dataesr/scientific-paragraphs-categorization huggingface dataset:
The Δ rpoS::kanR-ccdB cassette was then replaced by an otherwise wild type rpoS sequence to which an additional sequence coding for a 6-histidine tag (6xHis-tag) had been added by PCR amplification, using the rpoS_IF and rpoS_IR primers (Supplementary Table  S1 ). To this aim, DY330 cells carrying the rpoS knockout were transformed by electroporation with a linear DNA fragment encoding for the rpoS His6 gene, carrying the His-tag at the 3` end. Transformant selection was performed on M9 minimal medium agar plates containing 0. 2% rhamnose and 0. 01% biotin: due to the toxicity of the ccdB gene in the presence of rhamnose, only the cells in which an allele replacement has taken place are able to grow on this medium. The rpoS His6 allele was P1-transduced into MG1655 carrying the rpoS::kan-ccdB knockout, again selecting for loss of the ccdB gene by plating on M9 minimal medium agar plates containing 0.
Two pools of IP DNAs were produced. Prior to sequencing libraries construction, quantitative Real Time reverse transcriptase-PCR (qRT-PCR) was carried out to assess the enrichment of the promoter region of the rpoS-dependent dps gene in the immunoprecipitated samples in comparison to the Input sample. The sequences of the primers used for qRT-PCR are listed in Supplementary Table  S1. Library preparation and sequencing procedure. Illumina libraries were prepared either from 5 ng of each of the two pools of immunoprecipitated-DNA (RpoS-IP) or from 5 ng of the two control DNA (Input) following the Illumina TruSeq ChIP-seq DNA sample preparation kit; then each library was sequenced in a lane of a single strand 51 bp Illumina run on a GAIIx sequencer. Raw data are publicly available at Sequence Reads Archive under accession number BioProject SRP041323; BioSample SRS595203; Experiment SRX523029; Run1 SRR1265068; Run2 SRR1271103.
Statistical and bioinformatic data analysis. Raw reads were mapped against the Escherichia coli MG1655 genome using Bowtie  45  with zero mismatches. The resulting BAM files were processed using SAMtools  46  and BEDTools  47. The quality of each sequenced sample was checked using cross-correlation analysis implemented in spp R package  48. ChIP-seq peak calling was performed using CisGenome  12  by imposing default parameters. Input data (control DNA) was used to model the background noise. Determination of rpoS-dependent gene expression in vivo. For all gene expression experiments, bacterial strains were grown in LB medium to OD600nm = 3. 0. For qRT-PCR, RNA was extracted and experiments performed as previously described  49  , using 16S RNA as reference. Primers used in qRT-PCR experiments are listed in Supplementary Table  S1.
ASM payload, operating principle description, and standalone performances As the magnetic scalar reference of the ESA Swarm mission  (Friis-Christensen et al. 2006) , the Absolute Scalar Magnetometer (ASM) developed by CEA-LETI with the support of CNES provides continuous absolute measurements of the Earth's magnetic field strength B 0 for science purposes and in-flight vector calibration of the Vector Field Magnetometer (VFM) fluxgate instruments. Given its key role for the mission and considering the required data availability, a cold redundancy of the ASM has been implemented. Two complete and independent ASM instruments are flown onboard each of the three satellites of the Swarm constellation. The ASM electronics are located within the satellite main body, while the two ASM sensor heads are mounted at the tip of the 4-m satellite boom and linked to their respective electronics, thanks to dedicated electrical and optical harnesses.
This vector mode has been used on Swarm, and the amplitudes and frequencies of these modulations have been set to around 50 nT and respectively 7. 93, 10. 99, and 12. 97 Hz. To ensure proper vector measurements, however, and avoid interferences and aliasing errors in these measurements, it is mandatory to check in-flight that no specific noise is present around these f mi vector modulation frequencies. During commissioning, the burst mode has thus been operated to both estimate the scalar noise level of all instruments and assess the possible presence of signals in the vicinity of the vector modulation frequencies previously selected on-ground. This check confirmed that, in this vector mode, the ASM could deliver both scalar and vector data sampled at 1 Hz and low-pass filtered at 0. 4 Hz, with no modification of the scalar data quality and characteristics (i.
The geographical repartition of where these perturbations can occur is displayed in Figure  4. These fully predictable distortions are also flagged in the vector datasets. Once properly flagged, data affected by motor activations and heater perturbations can be replaced by interpolated data in the burst datasets. A noise spectrogram of such cleaned burst data is displayed in Figure  5  for a long acquisition period. As can be seen, only the previously detailed ASM RF modulation aliasing (around 30 Hz) and ASM internal laser D 0 wavelength control loop (3. 05 Hz and harmonics) signatures remain permanently, while noise bursts occur from time to time, with signatures on the spectrogram corresponding to vertical lines (mostly at high latitudes). A scalar noise analysis in the [35-to 40-Hz] frequency band performed on corrected burst mode noise spectrograms for all instruments during commissioning reveals scalar resolutions of respectively 1.
3, 2. 4, and 4. 5 nT on Swarm Alpha, Bravo, and Charlie. While nominal instruments on Swarm Alpha and Bravo  exhibit similar vector noise characteristics, the one on Swarm Charlie shows almost twice as much noise, a difference that cannot just be attributed to the higher scalar noise level of this instrument compared to those of Alpha and Bravo. The flag-filtered data exhibit reduced σ characteristics of respectively 1. 6, 1. 9, and 4. 3 nT. For the ASM instruments on Swarm Alpha and Bravo, these characteristics are in close agreement with those expected, given the intrinsic ASM vector noise. For the instrument on Swarm Charlie, the flag-based data selection does not lead to much improvement, revealing a vector noise level significantly higher than expected, given the scalar noise level otherwise measured on this instrument.
At this stage, no satisfactory explanation for this specific behavior has been found. An interesting analysis of the scalar residual behavior can also be provided by the Allan variance  (Allan 1966) , which is a commonly used time domain analysis technique for assessing the stability of time references (clocks) and inertial sensors (e. g. , accelerometers and gyroscopes). It consists in representing the root mean square random drift errors of a measurement as a function of averaging times. It thus provides information on the nature and magnitude of various sensor noise and drift terms. Figure  7  displays the Allan variance analysis of the ASM scalar residuals, which we also compare to the ASM-VFM scalar residuals, defined as the difference between the ASM scalar measurements and the modulus of the calibrated VFM vector data extracted from the official Swarm Mag_LR_1B product (dataset '03').
This was expected since the VFM instruments exhibit a much lower vector noise level (11 pT/√Hz at 1 Hz) than the ASM vector mode. But it also reveals a much degraded stability, compared to the ASM residuals, for τ higher than 200 s. This unexpected disturbance on the VFM measurements is being investigated by an ESA-lead Swarm-wide team. The investigations currently favor Sun-driven perturbation effects in the vicinity of the VFM sensor. Encouraged by these first promising ASM vector mode performances, data have since been systematically acquired and a self-consistent and autonomous ASM 1-Hz vector product, referred to as ASM_V, has been produced. This product is elaborated on the basis of the Mag_LR_1B product, where VFM data are replaced by ASM vector data. The product is computed and generated on a daily basis with a 3-day sliding window scheme for the ASM vector calibration parameters.
Acknowledgements The authors acknowledge the  ESA Swarm team  for computing and providing additional data access on Swarm satellites orbital characteristics for the long-term analysis of the ASM instrument behavior. They also gratefully acknowledge support from the  Centre National d'Études Spatiales (CNES)  within the context of the ' Travaux préparatoires et exploitation de la mission SWARM ' project. This is IPGP contribution no. 3628.
III. Standardize (meta-)data and product metrics and harmonize access to data and model archives: Making efficient use of data, and even finding data that are in principle useful in advancing the science of space weather require adequate standardization in data formats and access protocols to on-line data archives. Knowledge of quality of data products and of space weather applications requires development of data product standards. Recommendation: We recommend that funding agencies require development of data archiving, data search, and data access plans as part of observatory/instrument operations support, retro-actively where needed; this should include standardization of data formats and of data retrieval methods (i. e. , web and application interfaces). We recommend that funding agencies coordinate any needed reprocessing of historical datasets to make them generally available in a standard way.
This full-Sun coverage supports the study of conditions leading to variable space weather, including the evolution leading up to and following solar storms, and the coupling to adjacent flux systems. But the space to cover is vast, and the observables range in size scale, energy, wavelength, and other physical attributes over many orders of magnitude, requiring multiple types of observatories and necessarily leaving gaps in our knowledge. Years of increasing coverage and open-data policies have led to a growing open-access event archival database of well-observed flares, CMEs, and particle events that enables event comparisons and inter-domain coupling studies. Search and visualization tools are developing to increase the utility of and access to observational data. On the numerical front, leaps forward in the realism of numerical modeling that enable us to explore, for example, the generation, rise, and emergence of magnetic flux bundles into the solar atmosphere and the subsequent initial phases of a CME, the formation of sunspots upon field emergence onto the solar surface, and the analysis of chromospheric processes in a realm with radiative transfer, partial ionization, and comparable field and plasma forces.
There is improved access to data-product repositories, which in part is due to empirical model development based on longterm databases. All this supports the development of physics-based models and understanding of the processes involved, including data-ingestion into assimilative models, some of which are approaching transition to real-time operations. The rapid growth of observational and numerical resources is advancing our understanding of the Sun-Earth system as a coupled whole, but many major issues remain to be addressed on the path towards improved scientific understanding and desired specificity in forecasts for the various sectors of society that are impacted by space weather. poorly with often an unguided "no flare" forecast performing best, and with trained observers unable to differentiate forecasts within 24-h increments and flare magnitudes uncertain to one or more orders of magnitude, and with only the first advances to forecast the magnetic content of eruptions into the heliosphere being made in recent years.
A particular challenge is to measure the intensity of field-aligned currents that directly control the horizontal currents in the auroral ionosphere and consequently also the dB/dt values as measured on the ground. NEW MAINTAIN: When planning satellite fleets or constellations for probing the MIT system it is important to keep in mind the support that other existing satellite missions can provide. A nice example towards this direction is the AMPERE project which maintains an impressive set of magnetometers hosted by the Iridium satellites on LEO orbits. Another example of fruitful collaboration with long heritage of support to other space plasma missions is the DMSP program hosted by the United States Department of Defense. Ensuring continuity of this kind of missions will be an important factor in the attempts to keep the costs of multipoint MIT-monitoring on a tolerable level.
e. the energy reservoir from previous events is not completely emptied -no intrinsic time constant, influenced by other system input and output. • REQUIRE: Coordinated ground-based measurement can provide crucial support for satellite missions (6th priority in Pathway I recommendations for maintaining existing capabilities). We propose to establish a formal basis for collaboration and data sharing between heliospheric and magnetospheric missions and ground-based assets. Informal (e. g. , Cluster Ground-based Working Group) and formal (e. g. , THEMIS mission) agreements have been made before, but usually missions do not involve a requirement for GB support in their level-1 science requirements for ground-based support (Van Allen Probes, MMS, Solar Probe, etc). This must be rectified. Satellite missions require support from a global network of -MAINTAIN/IMPROVE: ground-based magnetometers, for the global and local current patterns.
• DESIRE, IMPROVE/NEW: Improved data assimilation method and models applied to the coupled magnetospheric system including magnetic fields, current systems, and hot and cold plasma populations. • DESIRE, IMPROVE: Capacity to specify the global state of the magnetosphere will ultimately be required to advance our knowledge of space weather to the true point of predictability. Even with currently operating multi-satellite missions in the so-called Heliophysics Great Observatory, geospace remains extremely sparsely sampled in-situ. Global networks of ground-based magnetometers, radars, and optical imaging (both ground and space) provide the only currently credible approach to specifying the global state of the coupled magnetosphere ionosphere system. Even supplemented by current satellite missions, the state remains sparsely specified in the critical regions of in-situ geospace.
Data from L1 typically gives the general idea and this location is definitely suited for the primary mission for SWx forecasts, but in the near future we will also need satellites closer to the subsolar bowshock/magnetopause to understand what really arrives at Earth. For such remaining science purposes during the years 2007-2009 a good constellation was formed by the Cluster and THEMIS multisatellite missions. Systematically during spring and autumn times one of these missions was monitoring the energy feed from solar wind and the other was probing the consequences in the magnetosphere. Ensuring such coordination between different missions will be vital for better physical understanding of energy transfer processes between solar wind and magnetosphere. In longer run the research conducted with Cluster-THEMIS (or in the future MMS-Cluster-ARTEMIS) observations should pave the way to design future cost-efficient solutions for continuous monitoring of upwind conditions with optimally configured satellite constellations.
e serving dense populations at latitudes typically suffering from large GMDs. • REQUIRE: MAINTAIN/IMPROVE/NEW: Deployment of a network of ground-based magnetometers and magnetotelluric instrumentation for geo-electric field measurements with infrastructure for data collection and distribution in near-real time. The critical density of real-time magnetometer and magnetotelluric networks needed for the regions of critical power grids under the risk of SWx disturbances should be defined on the basis of knowledge about underlying gradients in ground conductivity in the relevant regions, as these may cause very localized features in the geo-electric field. • REQUIRE, IMPROVE/NEW: Systematic studies on ground-conductivity in the regions of high GIC risk. Combining results from ground-based, air-borne and satellite (Swarm in particular) measurement campaigns including both solid-earth and sea-water conductivity effects.
We suggest this as a particularly fruitful area for modeling. • DESIRE: Visualization tools for magnetic fields and low and high-energy particle distribution in geospace. Goal MEP-2a: Specify extreme condition of soft particle (keV) environment in Geospace -Surface charging Dynamical variations of keV plasma, such as substorm injection, auroral particle precipitation, and field-aligned currents are a critical factor in surface charging of satellites at LEO and GEO. Thus soft plasma descriptions are an essential precursor for the mitigation of surface charging problems from extreme conditions in the soft particle (keV) environment; this information is essential for satellite design. • REQUIRE: Monitoring soft particle fluxes by LEO satellites (e. g. , DMSP, POES) (1st Priority in Pathway II recommendations for maintaining existing capabilities; 5th priority in Pathway I recommendations for maintaining existing essential capabilities) • DESIRE: permanent auroral oval monitoring from spacecraft in UV (like Polar) (7th priority in Pathway I recommendations for new instruments) • REQUIRE: Large databases of current and historical data obtained from in-situ particle measurements onboard spacecraft should be preserved (and compiled with cross-calibration) as we need to analyze the occurrence frequency distribution of extreme conditions of soft particles; Understanding the physical mechanism of particle injection and precipitation and relating solar wind conditions with extremes in the geospace environment is an important aspect in order to make progress in predicting extreme conditions in the soft particle environment (1st priority in the Pathway II recommendations for modeling).
Operators of space radars require nowcasts and short-term forecasts of TEC in order to correct for range and bearing errors in radar tracking of space objects in LEO. We note that statistical ionosphere models tuned with data from ground-based networks or LEO satellites can in many cases provide relatively good results for nowcasts or short-term forecasts in regional or global scales. However, with increasing lead times more comprehensive physicsbased modeling with data assimilation is required. Goal IO-1: Understand/quantify the benefits of data assimilation in ionospheric modeling. In the work to get longer lead times in predictions with adequate reliability space weather research can benefit from synergies with meteorology (c. f. General recommendations for Collaboration between agencies and communities, point m).
Systematics in the appearance of ionospheric storms in different latitudes, local times and during the different storm phases has not been studied comprehensively yet, which complicates the efforts even for short-time global forecasts. Goal IO-2a: Conducting ionospheric research with enhanced observations. The spatial resolution of measurement stations providing ionospheric data has great variability. Some regions are populated with dense GNSS receiver networks while no ground-based receivers are available in the ocean areas. To fill this gap that is typically for ground based measurements, space based monitoring techniques such as radio occultation, and satellite altimetry data can be used. While ionospheric plasma can be probed with a wide variety of different cost effective and robust instrumentation, monitoring of thermospheric properties (chemical composition, neutral wind, density and temperature) is challenging.
g. , through use of reanalysis techniques to reveal new systematic features in the data) and will also provide an efficient practical basis for future applications of our science. These assimilative approaches are significantly enhanced by the availability of diverse datasets from spatially dense networks as these data then provide strong constraints on the assimilation. We need to promote these ground-based networks as a global system for scientific progress on space weather, so that each individual (and often independently funded) instrument provider (and responsible funding agency) sees how their contribution fits into the wider picture, i. e. that a local contribution builds and sustains local access to a global system. Objectives: To make a step change in the international co-ordination, and delivery, of ground-based space weather observing systems to optimize our ability to observe space weather processes.
This must include increased engagement with modelers, operators of space-based sensors, and other consumers of space weather data, in order to ensure the optimum interaction between the collected data and state-of-the-art international models, and the synthesis of these data and model results into operational tools whose outputs can be made available to the applications and technology community. This would be a major advance on the current situation where ground-based instruments are mostly established and supported by individual national programs, with only a few projects formally constituted as multi-national programs (EISCAT being the notable example). There are a good number of projects that operate internationally through working level agreements in the scientific community (e. g. , SuperDARN) but experience shows that these are difficult to sustain in modern conditions; they rather reflect an older (make-shift) way of working that dates as far back as the IGY in 1957/58.
These models typically use magnetic maps of the photospheric magnetic field built up over a solar rotation, available from a ground-based and spacebased solar observatories. Two well-known problems arise from the use of these "synoptic" maps. First, the maps contain data that is as much as 27 days old. The Sun's magnetic flux is always evolving, and these changes in the flux affect coronal and heliospheric structure. Second, the line-of-sight (LOS) field at the Sun's poles is poorly observed, and the polar fields in these maps are filled with a variety of interpolation/extrapolation techniques. Unfortunately, these observational gaps can strongly influence the solution for the global magnetic field. In particular, poorly or unobserved active regions at the limbs (as viewed from Earth) as well as inaccurate polar field estimates can introduce unacceptable errors in the field on the Earthfacing side of the Sun.
Solar Orbiter may partially fulfill high latitude mission requirements at the latter stage of the mission. Supporting observations: Direct imaging data of the solar atmosphere (such as possible with the STEREO spacecraft) or indirect information derived from far-side helioseismology (such as with SDO/HMI and GONG) provide useful constraints, but are no substitute for direct magnetography because these methods do not provide adequate information on the magnetic field. Appendix F. 6. Determination of the foundation of the heliospheric field Rationale: The global solar magnetic field plays a crucial role in space weather at Earth. It influences the internal magnetic structure of interplanetary coronal mass ejections; the connectivity of the magnetic field determines where solar energetic particles propagate, and structure of the field determines whether fast solar wind streams will cross the Earth's location.