dataesr/scientific-paragraphs-categorization huggingface dataset:
2011 ) and heuristic approaches for transdisciplinary sustainability studies (Huutoniemi and Tapio 2014). There is always tension between broad generalities and context-specific considerations, and comparative cross-site research will require data reduction and control of variation (Preissle and LeCompte 1981,  Bollen et al. 1993). Case studies create informative and detailed local narratives that, when analyzed across sites, serve to identify commonalities as well as contrasts. With long-term data on socio-ecosystem conditions at a number of sites, it becomes possible to address place-to-place development trajectory differences. Using information from multiple ILTER sites is a way to examine land-use and cover change over time as well as the relative impact of ecosystem constraints on historical and current public decisions.
Finally, all participants are committed to working toward coordination and harmonization of research goals and data collection protocol. Recently, 22 European ILTER members were awarded a European Union Horizon 2020 grant to develop their infrastructures toward these goals. For more information of the sites, please refer to Tables  1  and 2 , and Figure  3. Marker's shape refers to site's continent (star is Africa, squares are Americas, triangle is Asia and circles are Europe).
Acknowledgments: The authors thank  Raúl Ahedo ,  Sandokan Barajas ,  Cristina Branquinho ,  Atzimba López , and  Lyliana Rentería  who helped with the preparation of the manuscript. We also thank a couple of anonymous reviewers for their comments and suggestions. The document was prepared during a visit by  Manuel Maass  to the  Finnish Environment Institute (SYKE)  with a DGAPA-UNAM sabbatical scholarship and within  CONACYT  support for ILTER. Some of the insights we have achieved were possible thanks to the partial support of the  European Union Seventh Framework Programme  ( FP7/2007(FP7/ -2013 ) ) under grant agreement n° 283093 -The  Role Of Biodiversity In Climate Change Mitigation (ROBIN ). The partial support of the project no:  308428  (OpenNESS) under the  same Programme  is also acknowledged.
Data from  Chamela LTER  derives from project  SEP-CONACYT 179045. Data from LTER Montado derives from projects  FCT-LTER/BIA-BEC/0048/20 09  and OPERAs ( FP7-Grand Agreement 308393 ). Data from Omora LTER derive from grants  IEB-ICM P05-002  and  IEB-CONICYT PFB-23. Patrick Bourgeron  acknowledges primary support from the  US NSF Coupled Natural Human Systems Program  ( DEB-1115068 ), as well as additional funding provided by a  Water Sustainability and Climate grant  ( USDA ANIF-2012/67003/19802 ) and the  Niwot Ridge Long-Term Ecological Research Program (US NSF   DEB 9810218 ).
Results Optical image correlation. We measured co-seismic fault slip for the two events using the optical image correlation software COSI-Corr (Co-registration of Optically Sensed Images and Correlation)  15  , which allows for the precise co-registration, orthorectification and subsequent correlation of pairs of pre-and post-event aerial photographs (see Methods for detailed processing steps). Specifically, to quantify surface motion we track movement of features between pairs of pre and post-event ortho-air photos using COSI-Corr's phase correlator that uses an iterative, unbiased processor that estimates the phase plane in the Fourier domain  15. The correlation results produced from subpixel matching of the before and after air photos are presented in terms of 2D horizontal surface deformation maps (Fig.
Methods Subpixel image correlation of air photos. For the Landers and Hector Mine earthquakes we selected 31 and 21 pairs of stereo-pair (60% overlap), 1 m resolution, National Aerial Photography Program aerial photographs, respectively, with 8 × 8 km footprint (purchased from http://earthexplorer. usgs. gov/). We selected air photos acquired in 1989, 1994 and 2002, where air photos from the two earlier flight missions serve as the pre and post Landers data and the latter two serve as the pre and post Hector Mine data. We note air photos from the 1994 flight mission serve as both the pre-Hector Mine and post-Landers dataset, giving rise to deformation maps for the two earthquakes derived from the same data acquired from the exact same optical sensor and flight mission, which helps minimize differences in data quality and accuracy.
To produce correlation maps that accurately constrain the ground deformation pattern, the input aerial photographs must be precisely orthorectified and co-registered before correlation. The COSI-Corr program (http://www. tectonics. caltech. edu/slip_history/spot_coseis/ download_software. html) allows for accurate orthorectification of images by taking into account the topography using a digital elevation model (DEM), the internal camera geometry using a camera calibration report (https:// calval. cr. usgs. gov/calval_osl/calibration_reports/) to correct for optical distortions and the exterior orientation determined from ground control points (GCPs)  17. To account for topographic distortion of the images, for both the Landers and Hector Mine events, we used the same 2012, 10 m National Elevation Dataset DEM that covers both ruptures, acquired from the USGS (http://ned.
Thus, more size bins improve the simulation of atmospheric processes. The radiative effects of dust over the area are discussed and evaluated with the CALIPSO dust optical depth (DOD). This study is among the first studies evaluating the vertical profile of simulated dust with a pure dust product. Reanalysis winds from ERA-Interim and the total precipitation flux from the Climate Research Unit (CRU) observational gridded database are used to evaluate and explain the discrepancies between model and observations. The new dust binning approach increases the dust column burden by 4 and 3 % for fine and coarse particles, respectively, which increases DOD by 10 % over the desert and the Mediterranean. Consequently, negative shortwave radiative forcing (RF) is enhanced by more than 10 % at the top of the atmosphere and by 1 to 5 % on the surface.
, 1993) , but there is a recently implemented alternative option to use the Community Land Model (CLM4. 5; Oleson et al. , 2013). The radiation transfer scheme used in RegCM4 is based on the NCAR Community Climate Model version 3 (CCM3;  Kiehl et al. , 1996)  with the additional option of the correlated-k rapid radiation transfer model (RRTM;  Mlawer and Clough, 1997; Mlawer et al. , 1997)  to improve the model representation of the radiation processes in the longwave spectrum  (Iacono et al. , 2000). The chemical part of the model contains gas-phase chemistry  (Shalaby et al. , 2012; Steiner et al. , 2014)  as well as natural and anthropogenic aerosols  (Solmon et al. , 2006; Zakey et al. , 2006 Zakey et al. , , 2008)). Most of the natural aerosols, such as dust and sea salt, are driven by RegCM4 meteorology, while all anthropogenic aerosols, organic carbon, black carbon and pollen require emission datasets.
LIVAS The "LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies" (LIVAS;  Amiridis et al. , 2015)  is a three-dimensional global climatic dataset derived from CALIPSO measurements and funded by the European Space Agency (ESA). CALIPSO obtains highresolution profiles of the attenuated backscatter of aerosols and clouds at 532 and 1064 nm and retrieves aerosol optical properties below optically thin clouds, in clear skies and above clouds  (Winker et al. , 2009). Thus, in regions with frequent optically thick clouds, aerosol measurements are limited. In regions with an absence of clouds like the Sahara, measurements of aerosol species (most likely dust) are available more frequently. LIVAS utilizes the level 2 (version 3) product of CALIOP measurements  (Amiridis et al.
, 2015). The CALIPSO level 2 database determines the vertical location of cloud/aerosol layers  (Vaughan et al. , 2009) , distinguishes the clouds from the aerosol layers  (Liu et al. , 2009) , separates aerosol layers into six subcategories (dust, marine, smoke, polluted dust, polluted continental and clean continental;  Omar et al. , 2009)  and calculates the AOD for each selected layer  (Young and Vaughan, 2009). The LIVAS extinction dust product is corrected for the lidar ratio (LR) based on multi-year measurements performed by the ground-based lidar stations of the EARLINET lidar network (https://www. earlinet. org) and intensive campaigns in different dust regions around the globe  (Wandinger et al. , 2010; Hänel et al. , 2012; Baars et al. , 2016). The LR of dust particles depends on their refractive index and may vary for aerosols of the same type.
(2016b)  showed that LIVAS correlates well with the highresolution TERRA MODIS and MACC dust optical depth over land-covered regions in the eastern Mediterranean. Monthly mean LIVAS data are available at a 1 • × 1 • horizontal resolution with a vertical resolution ranging from 60 m (-0. 5 and 21 km) to 180 m (above 21 km;  Amiridis et al. , 2015). We concentrate on the troposphere where the vertical distribution of layers is constant. In our work we use the specialized LIVAS pure dust product, which includes the extinction coefficient of pure dust calculated from the dust percentage of "dust" and "polluted dust" aerosol subcategories of CALIPSO  (Amiridis et al. , 2013). Since CALIPSO is a nongeostationary satellite, the obtained mean monthly profiles are highly dependent on the date and time the measurements were taken.
Meteorological data ERA-Interim is a state-of-the-art global atmospheric reanalysis product developed by the European Centre for Medium-Range Weather Forecasts (ECMWF;  Dee et al. , 2011). The data assimilation system uses various types of observational data from ground-based stations, radiosondes, ships and satellites. Data availability starts from 1979 and is extended forward in near-real time. Its assimilation scheme uses a 12 h cycle, where observational data are combined with forecast information from the previous time step in order to construct the global atmospheric conditions. ERA-Interim reanalysis database is exceptionally useful over isolated areas like the Sahara, where meteorological measurements are limited. Wind velocity and direction, associated with dust emission and transport, were used to evaluate RegCM4 wind fields.
ERA-Interim is also used for boundary conditions in several regional climate models (e. g. , RegCM4) for hindcast simulations. Climate Research Unit (CRU) data are a gridded global climate database of monthly meteorological measurements from ground-based stations  (Harris et al. , 2014). The dataset includes surface measurements of six meteorological variables, notably precipitation and temperature. Stations are interpolated into a 0. 5 × 0. 5 grid that covers all of the land surface of the planet (except Antarctica). Data availability peaks between the period 1950 and 2000 and drops dramatically in the last decade. During the period 2007-2014 and around the area of the Sahara, more than 600 monthly measurements of precipitation are included in the database from various stations. However, we note that most of the continual measure-ments occur at stations close to the border of the desert, and station coverage is generally limited over the Sahara.
3. 1). Because the aerosol lateral boundary conditions used a 4-bin dust model, we modified the boundary conditions for the 12-bin experiment. The new bins were defined according to the ratio between the 4-and 12-bin size range and size limits. Multiply-ing this ratio by each month and atmospheric level we have created the necessary global boundary condition for the 12bin dust scheme. This method assumes that the number of particles is homogeneously distributed in each bin. The dust size range of the boundary conditions dataset spans 0. 01-20 µm. Therefore, coarse dust size bins in both DUST4 and DUST12 scheme (e. g. , that exceed the upper limit of the 20 µm) are not influenced by boundary conditions. This does not introduce a significant bias in our results since large particles (> 20 µm) have a short atmospheric lifetime and the main dust sources from outside the domain are located far from our simulation boundaries.
Furthermore, the fine particle emission to deposition ratio steadily increases from March to August, leading to an accumulation of fine dust particles in the atmosphere that increases the column burden and the DOD. In the Sahel throughout the year, emissions are 2 times greater than the deposition for fine particles, with a mean ratio of 2. 26. As discussed later, RegCM4 exhibits some biases in the total precipitation annual cycle that influences this ratio. The column burden of dust can be affected by numerous meteorological variables that may alter the emission, deposition or the circulation and transport of dust. Thus, we have evaluated these variables with the observational gridded and reanalysis data to explain the spatial biases observed in the DOD. We chose the ERA-Interim for the evaluation of wind fields (surface, 925 and 850 hPa) in order to have large spa-  tial coverage and a long-term, continuous availability of data.
However, considering that the same wind pattern continues at both 925 and 850 hPa and that the larger amount of dust is concentrated in these layers (Fig. 7 ), it can also decrease its southward transport and the outflow of dust in the eastern Sahara. In Fig. 8 , the annual cycle of the meridional wind component confirms that, during the summer (June-September), the southward wind is underestimated by the model by more than 1 m s -1. Thus, a high load of dust remains stationary for a longer period over the eastern Sahara that likely increases the modeled column burden and the DOD (Fig. 4e ). Away from the Sahara region and especially in semiarid environments, like the Sahel, precipitation can affect both emission and wet deposition processes. According to the CRU database, RegCM overestimates precipitation in the Sahel by 10-20 mm month -1 (Fig.
Furthermore, the 0. 9 percentile value of the averaged wind over the desert is 4. 93 and 5. 92 m s -1 for RegCM and ERA-Interim, respectively, which indicates that the model potentially overestimates dust emission flux. In the Sahel during April, May and June the total precipitation is overestimated by the model in comparison with the CRU database. Thus, wet deposition is enhanced and the emission flux is decreased since the ground has higher moisture. Overall, this process-level analysis suggests that meteorological drivers such as wind and precipitation may explain some model biases with observations. These changes in the physical processes then link to the radiative properties that affect climate. We evaluate the dust extinction (DEX) from the model with LIVAS observations, and find that the RegCM overestimates DEX in all subregions in the middle and upper troposphere, which can be attributed either to an overestimation of dust convective transport or to an underestimation of some other deposition process (e.
Acknowledgement. This work is supported by the project  GEO-CRADLE  (Coordinating and integRating state-of-the-art Earth Observation Activities in the regions of  North Africa ,  Middle East , and  Balkans  and  Developing Links  with  GEO  related initiatives towards GEOSS), grant agreement no. 690133 , funded through the  European Union   Horizon 2020 Programme -Topic :  SC5 -18b-2015, Integrating North African,  Middle East  and Balkan Earth Observation capacities in GEOSS. We would also like to acknowledge the support for international research staff exchange through the  REQUA (Regional climate-air quality interactions ) project ( FP7-PEOPLE-2013-IRSES -Marie Curie Action ,  PIRSES-GA-2013-612671 ) and  ACTRIS-2  project (grant agreement no. 654109 , funded through the  European Union 's  Horizon 2020 programme ).
5 Data availability ERA-Interim wind velocity data are publicly available from the ECMWF and can be downloaded from http://www. ecmwf. int/en/research/climate-reanalysis/ era-interim. CRU TS 3. 23 precipitation data can be obtained from https://crudata. uea. ac. uk/cru/data/hrg/cru_ ts_3. 23/cruts. 1506241137. v3. 23/. The LIVAS database is available at http://lidar. space. noa. gr:8080/livas/. The regional climate model ReGCM4 code is available at https://gforge. ictp. it/gf/project/regcm/frs/. RegCM4 simulation data are available upon request from Athanasios Tsikerdekis (tsike@geo. auth. gr). The Supplement related to this article is available online at doi:10. 5194/acp-17-769-2017-supplement.
fNIRS analysis Measured concentrations of O 2 Hb and HHb from each of the Portalite devices were exported to MATLAB (MATLAB and Statistics Toolbox Release 2012b, The MathWorks, Inc. , Natick, Massachusetts, United States), in which further data processing was done. First, O 2 Hb and HHb signals of the three channels (the three transmitter-receiver distances) per PortaLite were averaged. Then, the moving standard deviation-based artifact removal (movement artifact reduction algorithm-MARA) method was performed within each trial  [47]. The threshold for artifact detection was set to 0. 45 for O 2 Hb and 0. 18 for HHb, with a window length for moving standard deviation calculation at 0. 5 s, and a window length for artifact correction (LOESS smoothing window) on 1 s. These parameters were chosen after testing several settings and visual inspection of the data by JC and FN on adequate removal of large (movement) artifacts while not affecting physiological fluctuations.
Gait performance analysis To be able to judge whether our protocol was able to detect behavioral dual task effects and to interpret the level of PFC activity in relation to behavioral performance, gait parameters, and performance on the cognitive tasks were measured. Walking performance parameters were measured on a GAITRite® mat (CIR Systems Inc. , Clifton, NJ 07012, USA), over which the participants walked while walking forth over the 8-m course. The GAITRite® mat is an electronic roll-up walkway with pressure sensors embedded in a carpet. The carpet is 5. 18-m long and 0. 90-m wide, and the active area is 4. 27-m long and 0. 61-m wide. The mat is connected to a personal computer using GAITRite software version 4. 0 (CIR Systems Inc. , Clifton, NJ 07012, USA) for processing and storing the data.
g. , skin) hemodynamics  [59, 60] , for example, by using a short reference channel  [59]. Thus, we cannot rule out the influence of blood flow through skin or the occipitofrontalis muscle, which might have increased during task performance  [61]. However, in frontal brain areas, high correlations were found between fNIRS signals and fMRI signals from the cortical gray matter layer while performing several cognitive tasks  [62, 63]. These correlations were higher than correlations between fNIRS signals and soft tissue fMRI signals  [62]. Although our fNIRS signals are likely affected by skin blood flow, we can still assume based on these data that they do reflect cortical neuronal activity. A further limitation is that only PFC activity levels were measured. We did not measure any other cortical areas to ensure specificity of signals to PFC instead of whole brain effects.
s → J/ψ φ and B 0 s → D - s D + s decays play key roles in testing the quark-flavour sector of the Standard Model. The theoretical interpretation of these observables is, however, limited by uncertainties from doubly Cabibbo-suppressed penguin topologies. With continuously increasing experimental precision, it is mandatory to get a handle on these contributions, which cannot be calculated reliably in QCD. In this summary, we discuss a data driven method based on the SU(3) flavour symmetry of QCD to relate the penguin contributions in B 0 → J/ψ K 0 S , B 0 s → J/ψ φ and B 0 s → D - s D + s to unsuppressed counterparts in decay modes with similar dynamics. The fit results obtained with the currently available data are presented for all three modes. In addition, we discuss prospects for the LHCb upgrade and Belle II era, and illustrate the possibilities for the determination of hadronic parameters.
Introduction We have yet to see an unambiguous signal from physics beyond the Standard Model. The picture emerging from the first years of data taking at the Large Hadron Collider (LHC) is, within the current level of precision, globally consistent with the Standard Model (SM). This is in particular true for the determination of the "B 0 q -B 0 q mixing phases" φ d and φ s from CP violation measurements in B 0 → J/ψ K 0 S , B 0 s → J/ψ φ and B 0 s → D - s D + s. If these CP phases are at all affected by new physics (NP) contributions, the impact is small and thus more challenging to differentiate from the suppressed, and so far ignored, higher order SM corrections. In view of the forthcoming physics runs at the LHC and KEK e + e -super B factory, which promise to reduce the experimental uncertainties on the CP measurements in these decays, we thus need to have a critical look at the theoretical assumptions underlying the experimental analyses.
7 (U-spin) • , (5. 2) and a solution for the CP phase φ s = -0. 6 +9. 8 -9. 9 (stat) +0. 3 -0. 7 (U-spin) •. (5. 3) Despite the suppression through the parameter ε, penguin topologies may have a sizeable impact on the extraction of φ s from B 0 s → D - s D + s , although the uncertainties are still too large to draw strong conclusions. Future Prospects Looking at how the picture derived from the current data can evolve for the LHCb upgrade and Belle II era, two main strategies can be identified. In a favourable scenario the input from the CP asymmetries in B 0 → D - d D + d is sufficient to determine a and θ , i. e. the use of the H observable is not necessary. This situation has the smallest associated theoretical uncertainty, and in addition allows us to get experimental access to the ratio of hadronic amplitudes, similar to Eq.
Despite that the Badakhshan Province (Afghanistan) remains the most plausible hypothesis for the lapis lazuli used in antiquity, alternatives proposed in literature are worth to study to confirm or disprove their historical reliability. In this work, a protocol for determining the provenance of lapis lazuli rocks used for carved artefacts is described. Markers for the univocal attribution of the raw material to a source were identified analysing 45 rocks of known provenance (among which 15 georeferenced) from 4 quarry districts. To the best of our knowledge, this reference database is the widest in provenance studies on lapis lazuli. All the markers are recognisable by means of Ion Beam Analysis (IBA) techniques, in particular micro-proton-induced x-ray emission (PIXE) and microionoluminescence (IL).
Protocol for lapis lazuli provenance determination To solve the issue, we started in 2008 a long-term research, involving an interdisciplinary team. Until now, 45 lapis lazuli rocks of known provenance from 4 quarry districts have been analysed, creating a database that, to the best of our knowledge, is probably the widest in provenance studies on this material. Our database is composed by 21 samples from Badakhshan in Afghanistan; 4 samples from Liadjura-Dara, Pamir Mountains in Tajikistan; 11 samples from Lake Baikal area in Siberia (4 from Malaya Bistraya quarries and 7 from Sludyanka River quarries) and 9 samples from Coquimbo region in Chile. Samples from Tajikistan and Siberia are georeferenced, i. e. GPS coordinates are known. In the case of Lake Baikal, a geological expedition was organised by the authors to collect samples from two quarries in the area (Malaya Bistraya and Sludyanka River), considering that the mines are no longer exploited and it is difficult to find rocks of recorded provenance.