dataesr/scientific-paragraphs-categorization huggingface dataset:
Despite the high genetic correlation, sex-specific correlations with anorexia nervosa were significant only for the females-only dataset. This suggests that the sex-specific genetic component of empathy can contribute differentially to psychiatric conditions. Several other factors may explain the observed phenotypic sex difference. For example, genetic variants for empathy may be enriched in sex-specific gene expression pathways. We conducted preliminary analysis by investigating if there is an enrichment in sex-differentially expressed genes in cortical tissue samples, but did not find significant enrichment. However, sex-specific gene expression is a dynamic process with both spatial and developmental differences  49, 64. Investigating across different tissues and developmental time points in well powered gene expression datasets will help better understand sex differences in empathy.
There are a few limitations that need to be taken into consideration in interpreting our results. The EQ is a self-report measure, and while it has excellent psychometric properties and construct validity, and it is unclear how much of the intrinsic biological variation in this trait is captured by it. Further, while this is the largest GWAS to date of self-reported empathy, it still is only modestly powered, reflected in our inability to identify genome-wide significant loci. This modest statistical power influences subsequent analysis, and we highlight several nominally significant results for further investigation in larger datasets. In conclusion, the current study provides the first narrow sense heritability for empathy. While there is a highly significant difference on the EQ between males and females, heritability is similar, with a high genetic correlation between the sexes.
Acknowledgements We thank  Richard Bethlehem ,  Florina Uzefovsky , and  Paula Smith  for discussions of the results. We are grateful to  Brendan Bulik-Sullivan ,  Hillary Finucane , and  Donna Werling  for their help with the analytical methods. This study was funded by grants from the  Medical Research Council , the  Wellcome Trust , the  Autism Research Trust , the  Templeton World Charity Foundation , the  Institut Pasteur , the  CNRS  and the  University Paris Diderot. VW is funded by  St. John's College, Cambridge , and  Cambridge Commonwealth Trust. The research was funded and supported by the  National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East of England at Cambridgeshire and Peterborough NHS Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the  NIHR  or the  Department of Health.
Such a demanding survey cannot be achieved as even modern in situ measurements of sediment discharge inherently lead to spatially sparse data, specific to one location along one river. In addition, such datasets are also temporally discontinuous, recorded at a specific date or with a frequency that rarely accounts for extreme events and the temporal variability of river discharge. To finish, these datasets are incomplete and biased, as bedload transport is rarely monitored  10. Nevertheless, basin-scale eroded sediment ultimately concentrates in oceanic sizelimited sedimentation zones offshore river mouths, where they must provide a clear gravimetric signal. For instance, an accumulation of 0. 5 cm year -1 of sediment replacing water over a 200-km radius region leads to a ~1 Gt year -1 net mass increase.
Yet the grain size significantly controls the extension of the estimated sedimentation zone. We thus tested a range of possible grain sizes, but robust estimates of the grain size distribution compiled in accessible database would make our sedimentation zones estimates more reliable. Another limitation comes from the GRACE data, which inherently suffer from leakage of hydrological signals into the coastal ocean  21. Although such a leakage effect is efficiently reduced in the regularized solutions we use (see Methods), it prevents from identifying masses of sediment accumulated out of rivers with sediment discharges smaller than ~150 Mt year -1 (Fig. 4  and Table  1 ) and makes this study focused on rivers having the world's largest sediment discharges. As an integrated sediment mass estimates, GRACE data complement in situ measurements by widening the range of spatial and temporal scales and providing a homogenous method to quantify these masses at the global scale.
7, VIC), WGHM v2. 1 and v2. 2b, AWRA-L (Supplementary Table  4 ). GRACE s2 is computed by removing the Australian Water Resource Assessment (AWRA in Supplementary Table  5 ), which is assimilating GRACE data  59. This approach is interesting as it considers GRACE signal on the continents to improve the representation of continental water storage changes. See Supplementary Fig. 1  and Supplementary Table  5  for details about each model. GRACE data information content and inversion strategy. The goal of this section is to investigate the data quality of different GRACE products and evaluate their ability to estimate localized mass changes close to the coast. The approach is led with both CSR regularized GRACE solutions  56  and CSR RL5 SH solutions  60  with different processing strategies.
Acknowledgements M. M. is supported by a postdoctoral grant by  Centre National d'Etudes Spatiales (CNES)  and by the  CRITEX  project funded by the  Agence Nationale de la Recherche  ( ANR-11-EQPX-0011 ). We acknowledge support by the  EROQUAKE  project funded by the  Agence Nationale de le Recherche  ( ANR-14-CE33-0005 ). We also acknowledge support from Université Rennes 1. We thank  Alexandre Guay  for his insights on a preliminary version of this work. We thank  Jean Braun ,  Saggy Cohen , and  Martine Simoes 's insightful discussions. Mette Bendixen  and  Stephen Darby  have provided stimulating reviews.
Superficial velocity is defined as the mean velocity in the porous media Figure  3  illustrated the link between mean physical velocity   and mean superficial velocitiy   by porosity value. A B C C F B E B B B C C A B A E γ = V fluid V total (1) U s = γU p (2) Since the objective of this work is not to develop a calculation code, this model is applied on the commercial software ANSYS FLUENT® 16. 2. The advection-diffusion equation is written in superficial form in order to keep velocity continuity at the interface between free-domain and porous medium. This method requires a volumetric force term source F for momentum conservation equation for modelling an equivalent hydraulic resistance. In the bundle, mass and momentum conservation equations are written: ∇ • (ρ𝐔 𝐬 ) = 0 (3) ∇ • (ρ𝐔 𝐬 ⨂𝐔 𝐬 ) = -∇ • (μ eff ∇𝐔 𝐬 ) -∇p + ρ𝐠 + 𝐅 (4) Hydraulic resistance is expressed in N/m 3 with K the pressure drop coefficients tensor.
data bank. If we only consider results for 0. 4mm baffle-to-tube clearances, it can be observed that prediction of ratio Q B /Q C with 1D method seem to be slightly superior than experience observations. Evolution of velocity field plotted on symmetry plane Figure  9  highlights a good distribution of flow : the fluid uses the full depth of the crosspass and the heat exchanger design does not create low-Reynolds recirculation zone. In order to examine the impact of porous media on flow structure, five velocity fields between second and third baffle have been exported from simulation. The positions of each plane are indicated on Figure  9. In plane 1, one portion of fluid crosses the baffle (Astream and E-stream). The other portion, is distinguished in the baffle window between tube bundle and annular space.
We introduce a new method to determine the anisotropy of reflectance of sea ice and snow at spatial scales from 1 m 2 to 80 m 2 using a multispectral circular fish-eye radiance camera (CE600). The CE600 allows measuring radiance simultaneously in all directions of a hemisphere at a 1 ∘ angular resolution. The spectral characteristics of the reflectance and its dependency on illumination conditions obtained from the camera are compared to those obtained with a hyperspectral field spectroradiometer manufactured by Analytical Spectral Device, Inc. (ASD). Results confirm the potential of the CE600, with the suggested measurement setup and data processing, to measure commensurable sea ice and snow hemispherical-directional reflectance factor, HDRF, values. Compared to the ASD, the reflectance anisotropy measured with the CE600 provides much higher resolution in terms of directional reflectance (N = 16, 020).
The hyperangular resolution allows detecting features that were overlooked using the ASD due to its limited number of measurement angles (N = 25). This data set of HDRF further documents variations in the anisotropy of the reflectance of snow and ice with the geometry of observation and illumination conditions and its spectral and spatial scale dependency. Finally, in order to reproduce the hyperangular CE600 reflectance measurements over the entire 400-900 nm spectral range, a regression-based method is proposed to combine the ASD and CE600 measurements. Results confirm that both instruments may be used in synergy to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set.
The first objective of the present study is to demonstrate the capabilities of the CE600 radiance camera to measure reflectance anisotropy, through a comparison with the ASD measurements. The second objective is to document the spectral characteristics of the reflectance anisotropy of snow and ice typically found on an Arctic landfast ice surface and its dependency on geometry of observation and illumination conditions. Finally, a method is proposed to use both instruments in synergy to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set.
Background There is a long history of reflectance anisotropy measurements, particularly over snow surfaces. Published measurements vary significantly with illumination and surface type but also in terms of angular, spectral, and spatial resolutions. Warren (1982)  gives a short overview of the snow reflectance anisotropy measurements made since the late 1960s. Taylor and Stowe (1984)  studied anisotropic reflectance over, among other things, snow surfaces based on satellite NIMBUS 7 Earth Radiation Budgets data with scanned surfaces ranging from 100 km 2 at nadir to 225 km 2 at horizon. Perovich (1994)  measured reflectance anisotropy in the field with a 1 ∘ field of view spectroradiometer over summer snow covered ice surfaces as well as bare and ponded Arctic sea ice. The instrument was placed on a goniometer near the ground to scan small enough surfaces.
(Nandy et al. , 2001)  further discussed the effect of calibration errors in the camera system. Based on several experiments, the authors computed the gain and offset parameters of each pixel in the 2-D imaging array, the point-spread function of the optics, the degree of polarization of the system and the lens transmission. The authors concluded that the bidirectional reflectance distribution function (BRDF) data measured with the camera were accurate to better than 1% at field angles of less than 20 ∘ and 3% for angles up to 70 ∘. In addition, comparison between data sets taken over several vicarious calibration sites and calibration tarpaulins with the camera and a goniometer-based system confirmed that the camera measurements were as accurate as the nonimaging radiometer measurements.
Radiance Sensors The CE600 and ASD instruments are complementary in terms of spectral, angular, and spatial resolution. The hyperspectral ASD measures the downward irradiance and upwelling surface radiance in a single direction between 320. 3 and 1,047. 865 nm with a spectral resolution of 1. 4238 nm. In the present study, ASD data were measured in an uncalibrated raw digital number mode and acquired with the RS 3 ASD spectral acquisition software (https://www. asdi. com/products-and-services/software/rs3) which outputs the data at 1 nm spectral resolution. Because of imperfections in the data at wavelengths below 390 and above 950 nm, we focused only on the 400-900 nm spectral range. Reflectance factors were obtained from the raw uncalibrated readings Earth and Space Science 10. 1002/2017EA000332 by taking the ratio with measurements made over a Spectralon panel (see section 3.
Spectralon radiance and downward irradiance data were collected with the COPS radiometer simultaneously for a large range of illumination conditions and geometries and different viewing angles. C spec () was then estimated for each COPS spectral band (i. e. , 19 bands in the 305-780 nm spectral range) as the linear regression coefficient between the irradiance data and the upwelling radiance data. Next, regression coefficients were interpolated for the entire ASD spectral range. For the Spectralon used in the present study, C spec () compares well with the typical reflectance values of a white Spectralon in the blue and green spectral range (0. 99 and 0. 98 at 400 and 500 nm, respectively), lesser in the red and NIR where our Spectralon appeared greyer than expected (0. 95 and 0. 93 at 650 and 780 nm, respectively).
This was done to avoid the introduction of noise within the ANIX(). The coefficient of variation, CV(), was also computed for each cycle. CV() is the ratio of the standard deviation to the median expressed in percentage. While the former reveals the absolute extent, the latter gives an indication of the variation in HDRF( v ,  s ,  s , Δ, ). Second, to evaluate the wavelength dependency of reflectance anisotropy, correlations were estimated between wavelength pairs on the directional reflectance data and on the standard normal variate, SNV( v ,  s ,  s , Δ, ). SNV( v ,  s ,  s , Δ, ) is often used to apply baseline and light scattering correction  (Barnes et al. , 1989). Here it allowed focusing Earth and Space Science 10. 1002/2017EA000332 on the shape of the spectrum rather than on its magnitude.
For the same reason, the sharp increases in HDRF(560) at Δ equals 0 ∘ and  s equals 60 ∘ in Figures  8c  and 8d , respectively, are more pronounced with the CE600 data. This is particularly true for the bare ice surfaces where the peak in reflectance anisotropy in the direction of the solar beam is often sharper. In addition, a darkening of HDRF() along the grazing angles is also observed with the CE600 and not with the ASD (Figure  8c ). Overall, for a same surface type, nadir HDRF() data measured with the ASD tend to be more variable than the nadir HDRF() measured with the CE600. In addition, according to Figures 8a, 8c and 8d, the CE600 directional reflectance data tend to be higher compared to the ASD measurements. These differences may be explained by several factors: (1) smaller footprints (i.
By combining the ASD and CE600 measurements, we are thus able to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set. To our knowledge, such a data set is missing in the literature and highly valuable for, among other purposes, improving radiative transfer simulations. In a future work, this data will be used to provide sea ice and snow directional reflectance data for the simulation of top-of-atmosphere reflectance data at the vicinity of the ice edge with a three-dimensional radiative transfer model  (Cornet et al. , 2010). The spectral, angular, and spatial resolutions of the field directional reflectance data are critical to achieve comparability with airborne and satellite measurements. Therefore, the hyperangular and hyperspectral property of the present data set will enable the simulation of any narrow and broadband sensor measured signal at any viewing angle in the visible spectral range.
The HG001 strain and ΔspdC mutant were grown in TSB until early exponential phase (OD 600nm = 1) and total RNA was extracted for RNA-Seq analysis (See Materials and Methods). We verified that spdC is well expressed under these conditions using a lacZ reporter fusion with the spdC promoter region (S2 Fig). Three biological replicates were analyzed by RNA-Seq for each strain and the data presented as the mean fold-change. Using a value cut-off greater than 2 with a P value less than 0. 05, we found that the expression of 42 genes was lowered in the ΔspdC mutant strain and that of 65 increased (Table  1 ). In order to perform a general analysis of the transcriptomic data we generated an ontological grouping of SpdC-regulated genes (Fig  2A ). Among the genes positively controlled by SpdC, 10 are known virulence factors, suggesting that SpdC may influence S.
Upon protein-protein interactions, the close proximity between the T18 and T25 subunits restores adenylate cyclase activity, leading to cAMP synthesis and activation of the lactose operon. Interactions were tested both by spotting the resulting strains on LB plates containing X-Gal and by measuring β-galactosidase activity. To determine pair-wise interactions, we chose a cut-off value of 100 Miller Units as indicating a positive interaction between the protein fusions. As shown in Fig  3A , strong β-galactosidase activity was only observed for the plasmid combination co-producing the membrane anchored proteins SpdC and WalK while no interactions between SpdC and the cytoplasmic regulator WalR could be detected. SpdC is annotated as an Abi domain protein (CAAX protease self-immunity) in genome databases.
cDNA synthesis and quantitative real time PCRs (qRT-PCRs) cDNA synthesis was carried out as previously described  [47]. Oligonucleotides were designed with the BEACON Designer 7. 91 software (Premier Biosoft International, Palo Alto, CA) in order to synthesize 100-200 bp amplicons (see Table  3 ). Quantitative real-time PCRs (qRT-PCRs), critical threshold cycles (CT) and n-fold changes in transcript levels were performed and determined as previously described using the SsoFast EvaGreen Supermix (Bio-Rad, Hercules, CA) and normalized with respect to 16S rRNA whose levels did not vary under our experimental conditions  [47]. All assays were performed using quadruplicate technical replicates, and repeated with three independent biological samples.
7) giving FASTQ formatted reads. Reads were cleaned by removing adapter and low quality sequences using an in-house program (https:// github. com/baj12/clean_ngs). Only sequences with a minimum length of 25 nucleotides were considered for further analysis. Bowtie (version 0. 12. 7, -m50-chunkmbs 400 -a-best -q -e50)  [67]  was used for alignment with the reference Staphylococcus aureus subsp. aureus genome (gi|88193823). Only uniquely aligning reads where considered for counting. HTseqcount (version 0. 5. 4p5, parameters: -m intersection-nonempty, -s yes, -t CDS -I locus_tag) was used for counting genes  [68]. Statistical analysis was performed with R version 3. 0. 2 [69]  and DESeq2 version 1. 2. 10  [70]. Data were first normalized with DESeq2 and the default parameters. Dispersion estimation and statistical testing were performed using the Generalized Linear Model with default parameters.
Cell suspensions were mixed with Vectashield mounting media (Vector Laboratories, Burlingame, CA) and used for microscopic observations with a Nikon Eclipse E600. Images were acquired with a Nikon DXM1200F Digital Camera. ImageJ software was used for quantifying fluorescence (http://imagej. nih. gov/ij/index. html; [73] ). Fluorescence ratios were calculated by measuring fluorescence at the division septa divided by the fluorescence at the lateral wall after subtracting background fluorescence. Quantification was performed for 33 cells and two independent biological replicates and plotted using GraphPad Prism (GraphPad Software, San Diego, CA; http://www. graphpad. com).
Acknowledgments We are grateful to  Jean-Yves Coppe  ´e and  Arnaud Firon  for helpful discussion. We thank  Dr. Gouzel Karimova  for the kind gift of E. coli strain DHT1 and plasmids pKT25 and pUT18c and  Dr. Magdalena M. van der Kooi-Pol  for the Staphylococcus aureus cell fractionation protocol.
Contacts were made with 25 µm Pt wires connected via silver paste with a contact resistance ranging from 1 to 10 Ω. The electric and heat currents were injected along the a-axis of the sample. By studying three different samples with different RRRs, we checked the reproducibility of our results (see the supplemental material). Supplementary information : Supplementary information accompanies the paper on the npj Quantum Materials website. carried out the DFT calculations. AJ, BF and KB analyzed the data with input from DM. All authors participated in the discussions leading to the paper, which was written by KB and AJ. T σ to Sommerfeld L0 = 2. 44 × 10 -8 W. Ω. K -2 , numbers as a function of temperature (red). The data reported for a micro-ribbon of WP2  [11]  are shown in green. d) L(T )/L0 as a function of temperature in CeRhIn5  [4].
FUNDING This project was funded by  Fonds-ESPCI  and supported by a grant from  Région Ile-de-France. K. B. acknowledges support by the  National Science Foundation  under Grant No. NSF   PHY17-48958. B. F acknowledges support from  Jeunes Equipes de l'Institut de Physique du Collège de France (JEIP). D. L. M. acknowledges support from  NSF   DMR-1720816.
Consequently, the public may underappreciate biodiversity or overlook non-charismatic species in need of conservation attention  [23]. As a word of ecclesiastic origin, charisma is more commonly used to describe people. According to the Oxford Dictionary, it describes "the powerful personal quality that some people have to attract and impress other people" without any references to other organisms such as plant and animal species, even though it is increasingly used to describe nonhuman species. According to the Web of Science database, it was first used in 1990 by Noss  [24]  who mentioned it as one of the required attributes of flagship species. Since then, studies using this term have increased exponentially, culminating in more than 300 publications to date (Web of Science; https://webofknowledge.
Therefore, we used a rigorous, open, and non-restrictive approach in order to ensure that the definition was as least oriented as possible. In this manner, we used data from four complementary sources to illustrate the charisma of species for the Western public, which enabled us to compile a list of 20 animals considered to be the most charismatic. These sources were the following: (i) a large-scale online survey, (ii) a questionnaire given to primary school children in Western Europe, (iii) the animals displayed on the websites of zoos situated in the 100 largest cities in the world, and (iv) the animals featured on the film posters of animated movies produced by Disney and Pixar. All were open (no pre-suggested species) and not conservation-oriented. Two sources involved direct questions to the public, while we worked under the assumption that the species displayed on the zoo websites and film posters would be selected by communication experts based on their general appeal to the public.
As there were very few responses in the Italian language, we removed them from the analyses. These data were collected anonymously. School surveys. The same survey was conducted with children aged around 10 years in three primary schools located in three different countries: England (London), Spain (Cordoba), and France (Limours, near Paris). The schoolteachers first explained the meaning of the term "charismatic" as attractive, appealing, and preferred, while taking care not to mention the six traits or their synonyms. The explanation was purposely kept concise, and pupils were given 10-15 minutes to complete a paper questionnaire with the same questions as found in the web survey. We collected 224 usable complete questionnaires. Zoo webpages. We collected the names of wild animal species displayed on the homepage of the official websites of major zoos from the 100 largest cities in the world (https://en.