dataesr/scientific-paragraphs-categorization huggingface dataset:
Salamanca et al. (2011)  conducted simulations with high resolution urban canopy parameters in Houston, and revealed that a simple bulk urban scheme is sufficient for an estimate of the 2-m temperature in an urban area. However a complex urban canopy scheme and a high resolution urban canopy parameter database (e. g. , urban fraction, building height and building area) are necessary for an evaluation of the urban heat intensity or the energy consumption due to air conditioning. The anthropogenic heat release is an important variable for accurate modelling of air temperature over urban areas. However it is difficult to estimate representative values for urban areas. The effect of the anthropogenic heat release has been studied by  Dupont et al. (2004) ;  Sailor and Lu (2004)  and  Fan and Sailor (2005)  over the U.
2007; Korsakissok and Mallet 2010; Sciare et al. 2010; Roustan et al. 2011; Royer et al. 2011). This paper aims at evaluating the relative impact of the PBL scheme used in the WRF model and the use of an UCM over Greater Paris. The WRF/urban model is evaluated over Greater Paris during May 2005. The model is compared to in-situ measurements of temperature, wind speed and humidity at a ground station (Palaiseau), a tall mast (Saclay), a radiosonde station (Trappes), and an observation deck at a height of 319 m on the Eiffel Tower (Paris). Furthermore, mobile lidar data from the LISAIR (LIdar pour la Surveillance de l'AIR, Raut and Chazette 2009) campaign are used to estimate PBL height. The paper is organized as follows: first, the settings of the WRF model used here are described. Second, meteorological measurements used for comparisons to modelled results are detailed, and then the different methods used for estimation of PBL heights are briefly presented.
Simulation Settings The regular latitude-longitude map projection is used for three simulation domains with two-way nesting. The horizontal grid spacing of the coarse domain is 0. 5 • , and 0. 125 • and 0. 03125 • , respectively, for the two nested domains. The largest 0. 5 • domain covers Europe and the smallest domain covers Greater Paris. The U. S. Geological Survey (USGS) Global Land Cover Characteristics (GLCC) database is used (10-arc minute, 2-arc minute and 30-arc second land-use data for the three domains, respectively). There are 28 vertical levels refined near the surface and the pressure at the model top is 100 hPa. The physical parametrizations used include the Kessler microphysics scheme  (Kessler 1969) , the RRTM longwave radiation scheme  (Mlawer et al. 1997 ), the Goddard shortwave scheme  (Chou and Suarez 1994) , the Grell-Devenyi ensemble cumulus parametrization scheme  (Grell and Devenyi 2002)  and the Noah land-surface model  (Chen and Dudhia 2001).
2011). The contribution of traffic emissions may also be underestimated in the local emission inventory used in this study. Figure  1  presents the diurnal variation of Q F for Paris in May. The USGS land-use data are commonly used in the WRF model. However, this database was created in 1993 and the land-use changes between 1993 and 2005 are important over Greater Paris according to the database of the European Environment Agency (EEA). Therefore, the recent Coordination of Information on the Environment (CORINE) land-use data of EEA is used instead of the USGS data. In order to use the CORINE landuse data in the WRF simulations, the land-use categories of the CORINE land-use data were converted to the categories of the USGS data following  Pineda et al. (2004). The geographical coordinate system of the CORINE land-use data, European Terrestrial Reference System 1989 (ETRS89)-Lambert Azimuthal Equal Area (LAEA) is not directly usable in the WRF model.
Thus the reprojection of the coordinate system to World Geodetic System 1984 (WGS84) was carried out following  Arnold et al. (2010). The CORINE land-cover 2006 raster data (version 13) with a resolution of 250 m, which are freely available at http://www. eea. europa. eu/data-and-maps/data/corine-land-cover-2006-raster, were used for this study. Figure  2  displays the changes of dominant land-use category from the USGS data to the CORINE data. The category for urban and built-up land (category 1) is dominant in Paris in both the USGS and the CORINE data but the category 1 area is extended southwards and westwards from Paris in the CORINE data. Lidar data are also used to estimate the PBL height. A ground-based mobile lidar (GBML) was used during the air quality observation campaign, LISAIR, over Greater Paris from 24 to 27 May 2005  (Raut and Chazette 2009).
Effects of the UCM and the CORINE Land-Use Data Impacts of the UCM and the CORINE land-use data on the meteorological fields are studied by comparing the reference simulations of the previous section (hereafter Reference) to simulations that use the UCM coupled to the CORINE land-use data (hereafter UCM-CORINE). Simulations are compared for the two PBL schemes that were the best performed in the previous section (the YSU and the MYNN schemes).
Impact on Temperature When the UCM is used, the sensible heat flux in the urban area increases. The increase is due to the anthropogenic heat flux and to differences in energy balance resulting from different geometric and thermal parameters in the UCM. The increase of the sensible heat flux results in an increase in surface temperature. The surface temperatures for the UCM-CORINE simulations are higher than the Reference simulations, especially during nighttime (0. 8 K on average for both YSU and MYNN, see Fig. 4 ). Influences of the UCM and the CORINE land-use data on the 100-m temperature are lower than influences on the 2-m temperature, partly because the 2-m level is within the urban canopy. Outside the canopy (100m temperature), the UCM-CORINE performs better than the Reference, as the temperature is underestimated by the model.
Impact on PBL Height The UCM increases the PBL height over urbanized surface. This increase is more important during nighttime than during daytime. Accordingly, the increase with the UCM-CORINE simulation of the modelled PBL heights at Trappes is 8 % for the YSU scheme and 5 % for the MYNN scheme during daytime while it is 15 % for the YSU scheme and 200 % for the MYNN scheme during nighttime. Figure  10a , b display the mean PBL heights from 6 May to 27 May over Greater Paris by simulations with and without the UCM and the CORINE land-use data. The PBL heights are greater with the UCM-CORINE simulation than with the Reference simulation in Paris and the near suburbs. The maximum difference of the mean PBL height is about 290 m near Orly airport located south of Paris (see Fig. 10c ). The effect of using the CORINE land-use data rather than the USGS data is shown in Fig.
10d , which shows differences of the PBL height between the UCM-CORINE simulations and a simulation with the UCM and the standard USGS land use. The influence of the CORINE land-use data on the PBL height is not significant in Paris while it is significant over urbanized areas mostly between 10 and 30 km from Paris. Compared to the GBML measurements, modelled PBL heights are also significantly influenced by the UCM and the CORINE land-use data (see Fig. 9 ). For the measurements from Palaiseau to Paris centre, as well as for the measurements at the main road and the beltway of Paris, the UCM-CORINE simulations produce better results than the Reference simulations, as the modelled PBL heights are higher. However, PBL heights are still underestimated on 25 May (see Fig. 9b ). Although the surface atmospheric stability is reduced by higher surface temperatures using the UCM, this influence is not significant because of a strong temperature inversion (increase in temperature with altitude) for the modelled temperatures at low altitudes.
Conclusion Meteorological modelling of the PBL over Greater Paris is performed using the WRF model for the period from 6 to 27 May 2005. As modelled meteorological data in the PBL have previously shown to be very sensitive to the PBL scheme, simulations were performed with various PBL schemes. Meteorological data obtained with the ACM2, MYJ, MYNN and YSU PBL schemes were compared to observations at various meteorological stations around Paris and its suburbs. For air temperature, the errors of the modelled values are in the range of the errors obtained in previous studies and the MYNN scheme performs slightly better than others. However, the amplitudes of the diurnal cycle of the temperature are underestimated, particularly during daytime; and the underestimations tend to increase with altitude.
Including the UCM and the CORINE land-use data produces more realistic modelled meteorological fields. Improvements in the temperature and the specific humidity modelling using UCM-CORINE are low, but the modelling of the wind speed, the relative humidity and the PBL height is significantly improved using UCM-CORINE. In particular, modelled PBL heights with the MYNN scheme during nighttime are strongly influenced by UCM-CORINE (200 %). Influences of using the UCM and the CORINE land-use data on the modelled meteorological fields are greater than those using different PBL schemes, while the latter are greater for the upper air temperatures (above 40 m) and the PBL heights estimated using radiosonde profiles at Trappes. Compared to the PBL heights observed by lidar measurements, the influences of using different PBL schemes at Palaiseau are more important than those of using the UCM and the CORINE land-use data, while the latter are more important at the centre of Paris.
Our results show that the use of a urban canopy model is crucial for meteorological and air quality modelling over the centre of Paris. Further work should be devoted to the study of uncertainties in the UCM, for example, by using a multi-layer model. Multiple urban land-use categories (e. g. , high intensity, medium intensity, and low intensity) should also be used. Multiple urban land-use categories are available in the CORINE land-use data, and should be mapped to a data type that can be used in the WRF model. Further work will also focus on evaluating the impact of the meteorological modelling on pollutant concentrations (O 3 , NO 2 , PM) within the PBL.
Model description The ocean model used in this study is the Nucleus for European Modelling of the Ocean (NEMO) in the ORCA025 and ORCA1 configurations  (Madec, 2008). The ORCA025 configuration is similar to the one used in  Blaker et al. (2012). For both resolutions, the model has 64 vertical levels with layer thickness increasing from 6 m at the surface to more than 200 m at the bottom. The surface forcing is obtained using 6-hourly winds and daily fluxes for heat and freshwater obtained from the DFS3 dataset  (Brodeau et al. , 2010)  and the bulk formulation according to  Large and Yeager (2004). For salinity a weak restoring with a time constant of 180 days is used to prevent salinities from drifting. With a horizontal resolution of 1/4 • ORCA025 is eddypermitting, and a horizontal resolution of 1/4 • has been shown to produce a satisfactory mesoscale ocean eddy field up to mid-latitudes (e.
As in the box model we will use the standard deviation of the differences between A025 and B025 (and between  Note that the method introduced above will allow us to provide a quantitative estimate of the chaotic MOC variability in a statistical sense. This means that we will only be able to make statements about the chaotic MOC variability on timescales that are short compared to the duration of the simulations. Since we want to avoid the initial phase of the model integrations where strong drifts occur, we are limited to 25 yr-long datasets (period from 1976 to 2001). We can therefore obtain estimates of the standard deviation of the chaotic MOC variability on subannual to interannual timescales, but we will not be able to comment on the likely amplitude of the chaotic MOC variability on decadal timescales.
Acknowledgements. This work was supported by the  RAPID-WATCH  project  VALOR  ( NE/G007772/1 ), the  NERC  project  MESO-CLIP  ( NE/K005928/1 ) and was also part of the  DRAKKAR  project. We enjoyed discussions with  Thierry Penduff  and  Florian Sévellec. We also thank  Balu Nadiga  and an anonymous reviewer for their constructive comments that helped to improve the paper. Edited by:  M. Hecht.
Acknowledgments The authors would like to especially thank  Carlo Angelantonj ,  Pablo Cámara ,  Jan Manschot ,  Sameer Murthy ,  Jan Troost  and  Sanders Zwegers  for extremely fruitful discussions and invaluable help. They are also very much indebted to  Emilian Dudas  for constant support and help, and acknowledge his participation to the initial phase of the project. They also benefitted from enlightening discussions with  Ignatios Antoniadis ,  Ioannis Florakis ,  Dumitru Ghilencea ,  Elias Kiritsis  and  Boris Pioline. They  acknowledge partial support from the  LABEX P2IO , the  ERC   Advanced Investigator Grant  no. 226371  " Mass Hierarchy  and  Particle Physics at the TeV Scale" (MassTeV) , the ITN program PITN-GA-2009-237920, the  French ANR  contracts:  TAPDMS ANR-09-JCJC-0146  and  05-BLAN-NT09-573739 , and the  IFCPAR CEFIPRA  program  4104-2.
Based on our investigations we can provide recommendations on when and where to use which model (Table  3 ). We recommend the use of a posteriori models over RCM-tag for historical or near-real time studies as a posteriori models are more flexible in their input data (they can, for example, draw on existing climate model, reanalyses or observational data sets). For future scenarios, new climate model runs may be necessary anyway and RCM-tag would be suitable, but offline methods can of course handle this as well. Regarding the most suitable method for a certain spatial scale it is logical that a very accurate method as RCM-tag is recommended for local studies, whereas this would be computationally costly on larger scales. WAM is not recommended for the localscale studies, especially in the tropics, where the wind shear factor is low, meaning a highly sheared system (Eqs.
Acknowledgements. R. J. van der Ent and  H. H. G. Savenije  did this work as part of the research program  Division for Earth and Life Sciences (ALW) , which is financed by the  Netherlands Organization for Scientific Research (NWO). O. A. Tuinenburg  did this work as part of the  European Union  ( FP6 ) funded Integrated Project WATCH. H. -R. Knoche  and  H. Kunstmann  did this work as part the  GLOWA-Volta  project and the  WASCAL  project. We thank  Bart van den Hurk ,  Helge Goessling  and one anonymous reviewer for their constructive comments. Edited by:  B. van den Hurk.
We sought to assess the extent to which pain relief in chronic back and leg pain (CBLP) following spinal cord stimulation (SCS) is influenced by patient-related factors, including pain location, and technology factors. A number of electronic databases were searched with citation searching of included papers and recent systematic reviews. All study designs were included. The primary outcome was pain relief following SCS, we also sought pain score (pre-and post-SCS). Multiple predictive factors were examined: location of pain, history of back surgery, initial level of pain, litigation/worker's compensation, age, gender, duration of pain, duration of follow-up, publication year, continent of data collection, study design, quality score, method of SCS lead implant, and type of SCS lead. Betweenstudy association in predictive factors and pain relief were assessed by meta-regression.
Literature Searches Studies were initially identified from a previous systematic review undertaken by some of the authors (RST, RJT). 11 This list of studies was updated by searching the following electronic databases from the end date of the previous review ( Portal and ClinicalTrials. gov) were searched for information on current or recently completed studies. ] [18]  Issues of the journal "Neuromodulation" were hand searched up to September 2012. Two reviewers (RST and RJT) independently scanned all the titles and abstracts and identified potentially relevant articles to be retrieved. Where there was uncertainty, full-text copies of papers were obtained.
Data Extraction The following categories of information were extracted from included studies: study population baseline characteristics (eg, age, gender, duration and location of pain); (2) SCS intervention (ie, use of test screen, type of internal implant generator, lead and placement method, stimulation parameters); study characteristics (eg, study design, country of publication, length of follow-up); and outcome results. Where studies assessed outcomes at more than one follow-up, we extracted the latest follow-up.
In addition to the assessment of patient-related outcomes, such as healthrelated quality of life and functional capacity, studies should collect pain outcomes in both the leg and back, to enable better understanding of the target of neurostimulation. We are aware of two randomized trials of SCS currently being undertaken in back pain. The first is a multicenter French study that aims to compare the analgesic efficacy of mono-column SCS (using longitudinal and transverse electric stimulation) versus mono-column SCS (using axial stimulation, represented by quadripolar or octopolar lead; ESTIMET, NCT01628237). A total of 115 patients with lumbar pain will be randomly allocated to each of the SCS approaches and their leg and back pain, function, level of depression, healthrelated quality, and costs at 6-and 12-month postrandomization.
Second, a multi-country randomized trial (PROMISE, NCT01697358) is ongoing. Two hundred and twelve patients with FBSS presenting with predominant back pain will be randomized to SCS using a tripolar 16-contact lead plus optimal medical management as compared to optimal medical management alone in a postoperative CBLP population with predominant back pain. This parallel designed trial aims to assess outcomes at 6 to 24-months including leg and back pain relief, health-related quality of life, functional capacity, and costs.
Demographic and clinical data Demographic data and history of MS, including MS course, number of relapses within the previous 24 months, date of disease onset, and all ongoing MS treatments, were collected at baseline. At baseline and subsequent evaluations, patients underwent a neurological evaluation, including and MS course. Neurological disability status was assessed using a neurologist-rated Expanded Disability Status Scale (EDSS) including eight Functional Systems scores (FS)  [15] : pyramidal, cerebellar, brainstem, sensory, bowel and bladder, visual, cerebral, and other. Each of the FSS is an ordinal clinical rating scale ranging from 0 to 5 or 6. The EDSS is an ordinal clinical rating scale ranging from 0 (normal neurologic examination) to 10 (death due to MS). Treatment and clinical relapses (defined as the appearance of a new symptom or group of symptoms, or the worsening/reappearance of old symptoms lasting at least 24 hours, in the absence of fever and preceded by stability or improvement for at least 30 days) were also recorded.
Patient characteristics In total, 600 patients were enrolled from 12 countries between November 2007 and October 2010; 1 patient was excluded because of a protocol violation (eligibility requirements not met) and 19 patients were excluded due to missing QoL data at months 6, 12, 18, and 24 (Figure  1 ). The final sample comprised 580 patients. The 24-month EDSS was available for 524 of 536 patients assessed at 24-month. A total of 417 (79. 6%) patients were defined as non-worsened and 107 (20. 4%) patients were defined as worsened. The baseline demographic characteristics differed between worsened and non-worsened subjects, with worsened patients on average being older, with higher baseline EDSS scores and a higher proportion of primary and secondary progressive MS than non-worsened patients (Table  1 ).
Acknowledgments We are greatful for funding of this work by  EQECAT, Paris  and by the  Federal Ministry of Education and Research in Germany (BMBF)  through the research programme MiKlip (FKZ:  01LP1104A ). Additional funding has been received from the  People Programme  ( Marie Curie Actions ) of the European Union's  Seventh Framework Programme  (FP7/2007-2013) under REA Grant agreement No. PCIG11-GA-2012-322208. We thank  Dominik Renggli ,  Tim Kruschke  and  Henning Rust  for valuable discussions and technical support. We would also like to thank the two anonymous reviewers for their comments, which helped to improve the manuscript. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Acknowledgements: We are very grateful to  Peter Forrester  for his idea of using circular ensembles for the heuristics above, and also for drawing our attention to [Ja]. We also thank the anonymous referee for a careful reading and very interesting comments. A. B. thanks  Alan Edelman  for help with numerics and S. S. thanks  C. Sinan Güntürk  for helpful discussions related to Section 4. A. B. was partially supported by  NSF  grant  DMS-1056390 , S. S. was supported by a  EURYI award. We also thank the  MSRI  for support to attend a workshop where this work was initiated.
Rarer members of the community were more easily detected in the larger pyrosequencing datasets. This study also revealed that more than 27% of reference rumen fungal sequences retrieved from GenBank was misnamed at the genus level, which confounds efforts to compare communities. In-depth rrs sequencing shows that the community structure of rumen bacteria is affected by changes in diet composition  (Callaway et al. , 2010; Pitta et al. , 2010). The community structure in the lower gastrointestinal tract is, as expected, different from that of the rumen  (Callaway et al. , 2010)  but also greatly influenced by diet  (Callaway et al. , 2010; Durso et al. , 2010; Shanks et al. , 2011). The complexity of the feed seems to favour diversity. Rumen communities associated with bermudagrass diets, rich in structural carbohydrates and secondary compounds, were more diverse than those associated with growing wheat forage  (Pitta et al.
However, most studies identified Prevotella as an important, if not the predominant, genus in the community. These studies also confirm that the cultivated cellulolytic bacterial genera Ruminococcus and Fibrobacter are not among the most abundant members of the community, but detected instead the presence of various other fibredegrading genera  (Brulc et al. , 2009; Pitta et al. , 2010). Deep sequencing produces useful and extensive coverage of the microbial diversity, allowing us to identify the prevalent 'core' members of the community but also 'rare' community members that could be associated with feeding practices (Shanks et al. , 2011). The rare members are otherwise not detectable using less sensitive techniques  (Pedros-Alio, 2006). Notwithstanding, this expanded rrs dataset generally confirms information that was suggested by fingerprinting approaches or shallow sequencing of clone libraries.
It has to be noted that these type strain might have some differences with strains evolving in their natural habitat, as their genetic makeup can change over generations  (Papadopoulos et al. , 1999)  and mutations can arise induced by the culture media  (Deng and Fong, 2011). In addition, variability within single species also exists  (Hansen et al. , 2011). Sequencing newly obtained isolates and single cells from the rumen will both determine the validity of type strains as models and inform the intraspecies variation in the wild population. The bacterial genome sequences completed to date have added a tremendous amount of gene sequences to the growing database of rumen microbial genes. The closed bacterial genomes alone have so far identified over 27 000 protein coding sequences, and this is likely to double in the near future with the closure of several draft genomes and the instigation of new rumen microbial genome projects.