dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements This work was primarily funded by  ESA/ESRIN (GHG-CCI ) but also received funding from  EU FP7  (grant agreement No. 283576 ,  MACC-II) ,  DLR (SADOS) , and the  State  and the  University of Bremen. We thank the members of the  GOSAT  Project (JAXA,  NIES , and  Ministry of the Environment (MoE), Japan ) for providing GOSAT Level 1B and Level 2 data products (GOSAT RA1  PI  project  CONSCIGO ). The ACOS v2. 9 data were produced by the  ACOS/OCO-2  project at the  Jet Propulsion Laboratory, California Institute of Technology , and obtained from the  ACOS/OCO -2 data archive maintained at the  NASA Goddard Earth Science Data and Information Services Center. We thank  NOAA  for making available the CarbonTracker CO 2 fields. We also thank TCCON and related funding organizations ( NASA  grants  NNX11AG01G ,  NAG5-12247 ,  NNG05-GD07G ,  NASA   Orbiting Carbon Observatory Program, DOE ARM program , the  Australian Research Council ,  DP0879468  and  LP0562346 , the  EU projects IMECC and GEOmon , the  Senate of Bremen ).
Identification of genes encoding active β-glucosidases in Y. lipolytica Analysis of the Y. lipolytica genome using BLAST revealed the presence of six sequences that were identified as putative family GH3 β-glucosidases (see Additional file 1: Table  S1 ; Additional file 2: Fig. S1 ) on the basis of high amino acid sequence identity with other yeast β-glucosidases (Fig. 2 , Additional file 2: Fig. S1 ). However, in the absence of biochemical data it was impossible to assert at this stage that these sequences actually encode β-glucosidases, since family GH3 contains glycoside hydrolases that display other specificities. Moreover, Y. lipolytica does not grow on cellobiose and has not been found to express a detectable level of β-glucosidase activity (Additional file 2: Fig. S2 ), despite the fact that preliminary transcriptional analysis revealed that the six genes are weakly transcribed when Y.
Acknowledgements The authors would like to express their gratitude to  Nelly Monties  for her help with chromatographic analyses. They thank the  ICEO facility  dedicated to enzyme screening and discovery and part of the  Integrated Screening Platform of Toulouse (PICT, IBiSA)  for providing access to its protein purification and analytical facilities. This work was funded by the  Agence Nationale de la Recherche  ( Investissements d' Avenir program ; reference  ANR-11-BTBR-0003 ). Dr. Guo  is a recipient of a postdoctoral fellowship from the  Institut National de la Recherche Agronomique.
Small-angle X-ray scattering experiments X-ray scattering data were collected immediately after elution from an SEC column at the Australian Synchrotron. GabR, DNA or GabR + DNA samples at 10 mg/ml were injected into a 23 ml sephacryl S-200 SEC column (GE Healthcare) at a flow rate of 0. 5 ml min -1. The outflow was piped directly into a temperature controlled 1. 5 mm quartz capillary at 20 • C through which monochromatic Xrays were passed at a flux of 4 × 10 12 photons per second. SAXS data was collected with exposure times of five seconds on a Pilatus 1M photon counting detector (Dectris, Baden Switzerland), which was set at a distance of 1. 48 m from the sample capillary. Data reduction was performed using a beamline specific software package known as scatterbrain (Australian Synchrotron, Clayton Australia, https://www.
synchrotron. org. au/aussyncbeamlines/saxswaxs/software-saxswaxs). Software for data processing were from the ATSAS suite of programs for SAXS data processing  (22)  including DATOP, PRIMUS, DATAVER, DAMMIN, DAMAVER, DATPOROD and CRYSOL. Custom software was written to generate plots of average intensity of binned wavelengthindependent scattering angles (Q) across all q-ranges. This was used to visualize the elution profile from SEC and select appropriate frames (20-50 frames) containing buffer only to subtract from scattering data. Averaged buffer scattering profiles were then subtracted from each acquisition frame using the program DATOP. The radius of gyration was then calculated using AUTORG for each buffer-subtracted frame and plotted over the average scattering at low q, which allowed the identification of frames consisting of monodispersed protein (Supplementary Figure  S2 ).
Subtracted data from monodispersed protein was then scaled and averaged Initial Gunier plots and probability atom distance distribution functions (P(r)) were plotted using the program PRIMUS. These data were used to generate P(r) plots, which were subsequently used to generate ab initio shape restorations using the program DAMMIN and. To allow a direct comparison all P(r) plots were scaled to have an area under the curve of 1. At least 20 ab initio dummy-atom shape restorations were performed for each dataset, which were aligned with the software DAMMIN.
Structural modeling Bent DNA models were generated using the webserver 3D DART (15) (http://haddock. science. uu. nl/dna/dna. php). Periodicities were specified at 10. 5 bp per turn and DNA was bent 'globally' over the DNA bases that bridge the AT-ACCA repeat sequence. This resulted in an even curvature across this bridging sequence. To compare different DNA models, these were structurally superimposed using the program Coot  (16). Electrostatic potentials were calculated using PDB2PQR  (17)  and the Adaptive Poisson Boltzmann Solver software package  (18). All structures and surfaces were rendered using The PyMOL Molecular Graphics System, (Schr ödinger, LLC).
This spontaneous dissociation of the wHTH domains would lead to a substantially different shape of the dimer in solution. To investigate this further, we determined the shape of the PLP-bound GabR dimer in solution by collecting SAXS data (Supplementary Figure  S3 ) directly from the elution of a SEC column (SEC-SAXS) to exclude the possibility of aggregates  (20, 21). Data were processed with the AT-SAS suite according to the materials and methods  (22). Estimated molecular weights from SAXS data were consistent with a dimeric protein (Supplementary Table  S1 ) and the radius of gyration (Rg) of GabR in solution was 34. 6 ± 0. 1 Å, which is similar to that calculated from the crystal structure (Rg = 33. 3 Å). The theoretical scattering and interatomic distance distribution (P(r)) plots calculated from the crystal structure of the GabR dimer (PDBID: 4N0B) (12) using the program crysol, (23) was also similar to the experimental scattering data (Figure  3A  and B ).
Ethics and study design The hemodynamic optimization using the PVI (OPVI) study is a multicenter randomized controlled two-armtrial. The institutional review board of the University Hospital of Caen approved the study for all co-investigator centers (Registration number ID RDB: 2014-A00330-47, 23 May 2014). The OPVI study is conducted in accordance with the Declaration of Helsinki, and was registered on 31 July 2014 on the ClinicalTrials. gov website with trial identification number NCT02207296. The OPVI trial follows the CONSORT statement  [17] ; the CONSORT diagram is shown in Fig. 1.
Sample size estimation Using the French national database, two groups of 193 patients are required to detect a difference of 1 day in the primary outcome measure between groups, using a two-sided α-risk at 0. 05 and a β-risk at 0. 20, assuming a standard deviation of ±3. 5 days for the primary outcome difference. An interim analysis is planned after Fig. 3  Hemodynamic algorithm for the PVI group. *Norepinephrine after failure of the use of ephedrine defined by the use of 30 mg of ephedrine without desired hemodynamic response. Norepinephrine: dosage begins at 0. 05 μg/(kg min), and is then adjusted in steps of 0. 05 μg/(kg min). IV, intravenous; IVD, intravenous drip; MAP, mean arterial pressure; PVI, plethysmographic variability index enrollment of the first 200 patients, to check the length of hospital stay after surgery in each group and perform a futility assessment with conditional power.
We anticipate no missing data for the primary outcome measure (length of hospital stay following surgery). However, we plan to conduct multiple imputation in the case of missing data. For per-protocol analysis (sensitivity analysis), the need to handle missing data (failure of PVI monitoring; hypotension following induction of general anesthesia leading to a requirement for norepinephrine; or serious undesirable events during the surgery) will be anticipated by including 27 additional patients for each group. Nevertheless, all randomized patients will be analyzed in the allocated group for the main, intention-to-treat, analysis. In addition, to comply with the intention-to-treat analysis, missing data for the primary outcome will handled by multiple imputation (PROC MI in SAS) and analyzed in sensitivity analyses using PROC MIANALYSE in SAS version 9.
Data collected and registered Baseline characteristics and prerandomization data will be recorded: sex, age, height, weight, ideal body weight, Lee score  [20] , smoking status, history and type of diabetes mellitus, dyslipidemia, history of cardiovascular disease (systemic hypertension, ischemic heart disease, valvular heart disease, peripheral vascular disease, cardiac medications), history of respiratory disease (asthma, chronic obstructive pulmonary disease) using the PROVILHO study criteria  [21] , history of hepatic disease (Child Pugh classification of cirrhosis  [22] ), renal insufficiency (classified according to the glomerular filtration rate [23]), history of neoplasia (active or remission), and blood sample (creatinine, bilirubin, albumin, rate of prothrombin). During the anesthesia and surgical procedures, the following will be recorded: type of procedure (first or reoperation), surgical site (hip or knee arthroplasty), duration of anesthesia and surgery, blood loss and transfusion requirements, all drugs used during anesthesia (anesthetics, opiates, neuromuscular blocking agent), all administered fluids (number of titrated fluid loading and total fluid loading), and all vasoactive drugs.
After the procedure and before the extubation, the blood lactate level will be recorded. Data from the Radical-7 monitor will be extracted (mean PVI, percentage of time that PVI < 13 %, mean heart rate). The mean arterial pressure, the ratio of mean arterial pressure to heart rate, and the percentage of time that the mean arterial pressure is less than 65 mmHg and less than 55 mmHg, will be extracted from the conventional monitor. During postoperative days 1, 3, and 5, blood samples will be taken, to assess creatinine, troponin, and hemoglobin levels. From postoperative day 0 until discharge from hospital, any postoperative complications will be recorded (Table  1 ). The real and theoretical (using the checklist) hospital length of stay and the survival status at day 30 following inclusion will be recorded.
Duration and timeline Patients from five French university hospitals (Caen, Amiens, Lille, Rouen) will be included during a two-year inclusion period, beginning in February 2015. The protocol, approval from the ethical committee, financial support, electronic case report forms, and interactive web response system were developed in 2014. Inclusion of patients is planned for 2015 and 2016. The database will be closed in 2017, after which data analysis, manuscript writing, and submission for publication will follow.
Data collection On the day of study entry, patients underwent a clinical examination and the following data were collected: visit date, body temperature recorded during visit, start date of fever, clinical signs, and the clinical diagnosis established at the end of the visit. Two venous blood samples were collected from each patient (5 mL in patients older than 10 years and 3 mL for those under 10 years): the first was used for haematological and biochemical tests and screened for the presence of Plasmodium parasites by microscopic examination using the thick blood film technique. These tests were carried out locally by the laboratory at each study site according to its own procedures. A confirmed malaria case was defined as a patient with a positive thick blood film result (i. e. , presence of the malaria parasite).
Weaning Dataset Electrocardiogram (ECG -lead II) and respiratory flow (FLW) signals were measured in 121 patients undergoing weaning from mechanical ventilation (74 males, aged 63. 9 ± 17 years; 47 females, aged 66. 3 ± 15 years). These patients were recorded between  January 2003 and April 2006, in   The patients were ventilated in assist-control (AC) mode or pressure support (PS) mode. The patients undergoing an SBT were disconnected from the ventilator just at the moment of the test, and left to breathe through an endotracheal tube for 30 min with close monitoring. Any patients who were not able to breathe spontaneously were reconnected, while those who were able to maintain spontaneous breathing were extubated. When a patient was still able to maintain spontaneous breathing after 48 h, the weaning trial process was considered successful.
Performance of S-Class Spectral signals of HRV, FLW and MSC between them were estimated from 0 to 0. 8 Hz. Then, the PCA method was applied to reduce the dimensionality of data set, and the classification was performed over this new space. The number of principal components (P C) and K neighbours were selected according to the maximum membership percentages of patients to their class. The minimum number of P C necessary for the classification was set at 2, and the maximum variance captured by these principal components was set at 90%. Table  3  shows the mean of the number of P C, the variance captured, and the number of K neighbours for each classification. In all comparisons, HRV with only 2 P C explained more than 90% of the variance of the signal. FLW and MSC signals with 3 and 6 P C, respectively, explained between 60 and 70% of the variance.
Acknowledgments This work was supported in part by the  Spanish Ministry of Economy and Competitiveness  under grants  TEC2010-21703-C03-01  and  TEC2010-20886-C02-01. The authors would like to thank the staff of the  Intensive Care Departments at Santa Creu i Sant Pau Hospital, Barcelona , and at  Getafe University Hospital, Getafe, Spain , for their collaboration with the signal database.
Data This data article contains data related to the research article  [1]  and can serve as benchmark dataset for quantitative evaluation of sulcal pit extraction algorithm. Defined as the deepest points lying in each fold of the cortical surface, the recently introduced geometric landmarks called "sulcal pits" are gathering growing interest as shown by the increasing number of related publications  [1] [2] [3] [4] [5] [6] [7] [8]. If their extraction if fairly simple on principle, algorithms are relying on a few parameters that are essential for the filtering of spurious pits. Such parameters are difficult to tune, and their value can have a large influence on the performance of algorithms. In  [1] , we proposed a method for the extraction of sulcal pits from a reconstructed cortical surface tessellation, that included a framework for the optimization of such parameters.
The validation of this technique was performed on two different groups of healthy subjects with carefully matched characteristics, in order to assess the reproducibility of the technique across groups. We here make available to the community all the data needed to run benchmark analyses. The data consists of 1) high quality cortical surface meshes, 2) the corresponding spherical representation of each cortical surface needed to compute group-level statistics, 3) the corresponding cortical depth maps (DPF), 4) the sulcal pit maps, 5) the population phenotype and identification number in the original database (OASIS).
Experimental design, materials and methods A particular attention was drawn to gather a large set of high-quality cortical surface tessellations from a well-controlled population of healthy individuals. For that purpose, 137 right-handed subjects were selected from the Open Access Series of Imaging Studies (OASIS) database (www. oasis-brains. org)  [9]. The OASIS cross-sectional dataset has a collection of 416 subjects aged from 18 to 96, including older adults with dementia. Fig. 1  illustrates the processing pipeline used and identifies the data provided with respect to this pipeline. For each subject, three to four individual T1-weighted magnetization-prepared rapid gradient echo (MP-RAGE) scans were obtained on a 1. 5 T Vision system (Siemens, Erlangen, Germany) with the following protocol: in-plane resolution¼256 Â 256 (1 mm Â 1 mm), slice thickness¼ 1.
For each cortical mesh, we then computed the Depth Potential Function (DPF) introduced in  [12]  as an estimation of the cortical fold depth, using a new implementation freely available in BrainVISA 4. 5. 0 (http://brainvisa. info/). We used this depth map to extract the sulcal pits of each fold using the technique detailed in  [1]. Both the DPF and the sulcal pits are provided for each subject in the dataset. T ¼ 0. 13/p ¼0. 89 Fig. 1. The MRI from a set of 137 subjects were segmented using freesurfer. The depth map and sulcal pits were then computed for each white mesh using the methods presented in  [1]. The data provided consist of the white and sphere. reg meshes from freesurfer as well as the depth map and the sulcal pits.
Acknowledgments This research was supported by grants from  Fondation de France  ( OTP 38872 ) and  Fondation Orange  ( S1 2013-050 ) to  G. Auzias  and  C. Deruelle. The OASIS database was supported by grants  P50 AG05681 ,  P01 AG03991 ,  R01 AG021910 ,  P20 MH071616 ,  U24 RR021382.
Detection of deletions and mutations of IKZF1 Multiplex ligation-dependent probe amplification (MLPA) was performed using the p335-B1;ALL-IKZF1 kit (MRC Holland, Amsterdam, the Netherlands; data available at http://www. mlpa. com). The data were analyzed with GeneMarker v. 1. 85 (SoftGenetics, State College, Pennsylvania, USA). Data were normalized to reference probes and control samples. A deletion was defined as a peak ratio below 0. 75; an amplification was defined as a peak ratio above 1. 25. Array comparative genomic hybridization (Array-CGH) was performed using the human genome CGH Microarray 105K (Agilent Technologies, Santa Clara, California, USA) according to the manufacturer's protocol; data were analyzed with Genomic Workbench v. 5. 0. 14 (Agilent Technologies, Santa Clara, California, USA).
Gene expression profiling Gene expression profiling (GEP) data were available from earlier studies. 30 Quantitative reverse-transcription-PCR (qRT-PCR) analysis was performed on a subset of patients to analyze the correlation between GEP data and qRT-PCR on relevant genes in patients of different cytogenetic subgroups and a variety of expression measured with GEP. The mRNA expression was determined using the average cycle threshold (Ct) in comparison to expression levels of GAPDH, using the comparative cycle threshold method.
Statistical analysis Statistical analyses for disease outcome and correlation were performed with IBM SPSS 21 (IBM, Armonk, New York, USA). To assess clinical outcome, complete remission (CR; defined as less than 5% blasts in the bone marrow, with regeneration of tri-lineage hematopoiesis, plus absence of leukemic cells), probability of event-free survival (pEFS; defined as the time between diagnosis and first event including non-responders calculated as an event on day 0), and probability of overall survival (pOS; defined as the time between diagnosis and death) were analyzed. Both pEFS and pOS were estimated by the Kaplan-Meier method and differences compared using log rank tests. The cumulative incidence of nonresponse or relapse (pCIR; defined as time between diagnosis and relapse, and with non-responders included as an event on day 0) was analyzed by the Kalbfleisch and Prentice method, and compared with the Gray's test.
IKZF1 haploinsufficient AML cells display an AML-specific gene expression signature Original gene expression data are available in the Gene Expression Omnibus repository (http://www. ncbi. nlm. nih. gov/geo;accession GSE17855). Focal IKZF1 deletions are also found in mixed phenotype acute leukemia. 34 To ensure the included cases were AML patients and not patients with a mixed ALL and AML phenotype, we used a previously defined AML versus ALL classifier. 35 Patients with focal IKZF1 deletions (dark green triangles) and patients with monosomy 7 (light green squares) clustered amongst the other AML patients (red circles) and away from the ALL patients (blue circles), based on the expression signatures of the AML-specific genes (Figure  3A ), the ALL-specific genes (Figure  3B ), and the combined AML/ALL-specific genes (Figure  3C ).
31 Probe sets were limited to those targeting unique genes or having a selectivity score of more than 0. 8 (www. geneannot. com). Further statistical analyses were performed in R v. 3. 0. 0. (R scripts are available upon request. ) We first compared gene expression profiles of monosomy 7 samples (n=8) to those of IKZF1-non-deleted samples (n=247). We detected 244 probe sets representing 198 genes differently expressed (BFDR<0. 05) between these two groups (Figure  4A ). As might be expected, a large proportion (44%) of these genes are located on chromosome 7, and are down-regulated (Figure  4B  and Online Supplementary Table  S3 ). Next, we compared the mean differences in expression of these 198 genes in monosomy 7 samples (n=8) to those in samples with IKZF1 focal deletions (n=3) (Figure  4C ).
A B C and focally deleted IKFZ1 samples are also GATA1 targets in K562. For this purpose, we used a GATA1 ChIP seq dataset in K562 cells. 38 From the 23 genes significantly upregulated in the IKZF1-deleted samples, 11 genes had a GATA1 peak ratio larger than 25, indicating the gene being a GATA1 target (Figure  6A ). Further analysis showed that whereas 13% of genes on our expression platform is a GATA1 target, 55% of genes that are up-regulated in IKZF1-deleted cases are GATA1 targets (P=3. 5 e-7) (Figure  6B ). While GATA transcription factors exhibit diverse functions in cellular proliferation, differentiation and gene regulation, only GATA1, GATA2, and GATA3 are expressed in developing blood cells and are critical for hematopoiesis. 39, 40 GATA1 (P=0. 07) and GATA3 (P=0. 006) were up-regulated in the IKZF1-deleted samples (n=11) as compared to the rest (n=247) (Figure  6C ).
Fuzzy Logic is a framework particularly useful to formalise and deal with imprecise concepts and statements expressed in natural language. This paper has three related aims. First, it aims to provide a short introduction to the basics of Fuzzy Logic within the context of social simulation. Secondly, it presents a well-documented NetLogo extension that facilitates the use of Fuzzy Logic within NetLogo. Finally, by providing a concrete example, it shows how researchers can use the Fuzzy Logic extension to build agent-based models in which individual agents hold their own fuzzy concepts and use their own fuzzy rules, which may also change over time. We argue that Fuzzy Logic and the tools provided here can be useful in Social Simulation in different ways. For example, they can assist in the process of analysing the robustness of a certain social theory expressed in natural language to different specifications of the imprecise concepts that the theory may contain (such as e.
3. 3 The functionality of the NetLogo extension (which is internally coded in Java) was initially implemented as a library of functions directly written in NetLogo language. This set of NetLogo functions -together with its own documentation and tutorial -is provided in Appendix E. The advantage of the extension over the library is that it is computationally more efficient (both in terms of speed and memory usage) and it is easier to use. Some researchers may still find the original NetLogo library useful if they plan to inspect and/or modify the code within NetLogo.