dataesr/scientific-paragraphs-categorization huggingface dataset:
A comprehensive search of several electronic databases, including EMBASE, MEDLINE, PubMed and Cochrane Databases (Cochrane Central Register of Controlled Trials, Cochrane Database of Abstracts or Reviews of Effects, Cochrane Database of Systematic Reviews) is performed using appropriate search strings to identify relevant studies. The time period for literature search for a new review is determined by the working group but is generally chosen to be the preceding 10 years, whereas that for updates is 3-5 years from the enddate of the previous review. The PROSPECT working group decided upon searching for relevant studies within a 10-year period because it more likely resembles current clinical practice given that rapid changes occur in peri-operative care, including surgical techniques. Broad search terms are used for the literature review to maximise the search and reduce the risk of missing relevant publications.
Acknowledgements PROSPECT is supported by an unrestricted grant from the  European Society of Regional Anaesthesia and Pain Therapy (ESRA). In the past, PROSPECT has received unrestricted grants from  Pfizer Inc. (New York, NY,  USA and Grunenthal, Aachen, Germany). GJ has received honoraria from  Baxter  and  Pacira Pharmaceuticals. MVdV has received honoraria from  Sintetica ,  Grunenthal ,  Vifor Pharma ,  MSD ,  Nordic Pharma ,  Janssen Pharmaceuticals ,  Heron Therapeutics  and Aquettant. EP-Z has received honoraria from  Mundipharma, Grunenthal, MSD, Janssen-Cilag GmbH, Fresenius Kabi  and  AcelRx. HB has received honoraria from  Abbvie ,  Aspen, Orion. No other competing interests declared.
The frequency resolution corresponded to ~26 cm -1 and the lowest resolvable frequency was ~52 cm -1. To extract the intrinsic 1 TT Raman spectrum, we recorded the vibrational coherence in the presence and absence of the actinic pump pulse and subsequently subtracted the two coherences in the time-domain to minimize ground-state contributions, as outlined previously. The remaining data analysis was the same. Care was taken to ensure that all traces were temporally aligned using reference measurements on toluene to exclude possible Fourier artefacts in the comparison between different experiments. Computational methods. Concerning the parametrisation of the model and the methodology for the time evolution, the following is very closely based on Schröder et al. 48 and the supplementary information of that work, and is presented here for the reader's convenience.
1. The energies of jLE ± i; jCT ± i are calculated within TD-DFT, using the range-separated functional LC-BLYP with an optimised range-separation parameter γ = 0. 29. The energy of the TT state is approximated by that of the spintwo ground state of DP-Mes as visualised in Supplementary Fig. 2. The energies and symmetries of the electronic states considered here are summarised in Supplementary Table  1. We included 252 out of the 318 vibrations of DP-Mes and excluded the very slow modes with frequencies below 110 cm -1 as these are highly anharmonic. Likewise, we excluded the very high-frequency C-H stretches above 1680 cm -1 as they are expected to make little contribution to the overall dynamics and they are beyond the scope of our experimental technique. The molecular vibrations were calculated at the cc-pVDZ, B3LYP level of DFT, using the NWChem software  83.
Acknowledgements This work was supported by the  Engineering and Physical Sciences Research Council, UK  (Grant Numbers  EP/M025330/1 ,  EP/M01083X/1 ,  EP/L015552/1  and  EP/M006360/1 ) and the  Winton Programme for the Physics of Sustainability. J. W. acknowledges financial support from  Singapore MOE Tier 3 Programme  ( MOE2014-T3-1-004 ). T. W. acknowledges the  Marie Curie Intra European Fellowship  ( PIEF-GA-2013-623652 ) within the  7th European Community Framework Programme. C. S. acknowledges financial support by the  Royal Commission for the Exhibition of 1851.
Prior to each experiment, the glassware was boiled once in Milli-Q water, and rinsed 3-fold with Milli-Q water. All electrochemical measurements were performed in custom-made single-compartment 10 mL glass cells using a threeelectrode configuration with an Autolab PGSTAT 12, 204, or 128N potentiostat operated by NOVA software. All electrochemical experiments were carried out under either an argon (Linde, Ar 5. 0) or an oxygen (Linde, O 2 5. 0) atmosphere, and the gas was bubbled through the electrolyte for at least 15 min prior to the experiment. The atmosphere was maintained during the experiments by flowing 1 atm of the gas over the electrolyte. The counter electrode was a large surface area coiled gold wire (99. 9% purity) that was flame annealed and rinsed with Milli-Q water prior to use.
BE calibration of Cu(OTf) 2 and Na 2 SO 4 was done by setting the C 1s peak of adventitious carbon at 284. 8 eV. Modified electrode samples were transported to the UHV chamber under a N 2 atmosphere. [Cu(tmpa)(MeCN)](OTf) 2 , ligand precursor 4, and HEPES were measured as reference compounds by dropcasting each of them on a separate bare disposable gold WE using either water or ethanol as the solvent. CasaXPS software was used to fit the obtained spectra. X-ray Absorption Spectroscopy. Cu K-edge XAS measurements were performed at ambient temperature at the Dutch-Belgian beamline (DUBBLE) at the European Synchrotron Radiation Facility (ESRF) in Grenoble, France. Cu foil was used as a reference for energy calibration, and all spectra were collected in fluorescence mode with a grazing incidence angle of 0.
3°. [Cu(tmpa)(MeCN)](OTf) 2 was measured as a reference compound by dropcasting it on a bare disposable gold WE using water as the solvent. Athena software was used to process the obtained spectra with a normalization order of 2 and the Boxcar average smoothening with a kernel size of 7. 34  X-ray Diffraction. XRD patterns were recorded under vacuum on a D8-Advance diffractometer from Bruker operating in Bragg-Brentano geometry. It was equipped with a Co Kα anode (λ = 1. 78897 Å) operating at 40 kV and 30 mA, and a Lynxeye position sensitive detector. Diffraction data were collected at angles ranging from 10°to 100°with a step size of 0. 02°and a scan rate of 0. 2°s -1. To be able to fit the samples in the sample holder, the disposable electrodes were cut into smaller sizes (Figure  S12 ).
Modified electrode sample EDTA Au|mixed SAM|Cu was cut under an argon atmosphere inside a glovebox and transported to the diffractometer in the dark. Scanning Electron Microscopy. SEM images were obtained with a Thermo Scientific Apreo scanning electron microscope operating under high vacuum at an accelerating voltage of 15 kV and a beam current of 0. 8 nA. The electron source was a Schottky type field emission gun, and secondary electrons were used to obtain the SEM images. A Thermo Scientific UltraDry energy dispersive Xray (EDX) detector was used to acquire the EDX spectrum and elemental mapping at the same position of the sample as the SEM image itself. The selected settings of the microscope resulted in a dead time of 29% for the EDX detector. Thermo Scientific Pathfinder X-ray microanalysis software was used for data processing.
1 eV is observed in the Cu 2p 3/2 region of the XPS spectrum. This energy coincides with the BE of a Cu I compound such as Cu 2 O. 36  According to the NIST XPS database, copper species with a BE between 932. 2 and 933. 2 eV can be attributed both to Cu(0) and various Cu(I) species. 37 The absence of the characteristic satellite features in the Cu 2p 3/2 region of the XPS spectra also indicates the presence of either a Cu 0 or a Cu I species at the gold electrode surface. The high KE of 918. 1 eV for the Auger peak maximum in the Cu L 3 M 4,5 M 4,5 spectra of the four modified electrode samples seems to suggest that the anchored copper is a Cu 0 species rather than a Cu I species. 37 owever, to the best of our knowledge, no XPS data have been reported for Cu I coordination complexes, making it rather difficult to make a relevant comparison to our modified electrode samples.
The relatively low onset energy of the absorption edge observed for modified electrode EDTA Au|mixed SAM|Cu might, however, be the result of the presence of a minor Cu 0 species besides the major Cu I species. A final comparison with the XANES data of a reference spectrum of Cu 2 O shows a significant negative shift of the onset energy of the absorption edge as well, confirming that the anchored Cu I species of interest is a molecular architecture rather than cuprous oxide (Figure  S9  dotted green line). 48 canning Electron Microscopy. To verify whether accumulated copper particles were present on the surface of the modified gold electrode, EDTA Au|mixed SAM|Cu was analyzed by a combination of scanning electron microscopy (SEM) imaging and energy dispersive X-ray (EDX) spectros- The total area of all species in the N 1s region was used to determine the ratios.
For the modified electrodes, the total area of all species in the S 2p region with a BE between 159 and 166 eV and the area of the Cu 2p 3/2 signal at BE = 932. 1 eV were used to determine the ratios. For [Cu(tmpa)(MeCN)](OTf) 2 , the total area of the Cu 2p 3/2 signals at BE = 932. 4, 934. 5, and 936. 7 eV was used to determine the ratios. b Average of two measurements (see Table  S2 ). Reference spectra from the literature of a distorted trigonal bipyramidal Cu II complex 38 (red dashed line, complex 1 in Figure  S8 ), 13 Cu I complexes  [38] [39] [40] [41] [42]  (thin blue lines, complexes 2-14 in Figure  S8 ), metallic copper  48   50  The shown spectrum of EDTA Au|mixed SAM|Cu is a smoothed fit of the raw data (Figure  S6 ). copy. The SEM images of both the modified electrode and an unmodified gold electrode (Figure  S10  and S11a, c,  and e ) are qualitatively the same.
Observations of circumstellar environments that look for the direct signal of exoplanets and the scattered light from disks have significant instrumental implications. In the past 15 years, major developments in adaptive optics, coronagraphy, optical manufacturing, wavefront sensing, and data processing, together with a consistent global system analysis have brought about a new generation of high-contrast imagers and spectrographs on large ground-based telescopes with much better performance. One of the most productive imagers is the Spectro-Polarimetic High contrast imager for Exoplanets REsearch (SPHERE), which was designed and built for the ESO Very Large Telescope (VLT) in Chile. SPHERE includes an extreme adaptive optics system, a highly stable common path interface, several types of coronagraphs, and three science instruments.
Then in Sect. 3 we present the global system architecture and the performance of the common path interface (CPI), which is the heart of SPHERE and feeds all the science sub-systems. The two fundamental components required for high-angular resolution and high-contrast observations, namely the adaptive optics system and the coronagraphs, are described in Sect. 4 and 5 respectively. Then Sect. 6 is dedicated to ZIMPOL, the visible polarimetric imager of SPHERE, and Sect. 7 and 8 are dedicated to IFS and IRDIS respectively, the two near-infrared instruments of SPHERE. Finally, the instrument control, the operations and the data reduction and handling are detailed in Sect. 9. We conclude and propose some perspective for future upgrades in Sect. 10.
The repeatability of this error has not been investigated in detail, but if it is stable it could be compensated for in the data processing of SPHERE pupil-tracking data. filtering pinhole, designed for removing aliasing effects, is automatically adjusted during the target acquisition as a function of the atmospheric conditions. It can also be changed manually by the instrument operator if conditions significantly change during the course of an observation. The EMCCD characteristics, combined with dedicated centroiding techniques (e. g. , weighted center of gravity), allow SAXO to have high-limiting magnitudes. Firstly the ultimate performance limit magnitude (R = 9-10) for which the instrument meets its initial requirements in terms of wavefront correction. In this regime the Strehl ratio (SR) in H-band is higher or equal to 90%.
2008). This mode offers an efficient combination of long-slit spectroscopy with coronagraphy. The spectral coverage in LSS is either 0. 95-2. 32 µm (YJHKs) with a resolving power of R∼50 or 0. 95-1. 65 µm (YJH) with R∼350, providing the so-called lowresolution (LRS) and medium-resolution (MRS) spectroscopy modes. A LRS dataset obtained on PZ Tel B is presented in Fig. 23. In practice, the slits and opaque coronagraphic masks have been merged into a single device that is placed in the coronagraph wheel of the CPI. Three different combinations of slit widths and coronagraphic mask sizes are provided, but the most widely tested and used combinations are the 0. 12 -wide and 0. 09 -wide slits with a mask of radius 0. 2. For the spectral dispersion, two dispersive elements are placed in the IRDIS cryostat in the Lyot stop wheel: a prism for the LRS mode and a grism for the MRS mode.
Performance and limitations IRDIS DPI is currently among the most powerful instrumental modes to perform polarimetric high-contrast imaging. Due to design choices, its performance is strongly dependent on the observation strategy, as will be illustrated in de  Boer et al. (in prep)  with the observations of TW Hydrae. The polarimetric crosstalk in IRDIS DPI can cause the polarimetry efficiency to drop toward 10% in H-and K s-band, while the efficiency remains above 60% in Y-band and well above 90% in J-band. The measured cross-talk is also responsible for an offset in the measured polarization angle in H and in K s to a larger extend. Both the effects are fully calibrated and can be corrected for by the use of a Mueller matrix model. This model has already been used successfully in several cases to correct for the variations in efficiency and polarization angle offset due to cross-talk observed in the various datasets  (van Holstein et al.
Further data handling tools Handling data of a SPHERE observation comprises much more than the processing of frames coming from the instrument's detectors. Beginning with the preparation of the observations in Phase 2, and ending with the analysis of large quantities of data in the context of the SHINE survey  (Chauvin et al. 2017 ), a number of tools have been developed and deployed within the SPHERE consortium which are partially available to the general user. The two main tools are SPOT and the Data center. SPOT is a scheduling tool developed to facilitate the preparation of observations for targets contained in a large database as is for example the case for the SHINE survey  (Lagrange et al. 2016b). SPOT can be fed with scientific priorities of each target plus a set of constraints such as required field rotation, or air mass or date restrictions.
Acknowledgements. SPHERE is an instrument designed and built by a consortium consisting of  IPAG (Grenoble, France ),  MPIA (Heidelberg, Germany) ,  LAM (Marseille, France), LESIA (Paris, France), Laboratoire Lagrange (Nice, France) ,  INAF -Osservatorio di Padova (Italy) ,  Observatoire de Genève (Switzerland) ,  ETH Zürich (Switzerland) ,  NOVA (Netherlands), ON-ERA (France)  and  ASTRON (Netherlands)  in collaboration with  ESO. SPHERE was funded by  ESO , with additional contributions from  CNRS (France) ,  MPIA (Germany) ,  INAF (Italy) ,  FINES (Switzerland)  and  NOVA (Netherlands). SPHERE also received funding from the  European Commission Sixth and Seventh Framework Programmes as part of the Optical Infrared Coordination Network for Astronomy (OPTICON)  under grant number  RII3-Ct-2004-001566  for  FP6  ( 2004-2008 ), grant number  226604  for FP7 (2009)(2010)(2011)(2012) and grant number  312430  for FP7 (2013)(2014)(2015)(2016).
Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (aGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. aGB and canopy height estimates with their associated uncertainties are derived at a 0.
Remote Sensing users typically have different product requirements compared to those of the ecological and forestry communities. Namely, RS users often (1) need access to AGB estimates at the pixel level, while ecologists and foresters produce area-based estimates derived from individual trees measurements. RS users typically (2)  need products at a consistent spatial resolution, while a variety of plot sizes and shapes have been adopted by ecologists and foresters. Finally, RS users (3) require AGB to be computed via globally and regionally consistent routines, while various approaches have been developed to derive AGB estimates from tree measurements. These communities also operate differently from a funding perspective. Most notably, recurrent investments are needed to maintain permanent forest plots -including censuses that temporally match RS data collection -and to ensure field and botanical staff are paid and trained, without whom the data would not be collected.
# A full list of authors and their affiliations appears at the end of the paper. Correspondence and requests for materials should be addressed to D. S. (email: schepd@iiasa. ac. at) The Forest Observation System -FOS (http://forest-observation-system. net/) -is an international, collaborative initiative that aims to establish a global in situ forest AGB database to support Earth Observation (EO) and to encourage investment in relevant field-based measurements and research  4. The FOS enables access to high-quality field data by partnering with some of the most well-established teams and networks responsible for managing permanent forest plots globally. In doing so, FOS is benefiting both the RS and ecological/forestry communities while facilitating positive interactions between them. To this end, the FOS project has established a data sharing policy and framework that seeks to overcome existing barriers between data providers and users.
For example, data made available on the FOS website are plot-aggregated (i. e. , stand AGB, canopy height, etc. ), while the underlying original tree-by-tree data are managed by participating ecological networks. To ensure that estimates added to the FOS are robust and consistent, a freely downloadable BIOMASS R-package 5 has been upgraded, which makes the procedure for computing plot AGB estimates from tropical forest inventories transparent, standardized and reproducible. There are developments underway to make the package usable for any forest type, including boreal and temperate ecosystems. This work has been complemented by the definition of a set of technical requirements and standards aimed at ensuring data comparability  4. The FOS currently hosts aggregate data from plots contributed by several existing networks, including: the network of the Center for Tropical Forest Science -Forest Global Earth Observatory (CTFS-ForestGEO)  6  , the RAINFOR  7  , AfriTRON  8  and T-FORCES  9  (curated on the ForestPlots.
net platform)  10  , the IIASA network  11, 12  , the Tropical Managed Forests Observatory (TmFO)  13  and AusCover  14. These international collaborations have already (i) invested in establishing permanent sampling plots; (ii) proposed robust protocols for accurate tree mapping and measurement, which are largely standardized across networks; (iii) monitored existing plots repeatedly; and (iv) established databases with particular emphasis on data quality control  10, 15. As the FOS is an open initiative, additional networks (e. g. , GFBI  16  ) and teams that comply with the aforementioned criteria are welcome to join in the future. The data presented here have been partly published before  [17] [18] [19] [20] [21]  , but never in such a unified and comprehensive manner. Results based on some of the plots presented here have impacted a wide range of scientific fields, including tropical forest ecology  [22] [23] [24] [25] [26]  , drought sensitivity of forests  19, [27] [28] [29]  , tree allometry  [30] [31] [32] [33]  , carbon cycles  21, [34] [35] [36]  , remote sensing  18, [37] [38] [39]  , climate change  8, [40] [41] [42] [43]  , biodiversity  [44] [45] [46] [47]  , diversity-carbon relationships  48, 49  and historical forest use  50, 51  , among others.
Methods Within the sample plots, every stem above a defined threshold in diameter at breast height (DBH, usually 1, 5, 7 or 10 cm) was taxonomically identified and the DBH measured, avoiding any buttresses or deformities. In most plots, tree height was measured for a subset of trees that are representative of different diameter classes and tree species in order to develop site-specific height-diameter regression equations. Based on an analysis using the Fig. 1  The Forest-Observation-System. net web portal. tropical forest plot data, as few as 40 tree height observations are sufficient for characterizing this relationship if stratified by diameter  22. All the data presented here were collected from permanent forest sample plots with known locations; accurate coordinates (with an error of less than 30 meters) have been either delivered to the FOS or will be recorded during the next census.
25 ha to 1 ha  17, 53. Clearly there are always size-effort tradeoffs, e. g. , smaller plots would permit greater replication, but by focusing on larger plots that are also permanent, FOS has chosen to focus its efforts on a smaller but high-quality set of plots. Our approach, therefore, excludes the possibility of using databases of smaller plots such as those found in national forest inventories. AGB and associated uncertainties were obtained using a standardized procedure implemented in the BIOMASS R-package  5. For the sake of standardization, we systematically considered only trees having a diameter ≥10 cm (or a 5 cm threshold in the case where these trees contribute substantially (>5%) to the total AGB, e. g. , in savannas). Taxonomy was first checked using the Taxonomic Name Resolution Service, which in turn served to assign a wood density value to each tree using the Global Wood Density Database (GWDD) as a reference  54, 55.
Data Records The data in FOS  58  are organized in a hierarchical structure (Fig. 3 ). The Plot description includes a link to the institution and network. The central part of the database is the Sub-plot table, where geolocation, the date of the census, the people who manage the specific plots, the AGB and the canopy height are stored. The FOS does not store individual tree-level information, only plot-level aggregates. Users interested in tree-level information can contact the contributing networks or the plot PIs using the links provided in the Plot table. • AGB -Above ground biomass (Mg ha -1 ) • AGB_local -aboveground biomass (Mg ha -1 ) estimated using local equations or equation 4 in Chave  30  with wood density, DBH and H derived from local height-diameter relationships. • Cred_2. 5 -lower bound of 95% credibility interval (Mg ha -1 ) • Cred_97.