dataesr/scientific-paragraphs-categorization huggingface dataset:
J. -B. Melin  thanks  Monique Arnaud  for constructive discussions which helped to improve this article and for suggesting the acronym PSZSPT. He also warmly thanks the high school students  Julie Hebert ,  Aubin Mayer ,  Hugo Levandowski  and Anaëlle Meurant who helped him search the PSZSPT locations in the SIMBAD and  NED databases. A portion of the research described in this paper was carried out at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with the  National Aeronautics and Space Administration.
, 2010; Dale et al. , 2008a, b; Knab et al. , 2008; Mogollón et   al. , 2012). Data from the Helgoland mud area, North Sea (Table  2 ; row F)  (Henkel and Kulkarni, 2015) , the Arabian Sea oxygen minimum zone (OMZ) transect (Table  2 ; rows J, K, and L)  (Bohrmann and cruise participants, 2010a, b, c) , Bering Sea (Table  2 ; row M)  (Gersonde, 2009) , and Argentine Basin (Table  2 ; row N)  (Henkel et al. , 2011)  are presented in the PANGAEA database (see above). We use those site-specific datasets to inform our data-model analysis and to constrain OM reactivity and related benthic processes.
However, such datasets are often not available. For instance, the first efforts to quantify a and v parameter values, and thus reactivity, on the basis of observations solely focused on downcore TOC profiles  (Boudreau and Ruddick, 1991). Such an approach was instrumental for the development of the RCM and for producing the first large-scale dataset of a and v. However, the increasing availability and accessibility of multi-species datasets allow for the use of additional information that is available across different sites. Because OM heterotrophic degradation is the driver behind biogeochemical dynamics in marine sediments, downcore profiles of TEAs (e. g. SO 2- 4 ) (e. g. Bowles et al. , 2014; Jørgensen et al. , 2019b)  or reduced products of OM degradation (such as CH 4 and NH + 4 ) could be used as further constraints.
However, data availability is often still limited; therefore, it is important to identify a minimum set of observational data that are widely available and comparably easy to measure. We tested the suitability of different artificial porewater datasets for the inverse determination of apparent OM reactivity. Using an artificially generated dataset (see Supplement Sect. S3), we ran the BRNS in the same fashion as we did for the site-specific data-model approach (see below). Our sensitivity analysis confirms that when TOC is considered as a single constraint, multiple pairs of a and v pro-F. S. Freitas et al. :  New insights into large-scale trends of apparent organic matter reactivity duce equivalent TOC depth profiles (Supplement Fig. S1 ). Model results show that including SO 2- 4 depth profiles as an additional constraint (Supplement Fig.
85 'Golgotha' here means the entire Holy Sepulchre complex. 86 This is the second chapter of the document given to the author by the Syriac patriarch. The first chapter is the previous paragraph. 87 Amh. fetha nagast. The Law of the Kings is a Christian book of law, written in Geʿez (translated from Arabic) and applied in Ethiopia from the 16th century onwards. It deals with religious and civil matters. 88 Amh. māhmud. Perhaps it refers to the Ottoman Sultan Mahmud Khan i (1730-1754). 89 This paragraph concerns the ceremony of the Holy Fire (in Geʿez redata berhan 'Descent of the Light') which takes place annually at the Church of the Holy Sepulchre on the Orthodox Good Friday.
MATERIALS AND EQUIPMENT Equipment We use a custom-made illumination box containing an array of 24 Light Emitting Diode (LEDs) (488 nm) delivering 10 mW/cm 2 (light intensity measured using a ThorLabs-PM16-121-power meter). The 24 LEDs are made of Creeâ XLampâ XR-E LED (Figure  2 ). The details on how to build the light box along with the code used for programming is described here: https://github. com/ jvrana/OptogeneticsLightBox. Alternatively, a service for tailored made optogenetic devices is Store the buffer at 4 C for three to six weeks. CRITICAL: For SDS usage, wear personal protective equipment/face protection. Store the buffer at 18 C-25 C. CRITICAL: Store the buffer at 4 C for three to six weeks. The day of the experiment, add 50 mL of 2-mercaptoethanol (14. 3 M) per 950 mL of 2X Laemmli Sample buffer (Total volume 1 mL).
CRITICAL: Avoid multiple boiling and freezing cycles of your samples. 46. For western blot analysis, resolve proteins by SDS-polyacrylamide gel electrophoresis (SDS-PAGE). We recommend loading 2-4 mg of proteins in the ''Input'' control well. 47. For Mass spectrometry analyses, use up to 2 mg of proteins isolated by streptavidin pull down. Analyze raw mass spectrometry data using the MaxQuant software (version 1. 5. 5. 1) with standard settings. Use Perseus (version 1. 6. 1. 1) for graphical representation and statistical analysis. Perform a standard t test to evaluate differences of protein abundance between samples.
B. Electric field simulations In simplified 1D geometry of a dielectric sample in a quartz cuvette between two parallel conducting electrodes (as shown in Fig. 2 ), the electric potential is given by ΔV = -∫ ⃗ Ed ⃗ l. ( 1 ) Applying this to a filled quartz cuvette between two electrodes, ΔV = -2E 1 l 1 -E 2 l 2 = -2 E 0 ε 1 l 1 - E 0 ε 2 l 2 , (2) where E 0 is the field in free space, ε 1 is the dielectric constant of the quartz, l 1 is the wall thickness, ε 2 is the dielectric constant of the sample, and l 2 is the width of the sample. As the potential between the electrodes is known, Eq. (  2 ) can be rearranged to give the E 2 , the electric field in the sample, E 2 = -ε 1 ΔV 2l 1 ε 2 + l 2 ε 1. ( 3 ) As the geometry of the sample environment is somewhat more complicated than this 1D representation, a finite element analysis (FEA) model of the sample environment was constructed and simulations were performed with the software program ANSYS Maxwell to determine the magnitude and geometry of the electric field within various samples.
ACKNOWLEDGMENTS This work was funded by the  BMBF  (Grant No. 05K16KT1 ). Experiments at the  ISIS Neutron and Muon Source  were supported by a beamtime allocation No. RB1520013  from the  Science and Technology Facilities Council. The authors gratefully acknowledge  Herbert Zimmerman  for providing us with the perdeuterated liquid crystal and the  ILL Instrument Control Service  for their support before and during the experiment and thank  Frédéric Thomas  at the  ILL  for running the FEA simulations featured in this work. D. W. H. also thanks the Partnership for Soft Condensed Matter (PSCM) and, particularly,  Peter van der Linden ,  Diego Pontoni , and  Yuri Gerelli  for their helpful advice and use of the rapid prototyping facility. This work benefited from the use of the SasView application, originally developed under  NSF  Award No.
For instance, the mass redistribution potential induced by the tides on an object on or above the surface is given by the product of the Love number k 2 and the forcing potential. The Love number k 2 measured by MESSENGER is still subject to considerable uncertainty. Mazarico et al. (2014)  report a central value of 0. 451 with a recommended realistic range of acceptable values of 0. 43-0. 50. Verma and Margot (  2016 ) quote a similar central value and a recommended range of 0. 420-0. 465. The latest gravity solutions carried out by analyzing the whole MESSENGER radio science dataset, including the low-altitude campaign, show independent adjustments of the Love number k 2 = 0. 57 ± 0. 03  (Genova et al. 2019)  and k 2 = 0. 53 ± 0. 03  (Konopliv et al. 2020 ). These larger estimates, which were retrieved by accounting for radio tracking data more sensitive to the gravitational tidal response, suggest a warm and weak mantle  (Padovan et al.
2014). The uncertainties of these tidal measurements are affected by the MESSENGER orbit geometry (i. e. , high-eccentric orbit) and by the strong perturbations of the non-conservative forces on the spacecraft dynamics. BepiColombo's MPO will help enhance our knowledge of Mercury's tidal response by measuring the planetary gravity field from a low-eccentric orbit. The precise orbit determination of the spacecraft will be based on the processing of MORE radio tracking data and ISA observations to accurately measure the accelerations induced by non-gravitational perturbations, including solar, albedo, and thermal radiation pressure. This experiment configuration enables a significant refinement of the Love number k 2 and a first estimate of its phase lag  (Imperi et al. 2018) , which allows constraining the rheological properties of the mantle and outer core.
2018). Furthermore, independent estimates of Mercury's obliquity with gravity and altimetric data may provide information on the shape of the inner core and the core-mantle boundaries  (Peale et al. 2016). Although it is not expected that Mercury would show a measurable polar motion (0. 2 arcsec on the Earth), it is also desirable to constrain the displacement of the pole transversal to the Cassini plane to a comparable level of accuracy.
While a real, computable theory seems at this time difficult to achieve, we have at least, based on general considerations, a firm prediction, that γ < 1; disproving this constraint would constitute a major advance. The accurate tracking of BepiColombo will involve at least four bodies: the spacecraft, the Earth, the Sun and Mercury. Their masses result from different combinations of different binding energies -for the three big bodies, mainly the gravitational contribution. It will be interesting to test their separate compliance with the Weak Equivalence Principle, to wit, whether they fall with the same acceleration in the gravitational field. BepiColombo will be able to test the strong equivalence principle in the weak field regime. A comparison with the recent test carried out in a different regime with the data analysis of the triple pulsar system  (Archibald et al.
The attained range accuracies are similar to those of DSA-3. Although MORE science goals can be achieved using only one station, the benefits of using two antennas are obvious: a) larger flexibility in the scheduling of the antenna time; b) larger immunity to hardware failures; c) less sensitivity to local weather conditions; d) less sensitivity to possible systematic effects; e) easier identification of noise-related effects in the data analysis; f) improved accuracies in the determination of physical parameters of interest. The ground stations are expected to meet two crucial requirements for the Ka2 link: an Allan deviation of 6 10 -15 at 1000 s integration time and a station delay calibration of at least 0. 3 ns (9 cm). The requirements in the other two links are less stringent and fully compatible with the current performance of the ESA and DSN ground stations.
The KaT core digital architecture provides broad advantages over an analogue solution (such as the one used for the Cassini unit): • Optimization of carrier acquisition and tracking performance. • Inclusion of PN ranging processing capabilities (demodulation and remodulation). • Data rate flexibility with easy matched filtering implementation. • Design flexibility with receiver tuning based on programmable constants. • All-digital modulation capabilities based on Direct Digital Frequency Synthesis. Extensive performance tests carried out in thermal vacuum conditions have shown the KaT has an internal stability (Allan deviation) of ∼ 4 × 10 -16 at 1000 s integration time. Another crucial feature of the MORE KaT is the WBRS, based on a PN ranging modulation scheme up to 24. 3 Mcps (although also a lower chip rate at approximately 3.
The Ground System Since RS observables are generated at the ground stations, only a very small fraction of telemetry, such as equipment housekeeping parameters, spacecraft attitude measurements, maneuvers, and orientation of movable parts are of interest to MORE data analysis. (Mass history, also important, is estimated on ground by the flight dynamics team. ) The microwave signals are mixed to lower frequencies, where they are sampled, averaged, and recorded for later analysis. Two-and three-way uplink transmissions are modulated with ranging codes, allowing the determination of round-trip light times after correlation with the modulation on the downlink signal. RS data are acquired via two types of receivers, closed-and open-loop. In order to track a spacecraft signal carrier, the closed-loop receiver utilizes a phaselocked loop (PLL) that precisely measures and records the carrier's phase.
Tropospheric noise has two components, usually called "dry" and "wet". While the dry component can be accurately measured by means of barometric pressure and temperature measurements at the station, the wet delay due to water vapor, although smaller, is much more difficult to estimate. Humidity data and GNSS estimates are not adequate due to the usually poor mixing of water vapour. Its magnitude and time variability are strongly dependent on local weather, with typical path delays from 3 to 20 cm (for zenithal elevations). The use of water vapour radiometer (WVR) has proven effective in Cassini and Juno radio science experiments (see Figs. 6  and 7 ). An advanced WVR is in operation at DSS 25 and is expected to support MORE measurements in cruise. ESA has recently developed a microwave radiometer to be used for tropospheric calibrations at DSA-3.
Cruise After launch, BepiColombo underwent a Near Earth Commissioning Phase (NECP) to test the functionality of each subsystem and instrument on-board the spacecraft. The MORE commissioning, carried out on 9 December 2018, indicated that the KaT instrument was operating nominally. The MORE team performed a test in May from ESA ESTRACK DSA-3, located in Malargue, Argentina and in August from NASA DSN DSS-25, located in Goldstone, California, to verify the in-flight performances of the Ka/Ka radio link  (Cappuccio et al. 2020b). In 2020, the MORE team executed the End-to-End (E2E) test of the tracking system. The purpose of this test is to demonstrate the operations of the full experiment setup. The data from the ESA DSA-3 are collected during 18 passes: 9 in September 2020 and 9 in November 2020.
The capability of the complete radio link will also be tested from the NASA DSS-25 with an additional 4 passes in November-December 2020, in addition to 7 shadow passes (3-way) in parallel with the DSA-3 2-way passes. These tests are performed with the spacecraft in a quiet dynamical state in order to minimize buffeting noise and to provide the dynamical coherence of the orbit. In the orbital phase around Mercury, ISA readings will be used to compensate for non-gravitational acceleration mainly due to solar radiation pressure  (Iafolla 2010). During the E2E test the ISA accelerometer data are collected to verify the in-flight performances. In April 2020 BepiColombo completed the Earth flyby. The MORE team used the Xband data from the DST to assess if a good orbital fit in unusual geometrical conditions and with a standard dynamical model was possible.
Analyzing each single conjunction, SSC #1, #3 and #5 prove to be the most convenient because of the specific configuration. Exploiting the joint dataset of all conjunctions the accuracy attainable on γ lays in the range [6-13] ×10 -6. In addition to the effect on the propagation of the radio waves, γ intervenes in the equations of motion of Mercury contributing to the advance of the perihelion. The novelty of MORE with respect to previous experiments (Viking, Cassini) aiming to constrain the value of γ  (Bertotti et al. 2003)  relies on the possibility of measuring both propagation and dynamical effects, thus decorrelating γ from the other parameters responsible for the perihelion advance (Eq. (  66 ) in Will 2014) (i. e. the solar oblateness J 2 and the PPN parameter β). Mercury, as seen by the Earth, undergoes three SSC per year, allowing MORE to perform additional SCE during the hermean phase.
Conclusions This paper is intended to provide a reference for the overall setup of the Mercury Orbiter Radioscience Experiment (MORE), including the novel radio system, the in-flight operations during cruise and at Mercury, and summarize the expected results in geodesy, relativity and space navigation. Together with the other onboard instruments, especially the Italian Spring Accelerometer (ISA), the BELA laser altimeter, the MERMAG magnetometer and the HRIC camera, MORE is set to improve our knowledge of the interior structure of the planet Mercury, answering many questions left open by the extraordinary MESSENGER mission. This work is based on the established hardware configuration and the predictions of the many numerical simulations carried out over the past years. We are also aware that parts of its content will be superseded once MORE and BepiColombo will start producing new data and new discoveries.
In the framework of the EUMETSAT Polar System-Second Generation (EPS-SG) preparation, a new generation of the Infrared Atmospheric Sounding Interferometer (IASI) instrument has been designed. The IASI-New Generation (IASI-NG) will measure radiances at a doubled spectral resolution compared to its predecessor and with a signal-to-noise ratio improved by a factor of 2. The large amount of data arising from IASI-NG will present many challenges for data transmission, storage and assimilation. Moreover, the full set of measured radiances will not be exploitable in an operational numerical weather prediction (NWP) context. For these reasons, an appropriate IASI-NG channel selection in needed, aiming to select the most informative channels for NWP models. Therefore, the standard iterative channel selection methodology, based on the optimal linear estimation theory and assuming spectrally correlated errors, has been applied to a set of simulated data of the IASI-NG spectrum.
Thanks to the instrument's excellent signal-to-noise ratio, reactive chemical species which were previously considered not to be measurable from space (i. e. , ammonia) have been measured. Other major atmospheric events, such as volcanic eruptions, fires, dust or pollution, can also be monitored thanks to the data acquired through this IR sounder  (George et al. , 2009; Karagulian et al. , 2010; Capelle et al. , 2014). Given its high potential demonstrated over the years, a new generation of the IASI instrument has been designed within the framework of the preparation for the next European polar-orbiting program. The IASI-New Generation (IASI-NG), to be launched on board the MetOp-Second Generation (MetOp-SG) series in 2022, will be characterized by improved spectral and radiometric characteristics relative to IASI.
It will measure at 16,921 wavelengths (or channels) with each sounding pixel benefiting from a spectral sampling of 0. 125 cm -1 , a spectral resolution of 0. 25 cm -1 after apodization and a signal-to-noise ratio improved by a factor of 2 compared to its predecessor  (Crevoisier et al. , 2014; Bermudo et al. , 2014). Measurement precision will also be improved compared to IASI. IASI-NG characteristics will lead to further improvements in detection and retrieval of numerous chemical species and aerosols, and in temperature and water vapour retrievals. The large amount of data resulting from IASI-NG will present many challenges for data transmission, storage and assimilation. Moreover, the total number of channels will not be exploitable in an operational NWP context and the choice of an optimal data subset is needed.
On the other hand, data compression using a principal component (PC) analysis is already used as one way of disseminating IASI data. Nevertheless, no NWP centre currently assimilates PC scores despite many investigations  (Matricardi and McNally 2014). This means that spectra would need to be reconstructed from PC scores before assimilation. For all these reasons, an appropriate IASI-NG channel selection must be undertaken, aiming to select the most informative channels to be used in NWP models. Several channel selection methods have been developed in the last two decades. Some of them are based on statistical analysis and information content theory  (Rabier et al. , 2002; Fourrié and Thépaut 2003; Collard 2007; Ventress and Dudhia 2014; Noh et al. , 2017). Some others rely on evaluating the radiances' response to the perturbation of specific chemical species and atmospheric variables, which allows the detection of spectral sensitivity features  (Susskind et al.
, 2003; Gambacorta and Barnet 2012). The objective of the present study is both to present a methodology to select channels using modern tools and to propose a first IASI-NG channel selection in an NWP context. Such a selection could be used either for dissemination purposes or as a basis for further channel extraction for assimilation. On the other hand, the methodology developed here could be exploited in other future studies on IASI-NG or other instruments. Our work has been carried out on an observation database of simulated radiances for IASI and IASI-NG  (Andrey-Andrés et al. , 2018) , using a method based on information content theory  (Rodgers 1996). Additionally, one-dimensional variational (1D-Var) assimilation experiments have been carried out in order to evaluate the impact of the channel selection on temperature and humidity retrievals.
Spectral area pre-selection Although the spectral coverage will remain unchanged, the IASI-NG spectrum will be split into four bands, compared to three bands for IASI. The limits of the first two bands will be slightly modified, whereas the IASI band 3 will be split into two new bands for the new generation instrument. Limits and characteristics of these four different spectral areas are displayed in Table  1. For IASI-NG, in order to compute the wave number  having the channel number n, the following formula can be used: 𝜈 = 0. 125(n -1) + 645. 000. (1) For this study, we focused on bands 1 and 2. Band 1 is mainly affected by the influence of CO 2 , surface temperature and O 3. In band 2, among the other gases, water vapour absorption predominates. These features make them the most relevant bands for operational data assimilation in an NWP context.
Observation-error estimation The observation errors consist of instrument noise, error in the observation operator, and representativeness and pre-processing errors. They can be split into systematic and random components. Systematic errors are usually biases that are corrected before the data are assimilated. As a consequence, the observation errors contained in the R matrix are the random ones. Most of the channel selection methods employed for the previous generation of the atmospheric sounders primarily used matrices containing only the instrument noise, which was often roughly inflated in order to take the other errors into account. These matrices were diagonal ones (e. g. ,  Rabier et al. , 2002; Collard 2007). Moreover, in the case of IASI, the measurements are apodized. This introduces inter-channel correlation and produces a matrix with non-zero covariance bands.
CASE-STUDY The actual data from IASI-NG will be available only in a few years. Accordingly, in order to be able to perform a selection among its channels, a carefully simulated dataset is necessary. For this purpose, a database of simulated observations has been built by  Andrey-Andrés et al. (2018). The database contains simulated observations using IASI's scan geometry for IASI and two possible versions of IASI-NG (KBr and ZnSe evaluated prism materials). It covers four dates in the middle of each season from 2013 in order to provide a maximum of meteorological variability: 4 February (Northern Hemisphere winter), 6 May (NH spring), 6 August (NH summer) and 4 November (NH autumn). A total of 5,242,047 simulated perfect measurements, in day/night illumination and sea/land conditions, is obtained through the use of the RTTOV (Radiative Transfer for TOVS) radiative transfer model, version 11.