dataesr/scientific-paragraphs-categorization huggingface dataset:
Functional status Patients in our study were categorized into one of four groups, depending on their FS according to the assessment method described previously by  Townsend et al. in 1995 [3] : FS 1 = normal, pain-free status; 2 = normal or near normal use with pain; 3 = significantly limited use or movement, alternatively requiring some type of prosthesis (e. g. , crutches, walker rollator); and 4 = nonfunctional status (e. g. , bedridden, wheelchair bound). To assess whether patients could walk or use the affected extremity in a meaningful way following surgery and irradiation, we combined patients with FS 1 and 2 (normal function), describing normal FS (± pain), and compared them to the grouped patients with FS 3 and 4 (reduced function). Data on patient FS was gained retrospectively covering four different periods: the outset of RT, which fell close (up to 3 days) to application of the first radiation fraction, and during 1-3, 3-6, 6-12, and 12-15 weeks of the postoperative period.
Statistics All calculations were done with IBM SPSS 25 (SPSS Inc. , Chicago, IL, USA) package software. In addition, two basic distributions and calculations of standard statistical parameters were performed. The differences between frequencies were analyzed using the chi-square test, and prognostic factors were calculated according to the Cox regression model. For the regression analysis, only variables with a distribution of at least 25 cases per group were included. The selection of variables for multivariate analysis required a p Ä 0. 1 on the univariate analysis. Time table analyses of FS and survival were performed using the Kaplan-Meier method. Statistical differences were calculated by the logrank method. P-values <0. 05 were classified as significant; values <0. 01 as highly significant; and values between 0.
Of all operated patients, postoperatively 79% regained walking capacity and 60% required no or only occasionally analgesic drugs. Bone-related complications included failure of the osteosynthetic device or prosthetic implant as well as progression or re-occurrence of the disease within the operative field. In the non-irradiated group, 21% had complications vs. 14% in the patients who had received additional radiotherapy. The difference was remarkable but not statistically significant. More recently, Drost et al. [10]  published a retrospective analysis on need for second surgery, rates of re-ir-radiation, tumor progression and prosthesis displacement following postoperative radiation of infiltrated bone. Data were collected from 65 patients who received postoperative radiation to 74 sites in the extremities.
Only 2 patients required a second surgery (2. 7%) at 9 and 10 months after postoperative radiation. Pain increase requiring re-irradiation was reported in 7 patients (9. 5%), at a median time of 9. 3 months after the delivery of radiation. Of the 47 patients who had radiological imaging available, local progression of bone metastases was seen in 8 patients (17. 0%) and displacement of the prosthesis in 1 patient (2. 1%). The current data confirm the efficiency of surgery combined with postsurgical fractionated external beam irradiation. In the presently investigated group the number of patients regaining normal function following surgery was higher and the functional recovery was achieved faster than in the publication by Townsend et al. [3]. The results of postoperative RT in our patient population suggest that about 80% of patients may achieve a good functional result within 3-4 months after surgery (Fig.
1 Intramedullary nailing 38/55. 8 Complete pathological fracture Yes 48/70. 5 No 20/29. 5 Resection of the secondary site No resection 34/50. 0 Complete or partially complete 29/42. 6 Unknown 5/7. 4 Osteolytic character Yes 48/70. 5 No 20/29. 5 Bisphosphonates Yes 39/57. 3 No 29/42. 7 Inclusion of the entire stabilizing device within the range of Yes 36/52. 9 target volume No 32/46. 1 Number of target volumes irradiated in postsurgical RT (in One 37/54. 4 case of multiple also extraosseous sites were treated) Multiple 31/45. 6 Received normalized total dose TD >35 Gy 33/48. 5 TD Ä35 Gy 35/51. 5 RT radiotherapy, TD total normalized dose pital database as having ICD code C79. 5, regardless of the primary site) were treated with EBRT. Of this group, 126 patients (11. 4%) had undergone a prior orthopedic stabiliz- ing procedure for impending or actual fracture.
Z contrast imaging has been carried out in high angle annular dark field (HAADF) with a probe convergence angle of 25 mrad and an inner collection angle of 58 mrad. The specimens analyzed are lamellas extracted from the samples by focused ion beam (FIB) milling in a FEI Helios Nanolab 600. X-ray Photoelectron Spectroscopy (XPS) data were recorded with a CLAM2 analyser under a base pressure of 5 × 10 -9 mbar using Mg Kα radiation and a constant pass energy of 200 eV and 20 eV for the wide and narrow scan spectra, respectively. The binding energy scale was referenced to that of the C 1s signal of the adventitious contamination layer which was set at 284. 6 eV. The samples were subjected to Ar + sputtering to investigate the in-depth distribution of the different chemical elements. An integral Ar + ion gun was used at 20 keV and 20 mA and an Ar pressure within the analysis chamber of 5 × 10 -5 mbar.
X-ray absorption spectroscopy (XAS) measurements is carried out at the Cu K-edge (8. 98 keV) and Bi L 3 -edge (13. 42 keV) at the beamline BM25A of The European Synchrotron (ESRF) in Grenoble (France). Bi and Cu foils were measured in transmission mode at the beginning of the experiment for energy calibration. Cu 2 O, CuO and Bi 2 O 3 reference samples were also measured in transmission mode. Samples spectra were collected in fluorescence yield mode placing samples at 45 • from the incoming X-ray beam and forming 45 • with the dispersive X-ray fluorescence detector. From three to five spectra were acquired from each sample and merged in order to improve the signal-to-noise ratio. The acquisition time for each energy scan was about 40 min. XAS data were processed using the Demeter package and applying standard methods  28.
Cu/Bi and O/Cu atomic ratios were calculated from the integration of the Cu 2p, O 1s and Bi 4f spectral areas after background subtraction (Shirley method) using the Multiquant XPS software. This package allows taking into account the attenuation brought about by the adventitious carbon layer  17. This is important in the present case, particularly for the Cu/Bi atomic ratio, since the Cu 2p and Bi 4f spectral regions are separated by approximately 800 eV and therefore the signal corresponding to the Cu 2p electrons, that have a much smaller kinetic energy than the Bi 4f ones, is significantly more attenuated by the contamination layer than that of the Bi 4f electrons. Figure  2. a shows the Cu/Bi and O/Cu atomic ratios obtained from the XPS data. It is clear from Figure  2  that the O/Cu ratio decreases rapidly with sputtering time, indicating that the surface oxidic layer is effectively removed by Ar + bombardment (XPS data, not shown, reveal that the most external part of the sample contains both Cu + and Bi 3+ ).
It seems that for low Bi content, Bi atoms incorporates in the Cu lattice, producing a distortion of it at larger local order, which makes difficult to analyze the second shell considering slight distortions of Cu structure. Finally, we performed FMR measurements on two YIG/BiCu heterostructures. The FMR was measured as described in the supplementary information. In order to calculate the damping constant, the measurements were performed at different values of the excitation frequency. Using Kittel's equation for in plane measurements  21, 22  it is possible to obtain the values of effective saturation magnetization and the Landé gyromagnetic factor (g). The continuous line in Figure  S3  corresponds to the fitting of experimental data using this equation %Bi N RCu-Cu( Å) σ 2 (×10 -3 Å2 ) Foil 12 2.
ACKNOWLEDGMENTS This work has been partially funded by  MAT2014-52477-C5 ,  MAT2017-87072-C4  and  MAT2015-64110-C2-2-P  from the  Ministerio de Ciencia e Innovación and Nanofrontmag from Comunidad de Madrid. IMDEA Nanociencia acknowledges support from the  Severo Ochoa Programme for Centres of Excellence in R&D (MINECO , Grant  SEV-2016-0686 ). We acknowledge The  European Synchrotron Radiation Facility (ESRF) ,.
The aim of this project was to update the areas that had been mapped within the framework of EUSeaMap and MeshAtlantic by integrating new geological and oceanographic datasets with improved accuracy, and to undertake the mapping of areas that had not yet been covered, namely the Norwegian Sea, the Canary Islands, the Adriatic Sea, the Central and Eastern Mediterranean and the Black Sea. As a result, EUSeaMap 2016 has achieved a pan-European seabed habitat cartography first initiated by the Irish Sea Pilot, which has gradually led to a comprehensive coverage of the distribution of seabed habitats across Europe. The lessons learned from the above introduced projects and activities, in combination with a growing use of the key products, i. e. BSHMs, have motivated us to synthesize how the BSHMs have been used in the context of 1) the implementation of the MSFD, especially with regard to the MSFD Initial Assessment, 2) the designation and assessment of Marine Protected Area (MPA) networks, and 3) other types of use.
In the Mediterranean, the EUSeaMap 2012 BSHM was used within the framework of that project, to assess the network within the Western Mediterranean EU countries in terms of the coverage of the broad-scale habitats covered by the network. At a basin-wide scale the EUSeaMap 2012 Western Mediterranean map was integrated with a proxy BSHM for the Eastern Mediterranean constructed by intersecting bathymetric data and sediment maps. The latter was used to assess the MPA network across the entire Mediterranean Sea. BSHMs have been used to assess the percentage cover of specific habitats in the network (representativity and adequacy) in all the analyzed reports, followed by the degree of replication of specific habitats, which is performed in most of the identified reports. The connectivity (sometimes referred to as proximity) criterion has been evaluated in the Baltic and Atlantic regions and sub-regions.
Literature Review on the Use of BHSMs in Multiple Pressure Analysis 25 out of the 40 cumulative impact assessment studies reviewed by  [20]  are European. Two of these (  [19]  and  [32] ) have included data layers representing BSHMS in their analyses of the potential impacts of the effects of multiple human stressors. In the study covering the Baltic Sea, BSHMs constitute 57% (8 out of 14; 6 out of 8 originated for BALANCE) of the ecosystem component data layers  [19]. In a similar study in the eastern parts of the North Sea, BSHMs accounted for 38% (10 out of 26; 8 out of 10 originated from EUSeaMap) of the ecosystem component data layers. In an ongoing Danish study of potential cumulative effects, where the objective   [10]  Benthic marine landscape habitat surface area cover (representatives), number of patches (replication), and distance between selected merged benthic marine landscapes (connectivity) occurring within the Baltic MPA network.
2013 French and UK Channel island EUSeaMap  [12]  at EUNIS level 3 Percentage surface area of broad scale habitat types (rep-resentativity) contained within the MPAs contained in the OSPAR database. [ [29] 2015 Celtic Seas EUSeaMap  [12] ; JNCC UKSeaMap Broad-scale habitat maps were used to assess % of broad scale habitat surface area cover (adequacy), size distribution of broad-scale habitat patches (Viability), and distance between broad scale habitats (connectivity) contained within network. Percentage coverage of each broad-scale habitat occurring within the Western Mediterranean EC country MPA network (representativity). [12]  2012 Mediterranean Sea EUSeaMap  [12]  for the western Mediterranean and a proxy broad scale habitat map constructed for the remainder of the Mediterranean. Percentage cover of the generated proxy broad scale benthic habitats contained within the MPA network (representativity), percentage cover of three priority habitats provided in the EUSeaMap broad-scale map for the western Mediterranean was also assessed.
The methods on which these assessments are based originates from  [1] , where pressure data is combined with information on ecosystem components and pressure-specific sensitivity. These studies rely to a relative large extent on BSHMs from BALANCE and EUSeaMap and would probably not have been as successful without these maps. Further, we are aware of ongoing activities updating the Baltic study and aiming at a provisional pan-European assessment of potential cumulative pressures and impacts in Europeans seas, where both rely on the produced BSHMs (EUSeaMap).
Acknowledgements The authors would like to thank  EU DG MARE for funding of EMODnet Seabed Habitats. This study includes data gathered through a survey, where all survey participants were informed that their replies would be used in a peer-reviewed publication on the use of BSHMs in Europe. According to institutional guidelines and national laws, no ethics approval was required. Hence, participants' consent was given by survey completion. Further, we thank the participants in the survey.
In experiments without MET addition, the same procedure was followed using pure ACN evaporated in distilled water to account for possible effects of ACN traces. ACN was never detected in the headspace of MET aqueous solutions (data not shown). Control experiments (performed in duplicate) consisted in filter-sterilized water spiked with MET to evaluate abiotic MET dissipation. To maintain aerobic conditions while limiting water loss and avoiding contamination, a 0. 22 µm syringe filter was mounted on a syringe tip stuck through the vial cap. Oxygen concentration in each microcosm was monitored weekly with oxygen sensor spots (PreSens Precision Sensing GmbH, Germany) fixed to the inner face of the bottles before autoclaving. Oxygen concentrations from 5 to 8 mg L -1 confirmed oxic conditions throughout the experiment (Supplementary Section C).
Laboratory experiments with or without addition of MET were incubated for 21 days, a duration typical of reported MET half-life values (The Pesticide Properties DataBase  [PPDB], 2006). Mean groundwater temperature was 15 ± 1. 3 • C. Experiments were incubated at the reference temperature for standardized testing of pesticides based on OECD guidelines of 20 • C (Organisation for Economic Cooperation and Development  [OECD], 1981). Experiments were incubated without stirring because (i) oxygen was continuously monitored and was not rate-limiting for bacterial growth  (Hensler and Schedel, 1991) , and (ii) stirring may artefactually alter the diversity of groundwater bacterial communities adapted to heterogeneous aquifer microenvironments and non-turbulent flows. At the end of incubations, water samples from each duplicate experiment were collected using sterile glass syringes for MET, TP analysis (2 × 15 mL) and the Microtox R assay (2 × 15 mL) (see below).
T-RFLP Analysis of Groundwater Samples Bacterial 16S rRNA gene fragments (0. 9 kb) were PCRamplified using 5-carboxyfluorescein (6-FAM) labeled 27 f and 927 r primers as described previously  (Mauffrey et al. , 2017). T-RFLP electrophoregrams were analyzed with PeakScanner V1. 0 (Applied Biosystems, Carlsbad, CA, United States). Noise cancelation, peak alignment and matrix (samples × T-RFs) generation was performed using T-REX 1  (Culman et al. , 2009). Peak heights were normalized to the same total fluorescence per sample, and resulting data matrices were used for statistical analysis.
Illumina MiSeq Sequencing and Data Processing Sequencing of laboratory exposure experiment samples was performed at INRA-UR0050-LBE (Narbonne, France) using Illumina MiSeq. The 16S rRNA gene spanning hypervariable region V4 and V5 was amplified in a twostep process including a set of multiplex indexed primers (U515F 5 -GTGYCAGCMGCCGCGGTA-3 and U909R 5 -CCCCGYCAATTCMTTTRAGT-3 )  (Walters et al. , 2011). Individual PCR products were purified and quantified using Qubit dsDNA HS Assay Kit R (Invitrogen, France), and a pool of equimolar amounts of each amplicon was prepared. A final gel purification step ensured elimination of non-specific products. The combined library was loaded onto the Illumina MiSeq Platform using a standard MiSeq paired end (2 × 250 bp) flow cell and reagent cartridge. Denoising, chimera checking, generation of operating taxonomic units (OTUs) and taxonomic classification were performed using Mothur software package v.
1. 33. 2  (Schloss et al. , 2009)  by following the default parameters from the analysis pipeline of MiSeq SOP 2. The detailed protocol is provided in Supplementary Section B. Obtained sequences were deposited in the NCBI BioProject database (BioProject ID: PRJNA393085). Obtained sequences analyzed using Mothur were clustered to define OTUs at 98% sequence identity. A subsample of sequences was randomly selected to obtain equally sized datasets according to the standard operating procedure  (Schloss et al. , 2009). The resulting datasets were used to calculate Shannon and inverse Simpson diversity indices and the Chao1 richness estimate using R, and for rarefaction analysis as previously described  (Babcsányi et al. , 2017).
PICRUSt Analysis Functional profiling of bacterial communities was predicted by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt)  (Langille et al. , 2013)  by classifying bacterial sequences against the Greengenes database  (McDonald et al. , 2012) ; 13 August 2013 version. OTUs were defined based on automatic 98% sequence identity. The biom file generated within Mothur command-line was uploaded into Galaxy 3 for preprocessing, the output file was analyzed using STAMP  (Parks et al. , 2014) , and retrieved metagenomic profiles were further analyzed using multivariate statistical analysis.
Illumina MiSeq sequencing data and PICRUSt profiles were classified separately by cluster analysis to investigate the relationship between bacterial communities exposed to different levels of MET. Hierarchical cluster analysis was carried out to identify robust groupings of sequence data and PICRUSt profiles based on the distances supplied in a hierarchical manner. For both analyses, distance between Hellinger-transformed datasets was computed based on the Hellinger distance. A hierarchical cluster analysis was performed on the resulting dissimilarity matrix using Ward's method  (Ward, 1963). The optimal number of clusters was determined using Spearman's rank correlations  (Becker et al. , 1988).
16S rRNA OTUs as Potential Biomarkers of MET Exposure PICRUSt-based predictions suggest the occurrence of only slightly distinct gene complements in the bacterial compartment of the two tested groundwater wells, despite markedly different contamination histories. This contrasts with previous work on diverse environments contaminated with hydrocarbons, where specific functional modules were identified that then served as biomarkers to distinguish between different oil contaminated sites  (Mukherjee et al. , 2017). Thus, and in the absence of known functional markers for MET degradation, we last asked the question whether taxonomical 16S rRNA gene OTUs that exclusively responded to MET as potential biomarkers of MET exposure could be identified, by comparison of identified OTUs across the different microcosms.
98 × 0. 98 μm. Data Analysis WorkbeNch (DAWN) software  37  was used to view and reconstruct the XRT images of each sample and Avizo ® was used to produce 3D renders of the XRT data using the generate surface module for specific ranges in greyscale (X-ray intensity) representing each examined material. Two horizontal XRPD line scans were measured across the 0. 5 mm width of each metal sample at two heights along the length of the sample. CeO 2 was used for beam calibration (NIST -Standard Reference Material 674b). Within the grout, the uranium rod orientation and position changed, resulting in a 1-2 mm variance in sample to detector distance from the central CeO 2 position. Small shifts in the 2θ value of the XRPD peaks were therefore expected when comparing data. Dawn software for 2D diffraction and processing tools  38  was used to produce 2D XRPD patterns to 1D.
Aqueous chemistry. 5 ml of the residual water was removed from the N2L, A6L and A47L water to measure the aqueous 238 U concentration using a VG Thermo Elemental PQ3 ICP-MS. Samples were prepared for ICP-MS by a set dilution in 1% nitric acid (analytical quality concentrated HNO 3 in Milli-Q water). Blanks and uranium standards were also prepared in 1% nitric acid. An internal bismuth standard of 10 ppb was also added to all blanks, standards and samples. Data underlying this article can be accessed on Zenodo at https://doi. org/10. 5281/zenodo. 1118280 and used under the Creative Commons Attribution licence.
Acknowledgements The authors would like to thank  Diamond Light Source  for access to beamline I12 (Experiments  EE8336  and  EE9127 ) that contributed to the results presented here. Also to the beam line staff,  Christina Reinhard ,  Robert Atwood  and  Michael Drakopoulos  for their technical and moral help throughout the beam time. Thanks must also go to the  Bristol Physics Workshop team  and  Bob Humphreys  for help in making the reaction cell. This work was funded by  EPSRC  and  Radioactive Waste Limited  under the  GEOWASTE program  ( EP/I036397/1 ) and was further supported by the  Sellafield Centre of Excellence in Uranium  and  Reactive Metals.
A final elongation at 72 °C for 7 min was carried out. We cloned the resulting 18S rRNA amplicons to identify individual fungal sequences using the Topo TA Cloning System (Invitrogen) following the manufacturer's instructions. Clone inserts were then amplified by PCR using flanking vector primers, and the inserts of expected sizes were sequenced bidirectionally with vector primers (Beckman Coulter Genomics, Takeley, U. K. ). Two closely related chytrid sequences were identified and compared with sequences in the GenBank nr database using BLAST  (Altschul et al. 1990 ). The new sequences and those retrieved by BLAST were aligned using MAFFT with the accurate '-linsi' option  (Katoh et al. 2002). The multiple alignment was trimmed with TRIMAL  (Capella-Gutiérrez et al. 2009) , and a Bayesian phylogenetic tree was reconstructed using MrBayes  (Ronquist et al.
2012)  applying the GTR + G + I model with four chains and 10,000,000 generations. After checking for convergence, the first 15,000 trees were eliminated as burn-in, and a consensus tree was constructed by sampling every 100 trees. The new Apiochytrium granulosporum strain X-124 18S rRNA sequences have been deposited in GenBank under accession numbers X-124a -MK179157, X-124b -MK179158.
Intron S943 phylogeny Intron localization was defined by comparing the assembled contig with other sequences from the NCBI nr database using BLAST. Insertion positions were identified using the 16S gene reference of Escherichia coli  (Cannone et al. 2002 ; http:// www. rna. icmb. utexas. edu/SAE/2C/rRNA_Introns). Additional SSU sequences containing intron S943 were downloaded from GenBank. Sequences were aligned with MUSCLE  (Edgar 2004 ) and manually adjusted in BioEdit  (Hall 1999). Bayesian inference was calculated with MrBayes applying the GTR + G + I model with four chains and 10,000,000 generations. After checking for convergence, the first 50% trees were eliminated as burnin, and a consensus tree was constructed. The resulting Bayesian tree was visualized using the iTOL web tool  (Letunic and Bork 2016).