dataesr/scientific-paragraphs-categorization huggingface dataset:
Computed Cases Cases Derived by Symmetry The second database (DB2) was generated to test the sensitivity of the results. The resolution is only marginally higher (18 vs. 14 datapoints), however, the topology of the datapoints is different. The two datasets are visualized in Figure  10. The nodes of the triangulated surfaces match the points on the unit sphere (see Figure  1 ) where the values of the force and momentum coefficients are pre-computed by CFD. The coloring is carried out by the magnitude of the force coefficient. Even if the resolution is rather low, the unit spheres are covered uniformly and the databases are deemed to be sufficient to function as proof of concept for the suggested method and to check the sensitivity of the results to the force coefficient database. Further improvement of the accuracy in the interpolated values of the force and momentum coefficients is a matter of carrying out further CFD computations.
Such CFD computations being the most time-consuming part (a typical computation needed around 2 h walltime on four cores), one should optimise the direction of the investigated relative velocities to regions with large gradients of the obtained coefficients. Note also that the influence of Reynolds number is not accounted for; this deficiency can also be remedied by adding one more dimension to the database. (1, 0, 0) (-1, 0, 0) (0, 1, 0) (0, -1, 0) (0, 0, 1) (0, 0, -1) (0.
Parked Wind Turbine First the case of a parked wind turbine is investigated. Figure  11a, b  show front (normal to the rotor disc) and top (normal to the ground) views of the computed trajectories for ice chunks released at a radial position of 45 m and varying azimuthal positions. The wind turbine parameters and the wind conditions are the same as for the 3DOF computations and the DB1 database (Figure  10a ) is used. Figure  11a  reveals significant effects of the forces normal to the object trajectories, if only the drag force would have been acting the trajectories would have been vertical lines in this view. The largest effect is observed for the ice released at an angle of 120 degrees (yellow, 0 degree being the lowermost position of the blade tip). The top view of the trajectories (see Figure  11b ) shows similar effects, compared to the 3DOF cases the impact locations are closer to the tower in the wind direction.
As one can observe, the impact positions determined with 3DOF computations (marked with triangles in Figure  14b ) deviate significantly from the ones predicted by the 6DOF approach (filled circles). One reason for the discrepancies is the fact that in the 3DOF computations, a constant value of C D = 0. 57 has been used, this value being based on the average magnitude of the force coefficients from the database. In the 6DOF computations, the value of the force coefficient changes in time depending on the orientation of the object. Another reason for the discrepancies is that in the 3DOF computations, only the forces in the direction of the relative velocity are accounted for.
Sensitivity to the Force Coefficient Database In order to assess the sensitivity of the results to the underlying force coefficient database, the trajectory computations of the ice chunks released from the rotating wind turbine have been repeated using the database DB2 (Figure  10b ). The front and top views of the ice chunk trajectories are shown in Figure  15. Comparing to the DB1 results (Figure  14 ), one can notice a significant influence of the force coefficient database on the predicted trajectories. In the case of DB2, the impact area is narrower but more elongated than in the DB1 case. This behavior is probably due to the fact that DB2 includes a datapoint with a larger magnitude of the force coefficient (see Figure  10 ), thus leading to a similar effect as increasing the drag coefficient in the 3DOF case (see Figure  7 ).
Conclusions A method was implemented to compute the trajectories of ice pieces released from rotating and parked wind turbines. First, the method commonly used in the literature (accounting only for translation) has been implemented and the sensitivity of the trajectories to several controlling parameters (wind speed, turbine rotation, azimuthal and radial release positions and ice drag coefficient) has been evaluated. The results agreed well with data reported previously in the literature. In the second part, the objects were also allowed to rotate during the flight. The aerodynamic forces and moments have been precomputed a-priori using CFD computations and their normalised values have been stored in a database. This database has been used in the trajectory computations to estimate the instantaneous forces and moments acting on the object during the flight, depending on the instantaneous relative velocity.
Although the accuracy of the 6DOF computations is limited due to the relatively coarse resolution of the database, the results revealed that the forces are normal to the trajectories and the changes in the object attitude might have significant effects on the ice trajectories. Furthermore, the results revealed that the predicted trajectories are very sensitive to the quality of the force coefficient database used for the 6DOF computations. Since all predicted impact locations were well within the limits prescribed by Equation (1), the investigated parameters are not expected to influence the safety when the safety distance prescribed by Equation (  1 ) can be respected. However, if one cannot afford the traditionally-prescribed safety distance, or if one needs to investigate incidents, 3D effects cannot be neglected any more.
Performance-wise, the suggested method is located in-between traditional 3DOF trajectory computations and full-CFD simulations of the flying objects. Due to the need for force and momentum coefficient databases, the computational cost of this method is significantly higher than the cost of pure 3DOF. Nevertheless, once a database is generated, it can be reused for similar objects and then the additional cost of interpolating coefficients from the database vs. assuming constant values of the coefficient is minimal and probably well motivated by the additional gain of accuracy. Full CFD computations of the flying objects is estimated to be at least one or two orders of magnitude more demanding computationally. Due to the large interval of scales which need to be captured and the relatively long time intervals (compared to the timescale of the flow around the object), a 3D computation of the flow-field including both the wind turbine and the flying ice chunks would require unreasonably large resources.
Thus, a more realistic approach would be CFD computations of the flow in a domain moving together with the ice chunk, however, that approach would still be significantly more demanding than the approach suggested herein. The accuracy of the suggested method can be increased primarily by increasing the resolution of the database used to store the aerodynamic forces. In addition, even more realistic wind velocity fields, by including a wake model or by precomputing the velocity field by CFD, would also enhance the quality of the results. The suggested method is easily applicable to other kinds of trajectory computations as well, for example, to assess the trajectory of flying debris in heavy storms.
Patient Cohort A prospective controlled observational comparative study (Circulating Tumor Cells and Melanoma: Comparing the EPISPOT and CellSearch Techniques; NCT01558349) was conducted at the Nîmes University Hospital, Nîmes, France, between June 2013 and June 2017. The main objective was to determine if we can observe more positive patients with the EPISPOT assay than the CellSearch ® system. All patients with melanoma signed a written informed consent before enrolment in the CELLCIRC study and treatment initiation. The study was carried out in accordance with the World Medical Association Declaration of Helsinki. The experimental protocol was approved by the French bioethical committee "Sud Méditerranée III" (Approval reference No. 2012. 06. 10). Blood samples from healthy volunteers (n = 38) and patients with metastatic malignant melanoma (n = 50; before any treatment) were collected in the morning and processed within 24 h.
S100-EPISPOT Assay Then, the two melanoma cell lines were used to evaluate the feasibility and detection threshold of the S100-EPISPOT assay. No immunospots (indicative of S100 secretion) could be detected when using MV3 cells, possibly due to their very weak S100 expression, as observed by FC and IF. Conversely, on average, 20-47% of WM-266-4 cells secreted S100 (Figure  2 ). This detection rate is considered normal for cell lines analyzed with the EPISPOT assay because of variations in cell cycle and protein productivity. In parallel, enriched peripheral blood mononuclear cells (PBMCs) from healthy donors were tested (n = 3) to confirm that S100 was not secreted by PBMCs (data not show) and validate this assay for CMC detection after blood enrichment.
S100-EPISPOT Assay Then, the two melanoma cell lines were used to evaluate the feasibility and detection threshold of the S100-EPISPOT assay. No immunospots (indicative of S100 secretion) could be detected when using MV3 cells, possibly due to their very weak S100 expression, as observed by FC and IF. Conversely, on average, 20-47% of WM-266-4 cells secreted S100 (Figure  2 ). This detection rate is considered normal for cell lines analyzed with the EPISPOT assay because of variations in cell cycle and protein productivity. In parallel, enriched peripheral blood mononuclear cells (PBMCs) from healthy donors were tested (n = 3) to confirm that S100 was not secreted by PBMCs (data not show) and validate this assay for CMC detection after blood enrichment. Surprisingly, the detection rate was higher with smaller numbers of tested cells (Figure  2 ).
It fits well for performing expert analysis on a system but has limited capacity of synthesization. To this purpose, report or dashboard definition is required. Reports and dashboards allow to visualize information in an organized way and to perform further analysis or point out advanced information built from raw variables. They both aim at having a focus on specific aspects of a dataset, yet they differ from several aspects. A report is defined as a document that contains information organized in a narrative, graphic or tabular form and aims at being communicated or presented in oral or written form. On the other hand, a dashboard characterizes "a visual display of the most important information needed to achieve one or more objectives". Table  13. 1 summarizes the main differences. Examples of specific views that can be extracted from knowledge base data are presented in Fig.
Locating distribution centers is critical for humanitarians in the immediate aftermath of a sudden-onset disaster. A major challenge lies in balancing the complexity and uncertainty of the problem with time and resource constraints. To address this problem, we propose a location-allocation model that divides the topography of affected areas into multiple layers; considers constrained number and capacity of facilities and fleets; and allows decision-makers to explore trade-offs between response time and logistics costs. To illustrate our theoretical work, we apply the model to a real dataset from the 2015 Nepal earthquake response. For this case, our method results in a considerable reduction of logistics costs.
The experts were five logisticians working on planning the relief operations in the UN WFP and International Federation of Red Cross and Red Crescent Societies (IFRC). After several iterative discussions, we were able to identify the required capabilities, model them, and ensure that they are implemented correctly. In the model development process, we compared the model calculations with practitioners' data, and investigated those cost or time components that were estimated differently or were left un-modeled. Following the discussions with the practitioners, we finally ensured that the un-modeled costs and times were integrated in the model. Although the specific characteristics of disasters contexts may imply constraints regarding datasets, disasters are not any more totally data lacking contexts (Van de Walle and  Comes, 2015).
The data that we used in our paper to build and validate the model is often available for different type of disasters through information sharing platforms. Typically, HOs would be provided maps, distances, and logistics prices through the Logistics Cluster in the early stages of response. Such information is also often shared on websites such as ReliefWeb, 1  LogCluster, 2  HumanitarianDataExchange (HDX) 3  as open data. In situations where data is not available or it is incomplete, practitioners use estimates, according to our interviews.
4 ), box sizes for delivered food (the UN WFP handbook and interviews), travel times/travel distances (acquired from one Nepalese logistics service provider), and specifications of the MSUs established during the Nepal response (reports from the Logistics Cluster). The parameters related to the logistics costs are elicited from the business experts of the UN WFP. We ensured that the used parameter values are the "best guess," as depicted in Table  4. In the calculations, the monthly costs were adapted to the estimated timeline of the operation. More details regarding our input data are provided in Appendix A.
Thus, decreasing the solution time for the model is preferred, specifically when the problem size increases. This will be further analyzed in Section 4. 3. Using the actual UN WFP data, we can compare our results with the performance of their network during the immediate response to the 2015 Nepal earthquake, as shown in Fig. 5. Sol. WFP, represents the optimized values of the objective functions for the given location of the SAs that the UN WFP used. Other curves represent the solutions provided by AUGMECON2 algorithm with default value of the relative gap parameter. Fig. 5  depicts the deviation between the model results and the network of the UN WFP. In this setting, Sol. 31 refers to the solution that suggests delivering relief items in 31 days, and it suggests 7% less costs than Sol. WFP.
Discussion In this section, we discuss our findings with respect to five aspects: scalability, runtime, the potential impact of uncertainty, stability of results, and interplay between immediate response and relief. Then, we explore the difference between our results and the choices of the practitioners for the Nepal case. Finally, we elaborate on the managerial implications and insights. Scale In our study, we used a data set related to a real world operation which included 1 MEP, 8 SAs, 24 (accumulated) PODs, 2 transportation modes, and a 45-days timeline. We ran the same model for a scenario with 4 MEPs, 18 SAs, 105 (accumulated) PODs and relaxed transportation/time constraints. Since the solution time for the latter was approximately 2 h on a personal laptop, we argue that this model can be run and used by operational responders equipped with a notebook.
For comparison, the displacements both in vertical and lateral directions of the physisorbed hydroxide on the h-BN surface vs. time have been computed and show similar behaviour (see Supplementary Fig. 5 ). The self-diffusion coefficients of the hydroxide were derived from those trajectories by applying the Einstein equation with computed mean square displacements (see Supplementary Methods). Both the lateral and the vertical diffusions of the anion in the vicinity of the surfaces were determined. A hydroxide in bulk water was also simulated as a reference  system to compare with the interfaces, using the same DFT dynamics framework. The isodirectional coefficient of a hydroxide in bulk water was obtained from a 50 ps MD trajectory. The obtained values are in qualitative agreement with both experimental and simulation data from the literature (see Table  1 )  18, 27, 28.
Acknowledgements This work was performed on the  French national supercomputer Occigen  under the  DARI grants   A0030807364  and  A0030802309. M. L. B acknowlegdes funding from the  H2020 - FETOPEN  project NANOPHLOW number  766972. The authors thank  Lydéric Bocquet  for fruitful discussions and for providing experimental data points for comparison with the presently reported analytic model. The authors also acknowledge  Maximilien Levesque  and  Ari Paavo Seitsonen  for profitable exchanges on technical issues.
Data availability The source data underlying Figs 1b, 2a, 3, 4 and 5 are accessible as source data files (https://figshare. com/articles/Plots_source_data/7623953) along with a corresponding python notebook (https://figshare. com/articles/Plots_python_notebook/762397). Experimental data points displayed Fig. 5  has been provided by Secchi et al. 4. Other data is available upon reasonable request to the authors.
Materials and methods The CardShock study (NCT01374867 at www. clinicaltrials. gov) is a European prospective, observational, multicentre and multinational study on cardiogenic shock. Recruitment was conducted between October 2010 and 31 December 2012. The study enrolled patients from emergency departments, cardiac and intensive care units, as well as catheter laboratories in nine tertiary hospitals from eight countries. The study was approved by the following ethics.
Inclusion criteria and data collection Consecutive patients aged over 18 years were enrolled in the study within 6 hours from identification of cardiogenic shock. The inclusion criteria were (1) an acute cardiac cause for the shock, and (2) systolic blood pressure <90mmHg (after adequate fluid challenge) for 30min or a need for vasopressor therapy to maintain systolic blood pressure >90mmHg, and (3) signs of hypoperfusion (any of the following: altered mental status, cold periphery, oliguria <0. 5mL/ kg/h for the previous 6 h, or blood lactate >2 mmol/L) (for details see Harjola et al. [21] ). Exclusion criteria were shock caused by ongoing hemodynamically significant arrhythmia or shock after cardiac or non-cardiac surgery. The etiology of cardiogenic shock was determined by local investigators.
Acknowledgments The CardShock study investigators in all participating hospitals. The CardShock steering committee:  Veli-Pekka Harjola  (chair),  Marek Banaszewski ,  Lars Køber ,  Johan Lassus ,  Alexandre Mebazaa ,  Marco Metra ,  John Parissis ,  Jose Silva-Cardoso ,  Alessandro Sionis ,  Salvatore Di Somma , and  Jindrich Spinar. List of investigators: Athens:  Katerina Koniari ,  Astrinos Voumvourakis ,  Apostolos Karavidas ; Barcelona:  Jordi Sans-Rosello ,  Montserrat Vila ,  Albert Duran-Cambra ; Brescia:  Marco Metra ,  Michela Bulgari ,  Valentina Lazzarini ; Brno:  Jiri Parenica ,  Roman Stipal ,  Ondrej Ludka ,  Marie Palsuva ,  Eva Ganovska ,  Petr Kubena ; Copenhagen:  Matias G. Lindholm ,  Christian Hassager ;  Helsinki: Tom Ba ¨cklund ,  Raija Jurkko ,  Kristiina Ja ¨rvinen ,  Tuomo Nieminen ,  Kari Pulkki ,  Leena Soininen ,  Reijo Sund ,  Ilkka Tierala ,  Jukka Tolonen ,  Marjut Varpula ,  Tuomas Korva ,  Anne Pitka  ¨la ¨;  Rome: Rossella Marino ; Porto:  Alexandra Sousa ,  Carla Sousa ,  Mariana Paiva ,  Inês Rangel ,  Rui Almeida ,  Teresa Pinho ,  Maria Ju  ´lia.
Funding: VPH was supported by the  Aarne Koskelo Foundation  (no grant number): http://www. aarnekoskelonsaatio. fi/, and the  Finnish Cardiac Foundation  (no grant number): https://www. fincardio. fi/. Laboratory kits were provided by  Roche Diagnostics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Advisory board fees from  Roche Diagnostics , research grant from  Abbott , speaker fees from Orion, all outside the present work. KP: Advisory board fees from  Roche Diagnostics (Finland). AM: lecture fees from  Novartis, Orion , and  Abbott , research grants from  Roche , and consultant fees from  Servier  and  Sanofi , all outside the present work. JL: Speakers bureau and consultancy fees:  AstraZeneca ,  Bayer ,  Boehringer-Ingelheim ,  Novartis, OrionPharma, Committee Sant'Andrea Hospital ;  Warsaw: Local Bioethics Committee of the Institute of The study  was approved by the  Danish Protection Agency  with reference number  GEH-2014-013 ; I-Suite number:  02731.
Effect of reactive oxygen species. The mean quantity of ROS in each sample was assessed using the specific ROS marker H2DCFDA. At 1 h, the mean quantity of ROS was significantly higher in sonicated groups than in DXR group and tend to be higher compared to non-treated group (p value = 0. 0015, post-hoc test p-value indicated on Fig. 7 ). At 72 h, the mean quantity of ROS was significantly larger for groups with DXR than for groups without DXR (p value = 0. 0009, post-hoc test p-value indicated on Fig. 7 ). The data may suggest two different mechanisms of ROS production, one short term due to acoustic cavitation, and one long term due to DXR. The results concerning mean intracellular quantity of doxorubicin, cell viability and growth index in each group were similar to those obtained in the previous experiments.
Reproducible generation of non-inertial cavitation. The cavitation device used in this study is composed of two confocal spherical PZ28 piezoceramic transducers (Ferroperm, Kvistgaard, Denmark) with curvature radius of 50 mm, separated by an angle of 90° and operated at 1. 1 MHz (Fig. 10 ). This configuration favors the occurrence of cavitation  55. The transducers were immersed in a tank filled with Ablasonic (EDAP-TMS, Vaulx-en-Velin, France), a cavitation-inhibitor liquid used to prevent acoustic cavitation outside the sonicated sample  56, 57. For treatment, a 2 mL safe-lock micro test tube (Eppendorf, Hamburg, Germany), containing 650 µL of cell suspension, was positioned at the focal zone of the confocal device (Fig. 10A ). The emission signal was generated with a National Instruments PXI-1031 device (National Instruments, Nanterre, France) driven by a LabVIEW software and powered by a 200 W amplifier (LA-200H EMV, Kalmus, Hong Kong, China).
After treatment, a volume of 20 μL of cell suspension was collected for cell counting to assess immediate mortality. Then, for each sample, a volume containing 100 000 cells was collected. Those cells were plated in a 24-well plate, supplemented with 1 mL of culture medium, DXR at 400 ng/mL was added for the DXR and US + DXR groups and cells were incubated for 72 h at 37 °C. To account for biological variability, this experiment was repeated six times, with 4 to 10 samples per group. Cell viability. Cell viability was assessed by flow cytometry using a FACS LSR II (BD Bioscience, Franklin Lakes, NJ) and data processed using the FACS DIVA Software. Cells were stained with necrosis marker DAPI (DAPI, Sigma-Aldrich, Saint Louis MO, USA, intensity measured with the 405 nm blue laser), and apoptosis marker Annexin V (Annexin V APC, Annexin V apoptosis detection kit APC, eBiosciences, Paris, France, intensity measured with the 633 nm red laser), and assessed viable if negative for both markers.
Acknowledgements This work was supported by the  LabEx DEVweCAN  ( ANR-10-LABX-0061 ) of the  University of Lyon , within the program " Investissements d' Avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR). Frederic Padilla  was supported by the  Merkin Fellowship  from the  Focused Ultrasound Foundation. The authors thank  Elisabeth Errazuriz-Cerda  ( CIQLE SFR Sante Lyon-Est ) for her help during transmission electron microscopy.