dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to reduce the redundancy and to maximize the effectiveness of classes, the statistical separability among the land cover/vegetation classes was examined before and after the segmentation process (Tab. 1) using the Jeffries-Matsushita (J-M) separability measure (0 ≤ J-M ≤ 2)  [Richards and Jia, 1999]. As a general rule, if the J-M value is greater than 1. 9, then separation is good. If the J-M is between 1. 7 and 1. 9 then separation is fairly good; below 1. 7 the separation is considered to be poor. Finally, Datasets A (with 4 classes: CC; DD; LL; NN) and B (with 5 classes: CC; DD; LL; NN and NN2) were randomly split into training (TA and TB) and validation (VA and VB) datasets. Both TA and TB datasets will be used for classification, whilst VA and VB will be used for assessing classification accuracy.
The fourth phase of our methodological approach consisted of the segmentation-based supervised classification of the IKONOS multispectral image (ortho-rectified and atmospherically corrected) by using TA and TB as training datasets, and by applying three different classifiers (SVM; MLC and KNN). In total, 6 classification maps were produced (three for each training dataset). Finally, the accuracy assessment of six outputted classification maps was performed by computing overall and "per class user's accuracy, producer's accuracy and overall Kappa coefficient of agreement, using both validation datasets  [Congalton and Green, 1999; Foody, 2002].
Results and Discussion Depuration of field data by interactive outlier detection and deletion reduced the number of segments from 525 to 440. It also improved overall separability (Tab. 1) in both datasets A (4 classes) and B (5 classes). -Cryptomeria japonica (CC) vs. Native scrubland (LL) in Dataset A (4 classes), which separability improvement (0. 9 to 1. 4) is insufficient (<1. 7). This low separability could be explained by a significant portion of training sites located in CC's forest stands marginal and transitional areas to LL patches. -Cryptomeria japonica (CC) vs. Bare Soil/Landslide areas (DD) in Dataset B (5 classes), which separability decreased (1. 6 to 1. 4). This lower separation between these two classes could be explained by the presence of some misclassified training sites.
Segmentation-based Supervised Classification At overall level, the best overall classifications when using Training Dataset TA (4 classes) were obtained by applying classifiers MLC (Overall KIA = 0. 97) and SVM (Overall KIA = 0. 93), showing a strong agreement and a good accuracy (Overall KIA ≥ 0. 8). KNN classification was slightly less accurate (Overall KIA = 0. 74). When using Training Dataset TB (5 classes), the overall accuracy results were slightly less accurate. The best overall classifications with this dataset were also obtained by applying MLC (Overall KIA = 0. 93) and SVM (Overall KIA = 0. 90). KNN classification didn't reach a strong agreement (Overall KIA = 0. 72) (Tab. 2). At overall level, the segmentation-based approach used in this study has shown a significantly higher accuracy when compared to standard pixel-based approach performed by  Gil et al.
[2011]  for the same area. MLC's overall accuracy (0. 78) and MLC's overall Kappa (0. 74) showed a good agreement, as it also occurred with SVM's overall accuracy (0. 78) and SVM's overall Kappa (0. 73). At the land cover/vegetation class level, Cryptomeria forest (CC) mapping was more accurate when training MLC (K = 0. 96) and SVM (K = 0. 95) with Dataset TB (5 classes). When using Dataset TA (4 classes), MLC was the most accurate classifier (K = 0. 91). KNN was the least effective classifier using both training datasets (K = 0. 47 for A and K = 0. 46 for B). The accuracy of both SVM and MLC results for CC in this study exceeded the best result (K = 0. 88 with SVM) reached by  Gil et al. [2011]  under a standard pixelbased approach. Therefore, a segmentation-based approach should be considered in this archipelago for operational forestry decision-support regarding Cryptomeria japonica stands mapping, monitoring and management.
Landslide and Bare Soil areas (DD) mapping has proven to be highly accurate with all three classifiers and both datasets (K = 1. 0). Those results exceeded the best one achieved by applying Mahalanobis Distance classifier (K = 0. 71) when using a standard pixel-based approach for the same area  [Gil et al. , 2011]. Therefore this segmentation-based approach can be highly effective for landslides detection and monitoring when using high spatial resolution satellite imagery and its integration within Regional Natural Hazard Monitoring System should be seriously considered. Native scrubland patches (LL) mapping was highly accurate when applying each one of the classifiers to both datasets (0. 83 ≤ K ≤ 0. 96), especially when using MLC (K for Dataset A = 0. 96; K for Dataset B = 0. 93). Regarding the main goal of this study, which was to map accurately the spatial distribution of Pittosporum woodland in the Pico da Vara Nature Reserve, the results were very positive in two cases.
First, when using Dataset A (single NN class), Pittosporum woodland mapping has been extremely accurate when applying MLC (K = 1. 0) and SVM (K = 0. 98) classifiers. These results exceeded significantly the best one achieved by applying Artificial Neural Networks classifier (K = 0. 66) under a standard pixel-based approach  [Gil et al. , 2011]. Second, when using Dataset B (NN split into NN and NN2), both sub-classes reached quite different accuracy results. KNN (K = 0. 88) and SVM (K = 0. 86) have been the most effective methods to map the first sub-class (NN), while MLC and SVM (K = 0. 96) have proven to be highly accurate when mapping the second sub-class (NN2). KNN was ineffective to map accurately this sub-class (K = 0. 53). These results showed that creating the Dataset B (with 5 classes) to split the NN initial class in two sub-classes (NN and NN2) had no positive effects on the accuracy of mapping at overall and land cover/vegetation class levels, excepting for the case of Cryptomeria forests (K = 0.
96), which was slightly more accurate than by using Dataset A with 4 classes (K = 0. 91). To perform a cost-benefit analysis to support a more realistic and cost-effective Pittosporum woodland control and management in Pico da Vara Nature Reserve under PRECEFIAS development, the approximated total area occupied by this invasive woody species has been estimated based on the best classification performed using MLC and dataset TA (K for Pittosporum woodland = 1. 0). Being the IKONOS multispectral band's spatial resolution equal to 4m (16 m² of minimal area unit), according to MLC results (Fig. 3 ), these IAS patches occupy 126 hectares of Pico da Vara protected area (815 hectares in total). According to the Regional Forest Inventory (RFI) the estimated area of Pittosporum Woodland in Pico da Vara Nature Reserve in 2007 is 35 hectares only.
Conclusions The results have shown that applying a segmentation-based approach to very high spatial resolution multispectral data (as IKONOS) can constitute a cost-effective approach for a continuous assessment of woody IAS spatial distribution and spread within Small Islands Protected Areas. The segmentation-based approach combined to the depuration of the initial field training dataset by interactive deletion of outliers allowed a significant increase in the separability between most relevant land-cover/vegetation classes, addressing and solving the most important problems that were identified in previous studies in the same area. Our main target vegetation class, Pittosporum woodland (highly aggressive IAS) showed a maximum separability value (2. 0) in all pairwise comparisons when using a 4 class's legend.
Acknowledgements This research has been developed on the behalf of a Doctoral ( M3. 1. 2/F/025/2007 )and a  Post-Doctoral  ( M3. 1. 7/F/005/2011 )Research Project, both supported by the  Regional Fund for Science (FRC) of the Azorean Regional Government. This particular case-study research has been developed with the support of project  Woody Biomass , funded by the  Green Islands program  ( MIT Portugal and Azorean Regional Government). We would like to thank  António Moniz  and  Rita Godinho  ( University of the Azores ) for their cartographic support. We would like to thank  SPEA/LIFE Priolo Project's staff  for sharing their vegetation monitoring program survey data. We are also thankful to the  R Development Core Team , and to  T. H. Keitt ,  R. Bivand ,  E. Pebesma  and  B. Rowlingson  for the development of rgdal;  R.
Calcium imaging For calcium dye loading, each coverslip containing differentiating neurospheres was incubated at 37°C for 45 minutes in the presence of 3 μM Oregon Green BAPTA 1 am (Life Technologies, Gent, Belgium). Imaging was carried out at room temperature using an upright Axioskop 2 microscope (Zeiss, Oberkochen, Germany) equipped with a CCD camera (iXon +, Andor). Images were acquired using a 63x, 0. 95 NA water-immersion objective (Zeiss, Oberkochen, Germany). To excite the fluorescence of the calcium dye, a light source composed of a LED array (OptoLED, Cairn) emitting at 488 nm was coupled to the microscope equipped with a dichroic mirror and a high-pass emission filter centred at 505 and 507 nm, respectively. Using the AndorIQ software, images were acquired every 2 seconds, with an exposure time of 50 milliseconds and with a resolution of 512×512 pixels (14 bits).
4). For the recordings, the glass coverslips were transferred into a recording chamber where they were continuously perfused (2-3 ml/min) with the extracellular solution at room temperature. All recordings were made with an Dual EPC10 amplifier and acquired using the software PatchMaster (HEKA). Signals were filtered at 4 kHz using the built-in filter of EPC10 and digitally sampled at 20 kHz. Data were analysed with Igor Pro software (WaveMetrics, Lake Oswego, OR). Passive cellular parameters were extracted in voltage clamp by analysing current relaxation induced by a 10-mV hyperpolarising step from a holding potential of -70 mV.
Analysis of contraction rhythm in cardiomyocytes Images were collected by time lapse every 68 or 26 milliseconds using Metamorph software and converted to multiframe TIFF images. Contraction profiles were built with ImageJ software by assessing the motion of light spots both in space and time. We calculated the ratio of the standard deviation to the mean of the intervals between 20 contractions, as described  (Yazawa et al. , 2011). The threshold for classifying a beating area as arrhythmic was a ratio at least two times higher than the average ratio of control cells.
Statistics Results are represented as mean ± s. d. Comparisons between groups for mean fluorescence intensity were made using one way analysis of variance (ANOVA) followed by Bonferroni post-hoc test using the Prism Software (GraphPad Software). Histograms were generated using Sigmaplot 10. 0. All histograms and images generated using ImageJ software (NIH) were imported in Adobe Illustrator and the final figure was exported in TIFF format. P-values less than 0. 05 were considered significant.
ACKNOWLEDGEMENTS We thank  Marcel Boeglin ,  Josiane Hergueux ,  Laetitia Fuhrman  and  Jean-Luc Weickert  from the IGBMC for technical help. We thank  Eric Jeandidier  ( CHU Mulhouse ) for iPSCs caryotypes. We thank  Karim Hnia ,  Alain Martelli  and  Karine Merienne  for helpful discussion and reading through the manuscript.
The total amount of water was obtained by the sum of the hydroxyl and molecular water concentrations calculated using the Beer-Lambert law, based on measurements of the 4470 cm -1 and 5210 cm -1 absorption bands. The sample thickness was measured on the infrared microscope and absorption peak heights were measured using a linear background correction. We used molar absorptivity values for phonolite from  Carroll & Blank (1997)  of 1•25 and 1•1 L mol -1 cm -1 for the 4470 and 5210 cm -1 bands, respectively. Electron microprobe analyses were performed using a Cameca SX100 at the Department of Earth Sciences, University of Cambridge. For glass analyses we used an accelerating voltage of 15 kV, a beam current of 2 nA and a defocused beam of 10 µm whereas for mineral phases we used an accelerating voltage of 10 kV, a beam current of 6 nA and a focused beam of 1 µm (details can be found in the Supplementary Data files DR2 and DR3, available for downloading at http:www.
Acknowledgements We are very grateful to  Joan Andújar ,  Rémi Champallier ,  Marina Alletti ,  Anita Cadoux ,  Mickael Laumonier ,  Giada Iacono Marziano ,  David Sifre ,  Nolwenn Le-gall ,  Fabrice Gaillard  and  Michel Pichavant  for their help with various instruments and for inspiring discussions. Special thanks also go to  Ida Di Carlo  and  Iris Buisman  for invaluable help with the SEM and electron probe. We are also grateful to  Marjorie Wilson ,  Ray Macdonald  and an anonymous reviewer for their constructive reviews of the original work.
Funding This research was supported by grants  ANT0838817  and  ANT1142083  from the  Office of Polar Programs (National Science Foundation ), and grant  202844  (' DEMONS ') from the  European Research Council  ( FP7 ). Y. M. was additionally supported by the  University of Cambridge Home  and  EU Scholarship Scheme  in addition to the Philip Lake and  William Vaughan Lewis  funds from the  Department of Geography, University of Cambridge. C. O. also acknowledges support from the  National Centre for Earth Observation  ( NERC NE/F001487/1  ' Dynamic Earth  and Geohazards' theme).
Primary antibodies incubations were performed overnight, at 4°C. Incubation with secondary HRP conjugated antibodies were done at RT for 1 hour. Detection of the immunoreactivities was obtained with Super Signal West Pico Chemiluminescent Substrate or West Femto Trial kit (Thermo Scientific). Scanned films or digitalized images acquired by Chemidoc (BioRad), Image Lab 4. 0. 1, were quantified using Image J software (NIH).
Immunohistochemistry and immunofluorescence Paraffin embedded U87EGFRvIII xenografts blocks were sectioned at the UCLA Pathology Histology and Tissue Core Facility and at the UCSD Histology and Immunohistochemistry Shared Resource. Immunohistochemistry was performed as described in Mellinghoff et al. (15). Three images per IHC slide were captured using DP 26 camera mounted on an Olympus BX43 microscope at 40x magnification. Quantitative analysis of the IHC stained slides was performed with the image analyzing software Microsuite Five (Olympus). Immunofluorescence staining was done as previously described in Gini et al. (16).
Acknowledgments Flow cytometry was performed in the  UCLA Jonsson Comprehensive Cancer Center (JCCC)  and  Center for AIDS Research Flow Cytometry Core Facility  that is supported by  National Institutes of Health  awards  CA-16042  and  AI-28697 , and by the  JCCC , the  UCLA AIDS Institute , and the  David Geffen School of Medicine at UCLA ; confocal laser scanning microscopy was performed at the  CNSI Advanced Light Microscopy/Spectroscopy Shared Resource Facility  at  UCLA , supported with funding from  NIH-NCRR  shared resources grant ( CJX1-443835-WS-29646 ) and  NSF   Major Research Instrumentation grant  ( CHE-0722519 );  National Institute of Health  ( NS072838  to D. G. );The  European Commission  ( PIOF-GA-2010-271819  to B. G. ).
Method of Calculations To fulfill the present calculation, we have applied the FP-LMTO method  [10, 11]  as embedded in LmtART MStudio MindLab 7 code developed by Savrasov  [11, 12]. The exchange and correlation potential was calculated using GGA Perdew Wang (PW) scheme  [13]. In the present study, the different muffin tin radius R MT used are given as follows  (   (2. 535). In these calculations, the FP-LMTO basis set consists of the 4d 7 5s 1 and 3d 5 4s 1 states for the transition elements Ru and Cr respectively. For the Z atoms, the valence states are 3s 2 3p 2 of Si, 4s 2 4p 2 of Ge or 5s 2 5p 2 of Sn. But the filled states 4d 10 of Sn and 3d 10 of Ge may also be considered as valence states, that are the default input in the code since the energy needed to separate semi-core and valence electrons was set to above -2Ry from the vacuum zero, which results in treating of Si, Ge and Sn semi-core electrons as valence electrons.
Data and analysis Data were collected using a structured questionnaire and sourced from antenatal, pre-ART and ART registers. Aggregated totals of patients newly registered in the clinic, numbers of patients who had undergone HIV testing and numbers of patients who had been screened for ART eligibility were collected from monthly reports. Data were double-entered, validated and analysed using E piData Version 3. 1 (EpiData Association, Odense, Denmark), and cross-validated against the ART and CD4 registers. The χ² test was used to compare differences in proportions; the t-test was used to compare differences between means. Relative risk (RR) was used to assess the strength of association. P ⩽ 0. 05 was considered statistically signifi cant.
We used data from existing sources and the data were carefully collected and validated. This is also the fi rst study to assess the impact of integration along with task-shifting. A limitation is that we had insuffi cient statistical power to assess associations with non-initiation of ART after integration. As routinely collected data were used, data were missing from certain records (Table  3 ). It is also possible that some patients who initiated ART were not recorded in the registers. In addition, as our comparison group was a historical control, this may have introduced a possible bias. However, there were no changes in staffi ng, and access issues such as transport and poverty level, which might have affected uptake, remained the same. In addition, intermittent antiretroviral drug ruptures in the post-integration period may have negated the effect of ART uptake in this period.
3). The plot of observed versus predicted values, with line fitted through the origin, showed low bias (slope close to 1. 0) and very high r 2. Similar predictive power was found for P 50 (see "Results"). ***P , 0. 001. it may contribute to the tolerance of incipient drought by preventing early K leaf decline and/or contribute indirectly to drought tolerance by preventing cell shrinkage to lethal levels. Indeed, a recent study quantified PLA dry in 380 diverse species  (Blonder et al. , 2012)  and found PLA dry to be slightly higher for dry habitat species, although that trend may have arisen due to error in the measurements. In that study, PLA dry was determined without first rehydrating the leaves to full turgidity, and erroneous negative PLA dry data were included in that study. Such errors need to be avoided for accurate species comparisons, especially if values are to be used as proxies for more intensive physiological or ecological parameters.
Computer Modeling of the Theoretical Importance of the Xylem and Extraxylem Water Transport Pathways for Leaf Hydraulic Vulnerability To refine our hypothesis that leaf shrinkage should influence leaf hydraulic vulnerability, we improved the K_leaf program (written by  Hervé Cochard; Cochard et al. , 2004b; McKown et al. , 2010; Scoffoni et al. , 2011 ; available on request from herve. cochard@clermont. inra. fr) to generate leaf hydraulic vulnerability curves. K_leaf creates a spatially explicit model of a leaf with up to six vein orders represented as a square grid of xylem resistors with outsidexylem resistors ("mesophyll" resistors) branching orthogonally from each junction of the vein grid. In modeled leaves, water exits through the mesophyll resistor located at each vein junction, with the bulk of the water exiting from the junctions of the minor veins.
Leaf area was measured using a flatbed scanner (Canon Scan Lide 90; Canon) followed by image analysis (ImageJ software version 1. 42q; National Institutes of Health). Leaf thickness was determined by averaging values taken in the centers of the bottom, middle, and top thirds of the leaf, using digital calipers (60. 01 mm; Fowler). Leaf mass was determined using an analytical balance (60. 01 mg; XS205; Mettler). Volume was determined as the product of leaf thickness and area. Once leaves had dehydrated beyond TLP or became too brittle to handle, they were placed in an oven for at least 3 d at 70°C before the dry leaf area, thickness, and mass were determined. We partitioned the leaf thickness (i. e. the volume per area) into that of the cells and airspace  (Roderick et al. , 1999). The "thickness" of the cells (T C,i ) and of intercellular airspace (T A,i ) at each level i of dehydration were calculated: T C;i ¼ n water;i LA i ð5Þ T A;i ¼ T i 2 T C;i ð6Þ where v i is the volume of water at level i of dehydration (i.
Spearman rank correlations were also determined, given that these are more robust in cases in which one or two outliers might drive a significant Pearson correlation  (Sokal and Rohlf, 1995). For a conservative approach, we typically recognized relationships as significant only when P , 0. 05 for both Spearman rank and Pearson correlations (r s and r p , respectively). Partial correlation analyses  (Sokal and Rohlf, 1995)  were conducted when three variables of interest were intercorrelated across species. These analyses tested the relationship between two variables when the third is statistically held constant (implemented using the corpcor package in R;  Schaefer et al. , 2007).
The first observation of the decay B 0 s → χ c1 φ and a study of B 0 → χ c1,2 K * 0 decays are presented. The analysis is performed using a dataset, corresponding to an integrated luminosity of 1. 0 fb -1 , collected by the LHCb experiment in pp collisions at a centre-of-mass energy of 7 TeV. The following ratios of branching fractions are measured: where the third uncertainty is due to the limited knowledge of the branching fractions of χ c → J/ψ γ modes.
Acknowledgements We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from  CERN  and from the national agencies:  CAPES ,  CNPq ,  FAPERJ  and  FINEP (Brazil) ;  NSFC (China) ;  CNRS/IN2P3  and  Region Auvergne (France) ;  BMBF ,  DFG ,  HGF  and  MPG (Germany) ;  SFI (Ireland) ;  INFN (Italy) ;  FOM  and  NWO  (The Netherlands); SCSR (Poland);  ANCS/IFA (Romania) ;  MinES, Rosatom ,  RFBR  and  NRC "Kurchatov Institute" (Russia) ;  MinECo, XuntaGal and GENCAT (Spain) ;  SNSF  and  SER (Switzerland) ;  NAS Ukraine (Ukraine) ;  STFC  ( United Kingdom );  NSF (USA). We also acknowledge the support received from the  ERC  under  FP7.
Introduction: Randomized trials investigating neuromuscular blocking agents in adult acute respiratory distress syndrome (ARDS) have been inconclusive about effects on mortality, which is very high in this population. Uncertainty also exists about the associated risk of ICU-acquired weakness. Methods: We conducted a systematic review and meta-analysis. We searched the Cochrane (Central) database, MEDLINE, EMBASE, ACP Journal Club, and clinical trial registries for randomized trials investigating survival effects of neuromuscular blocking agents in adults with ARDS. Two independent reviewers abstracted data and assessed methodologic quality. Primary study investigators provided additional unpublished data. Results: Three trials (431 patients; 20 centers; all from the same research group in France) met inclusion criteria for this review.
Search strategy Computerized literature searches included MEDLINE (1966 to October 2012), EMBASE (1980 to October 2012), ACP Journal Club (1991 to October 2012), the Cochrane (Central) database, and clinical trial registries (clinicaltrials. gov, ISRCTN Register, and WHO ICTRP) (see Additional file 1). Relevant conference proceedings were searched electronically through a specific service provided through McMaster University  [20].