dataesr/scientific-paragraphs-categorization huggingface dataset:
Fieldwork We used a dataset of arthropod species distribution and abundance in Terceira Island previously published  [26]. A total of 72 sites were sampled between 2000 and 2007, between June and September, once per site: 36 in natural forests and 36 in nonnative habitats, the latter including 9 in exotic forests, 11 in seminatural pastures and 16 in intensively managed pastures. We tried to spread the sampling sites all over the island independently of the surrounding land use matrix, although intensively managed pastures tend to be located in peripheral low-altitude areas, while natural forests tend to be present only in central high-altitude areas. At each site, epigean soil fauna was captured along 150 m long transects. Thirty pitfall traps, consisting of plastic cups with a top diameter of 42 mm and 78 mm deep, were dug into the soil so that the rim of the cup was level with the surface.
Investigating relationship between species response and species attributes The TITAN analysis distinguishes two species groups: (1) species significantly associated with low disturbance (i. e. negative z2 response; significant IndVal scores ,0. 05, purity. 0. 95 and reliability. 0. 95), and (2) species significantly associated to high disturbance (i. e. positive z+ response; significant IndVal scores ,0. 05, purity. 0. 95 and reliability. 0. 95). We therefore used TITAN results to test for potential association between species attributes and species response to disturbance. We considered four main characteristics: biogeographic categories (endemics, natives non-endemics and exotics), taxonomic order, feeding guild (predator, herbivore, fungivore and saprophagous) and body size. Since our data were greatly unbalanced (i.
Statistical analysis software All the analyses were performed using R  [40]. Particularly, we used the R code provided by Baker & King  [18]  to implement TITAN in R 2. 13. 0. Abundance data were transformed (log 10 (x+1)) to reduce the influence of highly abundant species on IndVal scores  [18]. Following the recommendations of Baker & King  [18] , taxa occurring in less than 3 sites across the gradient were deleted to remove outliers representing a potential bias. In our study, we also use a minimum group size of five observations to compute IndVal for TITAN analyses. We reran TITAN across 500 bootstrap replicates to compute purity and reliability of individual threshold indicator taxa and uncertainty surrounding thresholds based on the distribution of maximum TITAN sum(z2) (individual taxa) and TITAN sum (z+) values.
Data used in this manuscript were obtained in the projects funded by  Direcca ˜o Regional dos Recursos Florestais  (Project:  17. 01-080203 ,  1999-2004 ) and  Direcca ˜o Regional da Ciencia e Tecnologia (Project: ''Consequences of land-use change on Azorean fauna and flora -the 2010 Target '',  M. 2. 1. 2/I/003/2008 ). Grants and fellowships to the authors were provided by  Fundaca ˜o Ciencia e Tecnologia  ( SFRH/BPD/40688/2007  and  PTDC/BIA-BEC/100182/2008  for PC and FR, respectively) and  Azorean Biodiversity Group (CITA-A)  (Summer 2010, 2011 and 2012 grants to SF). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
A specimen was considered positive if the signal curve crossed the threshold line within 40 cycles. The assay limit of detection for pandemic H1N1pdm09 influenza virus is of order of magnitude of 10 copies/μL of initial sample  [9]. The assay limit of detection for influenza A and B viruses, HRSV, human metapneumovirus and PIV-3 is of order of magnitude of 10 copies/μL  [10]. For PIV-4, the assay limit of detection is of order of magnitude of 100 copies copies/μL, and for PIV-1 and -2, 1000 copies/μL  [10]. After amplification, the PCR products were purified and sent to GATC Biotech (Konstanz, Germany) for sequencing. Student's t test and the Pearson chi-squared test were used to assess intergroup differences. Statistical analyses were performed with EpiInfo software (V 3. 5. 1 CDC). A test was considered significant when the p value was < 0.
A 253-bp fragment of the haemagglutinin gene of the five H1N1pdm09 strains [accession numbers: CY092425, CY092426, CY092427, CY092428, CY092429] showed high sequence similarity (99-100%) to influenza A/California/04/2009 (H1N1) (data not shown). The 23 specimens positive for influenza B represented 82. 1% of the influenza viruses detected. Ten of the patients were hospitalized; one infant aged 9 months died 2 days after admission to intensive care with a clinical picture of severe acute respiratory illness. Influenza B virus was implicated in respiratory infections throughout the year, with two peaks: a first (11 positive samples) at the beginning of the rainy season and a second (8 positive samples) in November at the end of the rainy season (Figure  2B ). Partial genome analysis of nine amplified samples of influenza B virus [accession numbers: HE803088, HE803089, HE803090, HE803091, HE803092, HE803093, HE803094, HE803095] demonstrated high nucleotide similarity (98%) to vaccine strain B/Victoria/02/1987, except for one that belonged to the Yamagata lineage (data not shown).
HRSV was detected in 10 patients (Table  1 ) with a median age of 28 months, mainly in November (Figure  2B ). One infant aged 10 months died 1 day after admission to intensive care with a clinical picture of fever, cough, rhinitis, bronchiolitis, dyspnoea and myalgia. Fever and rhinitis were recorded in 9 of the 10 patients, and all had cough. No viral co-infections were reported. Analysis of the nucleotide sequences of six isolates [accession numbers: HE803082, HE803083, HE803084, HE803085, HE803086, HE803087] showed sequence similarity to both genotypes A and B. PIV-3 was detected in seven patients (median age, 16 months; range, 5-48 months) and PIV-1 in four infants (median age, 11 months; range, 3-24 months) between April and November 2010 (Figure  2B ). Respiratory viruses were found in 14.
Acknowledgements We would like to thank  Dr Edgar Dimbele ,  Dr Franco Banawane  and  Dr Léandre Mballa Dimbala  for assistance in sample collection. This work was supported by the  French Ministry of Health  and the Office of the Assistant Secretary for Preparedness and Response within the  US Department of Health and Human Services  (grant number  6 IDESP060001-01-01 ) through the  International Network of Pasteur Institutes. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Statistical analysis The 48 patient's database is composed of variables which are most often continuous quantitative. Some were analyzed in their initial measures while others were treated after discretization in binomial variables. Due to the number of subjects and the distribution of measures carried out, nonparametric or permutation tests were performed. Associations between nominal variables were tested by chi-square test or Fisher exact test. Comparisons of quantitative measures between groups were realized by Mann-Withney U or Kruskall-Wallis test and correlations were established by the Spearman's rank test. P values > 0. 05 were considered not significant (NS).
This work was supported by a  PHRC grant  to  Dr. Jaffar-Bandjee  and an  ANR  grant to Pr. B. Autran. Laboratory funding was also granted through the  ICRES/FP7 program  (Integrated Chikungunya Research). PG is an INSERM fellow of U945 unit (Pr. B Autran). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Of the group of 75 randomly selected isolates, 20 were obtained from diabetic patients. Detection of β-lactamase genes and insertion sequences was performed as described previously  (Ellington et al. , 2007; Poirel & Nordmann, 2006; Woodford et al. , 2006). Antibiotic MICs were determined by the plate doubling dilution method according to British Society for Antimicrobial Chemotherapy (BSAC) guidelines  (Andrews, 2010). As no breakpoint for tigecycline exists for A. baumannii, the breakpoint for Enterobacteriacea was used. For statistical analyses, isolates showing an intermediate level of antibiotic resistance were grouped with resistant isolates. Analyses were performed in SPSS v. 20 (SPSS Inc, Chicago, IL, USA), and where appropriate were corrected for multiple testing  (Benjamini & Hochberg, 1995).
Results and Discussion The isolates included in the study came from a total of 37 hospitals and a wide range of samples including blood, respiratory, urine and wound. Of the 24 hospitals contributing more than one isolate, 9 contributed isolates from both diabetic and non-diabetic patients. Analyses were first performed on the data by dividing it into the isolates selected because they were carbapenem resistant, and those selected randomly (Table  1 ). Combining the datasets for analysis was not possible as the method of isolate selection would bias the results. Determination of antibiotic MICs confirmed that carbapenem resistance was found in almost all isolates selected for this trait, with only 6 of the 196 isolates (3%) having lost resistance to both imipenem and meropenem during storage.
Carbapenem resistance was also prevalent in the randomly selected isolates, with a patient being more likely to carry a carbapenemresistant isolate than not (chi squared test, χ 2 = 7. 053, d. f. = 1, p = 0. 008). A high proportion of isolates (99%) carried genes for at least one acquired carbapenem-hydrolysing βlactamase, with bla VIM sequences particularly prevalent. Of the 32 carbapenem-susceptible isolates, 29 (91%) were positive for a bla VIM gene. The data were then analysed with respect to the disease status of the patient. Overall there is a significantly higher proportion of diabetic patients in the carbapenem-resistant isolate group than in the randomly selected isolate group (44% and 28% respectively, chi squared test, χ 2 = 5. 787, d. f. = 1, p = 0. 016). The data were then sub-divided into those isolates that were obtained from patients with diabetes, and those obtained from non-diabetics.
Acknowledgements The authors would like to thank  King Abdulaziz City for Science and Technology (KACST)  for funding, and to thank  King Faisal University  and the  Vice President for Graduate Studies and Scientific Research  for their support. In addition,  Hani Alrasasi ,  Hani Alfarhan ,  Hajer Alduhilan ,  Nof Alhumaini ,  Fatemah Alnajar ,  Abdulrazaq Alwebari ,  Abdulkadir Abuli , and Mohammed Alburake are thanked for their technical assistance. We would like to thank two anonymous reviewers for their useful comments which helped clarify the manuscript.
at the CERN Large Hadron Collider. Data are analyzed in the lepton+jets final state, characterized by a high-transverse-momentum isolated electron or muon, large missing transverse momentum and at least three jets. The analysis strategy relies on the substantial boost of the W bosons in the t ′ t′ signal when m t ′ 400 GeV. No significant excess of events above the Standard Model expectation is observed and the result of the search is interpreted in the context of fourth-generation and vector-like quark models. Under the assumption of a branching ratio BR(t ′ → W b) = 1, a fourth-generation t ′ quark with mass lower than 656 GeV is excluded at 95% confidence level. In addition, in light of the recent discovery of a new boson of mass ∼ 126 GeV at the LHC, upper limits are derived in the two-dimensional plane of BR(t ′ → W b) versus BR(t ′ → Ht), where H is the Standard Model Higgs boson, for vector-like quarks of various masses.
Data sample and event preselection The data used in this analysis correspond to the full dataset recorded in 2011, and were acquired using single-electron and single-muon triggers. The corresponding integrated luminosity is 4. 7 fb -1. The event preselection criteria closely follow those used in recent ATLAS top quark studies  [23]  and require exactly one isolated electron or muon with large transverse momentum (p T ), at least three jets among which at least one is identified as originating from a b quark, and large missing transverse momentum (E miss T ). Electron candidates are required to have transverse momentum p T > 25 GeV and |η| < 2. 47, excluding the transition region (1. 37 < |η| < 1. 52) between the barrel and endcap EM calorimeters. Muon candidates are required to satisfy p T > 20 GeV and |η| < 2.
Acknowledgements We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia; ARC, Australia; BMWF and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN; CONICYT, Chile; CAS,  MOST  and  NSFC , China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF,  DNSRC  and  Lundbeck Foundation , Denmark; EPLANET and  ERC ,  European Union ;  IN2P3-CNRS ,  CEA-DSM/IRFU , France; GNSF, Georgia; BMBF,  DFG ,  HGF ,  MPG  and  AvH Foundation , Germany; GSRT, Greece; ISF, MINERVA, GIF, DIP and Benoziyo Center, Israel; INFN, Italy;  MEXT  and  JSPS, Japan ; CNRST, Morocco; FOM and  NWO, Netherlands ;  BRF  and  RCN, Norway ;  MNiSW , Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MVZT, Slovenia; DST/NRF, South Africa; MICINN, Spain;  SRC and Wallenberg Foundation, Sweden ;  SER ,  SNSF  and  Cantons of Bern and Geneva, Switzerland ;  NSC, Taiwan ;  TAEK, Turkey ;  STFC , the  Royal Society and Leverhulme Trust ,  United Kingdom ;  DOE  and  NSF ,  United States of America.
4, 150 mM NaCl, 3. 4 mM EDTA, 0. 0005% surfactant P20). In all Biacore experiments, HBS-EPϩ buffer (Biacore GE Healthcare) served as running buffer and sensorgrams were analyzed with Biacore T100 evaluation software. CD146and Ligand Fc proteins were immobilized covalently to carboxyl groups in the dextran layer on a Sensor Chip CM5. The sensor chip surface was activated with EDC/NHS (N-ethyl-NЈ-3-dimethylaminopropyl) carbodiimidehydrochloride and N-hydroxysuccinimide (Biacore GE Healthcare). Proteins were diluted at 10 g/ml in coupling buffer (10 mM acetate, pH 5. 2) and injected until the appropriate immobilization level was reached (i. e. 600 to 800 Resonance Units RU). Deactivation of the remaining activated groups was performed using 100 mM ethanolamine pH 8 (Biacore GE Healthcare). Then, a solution of Galectin-1 (1.
Transfection efficiency was assessed by monitoring CD146 expression by flow cytometry analysis using S-Endo1 anti-CD146 mAb or isotype-matched control mAb (Biocytex, 5050) and by Western blot as previously described. Briefly, for Western blot analysis, cells were washed in PBS, submitted to trypsin action, and extracted with 500 l of icecold RIPA buffer (150 mM NaCl, 50 mM Tris HCl, pH 7. 4, 2. 4 mM EDTA, 1% Nonidet P-40, 0. 5 mM phenylmethylsulfonyl fluoride) for 30 min at 4 °C. After centrifugation (12,000 ϫ g, 10 min, 4 °C) to eliminate cell debris and nuclei, protein extracts were submitted to 7. 5% NuPage SDS-polyacrylamide gel electrophoresis (Invitrogen) and transferred onto nitrocellulose membrane (Invitrogen). Statistical Analysis-Data are expressed as mean Ϯ S. E. M. Student tests and Mann Whitney tests for independent samples were used.
The endothelial apoptosis, induced by Galectin-1 (20 g/ml) for 24 h, is evaluated by the percentage of Annexin-V/7AADpositive endothelial cells in comparison with basal conditions, without Galectin-1 (fold/cont) (right panel). E, endothelial cell apoptosis was evaluated by 7AAD/Annexin-V staining in HUVEC. Endothelial cells were treated with Galectin-1 (20 g/ml) alone or after previous exposure to anti-CD146 antibody (S-Endo1 clone, 5 g/ml). Exposure to anti-CD146 alone serves as a negative control. In A, B, D, and E panels, data are shown compared with control that corresponds to basal conditions without Galectin-1 stimulation.
E, endothelial cell apoptosis was evaluated by 7AAD/Annexin-V staining in HUVEC. Endothelial cells were treated with Galectin-1 (20 g/ml) alone or after previous exposure to anti-CD146 antibody (S-Endo1 clone, 5 g/ml). Exposure to anti-CD146 alone serves as a negative control. In A, B, D, and E panels, data are shown compared with control that corresponds to basal conditions without Galectin-1 stimulation.
Skin complexion is a critical modifier for the effect of UV radiation exposure on NMSC. We included skin complexion (i. e. , light vs. medium/dark) evaluated in multivariable regression models by the inclusion of two-way interaction terms between skin complexion and UV exposure. Effect modification by skin cancer histology and anatomical location was also considered by stratified analyses. To account for the reported latency  [25]  between UV radiation exposure at work and the development of skin cancer, association estimates for NMSC were also calculated for 20-, 25-and 30-year lag periods. In these analyses, the lag periods prior to study participation were considered to be unexposed. All analyses were conducted using SAS 9. 2 statistical software (SAS Institute, Cary, NC, USA). Statistical significance was defined as p,0.
The rest of this letter is organized as follows. In the next section, we present our analysis of invisible Higgs production at the LHC. We estimate the sensitivity to the invisible Higgs rate of the CMS monojet search using 4. 7 fb -1 of data at √ s = 7 TeV  [13]. We also study the constraints from the recent ATLAS monojet search using 10 fb -1 of data at √ s = 8 TeV [14]. In the following section we discuss the interplay of the monojet constraints on the invisible Higgs decays and the indirect constraints from the global analysis of the LHC Higgs data. We show that a portion of the theory space with a large Higgs invisible branching fraction favored by global fits is excluded by the monojet constraints. We then move on to discuss the implications for Higgs portal dark matter models and the complementarity between dark matter direct detection at the LHC and in XENON.
Acknowledgements: The authors would like to thank  J. Baglio ,  E. Bagnaschi ,  E. Bragina ,  C. Grojean ,  P. Boucaud , and  T. Volansky  as well as the Magic Monday Journal Club for discussions. This work was supported by the  French ANR TAPDMS   ANR-09-JCJC-0146  and the  Spanish MICINNs  Consolider- Ingenio 2010 Programme  under grant  Multi-Dark   CSD2009-00064. A. D. thanks the  CERN TH  unit for hospitality and support.
The particle level refers to particles as they emerge from the proton-proton interaction. The detector level corresponds to tracks as measured after interaction with the detector material, and includes the detector response. The results are corrected for detector effects, using simulation, to obtain distributions of the event shape variables defined at particle level which can be directly compared to MC models. This paper is organized as follows: Section II defines the event shape variables; the detector is described in Section III; Section IV discusses the MC models used in this analysis; Section V and VI respectively describe the event selections and background contributions. The correction of the data back to particle level, and estimation of the systematic uncertainties are described in Section VII and VIII; the results are discussed in Section IX and finally the conclusions are presented in Section X.
The pythia 8 generator uses a multi-parton interaction (MPI) model interleaved with both initial-state and finalstate (ISR and FSR) radiation, and all three processes compete against each other for emission phase space in the resulting evolution. The Herwig ++ UE7-2 tune employs color reconnection. Different settings of model parameters, tuned to reproduce the existing experimental data were used for the MC generators. Table  I  shows the different MC models used in this paper. The reference model for this analysis is chosen to be pythia 6 AMBT1. Samples generated with this tune were passed through the ATLAS detector and trigger simulations  [44]  based on GEANT4  [45]  and then reconstructed and analyzed using the same procedure and software that are used for the data. Reconstructed MC events are then used to correct the data for detector effects.
V. EVENT AND TRACK SELECTION The data used for the analysis presented here were collected in April 2010 with a minimal prescale factor for the minimum-bias trigger. The only further requirement for selecting the data sample is that the MBTS trigger and all inner detector subsystems were at nominal operating conditions. In each event the reconstructed vertices are ordered by the p 2 T over the tracks assigned to each vertex, and the vertex with the highest p 2 T is taken as the primary interaction vertex of the event. To reduce the contribution from beam-related backgrounds and decays of long-lived particles, and to minimize the systematic uncertainties, events are rejected if they contain any other vertex reconstructed with four or more tracks. If there is only one vertex in the event, or if any additional vertex in the event has three or fewer tracks, all tracks from the event that pass the track selection (described below) are retained.
A. Event-level correction Trigger and vertexing efficiencies are taken from a previous analysis using the same data sample  [19]. The efficiency of the MBTS trigger is determined from data using a control trigger and found to be fully efficient for the analysis requirement of at least six tracks. The vertex reconstruction efficiency is also measured in data by taking the ratio of the number of triggered events with a reconstructed vertex to the total number of triggered events. This ratio is also found to be very close to unity. The total correction applied to account for events lost due to the trigger and vertex requirements is less than 1% and it varies very weakly with the number of tracks associated with the primary vertex.
5 < p lead T < 5 GeV, before decreasing. A similar trend is observed by the ALICE Collaboration, which has measured the transverse sphericity distribution selecting charged particles with |η| < 0. 8, in inelastic 7 TeV pp collisions  [8]. Overall, the pythia 6 tune Z1, tuned to the underlying event distributions at the LHC, agrees the best with most of the distributions. The pythia 6 DW tune predictions are consistently furthest from the data, as seen in the τ ch ⊥ and T ch M distributions. This is not unexpected as DW is tuned to reproduce the Tevatron data and does not agree with the charged particle multiplicity and p T distributions in LHC data  [19]. However it performs similarly to other models/tunes for the S ch ⊥ distribution in intermediate to high p lead T values, as is seen in Fig.
5 (c)-Fig. 5(e ). The AMBT2B tune, which is based on minimum-bias LHC data, shows better agreement for the lowest p lead T distributions than for the intermediate p lead T distributions, as is seen in Fig. 3 (a) and in Fig. 4(a). Compared to the pythia 6 AMBT2B tune, the predictions of the pythia 8 A2 and Herwig ++ UE7-2 tunes show better agreement with the data in the intermediate to high p lead T ranges. The UE7-2 tune, based like Z1 on LHC underlying event data, is expected to perform better in events characterized by a hard scatter, resulting in higher p lead T values. However, the minimum-bias A2 tune shows a similar or slightly better level of agreement with data for the high p lead T distributions, possibly indicating that the improved MPI modeling compared to pythia 6 tunes does play a role.