dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusions This study focused on the local vegetation trends in drylands of Western Africa (Sahel of Mali and Senegal) over the 1982-2010 period. Two long-term satellite datasets of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) derived from Advanced Very High Resolution Radiometer (AVHRR) data were considered: Geoland Version 1 (GEOV1) and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g). Biomass ground measurements and rainfall data supported a quantitative validation of detected trends in satellite products. Auxiliary information and expert knowledge of the study areas allowed a qualitative validation and interpretation of the local observed trends. Our results show that the choice of the dataset has significant impact on the results. The study seems to indicate that, compared to GIMMS3g, the spatial pattern of GEOV1 trends show a better agreement with ground data, rainfall pattern, land-cover, land management of the two study areas in the Sahel of Mali and Senegal.
The differences in the processing lines (input reflectances and retrieval algorithms) seem to play a role in the observed differences rather beside the differences in their spatial resolution. Note however that our conclusions on the accuracy of GEOV1 and GIMMS3g time series for trend detection analysis are limited to the study areas. An extensive validation and comparison of both datasets at global scale should be addressed in a forthcoming study. This study shows the potential of GEOV1 for local trend detection. However, some inconsistencies have been detected in the GEOV1 dataset and are being to be corrected. Correction will be achieved through a second version of Geoland Version 2 (GEOV2) products from VEGETATION (VGT) and AVHRR sensors which is expected to contribute to global climate monitoring and earth science modelling applications.
Neither the re-greening nor the desertification paradigm can be generalized as both are present at a local level. for GEOV1 data and the DLR/RESA for RapidEye imagery. Aleixandre Verger is recipient of a Juan de la Cierva postdoctoral fellowship from the Spanish Ministry of Science and Innovation. The authors thank the anonymous referees for significantly improving the manuscript. This publication was funded by the German Research Foundation (DFG) and the University of Bayreuth in the funding programme Open Access Publishing.
Acknowledgments The authors thank the colleagues from the  CSE , especially  Moussa Sall  for a great collaboration and for collecting and sharing biomass data for such a long time period. The research is part of the  BMBF  funded project micle, which aims to find linkages between climate, environment and migration. We would like to thank all the guides, drivers and translators in the field (mainly  Mohammed Lecor  and  Yaya Koetioumbe ) as well as the project colleagues, especially  Clemens Romankiewicz ,  Raphael Spiekermann  and  Tobias Grau. Further thank goes to  Z. Zhu  for providing GIMMS3g data, Geoland2.
4 MPa checked with a vapour pressure osmometer (Vapro 5520; Wescor Inc. , Logan, UT, USA). Mannitol treatment was applied during the dark period 12 h before the light was switched on. In this experiment, the nutrient solution was renewed every 24 h. Other environmental data were measured and stored as above. LER was measured as presented earlier  15  when the tip of the sixth leaf appeared above the whorl and lasted until the appearance of leaf 8. During both EP and continuous light, the amplitude of oscillations was calculated as ((LER max -LER min )/LER max ), where LER max and LER min are the maximum and minimum values of LER, respectively. In continuous light, subjective dusks and dawn were defined as the times at which LER were minimum and maximum, respectively (Fig. 1d ). In this calculation, values of LER were averaged over 3 h around minimum or maximum, and over two consecutive subjective dusks during EP.
Transpiration rate was estimated every 15 min from the change in pot weight  15. Leaf water potential was measured  15  at pre-dawn and every 12 h in experiments 4, 9 and 21. Gas exchanges were measured every minute on the fully developed fifth leaf of one plant during 48 h with a gas analyzer (LI-6400, LICOR, Lincoln, NE, USA), and every hour in the same leaf of 10 plants with a diffusion porometer (AP4; Delta-T Devices) calibrated every 30 min. Only measurements performed with high and medium evaporative demands provided consistent data and are presented here (experiment 4). Quantitative RT-PCR and transcriptome analysis. Six-cm-long elongating tissues of leaves 7, 8 and 9, and the 5 cm behind root tips were sampled 1 h before light and every 12 h after the light was turned on (peaks of LER oscillations) in experiments 3, 20 and 21, with three (experiment 3) or four (experiments 20 and 21) biological replicates.
RNA extraction, complementary DNA synthesis and realtime PCR were performed as previously described  50. Data were analyzed by the 2 À DDCt method 51 and normalized using three reference genes, ACT1 (accession number gi: 450292), EF1-a (gi: 2282583) and polyubiquitin (gi: 248338). The oligonucleotide microarray Maı ¨s 45K BGA (Roche NimbleGen Inc. , Madison, WI, USA) was processed and analyzed as in ref. 15. Three samples of the leaf growing zone were collected 1 h before the light was turned on, 12 and 24 h after it in experiment 4. Total RNA, RNA integrity, complementary DNA synthesis, purification and labelling, overnight hybridization (16 h at 42 °C) and laser acquisitions were performed as earlier  15. Intensities were extracted, filtered and normalized with the NimbleScan software. Raw hybridization intensities were normalized across all arrays with Robust Multichip Average Express (RMA) in which the quantile normalization method was employed  52.
Data were imported into R (R Core Team, 2013, http://www. R-project. org). Change with time in transcript abundance corresponding to a given probe was considered as significant if (i) the P-value was o0. 05 in a t-test and (ii) it differed by a factor 41. 5 between times of sampling. Values shown in Fig. 4  and Supplementary Fig. S9  are log 2 (t 0 /t n ), where t 0 and t n are the values at dawn and at time n. Functional annotation was enriched with homologous genes of other species identified by BLASTp against plant protein sequences from Uniprot (http://www. uniprot. org/) and Rice Protein sequences (MSU Rice Genome Annotation Project Release 6. 0). The classes of genes presented in Supplementary Fig. 3  were prepared following the ontologies of MapMan (http://gabi. rzpd. de/projects/MapMan) for maize Zm_B73_ 5b_FGS_cds_2012 (http://mapman.
gabipd. org/web/guest/mapmanstore). Transcript analyses of plants grown under low evaporative demand (entrainment and continuous light) were obtained from a published study 2. The day VPD calculated from author's data was 1 kPa, with a photoperiod of 12 h light and 12 h dark. The data set containing the normalized expression values of each probe and the functional annotation of maize transcripts in the microarray was obtained from (http://www. biomedcentral. com/1471-2229/10/126). Model of water transfer. The model is derived from that of Tardieu and Davies 53 run at a time step of 1 min (Supplementary Fig. 13 ). Water flows from soil to air via plant compartments, following gradients of water potential from the rhizosphere (C rhiz ) to roots (C r ), xylem (C xyl ) and bundle sheaths (C bundle ).
LER ¼ a ler þ minð0; À a r abaÂln ABA ½ xy1 Â 1 þ c lerÂC xy1 À Á ð12Þ Photosynthesis can be calculated from stomatal conductance  61. A¼ max 0; À 1:6 þ 278:4Âgs þ 55:6 À 278:4Âgs þ 55:6 ð Þ ^2 À 0:828Â ð ð ð 55:6Â278:4ÂgsÞ^0:5Þ=2Â0:828Þ The model is implemented in the R language. Simulations were run with this model using time series collected in experiments conducted in Nerac and Karlsruhe in July 2012. Environmental data were collected daily in both sites every hour, namely air temperature, air relative humidity, incident light and rainfall. Experiments with B73 provided maize yields of 12. 1 T ha À 1 and 5. 1 T ha À 1 in Karlsruhe and Nerac, respectively. Two amplitudes of C xyl were used, namely 0. 2 and 0. 8 MPa in each site. The plant density in the model was similar to those in the corresponding experiments (7.
Acknowledgements This work was supported by the  EU  project  FP7-244374  ( DROPS) , the  ANR-08-GENM-003  project and the  Region Languedoc-Roussillon , together with the  Interuniversity Attraction Poles Programme-Belgian Science Policy  ( IAP7/29 ) and the  Belgian French community   ARC11/16-036  project. We thank  M Bosio ,  JP Pichon ,  A Clementi  and  S Praud (Biogemma)  for their contributions to the transcriptome analysis and for seeds of NCED plants. Field experiments were carried out at Nerac and Karlsruhe by  Biogemma  and  KWS , respectively, in the context of DROPS. Meteorological data were compiled and cleaned by  E. Millet  and  C. Welcker  ( INRA LEPSE ).
(  3 ) are foreground-corrected. Calibration factors c X and resulting spectra for 70 GHz, V, W, and V+W-band relative to 100 GHz are given in Fig. 23  and Table  3. The value of c 70 = 0. 994 seen in Fig. 23  is entirely consistent with the 70/100 ratios given in Sect. 5, taking into account mask and dataset variations as discussed in Sect. 5. A calibration factor for V relative to 70 GHz calculated the same way (D 100 b is replaced by D 70 b in Eq. 3) is also included in Table  3. To compare the likelihood results with the map-based ones, we need to identify the closest cases for which results are given. No correction for near sidelobes at 100 GHz (Sect. 4. 3) was included in the likelihood results, but corrections for residual unresolved sources were. On the other hand, from the results shown in Table  3 , residual-source corrections make negligible difference.
Conclusions Data consistency in CMB experiments is an important indicator of the validity of the results derived from these data. We have compared calibrated data from different Planck channels in three ways: (1) comparison of power spectra calculated on masked, publicly-released maps at 70, 100, and 143 GHz, including corrections for residual unresolved sources; (2) comparison of calibration factors determined to minimize differences between the CMB in the maps; and (3) comparison of power spectra and calibration factors obtained in the likelihood analysis used to de-  termine cosmological parameters. We have emphasized particularly the comparison of 70 GHz and 100 GHz, as these frequencies come from different instruments and are analysed independently, and are near the diffuse foreground minimum.
The internal consistency of the Planck data is remarkable (relative calibration inconsistencies between CMB channels of only a few tenths of a percent), and is at a level consistent with the uncer-tainties based on the 2013 solar dipole calibration scheme. In the future, calibration based on the orbital dipole should lead to more accurate absolute calibration. The estimate of the contribution of the near sidelobes to the HFI beam solid angles in March 2013 implicitly assumed azimuthal symmetry of the near sidelobes. Subsequent analyses of the beam and calibration procedures suggest that this assump- tion underestimated near-sidelobe power by as much as 0. 1 %. Corrections for this missing power result in improved agreement between 70 and 100 GHz, measured by ratios of power spectra, at a level of typically 0.
3 %, well below the levels of uncertainty estimated for LFI and HFI calibration, and therefore having little effect on the cosmological parameters determined from the 2013 data. Similar analysis applied to WMAP data shows a roughly 2 % difference between Planck and WMAP over the region of the first acoustic peak. At present, the explanation for this discrepancy with WMAP is not known. Precision calibration is an ongoing challenge. Future analyses will incorporate the lessons of this study of consistency, further reducing the size of uncertainties and errors on the scientific results from Planck. Frequency maps and difference maps using the GAL060 mask. Rms values are given in Table  1 ; histograms are shown in where P is the angular response ("beam"), normalized to unit solid angle ( 4π P dΩ = 1), D is the dipole signal (including the solar and orbital terms), T sky is the sky brightness temperature (CMB and foregrounds, i.
Acknowledgements. The development of Planck has been supported by:  ESA ;  CNES  and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MICINN  and  JA (Spain) ;  Tekes, AoF  and  CSC (Finland) ;  DLR  and  MPG (Germany) ;  CSA (Canada) ;  DTU Space (Denmark) ;  SER/SSO (Switzerland) ;  RCN (Norway) ;  SFI (Ireland) ;  FCT/MCTES (Portugal) ; and  DEISA (EU). A description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been involved, can be found at http://www. rssd. esa. int/Planck. Some of the results in this paper have been derived using the HEALPix package. We acknowledge the use of the Legacy Archive for Microwave Background Data Analysis (LAMBDA), part of the  High Energy Astrophysics Science Archive Center (HEASARC) ;  HEASARC/LAMBDA  is a service of the  Astrophysics Science Division at the NASA Goddard Space Flight Center.
The slope of the SED at long wavelengths is determined by the opacity and the size of the dust shell (i. e. , the contribution from colder dust). We produced our models taking into account the necessity to properly fit the Planck data and imposing that the outer temperature of the dust shell must match a mean ISM temperature of 10-20 K. Free Parameters Source R int R int /R c Luminosity T star T dust R out /R † int τ V Grains M dust [arcsec] [10 4 ] [10 3 L ⊙ ] [K] [K] composition [10 -4 M ⊙ ] NGC 6369 DUSTY treats the problem of radiation transfer independently from the distance to the star by taking advantage of the scaling properties of the radiative transfer equation  (Ivezic & Elitzur 1997). This implies that its output must be scaled to the actual data. We calculated the scaling factor taking into account the estimates of distance and luminosity available in the literature  (Goodrich 1991; Sabbadin et al.
However, this result can be extended to the whole sample, since in all cases the SEDs can be explained in terms of free-free and warm thermal dust emission only. For three sources, namely NGC 6369, NGC 7009, and NGC 3242, the high frequency Planck measurements appear to be systematically higher than the ancillary data. However, all the millimetre ancillary data for those sources are from the same study  (Casassus et al. 2007) , where 31 GHz and 230 plus 250 GHz fluxes are provided, which may suffer from some effects due to the fact that the dusty envelope is partially resolved. Supporting this conclusion, recent LABOCA/APEX measurements  (Cerrigone et al. in prep. )  of NGC 7009 and IC 418 are in good agreement with those obtained from Planck. Finally, one of our sources, NGC 40, appears to have a higher emission with respect to the model at around 70 GHz.
(2002). The results from our modelling of both free-free and thermal dust emission are shown in Fig. 9 , where a clear thermal dust contribution is superimposed on a typical optically-thin free-free spectrum. Planck data agree well with data from the WMAP 7year catalogue and with the 31 GHz data point from Casassus Fig. 7. Planck maps of the Helix (in Galactic coordinates). At each frequency, the corresponding beam (FWHM) is indicated in the bottom-left corner. In addition to the well known structures, associated with the evolved PN, diffuse emission is also present up to one degree from the central object. et al. (2004). However, the Planck data are fundamental to constrain the free-free and dust contributions, filling for the first time the observational range between 10 and 10 3 GHz where the lack of measurements has led to many speculations  (Casassus et al.
The ring-like structure of the inner ionised gas versus the more extended morphology of the molecular envelope is also supported by the images obtained using ISOCAM with the LW2 filter (centred at 6. 9 µm) and the LW3 filter (centred at 15 µm) by  Cox et al. (1998). Again, while the former traces the H 2 emission and thus delineates the molecular envelope morphology with the classical helical structure, the latter is dominated by the [Ne iii] emission and thus traces the ionised gas, clearly showing a more compact, rounder morphology. The interplay between the dust and ionised components is likely to evolve with the nebular expansion  (Chu et al. 2009). At the angular resolution of Planck, our data indicate that the ionised material is concentrated within the dusty nebula, closer to the central star.
Conclusions The remarkable frequency coverage of Planck has allowed us to collect important data for a small sample of Galactic PNe. These PNe, being among the brightest of such sources, are the best studied in our Galaxy. Nevertheless, a comprehensive picture of their CSEs in both their main components, i. e. , ionised gas and dust, has been provided for the first time. In particular, the evaluation of the emission from ionised gas (free-free) allows us to constrain the thermal dust emission. The modelling of the SEDs provides us with good estimates of the physical parameters of the CSEs. From our modelling, the density, spatial distribution and total mass of ionised gas have been derived, as well as the internal radius, the extent of the dusty envelope and its mass content. One interesting result is that, in general in the studied targets, dust and ionised gas appear to be partially co-spatial, which implies the existence of some kind of shielding mechanism to allow the dust to form, or at least to survive, in the harsh environment created by the strong UV radiation field of the central object.
Acknowledgements. The development of Planck has been supported by:  ESA ;  CNES  and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MICINN, JA  and  RES (Spain) ;  Tekes, AoF  and  CSC (Finland) ;  DLR  and  MPG (Germany) ;  CSA (Canada) ;  DTU Space (Denmark) ;  SER/SSO (Switzerland) ;  RCN (Norway) ;  SFI (Ireland) ;  FCT/MCTES (Portugal) ; and  PRACE (EU). A description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been involved, can be found at http://www. sciops. esa. int/index. php?project=planck& page=Planck_Collaboration The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc.
(2009)  found them in < 70% of bursts. In contrast to the light curves, the spectra of X-ray afterglows show little variation, with the photon index (Γ; N (E)dE ∝ E -Γ ) distribution 1  being approximately Gaussian, with a mean of 2. 0 and a FWHM of 0. 7  (Evans et al. 2009 , the live XRT GRB catalogue 2  ). This spectrum is generally found not to evolve with time (e. g. Butler & Kocevski 2007; Shen et al. 2009). In this paper we consider GRB 130925A, a GRB which triggered Swift, Fermi, Konus-Wind, INTEGRAL, and MAXI, and had a duration of > 5 ks, making it a candidate ultra-long GRB. However, this burst is also unusual in that its late-time X-ray data showed a strong hard-to-soft spectral evolution with time. Recently,  Bellm et al. (2014)  have analysed Swift, Chandra and NuSTAR data of this burst, and claim the presence of multiple afterglow components; however, we shall show that a simpler emission model can explain the data presented here.
OBSERVATIONS GRB 130925A triggered the INTEGRAL SPI-ACS instrument at 04:09:25 UT on 2013 September 25  (Savchenko et al. 2013) ; hereafter this time is referred to as T0. Fermi -GBM triggered just after this at 04:09:26. 73 UT  (Fitzpatrick 2013; Jenke 2013) , and Swift-BAT triggered at 04:11:24  UT (Lien et al. 2013) ; the GRB was also detected by Konus-Wind in waiting mode  (Golenetskii et al. 2013). These triggers all correspond to the same episode of emission, which lasted around 900 seconds (in the 15-350 keV BAT data the total duration above the background level was 846 s, while T90 = 179 s). There was an earlier 'precursor' lasting 6 s which triggered the Fermi -GBM at 03:56:23. 29 UT (T0 -781 s) this was also seen by Konus-Wind but not by INTEGRAL or BAT. The Fermi trigger also resulted in an automated slew of the satellite to orient the LAT boresight towards the GRB  (Jenke 2013) ; however, no emission was detected in the 0.
6×10 -9 erg cm -2 s -1 (0. 1-10 GeV,  Kocevski et al. 2013). At T0 +4. 8 ks Swift observations resumed, and the XRT detected a flare which was also seen by the BAT, INTEGRAL and GBM although at much lower levels than from the three main emission episodes. Two further flares were detected by XRT on the subsequent spacecraft orbits 4  , before the X-ray light curve settled down to the decay ubiquitous to X-ray GRB afterglows. Fig. 1  shows the multi-observatory light curve of the prompt emission and flaring episodes. For each instrument we obtained a single counts-to-flux conversion factor using the joint spectral fit to the first emission episode (Section 3) and multiplied the. Multi-observatory light curves of the prompt and flaring emission. These were built assuming a constant spectral model, as fitted to the Episode 1 data (Section 3).
PROMPT EMISSION AND FLARES Due to the unusual duration of GRB 130925A, we examined whether the intervals of high energy emission look like typical GRB prompt emission pulses (apart from their duration). Based on the light curve in Fig. 1 , we defined four intervals of high energy emission, and extracted spectra for each of these from whichever instruments were on target at the time, as shown in Table  3   7. For Fermi -GBM data a spectrum was created individually for each detector which detected the source during the time interval. We fitted the spectra of these time intervals in xspec  (Arnaud 1996)  with three models: a power-law, cut-off power-law, and Band function  (Band et al. 1993). For each fit the parameters were tied to be the same for all instru- ments, but a multiplicative normalisation factor was allowed to vary between them to allow for calibration differences in the absolute flux level.
For the precursor the cut-off powerlaw and Band models offered no significant improvement over the simple power-law. For the other spectra the cut-off power-law was significantly better than the simple powerlaw. The Band function offered no further improvement, tending towards unconstrained highly negative values for the high-energy index, at which point the Band function behaves as a cut-off power-law. The best fitting spectral parameters for the cut-off power-law and Band model fits are given in Table  4. We also created spectra covering the five flares that are seen in the XRT light curve (Table  3 ). For the first four spectra we have both Windowed Timing (WT) mode XRT data and BAT data (taken in survey mode). Although the source was not detected by BAT during the second flare the data provide constraints.
The final flare was too faint for BAT to make a meaningful contribution, but we have both WT and Photon Counting (PC) mode data for that flare. Following the latest calibration guidance 8 , as this source is moderately absorbed we used only single pixel (grade 0) events and ignored the data below 0. 6 keV. We used the gain files and RMF from the 2013-04-20 release of the Swift-XRT CALDB 9. A turn-up was seen in the WT data below 0. 8 keV, which could not be modelled even by adding thermal components to the spectra, and we therefore treated these as residual calibration systematics (which will be modelled in forthcoming calibration releases) and excluded them from the fits. The XRT spectra were fitted using the xspec 8 http://www. swift. ac. uk/analysis/xrt/digest cal. php 9 http://heasarc.