dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements. The authors gratefully acknowledge the  NASA AERONET program  for the very valuable data used in this study. We thank  Brent Holben  ( Barbados, La_Parguera ),  Didier Tanre  (Capo_Verde, Dakar), and  Olga Mayol-Bracero  ( Cape San Juan ) for their effort in establishing and maintaining their sites. This work has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement no. 54109  ( ACTRIS-2 ). The authors are grateful to  Spanish MINECO  for the financial support of the IJCI-2014-19477 grant,  PTA2014-09522-I grant , and  POLARMOON  project (ref. CTM2015-66742-R ). We also thank  "Consejería de Educación" of "Junta de Castilla y León " for supporting the GOA- AIRE  project (ref. VA100P17 ). Prospero received support from  NSF   AGS-0962256  and  NASA NNX12AP45G.
controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.
The numerous origins of the data and broad taxonomic scope, combined with the global geographic extent and input from diverse disciplines make proper handling of alien species data difficult, but also necessary. With this perspective, we gathered database managers, data users, data generators and biodiversity informatics specialists to outline how alien species data can be made more useful, taking into account the peculiarities and applications of such data. This resulted in seven recommendations, which, if followed, would improve the use of alien species data for research, policy and management purposes. Some of these recommendations are not unique to alien species data, but their impact would be particularly significant in this discipline. Alien species checklists Horizon scanning (e. g.
DOCUMENT THROUGH METADATA Good metadata provide information on provenance, scope, methods, limitations, data formats and units to facilitate correct data use, as well as license and contact information. USGS' Data Management Web site 2 lists multiple tools and best practices for metadata creation. Several metadata standards for biodiversity data are available: such as Ecological Markup Language (EML  [18] ) adopted by GBIF  [19] ; the INSPIRE directive framework (Infrastructure for Spatial Information in Europe) 3 , which describes geospatial data and the Data Catalog Vocabulary (DCAT) 4 , to describe datasets. We have not identified any specific metadata standards for alien species data and recommend the use of the metadata standards above, for which tools and services are already available  [20].
An example of a tool for metadata standardization is the desktop application Morpho 5 , which guides users through the creation of EML  [21]. Morpho can interface with a MetaCat registry to provide a searchable catalog of ecological datasets. This technology is used by both the DataONE repository 6 and the European Biological Observations Network (EU BON)  [22]. Creating metadata may seem secondary to primary data curation, but metadata are essential to ensure the data 2 https://www2. usgs. gov/datamanagement/describe/metadata. php 3 http://inspire. ec. europa. eu 4 https://www. w3. org/TR/vocab-dcat/ 5 https://knb. ecoinformatics. org/#tools/morpho 6 http://dataone. org Create and implement data management plans to define the alien species data life-cycle, good data quality and metadata, standardization, data sharing options, and long-term data preservation.
IMPROVED INTEROPERABILITY OF INFORMATION SOURCES Information on alien species is scattered among a multitude of sources, including databases; peer-reviewed and gray literature; unpublished research projects and institutional datasets  [8, 24]. Important international sources of these data include the 2000 Global Invasive Species Database (GISD) of the IUCN/SSC Invasive Species Specialist Group (ISSG)  [25] ; the 2004 Global Invasive Species Information Network (GISIN); and the Global Invasive Alien Species Information Partnership (GIASIP), as well as global information providers such as the CABI Invasive Species Compendium (ISC) and the Global Register of Introduced and Invasive Species (GRIIS). Any new initiative to collate data needs to consider its role and define its niche within a complex environment of global, continental, national and regional data repositories  [7, 26].
Yet this poses additional challenges of ensuring data quality, data curation, interoperability and future-proofing against obsolete technology and increasing data volumes  [35]. Technological change promises many improvements in data collection, with systems such as smartphones equipped with built-in GPS, image capture, external sensors, and automated and expert validation  [31]. Also, advances in species detection through environmental DNA, such as those of Dejean et al. [32] , need support to be included within alien species initiatives. We recommend that alien species databases work together to follow common standards and that these standards are further developed for emerging data streams.
FORMAT DATA USING EXISTING STANDARDS Within the scope of a single dataset, data only need to be formatted consistently to be usable. However, to combine datasets for broad-scale analysis, a community-defined exchange format or standard is required to allow data interoperability. Among the qualities of a "good standard" are that it be readable (by both humans and machines), simple, learnable and efficient  [36]. The alien species research community is not universally aware of biodiversity informatics standards, where they come from and how they can be extended. Standards for the exchange of biodiversity data, including alien species data, are developed, discussed and promoted by the Biodiversity Information Standards organization, TDWG  [37]. This organization is the guardian of Darwin Core, the most widely adopted standard to exchange biodiversity information related to species  [38].
ADOPT CONTROLLED VOCABULARIES FOR FOUR ALIEN SPECIES PROPERTIES In addition to a standard format to exchange data, specialist communities often also require further control on the values of terms to increase interoperability. This can be achieved by adopting controlled vocabularies. This not only means that data can be merged, but also contributes to the normative definition of a term. Four alien species properties were identified that are either missing from Darwin Core or lacking a reference to a recommended controlled vocabulary. These are introduction pathway, degree of establishment, impact mechanism, and species status. For each of these, vocabularies exist outside Darwin Core, yet these currently exist as frameworks and require further work to be developed into standards. For pathway terminology, the need for a consistent classification, hierarchy, and terminology has long been recognized  [39] [40] [41].
Meanwhile, a standardized hierarchical pathway classification was adopted by parties to the Convention of Biological Diversity  [42]  and is being applied to existing databases  [9, 43]. A framework for the degree of establishment has been presented by  Blackburn et al. [44]. This hierarchical classification provides a terminology for populations at different points in the invasion process (casual/introduced, alien, naturalized/established, invasive) and allows expression of the range of establishments from those organisms only kept in cultivation or captivity through to full naturalization and invasiveness. For alien species impact, a classification of categories based on the magnitude of environmental impacts was developed by Blackburn et al. [45] , and has been adopted by the IUCN in 2016.
However, for impacts other than environmental, such as socioeconomic, plant health, human health and animal health, no comprehensive overview is available, but several protocols have been developed for risk assessment that can provide inspiration for classifications (see  [46]  for an overview). Standards from the trade and agriculture sectors can be useful in describing species status, for example, the International Plant Protection Conventions International Standard for Phytosanitary Measures: specifically, IPSM 8 7 , Determining pest status in an area; and IPSM 6 8 , Guidelines for surveillance. We recommend these controlled vocabularies are expressed in a machine-readable format and are referenced from the appropriate terms in Darwin Core. This is in line with the recommendations of the GBIF Task Group on Data Fitness for use in Research into Invasive Alien Species  [33].
INCREASE DATA AVAILABILITY Much has already been written about the methods and needs for open data publication  [3, 17, 50]. Beyond the good intentions, Invasivesnet is a developing global association for open knowledge and open data on alien species  [51]. This association will facilitate greater understanding, communication, and improved management of biological invasions globally, by developing a sustainable network of networks for effective knowledge exchange. The association fosters tool development and cyberinfrastructure for the collection, management and dissemination of data and information on alien species from a range of sources (e. g. , research, citizen science). The key point is that data should be shared and standardized to ensure interoperability  [52]. In the case of species observation data a straightforward solution is to publish through a repository such as GBIF or the Ocean Biogeographic Information System (OBIS), as it ensures adherence to a minimum of common standards.
ENSURE LONG-TERM DATA PRESERVATION Under ideal circumstances databases would have funding for maintenance and updating for as long as they are useful, however, this is unrealistic. Furthermore, the end of a project is the wrong time to consider the long-term persistence of data  [29, 56]. Data actively being curated are often best maintained close to their source, however, longevity can be built-in to procedures by periodically depositing data in an open repository, not just on a personal or university website. Hence, data are protected from catastrophic events, human attrition, and the slow degradation of obsolescent hardware, which is the fate of much data  [57]. If a publication is based upon a specific dataset it is good practice to deposit that precise version in a repository. Not all repositories are the same, for example the Dryad 14  and Zenodo 15  repositories are general-purpose repositories able to accept data in ad hoc formats, not necessarily formatted to community standards.
CONCLUSION Many alien species databases have emerged either before or without knowledge of existing standards for database management in biodiversity informatics. Furthermore, existing standards do not adequately cover all the needs of the research domain. Not all ecologists have strong information technology skills, nor are experts in technology-mediated collaboration, shared instrumentation or standardized data collection  [59]. In the rapidly changing information technology landscape, ecologists and conservationists cannot be expected to keep up with developments in software and data standards. This should encourage data managers, wherever possible, to simplify the tools created for ecological practitioners. This becomes more pressing as new technologies are used to provide data on alien species.
Introduction New high-mass states decaying into two photons are predicted in extensions of the Standard Model (SM). The diphoton final state provides a clean experimental signature with excellent invariant-mass resolution and moderate backgrounds. This Letter presents an update of the searches for new high-mass states decaying into two photons, using both 2015 and 2016 proton-proton (pp) collision datasets recorded at a centre-of-mass energy √ s = 13 TeV by the ATLAS detector at the CERN Large Hadron Collider (LHC), corresponding to a total integrated luminosity of 36. 7 fb -1. The analysis closely follows that described in Ref. [1] , and includes small improvements in the photon reconstruction, selection and energy calibration. From the many extensions of the SM that predict new high-mass resonances decaying into two photons, the two benchmark signal models studied in Ref.
Data and simulated event samples Data were collected in 2015 and 2016 using pp collisions at a centre-of-mass energy of √ s = 13 TeV with a bunch spacing of 25 ns. The average number of pp interactions per bunch crossing is 13 in 2015 and 25 in 2016, with a peak instantaneous luminosity up to 1. 4 × 10 34 cm -2 s -1. Events from pp collisions are recorded using a diphoton trigger with transverse energy (E T ) thresholds of 35 GeV and 25 GeV for the E T -ordered leading and subleading photon candidates, respectively. In the high-level trigger, the shapes of the energy depositions in the EM calorimeter are required to match those expected for electromagnetic showers initiated by photons. The trigger has a signal efficiency close to 100% for events fulfilling the final event selection, with an uncertainty below 0.
The efficiency of the photon identification increases with E T from 90% at 50 GeV to 95% at 200 GeV. The associated η-dependent uncertainties were measured in the whole dataset from 2015 and 2016 using the same methods as in Ref. [39]. They vary between 0. 2% and 4% below 200 GeV, and between 1% and 4% above. To further reject the background from jets misidentified as photons, the candidates are required to be isolated using both calorimeter and tracking detector information. The scalar sum of the E T of energy clusters within a cone of size ∆R = (∆η) 2 + (∆φ) 2 = 0. 4 around the photon candidate, excluding the photon energy deposits and correcting for pile-up and underlying-event contributions  [40] [41] [42] , is required to be below 0. 022E T + 2. 45 GeV, where E T is the transverse energy of the photon candidate.
Uncertainties in these purity estimates originate from the statistical uncertainty in the data sample, the definition of the control region failing the tight identification requirement, the event generator dependence (difference between Sherpa 2. 2. 1 and Pythia8), the modelling of the isolation and shower-shape distributions, and possible correlations between the isolation variables and the inverted identification criteria. The remaining background is mostly composed of photon+jet and dijet production, with one or two jets misidentified as photons. Backgrounds from other sources are negligible. The composition derived from the 2×2D sideband method is used to select the function to model the background in the spin-0 resonance search. In the background estimate used for the spin-2 resonance and non-resonant signal searches, the composition of the data sample is determined by a third method, which exploits the isolation profile of the two photons in the calorimeter, with consistent results obtained for the spin-2 selection as mentioned above.
Results Since the results of the 2015 data analysis were published in Ref. [1] , photon reconstruction and energy calibration have been improved. The results for both the spin-0 and spin-2 resonance searches are updated as summarized below. In the light of the modest excess observed in the 2015 data alone, results are reported first considering the 2015 and 2016 data samples individually, before reporting the combined results. • Spin-0: the largest local deviation from the background-only hypothesis in the 2015 dataset is 3. 3 σ at a mass of 736 GeV with a relative width of 8%. The results obtained on the same dataset with the old reconstruction and calibration, published in Ref. [1] , presented a deviation of 3. 9 σ at 750 GeV with a relative width of 6%. • Spin-2: the largest local deviation from the background-only hypothesis in the mass range 700-800 GeV in the 2015 dataset is 3.
2 σ at a mass of 742 GeV with a k/M Pl value of 0. 28. The results obtained on the same dataset with the old reconstruction and calibration, published in Ref. [1] , presented a deviation of 3. 8 σ at 750 GeV with a k/M Pl value of 0. 23. In the 2016 dataset, the observations are summarized as follows. • Spin-0: the largest local deviation from the background-only hypothesis corresponds to a 2. 0 σ narrow-width excess at 304 GeV. Within the mass interval 700-800 GeV, the largest local deviation from the background-only hypothesis corresponds to a 1. 8 σ narrow-width excess at 780 GeV. • Spin-2: the largest local deviation from the background-only hypothesis corresponds to a 2. 8 σ excess at 698 GeV with a best-fit k/M Pl value of 0. 05. The results combining the 2015 and 2016 datasets are summarized below.
A complete set of tables with the full limit results, including those from additional width and k/M Pl scenarios not covered in this Letter, are available at the Durham HepData repository. • Spin-0: the diphoton invariant-mass distribution of the events passing the spin-0 selection is shown in Figure  2 (a). The compatibility of the data with the background-only hypothesis as a function of both the assumed mass and width values is shown in Figure  3 (a). The largest deviation from the background-only hypothesis is observed at a mass of 730 GeV for a narrow width, with a local p 0 of 2. 6 σ. The corresponding global significance is null, as the local deviation is less than the median largest deviation in background-only pseudo-experiments in the search region defined by 200-2700 GeV in resonance mass and 0-10% in relative width.
Conclusion Searches for new phenomena in high-mass diphoton final states with the ATLAS experiment at the LHC are presented. The proton-proton collision data corresponding to an integrated luminosity of 36. The data are consistent with the Standard Model background expectation. At a mass around 750 GeV, where the largest deviation from the background hypothesis was previously observed, no excess is seen in the 2016 data. In the combined dataset, the largest local deviation from the background-only hypothesis for the spin-0 (spin-2) resonance search is 2. 6 σ (3. 0 σ) for a mass near 730 GeV and narrow width (mass near 708 GeV and k/M Pl = 0. 30). The global significance of this excess is null (0. 8 σ) for the spin-0 (spin-2) resonance search. In the spin-0 resonance search, the observed 95% CL upper limits on the fiducial cross section times branching ratio for a narrow-width signal range from 11.
Materials and Methods Study site and period. The data were collected on Europa Island (22. 3°S, 40. 3°E; local time = GMT+3), which is located in the Mozambique Channel, 300 km from the coast of Madagascar and 500 km from the mainland coast of Africa. Europa hosts 2 800-3 800 pairs of breeding RFB, all located in the dry Euphorbia stenoclada forest on the northern part of the island  51. GPS tracking and visual surveys were carried out between 27 January and 4 March 2014, with 2 main periods of deployment (25 Jan-2 Feb and 15 Feb-17 Feb). All juveniles studied were recently fledged and within the first 2 weeks after their first flight. Opportunistic observations are also reported from later fieldwork in June 2014 and November 2014. In addition, to determine when juveniles became totally independent from the parents, 3 nests were monitored by camera trapping (see below).
The duration of the foraging trip (h), total distance covered (km) and the maximum range from the colony (km) were calculated for each track. Tracks were plotted on maps generated with the R package ggmap  68  or over bathymetric maps obtained from the one arc-minute resolution GEBCO bathymetric dataset using the R package marmap  69. To study the associations between individuals during foraging trips, we made pairwise comparisons between all locations from one bird with all the locations from the other birds. To our knowledge, no similar analysis has been conducted in the literature to identify association events from the GPS tracking of a seabird. After testing several values of time difference and distance parameters, association events were identified when the differences in latitude and longitude for two individuals were both lower than 0.
Each ARS was summarised for one central location by taking the median latitude and longitude. Kernel estimation  67  was used to determine the utilisation distribution (UD) probability based on ARS zones. Kernel density estimates offer the advantage of being widely used to identify population-level core habitat areas. We used the function kernelUD implemented in the R package adehabitatHR 68 using the reference bandwidth, which produces contiguous cores without over-smoothing, choosing a secant projection and a narrow zone to minimise the distortions in a map generated from projection. To estimate the size of the general (95%) and core (50%) foraging areas, we used the function getverticeshr with an adapted local projection (Europa: Moznet / UTM zone 37 S).
Combined with the camera trapping on some nests, the tours allowed the linking of the presence on the nest to the feeding frequency. Statistical analysis. As some individuals were tracked during several successive trips, linear mixed-effects models with 'individual' as a random factor were applied to avoid pseudoreplication. We used the function lmer from the R package lme4  69  to test for differences in trip parameters between study periods and age classes. Tukey's HSD test was used to calculate post hoc comparisons on each factor in the model using the function glht from the R package multcomp  70. When the residuals were not normally distributed, variables were log-or square-root transformed. When the data still did not meet the assumptions, we used non-parametric tests with a Kruskal-Wallis rank sum test followed by a Tukey and Kramer (Nemenyi) test for pairwise comparisons with a Tukey-Dist approximation for independent samples from the R package PMCMR  71.
Acknowledgements This research was funded by a  European Research Council   Advanced Grant  under the European Community's  Seven Framework Program   FP7/2007-2013 (Grant Agreement ERC-2012-ADG_20120314  to  Henri Weimerskirch ). We thank  Terres Australes et Antarctiques Françaises (TAAF)  for their logistic support, and the  FAZOI  for transport to Europa and for support while on the island. We thank  J. B. Pons  for his assistance in the field. Lastly, we thank the 2 anonymous reviewers whose suggestions greatly helped to improve the manuscript.
Non-LTE model A non-LTE (non-local thermodynamical equilibrium) analysis was applied to CO 2 and OH using the non-LTE ALI-ARMS (Accelerated Lambda Iterations for Atmospheric Radiation and Molecular Spectra) code package  (Kutepov et al. , 1998; Gusev and Kutepov, 2003; Feofilov and Kutepov, 2012) , which is based on the accelerated lambda iteration approach  (Rybicki and Hummer, 1991). Our CO 2 non-LTE model is described in detail by Feofilov and  Kutepov (2012). We modified its nighttime version to account for the "direct" mechanism, Reactions (R1)-(R3), in a way consistent with that of López-Puertas et al. (  2004 ) and added the "indirect" mechanism of  Sharma et al. (2015)  and  Kalogerakis et al. (2016)  as described in detail below. Our OH non-LTE model resembles that of  Xu et al. (2012).