dataesr/scientific-paragraphs-categorization huggingface dataset:
For protons, they amount to about 1/2 for the whole momentum range. The measurements of Λ spectra described in Section 4. 3 can be used to improve the precision of the correction. Therefore the feed-down contribution of Λ is calculated separately from the feed-down correction due to other weak decays. Technically the Λ feed-down correction based on data was evaluated by weighting the VENUS4. 12 generated spectra of Λ to agree with the measurements. The resulting change of the π - and proton spectra is shown in Fig. 15. Thus rescaling of the Λ spectra reduces the feed-down in π -spectra by a maximum of 8% at p = 2 GeV/c. For protons the reduction was found in most of the momentum range with a maximum at p = 9 GeV/c. The reweighting of the VENUS4. 12 K 0 S spectra based on the NA61/SHINE measurements impacts the corrected charged pion spectra by less than 2%.
At low momenta the ToF-F resolution ensures an unambiguous particle identification, thus small deviations of the dE/dx distribution from a single Gaussian in general are not important. A deviation has a significant effect only for momenta above 3 GeV/c. For pions it steadily increases up to 2% at p = 20 GeV/c. However for kaons, the uncertainty is an order of magnitude larger: up to 20% for K + at high momenta. (ii) Hadron loss. To ensure a high quality match of tracks and ToF-F hits the last point of a track should be within 1. 6 m from the ToF-F wall (z last > 6 m). This implies that a track segment is reconstructed in the MTPC-L or MTPC-R detectors. Possible imperfections in the description of the spectrometer can introduce a difference in the acceptance and reconstruction efficiency (merging track segments between VTPC-2 and MTPC-L/R) between simulation and real data which can be important for the reconstruction of long tracks.
The effect was not prominent in the 2007 data because the intensity of the beam was significantly lower than in 2009. The separation between electrons and mostly pions was found to be sufficient for all θ bins when a momentum-dependent cut on dE/dx was applied for each θ bin separately. The contribution of electrons was the largest for θ below 20 mrad and momentum below 4 GeV/c reaching about 10%. It decreased to 2% in bins of larger θ. In the next step, the raw yields of selected negatively charged hadrons were corrected using the standard NA61/SHINE simulation chain with the VENUS4. 12 model as primary event generator and GEANT3 for particle propagation and generation of secondary interactions. Like in the previous h -analysis one global correction factor was calculated for each {p, θ } bin.
Results on spectra This section presents results on spectra of π ± , K ± , and protons, as well as K 0 S and Λ in p+C interactions at 31 GeV/c. The large statistics of the 2009 dataset resulted in improved precision and larger coverage compared to the published 2007 data and allowed measurements of K -spectra in NA61/SHINE for the first time. The comparison between the 2009 and 2007 results is discussed. The new measurements are presented together with selected predictions of hadron production models, which are described    21:  (Colour online) Breakdown of π -systematic uncertainties for the h -analysis, presented as a function of momentum for the  [20, 40]  mrad angular interval as an example. in Section 6. Complete comparisons are shown in Ref. [56]. In order to avoid uncertainties related to the different treatment of quasi-elastic interactions and to the absence of predictions for inclusive cross sections, spectra are normalized to the mean particle multiplicity in all production interactions.
K ± results The tof -dE/dx analysis technique was used to obtain the K + spectra shown in Fig. 29  and the K -spectra plotted in Fig. 30. The large 2009 dataset allowed for the first measurements of K - yields in p+C interactions by NA61/SHINE. Large statistics for K + made it possible to use narrow {p, θ } bins in the analysis which is important for tuning the neutrino flux predictions in T2K. Numerical results are given in Tables  6  and 7  for K + and K -, respectively. The analysis of K + was repeated, as a crosscheck, with a coarser {p, θ } binning that corresponds to the previously published measurements based on the 2007 data  [6]. Good agreement was found. The total uncertainty for the 2009 data remains dominated by the statistical uncertainty as shown in Fig. 26  for K + as an example.
Proton results The tof -dE/dx analysis technique was used to extract proton spectra. These measurements, shown in Fig. 31 , cover a wide kinematic range above 1 GeV/c and are important for T2K since they provide the possibility to constrain the contributions from re-interactions in the long carbon target and in the elements of the beamline. Numerical results are given in Table  8. The new    proton spectra are in a good agreement with preliminary results obtained using the 2007 data  [58].
Summary This paper presents precise measurements of interaction and production cross sections as well as of spectra of π ± , K ± , protons, K 0 S and Λ in p+C interactions at 31 GeV/c. These data are crucial for predictions of the initial neutrino fluxes in the T2K long baseline neutrino oscillation experiment in Japan. Furthermore, they provide important input to improve hadron production models needed for the interpretation of air showers initiated by ultra high energy cosmic particles. The measurements were performed with the large acceptance NA61/SHINE spectrometer at the CERN SPS. A set of data collected with a 4% λ I isotropic graphite target during the high-statistics NA61/SHINE run in 2009 was used for the analysis. The measured spectra are compared with predictions of several hadron production models.
Acknowledgements We would like to thank the  CERN PH, BE  and  EN Departments  for the strong support of NA61/SHINE. This work was supported by the  Hungarian Scientific Research Fund  (grants  OTKA 68506  and  71989 ), the  János Bolyai Research Scholarship of the Hungarian Academy of Sciences , the  Polish Ministry of Science and Higher Education  (grants  667/N-CERN/2010/0 ,  NN 202 48 4339  and  NN 202 23 1837 ), the  Polish National Center for Science  (grants  2011/03/N/ ST2/03691 ,  2012/04/M/ST2/00816  and  2013/11/N/ST2/03879 ), the  Foundation for Polish Science -MPD program , co-financed by the  European Union  within the  European Regional Development Fund , the  Federal Agency of Education of the Ministry of Education and Science of the Russian Federation  ( SPbSU research  grant  11.
38. 193. 2014 ), the  Russian Academy of Science  and the  Russian Foundation for Basic Research  (grants  08-02-00018 ,  09-02-00664  and  12-02-91503-CERN ), the  Ministry of Education, Culture, Sports, Science and Technology, Japan ,  Grant-in-Aid for Scientific Research  (grants  18071005 , 19034011, 19740162, 20740160 and 20039012), the  German Research Foundation  (grant  GA 1480/2-2 ), the  U. S. Department of Energy , the  EU-funded Marie Curie Outgoing Fellowship , Grant  PIOF-GA-2013-624803 , the  Bulgarian Nuclear Regulatory Agency  and the  Joint Institute for Nuclear Research, Dubna  (bilateral contract No. 4418-1-15/17 ),  Ministry of Education and Science of the Republic of Serbia  (grant  OI171002 ),  Swiss Nationalfonds Foundation  (grant  200020117913/1 ) and  ETH   Research Grant   TH-01 07-3.
Over the last 20 years, the geoarchaeology of ancient harbours has been a very active area of research around the Mediterranean basin, generating much palaeoenvironmental data from many sites, including estimations of sedimentation rates, the height of the ancient sealevel at different dates and palaeo-geographical reconstructions. Combining this information has proved a major challenge. This article proposes a new chart called the Palaeoenvironmental Age-Depth Model (PADM chart), that allows the researchers to combine all relevant indicators in order to estimate harbour potential of a given ancient port, and to generate comparable data between harbours in terms of degree of closure and water depth available against a synchronised chronology. This new approach, developed in the context of the ERC-funded RoMP Portuslimen project, takes into account estimations of water depths relating to differing Roman ship draughts at different periods.
Palaeoenvironmental analysis After the conclusion of the excavations and coring, sediments are removed from the site and studied in the laboratory-all necessary permits were obtained for this study, which complied with all relevant regulations; Soprintendenza Speciale per il Colosseo, Museo Nazionale Romano e Area Archeologica di Roma (Ufficio di Ostia) authorized the access to the drilled fields. Palaeoenvironmental data from Ostia and Portus synthesised in this article is available in several published articles  [13] [14] [15] [16] [17]. Non-destructive analyses are performed to characterize the stratigraphic sequences sampled (magnetic susceptibility, itrax scanner etc. ). Destructive analysis starts with sampling the sedimentary units. This will differ according to the analyses needed, ranging from high to low resolution.
This rotation naturally mixes E-and B-modes of CMB polarization 2 and generates T -B and E-B correlations that would be zero Planck Collaboration: Parity violation constraints in the absence of parity violations. The cosmic microwave background (CMB) polarization is particularly useful for measuring such an effect, because even if the coupling is small, CMB photons have travelled a large comoving distance from the last-scattering surface (almost) completely unimpeded and thus the rotation could accumulate into a measurable signal. This effect has previously been investigated using data from many CMB experiments  (Feng et al. 2006; Wu et al. 2009; Brown et al. 2009; Pagano et al. 2009; Komatsu et al. 2011; Hinshaw et al. 2013; Ade et al. 2014a,b; Kaufman et al. 2014; Naess et al. 2014; di Serego Alighieri et al.
For Planck there is an estimate of the uncertainty of the possible instrument polarization angle using measurements performed on the ground  (Rosset et al. 2010) , as discussed further in Sect. 6. Unfortunately, in-flight calibration is complicated by the scarcity of linearly polarized sources that are bright enough, with the Crab Nebula being a primary calibration source (Planck Collaboration VIII 2016). 4 qs. (  1 )-(  6 ) include all the secondary anisotropies but the weak-lensing effect. Due the current precision of data (see the discussion in  Gubitosi et al. 2014)  we safely ignore the weak-lensing effect as it contributes a negligible error.
No further smoothing is applied to any of the maps (although this version of the data already includes 10 smoothing in both temperature and polarization). We note that there are known systematic effects in the polarization maps released by Planck that have not been fully remedied in the 2015 release (see Sect. 6 for a full discussion on the main systematic effects relevant for this analysis). These issues include various sources of large angular scale artefacts, temperature-to-polarization leakage  (Planck Collaboration VII 2016; Planck Collaboration VIII 2016; Planck Collaboration XI 2016) , and a mismatch in noise properties between the data and simulations  (Planck Collaboration XII 2016). In order to mitigate any largeangle artefacts, we use only the high-pass-filtered version of the polarization data.
The map-space analysis does not require the use of simulations, 7  since we only need a relatively crude noise estimate on the scales we work at and we use a weighting approach when stacking that is only dependent on the data (we have also checked that our results are quite insensitive to the noise level of the data, see Sect. 6. 1). Nevertheless it is reassuring that the map-space and harmonic-space analyses arrive at consistent results. We use realistic full focal plane (FFP8. 1) simulations described in detail in Planck Collaboration XII (2016). These are 10 3 simulations processed through the four Planck component-separation pipelines, namely Commander, NILC, SEVEM, and SMICA (Planck Collaboration IX 2016), using the same weights as derived from the Planck full mission data. The CMB output maps are used to build the harmonic space estimators used in this work.
20), we must estimate it from the halfmission data along with simulations in order to satisfy the recommendations on the use of polarization data given in Planck Collaboration IX (2016), based on the fact that only results with a weak dependence on noise are to be considered fully reliable. More specifically, C EE and C BB are estimated from cross-correlating half-mission 1 with halfmission 2 SMICA data and using the corresponding SMICA simulations only.
Harmonic-space results Following the recommendation given by the Planck collaboration (Planck Collaboration IX 2016), we present results below based only on cross-correlations. Therefore, as described in Sect. 3, we present results for the D T B -estimator using the full-mission data from Commander, NILC, SEVEM, and SMICA, and with half-mission data for SMICA. For the same reasons we present results with the D EB -estimator using the half-mission data from SMICA only. Additionally we present a joint analysis with the half-mission data from SMICA. Of course the D-estimators are built through the CMB angular power spectra. As an example, we display in Fig. 4  the T B and EB CMB angular power spectra obtained with the SMICA method using half-mission data. We also show the FFP8. 1 simulations for the same componentseparation method.
• 28. This final error is not exactly Gaussian, although it is close (68 % and 95 % CLs are 0. • 28 and 0. • 55, respectively). Given that we detect a rotation of around 0. • 3, we are, therefore, unable to disentangle the signal found in the data from the possible presence of this systematic effect. It remains to be seen whether or not this can be improved in a future Planck release. It might be expected that Commander would perform best in polarization in terms of noise and handling of systematics (based on the angular scales probed here, see Planck Collaboration IX 2016, for details). However, given that Commander uses a slightly different set of data than the other component-separation methods and given that they all use different algorithms, we cannot make any definitive claims as to which gives the most accurate constraint.
Noise properties of polarization The recommendation from the Planck collaboration is that any analysis performed on polarization data should not be very sensitive to mis-characterization of the noise. To this end cross-spectra, cross-correlation, and stacking analyses are examples of such approaches. Our harmonic space and map space temperature tests fulfil this criterion explicitly. It is less obvious that stacking on E-mode extrema should only weakly depend on the noise properties; however, we find this to be the case. This is because the statistics of the E-mode map are encoded in the bias parameters ( bν , bζ ), which depend on the total power in the map (see Appendix A for details). Therefore the bias parameters will be accurate to the level that the statistics of the polarization data can be determined by its two-point function.
In Fig. 8  we show a comparison of our estimate with the birefringence angle estimates provided by analysis on other CMB data in which, where possible, the total error budget is decomposed in these two parts, i. e. statistical (left point of a pair) and systematic (right). The total error budget of our estimate is dominated by the systematic uncertainty, which is a factor of 6 larger than the statistical one. It is clear, therefore, that future CMB polarization experiments (or a future Planck release) will require a much better understating of their polarimeter orientations, since this is appearing as the current limiting factor of this investigation. With a coordination of careful ground-based measurements and improved in-flight calibration on polarized sources (see  Kaufman et al. 2014 , for an example of a possible effort) we may be able to further probe possible parity violations in the Universe.
Acknowledgements. The Planck Collaboration acknowledges the support of:  ESA ;  CNES , and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MINECO , 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) ;  ERC  and  PRACE (EU). A description of the Planck Collaboration and a list of its members, indicating which technical or scientific activities they have been involved in, can be found at http://www. cosmos. esa. int/web/planck/planck-collaboration. Some of the results of this paper have been derived using the HEALPix package (Górski et al. 2005).
Background: Whole-genome sequence (WGS) data give access to more complete structural genetic information of individuals, including rare variants, not fully covered by single nucleotide polymorphism chips. We used WGS to investigate the amount of genetic diversity remaining after selection using optimal contribution (OC), considering different methods to estimate the relationships used in OC. OC was applied to minimise average relatedness of the selection candidates and thus miminise the loss of genetic diversity in a conservation strategy, e. g. for establishment of gene bank collections. Furthermore, OC was used to maximise average genetic merit of the selection candidates at a given level of relatedness, similar to a genetic improvement strategy. In this study, we used data from 277 bulls from the 1000 bull genomes project.
Conservation of livestock species aims at maximising genetic diversity on the long-term. Genetic material is conserved, for example in gene bank collections, in order to allow future use or recovery of genetic variation. However, breeding programs focus mainly on genetic improvement in the next generation. Optimum contribution (OC) selection strategies have been designed to simultaneously target genetic improvement and conservation of genetic diversity. In terms of genetic diversity conservation, OC aims at minimising or restricting average relatedness of the potential parents in order to minimise the rate of inbreeding and maximise genetic diversity in the long-term  [7, 8]. Previous studies  [9, 10]  investigated the impact of using genomic information from SNP chip data instead of pedigree information for OC and showed that adding genomic information resulted in a slightly increased genetic diversity.
Animals This study was performed on data from 277 Holstein bulls from Run 4 of the 1000 bulls genome project. These 277 individuals originated from Europe, North-America, Australia and New-Zealand (based on their Interbull ID) and were born between 1965 and 2010. Their full pedigree contained 12,949 individuals of which 4535 were sires and 8414 were dams, and was recorded from the 1900s onward. Base individuals in the pedigree, i. e. 3093 individuals with both parents unknown, had birth years ranging from 1883 to 2002. The average date of birth of the base individuals was 1931, while it was 1948 for the non-base individuals. Within the group of 277 sequenced bulls, we observed 106 parent-offspring relationships, three full-sib pairs and 200 half-sib pairs. All individuals were related to some extent.
Sequences Whole-genome sequence data of the 277 bulls contained a total of 35,726,017 variants across the 29 autosomes, of which 20,177,956 segregated in this set of animals. WGS were obtained using sequencing outputs from Illumina HiSeq Systems (Illumina Inc. , San Diego, CA) that were edited in five steps: sequence alignment, variant calling, phasing, quality controls and imputation. Of the called variants, 94. 52 % were SNPs and 5. 48 % were insertiondeletions. The overall sequence coverage per individual ranged from 3 to 38, with an average of 12. SNP-type variants that are included in the Illumina BovineSNP50 BeadChip v2 (Illumina Inc. , San Diego, CA) were extracted to be used as 50 K SNP chip. This SNP subset contained 48,652 SNPs of which 46,050 were segregating in the population of 277 bulls.
Acknowledgements The authors want to thank  J. Vandenplas  for his help in the programming and  I. Hulsegge  for the help in accessing the data. The authors thank the 1000  Bull genomes consortium  for providing the sequence data. The authors would also like to thank the anonymous reviewers and the editors for their valuable comments and suggestions. S. E. Eynard benefited from a Grant from the  European Commission , within the framework of the  Erasmus-Mundus joint doctorate "EGS-ABG ", co-funded by the  Dutch Ministry of economic Affairs  ( KB-12-005-03-001 ).
Acknowledgments Many thanks to  Paul Jepson  for his encouragement and helpful comments on a draft. Fieldwork was funded through private donations, some anonymous, via Indiegogo, for which we are grateful. Special thanks go to  Franco Bove  for his contribution. AL and BB thank all informants and everyone who generously provided their time and help during fieldwork. MR-B is funded by  Danish National Research Foundation Niels Bohr professorship project Aarhus University Research on the Anthropocene (AURA).
For each metal, there were individual samples that exceeded the established environmental reference values. Inorganic arsenic levels exceeded occupational reference values. The most commonly elevated levels were for copper and nickel, with 67. 5% and 30. 4% of samples exceeding the reference values, respectively. The highest copper levels were found value corresponding to half of the DL (DL/2), as proposed by the Centers for Disease Control and Prevention (CDC) for population studies in the United States over a similar study period. 32 We chose not to present creatinine-adjusted results because our reference values were obtained from studies focused on environmental exposure in the general population and provided unadjusted values. However, creatinine-adjusted levels were analyzed and this did not change the results (data not shown).
The highest levels found for nickel (5. 6 µg/L), arsenic (7. 6 µg/L), copper (10. 4 µg/L), and lead (1. 3 µg/L) were within the national drinking water standards. 38 Regarding food exposure, key informants indicated that locally-harvested seafood is not consumed in Chañaral due to obvious discoloration by copper. We were not able to obtain data on metals in foods more frequently consumed in the area. We did not collect blood samples to measure lead, which is the preferred method of assessing recent lead exposure. We use urinary lead level as a qualitative indicator of chronic exposure, as has been done previously in the United States. 32 This is the first publication of general population data on urinary lead levels in Chile. Notably, the highest urinary lead level (58 µg/L) was found among people who stated that they smelted lead for small-scale fishing, an activity unrelated to the exposure to mine tailings.
Acknowledgments Special thanks to  Dr. Paulina Pino , Director of the Doctoral Program in Public Health, and  Dr. Kyle Steenland , for their cooperation and continued support through the  Fogarty Program award  ( International Training and Research Program in Environmental and Occupational Health)  to the  University of Chile , School of Public Health. Thank you to  Professor Jorge Quense A ,  Institute of Geography (Pontificia Universidad Católica de Chile ) for his help making maps and to  Rosario Toro  for reviewing the final version. Special thanks to  Professor Germán Corey. His  dedicated comments undoubtedly improved the final version. Finally, we are grateful to the  Chañaral community  for their participation.