dataesr/scientific-paragraphs-categorization huggingface dataset:
Conflict resolution in DTWiki is similar to those in traditional wikis, as explained in section 2. 4. UniWiki  [6]  consists of multiple wiki front-ends that fetch and store their data over a DHT. It combines optimistic replication  [20]  techniques and DHT techniques. The originality of UniWiki is that it performs automatic merges of concurrent edits by running the WOOT  [28]  synchronization algorithm directly in the DHT nodes, which allows the system to support unstable content with a high rate of modifications while ensuring CCI consistency (see section 3. 2. 3 for a definition of this concept).
However, data quality is a major issue  [50, 51]. Wiki systems have demonstrated how communities of users can improve the quality of shared documents, and semantic wikis  [39]  or wikidata  [52]  apply the wiki approach to improving semantic documents and data. Other work  [53]  aims to transform wikis into collaborative integrated development environments mixing text, data and applications. Such wikis allow simple semantic web applications to be quickly developed and shared. Surprisingly, in such approaches, wikis remain centralized while the data is hosted in a federation of linked data. In fact, current semantic wikis allow authoring of one local dataset, even if this dataset is linked to others datasets of the LOD cloud. A federated semantic wiki should allow authoring of linked data across the federation, as part of it, or as a new federation accessing the existing federation of linked data.
As the amount of data hosted can be very large, this approach is problematic. The federated class of wikis seems more appropriate for building a federated semantic wiki. A federated semantic wiki should be able to "editorialize" data collected from LOD, i. e. , to author meaningful, human-readable documents from linked data. Such documents could then be further edited, and changes would be propagated to the federation of semantic wikis and the federation of linked data. In other words, a federated semantic wiki should be able to make the web of data understandable and editable by humans. However, a major issue is that the federated wiki and semantic wiki models cannot be applied directly to federated semantic wikis. In particular, there is a mismatch between the graph model of most semantic wikis, where concepts are generally associated with a unique page, and the hypergraph model of federated wikis, which represents the multiplicity of perspectives over shared concepts.
We used the channel 1 (3. 6 µm) mosaics made of eight 30 second frames per spatial position. The survey is described in detail in  Sheth et al. (2010)  which is the main reference for the S 4 G sample and data. 597 galaxies in the sample already had observations in the Spitzer Heritage Archive, and almost all of them have a total frame time depth of at least 240 seconds (that of the new observations). The only exceptions are NGC 5457 (96s), NGC  0470 and NGC 0474 (150s), and NGC 5218, NGC 5216, and NGC 5576 (192s). Several of the archival observations are from the Spitzer SINGS  (Kennicutt et al. 2003)  and LVL  (Dale et al. 2009 ) Legacy Projects that had a very similar mapping strategy to the S 4 G observations. We started with the basic calibrated data (BCDs) that are the fundamental IRAC pipeline-reduced images from the individual exposures.
The data were subsequently run through the S 4 G Pipeline 1 that mosaics them together using the Space Telescope Science Data Analysis System (STSDAS) dither package  (Sheth et al. 2010; Regan et al. , in preparation). Cosmic rays are eliminated in this process and the images are drizzled together to a mosaic that has 0. 75 pixels (the original pixel size is about 1. 2). Sheth et al. (2010)  give more details on pipeline processing. We used only the 3. 6 µm mosaics to search for faint outer features. The 4. 5 µm images are usually almost identical to the 3. 6 µm images, but are farther from the peak of the old stellar population spectral energy distribution, and may suffer from hot dust contribution. It should be noted that the 3. 6 µm band contains the 3. 3 µm PAH emission band, while the 4.
DETECTION AND CLASSIFICATION METHODOLOGY We displayed each galaxy with the SAOImage DS9 astronomical imaging and data visualization application (Joye & Mandel 2003), using both the histogram equalization and log scales, and in both black-and-white and rainbow color schemes, adjusting to the extremes of contrast and sampling carefully the contrast in between the extremes. We also experimented with making unsharp-masked versions of the images, but did not use those in the final classification of the outermost features, as they did not help in the detection of the outermost features. We can reliably classify features down to a per pixel surface brightness level of 0. 03 MJy/sr (21. 5 Vega mag arcsec -2 , 24. 3 AB mag arcsec -2 , or about 2. 5 σ above the background level) based on the faintest detected structures (the polar ring candidates) and assess asymmetries in the outer isophotes at about 0.
If the systemic velocity, checked using the NASA/IPAC Extragalactic Database (NED), was within ±600 km s - 1  of the target galaxy systemic velocity, we classified it as a companion galaxy. Previous studies using isolation criteria or searches for companion galaxies often use systemic velocity ranges between 500 km s -1 and 1000 km s -1 (e. g. ,  Zaritsky et al. 1993; Sales & Lambas 2005). Our value of 600 km s -1 is a compromise between these two, and represents the velocity dispersion of a modest size cluster of galaxies (less than Virgo), and more than that of a galaxy group, so we would find galaxy group members. There can be interacting galaxies beyond this cut in some rare cases, such as possibly NGC 4435 and NGC 4438. Note that the physical size of the imaged area varied a lot, as the sample galaxies are at distances from 1 to about 60 Mpc (almost all of them within about 40 Mpc), and vary in physical size as well.
This resulted in a wide range of morphologies at z = 0, even if 85 per cent of the sample has a bulge-to-total stellar mass ratio smaller than 0. 5 (see  Martig et al. 2012). Their final stellar mass ranges from 1. 7 ×10 10 to 2 ×10 11 M. To compare these simulated galaxies from  Martig et al. (2012)  to S 4 G data, we computed mock 3. 6 µm images for all 33 galaxies, at seven inclinations ranging from 0 • to 90 •. The mock 3. 6 µm images were computed using the PEGASE. 2 stellar evolution code  (Fioc & Rocca-Volmerange 1999) , assuming a Kroupa initial mass function from 0. 1 to 120 M (we did not include any dust contribution because at 3. 6 µm dust is not expected to play a significant role and can be excluded in the modelling). Each image corresponds to 100 x 100 kpc in size (with a similar total depth of 100 kpc).
ACKNOWLEDGEMENTS We thank  Ramin Skibba  for his helpful comments on a draft of this paper. We also thank  Carrie Bridge  for discussions on the merger rate. We acknowledge the helpful discussion with Chris Lintott about biases in classification. We acknowledge financial support to the DAGAL network from the  People Programme  ( Marie Curie Actions ) of the European Union's  Seventh Framework Programme FP7 /2007-2013/ under REA grant agreement number  PITN-GA-2011-289313. This work was co-funded under the  Marie Curie Actions of the European Commission  ( FP7-COFUND ). We also gratefully acknowledge support from  NASA JPL/Spitzer  grant  RSA 1374189  provided for the S 4 G project. E. A. and A. B. thank the  CNES  for support. K. S. , J. -C. M. -M. , T. K. , and T. M. acknowledge support from the  National Radio Astronomy Observatory , which is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc.
The authors thank the entire S 4 G team for their efforts in this project. This work is based on observations made with the  Spitzer Space Telescope , which is operated by the  Jet Propulsion Laboratory, California Institute of Technology  under a contract with  NASA. Support for this work was provided by  NASA  through an award issued by  JPL/Caltech. We are grateful to the dedicated staff at the  Spitzer Science Center  for their help and support in planning and execution of this  Exploration Science program. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by  JPL ,  Caltech , under contract with  NASA.
The purification procedure has effectively removed the pollution in 40 K and 137 Cs by one order of magnitude. The concentrations of thorium and radium were also decreased by factors 2 and 4, respectively. The following radioactive contamination of the 100 MoO 3 sample can be derived from the data of the experiment (in mBq/kg): 2. 0(2) for 226 Ra ( 238 U chain), 0. 8(1) for 228 Th ( 232 Th chain), 5. 9(1) for 137 Cs, and 36(2) for 40 K  [24]. The level of impurities in the 100 MoO 3 was also measured by inductively coupled plasma mass-spectrometry (ICP-MS) and atomic absorption spectroscopy (AAS) methods. The results of these measurements, presented in Table  1 , as well as radioactive contamination of the sample, suggest that the material should be additionally purified to be used for crystal scintillator production.
The Zn 100 MoO 4 scintillating bolometer array -before mounting of the LD -is shown in Fig. 3. The array was tested at very low temperatures by using a pulse-tube cryostat housing a high-power dilution refrigerator  [31]  installed at the CSNSM (Orsay, France). The cryostat is surrounded by a massive shield made out of low activity lead to minimize pile-up effects, which are particularly disturbing in aboveground measurements with slow detectors such as bolometers based on NTD Ge thermistors. A room-temperature low-noise electronics, consisting of DC-coupled voltage-sensitive amplifiers  [32]  and located inside a Faraday cage, was used for the read-out of the NTD Ge thermistors. Data streams were recorded by a 16 bit commercial ADC with 10 kHz sampling frequency. The test was performed at three base temperatures: 13.
1 A weak event cluster probably related to 210 Po is used to determine the activity of this radionuclide, considering a 200 keV interval around its centroid. The analysis of the data accumulated at 13. 7 mK and 19 mK with the Zn 100 MoO 4 -top and Zn 100 MoO 4 -bottom bolometers gives an activity of 210 Po in the crystals at the level of 1. 1(3) mBq/kg and 1. 2(3) mBq/kg, respectively. These activities are similar to those measured precisely in natural ZnMoO 4 bolometers  [18]. It should be noted that the current statistics of the 210 Po counts (4-6 events depending on the set of measurements) is not enough to get precise value of the activities and to distinguish a bulk contamination of 210 Po (or of the pro- The data were accumulated at 13. 7 mK. The events above 2. 6 MeV in the γ(β) region are caused by cosmic muons.
Acknowledgments The development of Zn 100 MoO 4 scintillating bolometers is an essential part of the LUMINEU program, receiving funds from the Agence Nationale de la Recherche (France). The work was supported partly by the project "Cryogenic detectors to search for neutrinoless double beta decay of molybdenum" in the framework of the Programme "Dnipro" based on Ukraine-France Agreement on Cultural, Scientific and Technological Cooperation. The aboveground facility for the test of the scintillating bolometers was realised with the indispensable support of ISOTTA, a project funded by the AS-PERA 2nd Common Call dedicated to R&D activities. The group from the Institute for Nuclear Research (Kyiv, Ukraine) was supported in part by the Space Re- It is a pleasure to thank Stefano Nisi from the Gran Sasso laboratory (Italy) for his kind help in the measurements of enriched molybdenum oxide by inductively coupled plasma mass-spectrometry.
Acknowledgements We thank  Lance Dixon ,  James Drummond ,  Matt von Hippel  and  Jeff Pennington  for several discussions and exchanges pertaining the three loop analysis and  Lance Dixon ,  James Drummond ,  Claude Duhr  and  Jeff Pennington  for discussions and correspondence related to the four loop checks and for insightful comments on the draft. We thank  Andrei Belitsky ,  Yasuyuki Hatsuda ,  Juan Maldacena ,  Joao Penedones  and  Kostya Zarembo  for enlightening discussions. B. B, A. S and P. V thank  IAS  and  ICTP-SAIFR  for hospitality. B. B thank PI for hospitality. Research at the  Perimeter Institute  is supported in part by the  Government of Canada  through  NSERC  and by the  Province of Ontario through MRI. A. S was supported in part by  U. S. Department of Energy  grant  DE-SC0009988.
The method includes selecting the appropriate atmospheric indicators, categorizing the potential thresholds, determining and testing the thresholds. The method is tested in the Ubaye Valley in the southern French Alps (548 km 2 ), which is known to have localized convection triggered debris flows and flash floods. This paper shows that instability of the atmosphere and specific humidity at 700 hPa are the most important atmospheric indicators for debris flows and flash floods in the study area. Furthermore, this paper demonstrates that atmospheric reanalysis data are an important asset, and could replace rainfall measurements in empirical exceedance thresholds for debris flows and flash floods.
Nuissier et al. (2011)  used synoptic (large-scale) weather types based on the Hess-Brezowsky Grosswetterlagen classification, as well as low-level moisture flux and low-level wind direction to detect heavy precipitation events in southern France. Other examples of using atmospheric indicators for heavy precipitation include  Schmidli et al. (2007) ,  Chen et al. (2010)  and  Jeong et al. (2012). Identification of synoptic atmospheric conditions that lead to flooding has also been undertaken in a number of studies (e. g. Petrow et al. , 2009; Parajka et al. , 2010). Atmospheric indicators can be obtained using reanalysis data from physically based models. Using a forecast model combined with observations, reanalysis data are consistent with both atmospheric observations and the laws of physics  (Dee et al.
2 ). As the valley is orientated west-east, north-facing slopes are likely to retain snow longer than south-facing slopes. Cepeda et al. (2010)  developed Eq. (  4 ) for debris flows based on hourly precipitation from station 1. Only seven debris flows were used, as the others occurred before subdaily precipitation measurements were available (1998), or the precipitation or inventory record was deemed to be not sufficient  (Cepeda et al. , 2010). For the threshold, 86 % of the debris flow events used were correctly predicted, and 5. 5 % of rainfall events above the threshold resulted in debris flow. However, no threshold was obtained using only the longer daily rainfall data set. To obtain a threshold for a longer time period, other methods or data sets are therefore required. ECMWF ERA-Interim reanalysis data are used for analysing the regional atmospheric variables.
The data have a spatial resolution of 80 km (T255) and are available for 1979 onwards  (Dee et al. , 2011). More information about observation and data assimilation and model characteristics for ERA-Interim can be found in  Dee et al. (2011). The study area is approximately half of one grid box, so only the grid box containing the study area and those directly beside it are used (nine in total). The variables chosen (Table  2 ) contain commonly used predictors for statistical downscaling precipitation from Global Climate Models at multiple atmospheric pressure levels  (Chen et al. , 2010; Jeong et al. , 2012). In addition, convective available potential energy (CAPE), deep layer shear (DLS), and soil moisture fields are also included. The first two are added as they might be indicative for convection  (Marsh et al.
Methodology This section explains a method to establish empirical thresholds for debris flows and flash flood events (flash events) based on regional atmospheric conditions or indicators from the reanalysis data set. Two different thresholds are considered: (1) a probabilistic threshold based on  Berti et al. (2012) , determining the likelihood of a flash event using a variety of indicators, and (2) a static threshold that takes into account the number of flash events below the threshold as well as the probability of occurrence. Besides defining the threshold, the methodology also examines (a) if the local weather station network was adequately capturing the rainfall causing the event, (b) whether intense convection was the main rainfall source triggering the events, and (c) if other meteorological triggers, such as snowmelt, are relevant to triggering events in the study area.
Acknowledgements. This work was undertaken as part of the  EU   FP7 Marie Curie ITN project  " CHANGES"  under Grant Agreement No. 263953. The authors would like to thank  J. P. Malet  and  A. Remaître  for their input and help with collection of data. Data were provided by  Météo France , and the  ECMWF ERA-Interim data  used in this study was obtained from the  ECMWF data server. Edited by: M. Parise Reviewed by:  S. Gabriele  and  J. L. Wood.
Images, as that shown in Fig. 1(b) , are grabbed at a frame rate of 5 fps with a USB camera mounted in place of one of the microscope eyepieces. The videos are analyzed with a homemade Matlab particle tracking program adapted from a free online code  [33]. The particles are produced using a three-step method. First, we synthesize the silica microparticles with a constant monomer supply technique  [34, 35]  to preserve monodispersity during particle growth; the final size of the particles is monitored by the flow rate amplitude of a diluted tetraethyl orthosilicate solution. The particles are then characterized by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). We choose two suspensions of average particle diameters, D = 1. 17 µm and D = 1. 46 µm with a standard deviation smaller than 3%, above the micron to guaranty optical actuation of pure silica particles with beam powers below the Watt.
For metal-dielectric particles, we calculated F rp with a Matlab code implemented for spherical core-shell particles  [43]. To do so, we need the dielectric functions of the core ε core and the shell ε shell. As the metal nanodots adsorbed on the silica microparticle surface are very small compared to the optical wavelength and since they are isotropically distributed onto this surface with a volume fraction φ around the percent, we can confidently assume a description of the shell as a continuous composite medium and use the Maxwell-Garnett approach to determine its dielectric constant: ( ) ( ) ( ) ( ) 1 2 2 1 , 1 2 m shell m m ε φ ε φ ε ε ε φ ε φ + + - = -+ +   (2) with ε the complex gold dielectric function derived from Johnson and Christy π η υ = for a solid sphere and η is the water viscosity.
Acknowledgments The authors acknowledge the scientific program  Advanced Materials in Aquitaine (GIS Matériaux ) and the  Conseil Régional d'Aquitaine  (Project  Nano-Trans N#   20111101010 ) for funding. The authors would also like to acknowledge networking support by the  COST Actions MP 1202  (http://www. cost-hint. cnrs. fr)and MP 1205 (http://costmp1205. eu).
We present the aggregated conformal predictor (ACP), an extension to the traditional inductive conformal prediction (ICP) where several inductive conformal predictors are applied on the same training set and their individual predictions are aggregated to form a single prediction on an example. The results from applying ACP on two pharmaceutical data sets (CDK5 and GNRHR) indicate that the ACP has advantages over traditional ICP. ACP reduces the variance of the prediction region estimates and improves efficiency. Still, it is more conservative in terms of validity than ICP, indicating that there is room for further improvement of efficiency without compromising validity.
Another interesting approach to improve efficiency is the cross conformal predictor (CCP)  [4]. Here the training data is divided into separate non-overlapping folds and each fold is used as a calibration set and the remainder of the data is used as a proper training set. This division allows for more data to be used for calibration and p-values are averaged over all folds. Similarly, the bootstrap conformal predictor (BCP) bootstraps datasets and uses the out-of-bag examples as a calibration set. p-values are then averages across all bootstrap replications. In this paper we attempt to generalize the BCP and the CCP in what we term the aggregated inductive conformal predictor (ACP). We will empirically assess the ACP using data from the pharmaceutical domain and we show through a theoretical argument and experiments that ACP seems to have advantages over the standard ICP.
Proposition 1. The aggregated conformal predictor is conservatively valid. Proof. Since we use an exchangeable resampling procedure to construct the ACP and since an ICP is conservatively valid (Proposition 4. 1,  [3] ), each resampled ICP in the ACP is conservatively valid (by symmetry). From this follows that the ACP also is conservatively valid. Remark 1. Proposition 1 only holds unconditionally. The situation is different conditional on the particular dataset we have observed.
Measure (8) normalizes the absolute prediction error with the predicted accuracy of the SVM on a given example. The nonconformity measure used with RF was α i = |y i -ŷi | νi , where νi is the RF prediction of the value |y i -ŷi | with the same settings as for the other RF model. Two public dataset (CDK5 and GNRHR) from the pharmaceutical domain was used  [12]. The datasets consist of 230 and 198 examples, respectively. Each example (chemical compound) was described (characterised) by so-called signature descriptors  [13]  in the same way as described in  [2]. The data was randomly split into two parts: A training set (80% of the original data) and a working set (20%). This procedure was repeated 50 times as to generate 50 training and working set, respectively. Furthermore, each training set was then, subsequently, randomly split into a proper training set (70% of the training set) and a calibration set (30%), similar to the 2:1 recommendation in  [5].
This random selection of proper training and calibration examples was, in turn, repeated 100 times enabling the construction of 100 inductive conformal predictors for each working set. This sampling procedure is often called the m -n sampling or non-replacement subsampling in the bootstrap literature and consistent with Definition 2  [14]. The results are presented in Tables 1-8 and in Figures  1  and 2. Table  5. The efficiency for an ACP and an ICP at one significance level for the 50 runs on the CDK5 data using SVM. Here, Q1 and Q3 are the lower and upper quartile, respectively. Method.
These tight prediction regions are offset by some prediction regions that are very wide (as wide or wider than the possible range of the response value) that are always valid, which produces a conformal predictor that is valid on average. Neither the too tight prediction regions that cannot be trusted nor non-informative regions are helpful for the researcher using the model. The results in Tables  1 2 3 4 5 6 7 8 show that the ACP (as used in this paper) is too conservative on datasets with a relatively small number of examples, which is clear from Equations (1) and (2). This indicates that improved efficiency can be achieved without compromising the validity of the ACP, e. g. by more clever resampling (a large body of literature exists that address this problem, see e. g. [15] ) or smoothing of p-values on either side of.