientific robustness. In the ExoClock project we use different activities that are implemented at different stages during the project (data collection, data analysis and data validation). Following recommendations from successful citizen science projects  [16, 17, 18] , we include strategies such as: educational material; training sections; interaction between the participants and the scientific team; data collection protocols; analysis tools; validation to a reference database; cross validation; interactive project development;.
The ECC can be found as part of the data provided in this work (see Section 5). To ensure consistency in the catalogued values, we constructed the ECC following the rules below: 1. The target parameters (position, and magnitudes) were extracted from: -SIMBAD for RA, DEC, and the magnitudes V, R, I -GAIA for the GAIA magnitudes G, G-BP, G-RP -2MASS for the 2MASS magnitudes J, H, K Where any of the V, R, I magnitudes were missing, we used the GAIA magnitudes to calculate them 4. This is indicated in the catalogue where applicable. 2. The stellar parameters used to calculate the limb darkening -effective temperature, surface gravity, metallicity -were extracted from a single source for each planet (reference in the catalogue); 3. The transit parameters -planet radius, semi-major axis, eccentricity, inclination, argument of periastron -were extracted from a single source for each planet (reference in the catalogue); 4.
TESS During its primary mission, TESS is surveying almost the entire sky. While the prime objective of the mission is to discover new planets, TESS will also observe stars which are known to host planets. As of November 2019, TESS has observed the host stars of 150 planets within the Ariel target list. However, data of sufficient quality has not necessarily been obtained for each of these. Thus, while TESS will undoubtedly be a great resource for the refinement of transit times [e. g. 19, 10, 20] , the extent of this contribution needs further exploration.
Other ground-based networks ExoClock as an integrated platform will incorporate all available observations produced by other ground-based networks, too. We are already collaborating with other networks and current projects to both make the best use of all resources and decrease the potential for overlapping efforts. Since homogeneity is key for the ExoClock project, we are currently examining the data sharing protocols and quality control protocols. Data from such databases will be included in the ExoClock database in future releases after defining the most effective strategy to collect them ensuring validity and accuracy. Although such networks carry out transit exoplanet observations, they are focused on different aspects, as far as exoplanet ephemerides are concerned. For example, the Exoplanet Transit Database  [ETD, 26]  run by the Czech Astronomical Society since 2009, provides more than 10,000 transit light curves for more than 350 exoplanets systems, with the scope of searching for transit time variations.
Catalogue of literature observations Since there is currently no organised and easily accessible database of past observations, conducted by other observatories (ground-or space-based) and recorded in the literature, it is difficult for the scientific community to distinguish which planets need their ephemerides to be updated. To facilitate easier access to the current literature we have developed an application within the website, in which participants and members of the scientific community can add results from other published works. The application includes all the appropriate conversions between the different time systems used across the different papers to the BJD TDB system. These contributions are validated and they are taken into account in the ephemerides refinement. In this work we include the literature data only for the planets for which an ephemeris update is required.
Light curve fitting While the data reduction and photometry can be performed using the observer's preferred tools, it is of great importance to perform the light curve modelling on the ExoClock webserver. We use the open source Python package PyLightcurve 8   [27]  to facilitate this process. At first, the time basis of the uploaded data is converted to BJD TDB. This step is necessary as the observers are allowed to upload their data in any available time basis. However, we recommend JD UTC to be used, as the conversions applied by different software may be subject to assumptions that are not reversible. Also, the data are converted from magnitude to relative flux, if necessary. If the uploaded data do not include uncertainties, these are estimated with a moving standard deviation. In both cases, we perform a first fitting, and then we scale the uncertainties to match the standard deviation of the first fitting residuals.
Then, the fitting process is repeated. This is a standard process in the literature applied to observations of HST  [28]. In this way, we take into account any extra scatter in the observation and end up with a conservative estimation of the uncertainties in the final results. The limb darkening coefficients are calculated based on the stellar parameters (temperature, gravity and metallicity) for the planet as provided in the ECC, the Phoenix 3D stellar models and the response curves of the different filters, through the open source Python package ExoTETHyS 9  [29]. For all the models, we use the 4-coefficients law by Claret 2000  [30]. During the fitting, we fix all the transit parameters, with the exception of the planet-tostar radius ratio and the mid-time, to the values in the ECC. Simultaneously with the transit model, we use a model for the out-of-transit systematics, which are usually due to airmass variations.
Educational material Continuous training and interaction between the participants and the science team are fundamental elements to ensure high quality in the produced results. The learning process is complex and multi-dimensional and every person learns in a different way. For these reasons, it is important to support the learning process through a variety of material: manuals; guidelines; videos; podcasts; newsletters; one-to-one feedback; training datasets. Because our project is open to people from various countries, it is significant to facilitate their participation and avoid misconceptions. Thus, a large part of the educational material is also provided in different languages (at the moment English, Greek, Portuguese, and French) and we also have national contact points for several countries, to assist at a local level.
Catalogue of ExoClock observations Here we present the first data release of the ExoClock project, containing 632 observations of 120 planets in the ECC (30%). These observations were conducted between 2011 and 2020, submitted to the ExoClock platform before the 15 th of April 2020, and validated according to the criteria described in Section 4. 3. The current rate of submitting new observations is above 100 per month. From the 632 observations in this dataset, 402 (17% from amateur astronomers) were acquired before the kick off of the project in September 2019, while the remaining 230 (73% from amateur astronomers) after September 2019. The largest contribution to this dataset has been made by the Observatoire des Baronnies Provencales with 356 observations, most of which were acquired before September 2019.
Note that in this work, only the observations that were submitted up to the 15 th of April 2020 are included. At the moment, the ExoClock platform contains more than 1500 observations (62% from amateur astronomers), which will be analysed in future publications. In addition, the ECC will be dynamically updated in the future, as more planets that are accessible by Ariel will be discovered. Figure  1  shows the cumulative distribution of all the observations based on the time of observation (not the time of submission). The online catalogue of ExoClock observations includes the following information for each observation: 1. the raw light curve; 2. metadata regarding the observer(s), the planet observed (link to ECC), the equipment used (telescope-camera-filter), the exposure time and the time and flux formats; 3.
Catalogue of ExoClock ephemerides The ExoClock project aims to deliver a catalogue of verified ephemerides for the planets in the Ariel target list, before the launch of the mission. An ephemeris is considered verified if it gives predictions for the end of 2028 with an uncertainty lower than 1/12 of the transit duration (see section 2. 3). This catalogue is initiated here with verified ephemerides for 84 planets in the ECC (22%). The verified status of these ephemerides is clearly indicated on the website, to encourage their use by the community. The 84 ephemerides that have been verified will be continuously monitored, as biases in measurements may still exist but require more observations to become statistically significant, and their status will be revised with future data releases. To produce this catalogue we assessed the ephemerides of the 120 planets observed in this first data release as follows: 1.
We updated the ephemerides that did not meet the verification criterion using both the ExoClock observations and values from the literature (19 in total). Note that for some of these planets, data existed in the literature but the ephemerides were either not updated by the authors or the updates where not properly listed in other catalogues. This proves the need for an organised way of listing the ephemeris information for all planets. 2. We evaluated the O-C drift for the remaining ephemerides and identified those for which our observations suggested an important, unexpected, drift (9 in total). An important drift is one that predicts an O-C greater than 1/12 of the transit duration for the end of 2028. We then updated these ephemerides using both the ExoClock observations and values from the literature.
Discussion The results presented here demonstrate that a manifold platform like ExoClock is very efficient in making the best use of all available resources towards addressing a defined scientific problem. In our case, the defined problem was the need for up-to-date ephemerides in order to increase the efficiency of the Ariel observations and other follow-up activities. However, the project architecture (priorities, organisation, website features etc) could support other endeavours, either in the same field or other sectors, to optimise data collection and ensure reliability and homogeneity in the results. The open nature of the ExoClock project guarantees the inclusion of various audiences that have the opportunity to contribute directly. This is fundamental to achieve the best use of all currently available resources.
These results would not had be identified and cross-validated without the participation of an active community that is always willing to observe, even planets with low or medium priority. Certainly, the highly interactive design of the ExoClock platform is another key element, and it is achieved through various approaches, such as: educational material, training, personal feedback, meeting, newsletters, and, even more importantly, the development of user friendly tools that enable participation from inexperienced observers. This is an element that contributes significantly towards achieving homogeneity in the results, as it supports the efficient implementation of the data collection and analysis protocols described above. It is important to note that 70% of the ExoClock participants use HOPS for data reduction and photometry.
Conclusions From the experience gained in ExoClock , we identified the importance of making the best use of all available resources through organising community-wide efforts. This is a prototype that can be used in other fields apart from exoplanets. Organising a project in a collaborative perspective by considering contributions from various audiences can maximise the outcome of the available resources. To implement efficiently such a project it is vital to create data collection and validation protocols, educational material (guides, newsletters) and easy-touse interfaces (user-friendly software and website). In future studies, we will provide the ephemerides verification and updates for more Ariel targets according to new discoveries. The monitoring of the Ariel candidate targets will be continued until the launch of the mission but ExoClock can be established as a platform and used by the exoplanet communities for further purposes.
Software and Data Software used: Django, PyLightcurve  [27] , ExoTETHyS  [29] , Astropy  [31] , emcee  [32] , Matplotlib  [33] , Numpy  [34] , SciPy  [35]. All the data products and their descriptions can found through the OSF repository with DOI: 10. 17605/OSF. IO/3W7HM. Planets with large drifts detected Fig. 3  Left: Comparison between the initial and the updated uncertainties in predictions for the end of 2028, relatively to the target uncertainty (1/12 of the transit duration) for updated planets in the category 1. Right: Drift of the mid-time predictions for the end of 2028 between the initial and the updated ephemerides for those planets which were found to have unexpected drifts. Table  1  New ephemerides for the 28 planets that have been updated here (categories 1 and 2), and references for the literature data used.
INTRODUCTION Proteins and nucleic acids are the main biological macromolecules responsible for function and maintenance of most of the machinery of life. The study of these macromolecules, their threedimensional (3D) structure, dynamical behavior and interactions are crucial to gain a better understanding of relevant biological processes both related to biotechnological applications as well as health related such as the development of new drugs. Since many years, in the context of WeNMR (www. wenmr. eu) now operating as a Thematic service provider in the European Open Science Cloud (EOSC), we have provided the community with relevant and specialized software that make up a valuable toolkit for structural biology researchers. One critical aspect aside from providing the community with valuable tools is to also provide the means of executing them in a user-friendly, efficient and cost-effective distributed manner, as done via the DIRAC Workload Manager  (Tsaregorodtsev and Project, 2014).
MetalPDB MetalPDB  (Andreini et al. , 2013a; Putignano et al. , 2017 ) is a database collecting information on the metal-binding sites present in the 3D structures of biological macromolecules  (Putignano et al. , 2017). In particular, metal sites are represented in MetalPDB, as 3D templates describing the local environment around the metal ion(s) independently of the overall macromolecular fold. Among its features, MetalPDB provides detailed statistical analyses regarding metal usage in proteins of known 3D structure, encompassing protein families, and in catalysis; it also includes tools for the structural comparison of metal sites  (Andreini et al. , 2013b). MetalPDB is available at https://metalpdb. cerm. unifi. it/.
PDB-tools web The classic Protein Data Bank (PDB) file format is a flat text file that is still used by many structural biology software to represent the spatial coordinates of macromolecular structures, even though the official format of the worldwide PDB (wwPDB)  (Berman et al. , 2003)  has now shifted to the Crystallographic Information Framework (mmCIF) dictionary  (Bourne et al. , 1997). The simple flat text PDB format, despite its apparent simplicity, follows strict formatting rules which can be easily overlooked during editing resulting in various errors. PDB-tools web (Jiménez-García et al. , 2021) is a fully configurable, user-friendly web interface for the commandline application pdb-tools  (Rodrigues et al. , 2018). Using the portal users can, in a few clicks, build a complex pipeline which can then be saved (and uploaded) for future use and reproducibility.
Powerfit Cryo-electron microscopy (cryo-EM) is an experimental technique that can be used to obtain direct images of large macromolecular complexes  (Fernandez-Leiro and Scheres, 2016). When the resolution of the resulting EM data is not sufficient to build models directly in the maps, it is common to fit existing 3D structures into those maps. To this end, Powerfit has been developed as a Python package for fast and sensitive rigid body fitting of molecular structures into EM density maps with a core-weighted local cross correlation scoring function  (Zundert and Bonvin, 2015b). It is freely available as a webserver  (Zundert et al. , 2017)  running on both local and GPU-accelerated distributed infrastructures at https://alcazar. science. uu. nl/services/POWERFIT.
EOSC-EGI The EGI Federation is an international e-Infrastructure providing advanced computing and data analytics for research and innovation. In the last decade it evolved from the high energy physics compute grid (WLCG) towards a multi-disciplinary, multi-technology infrastructure federating hundreds of resource centers worldwide and delivering large-scale data analysis capabilities (> 1 millions of CPU-cores and > 900 PB of disk and tape storage) to more than 70,000 researchers covering many scientific disciplines. During 2020 it delivered 13 billions of CPU hours of High Throughput Computing (HTC) and 18 millions of CPU hours of cloud computing. EGI was one of the main actors and the coordinator of EOSC-Hub, a three-year European project that ended in.
DIRAC Workload Manager The EGI Workload Manager is a service enabling users to access distributed computing resources of various types through a single user-friendly interface. It is one of the services offered by the EGI e-infrastructure project and it is also available via the EOSC Compute Platform. The service is built upon the software from the DIRAC Interware project (http://diracgrid. org) (Tsaregorodtsev and Project, 2014). The project is providing a development framework and a set of ready-to-use components to build distributed computing systems of arbitrary complexity. It provides a complete solution for communities needing access to computing and storage resources distributed geographically, integrated in different grid and cloud infrastructures or standalone computing clusters and supercomputers.
scientific data. In this paper, we investigate the relationship between a new estimate of potential fish production, derived from satellite remote sensing of productivity fronts (the Ocean Productivity available to Fish, hereafter OPFish), and catch or landings per unit of effort (CPUEs and LPUEs, respectively) in European Seas. We detail the links between productivity fronts, mesozooplankton and the feeding of higher trophic levels. We then use spatial fisheries data sets with different attributes to build a second index, the Harvest relative to ocean productivity (hereafter H P index). This H P index is defined as the ratio of gear-specific CPUEs or LPUEs over the potential fish production (OPFish). H P index aims to evaluate if the fishing intensity of each fleet segment is proportionate to the local fish production.
| The satellite-derived data and potential fish production   (Druon et al. , 2012 (Druon et al. , , 2021)). The norm of the chlorophyll-a gradient (gradCHL) was derived from the daily chlorophyll-a data, using a bidirectional gradient over a three-by-three grid-cell window as follows: with Gx, Gy, the longitudinal and latitudinal chlorophyll-a horizontal gradient, respectively, corrected by the pixel size in km. Small and large chlorophyll-a fronts refer to variable levels of chlorophyll-a gradient values (see the first section of the Supplementary Information, hereafter S. I. ). The gradCHL values, which are linked to the presence of pelagic species, were used in log-form to derive a dependent linear function (C g see Figure  S2 ), which is the main component of Ocean Productivity available to Fish (OPFish).