dataesr/scientific-paragraphs-categorization huggingface dataset:
The impact of the orbit parametrization should then be adequately taken into account when interpreting gravity field results for geophysical studies, e. g. , when comparing GRAIL estimates with those of independent techniques such as LLR  (Viswanathan et al. , 2019). This is best done by evaluating the spread of multiple solutions as different and independent as possible (i. e. , based on different software, parametrization, or combination of datasets), rather than based on provided formal errors. Similar procedures are common practice in Earth geodesy, for instance in the analysis of the Earth gravity field and of its temporal variations  (Jäggi et al. , 2019).
Conclusions At AIUB, orbit determination capabilities from Doppler deep-space tracking have been recently developed in the framework of the Bernese GNSS Software following the guidelines of  Moyer (2003)  and the most recent conventions for planetary reference frames and ephemerides. This allows to apply the tools and expertise of the BSW group to deep-space and planetary-borne OD and geodetic studies. We present our solutions for the lunar gravity field based on tracking data from the GRAIL mission. Orbiting the Moon in 2012, data from these twin probes significantly increased our knowledge of the Moon's gravity and of its interior (see, e. g. ,  Zuber, 2014; Chappaz et al. , 2017). We detail our modeling of two-way S-band Doppler and our approach to get an optimal combination of Doppler and KBRR.
Orbit improvement often involves the estimate of some sort of empirical parameters, especially for planetary probes whose geometrical and optical properties are often badly known, and for which accelerometer measurements are often not available. In this paper we thus outlined a procedure to choose an appropriate parametrization for orbit and gravity recovery, by a systematic analysis of results on both levels. We used accurate GRAIL KBRR data to evaluate the influence of empirical parameters adapted to the common scenario of Doppler-based OD, using a combination of empirical accelerations and stochastic pulses. We conclude that, although a combination of explicit modeling and empirical parametrization gives the best results, a purely empirical modeling without additional information gives satisfactory results if data coverage is sufficient (especially concerning stochastic pulses).
For practical reasons, in this work we chose to apply a unique parametrization over GRAIL PM. However, based on Fig. 3 , we note that future analysis could adopt different empirical parametrizations to each arc, depending on tracking geometry and predominant forces acting on the spacecraft. As all mission scenarios are different, the setup resulting from our analysis will not necessarily fit another probe, and the proposed algorithm should rather be applied as a pre-processing step when approaching a new dataset. solutions from the dispersion of independently estimated coefficients, when available, rather than from the provided (rescaled) formal errors.
Gamma-ray data are necessary to make correct estimation of neutrino fluxes from point-sources. For this reason, a multi-messenger search is mandatory for the identification of the origin of cosmic neutrinos. To search for PeVatrons, a gamma-ray experiment with detection sensitivity up to about 100 TeV is of fundamental importance. Indeed, the characteristic gamma-ray feature of a PeVatron include an hadronic, hard spectrum that extends until at least several tens of TeV. The High Altitude Water Cherenkov Observatory (HAWC) is a gamma-ray observatory sensitive in the multi-TeV energy domain. The HAWC observatory has reported new data on galactic sources in recent years, see e. g. [3, 4]. Among these sources, the eHWC J1825-134 source, located in the southern sky, has been detected with an hard spectrum that extends up to multi-TeV energies.
PoS(ICHEP2020)599 Neutrinos from galactic sources Viviana Niro region which encompasses the ∼ 1 TeV emission as observed by Fermi/LAT. The flux level measured by Fermi/LAT, in the TeV range, is higher than the one measured by the HAWC collaboration. Note, however, that the HAWC analysis assumes a Gaussian source morphology convolved with the HAWC point spread function, which does not match the complex morphology seen by Fermi/LAT. In the figure, we report also the data points for the HESS J1825-137 source considering an opening angle of 0. 8 •  [8]  and for the HESS J1826-130 source  [8]. The 1. 5 • region extracted from the Fermi/LAT analysis, includes, apart from the HAWC extended source itself, also the pulsar PSR J1826-1256 and the diffuse emission from the Galactic disk in front/behind the source.
Conclusions We have calculated the expected number of events at the KM3NeT detector from the source eHWC J1825-134, using data provided by the HAWC collaboration, as well as information derived by analysis of the Fermi/LAT data. We found that, after 10 years of running, a statistical significance between 4 and 5 σ has to be expected, depending on the actual extension and diffuse emission of the source. The discovery potential for the eHWC J1825-134 source at the BAIKAL-GVD detector  [14]  in Baikal Lake will be similar to the one found for the KM3NeT detector.
Convergence of random walks In order to quantify the effect of the laziness parameter q and the teleportation parameter d on the speed of convergence of the quantities described above to their deterministic limit, we used the well-known Primary School temporal network (  11 ) oTR(x) = 1 T T t=1 π t (x)1 odeg t (x)>0 (12) V n (x) = |{k ≤ n, π(X k ) = x}|, (13) O n (x) = |{k ≤ n, π(X k ) = x and π(X k+1 ) � = x}|. (14) lim n→∞ n -1 V n (x) = TR(x), (15) lim n→∞ n -1 O n (x) = (1 -q) d N -1 N TR(x) + (1 -d)oTR(x). 1 https://github. com/phoscheit/DynPageRank (Gemmetto et al. 2014 ). This network is constituted by face-to-face close interactions between high school students and teachers, as measured in 20-second intervals. We aggregated all contacts occurring in a given hour into a single time-slice, which resulted in a temporal network of 242 nodes and 26,603 edges over 19 time-slices.
Centrality measures in cattle trade networks In this section, we will use the previously defined centrality measures to identify the nodes most responsible for the spread of disease in a large network of cattle movements in France. Other than the static and temporal PageRank centralities defined above, we also consider Katz and betweenness centrality (definitions can be found in Additional file 1: section 1). The French BDNI network TAPE = x∈V |O n (x) -oTR(x)| oTR(x). The French Base de Données Nationale d'Identification (BDNI) is a national database logging all movements of cattle between two holdings in France. For the purpose of this work, we extracted all movements occurring in a two-year period between 2014-01-01 and 2015-12-31. We used these movements to construct a temporal network, with holdings as vertices and cattle movements as edges, with a time-stamp corresponding to the day of the movement.
Percolation analysis Ultimately, we wish to understand how centrality of a node is correlated with the role this node plays in epidemic outbreaks and if it can be a good predictor of the spread of infection on the temporal network under study. This is a classical problem in network analysis  (Lü et al. 2016)  and is usually studied either by direct simulation  (Vidondo and Voelkl 2018; Payen et al. 2019)  or by computation of a proxy of epidemic spread, such as the size of the largest connected component  (Mweu et al. 2013; Büttner et al. 2013)  or the so-called epidemic threshold  (Valdano et al. 2015 (Valdano et al. , 2018)). In this section, we will use as a metric the mean final outbreak size of simulated SIR processes. We will use the tsir package for fast outbreak simulation  (Holme 2020).
It should be possible to account for such ruptures, provided they can be accurately detected  (Ranshous et al. 2015; Donnat and Holmes 2018; Monnig and Meyer 2018)  by appropriately reweighting time-slices in the definition of TempoRank centrality (10). Other, so-called online centrality measures update the scores as new interactions are added to the dataset  (Béres et al. 2018; Rozenshtein and Gionis 2016)  but fail to identify older, periodically active nodes which might have an important role to play in epidemic spread in specific timeframes. An important next step will be the use of centrality measures for targeted control measures more subtle than the outright removal procedure studied here. For instance, targeted vaccination campaigns or diagnostic strategies are some of the tools available for the control of cattle disease, but they need to be weighted against their economic impact.
As a byproduct of this demonstration strategy, we can extend Theorem 1 to angularly controllable homogenous control systems (see Corollary 10). Acknowledgements. This work was supported by the Grant ANR-17-CE40-0007-01 QUACO of the French ANR. DC is supported by the DIM Math Innov grant from Région Île-de-France. The authors want to thank Francesco Boarotto, Ugo Boscain and Leonardo Martins Bianco for preliminary discussions on the subject of this note.
Synchrotron X-ray diffraction and multipole modeling. Single crystals of 1 and 2 of suitable size for the synchrotron beam were mounted on a Huber goniometer head via a glass-fiber and using glue. The crystal quality was tested at room temperature and subsequently cooled to low temperature. Data were collected at beamline BL02B1 at SPring-8, which is equipped with a Pilatus3 X CdTe 1M detector and a gaseous He-cooling device. The datasets consist of 180 omega-scans in steps of 0. 5 with fixed at 0, 20 and 45 and with 2 = 0 and 20 (scan speeds of 2 and 4 s À1 for 1, and 1 and 2 s À1 for 2), thus six runs for each crystal. The detector frames are converted to Bruker format, followed by a Lorentz and polarization correction, and the raw images are then integrated using SAINT+ (v8. 38A). Subsequently, integrated intensities are corrected for absorption and other effects in SADABS  (Krause et al.
The powder diffraction patterns for 1 were measured at a magnetic field of 1 T and a temperature of 2 K using a position-sensitive detector. Singlecrystal measurements for 2 were made in the magnetic field of 1 T at 3 K, and the flipping ratios were collected for five different sample orientations. Flipping ratios for compound 2 were then extracted from the raw images by employing the inhouse data reduction suite at the LLB. The refinement of susceptibility tensors both for singlecrystal and powder PND data were performed with the newly developed software library Cryspy (v. 0. 5. 8) through the Cryspy Editor (v. 1. 5. 6), both available for Python3. X through PyPI  (Kibalin & Gukasov, 2019).
Theoretical calculations Ab initio calculations were performed using the ORCA software (4. 1; Neese, 2012 Neese, , 2018) )  with the solid-state geometry of complexes 1 and 2 obtained from synchrotron X-ray diffraction at 20 K. CASSCF(7,5)  (Malmqvist & Roos, 1989)  and subsequent NEVPT2  (Angeli et al. , 2001)  correction was performed including all the ten quartet S = 3/2 states and using the Douglas-Kroll-Hess triple-DKH-def2-TZVP basis set  (Scha ¨fer et al. , 1992 (Scha ¨fer et al. , , 1994;; Weigend & Ahlrichs, 2005). Including the 40 doublet states (S = 1/2 states) did not change the results. The AILFT  (Atanasov et al. , 2012 (Atanasov et al. , , 2013) )  program was used to get an estimated d-orbital splitting of the compounds. The SOC was accounted for on the basis of nonrelativistic configuration interaction eigenstates using quasidegenerate perturbation theory.
Theoretical results Before we describe the experimental results (Section 3. 2 and onwards), we look at the calculated electronic structures of 1 and 2, obtained using the ORCA program suite from CASSCF(7,5) and subsequent NEVPT2 correction to the energies. Two main results from the calculations will be described in turn in the following:  (1)  the AILFT orbitals provide an intuitive interpretation and prediction of the magnetic anisotropy; (2) the g, D and E values, which quantify the magnetic anisotropy, and can be compared with the experimental measurement of the magnetic susceptibility tensors. In addition, Section 3. 3 contains a comparison of the theoretically calculated electron density (ED) and the experimentally derived ED. (1) The AILFT analysis of an ab initio calculation provides orbitals independent of the input molecular coordinate system, thus providing the most consistent orbitals.
As already discussed, both 1 and 2 are best described as distorted tetrahedral complexes (see above). Therefore, we expect to have the e-type (in T d symmetry) orbitals (i. e. We note that the orbital ordering reported for both complexes in the earlier report  (Vaidya et al. , 2018)  are slightly different from the orbital ordering reported here. This is because, in the earlier paper, we reported the CASSCF ground state wavefunction which is multideterminant in character, whereas in this manuscript we report AILFT orbital ordering. However, we noticed the same orbital ordering (as we notice in this manuscript) when we compute the AILFT orbitals. (2) The pseudo-spin 3/2 SH approximation allows for the extraction of the magnetic anisotropy from the ab initio calculations. The eigenvectors for the D-and g-tensor are almost parallel, and the eigenvalues as well as the directions of the vectors with respect to the coordinate system chosen for the AILFT orbitals above are found in Table  3.
We thank the anonymous referee for comments that substantially improved the manuscript. PW thank  Jiajun Zhang  for useful discussion. PW, NIL, XK, and QG acknowledge support from the  joint Sino-German DFG research Project  " The Cosmic Web and its impact on galaxy formation and alignment " ( DFG-LI 2015/5-1 ,  NSFC  No. 1186131006 ). PW, MSP, and NL thank the  DAAD  for PPP grant  57512596  funded by the  BMBF. MSP thanks the  Klaus Tschira Stiftung gGmbH and German Scholars Organization e. V. for support via a  Klaus Tschira Boost Fund. NIL  acknowledges the financial support of  Project IDEXLYON at the University of Lyon  under the Investments for the  Future Program  ( ANR-16-IDEX-0005 ). ET was supported by  ETAg  grant  IUT40-2  and by  EU  through the  ERDF CoE TK133. XK acknowledges financial support by the  NSFC  (No.
----- Methods Plate-like single crystals of κ-[(BEDT- STF) x (BEDT-TTF) 1-x ] 2 Cu 2 (CN) 3 were grown electrochemically  17  with a typical size of 1 × 1 × 0. 3 mm 3 ; here BEDT-TTF stands for bis(ethylenedithio)tetrathiafulvalene and BEDT-STF denotes the partial substitution by selenium according to Fig 2a. The composition of 0 ≤ x ≤ 1 was determined by energy-dispersive x-ray spectroscopy  17. The dc resistivity was recorded by standard four-point measurements; superconductivity was probed by magnetic susceptibility studies of polycrystalline samples using a commercial SQUID and magnetoresistance measurements on single crystals. We performed complementary pressure-dependent transport experiments of the parent compound (x = 0) providing the grey data points in Fig. 4a , see Ref. 18. Since the compounds are isostructural they retain the highly-frustrated triangular lattice and do not exhibit magnetic order down to lowest temperatures; a hallmark of the spin-liquid state.
Acknowledgments We acknowledge fruitful discussions with  D. L. Maslov ,  A. V. Chubukov ,  A. Georges  and  E. van Heumen. The project was supported by the  Deutsche Forschungsgemeinschaft (DFG)  via the projects  DR228/39-3 ,  DR228/41-1 ,  DR228/48-1  and  DR228/52-1. A. P. acknowledges support by the  Alexander von Humboldt-Foundation  through the  Feodor Lynen Fellowship.
These characteristics are consistent with direct determination of the wave normal angle from three component measurements of the magnetic field fluctuations, which show that in most cases the wave normal angle is less than 20° (e. g. ,  Grigorenko et al. , 2020; Huang et al. , 2012; Le Contel et al. , 2009). The duration of whistler bursts varies from ∼0. 5 to ∼8 s. The first burst was observed within 1 min after the onset during the B Z pulse (the interval "I" in Figure  1 ). The other bursts were detected at the later stage of the dipolarization when the B Z field was quasi-steady but still large (intervals "II-IV"). For Fourier analysis, we used SCM data in the frequency range from 4 to 4,096 Hz with time resolution 0. 25 s (sampling frequency MALYKHIN ET AL. was 8,192 Hz). To determine the direction of the ambient magnetic field, we used FGM data in burst mode (128 Hz).
The method for calculating the growth rate is described in detail in  Grigorenko et al. (2020). Figure  4  shows the distribution of the normalized growth rate γ/ω ce on the (T-F) plane, where the values γ/ω ce themselves are shown by a color code. The growth rates were calculated based on the local distribution function measured during each burst of whistlers in the intervals I-IV. Data corresponding to the particular intervals are shown in separate blocks of panels. The growth rates were calculated for whistler waves propagating antiparallel (k•B < 0) and parallel (k•B > 0) to the external magnetic field B. The corresponding values are shown in panels (b) and (c), respectively. The frequencies of whistler waves are shown in these panels by the solid magenta lines. To calculate the growth rate, we used a 3D electron distribution function averaged over time interval of 120 ms.
For each instant of time, we look for a local maximum or a bulge in the frequency spectrum between the lower hybrid (f LH ) and electron cyclotron (f ce ) frequency where the whistler waves related to dipolarizations are observed most often (e. g. ,  Liang et al. , 2012). We find local spectral maximum using the method of gradient descent (e. g. ,  Akilov & Kantorovich, 1982)  just as it was done by  Grigorenko et al. (2020). To be sure that the bulge in each spectrum represents the quasi-parallel whistler wave, we check the condition for the wave normal angle to be less than 40° and the degree of polarization >0. 7. In total, we have obtained 2,688 wave measurements taken at various moments of time within all bursts from our data base, which we will further term wave moments. For each such moment, we analyzed electron velocity distribution function and calculated the growth rate γ.
The estimated shooting time was about 4 min and 512 slices were acquired. The mean dose absorbed by the mice was about 900 mGy of dose to water. The images were analyzed using AnalyzePro Software, which allows for semi-automatic and manual segmentation. The main bronchi and right and left lungs were segmented using the semi-automatic option with the same threshold range for each mouse in order to be able to compare them. Lesions induced by irradiation-the injury patch-were manually contoured by the same operator. From these segmentations, volumes were computed and, for each volume, Hounsfield Unit (HU) histograms were extracted using a bin width of 1-HU. For density distribution representation, smoothing curves were constructed using PRISM software applying second-order smoothing with 60 neighbors.
Histopathology and Immunohistochemistry HES and Masson's trichrome-stained tissue sections were used to assess overall lesion severity. The thickness of the alveolar septa was measured using the Visiol@b TM 2000 image analysis software (Biocom SA, France). Immunostaining of club cells (uteroglobin, UGB) and type II pneumocytes (prosurfactant protein C, SFTPC) was used to monitor parenchymal and epithelial lung damage. UGB-positive cells were counted on the bronchiolar epithelium both inside and far from the injured area, taking into consideration at least three different bronchioles. UGB-positive cells were expressed as a percentage of total cells. The total number of cell nuclei per 100 µm was also tracked in order to monitor radiation-induced variations in total epithelial cell density. SFTPC-positive cells were counted both inside and far from the injured area with between 3 and 5 different fields (X 400 magnification).
The Cryogenic Underground Observatory for Rare Events (CUORE) is the first cryogenic experiment searching for neutrinoless double-beta (0 ) decay that has been able to reach the one-ton scale. The detector, located at the Laboratori Nazionali del Gran Sasso in Italy, consists of an array of 988 TeO 2 crystals arranged in a compact cylindrical structure of 19 towers. Following the completion of the detector construction in August 2016, CUORE began its first physics data run in 2017 at a base temperature of about 10 mK. Following multiple optimization campaigns in 2018, CUORE is currently in stable operating mode. In 2019, CUORE released its 2 nd result of the search for 0 with a TeO 2 exposure of 372. 5 kg•yr and a median exclusion sensitivity to a 130 Te 0 decay half-life of 1. 7 • 10 25 yr.
8 mK. After the successful installation of the detector in the summer 2016 the first CUORE cool-down took place between December 2016 and January 2017. After some initial detector optimization campaigns, CUORE has been collecting data since May 2017, and after upgrade efforts in 2018 and 2019 the experiment has been running continuously. The achieved stable conditions allowed continued data taking with minimal onsite activity also during recent lockdowns. CUORE is the culmination of a multi-decade effort to develop low temperature detectors research for neutrino mass studies. Designing, building, and operating CUORE took over a 10-year period. The successful operation of CUORE marked a major milestone in the history of low-temperature detector techniques and opened the way for large calorimetric arrays (tonne-scale) for rare event physics.
Search for neutrinoless double beta decay CUORE has collected 7 datasets since April 2017. Each dataset includes one-day-long runs for a total of about one month of Physics data, and is started and ended with a calibration measurement. The number of active channels is 984. However, during the analysis, some of these channels were removed for different reasons (e. g. high noise, failure during one or more analysis steps, insufficient statistics collected during calibration, etc). In the end, the analysis was performed with a number of channels that changed dataset by dataset (900 min -950 max). The average energy resolution at the Q-value, mediated over all the active channels, was (7. 0 ± 0. 4) keV, with an observed improvement during the data collection thanks to the optimization campaign.
Since spring 2019, CUORE has been stably collecting data at an average rate of 50 kg•yr/month. During the data-taking campaign between May 2017 and July 2019 CUORE collected a total exposure of 372. 5 kg•yr of TeO 2 (103. 6 kg•yr of 130 Te)  [9]. A blind search for 0 was performed, and the ROI fit model defined prior to unblinding. The model parameters are the 0 decay rate, a dataset dependent background index (BI), the 60 Co sum peak amplitude and its position, which is a free parameter as in the previous analysis  [10]  (figure  1 , left). The BIs are dataset dependent, while all other parameters are common to all datasets, including the 60 Co rate, which is scaled by a dataset dependent factor to account for its decay. The line shape parameters for each detector-dataset were estimated with a simultaneous, unbinned extended maximum likelihood (UEML) fit performed on each tower in the energy range (2530 -2720) keV.
Conclusion The CUORE experiment will collect data for a total of five years of live-time. The predicted final sensitivity is 9. 0•10 25 yr at 90% C. L. [12]. The demonstrated performance and results represent a fundamental step toward the next generation of tonne-scale detector arrays. Starting from the experience, the expertise, and the lessons learned while running CUORE, the CUPID project (CUORE Upgrade with Particle IDentification  [13] ) aims at developing a future large calorimetric 0 experiment with sensitivity on the half-life of the order of (10 27 -10 28 ) yr. Thermal detectors are expected to play a central role in the forthcoming future of the search for 0.