dataesr/scientific-paragraphs-categorization huggingface dataset:
e. cortical, subcortical and central part) were prepared for wider stems. Xper 2 and the computer-aided identification ). Xper 2 is a management tool for taxonomic descriptions that allows editing standardised descriptions (the descriptors and their states, logical dependencies between descriptors and groups of descriptors). This knowledge base can be used by palaebotanists and archaeobotanists as an interactive identification tool available on the Web, as it already exists for wood with the InsideWood Database (InsideWood 2004). In the Palm-ID knowledge base, taxa (subfamily, tribe and genera) of the palm family are described by 32 stem descriptors in 7 groups (e. g. , cortex, central cylinder, fibrovascular bundles, etc. ) with a total of 107 states.
A vegetation model-based climate reconstruction for the Eastern Mediterranean, reconstructed from pollen data extracted from the European Pollen Database, also indicates a major precipitation anomaly for this period (Fig. 5 ). The core B 22 is consistent with a termination of the drought event during the 9 th century BC. In Cyprus, the belated reappearance of state-level polities on the island during the 8 th century BC seems incontestable on archaeological grounds  [58]. Archaeological data from coastal Syria show that dense occupation reappears at the end of the 9 th or the 8 th century BC  [75]. Egyptian, Aegean, and Assyrian empires also recovered with diversified agro-production, pastoral activities, and sustained a cultural revival during this period  [20].
Late Cypriot IIC ceramics, imported from Cyprus, were also found at Gibala-Tell Tweini (Fig. 6 ), in the destruction layer dated from the end of the LBA. Gibala-Tell Tweini was a thriving trade center   [11] ; (c) Time-series (5000 BP to present by step of 100 years) of annual precipitation (anomalies from the present in mm/yr) averaged on Southeastern Mediterranean region (longitude 20uE250uE, latitude 30uN-45uN); the data are reconstructed from pollen data extracted from the European Pollen Database; (d) fluctuations in Nile floods, indicated by lake level variations of Lake Qarun (Fayum depression, Egypt) inferred from paleoshorelines and lake sediments  [73] ; (e) reconstruction of annual precipitation based on botanical-climatological transfer functions applied to pollen data from Ain Gedi sediments (Dead Sea shore)  [15] ; (f) Abundance of Cyperaceae pollen, a marker of fresh water input, in a sediment core from Burullus Lagoon in the north-central Nile Delta  [14].
This research was funded by the  Geological Survey of Belgium , the  UniversitePaul Sabatier -Toulouse 3 , and the  PAI PVI/34  ( Belspo)  project. This work is also a contribution to the  Labex OT-Med  ( ANR-11-LABX-0061 ) funded by the  « Investissements d'Avenir», French Government program  of the  French National Research Agency(ANR)  through the  A-Midex project  ( ANR-11-IDEX-0001-02 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We consider this explanation for the difference highly unlikely however, given that examples in Condition 7 were consciously constructed to test knowledge that speakers would be unlikely is present on the basis of which it would be possible to verify the sentence (given some appropriate knowledge dataset, say Wikipedia). For the actual knowledge-effect, the properties of the NP provide a basis for verification given the speaker's actual knowledge base. This explains the finding that the actual knowledge-effect is stronger: Our sentences that satisfied Lasersohn's criteria also satisfied von Fintel's criteria, but not the other way around. So, Condition 8 in fact tested both effects, while Conditions 7 (and 9) only tested one, the independent NP-effect. We also found that there was a topic-effect: there was a significantly higher number of TRUE responses in Condition 10, where an existentially sound NP was topicalised, (16b), than in Condition 9, where the NP with referential failure was topicalised (16a).
Setting new goals for international classification systems Given the relative failure to validate the DSM-or ICDderived categories, it is time to set new goals (Table  1 ) -and propose a range of possible, and rather diverse, strategies to support those goals (Table  2 ). An overriding concern in mental health has become the reduction of the population-health burden by adoption of various early intervention strategies  [28, 50, 51]. These focus clinical service development and related research on identifying early forms of illness not only to reduce current morbidity but also to prevent progression to more severe or chronic illness types and associated role impairment  [52] [53] [54] [55] [56] [57]. Although the fundamental empirical work in this area has focused largely on psychotic disorders, there is now a much broader clinical database emerging that is targeted at the early phases of the more prevalent anxiety and depressive disorders  [22, 53, [58] [59] [60] [61].
Greek has an expression meaning 'disorderly place' which translates literally as 'Jewish synagog'. And it's been suggested that French brouhaha and English charivari go back to non-Jewish perceptions of Jewish prayer services as being particularly noisy (some take those suggestions to be proven, but to my mind the etymology of those two words needs more study). More data from other languages could probably be cited, but the point is clear by now that in studying Afrikaans usages of Jewish interest, one must look at a range of languages -not only Dutch and South African Englishin order to put matters into perspective. We see the value of that approach not only with respect to the Afrikaans expressions themselves but also with regard to the correct interpretation of jodeskool. If you consider the usages I've just mentioned; only Afrikaans jodeskool and German /udenschule seem to be different in that they appear to mean 'Jewish school' (cf.
Three lakes are from peninsular Italy (Lake Ledro, Lake Accesa, Lake Trifoglietti), and one is from Sicily (Lake Pergusa). We investigate climatic trends during the Holocene to test whether reconstructions from pollen records can support opposing mid-Holocene summer precipitation regimes across the north-central (minimum precipitation) and southern (maximum precipitation) Mediterranean  (Magny et al. , 2012b). Special attention will be given to reconstructions of precipitation and temperature seasonality, as was the case for Lake Accesa  (Peyron et al. , 2011). Reconstructions of seasonal precipitation and temperature from Accesa brought new insight into the role of seasonality in this region and proposed an explanation for discrepancies between pollen, lake levels and isotope data observed in north-central Italy by invoking changes in precipitation seasonality  (Peyron et al.
Sites and data The core transect used in this study runs from north to south through Italy (Fig. 1 ), linking Lake Ledro, located on the southern slope of the Alps, to Lake Pergusa in Sicily. The sites are grouped into northern sites (Lake Ledro and Lake Accesa) and southern sites (Lake Trifoglietti and Lake Pergusa) for the purposes of most subsequent analysis. For all sites we provide information on the radiocarbon dates used in constructing the chronologies (Table  1 ). Site age models are described in their original publications (referenced below).
Lake Accesa (Tuscany, central Italy) Lake Accesa (42 • 59 N, 10 • 53 E, 157 m a. s. l. :  Magny et al. , 2007; Drescher-Schneider et al. , 2007; Vannière et al. , 2008  Although the Lake Accesa region is widely cultivated (cereals, vineyards and olive trees), vegetation in the region would likely be dominated by Quercus ilex  (Ozenda, 1979)  A core transect was carried out from the western shore of Lake Accesa  (Peyron et al. , 2011). Pollen data for the current study were extracted from two overlapping cores, AC3 and AC4 (AC3/4), obtained in a littoral mire, 50 m from the present-day lake shore. The chronology, based on 17 14 C dates and 4 tephra layers, spans the last 11 000 yr with a temporal resolution of 85 yr / sample (Table  1 ). Holocene vegetation at Lake Accesa (Fig. 2 ) was dominated by deciduous Quercus (probably Q.
Here, the modern analogue technique (MAT:  Guiot, 1990 ), the weighted averaging method (WA: Ter Braak and Van Dam, 1989), the weightedaverage partial least-squares regression (WAPLS: Ter Braak and Juggins, 1993), and the non-metric multidimensional scaling/generalized additive model method (NMDS/GAM:  Goring et al. , 2009)  are used. The WA, WAPLS and the NMDS/GAM are true transfer functions based on a calibration between environmental variables and modern pollen assemblages, whereas the MAT does not require real calibration and is based on a comparison of past assemblages to modern pollen assemblages. For all the methods presented here, we use the modern pollen dataset developed by  Dormoy et al. (2009) , containing more than 2000 samples from the Mediterranean region with climate estimates for sites developed by  New et al.
WAPLS WAPLS is a "classic" regression method which also assumes that the relationships between pollen percentages and climate are unimodal: each taxon grows best at a particular optimal value of an environmental variable and cannot survive when the value of that variable is too low or too high. If taxon ecology can be assumed to be constant through time, then, even if the overall pollen assemblage has no modern analogue, a reasonable reconstruction can be given. WAPLS operates by compressing the overall data structure onto latent variables. The modern pollen dataset used may be considered a large multidimensional matrix. Since there is some co-linearity among pollen taxa, and since some taxa will be related to climate parameters of interest, it is possible to reduce the dataset into a smaller number of components based   (1993)  requires transformation of the initial dataset using weighted averaging (ter Braak and van Dam, 1989) along a gradient defined by the climate parameter of interest, such that the pollen taxa that best define the climate gradient are weighted more heavily than those that show little specificity to the gradient.
NMDS/GAM This method, first developed from pollen assemblages in British Columbia, Canada  (Goring et al. , 2009) , has recently been successfully tested on Mediterranean pollen assemblages  (Dormoy et al. , 2009; Peyron et al. , 2011). This method begins by reducing the dimensionality of the dataset using non-metric multidimensional scaling, a non-parametric ordination method that retains the dissimilarity structure of the data to generate low-dimensionality representations. In this way it is somewhat similar to the MAT, although the ordination recovers not only the degree of dissimilarity between samples, but also the direction of dissimilarity. Once the lowdimensionality representation is generated, the NMDS/GAM method fits a generalized additive model to the ordination space to reconstruct the climate parameter of interest.
Validation of the methods and error calculation To some degree all methods are subject to error resulting from "noise" in the dataset. This noise may result from variation in basin characteristics, co-variance of climate variables, differential degradation of pollen taxa resulting from the deposition substrate, differences in pollen transport and local anthropogenic effects. The ecological noise is internalized differently in each pollen-based reconstruction method, although overlap exists among more closely related methods (e. g. effects of spatial autocorrelation: Telford and Birks, 2005; effects of sample depositional environments:  Goring et al. , 2010). In general, as noise in the pollen dataset increases, model error increases. But as dataset size increases, many models become more robust  (Birks et al.
, 2010). More details on the validation procedure used for pollen-climate calibration with the European pollen dataset are given in  Peyron et al. (2011). Non-climatic factors may also affect pollen assemblages during the Holocene. Human impacts in particular have affected the natural vegetation of the Mediterranean since ∼ 7500 cal yr BP, but disentangling climatic and anthropogenic causes of vegetation change is complex. For example, both human activity and climate may have resulted in the apparent aridification in Sicily and across the Mediterranean Basin at 3500 cal yr BP  (Sadori et al. , 2013). While pollen records may be susceptible to change from anthropogenic effects, previous studies show that human impacts on Mediterranean vegetation (using pollen as a proxy) are often hard to detect prior to the Bronze Age  (Sadori et al.
(e) Pollen-based temperature index "T index" for the marine cores MNB3 (North Aegean Sea), and NS14 (South Aegean Sea),  (Kouli et al. , 2012). (f) Pollen-inferred temperature of the warmest month for Lake Pergusa (as for Fig. 3 ), MAT only. (g) Polleninferred temperature of the warmest month for Lake Trifoglietti (as for Fig. 3 ), MAT only; the curve of temperature is calculated with a moving average (bold curve) and raw values are also plotted (dotted curve). (h) Reconstruction of temperatures of the warmest month (anomalies) for Southern Europe based on pollen data from over 500 pollen sites from across Europe, MAT only  (Davis and Brewer, 2009; Davis et al. , 2003). Fig. 6. Comparison between pollen-inferred summer precipitation (MAT only) and lake-level variations at Lakes Ledro, Accesa, Trifoglietti and Pergusa.
More details on the lake-level data are given in  Magny et al. (2012a)  for Lake Ledro,  Magny et al. (2007)  for Lake Accesa, and  Magny et al. (2011)  for Lake Preola (Sicily). Oxygen isotope data based on speleothem from Soreq Cave, Israel, is also plotted for comparison with eastern Mediterranean sites  (Bar-Matthews and Ayalon, 2011; Bar-Matthews et al. , 1998; Vaks et al. , 2006). MRCAI = period of maximal rate of change in annual insolation. Italy  (Piccarreta et al. , 2011). The correlation between the precipitation reconstruction and independent assessments of hydrological activity may indicate that, while the reconstruction values may be offset strongly at Lake Trifoglietti, the anomaly trends are consistent with long-term change in regional precipitation. One goal of this study is to test the hypothesis proposed by  Magny et al.
Acknowledgements. This study is a part of the  LAMA ANR  project ( MSHE Ledoux ,  USR3124 , CNRS) financially supported by the  French CNRS  ( National Centre for Scientific Research ). This project is supervised by  Michel Magny  (LCE,  UMR6249 ,  University of Franche-Comté ) and  Nathalie Combourieu-Nebout  (LSCE,  UMR1572 CEA-CNRS-UVSQ ). This is LSCE contribution no. 4584. Simon Goring  is currently supported by the  NSF  Macrosystems-funded  PalEON  Project. We also thank  Stefania D'Angelo  ( WWF Nature Reserve Lago Preola e Gorghi Tondi ). We also express special thanks to  Elena Ortu  and  Boris Vannière  for fruitful discussion. Edited by: M. -F. Loutre.
The very low Pb levels eventually obtained after multiple passes (< 1 µg. g -1 , see Fig. 3 ) demonstrate that the outer contaminated layers are eventually removed and, at this point, the remaining traceelement data can be considered free of such artefacts. This experiment suggests that after about four passes Frankcombes Cave is located in south central Tasmania (42. 53°S, 146. 45°E, ~360 m above sea level;  Desmarchelier et al. , 2006). The cave is formed in the Ordovician marine limestone that comprises the floor of the Florentine Valley. The cave is 900 m long, with an upper and lower chamber. The lower chamber contains an active streamway. Both straws in this study were collected from the upper chamber, which we estimate to be ~10-15 m below the surface. Climate records for the area are available from the Australian government Bureau of Meteorology.
ACKNOWLEDGMENTS Since 2002, the  Río Bec  project has received continuous support from the  Instituto Nacional de Antropología e Historia and several other Mexican and French institutions. I would also like to thank the entire crew of the  Río Bec project  for their support over the course of this research. I am particularly grateful to  Amparo Robles ,  Joel Olvera ,  Damian Alvarez , and  Isaac Barrientos  for their indispensable assistance with the fieldwork. I would like to thank  Dominique Michelet ,  Charlotte Arnauld ,  Philippe Nondédéo ,  Damien Bazy ,  Travis Stanton ,  Gabriel D. Wrobel ,  Sonja A. Schwake , and an anonymous reviewer for their helpful comments on the manuscript. I thank  Michelle Elliott  for the translation of this article from French to English,  Nicolas Latsanopoulos  for his wonderful drawings of the funerary ceramics, as well as  Sara Dzul  for the ceramic type identifications, and  Elodie Mas  for the shell identifications.
A new set of sound files was created for the sister-melody condition by mixing the melodies played with the original instrument with the same melodies played with a simulation of the sister instrument. The simulation consisted in a pitch-shifting of each note of the original instrument using the pitch-shift algorithm with preservation of the spectral envelope available in the software Audiosculpt 1. In other words, the simulated sister instrument had the same spectral structure as the original instrument, but all the frequencies were shifted. There is no resampling in Audiosculpt, rather pitch is shifted with conservation of the duration using fast Fourier transform (FFT) and inverse FFT. Two sound files here (http://katestevens. weebly. com/stimuli. html) demonstrate that the manipulation does not alter the timbre of the sound.
In order to get the necessary amount of pitch shifting for each note, the sister instrument was recorded with the performer playing the same nine notes as for the original instrument. The recording used the AKG C414(B) microphone, MOTU 896 HD firewire audio interface, a MacBook and the software MAX/MSP. Each note of the sister instrument was analyzed in Audiosculpt in order to find the pitch of each note in Hz. The same operation was performed on the original instrument in order to calculate the pitch difference in Hz (see Appendix 1). Then, each note of the original instrument was pitch-shifted to the appropriate value using Audiosculpt, to create a "simulation" of the sister instrument, to ensure that the duration and tonal dynamics of each sister tone were identical to those of the corresponding original tone.
Other researchers use some variables measured from 3D skulls to establish discriminant functions. Spradley and Jantz  [16]  construct multivariate discriminant models using the skull data from the Forensic Anthropology Data Bank. They measure different variables for different races, and the highest identification rate is no more than 90%. Jantz and Ousley  [17]  issue the computer-aided software called Fordisc for skeleton analysis. This software measures skeleton characteristics by the human-computer interactive way and utilize the data from American Forensic Data Bank to establish the discriminant function. Guyomarc'h and Bruzek  [18]  compare the sex identification effects of the software for different races such as Thailand and France, and the correct recognition rate is between 52. 2% and 77.
As in  [25] , the back part of the reference skull is cut away (as shown in Figure  2 ) considering that there  From the skull dataset, the mean skull data S and covariance matrix Σ of the mean normalized skulls are calculated. PCA essentially transforms the mean normalized shape data into a subspace spanned by the orthogonal unit eigenvectors U  ,  = 1, 2,. ,  -1, of the covariance matrix in descending order according to their associated eigenvalues    , which represent variation modes of the data. Then the skull statistical shape model is constructed as in the following parameterized model: S (a) = S + 𝑀 ∑ 𝑘=1 𝑎 𝑘 U 𝑘 , (1) where the number  is the mode number, usually determined by a variance contribution rate calculated from the cumulative eigenvalues, and the combination coefficient a = ( 1 ,  2 ,.
Results The used data are the 208 whole skull CT scans described in Section 2. We chose about three-fourths of the 208 skulls according to the age distribution as training samples, including 92 males and 58 females, and other skulls as test samples. In order to determine an appropriate mode number ( in (1)) to build the statistical shape model, we use the trial and error technique and analyze the variation of the classification accuracy of the test samples with varying the mode number by experiments. It is well known that, in PCA, generally only some eigenvectors corresponding to large eigenvalues of the covariance matrix represent modes of variation of the data, while others represent noises. We vary the mode number from 23 to 150, corresponding to variance contribution rate from 96% to 100%, and the correct classification rates for test samples are shown in Figure  4 , while the rate of training samples is 100% when the mode number is larger than 80.
An analytical study of the Raman signal can be used to identify the phases present in the volume of the analyzed system. Typically, many non-colored minerals and compounds can be identified by simple comparaison with reference spectra found in databases  [75, [165] [166] [167] [168] [169] [170] [171] [172]. The narrower bandwidth of many signatures leads to a better detectivity of minor phases by Raman spectroscopy than by IR spectroscopy. However, the large variation of the Raman signal intensity with chemical bond polarizabilities (no spectrum for ionic bonding compounds, intense spectrum for covalent bonding compounds) renders quantitative analysis difficult. Recently available (portable) IR spectrometers give very useful information in the case of samples with flat, glossy surfaces  [173, 174].
The specific interaction between the laser light and the electronic levels of chromophores  [117, [173] [174] [175]  gives rise to Raman resonance that leads to a high detectability, but requires a deep understanding of the phenomenon and, therefore, prevents from using databases. Instead, a Solid State Physico-Chemist approach is mandatory  [176] [177] [178] [179]. This approach, through the modeling of the Raman signal, allows for the analysis of the micro and nanostructure of matter, thus detecting many technological signatures in the objects: second phases, short range-order and structural distorsions, grain orientation and shape, etc. A discussion of the different models developed, especially for poor crystalline materials (Figure  6 ), is out of the range of this text but can be found in refs  [160] [161] [162] [163] [164].
This also justifies the link between corpus linguistics and cognitive linguistics which is claimed in this section. Secondly, she presents the data gathered for the study. They consist of a sample of phrases (V NP-constructions, i. e. containing a verb and a noun phrase, e. g. cross X mind, meet X eye, etc. ) included in the Collins COBUILD Dictionary of Idioms (1995), to which are added a number of frequent phrases not included (e. g. call X police). Informants are asked to judge the idiomaticity of each phrase, and the results are then normalised for easier comparison. In Chapter 3, Wulff looks at the question of compositionality. After looking at previous approaches, she adopts Berry-Rogghe's view (1974) that compositionality can be measured by comparing the phrase's collocates with those of the constituent parts.