dataesr/scientific-paragraphs-categorization huggingface dataset:
SEQUENCE ANALYSES OF SmFz1, SmFGFR-A AND SmFGFR-B Searching the genome of S. mansoni for frizzled genes using the database GeneDB  (Protasio et al. , 2012)  an annotated entry (Smp_118970) was found coding for the C-terminal fragment of a frizzled homolog named SmFz1. Full-length cloning of SmFz1 revealed that the missing N-terminal part was coded by another sequence annotated as Smp_173940. The whole open reading frame (ORF) of the frizzled gene consists of 2091 bp and an alignment with the GeneDB entries Smp_119870/Smp_173940 revealed a sequence identity of 99% (accession number: KJ820759). Sequence analyses showed that the predicted protein sequence of SmFz1 contained typical features of frizzled receptors, which belong to the superfamily of seven transmembrane receptors  (Schiöth and Fredriksson, 2005)  (Figure  2 ).
BLOCKING OF FRIZZLED-DVL SIGNALING LED TO DRAMATIC PHENOTYPES IN THE GONADS AND INHIBITED EGG EMBRYOGENESIS To investigate the role of Frizzled-signaling in reproduction and developmental processes of schistosomes, S. mansoni couples were treated in vitro with different concentrations of the commercially available compound 3289-8625 (also Dvl-PDZ domain inhibitor II, Merck Millipore). This inhibitor blocks canonical Frizzled-signaling by binding to the PDZ (post-synaptic density-95/discs large/zonula occludens-1) domain of the Frizzled downstream interaction partner Disheveled (Dvl) with an IC 50 of 12. 5 μM in cell culture experiments  (Grandy et al. , 2009; Voronkov and Krauss, 2013). Because of the drug's specificity targeting the Frizzled-Dvl interaction directly we performed database analyzes to identify Dvl homologs in the genome of mansoni couples.
Transcripts of all genes were detected in the testes of the male and the ovary of the female. SmFGFR-B transcripts were also observed in the vitellarium of the female and the parenchyma as well as the gastrodermis of both genders. Negative controls using sense-RNA probes showed no color reaction (J,K). [te, testes; ov, ovary; v, vitellarium; p, parenchyma, g, gastrodermis; ♂, male; ♀, female]. S. mansoni. As results two Dvl genes SmDvl1 (Smp_162410) and SmDvl2 (Smp_020300) were found and their transcription in testes and ovaries was confirmed by gonad-specific RT-PCRs (data not shown). In vitro-culture experiments with inhibitor concentrations up to 400 μM for at least 96 h had no significant effect on the vitality, morphology, pairing stability or egg production of treated worms (data not shown).
ACKNOWLEDGMENTS The authors thank  Christina Scheld ,  Bianca Kulik , and  Mathias Riedl  for their excellent technical assistance. This work was financially supported by a grant of the  Deutsche Forschungsgemeinschaft  ( GR-1549/7-2 ). Sophia Parker-Manuel receives a fellowship from the  Alexander-von-Humboldt (AvH) foundation. Zhigang Lu  is a member of the  International Giessen Graduate Centre  for The Life Sciences (GGL) and receives a fellowship from the  China Scholarship Council (CSC).
Identification of TE insertions In order to determine orthology relationships between L. menadoensis BAC clones and the L. chalumnae genome, sequence comparison was performed using MegaBlast  [30]. Best hits were selected and the main alignment diagonals were used to define the maximum match coordinates along with their orientation. Orthologous fragments are listed in Table  S1. L. chalumnae and L. menadoensis TEs were localized using the RepeatMasker software  [31]  with a TE library specifically built for the L. chalumnae genome  [6, 26]. TEs were selected according to the following criteria: length >100 nucleotides (nt) and divergence to the consensus sequence from the library #20%. Low complexity sequences, simple repeats as well as tRNA and rRNA (pseudo)genes were discarded. Remaining elements located in corresponding L.
Counting of shared TE insertions Using RepeatMasker, masking of L. menadoensis with the L. chalumnae TE library might lead to artifactual split insertions in L. menadoensis due to discrete interspecific sequence differences with L. chalumnae TEs. This would lead to an overestimation of the number of common insertions. To avoid this problem, the number of common insertions between both Latimeria species was estimated on L. chalumnae data. Close hits matching contiguous parts of the same TE sequence from the database and indexed by a common element number in RepeatMasker outputs were counted as a unique insertion. The same procedure was applied on the whole genome of L. chalumnae to estimate its global TE content. Annotation of species-specific TE insertions TE insertions were assigned to known TE superfamilies based on Wicker's classification by combining comparative and predictive approaches  [16].
In order to look for putative coding regions, TE sequences were submitted to the de novo gene prediction program Genscan  [33]  and to a BlastX search  [34]  on the NCBI website with default parameters against the Genbank non-redundant protein sequence database. Insertions were also analyzed with the Censor software  [35]  that compares sequences with the Repbase repeat database  [36]. Structural features such as Long Terminal Repeats (LTRs) and Terminal Inverted Repeats (TIRs) were identified with the Blast bl2seq utility  [34]. Target Site Duplications (TSDs), which correspond to the duplication of few nucleotides from the insertion site, were searched at the extremities of insertions. TE expression was analyzed by sequence similarity analysis of a transcriptome of L. menadoensis testis  [6]  using the Blast algorithm with default parameters.
PDBbind v2013 round-robin benchmark We propose a new benchmark to investigate how prediction performance of the four models changes in cross validation and with varying numbers of training samples. We used PDBbind v2013 refined set (N = 2959), which is the latest version and constitutes the most comprehensive and publicly available structural dataset suitable for training scoring functions. We used 5-fold cross validation, as was used by the recently published empirical scoring function ID-Score  [23] , to reduce overfitting and thus generalization errors. The entire PDBbind v2013 refined set (N = 2959) was divided into five equal partitions using uniform sampling on a round-robin basis: the entire 2959 complexes were first sorted in the ascending order of their measured binding affinity, and the complexes with the 1st, 6th, 11th, etc.
lowest binding affinity belonged to the first partition, the complexes with the 2nd, 7th, 12th, etc. lowest binding affinity belonged to the second partition, and so on. This partitioning method, though not completely random, has two advantages: on one hand, each partition is guaranteed to span the largest range of binding affinities and incorporates the largest structural diversity of different protein families; on the other hand, each partition is composed of a deterministic list of complexes, permitting reproducibility and comparisons in future studies. Table  2  summarizes the statistics of the five partitions. The PDB IDs and measured binding affinities of the complexes in the five partitions are available in the Additional file 1. We then used the partition on which the best performance was obtained (It turned out to be partition 2 (N = 592).
So far LCOCV has been applied to the assessment of six scoring functions, which are RF-Score  [20, 21, 27] , ddPLAT+MOE  [28] , CScore  [20] , B2Bscore  [21] , SFCscor-eRF  [22]  and the work of Ross et al. [29]. For the purpose of comparison to other scoring functions, PDBbind v2009 refined set (N = 1741) was used in this study to perform LCOCV. The 1xr8 entry in cluster X was discarded because its ligand is far away from its protein, thereby leaving 1740 complexes. The PDB IDs and measured binding affinities of the complexes in the 23 protein families (A to W) and the 3 multi-family clusters (X to Z) are available in the Additional file 2.
MLR::Cyscore performance does not increase with more training samples On both PDBbind v2007 and v2012 benchmarks, MLR::Cyscore performed best when it was trained on the 247 carefully selected complexes used by Cyscore. Its performance dropped when more complexes were used for training. On PDBbind v2013 round-robin benchmark, MLR::Cyscore performance stayed flat regardless of training set sizes. These results show that MLR::Cyscore is unable to exploit large sizes of structural data given only a small set of sophisticated features. Feeding more training samples to MLR::Cyscore actually increases the difficulty in regressing the coefficients well. Generally it would be a good idea to select the training complexes that provide the best performance on a test set, as was the case of Cyscore. However, in real applications the binding affinities of the test set are not known and unfortunately selection of training complexes is not performed blindly (i.
Acknowledgements We gratefully acknowledge the Direct Grant from the  Chinese University of Hong Kong , the  GRF  Grant (Project Reference 414413) from the  Research Grants Council of Hong Kong SAR , the  Inserm  funding (P. J. B. ), and the  Medical Research Council  for a  Methodology Research Fellowship  (Grant No. G0902106 , awarded to P. J. B. ). We thank  Yang Cao  for helping us reproduce the Cyscore results.
Also we would like to thank S. Hook, P. Rice, N. Rodrigues and S. Thornton for technical support during the experiment as well as J. Underwood and M. Siano for their contributions to the design of the VMI spectrometer. KvH kindly acknowledges funding by STFC (seed corn fund for experiments using 4th generation light sources) and the Leverhulme Trust (F/00212/AH). RSM would like to thank the Royal Society for a University Research Fellowship (UF100047), ML and MM acknowledge computational resources funded through ANR grant ANR-08-BLAN-0146-01. Author contributions. G. Galinis: prepared, set up and performed experiment, analysed and interpreted data and wrote the manuscript, C. Cacho: supported experiment, R. Chapman: prepared, set up and supported experiment, A. Ellis: set up and performed experiment, interpreted data and wrote manuscript, M.
Herman, M. , Campargue, A. , Idrissi, M. I. E. & Van der Auwera, J. Vibrational Spectroscopic Database on Acetylene, X 1 Σ + g ( 12 C2H2, 12 C2D2 and 13 C2H2) J. Phys. Chem. Ref. Data, 32, 922 (2003).
The anticipated discovery of a pulsar in orbit with a black hole is expected to provide a unique laboratory for black hole physics and gravity. In this context, the next generation of radio telescopes, like the Five-hundred-metre Aperture Spherical radio Telescope (FAST) and the Square Kilometre Array (SKA), with their unprecedented sensitivity, will play a key role. In this paper, we investigate the capability of future radio telescopes to probe the spacetime of a black hole and test gravity theories, by timing a pulsar orbiting a stellar-mass-black-hole (SBH). Based on mock data simulations, we show that a few years of timing observations of a sufficiently compact pulsar-SBH (PSR-SBH) system with future radio telescopes would allow precise measurements of the black hole mass and spin. A measurement precision of one per cent can be expected for the spin.
Mock data analysis Based on the simulation scheme described in Section 3. 1. 2, we have estimated the measurability of the black hole spin by timing a PSR-SBH system. Here when calculating the time delays we also include the orbital precession due to the black hole spin, by inputting the secular changes of Φ and Ψ described in Eq. (  15 )-(  16 ). Then we fit the calculated TOAs with the MSS timing model of TEMPO  (Wex 1998 ) to determine the black hole spin and its orientation, as described in  Liu et al. (2012). The expected black hole spin measurement precision in PSR-SBH systems of a slow pulsar is investigated in Fig. 4. Here we also show the measurability of the secular change in orbital projected semi-major axis (top), which usually provides the first sign of the black hole spin. We applied the same weekly observing scheme as described in Fig.
Mock data analysis As first suggested in  Wex & Kopeikin (1999) , in a PSR-SBH system measurement of the black hole quadrupole moment may not be possible since the amplitude of the quadrupolar signal in one orbital period is only of order 1 ∼ 10 ns even for a highly relativistic system (e. g. , P b ∼ 0. 1 day, e = 0. 9). Nevertheless, due to the precession of the orbit the quadrupolar feature will evolve on timescales of years, which can increase the chance to detect the signal. To investigate the circumstances where measurement of the black hole quadrupole moment may become possible, we have performed extensive mock data simulations. We assume weekly, four hour timing observations of a MSP, for a period of 20 yr with the sensitivity of the SKA. We extend our TOA calculation and use the timing model as described in in Section 3.
Mock data analysis The potential of a PSR-SBH system in constraining scalartensor theories of gravity can be demonstrated by mockdata simulations. Here we assume a PSR-SBH system with P b = 5 day, e = 0. 8, and mp = 1. 4. A stiff EoS allowing a maximum neutron star mass of ∼ 2. 5 M⊙  (Müther et al. 1987) , is used to calculate αp for any given theory T1(α0, β0). Note that this choice of EoS leads to conservative constrains, as the application of a softer EoS would generally lead to larger scalar charges for the neutron star and therefore more limits. For the black hole, we have assumed a nonrotating (χ = 0) 10 M⊙ black hole, because a significant spin would only complicate the timing analysis (see Section 3) but should not greatly influence the constraints on scalartensor theories. The applied observational scheme is retained as in Section 3.
SEARCHES FOR PULSAR-BLACK HOLE BINARIES Searches for undiscovered pulsars have been extensively performed ever since the first discovery in 1967  (Hewish et al. 1968 ). Despite improvements in both observational hardware and data processing techniques, the discovery of a PSR-SBH system has so far eluded pulsar astronomers. Although it is expected that PSR-SBH systems are rare, it can be shown that observational selection effects could have played an important role in the non-detection. Pulsars in binary systems show periodic changes in their spin frequency because of Doppler effects induced by orbital motion. In compact, high-mass, or eccentric systems these effects can manifest themselves within the timescale of individual pulsar survey observations i. e. typically of the order of minutes.
1. 1), we find that a pseudo real time acceleration and jerk search would require over an Exa Flop per second of computation. By covering the increased acceleration and jerk parameter ranges expected to be observed in PSR-SBH (Section 6. 1. 1), the computational cost could be higher. 11 https://github. com/jintaoluo/presto on gpu 12 https://github. com/ewanbarr/peasoup c 0000 RAS, MNRAS 000, 000-000 Pulsar-black hole gravity tests 15 we find |j| ∼ 0. 2, 0. 6, and 0. 9 m s -3 for companion masses of 1. 3, 10, and 30 M⊙ respectively. As we will show in Section 5. 3. despite acceleration searches performed on time series that have a length where T obs P b /10, these higher order effects can still degrade the effectiveness of the acceleration search method. It is also worth noting that pulsars in eccentric systems, like those displayed in panel (b) and (c), spend the majority of the time in a state of low and constant orbital acceleration.
Computational scaling The dominant fraction of computing time in pulsar search processing is typically spent at the acceleration search stage, where the entire search process is essentially repeated a large number of times for a number of trial accelerations. As such, consideration of the level of computation required to find PSR-SBH with next generation telescopes is needed to test the feasibility. Here we limit our discussion to time-domain acceleration searches where the approximate number of computational operations for acceleration searches, Ca, is proportional to the product of number of trial accelerations na and the standard Fast Fourier Transformation (FFT) operation count for one-dimensional real valued data, Ca ∝ na 2. 5 nsamp log 2 (nsamp) (56) where na = ∆a/δa and nsamp = T obs /τsamp; here ∆a is the total range of trial accelerations searched, δa is the step size in acceleration over this range and τsamp is data sampling interval.
On the right-hand y-axis we give the number of spectral bins drifted (n drift ) by this eighth harmonic of the spin frequency; a number relevant to acceleration searches performed in the frequency domain  (Ransom et al. 2002). Both the simulation of data and the search are conducted with an updated version of the sigproc software package 14. Panel (a) shows that for an observing time of 6. 2% of the orbital period (≈ 537 s) the search succeeds in recovering over 90% of the power at most orbital phases when the companion is of solar-mass. However, for PSR-SBH systems observed with this integration time (panels c and e) the same level of recovery can only be achieved at orbital phases where the variation of acceleration is minimised i. e. at the peaks and troughs. When the observing time is halved to ≈ 268 s, 90% signal recovery is achievable for observations starting at most orbital phases and for companion masses up to 30 M⊙.
CONCLUSIONS In this paper, we investigate the achievable gravity tests by observing a PSR-SBH binary system, in particular with the next generation of radio telescopes. For our studies, we have used the sensitivity of the FAST and SKA as representatives for the future telescopes. The investigations are based on simulated pulsar timing data with consistent timing models. It has been shown that with three to five years pulsar timing observations we can expect to measure the masses of the pulsar and the black hole with a high precision (e. g. , 0. 001 % -1%), especially when the pulsar is a MSP and the observations are conducted with the next generation of radio telescopes. The black hole spin can be measurable on timescales of five to ten years, with high precision (∼ 1%) on the same optimal scenario.
ACKNOWLEDGEMENTS We thank  P. C. C. Freire  and  S. M. Ransom  for useful discussions and reading the manuscript. We are grateful to  J. Lattimer  for providing the tables for equations-of-state MPA1. The authors also wish to thank the anonymous referee for valuable comments. K. Liu is supported by the  ERC Advanced Grant "LEAP" , Grant Agreement Number  227947  ( PI M. Kramer ).
, 2003). One way to either confirm or to refute direct solar forcing on LOD would be to identify its underlying, albeit hypothetical, mechanism and then to simulate it with numerical models. However, the difficulty lies in the fact that the 11-year solar forcing on climate is rather small, whatever the considered mechanism (changes of total solar irradiance, of UV irradiance, or cosmic ray (CR) modulation (see  Gray et al. , 2010 , for a review)). Another way to study the possible solar influence on LOD is to perform statistical studies of time series. Chapanov and Gambis (2008, 2009a, b)  decomposed the LOD data set empirically into a set of mathematical components. Using fast Fourier transform (FFT) these authors succeeded in finding a set of components corresponding to processes such as zonal tides (5.
Rotation of the Earth -length of day (LOD) We are mainly interested in 11-year variations of semiannual oscillation of LOD because of a sharp spectral peak which is evidenced in LOD oscillations  (Bourget et al. , 1992; Le  Mouël et al. , 2010). Original data are taken from the database of the International Earth Rotation and Reference System Service (IERS), of the Earth Rotation Center at Paris Observatory (http://hpiers. obspm. fr/eoppc/eop/ eopc04/eopc04_IAU2000. 62-now). The analysed data set was obtained using calculations described by Le  Mouël et al. (2010). After preprocessing, the resulting data set covers the time interval from January 1964 to March 2012. The main goal of preprocessing was to extract from the original data set, containing oscillations at various frequencies, the semi-annual LOD variation.
A derivative of the original data set of the daily values of LOD was calculated for each day k. As a result we obtained the data set lod (k). Next, for each day k we calculated Fourier coefficients C(k) corresponding to the 0. 5-year (T ) spectral line. For this calculation we used a 4-year (2τ ) sliding window width which was centred on each day k. C(k) = A(k) + iB(k) = t/(2τ + 1) ρ=k+τ ρ=k-τ lod (k)(cos(ωρ) + i sin(ωρ)), where ω = 360 • /T (in degrees per day), T = 0. 5 year (182. 62 days), τ = 2 years (730 days), and t = 1 day is the sampling interval. An amplitude α(k) of the 0. 5-year variation of the lod can be estimated as a module of the FFT amplitude multiplied by the factor of T /2π: α(k) = (182. 62/2π ) • A(k), where A(k) = (A 2 (k) + B 2 (k)) 1/2. Two questions can be raised at this point: one technical, the other physical.
Solar activity -sunspot number (SSN) As a simple and robust parameter characterizing SA variations, we used the monthly index of sunspot numbers (SSNs, from the Solar Influence Data Center (SIDC) database). The data set is extensive, starting in 1749 and continuing until the present. This data set may be too rough as a proxy of SA. Another index such as the total solar irradiance (TSI, in W m -2 ) is certainly preferable, but it covers a shorter time interval from 1975 to 2003 (Composite Total Solar Irradiance database 1978-present, compiled by C. Fröhlich and J. Lean; Fröhlich, 2003). The 1978 to 2003 portion of the data set is based on observed data, and the 1975 to 1978 portion is based on modelled data. Both (SSN and TSI) extended data sets can be found in the NGDC-NOAA database (SSN -http://www.
The choice of parameters used for the construction of a cross-recurrence matrix is important. In this paper we present results obtained using the "fixed distance maximal norm" (L ∞ ), embedding dimension m = 1, time delay τ = 1 and ε = 0. 1σ , where σ is the standard deviation. A detailed description of cross-recurrence-plot analysis can be found in  Marwan et al. (2007). In this study we used the package for MAT-LAB that can be found at http://www. agnld. uni-potsdam. de/ ~marwan/toolbox/.
However, the same authors mention that the global AAM data set at this 11-year timescale shows a significant phase lag with solar activityabout 2 months on average -over the last 50 years. Moreover, some studies (see  Abarca del Rio et al. , 2003, and references therein)  show at least a partial agreement between solar activity and independent measurements (sea surface temperature, global temperature (GT), AAM, LOD) over the last 50 years while being out of phase at the beginning of the 20th century. Moreover, multiple signals having distinct origins within the atmosphere with about the same frequency band as the 11year solar cycle can impact global AAM and interfere with the solar signal (Abarca del  Rio et al. , 2003) , complicating a precise detection of solar forcing. For this reason, the role of the solar forcing in zonal wind redistribution cannot be ruled out.
Population diversity by deep sequencing To estimate the population diversity of variants by deep sequencing, cDNA libraries were prepared by Superscript III from RNA extracted from virus generated in BHK-21 or C6/36 cells, and the viral genome was amplified using a high fidelity polymerase (Phusion) to generate 5 overlapping amplicons 2-3 kb in length. PCRs were fragmented (Fragmentase), multiplexed, clustered, sequenced in the same lane with Illumina cBot and GAIIX technology and analyzed with established deep sequencing data analysis tools and in house scripts. Briefly, per-base Phred quality scores were utilized to trim bases with error probabilities higher than 0. 001, and sequences with less than 16 bases after trimming were discarded. For this purpose we used the fastq-mcf tool from the ea-utils toolkit at http://code.