dataesr/scientific-paragraphs-categorization huggingface dataset:
We compare v 3D (r) with v ad (r), the velocity profile associated with a radial adiabatic eigendisplacement, r. The eigen-displacements, r , were computed using the adiabatic pulsation code ADIPLS  [34]  and the global 1D "patched" models associated with the 3D models. Each patched model was computed in such a way that the outer layers are obtained from the 3D model  [19]  while the interior layers were computed using the CESAM2K code  [35]. We normalized r such that the mode kinetic energy equals that of the trapped mode. Finally, we get v ad ≡ 2 ν ad r , where ν ad is the adiabatic mode eigenfrequency. We choose the adiabatic mode that is both close in frequency and with a node close to that of the trapped mode.
At the frequency ν ad = 2. 495 mHz (i. e. the frequency of the adiabatic mode close in frequency with the dominant mode of the solar 3D model), the driving by the Reynold stress is increased by ∼15%. This increase remains smaller than the uncertainties associated with the current helioseismic data  [1, 37]. However, this amount is expected to be larger at higher frequency. Furthermore and more problematic, the entropy contribution is increased by a factor about 20. As for the red giant 3D model, this implies a severe overestimation of the solar mode amplitude (but see the discussion in Sect. 5).
RESULTS The diffusion absorption refrigerator cycle is modeled taking into account the assumptions and operating conditions given in Table  1. Water at 25°C is utilized for cooling the absorber and the condenser. The condensation temperature is assumed to be 13°C higher than the temperature of the cooling water and is thus equal to 38°C. This yields to a total pressure of about 13. 1 bar. Pressure drops and heat losses along and through the pipes are neglected. Numerical steady state simulations are conducted using the Aspen plus program in sequential modular mode. The thermodynamic properties of C 3 H 8 and C 9 H 20 pure substances and their binary solution properties are retrieved from the software databank using the Peng-Robinson equation of state. Simulations are performed with a molar flow of the rich solution equal to 0.
Model summary The model was implemented in Matlab (The Mathworks, Natick Massachusetts). The model equations can be summarized as follows:. So in tension: , (eq 1) and in compression: , (eq 2) with: , ∑ , , , 2 , √ 1 , ,. The expressions above are independent of the length of the muscle fibre modeled and depend only on the cross-sectional areas occupied by the connective tissue and by the muscle fibre. Therefore these formulations can be extended to a muscle sample of cross-sectional area by introducing the percentage of connective tissue in the cross-sectional area of a muscle sample ( ), so that becomes and becomes 100.
Model implementation The model was implemented using the software Matlab (The Mathworks, Natick Massachusetts). To account for uncertainty in the input parameters, a separate simulation was run with a maximum, minimum and average value of each parameter presented in Table  1 , leading to a total of 3 11 (=177147) simulations. A sensitivity analysis was performed to assess the influence of uncertainty in the collagen stiffness and the proportion of collagen in the connective tissue.
, 2010 , Morrow et al. , 2010 , Nie et al. , 2011 , Yamada, 1970 , Martins et al. , 1998 , Van Loocke et al. , 2006 , Grieve and Armstrong, 1988 , Vannah and Childress, 1993 , Zheng et al. , 1999). data is from  (Takaza et al. , 2013 , Calvo et al. , 2010 , Morrow et al. , 2010 , Nie et al. , 2011 , Yamada, 1970 , Martins et al. , 1998 , Van Loocke et al. , 2006 , Grieve and Armstrong, 1988 , Vannah and Childress, 1993 , Zheng et al. , 1999). Nie et al. , 2011 , Yamada, 1970 , Martins et al. , 1998 ) and compressive (Van Loocke et al. , 2006 , Grieve and Armstrong, 1988 , Vannah and Childress, 1993 , Zheng et al. , 1999 , Martins et al. , 1998)  bulk muscle experimental responses found in the literature and to assess the mechanisms of physical resistance to applied deformation. The literature shows that the stress induced through applied external tension is much greater than the stress induced through applied external compression in both the along-fibre and cross-fibre directions, as well as in tests at oblique angles to the muscle fibres  (Takaza et al.
Therefore, inventorying and evaluation processes need to be enhanced and speeded up by using other approaches. In this respect, inventories based on passive acoustic methods have demonstrated convincing advantages as they are non invasive, allow large automatic sampling, can be simultaneously used on several taxa, and provide very large temporal and spatial data sets  [13] [14]. Similar to classical inventory methods, passive acoustics can potentially be used to identify species directly by ear  [15] [16]  or by automatic identification methods  [17] [18] [19] [20]. However, identification of singing species by human observers is partly subjective depending on the experience and listening skills of the observer and to the difficulty of handling large samples. Automatic identification processes, which aim at finding species-specific songs, require an important sound reference database.
These sites were selected according to a census based on all published phylogenetic and inventory studies so far (see Table  S1 ), and on Global Biodiversity Inventory Facility (GBIF) records from collection databases. Automatic recorders collected acoustic data on these three sites. Distance based acoustic indices and statistical analyses assessed the acoustic dissimilarities among the three different sites. The study can be seen as a very stringent test of the capacity of the global acoustic method to detect dissimilarity of biodiversity, given that allopatric speciation with niche conservatism, which is important in New Caledonia, is expected to maximize ecological similarity between sites. According to this capacity to detect dissimilarity, the global acoustic method could be an effective and efficient new approach to contrast sites of high biodiversity value.
Study sites Mandjelia (20u24. 0989S, 164u31. 4589E), Aoupinie(21u10. 0349S, 165u19. 0179E) and Koghis (22u10. 8339S, 166u30. 6329E) mounts were chosen as reference sites for their distinct species occurrence and specific microendemism (Figure  1 ). This selection was made in accordance with the most accurate inventories performed so far in the framework of 18 phylogenetic and 7 inventory studies published on varied groups of organisms in New Caledonia (see Table  S1  in Supporting Information). These studies gathered 269 species and 33 genera including plant and animal species with only a few of them producing sound. The Global Biodiversity Information Facility (GBIF,  [25] ) provided a dataset of all specimens collected on a square of 80 km 2 around the three sites, belonging to both animal and vegetal taxa.
Passive acoustic recording The recordings were made from 10 April to 30 June 2010 with Song Meter SM2 digital audio field recorders  [26]. These offline and weatherproof recorders were equipped with a single omnidirectional microphone (frequency response: 23564 dB between 20 Hz and 20 kHz) oriented horizontally at a height of 1. 5 m. The signals were digitized at a sampling frequency of 44. 1 kHz and a depth of 16 bits quantization. The files were saved in the lossless compressed format. wac and then transformed into the format. wav with the software WAC to WAV Converter Utility version 1. 1  [26]. The first minute of every hour was recorded leading to a total of 13,602 sound files. All recordings were examined by A. G. to remove files where the occurrences of rain, wind or anthropogenic noise were detected and could bias the results.
Acoustic activity level A level of acoustic activity was defined as the number of song types and was assessed by ear by A. G. for each recording. A song type was identified as any unique acoustic sequence that can be differentiated by a human ear based on frequency and timeamplitude features. Three levels were used: (1) ''Moderate to high activity'' where more than two different song types were identified, (2) ''Low activity'' where one or two different song types occurred, and (3) ''Null activity'' where no animal songs could be detected (see Table  S3 ). This scale was designed to fulfil aural discrimination constraints on a very large data set (6,571 files). In particular, it was not possible to clearly distinguish more than two song types in complex recordings. This characterisation of the acoustic activity level was also built for an easy use by other potential observers.
Acoustic complexity index NP A new index was developed to assess acoustic complexity. This index, named NP for ''Number of Peaks'', counts the number of major frequency peaks obtained on a mean spectrum scaled between 0 and 1. A mean spectrum was obtained for each audio file by computing a short-time Fourier transform (STFT, non overlapping window size = 512 samples = 11 ms). A specific function was developed within the 'seewave' package  [27]  of the R environment  [28]  to process the automatic detection of frequency spectral peaks of each mean spectrum. All peaks of the spectrum were first detected and then selected using amplitude and frequency thresholds. The first selection factor was based on the amplitude slopes of each peak. Only peaks with slopes higher than 0. 01 were kept. The second selection factor was based on frequency.
Phylogenetic and GBIF data From the 18 phylogenetic and 7 inventory datasets analysed, the percentage of microendemics calculated was 12. 50% for Mandjelia, 15. 38% for Aoupinieand 23. 73% for Koghis. From the GBIF data , the ratio of endemic species to the number of collectors was 4. 89 for Mandjelia, 3. 76 for Aoupinieand 4. 71 for Koghis.
Recent ecological sensing methods should help in drawing such general diversity patterns by relaxing the constraint of taxonomic inventorying. In particular, non-invasive global acoustic approaches may be considered as an alternative or a complementary approach to classical biodiversity surveys  [21, 37]. Comparing the sound properties of animal assemblages through the computation of acoustic dissimilarities may help in pointing out differences between sites that have distinct species composition, here partly related to different evolutionary histories and microendemism. A preliminary test for the efficiency of such an approach was run here on three major diversity sites in New Caledonia. Global acoustic analysis discriminated sites that are known for their high and comparable level of species richness, according to records in biodiversity meta-databases GBIF  [25] , and for their high level of microendemism according to all reported phylogenetic studies.
Acknowledgments We would like to thank  Christian Mille  for elements of bibliography of New Caledonia. We would like to thank  HerveJourdan  and  Edouard Bourguet  for their help when collecting the acoustic data. We thank  Dr. James F. C. Windmill  ( University of Strathclyde, Glasgow ) and  Dr. Yoland Savriama  ( St. John's University, New York ) and  Theresa Murtagh  for improving the language of the manuscript. We would like to thank the two anonymous referees and  Alex Kirschel  for their helpful comments on the manuscript.
The secondary slits, after the monochromator, are set to a horizontal narrow gap (50 mm), and moved vertically to isolate rocking curve data to a specific striped area on the surface of the first crystal. The DCMs used for these tests allow the second crystal to be scanned while keeping the first one fixed. As the first crystal absorbs almost all of the incident power, the heat load on the second crystal is insignificant for the thermal deformation. Therefore the second crystal is supposed to be non-deformed with an ideal flat shape. The increase of the rocking curve width (measured after the secondary slits) for a distorted first crystal with respect to the undistorted flat crystal provides an estimate of the global slope error (peak-to-peak slope error). In order to measure the local slope error distribution on the first crystal surface, a series of rocking curves were measured at different vertical positions of the narrow-gap slit after the monochromator.
When is constant, this expression becomes " ¼ T À T ref ð Þ : ð4Þ For temperature-dependent , the strain can still be calculated using a formula similar to (4), but replacing with the secant coefficient of thermal expansion, se (see x2. 1. 3 of the ANSYS documentation Theory Reference), " ¼ se T À T ref ð Þ ; ð5Þ where se ¼ h R T T ref ðTÞ dT i T À T ref ð Þ : ð6Þ Note that se depends on both the reference temperature T ref and the temperature T. The data for the thermal expansion coefficient given in the literature are usually the values of as a function of temperature, as in  Touloukian et al. (1970b). This is the so-called 'instantaneous' in the ANSYS documentation. The secant coefficient of the thermal expansion se calculated by (  6   then goes back to its initial size (no deformation) at 165 K.
e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome. Results: Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.
Marker selection and genotyping The five F 1 sires were genotyped for a set of 9216 SNPs covering the 28 first autosomes and the GGAZ (Gallus gallus chromosome Z). A subset of 1536 SNPs was selected using MarkerSet software  [15]  based on SNP location and heterozygozity in the F 1 population to maximize both genome coverage and marker informativity. All F 2 animals were genotyped for these 1536 SNPs and for 120 microsatellites that were used in a previous analysis  [11]. SNP genotyping was performed at the National Genotyping Center (CNG, Evry, France) using Illumina GoldenGate technology (Illumina, San Diego, CA, USA). For microsatellite genotyping, two to 10 markers were combined for multiplex PCR amplification based on size and amplification conditions and analyzed on an automated sequencer (ABI 3700, PE Applied Biosystems, Foster City, CA).
QTL mapping When needed, the GLM procedure of SAS was used to adjust traits for sex and hatch groups (fixed effects) and BW9 (covariate). BW9 was not used as covariate for BW1, BW3, BW5, BW7, ThP and IGF-I. Correlations between adjusted traits were then calculated using the "cov2cor" function in R  [17]. The significance level for the bilateral correlation test for more than 500 values and P < 0. 01 was 0. 115, using the Bravais-Pearson r table. Heritabilities and genetic correlations of the measured traits were estimated by the REML method with the VCE6 software  [18]. The model included the fixed effects of hatch (N = 5) and sex (N = 2), the animal genetic effect (N = 623), as well as BW9 as a covariate (except for BW1, BW3, BW5, BW7, ThP and IGF-I, as previously mentioned). For body weight traits, a maternal random effect (N = 47) was added.
A fast algorithm was used to estimate transmission probabilities at each location of a chromosome based on the SNP genotypes  [20] , which made it possible to use a large set of markers. A specific GPU accelerated version of QTLMap was used to reduce computation time  [21]. The presence of QTL was assessed using a likelihood ratio test (LRT) under the hypothesis of one versus no QTL linked to a given set of markers  [12]. The QTLMap software was also used to test more complex hypotheses, such as whether two linked QTL influence the same trait  [22]. Two approaches were used for multiple-QTL analysis. When one QTL was identified in a chromosome, the hypothesis of one QTL in the chromosome (H1) was compared to the hypothesis of two QTL in the chromosome (H2). This is of particular interest to test whether a QTL detected in a single-QTL linkage analysis was a ghost, or whether another QTL might be segregating elsewhere on the chromosome.
Acknowledgements Experimental design and genotyping of microsatellite markers were funded by grants from the  USDA-IFAFS Animal Genome Program  (Grant  00-52100-9614  to  LA Cogburn , project director) and by  Analyse du Génome des Animaux d'Elevage (AGENAE) program  and  INRA (France). Genotyping of SNP markers was funded by the  European Animal Disease Genomics Network of Excellence for Animal Health and Food Safety (EADGENE) program. The authors thank the staff of the breeding facilities ( INRA, Pôle d'Expérimentation Avicole de Tours, F-37380 Nouzilly, France ) and of the research unit ( INRA, UR83 Recherches Avicoles, F-37380 Nouzilly, France ) for technical participation. Special acknowledgments go to  Nicole Millet  ( URA-INRA, Nouzilly, France ) who supervised the maintenance of the FL and LL broiler lines, to  Katia Feve  and  Florence Vignoles  ( INRA, Toulouse, France ) who validated the genetic markers at the  Centre de Resources, Génotypage, Séquençage platform of the Génopole Toulouse Midi-Pyr énées , to  Frédéric Hérault ,  Cécile Duby  and  Colette Désert  who extracted the  DNA (INRA ,  UMR598   Génétique Animale , 35042  Rennes, France) , to  Yves Amigues  and  Sabine Janin  ( Labogena, INRA Jouy-en-Josas, France ),  Diana Zelenika  ( CNG, Evry, France ) who genotyped the samples and to  André Neau  ( INRA, Jouy-en-Josas ) who managed the archiving of genotyping data in the INRA database.
Sections were washed between each subsequent step with 0. 1% Tween 20 in TBS. Sections were subsequently incubated with polyclonal Cy3-conjugated donkey anti-goat antibodies (1:400; Jackson Immu-noResearch) and polyclonal Cy2-conjugated donkey anti-mouse antibodies (1:400; Jackson ImmunoResearch) for 1 h at room temperature in 3. 5% donkey serum with 0. 1% Tween 20 in TBS. The sections were washed three times for 10 min in 0. 1% Tween 20 in TBS and mounted in Fluoromount G (Southern Biotechnology) mounting medium. The staining specificity was checked in control incubations performed in the absence of the primary antibody. All counts were performed using NIH ImageJ software version 1. 37. Color images were tinted using Image Pro-Plus software, in which identical brightness, contrast, and color balance adjustments were applied to all groups.
Microscopy. All immunofluorescence images were collected with a CCD camera (QImaging Retiga 2000R Fast, Cooled Mono 12 bit) mounted on Olympus microscope (BX51) using the Image Pro-Plus version 6. 0 software (MediaCybernetics) with 40ϫ (4ϫ Olympus objective UPlan FL N 0. 13), 100ϫ (10ϫ Olympus objective UPlan FL N 0. 3), 200ϫ (20ϫ Olympus objective FL N 0. 5), 400ϫ (40ϫ Olympus objective UPlan FL N 0. 75), 600ϫ (60ϫ Olympus objective UPlanS Apo 1. 35 oil), and 1000ϫ (100ϫ Olympus objective UPlanS Apo 1. 4 oil) magnifications. Protein and Western blot analyses. The ventral part of frozen spinal cord was separated from the dorsal part by razor blade at Ϫ20°C. The dissection is performed at the level of the depression that separates the ventral from the dorsal part of the spinal cord. Brain, heart, kidneys, lungs, liver, diaphragm, tibialis muscle, and ventral lumbar spinal cord samples (2-5 mg) were homogenized in 100 l/5 mg tissues in the presence of ice-cold RIPA buffer [50 mM Tris HCl, pH 8.
This global activation of SMN2 gene transcription led to an increase from 26 to 65% of exon 7-containing SMN transcripts in U0126-treated SMA spinal cord. In addition, the 2 h delay between the U0126 treatment and the SMN2 gene transcriptional activation suggested that the ERK inhibition effects occurred directly, without any additional transcription event. The MEK/ERK/Elk-1 and the PI3K/AKT/CREB signaling pathways are in competition for SMN2 gene regulation in the spinal cord of type 1 SMA-like mice Because these data suggested for the first time that the ERK pathway might have a crucial role in the regulation of SMN expression, we analyzed the effects of ERK inhibition at the level of SMN gene promoter. Interestingly, when we analyzed the sequence of the human SMN promoter (GenBank accession number AF187725), we found that several CREB binding sites were flanked by putative response elements for Elk-1, a transcription factor of the ETS family, known to be a direct target of ERK  (Whitmarsh et al.
Based on an extensive dataset of networks and neuronal simulations we assess statistical relations between features of the network structure and the spiking activity. Our results highlight the strong influence that some details of the network structure have on the activity dynamics of both single neurons and populations, even if some global network parameters are kept fixed. We observe specific and consistent relations between activity characteristics like spike-train irregularity or correlations and network properties, for example the distributions of the numbers of in-and outgoing connections or clustering. Exploiting these relations, we demonstrate that it is possible to estimate structural characteristics of the network from activity data. We also assess higher order correlations of spiking activity in the various networks considered here, and find that their occurrence strongly depends on the network structure.
Finally, we measure the maximum degree of higher-order correlations that can be detected in the observed activity using an algorithm proposed in  Staude et al. (2010b) , with parameters α = 5% (significance level) and m max = 4 (cumulants of the population activity up to order 3 are used). In short, it is tested whether groups of neurons have a tendency to spike together beyond what can be expected from the correlations among smaller sub-groups. The largest group size that can significantly be inferred in the given dataset is returned. In Figure  1C  the variability of the network features in the chosen network ensemble is demonstrated by comparison of the resulting feature distributions with the ones from alternative network models. The feature distributions of both random and small world networks are generally much narrower, indicating that different network realizations within these ensembles are much more alike in their statistical properties.
ACKNOWLEDGMENTS The article processing charge was funded by the  German Research Foundation (DFG)  and the  Albert Ludwigs University Freiburg  in the funding  programme Open Access Publishing. Supported by the  German Federal Ministry of Education and Research (BMBF ; grant  01GQ0420  " BCCN Freiburg ," grant  01GQ0830  " BFNT Freiburg * Tübingen "), and the  German Research Foundation  (DFG;  CRC 780 , subproject  C4 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Virus isolates sampling and aphid surveys All vegetation sampling in the Kerguelen Islands was performed under permits 2008-97, 2009-51, and 2010-76 issued by the relevant TAAF (Terres Australes et Antarctiques Francaises) Authorities. BYDV isolates were collected during the summer campaigns 2008-2009, 2009-2010, and 2010-2011 from P. cookii (Table  1 ) and from other native or introduced grasses listed in Table  2. Generally, random sampling was performed but grasses species showing yellowing or reddening symptoms reminiscent of BYDV infection were systematically collected in sites rich in P. cookii. All collection points were identified by GPS (listed on Table  S1 ). For data analysis, collection sites within a two kilometer radius were considered as representing a single sampling point.