dataesr/scientific-paragraphs-categorization huggingface dataset:
Realism artistic movement aims to portray real and typical contemporary people and situations by taking care to be as close as possible to truth and accuracy. Such paintings depicted everyday subjects and situations in contemporary settings, and attempted to depict individuals of all social classes in a similar manner  [54]. Romanticism period emphasized intense emotion as an authentic source of aesthetic experience, placing new emphasis on such emotions as apprehension, horror and terror, and awe  [55]. The performance of deepbased models on these two art movements could be explained by the fact that deep models have been trained over natural scenes, depicting the daily life. For instance, MLNET model has been trained over SALICON dataset  [56]  and MIT300 dataset  [57] , whereas SAM-ResNet and SAM-VGG have been trained over 4 datasets, i.
e. SALICON dataset  [56] , MIT1003 dataset  [58] , CAT2000 dataset  [53]  and MIT300 dataset  [57] , as given in Table  3. The art movements for which deep models perform least are the Pointillism and Impressionism movements. This observation could be explained by the art history. Indeed, one key factor that usually explains the emergence of Impressionism, is the arrival of photography that questions artists about their own works. In a kind of opposition to photography mechanical realism, the impressionist painters do not try to copy reality; they rather try to create images that depict their own visual perception and feeling. Less importance is then given to realism and details whereas the focus is set on visual feeling. Pointillism, that belongs to neo-impressionism, also proposes an approach to differentiate painting from photography realism.
Can we go further? To test whether or not we can improve the performance of prediction, we fine-tune the best performing model on the paintings dataset, namely SAM-ResNet. We have chosen SAM-Res-Net for several reasons. First, this is the model that performs the best over the proposed paintings dataset as presented in the previous section. As it already performs rather well, the challenge to improve it is then more difficult. Second, we believe that SAM-ResNet architecture has some advantages compared to other deep models, such as the priors that are learned, and the loss function which leverages both saliency maps and fixation maps. Obviously, its high number of trainable parameters is also interesting to tailor the model to paintings. For fine-tuning SAM-ResNet, we split the paintings dataset into a training set, composed of 90 paintings randomly chosen, a validation set of 20 paintings, and a test set composed of 40 paintings.
In tectonically active mountain belts, landslides contribute significantly to erosion. Statistical analysis of regional inventories of earthquake-triggered-landslides after large earthquakes (Mw > 5. 5) reveal a complex interaction between seismic shaking, landslide material, and rainfall. However, the contributions of each component have never been quantified due to a lack of in-situ data for active landslides. We exploited a 3-year geodetic and seismic dataset for a slow-moving landslide in Peru affected by local earthquakes and seasonal rainfalls. Here we show that in combination, they cause greater landslide motion than either force alone. We also show the rigidity of the landslide's bulk clearly decreasing during Ml ≥ 5 earthquakes. The recovery is affected by rainfall and small earthquakes (Ml < 3.
a Seismicity reported by the Peruvian Geophysical Institute (IGP) for earthquakes with PGV above 0. 01 cm. s -1 (see SI) on the landslide (gray dots), and cumulative rainfall over the rainy season (solid blue line). Earthquakes strong enough to saturate the seismometer located on the landslide or earthquake where no records were available due to problems with the seismometer are indicated by black dots. For significant earthquakes, magnitudes and distances to the Maca landslide were indicated. b Time series of the Maca GPS North cumulative displacement (red) and velocity (gray) at a 1-day sampling rate. Blue zones represent periods were the dv/v in under -1. 2%, and red zones represent periods were the dv/v is likely under -1. 2% but gaps in the seismic data exist. c Changes to relative seismic velocity of the material determined by comparing daily seismic noise correlograms in the 3-8 Hz frequency range (black), which have a depth sensitivity of up to 40 m (see Supplementary Figs.
Methods GPS processing. Fifty-five continuous GPS (cGPS) recordings were processed from various networks in the Andean region, South America and Nazca Plates (see Supplementary Fig. 7  in Supplementary Information). Thirty-three stations were installed and are maintained in Southern Peru and Northern Chile as part of the following projects: Integrated Plate Boundary (IPOC, www. ipoc-network. org), LIA-MB (www. lia-mb. net), CAnTO (www. tectonics. caltech. edu), CSN (www. csn. uchile. cl), and CAP (www. unavco. org). The remaining stations are part of the International GNSS Service (IGS, www. igs. org) global network. Data were processed using the double-difference method in GAMIT 10. 6  65  , choosing the ionosphere-free combination and setting the ambiguities to integer values. Precise orbits from IGS, precise EOPs from the IERS bulletin B, IGS tables describing the phase center of the antennas, FES2004 oceantidal loading corrections, and atmospheric loading corrections (tidal and non-tidal) were used.
One tropospheric Zenith delay parameter was estimated every 2 h, and one pair of horizontal tropospheric gradients were determined per 24-h session using Vienna Mapping Functions (VMF1)  66. These estimations allow the tropospheric delay to be mapped in the perpendicular direction, with a priori ZHD derived from pressure and temperature values from VMF1 grids. The daily solutions and position time series were obtained using PYACS software  67  , mapped first onto the ITRF 2008 reference frame  68  and then onto the South American plate, using a fixed pole  69, 70. Landslide velocity computation. To reduce noise when computing the velocity of the landslide at the location of the Maca GPS station, the displacement was averaged over a 5-day moving window. However, to reduce the smoothing effect and provide more realistic velocities after the August 2016 earthquake, the velocity was not smoothed for the 2 days following the earthquake.
Surface wave depth sensitivity. As surface waves are mainly composed of shear waves (S waves), active seismic acquisitions on the landslide were used to measure the velocity of the S waves. The surface wave inversion technique was applied in the Geopsy software (http://www. geopsy. org) with signals generated by dropping a mass of 80 kg from a height of 2 m using a tripod (see Supplementary Fig. 11 ). The model obtained by inversion gave a first layer of ~8-12 m with S waves traveling at around 110 m/s. Below, lies another layer composed of lacustrine deposits, where the S-wave velocity was close to 350 m/s (see supplementary Note 2 for further details). From this model, it was possible to study the Rayleigh wave sensitivity as a function of depth and frequency using the gpdc package available in the Geopsy software.
e. , Vp = 1900 m. s -1 and Vp = 350 m. s -1 , were used as fitting values to set the equations parameters (the porosity and the consolidation coefficient) and calibrate them when the soil is completely saturated. As no values of the bulk and shear modulus were obtained on the landslide, we used as input the bulk and shear modulus of the feldspar plagioclase, one of the main minerals present in the landslide  77  , i. e. , Ks = 75. 6 MPa and Gs = 25. 6 GPa 78. We fit the P-and S-wave velocities by choosing a porosity of the soil of 35% and a compaction coefficient of 120. Then the gpdc package available in the Geopsy software is again used to estimate the Rayleigh wave velocity variations as a function of the frequency for undrained loading (see Supplementary Fig. 14b  and the supplementary Note 4) or when a water table at 10-m depth experiences a 1-m variation.
These limits allowed us to compare PGV values from a catalog of 348 events between February 2016 and November 2018. Finally, the PGV of all these events was computed for the two horizontal components: North (PGV N ) and East (PGV E ). The final measured PGV is defined as follows: PGV measured ¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi PGV N Ã PGV E p : The fit between measured an estimated PGV (see Supplementary Fig. 9 ), shows a better result using the GMPE from Akkar and Boomer 81 for our dataset. Therefore, the PGVs were taken directly from the seismic signal when the seismometer did not saturate, and from the Akkar and Boomer GMPE when the Maca station saturated. The PGV was considered to have no uncertainties when determined from recorded seismic signals.
However, the uncertainty on the PGV obtained from GMPEs could be considerable. This uncertainty was estimated by computing the standard deviation of the relative error between the PGV measured and the approximated values when both were available. A final relative error of 56% was obtained in the case where the PGV had to be approximated using the Akkar and Boomer GMPE  81. Meteorological data. Daily precipitations, daily minimum and maximum temperatures were recorded at the SENAMHI meteorological station in Madrigal, 5 km west of the Maca landslide and at the same elevation. Precipitations, at the valley scale, are homogeneous 24 so that meteorological data collected in Madrigal are representative of those at the landslide location. However, although precipitations are known to be similar, no specific studies have compared the temperature between Madrigal and Maca.
Acknowledgements This experiment was funded by an  SEG   Geophysicists Without Borders grant , a grant from  ESA  through the  Alcantara  project " Monitoring and Detection of Landslides from optical Images time-Series " ( ESA 15/P26 ), a  CNES/TOSCA grant , and a  CNRS/INSU  grant. This work was supported by a grant from  Labex OSUG@2020  (Investissements d'avenir  ANR10 LABEX56 ). The principal investigator,  Noélie Bontemps , is funded by a  CNES doctoral fellowship. The authors are grateful for support from the  INGEMMET ,  J. C. Villegas  from the  Instituto Geofisico del Peru (IGP) , the  International Plate Boundary Observatory Chile  (IPOC, www. ipoc-network. org), Laboratoire International Associe" Montessus de Ballore " (www. lia-mb. net), Central Andean Tectonic Observatory Geodetic Array (CAnTO , http://www.
Background: The purpose of this study is to search for reports on the clinical effectiveness of FLS being implemented worldwide through the systematic review, analyze the roles of coordinators in each study, and provide basic data for the development of future coordinator education programs. Methods: A systematic search of the literature using the Medline, PubMed, and EMBASE databases and the Cochrane Library was conducted for using the following keywords: 'osteoporosis' AND 'fractures' AND 'secondary prevention'. Finally, 65 studies are included in this study. Results: At the coordinator-based fracture liaison service (FLS) center, the coordinator (often a nurse) acts as a central player in the establishing of patient connections, orthopedic surgeons, radiologists, and attending physicians.
They can also help patients to understand the need for osteoporosis evaluation and anti-osteoporotic medication use and to maintain the continuity of patient care. However, there are only a few reports of what role coordinators perform in these secondary fracture prevention programs, and there is no globally recognized training program for them. The hypothesis of this study is that the role and assignment of the coordinator will vary among FLS studies. Therefore, the purpose of this study is to search for reports on the clinical effectiveness of FLS being implemented worldwide through the systematic review, analyze the roles of coordinators in each study, and provide basic data for the development of future coordinator education programs.
METHODS A systematic search of the literature using the Medline, PubMed, and EMBASE databases and the Cochrane Library was conducted for publications (January 2000-October 2019 inclusive) using the following keywords: 'osteoporosis' AND 'fractures' AND 'secondary prevention'. The detailed search method is shown in the Supplementary Appendix 1. Relevant papers have also been searched for other local repositories, blogs, and gray literature outlets. The systematic reviews adhere to the Cochrane Collaboration approach. Inclusion criteria for the trials were: performed in patients ≥50 years of age with all forms of osteoporosis-related fractures; randomized or non-randomized stage 1 to 4 studies; retrospective or prospective observational studies. Excluded are research relating to the prevention of primary fractures or other bone-associated diseases, forms of narrative analyses, systematic reviews, meta-analysis, opinion articles, editorials, case reports, letters, and publications in languages other than English.
Two independent reviewers selected the studies by first screening the title and abstract followed by full-text articles. The discrepancy between the 2 reviewers was resolved by consensus or by a third independent reviewer, if necessary. Data analysis used the parameters Population, Procedure, Contrast, Outcomes, Environment (PICOS) and included general information about the article (e. g. , authors, publication year), study characteristics (e. g. , design, sample size), patient characteristics (e. g. , fracture type, osteoporosis duration), and outcomes (bone mineral density testing, treatment initiation, adherence, persistence, rates of re-fracture, and mortality). Data synthesis and findings were reported in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement.
Searched Studies of FLS in Various Countries The initial search identified 755 references from the selected databases. The 681 references were excluded by screening the abstracts and titles for duplicates, unrelated articles, case reports, systematic reviews, and non-comparative studies. The remaining 74 studies underwent full-text reviews, and subsequently, nine studies were excluded. Finally, 65 studies are included in this study. The details of the identification of relevant studies are shown in the flow chart of the study selection process (Fig. 1 ). Seventeen randomized controlled studies, 26 comparative studies, and 22 cohort observation studies were selected for further investigation. [1] [2] [3] [5] [6] [7]  The main characteristics and outcomes of the studies included in this systematic review are presented in Table  1.
In some studies, vertebral fractures were excluded because they did not increase mortality. [5, 34]  Hurrington and Lease  [50]  and Beaton et al. [2]  included pelvic fractures in the subjects. This study has several limitations. First, only limited in-formation could be extracted from these selected papers. Although included studies have reported the role of the FLS coordinator, most studies do not mention detailed protocols of an education program for FLS coordinator. Therefore, it is important to share information on the role of FLS coordinator, and actual educational programs of the FLS coordinator through consensus meetings and academic meeting on different continents. Second, we only included papers that were found after a systematic search against scientific databases. Thus, grey literature on this topic, including abstracts of presentations at meetings on FLS, was not included in this systematic review.
Third, we have included retrospective studies, and it may make some biases for data analysis. But, we didn't perform statistical analysis and just collected for the descriptions of the role of coordination in FLS. Thus, we believe that there are a few possibility for risk of bias by including retrospective studies in our study. The importance of FLS has been proven in many studies. In addition, it is also reasonable to say that the coordinator is a member who plays a key role in the successful progress of the fracture prevention program between doctors and patients. However, it seems showed that the roles of coordinators and educational programs were not unified worldwide. In our best knowledge, this is the first study for analysis about the roles of coordinator and their education. Based on the results of this study, it is considered that the role of the coordinator should be clearly defined, and efforts should be made to activate the educational program for coordinator training.
2. The SANS patterns were recorded on the (111) plane for several angles of the field. In order to continuously follow the phase boundaries on the H -H ⊥ plane, we carried out magneto-current and magnetic torque measurements, when the magnetic field was rotated in fine steps within the (110) plane between successive field sweeps. The corresponding data are depicted in Fig. 3  in the form of colour maps over the field magnitude-orientation plane (φ denotes the angle of the field spanned with the [111] axis, as sketched in Fig. 1b ), where the magnitude of the magneto-current (Figs. 3a  & c ) and the dissipative part of the torque signal (Fig. 3b ) are represented by colours. The anomalies labeled in Fig. 3  are used to establish the magnetic phase diagrams corresponding to polar mono-and multidomain samples in Figs.
2  were taken. In panel b, the phase boundaries, which are also present in the polar mono-domain case, are shown only as deduced from the magneto-current measurements. Labels of the phase boundaries (1a, 1b, 2a, 2b) correspond to those in Fig. 3. The additional phase boundary labeled by 1 * & 2 * is determined by magneto-current (solid blue line), by torque (dashed light blue line) and by susceptibility measurements (blue square). and their polar axes varies over a limited range, 54-90 • , while the field is rotated in the (110) plane. In polar mono-domain samples (Fig. 4a ), there are three magnetic phases showing up, the cycloidal, the Néel-type SkL and the FM state, in accord with for-mer studies  41, 50. Note that phase boundaries in Fig. 4a  are displayed from one hand, as obtained from magnetocurrent data on a nearly polar mono-domain crystal (Fig.
The sample was cooled using an Oxford helium flow cryostat. For changing the orientation of the magnetic field with respect to the electric contacts, the sample was mounted on a platform, which can be rotated by a stepper motor. To ensure low noise measurements, the platform was equipped with two coaxial cables. For magneto-current measurements, the current was recorded using Keysight B2987A electrometer while the magnetic field was swept with a typical rate of 0. 5-1 T/min. For pyrocurrent measurements, the current was recorded with the same electrometer while the temperature was swept from 3 K to 50 K with a rate of about 6 K/min. Torque magnetometry. Torque data was recorded with dynamic cantilever magnetometry (DCM)  29, 55. A single crystalline piece of GaV 4 Se 8 (spacial dimensions in the order of 100 µm) was attached to the end of a commercial cantilever (Arrow-TL1, Nanoworld).
The cantilever's motion is read out using an optical fiber interferometer using 100 nW of laser light at 1550 nm  56. Small-angle neutron scattering. Small-angle neutron scattering (SANS) was performed on a 11. 6 mg single crystal sample of GaV 4 Se 8. SANS patterns discussed in the main text were measured using the SANS-I instrument of SINQ at the Paul Scherrer Institut (PSI), Villigen, Switzerland. The wavelength of the incoming neutrons was 6 Å, the collimation and the sample-detector distances were set to 6 m. The magnetic field was applied in various directions within the (110) plane. Additionally, magnetic field dependence of the scattering data shown in the supplement was measured using the D11 and the D33 instruments at the Institut Laue-Langevin (ILL), Grenoble, France. The neutron wavelength of 5 Åwas selected and the collimator-sample and the sample-detector distances were set to 5 m.
Acknowledgements We thank  Á. Butykai  for stimulating discussions. This work was supported by the  DFG  via the  Transregional Research Collaboration TRR 80 From Electronic Correlations to Functionality (Augsburg/Munich/Stuttgart ), by the  Hungarian National Research, Development and Innovation Office NKFIH ,  ANN 122879   BME-Nanonotechnology FIKP grant  ( BME FIKP-NAT ), by the  Swiss National Science Foundation  via Grants No. 200020-159893 , the  Sinergia network Nanoskyrmionics  (Grant No. CRSII5-171003 ), and the  NCCR Quantum Science and Technology (QSIT).
We use global data from the Lunar Orbiter Laser Altimeter (LOLA) to retrieve the lunar tidal Love number h 2 and find h 2 = 0. 0387 ± 0. 0025. This result is in agreement with previous estimates from laser altimetry using crossover points of LOLA profiles. The Love numbers k 2 and h 2 are key constraints on planetary interior models. We further develop and apply a retrieval method based on a simultaneous inversion for the topography and the tidal signal benefiting from the large volume of LOLA data. By the application to the lunar tides, we also demonstrate the potential of the method for future altimetry experiments at other planetary bodies. The results of this study are very promising with respect to the determination of Mercury's and Ganymede's h 2 from future altimeter measurements.
(2010)  who only used cubic splines in longitude direction. For the retrieval of h 2 , we use data from the Lunar Orbiter Laser Altimeter (LOLA). LOLA is a multi-beam laser altimeter with a ground pattern of five spots with a distance of approximately 25 m from each other. The primary objective of LOLA is the generation of topographic maps of the lunar surface with appropriate resolution and accuracy for future robotic and human exploration  (Smith et al. 2010a ). Laser pulses are fired at a frequency of 28 Hz. While the measurement precision on a flat surface is 10 cm  (Smith et al. 2017) , knowledge of the spacecraft position and orientation limit the radial accuracy to about 1 m  (Mazarico et al. 2018). For a review of LOLA's achievements see  Smith et al. (2017). LOLA is a payload of the Lunar Reconnaissance Orbiter (LRO), which has been orbiting the Moon since June 2009.
Data We work with a subset of the over 7 × 10 9 range measurements that have been recorded and published on the Planetary Data System (PDS, Neumann 2009a). As a first filtering step, we only include LOLA shots within a predefined topographic range of ±13 km and observed at solar phase angles of < 90 •. This ensures that extreme outliers in height and LOLA shots that were recorded during the night where the so-called LOLA thermal blanket anomaly occurs do not enter the evaluation  (Smith et al. 2010b (Smith et al. , 2017)). As a second step, we divide the surface of the Moon in 16 tiles and for each derive a coarse 400 m/pixel LOLA Digital Terrain Model (DTM) compiled from all available tracks from all mission phases. Each track is then co-registered to the 16 tiles  (Gläser et al. 2013 (Gläser et al.
, 2018)). At each tile, we sort out the entire track segment if the mean height difference or the standard deviation to the DTM tile is > 100 m or if less than 500 points were co-registered to the tile. As a third step, to ensure a homogeneous spatial distribution, we select only measurements from the near-circular orbit phase of LRO extending over the 27 months between September 2009 and December 2011 (orbit numbers 1005-11,403), when LOLA achieved global data coverage. As a fourth step, we run a first adjustment as described in Sect. 3. Visual inspection of the spatial distribution of adjustment residuals ê (Eq. 13) reveals five further outlier orbits (orbit numbers  1803, 2351, 7756, 10, 302, 11, 226)  which we removed for a remaining total of K = 3,686,466,983 measurements from 10,016 orbits.