dataesr/scientific-paragraphs-categorization huggingface dataset:
We ran partitioning of variance for the set of samples on the global scale and individually for each climate zone. For biofilms, the analysis was done for samples of the temperate zone only because of the limited number of samples from other climate zones. All statistical analyses were performed in r 3. 2. 2 (R Core Team, 2017), except for the PLS analysis which was conducted using xlstat software (XLSTAT, 2017, Addinsoft, Germany).
ACK N OWLED G EM ENTS This work was carried out within the  SMART Joint Doctorate Programme "Science for the MAnagement of Rivers  and their Tidal systems" funded by the  Erasmus Mundus Joint Doctorate Programme of the European Union  (http://www. riverscience. it). O. S. was also supported by a grant for a short-term scientific mission to the  University of the Basque Country, Spain , within the  COST Action CA15113 (SMIRES, Science and Management of Intermittent Rivers and Ephemeral Streams , www. smires. eu). O. S. is thankful for a partial support from IGB equal opportunity fund for young female scientists and  DFG  ( SU 405/10-1 ). F. A. was supported by the  Swiss National Science Foundation  grants no  PP00P3_179089  and  PP00P3_150698  and the  URPP Global Change and Biodiversity, University of Zurich.
The crystalline phases present in the catalysts were analyzed by XRD at ambient temperature on Bruker D8 Advance instrument, equipped with a CuKα source (λ = 0. 154 nm). The samples were scanned at a rate of 0. 02 • over the 5 • ≤ 2θ ≤ 90 • range with an integration time of 0. 5 s. The diffractograms were indexed using the JCPDS database. The oxidation state of platinum and its quantification on the surface of catalysts were determined by XPS analysis (AXIS Ultra Kratos) using a monochromatized aluminum source (AlKα = 1486. 6 eV, 150 W), and the value of the C1s core level (285 eV) was used for the calibration of the energy scale. Curve fitting was performed using the Casa XPS software applying a Shirley-type background subtraction. To determine the size of the platinum particles, transmission electron microscopy analysis was used.
ACKNOWLEDGMENTS The  Fonds Européen de Développement Régional (FEDER) ,  CNRS ,  Région Nord Pas-de-Calais and Ministère de l'Education Nationale de l'Enseignement Supérieur et de la Recherche  are acknowledged for fundings of XPS/LEIS/ToF-SIMS spectrometers within the  Pôle Régional d'Analyses de Surface. This work was performed in partnership with the SAS PIVERT, within the frame of the  French Institute for the Energy Transition (Institut pour la Transition Energétique (ITE) P. I. V. E. R. T. (www. institut-pivert. com)selected as an  Investment for the Future (Investissements d'Avenir).
Image Segmentation Image processing was performed by 2 trained technicians using the MUSIC platform (Liryc, Université de Bordeaux, Bordeaux & INRIA, Sophia Antipolis, France), as described previously  [8] [9] [10] [11]. Briefly, the cardiac chambers, ventricular epicardium, ascending aorta, and coronary sinus (CS) were segmented semi-automatically  9  , and ventricular endocardium automatically. WT was automatically computed from endoand epicardial contours. We used 5-mm as a cutoff for significant myocardial thinning based on previously reported MDCT values of WT in a healthy population  11. A 3-dimensional patient-specific model comprising all anatomical information was generated and exported in Matlab (The Mathworks, Inc. , Nattick, MA) for subsequent post-hoc integration with electroanatomical geometries.
Post-hoc analysis The 3D-EAM was merged on the MDCT geometries on the Rhythmia TM system (Boston Scientific, Marlborough, MA) using identifiable anatomic reference points (Superior vena cava, inferior vena cava, left atrium, CS, aortic root, LV apex, and mitral annulus (MA) [3, 6, 9, and 12 o'clock]) to align both surfaces (Figure  1 ). The analyses were then performed using custom-built software in Matlab (The Mathworks, Inc. , Nattick, MA). On MDCT data, a CT-channel was defined according to the following 3 criteria, as shown in Figure  2. 1. Abnormal thickness (<5 mm) 2. Thickness on both edges thinner than that inside the channel.
Baseline data and follow-up For the present study, medical records and meeting reports were analysed retrospectively. Uncontrolled hypertension was defined as a systolic and/or a diastolic measurement above 140 or 90mmHg, respectively. Resistant hypertension was defined as uncontrolled hypertension despite three antihypertensive medications belonging to three different drug classes. Estimated glomerular filtration rate (eGFR) was calculated based on the Chronic Kidney Disease-Epidemiology Collaboration (CKD-epi) formula. Worsening of renal function was defined as a decrease in eGFR �20% as compared to its baseline value. For patients with a bilateral disease, the radiological parameters related to the side with the highest peak systolic velocity were recorded. For each patient, the decision taken during the multidisciplinary meeting (medical treatment or revacularization) was collected and compared to the one guided by international guidelines, that is to the one that would have been taken if the 2011 ESC  [9] , 2013 AHA  [10]  and 2017 ESC  [12]  Guidelines had been followed.
Three situations were considered: 1/ revascularization was recommended (guideline class I to IIa), 2/ revascularization could be considered (guideline class IIb), and 3/ revascularization was not recommended or suggested. Patients with a clinical situation corresponding to a Class I, IIa or IIb recommendation were considered as eligible to be revascularized. The guidelines were considered as not followed when a revascularization was either performed but not recommended, or not performed but recommended with a I or IIa class guideline. After a one year follow-up, the following data were collected: systolic and diastolic blood pressure, number of concomitant anti-hypertensive drug classes, eGFR and/or initiation of a dialysis treatment, proteinuria, survival status, grade 3 complications related to the procedure, and procedure failures.
The detector is nearly hermetic, permitting accurate measurements of H miss T. The CMS trigger is described in Ref. [39]. For this analysis, signal event candidates were recorded by requiring H miss T at the trigger level to exceed a threshold that varied between 100 and 120 GeV, depending on the LHC instantaneous luminosity. The efficiency of this trigger is measured in data and is found to exceed 97% for events satisfying the event selection criteria described below. Additional triggers requiring the presence of charged leptons, photons, or minimum values of H T are used to select control samples for the evaluation of backgrounds, as described below.
2. 2 at next-toleading order (NLO)  [57] , except that WW events in which both W bosons decay leptonically are generated using the POWHEG v2. 0  [58] [59] [60] [61] [62]  program at NLO. This same POWHEG generator is used to describe single top quark events produced through the t and tW channels. The detector response is modeled with the GEANT4  [63]  suite of programs. Normalization of the simulated background samples is performed using the most accurate cross section calculations available  [55, 61, 62, [64] [65] [66] [67] [68] [69] [70] [71] [72] , which generally correspond to NLO or next-to-NLO (NNLO) precision. Samples of simulated signal events are generated at LO using MADGRAPH5 aMC@NLO 2. 2. 2, with up to two additional partons included in the matrix element calculations. The production cross sections are determined with approximate NNLO plus next-to-next-to-leading logarithmic (NNLL) accuracy  [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84].
Events with gluino (squark) pair production are generated for a range of gluino m g (squark m q ) and LSP m χ 0 1 mass values, with m χ 0 1 < m g (m χ 0 1 < m q ). The ranges of mass considered vary according to the model, but are generally from around 600-2500 GeV for m g , 200-1700 GeV for m q , and 0-1500 GeV for m χ 0 1 (see  Section 9). For the T5qqqqVV model, the masses of the intermediate χ 0 2 and χ ± 1 are given by the mean of m χ 0 1 and m g , as was already stated in the introduction. The gluinos and squarks decay according to the phase space model  [85]. To render the computational requirements manageable, the detector response is described using the CMS fast simulation program  [86, 87] , which yields results that are generally consistent with the GEANT4-based simulation. To improve the consistency of the fast simulation description with respect to that based on GEANT4, we apply a correction of 1% to account for differences in the efficiency of the jet quality requirements  [48, 49] , corrections of 5-12% to account for differences in the b jet tagging efficiency, and corrections of 0-14% to account for differences in the modeling of H T and H miss T.
The purity is determined as a function of H miss T and typically exceeds 90%. In the generation of simulated γ+jets events, photons that are approximately collinear with a parton (∆R < 0. 4) are removed to improve the fraction of events with well-isolated photons and thus the statistical precision of the sample. A correction denoted F dir is evaluated to account for a bias from this requirement, using simulated events with a looser restriction on the angular separation between the generator-level photons and partons. The corrections are typically less than 10%. A systematic uncertainty in the correction given by 0. 30(1 -F dir ) is determined by evaluating the level of agreement between simulation and data in the distribution of the angular separation between a photon and the nearest jet, and the effect of changing the definition of collinear photons in the simulation.
Summary Using essentially the full CMS Run 2 data sample of proton-proton collisions at √ s = 13 TeV, corresponding to an integrated luminosity of 137 fb -1 collected in 2016-2018, a search for supersymmetry has been performed based on events containing multiple jets and large missing transverse momentum. The event yields are measured in 174 nonoverlapping search bins defined in a four-dimensional space of missing transverse momentum (H miss T ), the scalar sum of jet transverse momenta (H T ), the number of jets, and the number of tagged bottom quark jets. The events are required to satisfy H miss T > 300 GeV, H T > 300 GeV, and to have at least two jets with transverse momentum p T > 30 GeV. Events with isolated high p T leptons or photons are vetoed. The results are compared to the expected number of background events from standard model (SM) processes.
The principal backgrounds arise from events with neutrino production or jet mismeasurement. The SM background is evaluated using control regions in data supple-. The thick solid (black) curves show the observed exclusion limits assuming the approximate-NNLO+NNLL cross sections  [73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84]. The thin solid (black) curves show the changes in these limits as the signal cross sections are varied by their theoretical uncertainties  [102]. The thick dashed (red) curves present the expected limits under the background-only hypothesis, while the two sets of thin dotted (red) curves indicate the region containing 68 and 95% of the distribution of limits expected under this hypothesis.
Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies:  BMBWF  and  FWF (Austria) ;  FNRS  and  FWO (Belgium) ;  CNPq ,  CAPES ,  FAPERJ ,  FAPERGS , and  FAPESP (Brazil) ;  MES (Bulgaria) ;  CERN ;  CAS, MoST , and  NSFC (China) ;  COLCIENCIAS (Colombia) ;  MSES  and  CSF (Croatia) ;  RPF (Cyprus) ;  SENESCYT (Ecuador) ;  MoER ,  ERC IUT ,  PUT  and  ERDF (Estonia) ;  Academy of Finland ,  MEC , and  HIP (Finland) ;  CEA  and  CNRS/IN2P3  (France);  BMBF ,  DFG , and  HGF (Germany) ;  GSRT (Greece) ;  NKFIA (Hungary) ;  DAE  and  DST (India) ;  IPM (Iran) ;  SFI (Ireland) ;  INFN (Italy) ;  MSIP  and  NRF (Republic of Korea) ;  MES (Latvia) ;  LAS (Lithuania) ;  MOE  and  UM (Malaysia) ;  BUAP ,  CINVESTAV ,  CONACYT ,  LNS ,  SEP , and  UASLP-FAI (Mexico) ;  MOS (Montenegro) ;  MBIE (New Zealand );  PAEC (Pakistan) ;  MSHE  and  NSC (Poland) ;  FCT (Portugal) ;  JINR (Dubna) ;  MON, RosAtom ,  RAS ,  RFBR , and  NRC KI (Russia) ;  MESTD (Serbia) ;  SEIDI, CPAN, PCTI , and  FEDER (Spain) ;  MOSTR (Sri Lanka) ;  Swiss Funding Agencies (Switzerland) ;  MST (Taipei) ; ThEPCenter, IPST, STAR, and  NSTDA (Thailand) ;  TUBITAK  and  TAEK (Turkey) ;  NASU  and  SFFR (Ukraine) ;  STFC  ( United Kingdom );  DOE  and  NSF (USA).
| Numerical tools The numerical simulations are performed with the computational fluid dynamics (CFD) code Fire Dynamics Simulator (FDS) version 6. 7. 0. FDS is a computational code in fluid dynamics that incorporates a combustion model and a large-scale model (LES) for the description of turbulent flows. This tool allows 3D modelling of the computational domain. It considers heat transfer at walls, ventilation conditions for the removal of hot gases and air intake. The Navier-Stokes equations are solved in the limit of low Mach number, thermally driven flow with an emphasis on smoke and heat transport from fires. The radiative heat transfer is included in the model through the solution of the radiative transport equation for a grey gas. Detailed information is provided in previous work. 23 e default submodels of FDS were used for the gas phase radiation exchanges even if a sensibility analysis performed with 100 (default value), 500, and 800 solid angles was addressed.
056 g/g. 27 The char yield is close to 0%,  27, 30  and the asymptotic mass loss rate is 0. 04 kg/m 2 /s. 27, 30, 35  previous works,  27, 36   The thermal properties for aluminium are extracted from Eurocode 9. 36, 38  Namely, a density of 2700 kg/m 3 is used in this study. The emissivity of aluminium ranges between 0. 3 and 0. 7. 36 In order to be conservative, a value of 0. 7 was chosen. The cavity barriers include an intumescent coating. Their thermal properties are extracted from laboratory databases and supplier datasheet. It has a density of 360 kg/m 3 and a specific heat of 1. 0 J/ g/K. The emissivity of the cavity barrier is taken at 1. The thermal properties of the calcium silicate supports are extracted from laboratory database and supplier datasheet. It has a density of 285 kg/m 3 and a specific heat of 1.
Demographic characteristics A summary of the study population's characteristics is presented in Table  1  and Table  S2  (participants with and without metastases). Both datasets reflected the homogeneity of the groups. The median age of participants ranged from 58 to 67 years. A majority of women had undergone menopause (71-85%). The most frequent histological subtype in both groups was infiltrating ductal carcinoma. There was no difference in the expression of ER, PR and HER2. As expected, the number of lymph nodes, the frequency of larger tumors and the Ki-67 proliferation index > 20%, were higher among patients with metastatic cancer. For several participants, the volume of serum or the amount of adipose tissue was insufficient to complete the chemical analyses and vice versa. Therefore, the serum dataset contained the results derived from 40 participants with metastatic cancer and 47 with non-metastatic cancer, different than the 38 participants with metastatic cancer and 53 with non-metastatic cancer recorded in the AT dataset.
Acknowledgments This work was supported by  PNRPE  ( METAPOP  project,  n°11-MRES-PNRPE-5-CVS-031 Chorus n°2100532530 );  INSERM  ( Institut National de la Santé et de la Recherche Médicale );  Université Paris Descartes ;  Assistance Publique -Hôpitaux de Paris  ( AP/HP ); we thank  Dr. Lawrence Aggerbeck  for his critical reading of our manuscript.
Patient Inclusion and Data Collection Consecutive patients older than 17 years with a histopathologic diagnosis of supratentorial glioblastoma and first-time brain surgery in 2012 or 2013 were included from two brain tumor treatment centers: the Vrije Universiteit Medical Center in Amsterdam and the University Medical Center in Utrecht, the Netherlands. Patients underwent either resection with glioblastoma removal or biopsy for diagnosis. We defined tumor removal for histopathologic diagnosis only by an open or stereotactic approach as biopsy and more contrast-enhanced tumor removal than necessary for a histopathologic diagnosis by craniotomy as resection. The histopathologic diagnosis was based on WHO 2007 criteria. Written informed consent was obtained from all patients. The two multidisciplinary neuro-oncologic teams had a similar approach to decision making in tumor board meetings on surgical indications for new patients by consensus of neurosurgeons based on patient and tumor characteristics.
Intraoperative decision making was performed by neurosurgical teams under the supervision of a neuro-oncologic surgeon from a pool of two or three per center, respectively. Image guidance with neuronavigation was routinely applied. Functional MRI, DTI tractography, and intraoperative stimulation mapping for language and motor functions were used by indication. The Utrecht team had started using fluorescence-guided microscopy in 2013; the Amsterdam team had not. Baseline characteristics of these patients were extracted from digital department databases, as well as from pre-and postoperative MRI. MRI acquisition protocols were comparable between the two teams (Data Supplement). A complication was defined as a new intervention or intensive care admission. A functional decline was defined as a drop in Karnofsky performance score of.
Brain Map Construction The construction of brain maps is described in detail in the Data Supplement. Briefly, the enhancing portions of tumors were segmented on pre-and postoperative T1-weighted gadolinium-enhanced images. For patients who underwent biopsy, postoperative MRI was usually omitted, and we therefore considered the residual tumor to be identical to the preoperative tumor. Next, tumor volumes were nonlinearly registered to the Montreal Neurological Institute (MNI) 152 1-mm brain template to compare tumor locations between patients and teams. Three types of probability maps were constructed by voxelwise aggregations of the registered tumor volumes, each.
The material originates from the literature  (Wahl et al. , 2010)  and the reported study design was previously used in a four-country comparison  (Kogler et al. , 2013). The same design was later applied in three other countries  (Carvalho Wilks, & Pacheco 2014; Kaplanoglou & Rapanos, 2015; Lemoine & Roland-Lévy, 2013). The data from these seven countries were incorporated in this extension to reach a total of 44 countries. The following OSF repository contains the data file and supplementary materials: https://osf. io/2zqnp/.
Each videotaped interview was watched and listened to by 50% of the sample of judges. All participants of both samples were recruited among students and experimenters' acquaintances. There was neither kinship, nor friendship, nor familiarity between the two samples: Each judge was unknown to each interviewee, and vice versa. Data were collected anonymously, and participants were preliminarily presented with an informed consent form. The Ethical Committee of the Department of Education, Psychology, Communication, University of Bari approved the study.
Higher values indicate a greater probability of positive category (1 = truth-teller). Diagnostic accuracy is measured by the Area Under the Curve (AUC), which takes values from 1 (perfectly accurate discrimination) to 0 (perfectly inaccurate discrimination). In general, an AUC of 0. 5 suggests no discrimination, from 0. 7 to 0. 8 is considered acceptable, from 0. 8 to 0. 9 is considered excellent, and more than 0. 9 is considered outstanding  (54). The ROC analysis ran on the present data yielded an AUC of 0. 61, indicating a little above typical power to discriminate truthful from deceitful videotaped interviews.
Multilevel Analyses The following analyses were run to control for the judges' individual variability in accuracy, confidence, and experiential criteria for lie/truth detection. To this end, we tested a random intercept model with the package lme4 (55) for multilevel analysis through R (  56 ). This analysis was separately applied to the indices of Detection Accuracy and Detection Confidence, and to the proportion of occurrence of the four categories of criteria for each interview shown to each judge (Emotional features, Expressive indices, Cognitive complexity, and Paraverbal aspects). Only for the Detection Accuracy index, given the dichotomous nature of the dependent variable (0 = "error"; 1 = "correct"), the estimated model was a logistic regression. As a general procedure, we first estimated a model with fixed factors only and we included the Interview condition (Liar vs.
75. The fit of our models was estimated by applying the car R package to obtain the Wald test statistics  (59). The AIC and BIC indices were computed to enable a comparison between the model with only fixed effects (Interview condition and gender congruence) with the model with both fixed and random effects (judges' ID). As Table  5  shows, the only significant fixed effect was found for the Interview condition on the measure of Detection Accuracy, in that truth-teller interviewees were more  For none of the dependent variables entered in the model the effect of gender congruence judge-interviewee was found to be significant. Furthermore, for none of our dependent variables, controlling for the judges' individual variability resulted in a significant improvement of the model [AIC and BIC were lower for the model with fixed effects only;  (60) ].
[22, 38]. To improve the current picture of the explosion course from nanosize to microsize, a database gathering explosion safety parameters for several metallic materials was build and enriched with additional measurements of explosion severity of nanopowders. In a second part, the available data were analysed in order to describe the course of explosion behaviour from nanosize to microsize. Finally, an attempt has been made to highlight the detailed physico-chemical parameters that drive the explosion severity mainly by analysing flame propagation models and reconsidering the classical 'Kst approach' that is known to suffer from intrinsic theoretical limitations  [39].
Selection and characterisation of nanodust metallic samples Most of the experiments performed with metal nanoparticles and detailed in the literature have been carried out on aluminium, zinc, titanium, iron, magnesium or, less frequently, on copper. Titanium, iron and magnesium are known to be prone to pre-ignition, even pyrophoricity, when handled in the form of very fine powders. In order to perform additional measurements while avoiding such perturbation, experimental efforts were focused on six different fractions of aluminium and one fraction of zinc. Former investigations  [6, 8, 36]  have shown that nano-aluminium powders can be tested well in apparatuses like 20 L-sphere without showing pre-ignition behaviour like titanium or iron samples, up to a certain concentration  [40]. Moreover, the database for micron scale aluminium is also very comprehensive.