dataesr/scientific-paragraphs-categorization huggingface dataset:
This work fulfilled for the GP, the Irish Medical Council requirement to conduct an annual audit. Eligible patients were identified as those patients who were coded for stroke or TIA or those who were not coded but had a hospital diagnosed stroke or TIA in their discharge summaries from specialists. These events were classed as either ischaemic stroke, haemorrhagic stroke, TIA or unknown. If patients had more than one of these events, they were classed based on their most severe event. Disease coding typically categorised the type of each stroke, where this was not available or ambiguity existed, hospital discharge summaries and consultant reports were examined to clarify the diagnosis. All practices used electronic health care records, but used a variety of software systems; Socrates®, Health One™ or Helix Practice Manager.
Strengths and limitations We believe this is the first estimate of blood pressure control in a cohort of patients post stroke/TIA in primary care with specific consideration of antihypertensive drug dosing. A further strength of this study was that all data was collected at the level of the patient's file in their own general practice. Limitations of this study include the use of 10 general practices from the same geographical area. The crosssectional design took in to account BP readings from one point in time only and did not take in to consideration out of office BP monitoring or indeed the other factors that may influence recurrent stroke (smoking, hyperlipidaemia, obesity, diabetes, atrial fibrillation and sedentary lifestyle). As this was a retrospective study, there was no common protocol for the measuring and recording of office BP.
, 2017) ; even repeated smaller events can stress transformers and reduce their operational lifetime  (MacManus et al. , 2017). Despite its significance, the LTI is the least measured and understood of all atmospheric regions; in particular, the altitude range from ∼ 100 to 200 km, where the magnetospheric current systems close and where Joule heating maximizes, is too high for balloon experiments and too low for existing LEO satellites due to significant atmospheric drag. Furthermore, few spectral features emanate from this region; these have been exploited by recent remote sensing spacecraft and from ground instrumentation, but despite these advances, this region remains under-sampled with many open questions. For example, no dataset is currently available from which the LTI energy budget can be confidently derived on a global basis.
Some major species composition information is obtained by a combination of ultraviolet (UV), infrared (IR) and Fabry-Pérot interferometer (FPI) measurements, but there is a significant gap in the obtainable profiles at ∼ 100-200 km due to a lack of appropriate emissions for observation. It is also noted that different observation methods may produce large deviations (even orders of magnitude) in estimates of key parameters in the LTI, such as conductivity, ion drifts and neutral winds, with no baseline dataset for comparison.
geosci-instrum-method-data-syst. net/9/153/2020/ Geosci. Instrum. Method. Data Syst. , 9, 153-191, 2020 of Joule heating estimates over the rocket launch site, without information on the latitudinal distribution or temporal evolution. Together with rocket flights, datasets that have traditionally been used for Joule heating estimates include measurements from ground radars  (Ahn et al. , 1983; Aikio et al. , 2012)  and from low-altitude satellites, such as AE-C  (Foster et al. , 1983) ,  DE-1 and DE-2 (Gary et al. , 1994)  and Astrid-2/EMMA  (Olson et al. , 2004). Of these measurements DE-1 and DE-2 were the only spacecraft that performed simultaneous neutral wind and electric field measurements; however, they only went down to 567. 6 and 309 km, respectively, and even though the region that the DE spacecraft sampled is certainly heated up after the deposition of energy in the E-region, it is well above the region where Joule heating maximizes.
Solar activity is plotted in terms of daily (gray crosses) and average (gray lines) values of the F10. 7 index. including propellant mass) and initial spacecraft apogee selection. In the background of Fig. 5 , the expected solar activity index F10. 7 is calculated by Monte Carlo sampling of the past six solar cycles. Lifetime simulations were performed using ESA's DRAMA software, assuming a drag coefficient of 2. 2 (suitable for a cylindrical satellite) and a total satellite drag area of 0. 6 m 2 (including the electric and magnetic field booms). It is noted that increasing apogee altitude increases the mission lifetime but leads to enhanced radiation exposure in the inner radiation belt. This should be studied as part of a trade-off analysis to be conducted during the initial Daedalus mission phases.
Ram Wind Sensor (RWS) and Cross-track Wind Sensor (CWS) Studies of the kinetics of neutral particle flow in the free molecular flow regime of the satellite environment led early on to various concepts for neutral wind measurements. Based on these concepts, measurements have since resulted in a large body of data of high spatial resolution. These data have revealed an unexpectedly complex and variable neutral atmo-sphere, a signature of the deposition of large and highly variable quantities of energy. To resolve neutral winds, two sensors will be used on Daedalus: the Ram Wind Sensor (RWS) and Cross-track Wind Sensor (CWS). Description of the RWS. The Ram Wind Sensor (RWS) will obtain the neutral wind speed along the ram direction of Daedalus by performing a retarding potential energy analysis on an ionized fraction of the flowing neutral gas.
Accelerometer (ACC) The accelerometer onboard Daedalus will measure nongravitational accelerations such as air drag, Earth albedo and solar radiation acting on the satellite. The direct measurement of acceleration α due to air drag can in turn be used to derive the total atmospheric mass density ρ through the fundamental relationship α = 1/2ρV 2 C d A/ m, where C d , A, m and V are the s/c coefficient of drag, cross-sectional area, mass and velocity, respectively  (Hedin, 1991). Accelerometer data can also be used to derive winds in the thermosphere  (Sutton et al. , 2007; Doornbos et al. , 2010; Dhadly et al. , 2018). Using expected values of these parameters and obtaining values for ρ from the NRLMSISE-00 atmosphere model, it is calcu- lated that the drag acceleration will be on the order of 10 -7 g at 500 km and 10 -3 g at 120 km.
Magnetometer (MAG) High-precision measurements of in situ magnetic fields are crucial for Joule heating estimates, deriving current structures in the ionosphere, and studying and interpreting EPP fluxes and magnetosphere-ionosphere current systems. The Daedalus magnetometers will measure DC magnetic fields. DC magnetic field measurements are a required measurement in Eqs. (  10 ) and (  14 ) of Joule heating, Eq. (  15 ) of Pedersen conductivity, and Eq. (  22 ) of ion-neutral collision frequency; they are also needed for determining the pitch angles of precipitating charged particles, as measured by the EPDS. DC magnetic field measurements also allow for a quantitative determination of the upward and downward currents traversed by the instrument: there are well-established methods for extracting current measurements from in situ magnetometer data (e.
However, their role is significant as a proxy for EPP estimations, and simultaneous measurements of N e at different altitudes along the same orbit (even with the implications of the phase difference between the two satellites, as described in Sect. 4. 3. 5) can provide significant improvements to models that have been used as a proxy for EPP by improving the assumptions made therein (see, e. g. ,  Rees, 1963; Schunk and Nagy, 2004; Semeter and Kamalabadi, 2005). Furthermore, in situ measurements of N e would also be relevant for studying ionization and the energy input by solar EUV. For example,  Lin and Chu (2017)  recently performed an extensive modeling but could only compare to the ∼ 40-year-old AE-C data, which reached down to 135 km. The combination of N e from the main satellite at 150 km perigee and the subsatellite at 120 km perigee would provide a novel dataset from which to improve such modeling.
C-NOFS targeted the effects of ionospheric activity on signals from communication and navigation satellites. Similarly to Daedalus, it performed in situ measurements of ion and neutral velocities as well as electric fields using six booms from an elliptical orbit; however, it had an equatorial orbit, and its perigee was 405 km, much higher than It is also noted that the dynamic range of some of the key measurements of the AEs, such as mass spectrometer composition, made the data interpretation difficult at low altitudes. Remote sensing missions of the LTI include UARS (e. g. , the WINDI instrument looked at winds and temperature at low and middle latitudes at 85 to 250 km) and TIMED (which obtained O, O 2 , N 2 and ion density during daytime). These are among the primary sources of information on the LTI; however, for many key processes simultaneous measurements of all key geophysical variables are needed.
, 1985; Deng et al. , 1995; Wu et al. , 1996)  to calculate ionization, heating and composition changes, which can be compared with observations of thermospheric temperatures. These models can use along-track data to derive the global EPP heating. A comparison with observations of thermospheric temperature can lead to estimates of global Joule heating based on the differences between EPP models and observations. Daedalus data will be assimilated into TIE-GCM and other ionosphere-thermosphere models to provide accurate calculations of global Joule heating and EPP heating. At high latitudes, Daedalus data will be used to build AMIE (Assimilative Mapping of Ionospheric and Electrodynamics) convection maps  (Richmond, 1992). Thus, an advancement of EO capabilities is that Daedalus measurements will enable the calibration, assimilation and accurate driving of upper atmosphere models.
Acknowledgements. Mark Clilverd  would like to acknowledge the  National Environment Research Council Highlight Topic  grant  NE/P10738X/1  ( Rad-Sat ) and  National Environment Research Council  grant  NE/R016455/1  for funding. Financial support. This work has been supported in part by an  ESA  contract (grant no. 4000127346/19/NL/IA ) and  DUTH  (project.
Accurate Fourier-transform spectroscopic absorption measurements of vacuum ultraviolet transitions in atomic nitrogen and carbon were performed at the Soleil synchrotron. For 14 N transitions from the 2s 2 2p 3 4 S 3/2 ground state and from the 2s 2 2p 3 2 P and 2 D metastable states were determined in the 95 -124 nm range at an accuracy of 0. 025 cm -1. Combination of these results with data from previous precision laser experiments in the vacuum ultraviolet range reveal an overall and consistent offset of -0. 04 cm -1 from values reported in the NIST database. The splittings of the 2s 2 2p 3 4 S 3/2 -2s2p 4 4 PJ transitions are well-resolved for 14 N and 15 N and isotope shifts determined. While excitation of a 2p valence electron yields very small isotope shifts, excitation of a 2s core electron results in large isotope shifts, in agreement with theoretical predictions.
I. INTRODUCTION The determination of level energies in first row atoms critically relies on accurate spectroscopic measurements in the vacuum ultraviolet (VUV) region below the atmospheric absorption cutoff. The present study applies a unique Fourier-transform spectroscopic instrument in combination with synchrotron radiation to access this wavelength range at high resolution and accuracy for improving the atomic level structures of N and C atoms, including isotopic effects. The currently available level energies and line classifications for the N atom, compiled in the comprehensive NIST database  [1] , mostly originate from the work of Eriksson and coworkers from late 1950s in combination with the work by Kaufman and Ward  [2]. Eriksson measured N I transitions between 113. 4 -174. 5 nm at about 0.
1 cm -1 accuracy and constructed the atomic level structure, also including information on transitions between excited states in the visible and IR region  [3, 4]. Kaufman and Ward measured the 2p 3 2 D J -3s 2 P J and 2p 3 2 P J -3s 2 P J transitions to extend the knowledge of the level structure of the ground configuration at better than 0. 04 cm -1 accuracy  [2] , also including the forbidden transition 4 S 1/2 -2 P J measured by Eriksson. Further analyses were performed by Eriksson  [5, 6] , and a compilation was made by Moore  [7] , now used as a primary reference in the NIST database. Eriksson published an extensive analysis with newly determined energy levels at an uncertainty of 0. 003 cm -1  [8]. More recently, Salumbides et al. [9]  measured 12 transitions from the ground state at around 96 nm using VUV precision laser spectroscopy with 0.
Also shown is the reference Kr I used for calibrationo Here again a systematic offset is found, now positive and of opposite sign at 0. 078 cm -1 , again corresponding to 1. 5 σ of combined uncertainties. The same systematic offset of -0. 07 cm -1 is also found when comparing the results of the VUV laser measurements  [9]  with those of Kaufman  [2]. Two additional transitions are observed near 87439 cm -1 , which we assign as 2p 3 2 P 1/2 , 2 P 3/2 -( 1 S) 3s 2 S 1/2. Eriksson first identified a line at 114. 3649(2) nm, or 87439. 42(15) cm -1  [3]. From the level energies reported in the NIST database frequencies for these two transitions can be computed, and these predictive results are found to be well in agreement with the present direct measurements (see Table  II ). The fine-structure splitting of 2p 3 2 P 3/2 -2 P 1/2 is determined to be 0.
IV. DISCUSSION A. Level energies of 14 N I Three transitions from the metastable 2s 2 2p 3 2 D J state, the transitions 2 D 3/2 -3d 2 D 3/2 , 2 D 5/2 -3d 2 D 5/2 and 2 D 3/2 -3d 2 F 5/2 , share their excited state in the high precision VUV laser measurements of Ref. [9]. In combination with those laser measurements, the level energies of all states can be fitted using LOPT program  [34]. Table V lists the level energies of 25 states and makes a comparison with values from the NIST database. A global and consistent negative offset, of -0. 04 cm -1 , is observed. For the 2p 3 2 D J metastable states larger deviations are found of size -0. 07 and -0. 09 cm -1. The determination of 2 D J level energies presented in the NIST database is likely based on the VUV measurements by Kaufman and Ward  [2] , which is determined by taking combination differences of transitions 2 D J -3s 2 P J and 2 P J -3s 2 P J and the forbidden transition 4 S 3/2 -2 P J measured by Eriksson.
V. CONCLUSION Accurate measurements of transition energies in nitrogen and carbon atoms were obtained at an absolute accuracy of 0. 025 cm -1 using VUV Fourier Transform spectroscopy with a synchrotron radiation source. For 14 N and 15 N, transitions originating from the ground 2s 2 2p 3 3 P states as well as from metastable states 2s 2 2p 3 2 D and 2s2p 3 2 P states are observed. For 12 C and 13 C, transition energies for 2s 2 2p 2 3 P J -2s 2 2p3s 3 P J lines were measured. The comprehensive dataset for N I is included in a reevaluation of the level energies of the excited states, in combination with data from a previous laser-based precision study  [9]. This results in an averaged shift of -0. 04 cm -1 with respect to the level energies reported in the NIST database  [1]. The determination of isotope shifts for carbon and nitrogen in this study will be useful in assessing the effectiveness of various strategies in ab initio calculations for many-electron atoms in particular towards the treatment of electron correlation.
643(72) 3d 2 F 5/2 85577. 230(25) 85577. 181(73) 2 D 3/2 3d 4 P 5/2 85591. 960 (25) 85591. 933(73) 3d 2 D 3/2 85886. 730 (25) 85886. 702(66) 5s 2 P 1/2 90802. 570 (25) 90802. 522(66) 4d 2 F 5/2 91053. 168 (25) 91053. 04(17) a 4d 4 P 5/2 91066. 829 (25) 91066. 64(17) a 2 P 3/2 2 P 1/2 ( 1 S) 3s 2 S 1/2 87439. 234(25) 87439. 252 b 87439. 717(25) 87439. 638 b [5]easured frequency presented in Ref. [5]. b Calculated frequency from NIST database. 2 D.
A A positive control experiment. SARS-CoV-2 readily targets ciliated human respiratory epithelial cells (hRECs). Acetylated a-tubulin labels cilia. Arrows point SARS-CoV-2-positive cells labeled by AB4 (green). Figures display scale bars. Bar diagram at right quantifies frequencies of SARS-CoV-2-positive cells in hRECs. At least six hREC sections from three (n = 3) independent samples were examined. Data presented as mean AE SEM. B Mock organoids of two age groups Day-15 (i) and-60 (ii) display typical cytoarchitecture of brain organoids. L, lumen, VZ, ventricular Zone is containing compact and palisade-like elongated nuclei of neural progenitor cells (NPCs, blue) and CP, a cortical plate containing TUJ-1-positive neurons (magenta). Note a distinct difference TUJ-1 labeling pattern between younger (Day-15) and older (Day-60) brain organoid.
Statistical analysis The statistical analyses were performed using GraphPad Prism version 8. All experiments were performed at least in triplicates, and the statistical significance of each dataset was analyzed using Student's t-test followed by Welche's correction and non-parametric one-way ANOVA followed by Tukey's post hoc test. For immunofluorescence-based experiments, we randomized the samples to avoid any bias. The values are expressed as mean AE SD or SEM. Independent experiments have been represented by "n".
Acknowledgements We want to thank  Dr. Boris Görg  for offering generous support with their microscope facility. We want to thank  Ms Gladiola Goranci  and  Nazlican Altnisk  for their excellent technical assistance. This work was financially supported by a grant from  Fritz-Thyssen Foundation and Foundation  and by the  Jürgen Manchot Foundation. We would like to thank the diagnostics department of the  Institute of Virology, University Hospital Düsseldorf. Open access funding enabled and organized by Projekt DEAL.
Materials and methods Five stainless steels are selected in this study, namely 316L, 316LN, Nitronic60, AISI660 (austenitic stainless steels) and Uranus45 N (duplex austenite-ferrite). These grades differ by their chemical composition, crystallographic structure and mechanical properties, as presented in Table  1  and Table  2. Most data are coming from ThyssenKrupp provider, while surface hardness and grain size are determined experimentally. Surface hardness is determined by nano-indentation using a Berkovich tip with an indentation depth of 1 μm and a peal hold time of 10 s. Grains size is measured by Electron BackScatter Diffraction (EBSD) realized on as-received material. Electron BackScatter Diffraction (EBSD) investigations are performed on as-received materials as well as galled samples.
After galling test, the occurrence of galling is determined using ASTM G98 8. 9 standard. This standard indicates that a sample is galled if any macroscopic surface modification apart from scoring and surface waviness is to be seen with unassisted visual observation. In situ acoustic emission measurements could confirm the occurrence of galling, as proposed in Saidoun et al. [24]. Surface topography measurement are performed by non-contact 3D profilometry Sensofar S Neox. Material transfer associated with galling is confirmed by Energy-Dispersive Spectroscopy (EDS) on both surfaces. Microscale observations are realized by Scanning Electron Microscopy (SEM) observation on Zeiss Σigma microscope, a current of 25 kV is used for both imaging and EBSD mapping. The EBSD patterns acquisition are made with the software Nordif UF1100 and the corresponding mapping done by OIM Data collection 5.
However, no data could be found in the literature concerning the martensite transformation of other stainless steel grades during galling test. In order to study the transformed phases, EBSD analyses are performed on galled samples of each austenitic grades. From now on, results are shown for one grade of each galling category: Nitronic60  (tolerant galling), AISI660 (moderate galling) and 316L (severe galling), which present the most representative case. For Nitronic60 (Fig. 13a ), ε martensite is visible in thin laths. No evidence of α' martensite has been found for this grade. As opposite, α' martensite is observed with a pseudo-spherical shape for 316L (Fig. 13b ) while no ε martensite could be found. No martensitic transformation has been observed for AISI660 using EBSD analysis. It can be concluded that for Nitronic60 (tolerant galling), austenite is transformed into hexagonal compact martensite, while 316L and 316LN (severe galling) form pseudo-cubic body centered martensite.
Acknowledgement The authors would like to thank the  Hauts-de-France Region (France)  and the  European Regional Development Fund (ERDF)   2014/2020  for the funding of this work. The authors would also like to thank  David CAZE  ( CETIM Senlis ) for galling test realization. Special thanks go to  Abdelali OUDRISS  and  Xavier FEAUGAS  from  Université de La Rochelle  for TEM investigations and exploitation.
Solar wind ion irradiation continuously modifies the optical properties of unprotected surfaces of airless bodies in the Solar System. This alteration induces significant biases in the interpretation of the spectral data obtained through remote sensing, and it impedes a correct estimation of the composition of the sub-surface pristine materials. However, as the alteration of the surface is a function of time, an in-depth understanding of the phenomenon may provide an original way to estimate the weathering age of a surface. Laboratory experiments show that mid-and far-IR bands are very sensitive to space weathering, as they are significantly modified upon irradiation. These bands can thus constitute a reliable proxy of the time-bound effects of irradiation on an object. We show that the detection of irradiation effects is within the reach of IR spectral resolution of the OSIRIS-REx mission and of the future James Webb Space Telescope.
A similar procedure to determine the peak positions was applied to remote sensing data of Bennu and Hektor asteroids (see Section 4) and an additional double-check was obtained from polynomial fits around the center of the bands. In our microscopes we used Schwarzschild objectives, which accept photons in a large range of angles at all azimuths. The geometry of the spectral measurements can influence the spectral shape  (Salisbury et al. 1991; Salisbury 1993) , thus a direct comparison between reflectance and emissivity spectra must be taken with great care. In this paper we do not try to necessarily find the best laboratory match to asteroid spectral data, but we rather focus on relevant modifications of spectral features induced by ion irradiation. Irradiation experiments and IR spectral measurements were performed in two different laboratories, and the spectra were measured ex situ in laboratory air.
FIR spectral effects of He implantation in carbonaceous chondrites We report in Fig. 1  the new laboratory spectra of virgin and irradiated meteorites measured in the FIR range. In Fig. 2  we illustrate the combination of FIR and MIR ranges, as described in Section 2. 2, with the examples of a meteorite whose matrix is rich in hydrated minerals (C2-ung Tagish Lake) and a meteorite whose matrix is rich in anhydrous phases (CO3 FM95002). The full collection of combined MIR-FIR spectra will be available at the DAYSY spectral database hosted by the SSHADE  (Schmitt et al. 2018 ) Solid Spectroscopy database infrastructure (www. sshade. eu). Different classes of carbonaceous chondrites have different IR spectra  (Salisbury et al. 1991; Beck et al. 2014; Vernazza et al. 2017; Hamilton et al. 2018 Hamilton et al.