dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis All statistical calculations were performed using GraphPad Prism 6. 0. Error bars displayed on graphs represent the means ± SD of three or more independent replicates of an experiment. D'Agostino-Pearson normality test was used to determine whether datasets were normally distributed. Statistical significance was calculated using Student's t test or one-way analysis of variance followed by Tukey's multiple comparisons test. For image analysis, six or more biological replicates per sample-condition were used to generate the representative data. Western blot, qRT-PCR, Northern blot data presented are representative of at least three independent experiments.
ACKNOWLEDGEMENTS We would like to thank  Prof. Yasuko Mori  and  Dr. Eain Murphy  for providing the HHV-6A BAC DNA and BAC-derived virus containing cells. We also extend our thanks to  Kristin Loomis  and  Dharam Ablashi  from  HHV-6 Foundation  for their support. Our thanks also go to  Flor M. Munoz  and  Karen Eldin  from  Baylor College of Medicine, USA  for providing liver biopsy materials. We also thank  Elizabeth Jane Phillips  from  Vanderbilt University  for providing blood-derived DNA of the DRESS patient. We thank the  Helmholtz Institute for RNA-based Infection Research (HIRI)  for supporting this work with a seed grant to B. K. P. through funds from the  Bavarian Ministry of Economic Affairs and Media, Energy and Technology  (Grant allocation nos. 0703/ 68674/5/2017  and  0703/89374/3/2017 ).
This is more so when the resolution of the point clouds are heterogeneous, as in the case where the point cloud sources are different  (Grussenmeyer et al. , 2012). One main problem that arises from the registration of exterior and interior data is the lack of overlap between the two point clouds, more so when both datasets were acquired separately and using different types of sensors. This paper presents a comparison of two registration approaches in order to combine the exterior and interior point clouds of a heritage building. Assessment of the geometric quality of each approach will be performed using checkpoint residuals. These checkpoints were measured independently from the main point cloud acquisition mission. In addition, some ongoing work on the automation of some parts of the exterior-interior registration workflow will also be presented.
The registration is based on a set of tie points, which are evenly distributed throughout the building. These tie points concern mainly openings such as windows. The tie points were identified in the first place by manual measurements, with results to be discussed in section 4. 1. Afterwards, an ongoing work on the automation of tie point detection and matching will be presented in section 4. 2. In both cases, an ICP procedure is not feasible due to the minimum overlapping zones between the two datasets. In the free-net approach, a total of 24 tie points (Figure  3 ) were identified on the church. The windows which represent overlapping spaces between the exterior and interior were used as point candidates, although physically they are not the same points due to the thickness of the window panes.
In this regard, by assuming a window pane thickness of around 2 cm, an error of this order should be expected on the final results. Furthermore, the point clouds used in the experiment were subsampled to 1 cm in order to give a more manageable data set while keeping enough details to identify as tie point candidates. In order to assess the quality of the registration and georeferencing of both approaches, a set of independent check points were measured on the exterior and interior of the building using a total station. The spatial intersection method was chosen to measure these points, in order to generate highprecision coordinates with standard deviation values available. Measurements were based on a traverse network established in and around the church. Each check point was measured from at least two stations.
In this paper, the Trimble S8 robotic total station was used to perform the measurements. Coordinates of these points on the processed point cloud issuing from both approaches were then compared to the ones measured using the total station. The comparison of their residuals was then used as a criterion for quality assessment. In terms of software used in the experiments, the open source software CloudCompare (version 2. 9. 1) and the scientific software 3DVEM were used. CloudCompare offers a 3D transformation module in which a standard similarity transformation is performed. The software gives the users possibility to choose between a 6-parameters (no scaling) or 7parameters (with scaling) transformation. 3DVEM is a scientific software programme developed by the University of Valencia (Spain) which performs point cloud registration and georeferencing with the possibility to use the standard leastsquares based method or robust estimators (namely the modified Danish and minimum sum estimators)  (Fabado et al.
Independent georeferencing In the independent georeferencing approach, each data set was georeferenced separately using methods employed in their respective workflow. The exterior point cloud was generated entirely from images taken using UAVs and cameras; thus the georeferencing follows the absolute orientation method normally seen in photogrammetry. A total of 25 ground control points (GCPs) were used to this end, yielding an overall RMS value of 0. 018 m on the GCP residuals. The interior of the church was scanned entirely using the FARO Focus X330 terrestrial laser scanner (TLS). The registration between the stations was performed using the FARO Scene software, with the aid of automatically detected spheres and targets. The coordinates of these spheres were measured using a total station, enabling the georeferencing of the interior point cloud.
A total of 31 spheres and targets were used in the georeferencing process, yielding an overall final precision of 0. 010 m. The control points used in both data sets were measured from traverse network points. This network was measured in the French national projection system, with several points fixed using GNSS-measured coordinates. Since no levelling benchmark was to be found near the site, the GNSS altitudes were used in the coordinate computation. This common projection system used by the control points in both data sets means that at the end of their respective georeferencing process the interior and exterior point clouds were directly merged in one coordinate system. The results of this approach are illustrated in Figure  4. Figure  4. The two point clouds registered and georeferenced using the independent method.
Free-net registration and georeferencing The free-net approach assumes that both data sets have been neither registered on each other nor georeferenced to the reference system. In practice, in the interior TLS data this means that the point cloud was simply not georeferenced. In the photogrammetric exterior point cloud, the absence of absolute orientation implies that the relative model is not scaled either. Since 3DVEM does not support scaling during the registration step, absolute orientation was nonetheless performed on the photogrammetric data. However, noises on the rotational and translational parts were introduced on purpose to generate a simulated data for the purposes of the experiment. The registration was based on the 24 tie points manually measured on both point clouds. The process was performed on the software CloudCompare as well as 3DVEM.
Free-net Registration Software Residuals RMS (m) CloudCompare 0. 028 3DVEM LS 0. 029 MS 0. 029 Table  1. RMS of the tie point residuals used for the registration of the exterior and interior point clouds using the free-net approach. As can be seen from Table  1 , all proposed algorithms give similar results of the order of 0. 030 m in RMS. Assuming a point marking precision of 0. 010 m, this value is only slightly outside the a priori tolerance of 2σ (for a level of confidence of 95%) but falls within the 3σ (99. 8% level of confidence) range. It is also worth noting here that the use of robust estimators in this case does not show a significant difference from the use of standard least squares solution. Once the registration was performed, the georeferencing step followed which used 15 photogrammetric GCPs on the exterior and 6 measured 3D spheres in the interior.
Free-net Georeferencing Software Residuals RMS (m) CloudCompare 0. 031 3DVEM 0. 031 Table  2. RMS of the control point residuals used in the georeferencing process using the free-net approach. The RMS of the control point residuals in both solutions shows similar results. The values obtained are also of the same order with the registration RMS, further showing the georeferencing precision of the process and the absence of systematic error.
Direct keypoint detection and matching to this kind of segmentation proved to be insufficient, as the algorithm takes the exterior and interior parts to be the same object. A RANSAC-based plane fitting was therefore employed in order to extract the window panes, the part which involves the overlapping zone between the two data (Figure  6 (b)). Working with this data, 3D keypoints were detected on the window glasses. To this end, the 3D SIFT algorithm was used. The 3D SIFT is an implementation of the SIFT method  (Lowe, 2004)  for 3D data. Results of the keypoint detection can be seen in Figure  6  (c). In order to find correspondence matches between the detected keypoints, descriptors need to be computed for each keypoint on each data. In this experiment, the SHOT (Signature of Histograms of OrienTations)  (Tombari et al.
However, the data showed that the delayed administration of TA was associated with potential harm. Thus TA, if used, should be given early and empirically as soon as a PPH is diagnosed, and before severe haemorrhage. As the study was based on robust clinical endpoints, neither blood loss estimation nor haemoglobin drop were available. There was no subgroup analysis of TA efficacy according to the volume of bleeding. Laboratory results were not included in the primary analysis but were assessed in a few centres as a part of a secondary analysis  [25]. The biological effect of the high TA dose administered in the EXADELI trial was observed and compared to a non-treated haemorrhagic group and a non-haemorrhagic postpartum group. Significant excessive fibrinolysis was noted in the untreated haemorrhagic group vs the non-haemorrhagic group at PPH onset.
Drapes and pads are weighed at each observation time. Amniotic fluid, washing solutions and antiseptics are subtracted or collected in a separate aspiration bag. The investigation centres have been selected regarding their routine practice in surgical blood measurement during CS. Blood-loss calculation can be biaised by the haemodilution/haemoconcentration process and by haemolysis. However, in order to obtain a double assessment of the primary criterion, the haemoglobin-(Hb)-drop-based blood loss calculation will be performed using haemoglobin drop (last Hb measurement available before delivery as reference to day-2 final Hb) corrected by the transfused haemoglobin amount (red blood cell (RBC) concentration of 54 g/100 mL). Secondary endpoints aim to produce scientific data for dose-ranging reduction of maternal morbidity: total blood loss, postpartum anaemia, postpartum organ failure, late postpartum side effects and death.
However, arterial or venous thrombotic risks must be monitored considering the prohaemostatic characteristics of the drug. Nausea and vomiting have been previously reported with TA  [21]. Data collection Inclusions are performed 24 h per day, 7 days a week. Each patient admitted for an elective or non-emergency CS during labour will be informed before the CS commences and a signed consent will be obtained. Patients will be included in the haemorrhagic group when haemorrhage exceeds 800 mL. Blind injection of the 10 mL-vial containing 0, 0. 5 g or 1 g of TA will be performed over 1 min between T0 and T1 after injection. Transfusion, maternal haemodynamic, resuscitation measure, uterotonic and invasive procedure data and maternal morbidity parameters are recorded before inclusion (T0) and at T30, T60, T120 and T360, respectively 30, 60, 120 and 360 min after inclusion and at day 2 (±12 h) and day 42 (±14 days) postpartum.
Data collection and management Data will be anomymised in accordance with the law dated 6 January 1978. Data will be collected electronically. Data will be analysed in accordance with the methodology described in MR 06001 form of the French Data Protection Authority by Prof. Alain Duhamel's epidemiology and public health biostatistics platform Lille University Hospital Lille. Access to data will be restricted to individuals who are directly involved in the study. Data may be modified by any physician participating in the study or a fellow working with a physician participating in the study. Trial data will be archived for at least 15 years after the trial has ended.
Sample size calculation The sample size computation is based on the expected difference between the placebo group and the low-dose group and available data on the TA use in active PPH. Ducloy et al. recruited patients who experienced moderate PPH after a vaginal delivery. The treatment was a TA uniform high dose: 4 g over 1 h, then 1 g/h over 6 h. T0-T360 blood loss after inclusion was estimated at 133 ± 252 mL (mean ± standard deviation) in the placebo group and at 58 ± 96 mL in the treated arm. Kolsi et al. recruited patients who experienced moderate PPH during CS and tested a uniform TA dose of 10 mg/kg. The TA group received 10 mg/kg of TA as an induction dose within 12 min after second-line uterotonic drug onset and 1 mg/kg/h as maintenance within the two following hours. The placebo group received the same volumes of normal saline.
Statistical analysis Statistical analyses will be independently performed by the Biostatistics Department of University of Lille under the responsibility of Prof. Alain Duhamel. Data will be analysed using SAS software (SAS Institute Inc, Cary, NC, USA) and all statistical tests will be performed with a two-tailed alpha risk of 0. 05. A detailed statistical analysis plan will be written and finalised prior to the database lock. Baseline characteristics will be described for each group. The quantitative variables will be expressed as mean and standard deviation in cases of normal distribution and median and interquartile if not. The normality of distributions will be checked graphically and using the Shapiro-Wilk test. Qualitative variables will be expressed as frequencies and percentages. For the main objective, the blood loss measured in each experimental group (low-dose and high-dose) will be compared to that of the placebo group by using an analysis of covariance adjusted for baseline blood loss volume and centre effect.
Study organisation The coordinating team includes the coordinator, the promotor and the major investigators of each of the centres. A call conference will be organised every 2 months between the coordinator and the centres, supported by a newsletter reporting inclusion rates and protocol information. Data and consent collection will be monitored by the promotor. An independent safety monitoring committee is recruited to observe blinding safety issues and allow trial continuation. Data management and statistical analysis will be done by an independent unit. Plans are written in advance for investigators and sponsor to communicate trial results to participants, healthcare professionals, the public, and other relevant groups (e. g. via publication, reporting in results databases, or other data-sharing arrangements).
RESULTS The Micra device was successfully implanted in 1801 of 1817 patients (99. 1%). The mean follow-up period was 6. 8 6 6. 9 months. Through 12 months, the major complication rate was 2. 7% (95% confidence interval [CI] 2. 0%-3. 7%). The risk of major complications for Micra PAR patients was 63% lower than that for patients with transvenous pacemakers through 12 months postimplantation (hazard ratio 0. 37; 95% CI 0. 27-0. 52; P ,. 001). The The Micra Post-Approval Registry and Micra Transcatheter Pacing Study are funded by Medtronic, plc, USA. Dr El-Chami has received compensation for services from Boston Scientific and Medtronic. Dr Clementy, Dr Martinez-Sande, Dr Ritter have received compensation for services from Medtronic. Dr Garweg has received proctoring fees from Medtronic. Dr Piccini has received compensation for services from Medtronic and research grant from Abbott and Boston Scientific.
Statistical analysis At the time of the database freeze for this analysis, all but 6 successfully implanted patients were included because of delayed data entry. Summary statistics were obtained and reported using mean 6 SD for continuous variables and frequency and percentage for categorical variables. The major complication rate was calculated for each category and subcategory for both acute major complication (30 days of follow-up) and chronic major complication (. 30 days of follow-up). The distribution of pacing percentage for Micra patients at the last follow-up visit was plotted. Battery longevity estimates were obtained from each patient's last device interrogation and normalized to the longevity remaining at 6 months (183 days) postimplantation. Kaplan-Meier methods were used to estimate the rate of major complication (and its components) at 12 months postimplantation.
In addition, the Fine-Gray competing risk model was used to compare the risk of major complications (and its components) through 12 months between 2 groups: 2667 patients in the transvenous control group vs 1817 patients with an attempted Micra implantation procedure in the postmarket population and 726 patients with an attempted Micra implantation procedure in the IDE study. However, when comparing components of the major complication rate, the Fisher exact test was used if zero events were observed for one of the groups. All analyses were performed with SAS version 9. 4 (SAS Institute Inc. , Cary, NC) or the R statistical package (R Project for Statistical Computing, Vienna, Austria). Electrical parameters were summarized at each study visit using means and SDs.
This highlights the importance of careful groin access and consideration of vascular ultrasound guidance for venous puncture, especially   when dealing with octo-or nonagenarians, a population at increased risk of groin complications. An important finding of the PAR is the significantly lower rate of perforation (0. 77% total and 0. 44% meeting the criterion for a major complication definition) as compared with the original Micra IDE study data (1. 8% total and 1. 5% meeting the criterion for a major complication definition). This possibly reflects the rigorous training programs that new implanters are exposed to. A major focus on implanting these devices in the septum and on the use of intravenous contrast with orthogonal radiographic views to confirm the position of the delivery system could explain the lower rate of perforation.
Study design and participants This study was part of a larger, prospective observational cohort study conducted in an 18-bed intensive care unit (ICU) between January 2014 and December 2014  [7]. The study was approved by our Institutional Review Board (Comité de Protection des Personnes Nord-Ouest 3); NCT02363231 www. clinicaltrials. gov. In conformity with the Declaration of Helsinki, all patients participated voluntarily. Patients were included if they were over 18 years of age and had undergone a minimum of 24 h of MV. They were not included if they had chronic loss of autonomy (a KATZ score below 6/6  [13] , a degenerative neurological pathology with disabling muscle weakness, were agitated prior to the evaluation (Ramsay score of 1 or Richmond Agitation-Sedation Scale (RASS) greater than 1) or a decision to withhold life sustaining treatment had been made.
The in-situ loading sample was tested at 293 K in uniaxial tension at an initial strain rate of 4 × 10 -4 s -1. These diffraction patterns recorded using a Pixium area detector with a 0. 5 × 0. 5 mm 2 beam and 0. 4 s count time. Ten patterns were averaged and saved every 4 s. For EPSC modeling and plotting of peak intensities during cyclic loading, raw diffraction patterns were calibrated using Fit2d software and a cerium dioxide calibration sample to refine the sample-detector distance and detector misalignment.
For example, with k = 1, 2, or 3, there is 68, 95, or 99. 7% confidence that the true value falls within the ± ku c interval centered around the calculated value, assuming the variable is normally distributed. Given the basic scientific requirement to understand uncertainty, experts from the ocean acidification community have emphasized the need to enhance existing CO 2 system software packages to allow them to also propagate uncertainties  (Martz et al. , 2015). Here our main aim is to do just that, thus providing marine scientists with public tools to easily propagate uncertainties using (1) automatically calculated sensitivities, which vary from region to region, and (2) input standard uncertainties that may be user specified. Standard uncertainties should be estimates that include both random and systematic components.
Eq. (  2 ) is the most common form of the Method of Moments because it uses a first-order approximation of y to estimate that dependent variable's second moment, i. e. , its standard deviation u c (y); when covariance terms are neglected, it simplifies to the Gaussian approach  (Taylor, 1996; Kirchner, 2001). We implemented both approaches in four public software packages that are commonly used to compute marine carbonate chemistry: CO2SYS-Excel  (Pierrot et al. , 2006 ), CO2SYS-MATLAB (van Heuven et al. , 2011) , mocsy  (Orr and Epitalon, 2015) , and seacarb  (Proye and Gattuso, 2003; Lavigne and Gattuso, 2011; Gattuso et al. , 2018). In the current implementation, users may specify the covariance between the uncertainties of the input pair of carbonate system variables. Other covariances are assumed to be negligible.
Sensitivities To propagate uncertainties with both the Gaussian approach and the Method of Moments, we must first compute the sensitivity of each computed variable to each input variable. These sensitivities were computed numerically, optimizing the numerical step size by comparing results to analytical solutions and so-called automatic derivatives. A routine derivnum was coded to compute all partial derivatives numerically with centered differences, a commonly used approach but one for which a reference should be used to optimize the numerical step size. Optimal step sizes differ between derivatives. In parallel, we coded a reference routine to provide analytical solutions to some of the partial derivatives of the carbonate system needed for uncertainty propagation. That code was built upon an existing routine in seacarb, buffesm developed by  Orr (2011)  using equations from  Egleston et al.
(2010)  with corrections to typographical errors consistent with those from  Álvarez et al. (2014). Yet  Egleston et al. (2010)  ignored contributions to the total alkalinity from phosphoric and silicic acid systems. Hence both systems were added here following the procedure outlined in Appendix B. The modified version of buffesm used to make these calculations is available in the seacarb package. A second reference routine derivauto was developed in the mocsy package using an approach known as automatic differentiation to compute all relevant partial derivatives (buffer factors). In some languages such as Fortran 90, automatic differentiation requires minimal coding, taking advantage of operator overloading, to adapt an exisitng routine to compute derivatives of its output variables with respect to its input variables.