dataesr/scientific-paragraphs-categorization huggingface dataset:
It is difficult to have daily observations, which are not included in the analysis fields used for initialization, especially for the Atlantic. The forecast range evaluated is 24 h, i. e. , the first forecast day. A contrasting feature to the other two models used here is the formulation of the source function (characterization of accumulated sediments, soil texture, porosity, bulk density, composition, soil moisture, and soil particle size distribution). SKIRON uses the soil texture database developed by  Miller and White (1998)  which, in turn, is based on the US Department of Agriculture's State Soil Geographic Database. The atmospheric model is based on the ETA/National Centers for Environmental Prediction (NCEP) model but is heavily modified to include state-of-the-art parameterization schemes for meteorological and desert dust processes (see  Spyrou et al.
MACC/CAMS MACC (Monitoring Atmospheric Composition and Climate) was developed within the framework of a EU project (http: //www. gmes-atmosphere. eu/about/project/) which was coordinated by ECMWF (European Centre for Medium-range Weather Forecasts, Reading, United Kingdom). MACC activities are now carried out under the Copernicus Atmosphere Monitoring Service (CAMS). The simulation system MACC/CAMS combines state-of-the-art atmospheric modeling with operationally assimilated Earth observation data to provide near-real-time (NRT) forecasts for a wide range products regarding European air quality, global atmospheric composition, climate forcing, the ozone layer and UV, solar energy, and emissions and surface fluxes. The MACC/CAMS simulation system gets input data from satellites, in situ measurements, and information about aerosol emissions and fires.
The MACC reanalysis was stopped in 2012, so reanalysis products are not available for 2013. Therefore, the operational (forecast) runs for 2013 were used in our study. Data sets of particle mass concentrations were downloaded from the ECMWF data server (MACC, 2016) for a fixed grid with a resolution of 1. 125 •. We selected the data sets for the nearest grid points to the position of R/V Meteor and 00:00 UTC (cases 2-4) and 04:00 UTC (case 1, 23 May 2013). The model resolution was 0. 8 • × 0. 8 • with 60 vertical levels in 2013. Since 2016, the model resolution has been increased to 0. 5 • × 0. 5 •. As mentioned, dust mass concentrations are available for three radius classes. The radius class from 0. 03 to 0. 55 µm defines the fine dust fraction; the two other size classes belong to the coarse mode.
The model also has a data assimilation system. The dust model is online coupled with the non-hydrostatic NMMB model  (Janjic et al. , 2011, and references therein) , which is able to increase the model horizontal resolution up to 1 km. The NMMB/BSC-Dust model provides operational forecast over regional (north Africa, the Middle East, Europe) and global domains, and it has been selected by the World Meteorological Organization (WMO) as the operational model for the Barcelona Dust Forecast Center (http:// dust. aemet. es/), the first WMO regional center specialized in atmospheric sand and dust forecasts. Additionally, the model is participating in the WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS; https:// sds-was. aemet. es/) and ICAP (International Cooperative for Aerosol Prediction) model intercomparison exercises  (Sessions et al.
, 2015). The MACC/CAMS model also contributes to WMO SDS-WAS and ICAP. The NMMB/BSC-Dust model assumes a viscous sublayer between the smooth desert surface and the lowest model layer  (Janjic, 1994; Nickovic et al. , 2001) , and its dust emissions caused by surface and turbulence winds are physically based on an emission scheme which explicitly considers saltation and sandblasting processes  (White, 1979; Marticorena and Bergametti, 1995; Marticorena et al. , 1997). The model uses soil texture data from the hybrid STATSGO-FAO (STATSGO: State Soil Geographic Database; FAO: Food and Agriculture Organization of the United Nations) soil map and land use data from the USGS (United States Geological Survey). According to the criteria used in  Tegen et al. (2002) , the model considers four soil populations (i.
Conclusions A unique observational data set of Saharan dust profiles, measured with ship-based state-of-the-art polarization/Raman lidar over the tropical Atlantic, was compared with dust forecasts of a regional (SKIRON) and two global atmospheric models (MACC/CAMS, NMMB/BSC-Dust). Undisturbed dust transport and removal conditions could be studied in detail. As new feature, the recently introduced lidar data analysis scheme (POLIPHON) allowed us to retrieve height profiles of dust light extinction coefficient and mass concentration separately for fine dust, coarse dust, and the non-dust (marine, haze, smoke) aerosol components, and thus to study and discuss the uncertainties in the modeled dust size distribution characteristics during long-range transport. In part 1  (Rittmeister et al. , 2017) , we presented a dense set of height-resolved observations of dust optical properties and layering structures, and found good agreement of the observations with the basic features of the conceptual model of  Karyampudi et al.
g. , of the Polly type) at distinct stations in key regions of dust occurrence and transport. Data availability. The R/V Meteor lidar data are available at TROPOS upon request (info@tropos. de). The NMMB/BSC-Dust dust profiles are available upon request (http://www. bsc. es/ESS/bsc-dust-daily-forecast; info-services-es@bsc. es). The MACC/CAMS dust profiles are downloaded from the MACC aerosol database  (MACC, 2016). The SKIRON dust profiles can also be provided upon request and are also available at http:// forecast. uoa. gr/dustindx. php. Competing interests. The authors declare that they have no conflict of interest. Special issue statement. This article is part of the special issue "The Saharan Aerosol Long-range Transport and Aerosol-Cloudinteraction Experiment (SALTRACE) (ACP/AMT inter-journal SI)".
Acknowledgements. We thank the  R/V Meteor team and German Weather Service (DWD)  for their support during the cruise  M96. We appreciate the effort of AERONET MAN to equip research vessels with sun photometers for atmospheric research. We are grateful to  Angela Benedetti  ( MACC/CAMS model; European Centre for Medium-Range Weather Forecasts, Reading, UK ) for all her fruitful comments and suggestion during the initial phase of paper preparation. The SKIRON model operations were supported by the  European Commission  through the  Seventh Framework Programme MARINA platform (Marine Renewable Integrated Application Platform , grant agreement  241402 ). NMMB/BSC-Dust model simulations were performed in the MareNostrum supercomputer hosted by  BSC. Sara Basart  and  Oriol Jorba  acknowledge the  CICYT  project ( CGL2016-75725-R ) of the  Spanish Government  and the  AXA Research Fund.
Summaries of the NAWX system specifications are listed in Tab. I. The two radars have the following common features: • two channel 12-bit digital receivers; • electronic switching at both frequencies, allowing nearsimultaneous sampling of the atmosphere in three planes along the flight-line using six antennas; • synchronized operation and data collection for dualwavelength analysis; • pulse pair and FFT Doppler processing. The NAWX W-band has some unique components and design features that allow high resolution cloud measurements from an airborne platform as listed below: • a space qualified W-band Extended Interaction Klystron (EIK) tube with 3% duty cycle, designed by CPI Canada for the CloudSat mission; • a motorized two-axis reflector plate that allows the beam from the aft-looking dual-polarized 12" antenna to be reflected up to 40 • in forward direction in either the horizontal or vertical (nadir) planes, providing dual-Doppler measurement in either horizontal and vertical (nadir) planes; • dual channel DDS board (developed by ProSensing) is used to change the output frequency of each pulse for frequency hopping mode to de-correlate samples of the radar parameters and to generate standard pulses or linear FM chirp waveforms with selectable bandwidth and pulse length.
The NRC Airborne W-band and X-band Radar System (NAWX) has been used in several field campaigns (e. g. ,  ISDAC, ). The W-band system (NAW) was upgraded for this project to run in a polarization diversity pulse pair (PDPP) mode. For the NAW PDPP upgrade a conventional pulse-pair PP10 mode was modified (Fig. 3 ) allowing to collect conventional pulse pair and PDPP data from one of the two dual-polarization antennae. In this modified PDPP mode, sequences of H/V and V/H polarization diversity pulse-pairs are transmitted interleaved with staggered conventional H/H and V/V pulse-pairs. The main NAW upgraded features include the ability to transmit near double pulsing with short spacing as low as 5 µ s and recording the raw IQ radar data in PDPP mode. The PDPP data is collected using either the dualpolarization aft-looking antenna and reflector combinations or the side dual-polarization antenna.
C. Antenna beam vector calibration The accuracy in the calculation of the incidence angle is determined by the accuracy of the antenna beam pointing vector and the accuracy of the aircraft altitude and ground velocities measurements. The Convair-580 INS module and the NAWX W-band radar are co-located. This and the Convair INS-GPS real-time integrated data system provide precise altitude and velocity information. The beam pointing vectors are calibrated using data selected from many flights over stationary surface targets such as low-height vegetation farm lands. The calibration procedure is done using a similar optimization method described in  [25]. For the side looking antenna, the antenna mount is rigid and no moving mechanism on the beam transmit path is involved, so the beam angle can be calibrated with a maximum root mean square error less than 0.
ACKNOWLEDGMENT The work was supported by the  European Space Agency  under the activity " DOPPLER WIND RADAR DEMONSTRATOR" (ESA-ESTEC  Contract Number  4000114108/15/NL/MP ) and by the  CEOI-UKSA  contract  RP10G0327E13. We thank the  National Research Council of Canada Convair Aircraft  flight crew for conducting the project flights,  Andrew Pazmany of ProSensing  for the implementation of the PDPP mode on the  NRC Airborne W-band Radar.
OBSERVATIONS AND TECHNIQUES The full details of the SUPERB observing system and analysis setup can be found in Paper 1; here we briefly summarise the key points relevant to this work. Real-time searches are conducted for both transient and periodic signals in the incoming data. These data are also searched offline through a more rigorous process which operates slower than real time. These two streams are called the "Fast" (F) and "Thorough" (T) pipelines, respectively. For the single pulse pipeline, data are acquired in the form of a time, frequency and total intensity matrix. These are fed to the transient detection pipeline, 1 , which applies sliding boxcar filters of various widths and performs a threshold search. This produces candidate detections that are classified as FRBs if they meet the following 1 https://sourceforge.
The burst is slightly scattered but unresolved. 2  We determine the frequency dependence of the observed dispersion, t delay ∝ DM × ν -β , to be β = 2. 000 ± 0. 008, perfectly consistent with a cold-plasma law. FRB 151206 fell just between search trials in the F pipeline, placing it slightly below the detection threshold. However the Tpipeline (which samples DM parameter space more completely) identified it soon after. As a result the full-Stokes data were not retained and no polarisation information is available. The burst is unresolved and slightly scattered. The limited signal-to-noise ratio prevents a fit for the DM index. The trigger was issued only 25 hours after the time of occurrence and eleven telescopes observed the Parkes position over the following days to months. Observations and results from each of these telescopes are described in §4.
Radio interferometric follow-up for possible counterparts Radio imaging observations were performed using the Australian Telescope Compact Array (ATCA)  (Wilson et al. 2011) , VLA, the Giant Metrewave Radio Telescope (GMRT)  (Ananthakrishnan 1995)  and the e-Merlin radio telescope  (Garrington et al. 2004) , spanning 4 to 8 GHz and 1 to 1. 4 GHz. The details of the observations, data analysis and variability criteria are listed in Appendix B. Here we present the results of the follow-ups and the implications of the variability are discussed in §5. FRB 151206: ATCA observed the field of FRB 151206 on 2015 December 9, 3 days after the burst. Visibilities were integrated for 3 hours yielding a radio map with an rms noise of 50 µJy/beam at 5. 5 GHz and 60 µJy/beam at 7. 5 GHz. The declination of the FRB field (δ = -04 °) was not favourable for ATCA observations, therefore no subsequent observations were performed and no variability analysis was conducted on these data.
Follow-up at non-radio frequencies We have carried out optical and high energy follow-up and searched for neutrino counterparts to these four SUPERB FRBs. The results are presented in this section and the details of the observations and magnitude limits are listed in Appendix C. Note that the data have not been calibrated to the same absolute flux scale, and there may be systematic differences between different instruments. However, the data are self-consistent for variability analysis for each instrument. Table  3. The results of the radio follow-up performed using the ATCA, VLA and GMRT on the fields of SUPERB FRBs. N total denotes the total number of sources detected above 6-sigma and N analysis are the number of sources used in the variability analysis. This excludes extended sources in the field of respective FRBs.
ACKNOWLEDGEMENTS The Parkes radio telescope and the  Australia Telescope Compact Array  are part of the  Australia Telescope National Facility  which is funded by the  Commonwealth of Australia  for operation as a National Facility managed by  CSIRO. Parts of this research were conducted by the  Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) , through project number  CE110001020. The GMRT is run by the  National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. VLA is run by the  National Radio Astronomy Observatory (NRAO). NRAO is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc. This work was performed on the gSTAR national facility at  Swinburne University of Technology.
TB and RWW are grateful to the  STFC  for financial support (grant reference  ST/P000541/1 ). Research support to IA is provided by the  Australian Astronomical Observatory. The ANTARES authors acknowledge the financial support of the funding agencies:  Centre National de la Recherche Scientifique (CNRS) ,  Commissariat  à l'énergie atomique et aux énergies alternatives (CEA),  Commission Européenne (FEDER fund and Marie Curie Program) ,  Institut Universitaire de France (IUF) ,  IdEx program  and  UnivEarthS Labex program at Sorbonne Paris Cité  ( ANR-10-LABX-0023  and  ANR-11-IDEX-0005-02 ),  Labex OCEVU  ( ANR-11-LABX-0060 ) and the A* MIDEX  project ( ANR-11-IDEX-0001-02 ),  Région Île-de-France (DIM-ACAV) ,  Région Alsace  (contrat CPER),  Région Provence-Alpes-Côte d'Azur, Département du Var and Ville de La Seyne-sur-Mer, France ;  Bundesministerium für Bildung und Forschung (BMBF) ,  Germany ;  Istituto Nazionale di Fisica Nucleare (INFN), Italy ;  Stichting voor Fundamenteel Onderzoek der Materie (FOM) ,  Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO) , the  Netherlands; Council of the President of the Russian Federation  for young scientists and leading scientific schools supporting grants,  Russia ;  National Authority for Scientific Research (ANCS) ,  Romania ;  Ministerio de Economía y Competitividad (MINECO) :  Plan Estatal de Investigación  (refs.
It is difficult, however, to quantitatively disentangle the contribution of these factors to the wide-spread RNAP pausing. In the present study, we made use of publicly available genomewide datasets of RNAP pausing and backtracking  [8]  and nucleosome positions  [19]  to compare the explanatory power of basepairing thermodynamics of nucleic acids and known nucleosome positions on the reported pervasive RNAP pausing and backtracking  [8]. To this end, we also built a simple, data-driven quantitative model of how basepairing of nucleic acids affects RNAP pausing during forward movement, pausing during backtracking and the incidence of backtracks.
To do this, we used a sequence-dependent nearest neighbor model as is often used to determine PCR primer melting temperatures  [25, 26]  (see Materials and Methods and S1 and S2 Tables). We then averaged the melting energy for the positions around all pause sites to determine if any systematic pattern emerged (Fig 2C  and 2E ). In the dst1Δ NET-seq dataset-which captures the position where RNAP pauses when moving downstream, (i. e. in the direction of transcription)-we found that the sequences directly upstream of pause sites have more stable RNA:DNA basepairing than DNA:DNA basepairing (Fig 2A  and 2B ). These are the nucleotides which would form the RNA:DNA hybrid inside RNAP. Further, in the sequence directly downstream of pause sites, RNA:DNA basepairing is weaker than DNA:DNA basepairing.
These are the DNA:DNA base pairs that would need to be melted for the polymerase to continue moving downstream. Although these bases have not yet been transcribed, they seem to influence pausing; this observation will be discussed further below. Therefore, we suggest that the polymerase is found at specific locations in NET-seq data because it thermodynamically favors these positions over positions downstream. For the WT dataset, where the polymerase is assumed to be backtracking, RNA:DNA basepairing is weaker than DNA:DNA basepairing in the sequence directly upstream (i. e. in the direction of backtracking) of RNAP, suggesting that RNAP pauses during backtracking at positions it thermodynamically favors over continuing its backtracking. These are the sites where subsequent cleavage mediated by TFIIS is most likely to occur, and thus these sites are revealed in the WT NET-seq dataset.
If the difference in RNA:DNA and DNA:DNA basepairing strength is summed over the presumed length of RNA:DNA hybrid of 8 bp  [5, 12, 15, 27]  (for simplicity, we assumed the length of RNA:DNA hybrid to be constant), a clear pattern emerges for both dst1Δ and WT datasets (Fig 2C  and 2E ). Based on the direction of RNA polymerase movement, the polymerase pauses at sites when the change in RNA:DNA basepairing energy compared to DNA:DNA basepairing energy is greatest. Importantly, the change in basepairing energies around pause sites for dst1Δ and WT datasets looks similar if the change in direction of RNAP movement is accounted for (Fig  3B ). Specifically, in dst1Δ datasets, it is thermodynamically unfavorable for RNAP to move downstream, and in WT datasets it is thermodynamically unfavorable for RNAP to move upstream.
The incidence of backtracks depends on nucleotide basepairing Having determined a feature of DNA sequences that can predict RNAP pausing during downstream movement (dst1Δ) as well as during upstream movement (WT), we next asked whether this sequence feature could also predict the propensity of RNAP to enter into backtracking after an initial pause. This is of biological interest since RNAP backtracking increases transcriptional fidelity  [1] , but long backtracking excursions also promote genome instability  [28]. Since the dst1Δ NET-seq dataset shows the positions of initial pauses, and the WT NET-seq dataset shows the sites where the cleavage of 3' end of backtracked RNA by TFIIS occurred  [8] , comparing the pause sites in these two datasets offers the opportunity to classify the pauses in dst1Δ the dataset as leading to backtracking or not.
Pauses in dst1Δ the dataset for which there is a pause in the WT dataset that is 0-1 nt upstream were considered non-backtracking (63. 9% of total dst1Δ pauses). Pauses in the dst1Δ the dataset for which there is a corresponding pause in the WT dataset between 2 and 15 nucleotides upstream were considered backtracking (35. 7% of total dst1Δ pauses, Fig  4A ). We found that pauses with higher ΔTEC were more likely to exhibit backtracking (Fig  4B ). This correlation between higher ΔTEC and backtracking was far more predictive than nucleosome positions were (Fig  4C ). Therefore, sequences with higher TEC stability differences not only cause more RNAP pauses, but also cause backtracking more often after the initial pause.
Discussion In the present study we find that RNAP pauses at specific and ubiquitous DNA sequences for thermodynamic reasons. RNAP essentially operates as a Brownian ratchet  [32]. As it transcribes and moves downstream, DNA:DNA base pairs ahead of the polymerase are broken and replaced with RNA:DNA base pairs inside of the transcription elongation complex (TEC). Upon further downstream movement, the RNA:DNA base pairs are broken as the nascent RNA exits from RNAP and the DNA:DNA duplex reforms. Since both RNA:DNA and DNA: DNA basepairing energies are sequence-specific, the propensity of RNA polymerase for forward movement is likely to be influenced by changes in thermodynamic stability due to the nucleotide sequence. By analyzing the pause sites uncovered in NET-seq datasets, we found that RNAP pauses where its current position in the S.
cerevisiae genome is thermodynamically favored over the position further in its direction of movement. We find this to be the case both for RNAP pausing while the polymerase transcribes and moves downstream, as well as for RNAP pausing while the polymerase backtracks and thus moves in the upstream direction. The similarity of basepairing energy profiles around pauses in WT and dst1Δ suggests that the underlying physical mechanism of RNAP pausing due to nucleotide sequence is the same irrespective of whether the polymerase moves forward (dst1Δ dataset) or backwards (WT dataset). It also provides further evidence that NET-seq of WT yeast strain captures the RNAP in the backtracked, post-cleavage state and thus that the restart of transcription after TFIIS cleavage is the rate limiting step during proofreading, as originally inferred only from the relative shifts between WT and dst1Δ NET-seq data  [8].
Materials and methods Alignment Sequencing data from Churchman et al. [8]  was downloaded from http://www. ncbi. nlm. nih. gov/geo/ via GEO accession number GSE25107. Sequences were converted from. sra to fastq format with sratoolkit and were aligned to the SacCer3 transcriptome data (UCSC) with topHat2 and allowing only up to 3 mismatches for each alignment. Non-unique alignments were excluded. A custom python script was used to map the beginning of each read to positions in the genome to generate bedgraph files (see included files). Custom MATLAB1 script was then used for analysis and is available as a supplement at IST Austria Data Repository, http://dx. doi. org/10. 15479/AT:ISTA:45.