dataesr/scientific-paragraphs-categorization huggingface dataset:
Populations above or to the left of this line are classified into the interference selection regime, and the silent site variability in these populations can be predicted from the coarsegraining algorithm above. The remaining populations belong to the background selection regime, where the structured coalescent is already valid. We have implemented this coarse-graining procedure in a freely available Python library (see Methods), which rapidly generates predictions for the site frequency spectrum for arbitrary combinations of Ns and NU, and implements the linkage block approximation for recombining genomes described below. Other common diversity statistics (e. g. , MAF or Tajima's D) can be computed from this site frequency spectrum as desired. Concrete examples of these predictions for the reduction in pairwise diversity are shown in Figure  5.
We see that even with highly resolved frequency spectra (unavailable in the original dataset), there is little power to distinguish between these predicted alternatives despite rather large differences in the underlying parameters. However, this ''resolution limit'' suggests that individual fitness effects are not the most interesting quantity to measure when interference is common. Individual fitness effects may play a central role in single-site models, but we have shown that global properties like the variance in fitness and the corresponding linkage scale are more relevant for predicting evolution in interfering populations. Estimating these quantities directly may therefore be preferable in practice. Our coarse-grained predictions provide a promising new framework for inferring these quantities based on allele frequency data or genealogical reconstruction.
Forward-time simulations Forward-time simulations were implemented in a custom C++ program using a discrete-generation Wright-Fisher algorithm. Each simulation started with a clonal population of N = 10 4 individuals with initial fitness W = 1, and subsequent generations were obtained by performing a reproduction step, a recombination step, and a mutation step. In the reproduction step, the new generation was formed by sampling individuals with replacement from the previous generation, weighted by the relative fitnesses W i = P i W i. In the recombination step, we drew Poisson(NR) recombination events, and for each of these, we drew two individuals from the population and replaced the first individual with the recombinant offspring formed from a single randomly chosen crossover of the two chromosomes.
Determination of the effective linkage scale The effective linkage scale, L b =L, was obtained by inverting the condition L b =L~1zNR : f Ns,NU : L b =L ð Þ =4 ½ {1 , ð9Þ where f (Ns,NU) denotes the coarse-grained prediction for p=p 0 in Eq. (  3 ). Numerical solutions were obtained using the Brent algorithm in the SciPy library. See Text S4 for additional discussion. coarse-grained parameters and frequency spectrum predictions for arbitrary combinations of Ns, NU, and NR in the interference selection regime. Our source code is available for download at https://github. com/benjaminhgood/coarse_coal.
2012) , with associated neutrino production. Even more exotic scenarios have been proposed, such as photons produced inside the BLR, tunneling through it via photon to axion-like particle oscillations  (Tavecchio et al. 2012). In this paper, we present the multifrequency data of 4C +21. 35 collected from radio to VHE during 2010, and discuss a possible emission model for this source. A summary of the complete multiwavelength data of 4C +21. 35 presented in this paper and the relative facilities can be found in Table  1. The paper is organized as follows: in Sections 2 and 3 we briefly report the LAT and MAGIC data analysis and results, respectively. In Section 4 we report the result of Swift optical/UV/X-ray observations. Optical data collected by the Abastumani, ATOM, Catalina, Crimean, KVA, Steward, and St.
MAGIC Data and Analysis The MAGIC experiment is situated in the Observatorio del Roque de los Muchachos in the Canary Island of La Palma (28 • 45 ′ north, 18 • 54 ′ west), 2200 m above sea level. It consists of two 17-m Imaging Atmospheric Cherenkov Telescopes and can reach an energy threshold as low as 50 GeV in standard trigger mode. Details on the performance of the MAGIC telescope stereo system can be found in  Aleksić et al. (2012). MAGIC observed 4C +21. 35 between 2010 May 3 and June 19. In total, 16 hr of good quality data were collected. The data analysis was performed in the MAGIC Analysis and Reconstruction Software analysis framework  (Moralejo et al. 2009; Lombardi et al. 2011 ). On May 3 (MJD 55319), MAGIC obtained an excess with respect to the background of ≈ 78 events in 2.
Swift/XRT The XRT data were processed with standard procedures (xrtpipeline v0. 12. 6), filtering, and screening criteria by using the HEASoft package (v6. 11). The data were collected in photon counting mode in all observations, and only XRT event grades 0-12 were selected. The source count rate was low (< 0. 5 counts s -1 ), thus pile-up correction was not required. Data collected in the same day were summed in order to have better statistics. Since the observation performed on 2010 May 26 was short (∼500 s), it was not considered. Source events were extracted from a circular region with a radius of 20 pixels (1 pixel = 2. ′′ 36), while background events were extracted from a circular region with radius of 50 pixels away from the source region. Ancillary response files were generated with xrtmkarf, and account for different extraction regions, vignetting and point-spread-function corrections.
Swift/UVOT The script that handles the UVOT analysis is uvotgrblc (available within HEASoft). It determines the aperture corrected magnitude by (1) selecting the aperture size based on the observed source count-rate and the presence of close field sources; (2) choosing the background region based on the surface brightness among three annular regions centered on the main source in the summed images (circular regions around field sources are automati-cally excluded); (3) finding field stars to estimate the aperture correction, specific for each observation; (4) calling the task uvotsource to estimate the photometry. Since 4C +21. 35 is a very bright object in the optical and UV range and lies in a sparsely populated area of the sky, uvotgrblc selected a circle of 5 ′′ as the source extraction region and a full annulus for the background region for all the observations.
Abastumani, Crimean and St. Petersburg Data Observational data at optical wavelengths (R-band) were obtained at the 0. 7-m reflector of the Crimean Astrophysical Observatory and 0. 4-m LX-200 telescope of the Astronomical Institute of St. Petersburg State University, both equipped with photo-polarimeters based on ST-7XME CCDs. A standard technique of bias and dark subtraction and flat-field correction was used. Photometric calibration was made relative to two nearby standard stars, located in the same field. Optical observations in R-band were performed also by the 0. 7-m meniscus f/3 telescope of Abastumani Astrophysical Observatory in Abastumani, Georgia.
ATOM Data Optical observations in R filter for this campaign were obtained between 2010 February and May with the 0. 8-m optical telescope ATOM in Namibia  (Hauser et al. 2004). ATOM is operated robotically by the H. E. S. S. collaboration and obtains automatic observations of confirmed or potential γ-bright blazars. Data analysis (debiassing, flat fielding, and photometry with Source-Extractor; Bertin and Arnouts 1996) is conducted automatically using the pipeline developed by the ATOM Team.
SMA Data The 230 GHz (1. 3 mm) light curve was obtained at the Submillimeter Array (SMA) on Mauna Kea (Hawaii). 4C +21. 35 is included in an ongoing monitoring program at the SMA to determine the fluxes of compact extragalactic radio sources that can be used as calibrators at mm wavelengths. Details of the observations and data reduction can be found in  Gurwell et al. (2007). Data from this program are updated regularly and are available at the SMA Web site. 4.
OVRO Data As part of an ongoing blazar monitoring program, the Owens Valley Radio Observatory (OVRO) 40-m radio telescope has observed 4C +21. 35 at 15 GHz regularly since the end of 2007  (Richards et al. 2011). This monitoring program includes about 1700 known or likely γ-ray-loud blazars, including all candidate γ-ray blazar survey (CGRaBS) sources above declination -20 •. The sources in this program are observed in total intensity twice per week with a 4 mJy (minimum) and 3% (typical) uncertainty on the flux density. Observations are performed with a dual-beam (each 2. 5 arcmin full-width half-maximum) Dicke-switched system using cold sky in the off-source beam as the reference. Additionally, the source is switched between beams to reduce atmospheric variations. The absolute flux density scale is calibrated using observations of 3C 286, adopting the flux density (3.
UMRAO Data UMRAO centimeter band total flux density observations were obtained with the University of Michigan 26-m paraboloid located in Dexter, Michigan, USA. The instrument is equipped with transistor-based radiometers operating at frequencies centered at 4. 8, 8. 0, and 14. 5 GHz with bandwidths of 0. 68, 0. 79, and 1. 68 GHz, respectively. Dual horn feed systems are used at 8 and 14. 5 GHz, while at 4. 8 GHz a single-horn, mode-switching receiver is employed. Each observation consisted of a series of 8-16 individual measurements over approximately a 25-45 minute time period, utilizing an on-off observing technique at 4. 8 GHz, and an on-on technique (switching the target source between the two feed horns, which Fig. 2. -Radio and mm light curves of 4C +21. 35 in units of Jy. The period covered is between 2009 January 1 (MJD 54837) and 2011 February 28 (MJD 55620).
Medicina Data We observed 4C +21. 35 with the Medicina radio telescope five times between 2010 April 26 and 2010 May 11. We used the new Enhanced Single-dish Control System (ESCS) acquisition system, which provides enhanced sensitivity and supports observations with the cross scan technique. We observed at 22 GHz in the first four epochs, and at 5 GHz in the last two; the observations on 2010 May 10 were carried out at both frequencies and can be used for an estimate of the simultaneous spectral index. At each epoch, the source was observed for about 10 minutes and calibrated with respect to 3C 286, after correcting the data for atmospheric opacity. The observing conditions varied from epoch to epoch, resulting in different noise levels and significance of the detections. However, after flagging bad scans, we always obtained a highly significant (≫ 5σ) detection.
MOJAVE Data 4C +21. 35 is part of the Monitoring of Jets in Active Galactic Nuclei with VLBA Experiments (MOJAVE) sample, allowing us to investigate at 15 GHz the radio structure and jet kinematics of this source over a long period. The data were processed using the standard procedures described in the AIPS cookbook 5 (for details see  Lister et al. (2009) ). The radio properties of 4C +21. 35 strongly indicate that it has a relativistic jet beamed very closely along our line of sight. The kiloparsec scale radio morphology from Very Large Array images  (Cooper et al. 2007; Saikia et al. 1993 ) consists of a bright jet starting out to the north-east of a bright core, and gradually curving to the east, terminating in a hotspot located approximately 60 kpc from the core. Surrounding the core is a circular halo of diffuse radio emission ∼100 kpc in diameter, which is consistent with a large radio lobe being viewed end-on.
Data Selection We have built three quasi-simultaneous SEDs from the data discussed above, shown in Figure  9. These SEDs include the flaring states of 2010 June 17 (red circles) and 2010 April 29 (green squares), and a quiescent state, integrated in time from 2008 August 4 to 2008 September 12 (blue diamonds). For the three SEDs we used the LAT spectra calculated over 2010  June 17, 2010 April 23-May 2, 2008 August 4-2009 September 12 (taken from Tanaka et al. 2011; Aleksić et al. 2011) , and the Swift data collected on 2010 June 20, 2010 April 23, and 2009 April 10, respectively. The MAGIC data collected on 2010 May 3 and June 17 are included for the two flaring states. These data have been corrected for EBL absorption using the model of  Finke et al. (2010). This model is nearly identical in the energy range    2004 ) relies on the H-β broad line and the continuum luminosity-BLR radius relation from  Kaspi et al.
Accretion Disk Emission For both the flaring state models, we find that a good fit to the UV data from Swift-UVOT requires an inner disk radius R in < 6R g , where 6R g is the value one would expect for the innermost stable circular orbit around a nonrotating Schwarzschild BH. Indeed, our fits favor R in = 3R g (see Figure  10 ), the value one would expect for a maximally (prograde) rotating Kerr BH. This is because, as seen in the figure, a larger R in will not fit the UV data points. We also performed fits with the color correction of  Chiang (2002). This requires a slightly higher disk luminosity (L disk = 2 × 10 46 erg s -1 ), but our results for the inner disk radius remain unchanged. This is of interest since one would expect a BH spin at or near the maximum value if the jet is generated from the Blandford-Znajek mechanism  (Blandford & Znajek 1977).
The Fermi LAT Collaboration acknowledges generous ongoing support from a number of agencies and institutes that have supported both the development and the operation of the LAT as well as scientific data analysis. These include the National Aeronautics and Space Administration and the Department of Energy in the United States, the Commissariat à l'Energie Atomique and the Centre National de la Recherche Scientifique / Institut National de Physique Nucléaire et de Physique des Particules in France, the Agenzia Spaziale Italiana and the Istituto Nazionale di Fisica Nucleare in Italy, the Ministry of Education, Culture, Sports, Science and Technology (MEXT), High Energy Accelerator Research Organization (KEK) and Japan Aerospace Exploration Agency (JAXA) in Japan, and the K. A. Wallenberg Foundation, the Swedish Research Council and the Swedish National Space Board in Sweden.
also supported by the  CPAN CSD2007-00042  and MultiDark  CSD2009-00064  projects of the Spanish Consolider-Ingenio 2010 programme, by grant  127740  of the  Academy of Finland , by the  DFG Cluster of Excellence  " Origin and Structure of the Universe ", by the  DFG Collaborative Research Centers   SFB823/C4  and  SFB876/C3 , and by the  Polish MNiSzW  grant  745/N-HESS-MAGIC/2010/0. We thank the  Swift team  for making these observations possible, the duty scientists, and science planners. This research has made use of data from the MOJAVE database that is maintained by the MOJAVE team (Lister et al. 2009, AJ, 137, 3718). The  MOJAVE  project is supported under  NASA-Fermi  grant  11-Fermi11-0019. The  National Radio Astronomy Observatory  is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc.
Data from the Steward Observatory spectropolarimetric monitoring project were used. This program is supported by  Fermi Guest Investigator  grants  NNX08AW56G ,  NNX09AU10G , and  NNX12AO93G. The St. Petersburg University team acknowledges support from  Russian RFBR  foundation, grants  12-02-00452  and  12-02-31193. The Abastumani team acknowledges financial support of the project  FR/638/6-320/12  by the  Shota Rustaveli National Science Foundation  under contract  31/77. The Metsähovi team acknowledges support from the  Academy of Finland  to our observing projects (numbers  212656 ,  210338 ,  121148 , and others). E. R. was partially supported by the  Spanish MINECO  projects  AYA2009-13036-C02-02  and  AYA2012-38491-C02-01  and by the  Generalitat Valenciana  project  PROMETEO/2009/104 , as well as by the  COST MP0905 action  " Black Holes in a Violent Universe ".
The corresponding multijunction structure requires series connection of subcells via tunnel junctions. At this design stage of the MULTISOLSI project, we rely on published values as a guideline and on numerical calculations for Si tunnel junctions we have performed with SILVACO software. These show that in GaAs tunnel junctions  [17] , for example, peak tunelling currents above 10 4 A. m -2 are readily obtainable. The total current density obtainable with the global AM1. 5G terrestrial spectrum is 726 A. m -2. The multijunction current flow is therefore at least an order of magnitude less than that of a suitable GaAs tunnel junction, which therefore serves to cause a small voltage loss, as it is designed to. As such, in this work we treat the tunnel junctions as absorbing layers from an optical point of view, and as series resistance elements from the electrical point of view.
For the images presented in this paper, the reconstruction typically took 30 min. Both classical imaging and super-resolution imaging are performed through the native software (NIS-Elements, Nikon, Figure  1c ). Macro instructions in the NIS-Elements software, coupled to a custom software module (LabView, National Instruments, Austin, Texas, USA) were used to control the different optic elements (laser, cameras, polarization control). In a typical use-case, the user acquires a standard image of the sample through classical imaging, draws a region-of-interest (ROI) on the image, and captures a super-resolution view of this region.
Non-invasive long-term live cell super-resolution imaging The BSR modality requires only a few mW of light intensity at the sample level to operate, much less than required by some other super-resolution techniques. 1  This small amount of light nonetheless allows it to generate images of good quality, which makes it well suited to study live specimen in super-resolution. To support this assertion, we imaged U373 live cells stained for microtubules thanks to a transfection with tubulin-eGFP or EMTB-3G. 25 We implemented in the LabView software module a scanning mode dedicated to the imaging of a region in quick Figure  1  (See previous page). A super-resolution system based on conical diffraction. (A) Overview of the system. The laser fiber input of a classical commercial laser-scanning microscope is hijacked to pass through the BSM.
Acknowledgments We greatly benefit from the galvanizing environment of the  Institut Pasteur  and its researchers, and would like to thank them for their contributions, whether it is samples or stimulating discussions. In particular, we are grateful to  Ce ćile Leduc  and  Sandrine E ́tienne-Manneville ,  Fabrizia Stavru ,  E ́dith Gouin  and  Pascale Cossart ,  Ellen Arena  and  Philippe Sansonetti. We also thank  M ebarek Temagoult ,  B eatrice Durel  and  Pierre Bourdoncle  from the  Cochin Imaging Facility  ( INSERM U1016/ CNRS UMR8104 / Univ Paris Descartes/Institut Cochin ), and our colleagues from the imaging platform of the  Institut Pasteur  (www. imagopole. org) for constant support. For their generous support for the facilities, and funding of the 3D-SIM equipment, we are grateful to  France BioImaging (FBI)  funding ( Program: Investissement d'Avenir, "Investments  for the future") supported by the  French National Research Agency  ( ANR-10-INSB-04-01 ); the  Region Ile de France  (program  DIM-MalInf project: "A platform for multi-scalar imaging "), the  Ministe re de l'Enseignement Supe ŕieur et de la Recherche, OSEO/BPI , the incubator  Paris Biotech Sante  , and the  Institut Pasteur.
In cavity polariton quantum gases, where images can be taken in real time, PCA will allow to extract the relevant information inside a large data set  [40]. Finally, cold trapped ions systems behave as crystals supporting many collective modes, which could be studied using PCA  [41]. We envision that PCA is suited to perform Bogoliubov spectroscopy, in the spirit of the method used in references  [10, 11]. A mode largely excited by a resonant excitation will be easily identified by PCA and its frequency precisely determined by measuring its eigenvalue with respect to the modulation frequency. In contrast to Fourier methods, PCA can identify the dominantly excited mode using samples covering only one oscillation period of the mode either by recording the time evolution or by varying the excitation phase.
The sampling is performed every T s = 0. 126. The result of this procedure is shown in the left panel of figure  4. On the other hand we directly compute the small excitation spectrum using Bogoliubov-de Gennes equations obtained from the linearisation of (B1) around the system ground state in the final trap. This implies the ability to diagonalize a square 2 15 × 2 15 matrix which is quite challenging. Fortunately this matrix is sparse and we are interested only in the lowest energy part of the spectrum, which means we do not have to compute all the eigenstates. We designed a fast custom C program that uses a combination of an iterative method  [42]  with an efficient sparse matrix library  [43]  to compute the relevant eigenvectors. The result of this procedure is displayed in the right panel of figure  4.
, 2012) , cloud deployment  (Zhao et al. , 2013) , algorithm vectorization  (Rizk and Lavenier, 2010) , multithreading, etc. , have demonstrated high potentiality on NGS processing. The overall efficiency of NGS software depends on a smart combination of data representation and use of the available processing units. Developing such software is thus a real challenge, as it requires a large spectrum of competence from high-level data structure and algorithm concepts to tiny details of implementation. The GATB library aims to ease the design of NGS algorithms. It offers a panel of high-level optimized building blocks to speedup the development of NGS tools related to genome assembly and/or genome analysis. The underlying data structure is a memory efficient de-Bruijn graph  (Compeau et al. , 2011) , and the general parallelism model is multithreading.
The GATB library targets standard computing resources such as current multicore processor (laptop computer, small server) with a few gigabytes of memory. Hence, from the high-level C+ + functions available in the GATB library, NGS programing designers can rapidly elaborate their own software based on state-of-the-art algorithms and data structures of the domain. Based on the same idea, other bioinformatics libraries exist, from which domain-specific tools can be elaborated. The NGS++ library  (Markovits et al. , 2013)  is specifically tailored for developing applications that work with genomic regions and features, such as epigenomics marks, gene features and data that are associated with BED type files. The SeqAn library  (Doring et al. , 2008)  is a general-purpose library targeting standard sequence processing.
Advanced data structures such as de-Bruijn graphs are not included in SeqAn. Khmer  (Crusoe et al. , 2014)  is a library and toolkit for doing k-mer-based NGS dataset analysis. As with GATB, most of khmer relies on an underlying probabilistic data structure (Bloom filter). The khmer library can be used in various k-mer processing such as abundance filtering, error trimming, graph size filtering or partitioning.
METHODS One of the main concerns of the GATB-core library is to provide computing modules able to run on standard machines, i. e. computers not requiring large amount of main memory. The central data structure is a de-Bruijn graph from which numerous actions can be performed as shown Figure  1 : data error correction, assembly, biological motif detection [e. g. single nucleotide polymorphism (SNP)], etc. The graph is constructed by extracting and by counting all the different k-mers from one or several sequencing datasets. This timeand space-consuming task is conducted by a disk streaming algorithm, DSK  (Rizk et al. , 2013) , which adapts its memory requirement according to the available computer memory. Trade-off between execution time and memory occupancy can be set up: the larger the computer memory, shorter the computation time (reduced disk access).