dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements  K. J. Sanchez  and  G. C. Roberts  acknowledge the support of  NSF  Grant No. AGS-1660374. G. Saliba  and L. M. Russell acknowledge  NSF   AGS-1660509. SOCRATES data are available through the following EOL UCAR repository https://data. eol. ucar. edu/master_lists/generated/socrates/(Sanchez and Roberts, 2018;  UCAR/NCAR-Earth Observing Laboratory ,  2019 ). GDAS data are available at https://ready. arl. noaa. gov/HYSPLIT. php. Directions to obtain the ERA5 data are available at https://confluence. ecmwf. int/display/CKB/How+to+download+ERA5#HowtodownloadERA5-1-Introduction. Contains modified Copernicus Climate Change Service Information 2019. The Authors wish to thank the  CSIRO Marine National Facility (MNF)  for its support in the form of sea time on RV Investigator, support personnel, scientific equipment and data management.
V. NUMERICAL EXPERIMENT In this section, we conduct a series of numerical experiments to explain: (1) the efficiency and effectiveness of the proposed optimization model and solution algorithm. (  2 ) how the duplication sampling number M and sample size N /N k affect the performance of the HSAA algorithm; (3) the effect of different sampling methods on objectives values. We implement all the numerical experiments in MATLAB 2014b by using PC with Inter(R) Core(TM) i5-6500U CPU @3. 2GHz and 4 GB RAM. In Subsection V-A, we detail our experimental data and parameters pretest results. The improvement of runway scheduling comparing current practice and off-the-shelf solvers are reported in Subsection V-B. In Subsection V-C, the performance of the HSAA algorithm on parameters M and N /N k are discussed.
Statistical analysis Statistical analysis were performed with the R software (Rx64 3. 2. 3 R Development Core Team, http://www. R-project. org). We used signed rank Wilcoxon test to compare the DV and PV condition for the 10-meters walking speed on the normal and double-task conditions, the time to perform the timed-up-and-go test, the time to raise up from the floor. We used standard deviations and coefficients of variation to assess the variability of walking speed on the DV and on the PV conditions.
Effect of PAT exposure and the DSS challenge on the intestinal microbiota Next, we examined the effects of the PAT (tylosin) exposure and the DSS challenge on intestinal microbial communities. We collected fecal pellets at weaning and 1, 3, and 7 days after the DSS challenge was begun, as well as ileal, colonic, and cecal samples at sacrifice. Intestinal microbial community diversity was significantly decreased in the PAT-exposed mice (Fig. 3a ). Microbial richness and evenness was significantly decreased in PAT-exposed mice compared to the controls at weaning (P21, 11 days after PAT), persisting until P32 (3 weeks after cessation of the exposure) (Additional file 1: Fig. S1D ). While PAT effects on colonic and cecal populations were comparable to those in the fecal samples, ileal community differences were less (data not shown), in accordance with prior literature indicating the highly dynamic  [42]  and less diverse  [43]  nature of the small intestinal microbiota.
Effect of tylosin treatment on the microbial community in the later time period Next, we examined the duration of the effects of the early-life tylosin exposure on the microbiota. By P40, microbial richness and evenness (alpha-diversity) began increasing, becoming similar to the controls (data not shown). However, the microbial community structure of the PAT and control mice remained distinct at P40 (Fig. 4g ). As described above, the short-term DSS challenge had no substantial effect on intestinal microbiota composition (data not shown). As before, Proteobacteria and Rikennellaceae were abundant, and Prevotellaceae, S24-7, and Ruminococcaceae were significantly decreased in the PAT mice at weaning. By P40, Proteobacteria and Rikennellaceae remained significantly more abundant in PAT mice.
An ROI to select the water ring was integrated as I 0. Dividing the TFY by I 0 yields the normalization corrected XAS signal (Fig. 1 ). To measure time-resolved XAS, the sample was excited with visible laser pulses at a wavelength of 500 nm and a pulse energy of 12 mJ, which were focused to a 150 mm (fwhm) spot at the sample position. Arbitrary data acquisition patterns of laser-excited and ground state (no visible excitation laser) can be chosen, and 2 out of 9 X-ray pulses were used to measure the ground state, while 7 out 9 pulses were used for the laser-excited XAS measurement.
1 Å. Similarly, an average metalligand bond elongation of B0. 1 Å has been observed for the doublet-quartet transition in [Co(terpy) 2 ] 2+. 23 he XAS spectrum, with and without laser excitation (Fig. 2 ) was removed from artifacts (see ESI † for details on the deglitching procedure). The measured energy range allows the analysis of the EXAFS spectrum up to a photoelectron wavevector k of B11. 9 Å À1 and optically induced transient differences are visible over the whole spectral range (see inset on Fig. 2 ). The total acquisition time of the data shown in Fig. 2  was B3. 5 h, with B250 energy points equidistant in k-space. The laser excitation fraction is determined to be f = 76% by comparing the intensity of the transient difference (normalized to the K-edge amplitude) of [Fe(terpy) 2 ] 2+ to the published synchrotron measurements, in which complementary X-ray emission spectroscopy (XES) measurements were used to precisely determine the excited state fraction.
30 The laser excited spectrum m LON contains contributions from both ground and excited state, as not all molecules are turned over to the HS state by the optical laser. As the excited state fraction f is known, the ES absorption spectrum m ES is obtained by removing the contribution from the ground state absorption spectrum m GS (= m LOFF ) via 31 m ES = m LOFF + (1/f ) Â (m LON À m LOFF ) (1) The EXAFS spectra m GS and m ES , were then analyzed with the Demeter 0. 9. 26 software package, which includes ATHENA for background subtraction, FEFF6 for the EXAFS simulation and ARTEMIS for the final fit. 40 Fig. 3c  shows the spectra after removing the atomic background in ATHENA and translating to photoelectron wavevector k-space. The EXAFS spectra of the LS and HS states were further modeled with FEFF6 using structures obtained by density functional theory (DFT) calculations of both states from literature.
Acknowledgements This work was supported by the  Computational Materials Sciences Program  funded by the  U. S. Department of Energy, Office of Science, Basic Energy Sciences , under Award No. DE-SC0014607. Use of the Linac Coherent Light Source (LCLS) ,  SLAC National Accelerator Laboratory , are supported by the  U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences  under Contract No. DE-AC02-76SF00515. AB thanks  Amy Cordones-Hahn  for her support in characterizing the synthesized [Fe(terpy) 2 ] 2+ and  Clemens Weninger  for his support with data processing.
The Belle II experiment runs at the SuperKEKB accelerator at the High Energy Accelerator Research Organization (KEK) in Tsukuba, Japan. Belle II  [2]  is a next-generation B-factory experiment  [3]. It is the successor to the Belle experiment  [4]  and plans to record a dataset of 50 ab -1 , which is about 50 times the Belle dataset. With these data, Belle II aims to search for physics beyond the Standard Model and further study CP violation in the flavor sector, and precisely measure all parameters of the Cabibbo-Kobayashi-Maskawa "unitarity triangle"  [2]. The experiment will also study properties of the strong interaction in hadron physics. Operation of the SuperKEKB accelerator and the Belle II detector can be divided into three phases: Phase 1, from February to June 2016; Phase 2, from April to July 2018; and Phase 3, from March 2019 onwards.
The data sample under study in this work was recorded during Phase 2. During this phase, the beams of electrons and positrons collided at the centerof-mass (CM) energy of the Υ (4S) resonance, with a peak instantaneous luminosity of 5. 55×10 33 cm -2 s -1 , and the data sample was collected with a nearly complete Belle II detector. (The full vertex detector was not yet installed; see the next section for the detector description. ) In the earlier Phase 1, the beams were circulated but not collided in the accelerator's storage rings for beam-line conditioning, accelerator performance tuning, and beam background studies  [5]. In current and future Phase 3 running, copious data samples of beam-collision events are recorded for the comprehensive physics program of Belle II. The luminosity measurement of the collision data in Phase 2 is necessary for physics measurements with this data, and is valuable preparation for future measurements in Phase 3.
and response of the detector. In the simulation, beam backgrounds, such as those arising from the Touschek effect and beam-gas interactions, were overlaid on the e + e -collision events. The beam backgrounds were first simulated with dedicated accelerator-design software  [27] , and then processed by Geant4 to handle the interactions of the primary beam-background particles with the accelerator and detector material. [28]. Notably, a complete simulation of the material in the VXD region, including the cables, electronics, and support structure, was not yet available at this early stage of the experiment. The unsimulated material is conservatively estimated to be 20% of the simulated material, and its impact on the measured luminosities is discussed in Section 6. Both the data and MC samples were reconstructed and analyzed with the Belle II analysis software framework, basf2  [29].
Event selection To determine the integrated luminosity of the data sample, we first select the signals, namely Bhabha and digamma events. For this purpose, we require that candidate events have at least two ECL clusters, and we subsequently identify the two clusters with the largest energies in the CM frame. Because the ECL energies for the electrons and positrons of Bhabha events, and the photons of digamma events, tend to be distributed near half the CM energy, the higher energy of the two clusters in the CM frame is required to be less than 5. 82 GeV, and the lower energy of the pair is required to be greater than 2 GeV. To guarantee that the two clusters are well reconstructed within the ECL barrel region, their polar angles, i. e. those of the position vectors of the cluster centers (similar definition applies to their azimuthal angles), in the laboratory frame are required to be in the range 37.
Conclusions The integrated luminosity of the first data sample collected with the Belle II detector at SuperKEKB during Phase 2 is measured using ECL information with Bhabha and digamma events. The result obtained in the Bhabha-dominant measurement is consistent with that obtained in the digamma-dominant measurement. Combining the two measurements, we determine the integrated luminosity to be (496. 3 ± 0. 3 ± 3. 0) pb -1 , where the first uncertainty is statistical and the second is systematic. The result will be used in the early studies with the Phase 2 data at Belle II, particularly in the searches for new physics in the dark sector, in which Belle II expects to achieve good sensitivities owing to the dedicated triggers for single photon and low multiplicity events  [31]. Using ECL information alone, this work builds a foundation for future luminosity measurements in the Belle II experiment, in which we will incorporate the information obtained by other subdetectors, particularly the CDC, to select signal events.
We thank the  SuperKEKB group  for the excellent operation of the accelerator; the  KEK cryogenics group  for the efficient operation of the solenoid; and the  KEK computer group  for on-site computing support. This work was supported by the following funding sources:  Science Committee of the Republic of Armenia  Grant No. 18T-1C180 ;  Australian Research Council  and research grant Nos. DP180102629 ,  DP170102389 ,  DP170102204 ,  DP150103061 ,  FT130100303 , and  FT130100018 ;  Austrian Federal Ministry of Education, Science and Research, and Austrian Science Fund  No. P  31361-N36 ;  Natural Sciences and Engineering Research Council of Canada, Compute Canada and CANARIE; Chinese Academy of Sciences  and research grant No. QYZDJ-SSW-SLH011 ,  National Natural Science Foundation of China  and research grant Nos.
11521505 ,  11575017 ,  11675166 ,  11761141009 ,  11705209 , and  11975076 ,  LiaoNing Revitalization Talents Program  under contract No. XLYC1807135 ,  Shanghai Municipal Science and Technology Committee  under contract No. 19ZR1403000 ,  Shanghai Pujiang Program  under Grant No. 18PJ1401000 , and the  CAS Center for Excellence in Particle Physics (CCEPP) ; the  Ministry of Education, Youth and Sports of the Czech Republic  under Contract No. LTT17020  and  Charles University  grants  SVV 260448  and  GAUK 404316 ;  European Research Council , 7th Framework PIEF-GA-2013-622527, Horizon  2020 Marie Sklodowska-Curie  grant agreement No. 700525  ' NIOBE ,'  Horizon 2020 Marie Sklodowska-Curie RISE  project  JENNIFER  grant agreement No. 644294 ,  Horizon 2020 ERC-Advanced  Grant No. 267104 , and NewAve No.
W03. 31. 0026 ; Slovenian Research Agency  and research grant Nos. J1-9124  and  P1-0135 ;  Agencia Estatal de Investigacion, Spain  grant Nos. FPA2014-55613-P and FPA2017-84445-P, and  CIDEGENT/2018/020  of  Generalitat Valenciana ;  Ministry of Science and Technology  and research grant Nos. MOST106-2112-M-002-005-MY3  and  MOST107-2119-M-002-035-MY3 , and the  Ministry of Education (Taiwan) ;  Thailand Center of Excellence in Physics ;  TUBITAK ULAKBIM (Turkey) ;  Ministry of Education and Science of Ukraine ; the  US National Science Foundation  and research grant Nos. PHY-1807007  and  PHY-1913789 , and the  US Department of Energy  and research grant Nos. DE-AC06-76RLO1830 ,  DE-SC0007983 ,  DE-SC0009824 ,  DE-SC0009973 ,  DE-SC0010073 ,  DE-SC0010118 ,  DE-SC0010504 ,  DE-SC0011784 ,  DE-SC0012704 ; and the  National Foundation for Science and Technology Development (NAFOSTED) of Vietnam  under grant No  103.
230 Th data were not available for MD88-772 so opal mass accumulation rate (MAR) was determined using the dry bulk densities and sedimentation rates. However, it was noted in a previous study using a collection of sediment records from the Indian sector of the Southern Ocean, including MD88-773, that although MAR cannot be used quantitatively, the overall glacialinterglacial patterns observed in MAR records remained largely the same after 230 Th-normalisation  39. Preservation changes are not corrected for here, but Dezileau et al. 39  showed that changes in preservation were not important drivers of opal accumulation variability in the region over the last 40 ka. Supply of DSi to the Southern Ocean surface. The initial δ 30 Si diat rise observed from the LGM through the first Antarctic warming interval associated with Heinrich Stadial 1 (HS1) (~23-15 ka) coincides with a reduction in dust-borne iron flux  40, 41  and may represent a gradual progression towards iron limitation, favouring an increase in the DSi demand by the diatom community  36.
2a ). Hence, the Abyssal Silicon Hypothesis places a greater importance on deep diapycnal mixing and overturning in driving the redistribution of DSi across the global ocean. The Abyssal Silicon Hypothesis also differs from the Silicic Acid Ventilation Hypothesis  30  , which argues that the redistribution of DSi occurs primarily during deglaciations but with little overall change between glacial and interglacial states. Firstly, an important difference in light of the high-resolution records  In each of the reconstructions an open and closed isotope system models were applied to the Antarctic and Subantarctic, respectively. Black and grey arrows and text denote the transfer of DSi and opal, respectively. Bold data are those extracted from the literature and available data. The remaining data have been calculated from the simple mass balance model.
Age models. Where possible, the age models for the three cores were constructed based on accelerator mass spectrometry  14  C data, with analysis performed at the NERC Radiocarbon Laboratory, East Kilbride. 14 C ages were calibrated using the Calib 7. 04 software with the Marine13 calibration curve. Reservoir effects were applied to the dates, see Supplementary Note 1 for more details. Poor CaCO 3 preservation prevented the use of  14  C dating for MD88-773 and MD88-772 during the early deglaciation and LGM. The age models at these intervals were constructed by graphical correlation of titanium with detritus fluxes in nearby  14  C-dated sediment cores (see Supplementary Note 1, Supplementary Tables 1-3 and Supplementary Figs. 2  and 3  for more details).
Acknowledgements This work was supported by the  NERC   E3  DTP studentship awarded to  M. Dumont  and  NERC  Grant (ne/j02371x/1) award to  R. S. Ganeshram  and  L. E. Pichevin. We would also like to thank  S. Mowbray  and  C. Chilcott  from the  University of Edinburgh  for their invaluable technical assistance. Radiocarbon analyses were supported by the  NERC Radiocarbon Facility  (allocation  1883. 0415 ).
C. , J. B. R. ). The study protocol was approved by the Institutional Review Board of the University Hospital of Toulouse. All patients provided consent for the operation. Once completed and audited, the database was de-identified, and individual consent for the use of the database was waived by the institutional ethics committee. Open JRAAA repair was performed under general anaesthesia, with additional epidural anaesthesia according to the anaesthetist's experience. The choice of a transperitoneal or a retroperitoneal approach was decided after reviewing the fine cut (1 mm slices) CTA images of the aorta with three dimensional (3D) reconstructions to select the best location for aortic clamping. The retroperitoneal retrorenal approach was preferred to allow easy clamping of the suprarenal aorta without the obstacles represented by the left renal vein and by the pancreas.
Operative data Operative data are reported in Table  4. Mean total operating time was 194 AE 45 min. A retroperitoneal approach was most commonly performed (n ¼ 212 [67. 3%]) using a left lumbotomy (n ¼ 164 [52. 1%]) or a short thoracophrenolumbotomy (n ¼ 48 [15. 2%]). A transperitoneal approach by a midline laparotomy was used in 103 patients (32. 7%). Proximal clamping was carried out at the level of the interrenal aorta, above one renal artery, in 69 patients (21. 9%), above both renal arteries and below the superior mesenteric artery in 235 patients (74. 6%), and at the level of the supracoeliac aorta in 11 patients (3. 5%). The mean renal artery clamping time was 24 AE 7 min (range 18e55 min). In the 33 patients with supracoeliac clamping, the median visceral ischaemic time was 23 AE 6 min (range 18e40 min).
RSV genome assembly and annotation Assembly of the sequencing reads into complete genomes is performed with AstraZeneca's Next-Generation Sequencing Microbial Surveillance Toolbox (NGS-MSTB)a fully automated distributed pipeline implemented with a Common Workflow Language (CWL), and with a user interface based on the Galaxy bioinformatics workbench  [12]. The main processing step is a targeted de-novo assembly using Ariba  [13]  with AstraZeneca's customized assembly protocol tuned for robustness in the presence of mixed viral subpopulations and very high coverage variability. This is followed by post-assembly filtering of the low-abundance poorly assembled quasi-species. The pipeline creates a Web report with quality control metrics and genome browser views at the contig and individual read levels.
A manuscript with detailed description of the assembly pipeline and its opensource release is in preparation. The assignment of RSV subtypes is performed during the assembly process and the assignment of RSV genotypes is performed by phylogenetic clustering using a reference database of previously described genotypes  [14]. To determine the polymorphisms in the F protein binding regions of RSV mAbs, the gene sequences are translated into amino acid sequences, aligned against reference sequences (NL13 strains), and the amino acid changes are recorded.
08 using a 4 degrees of freedom chi-square test. This means, for example, that this study can detect a difference in the distribution of RSV subtypes if the prevalence of RSV A across the sites were approximately as follows: 58, 62, 66, 70, and 74%. These sample size calculations were conducted in PASS software, using the two-sided CIs for single proportions with the simple asymptotic method with continuity correction and a chi-square test power analysis. Although 2500 samples are sufficient to detect the desired effect, and based on the minimal invasiveness for INFORM participants, the study will expand and add more countries to maximize insight in geographic and temporal diversity.
Discussion In the INFORM RSV study, RSV isolates are subject to RSV subtyping and viral genome analysis. The main purpose of the project is to secure RSV samples to monitor RSV strains for changes in key epitopes recognized by mAbs. RSV is a member of the human orthopneumoviridae family  [15] , which are RNA viruses and therefore prone to genomic mutations. The possibility of immunological escape or viral resistance from mAbs approved or under development is a potential concern. In fact, a previous study performed by Regeneron (NCT02325791) to evaluate the efficacy and safety of suptavumab for the prevention of medically attended RSV infection in preterm infants failed to meet its predefined efficacy endpoint based on its reduced efficacy against RSV B strains  [16]. The reduced RSV B efficacy was due to a twoamino acid change at positions 172 and 173 in the antigenic site V region of the F protein, the epitope of suptavumab, which reduced susceptibility to suptavumab neutralization in vitro.
It is therefore important that clinical studies involving anti-RSV F mAbs monitor for amino acid substitutions in antigenic binding regions of RSV isolates from subjects experiencing virologic failure, and to assess the impact of these changes on phenotypic susceptibility and viral fitness. A key challenge for the INFORM RSV study is temporal diversity, as the timing of RSV outbreaks differs by season and location around the world. Another challenge is how to best integrate and interpret whole genome sequences in relation to clinical variables. To overcome this challenge, bioinformaticians from Astra-Zeneca, UMCU and Julius Clinical are working closely together to develop an integrated database and a robust pipeline to characterize the thousands of RSV sequences that will be generated. In summary, this global prospective study aims at monitoring the molecular epidemiology of RSV to ensure that already approved therapeutics and those in development will be effective against currently circulating strains worldwide.
Methodology 3. 1. Tectonics. Tectonic structures (fault planes, stylolithic peak axes, and tension joints) were measured over the entire Grands Causses area in the Jurassic cover over a surface area of 2500 km 2 , from Ste-Enimie to the north to Navacelles to the south, and from Sévérac-le-Château to the west to Florac to the east (Figure  2 ). They have been inversed using Win-Tensor software  [73]  in order to determine the paleostress field orientation using the right dihedral inversion method  [74]. Field observations also allowed us to determine relative 3 Geofluids chronology criteria in order to define the tectonic timeline in the Grands Causses area.