dataesr/scientific-paragraphs-categorization huggingface dataset:
As outlined in Section 2. 2, high signal-to-noise detections on baselines to ALMA can be used to remove atmospheric phase fluctuations on non-ALMA baselines. Phase stabilizing the array in this way allows coherent integration of the VLBI signal on non-ALMA baselines beyond the atmospheric coherence time. Figure  13  demonstrates the process on real EHT data during relatively poor weather conditions, confirming the general approach and basis for the specifications in Section 2. Precise estimates of the observed systematic errors during the 2017 April EHT campaign are detailed in Paper III. Subsequent calibration steps convert the correlation coefficients derived from fringe detection to correlated flux density (Jy). This is accomplished through use of apriori information about station sensitivities, and by the application of selfcalibration techniques to correct for variations in telescope gain over time and frequency.
Stochastic atmospheric phase variations result in fringe-rate variation over time, spreading the signal in the plot on the left. To recover the total fringe amplitude, baselines to ALMA are used to phase reference the array at a short timescale. Data shown are from a VLBI scan on a quasar calibrator (3C 279) obtained during EHT observations in 2017 April. The data are taken at low elevation, and at several sites during the afternoon and early evening when the atmosphere is often unstable. Baselines to ALMA are able to phase steer the remaining sites in the array at an effective timescale of 1-3 s depending on S/N. At SMA due to the mid-afternoon local observation, phasing is particularly challenging. This leads to an amplitude efficiency of about 90 % on SMA baselines, as well as increased measurement thermal noise for the APEX-SMA spectrum with a full-scan S/N of only ∼10.
Technology maturation, fueled by industry-driven trends, was focused primarily on improving the bandwidth of observations by increasing digitization and recording rates. Over a period of 10 yr, EHT data capture rates increased from 4 to 64 Gbps, allowing for observations that take full advantage of the capabilities of modern millimeter receivers. The parallel development of phased array technologies and investment in site-specific infrastructure (see the Appendix) have now led to a global EHT array with the capability to address its science goals. Had the EHT project needed to build a VLBI array from the ground up, the cost would have been prohibitive. By developing new systems and infrastructure that allowed for the use of existing telescopes and facilities, most of which were not originally conceived to operate as VLBI elements, the EHT has created a purpose-built array with unique capability at modest cost.
First, the beamformer processing of 2 GHz bands is spread across eight ROACH2 devices. These parallel data streams must be collected and formatted in real time in order to record to the Mark 6, which is done using a custom FPGA device called the SWARM Digital Backend (SDBE). The data are received on four of the eight 10 GbE ports on the SDBE. The packets are time-stamped, the frequency domain samples are quantized from 4-bit complex to 2-bit complex, the packets are formatted with VDIF headers, and then transported over Ethernet to the Mark 6. As the beamformer data packets are relatively small, several of these packets are bundled into each UDP packet to reduce the interrupt rate on the Mark 6 and prevent packet loss. The second complication to using SWARM in VLBI is that the data are in complex frequency domain representation as opposed to the time-domain format used by the majority of stations in the EHT, and the data are sampled at a different rate than the single-dish EHT stations: 4.
576 Gsps compared to 4. 096 Gsps at single-dish sites. Prior to the correlation of SWARM data with data from other sites, an offline inversion and resampling program known as the Adaptive Phased-array and Heterogeneous Interpolating Downsampler for SWARM (APHIDS) is used to preprocess the SMA data. Development of a real-time preprocessing system to be integrated into the SDBE is currently in progress. The SMA VLBI pipeline is illustrated in Figure  14. A. 10. SMT (3200 m Altitude) The SMT, located on Mount Graham, Arizona, was built by the Max-Planck-Institut für Radioastronomie in 1993, and is now operated and maintained by the ARO  (Baars et al. 1999). Work to incorporate the telescope in mm-wavelength VLBI experiments began in the late 1990s  (Doeleman et al. 2002; Krichbaum et al. 2002).
Figure7. Functional diagram of the R2DBE. A pair of ADCs sample two channels of 2. 048 GHz Nyquist bandwidth IF bands, typically representing two antenna polarizations. After requantization of the samples to 2 bits, the data are distributed in VDIF packets over a 10 GbE network to Mark 6 recorders. The maximum FPGA clock speed is too slow to process the ADC output stream rate of 4096 megasamples per second in series, so 16 ADC samples are transferred from the sampler in parallel on each FPGA clock cycle and are processed in parallel though the FPGA, which is clocked at a sixteenth of the sample clock, or 256 MHz. The FPGA and sampler clocks are locked to the maser reference frequency. In addition to the sample clock and dual IF inputs, each ADC circuit board is also equipped with a lowfrequency synchronization input.
The authors of this Letter thank the following organizations and programs: the  Academy of Finland  (projects  274477 ,  284495 ,  312496 ); the  Advanced European Network of Einfrastructures for Astronomy with the SKA (AENEAS)  project, supported by the  European Commission   Framework Programme Horizon 2020 Research and Innovation action  under grant agreement  731016 ; the  Alexander von Humboldt Stiftung ; the  Black Hole Initiative at Harvard University , through a grant ( 60477 ) from the  John Templeton Foundation ; the  China Scholarship Council ;  Comisión Nacional de Investigación Científica y Tecnológica (CONICYT, Chile , via PIA ACT172033, Fondecyt  1171506 ,  BASAL AFB-170002 , ALMA-conicyt 31140007);  Consejo Nacional de Ciencia y Tecnología  ( CONACYT, Mexico , projects  104497 ,  275201 ,  279006 ,  281692 ); the  Delaney Family via Delaney Family John A.
043. 513 ) and  Spinoza Prize SPI   78-409 ; the  New Scientific Frontiers  with  Precision Radio Interferometry Fellowship  awarded by the  South African Radio Astronomy Observatory (SARAO) , which is a facility of the  National Research Foundation (NRF) , an agency of the  Department of Science and Technology (DST) of South Africa ; the  Onsala Space Observatory (OSO)  national infrastructure, for the provisioning of its facilities/observational support (OSO receives funding through the  Swedish Research Council  under grant  2017-00648 ) the  Perimeter Institute for Theoretical Physics  (research at  Perimeter Institute  is supported by the  Government of Canada  through the  Department of Innovation, Science and Economic Development Canada  and by the  Province of Ontario  through the  Ministry of Economic Development, Job Creation and Trade) ; the  Russian Science Foundation  (grant  17-12-01029 ); the  Spanish Ministerio de Economía y Competitividad  (grants  AYA2015-63939-C2-1-P ,  AYA2016-80889-P ); the  State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa " award for the  Instituto de Astrofísica de Andalucía  ( SEV-2017-0709 ); the  Toray Science Foundation ; the  US Department of Energy (USDOE)  through the  Los Alamos National Laboratory  (operated by  Triad National Security, LLC , for the  National Nuclear Security Administration of the USDOE  (Contract  89233218CNA000001 )); the  Italian Ministero dell'Istruzione Università e Ricerca  through the  grant Progetti Premiali 2012-iALMA  ( CUP C52I13000140001 ); the  European Unionʼs   Horizon 2020 research and innovation programme  under grant agreement No 730562  RadioNet ;  ALMA North America Development Fund Chandra   TM6-17006X.
NRAO and the  Massachusetts Institute of Technology Haystack Observatory  supported the acquisition of the ALMA-North America prototype antenna and its repurposing for deployment in Greenland. The NOEMA observatory at the  Plateau de Bure, France , and the IRAM 30-m telescope on Pico Veleta, Spain, are operated by IRAM and supported by  CNRS  ( Centre National de la Recherche Scientifique, France ),  MPG  ( Max-Planck-Gesellschaft, Germany)  and  IGN (Instituto Geográfico, Nacional, Spain). The SMA is a joint project between the SAO and ASIAA and is funded by the  Smithsonian Institution  and the  Academia Sinica. The JCMT is operated by the  East Asian Observatory  on behalf of the NAOJ, ASIAA, and  KASI , as well as the  Ministry of Finance of China, Chinese Academy of Sciences , and the  National Key R&D Program  (No.
Simulation results In order to predict the properties of the cells to be developed by CRHEA, we performed simulations using SCAPS software. SCAPS is a software for modeling solar cells based on CdTe and CIGS  (7) , developed by Marc Bulgerman of the Department of Electronics and Information Systems (ELIS), University of Gent, in Belgium. Our simulations thus consisted in the optimization of the emitter layer of the heterojunction 3C-SiC/Si. We optimized also the influence of the diffusion length of the carriers in the bulk of Si following the deposition temperature during growth of the SiC/Si deposition process by the CVD method.
The entropy rate h of a natural language quantifies the complexity underlying the language. While recent studies have used computational approaches to estimate this rate, their results rely fundamentally on the performance of the language model used for prediction. On the other hand, in 1951, Shannon conducted a cognitive experiment to estimate the rate without the use of any such artifact. Shannon's experiment, however, used only one subject, bringing into question the statistical validity of his value of h = 1. 3 bits per character for the English language entropy rate. In this study, we conducted Shannon's experiment on a much larger scale to reevaluate the entropy rate h via Amazon's Mechanical Turk, a crowd-sourcing service. The online subjects recruited through Mechanical Turk were each asked to guess the succeeding character after being given the preceding characters until obtaining the correct answer.
6 bpc. For extrapolation, however, a large number of observations becomes necessary in order to capture the dependence of the entropy rate on n well. To that end, we conducted a large-scale cognitive test to acquire the English language entropy rate h through Amazon Mechanical Turk (AMT). AMT is a crowd-sourcing service offered by Amazon that allowed us to gather a large number of participants in a short time and at a reasonable cost. We focused on the entropy rate in English to make a fair comparison with Shannon  [1]  and other works. Other languages possibly have different values of the entropy rate, as can be seen in the comparison made in  [4]. We collected a total of 172,954 character predictions from 683 different subjects. To the best of our knowledge, the scale used in this experiment was more than two times larger than any used in previous studies.
Recently, Dai et al. [7]  reported h = 1. 08 bpc when using Transformer XL on text8. This dataset is a collection of natural language text taken from Wikipedia and cleaned to the point of having only 26 alphabet characters and space corresponding to the setting of the Shannon's experiment. That h value was smaller than our estimated value, suggesting that humans may not be able to outperform computational models in character guessing games. Nevertheless, it is worth considering the differences in the conditions of the experiments. The primary factor is the context length. Dai et al. [7] 's model utilized several hundred context lengths to acquire their results. The high performance of the neural language models can be explained, at least partially, by their ability to utilize long contexts.
8 to 46. 2 (Table  S2 ) for the six bats (where QV 40 represents 1 error in 10,000 bp). Since the algorithms for assembling, scaffolding, and haplotyping are an active area of research  23  , we expect that in the future even more complete genome reconstructions can be produced with the data we collected. Even so, our current strategy and algorithms generated chromosome-level assemblies of the six bats with unprecedented contiguity, which are comparable to the best reference-quality genomes currently generated for any eukaryotic species with a complex, multi-gigabyte genome  24. Importantly, they meet the Vertebrate Genome Project (VGP) minimum standard of 3. 4. 2QV40 and have been added to the VGP collection. To assess genome completeness, we first evaluated the presence of 4,104 genes that are highly conserved among mammals (BUSCO, Benchmarking Universal Single-Copy Orthologs  25  ).
Iso-seq data were processed using the TAMA pipeline  30  which allowed capturing a substantially greater diversity of transcripts and isoforms than the default pipeline (https://github. com/PacificBiosciences/IsoSeq3). All transcriptomic, homology-based and ab initio evidence were integrated into a consensus gene annotation that we further enriched for high-confidence transcript variants and filtered for strong coding potential. For the six bats, we annotated between 19,122 and 21,303 coding genes (Fig. 1f ). These annotations completely contain between 99. 3 and 99. 7% of the 4,104 highly conserved mammalian BUSCO genes (Fig. 1f , Table  S4 ), showing that our six bat assemblies are highly complete in coding sequences. Since every annotated gene is by definition present in the assembly, one would expect that BUSCO applied to the protein sequences of annotated genes and BUSCO applied to the genome assembly should yield highly similar statistics.
The Origin of Chiroptera within Laurasiatheria Identifying the evolutionary origin of bats within Laurasiatheria is a key prerequisite for comparative analyses aimed at revealing the genomic basis of traits shared by bats. However, the phylogeny of Laurasiatheria and, in particular, the position of bats has been a long-standing, unresolved phylogenetic question  14, 34. This is perhaps the most challenging interordinal problem in placental mammal phylogenetics, as multiple phylogenetic and systematic investigations using large nucleotide and genomic scale datasets or transposable element insertions support alternative topologies  35. These incongruent results have been attributed to the challenge of identifying two, presumably short, internal branches linking four clades (Chiroptera, Cetartiodactyla, Perissodactyla, Carnivora + Pholidota) that diverged in the Late Cretaceous  35.
We revisited this question leveraging the high completeness of our gene annotation. First, we extracted a comprehensive set of 12,931 orthologous protein-coding genes from the 48 mammalian genomes, resulting in a dataset comprising 21,471,921 aligned nucleotides in length, which contained 7,913,054 parsimony-informative sites. The best-fit model of sequence evolution for each of the 12,931 gene alignments was inferred using ModelFinder 36 (Table  S9 ). The species tree was then estimated by maximum likelihood using the model-partitioned dataset with IQTREE  37  and rooted on Atlantogenata  38. Branch-support values were obtained by UFBoot  39  with 1000 bootstrap pseudoreplicates. These analyses led to 100% bootstrap support across the entire tree (Fig. 2a ) and seemingly identified the origin of bats within Laurasiatheria.
The basal split is between Eulipotyphla and other laurasiatherians (i. e. , Scrotifera). Within Scrotifera, Chiroptera is the sister clade to Fereuungulata (Cetartiodactyla + Perissodactyla + Carnivora + Pholidota). This tree disagrees with the Pegasoferae hypothesis  40  , which groups bats with Perissodactyla, Carnivora and Pholidota, but agrees with concatenation analyses of phylogenomic data  41. Evolutionary studies based on 102 retroposons, including ILS-aware analyses, also support a sister-group relationship between Chiroptera and Fereuungulata, but differ from the present analyses in supporting a sister-group relationship between Carnivora and Cetartiodactyla  34, 35. However, as the number of homologous sites increases in phylogenomic datasets, so too does bootstrap support  42  , even sometimes for an incorrect phylogeny  43  , and as non-coding sequences can produce a different topology than coding sequences  44  , we further explored the phylogenomic signal within our genomes.
To assess whether the tree inferred from the concatenated dataset (Fig. 2a ) is also supported by the non-coding part of the genome, we estimated a phylogeny using the models of best fit (Table  S9 ) for a dataset comprising 10,857 orthologous conserved non-coding elements (CNEs), which contained 5,234,049 nucleotides and 1,225,098 parsimony-informative sites (Table  S10 ), using methods as described above. The result of this analysis (Fig. 2b ) supports a tree similar but not identical to that inferred from the protein-coding sequences (Fig. 2a ), including a sister-group relationship between Chiroptera and Fereuungulata, but with Perissodactyla more closely related to Carnivora + Pholidota than to Cetartiodactyla. The CNE tree also recovered a different position for Tupaia (Scandentia) within Euarchontoglires.
The remaining 10,827 genes supported one fixed tree topology over the other 14 (Table  S11 ), with the number of genes supporting each topology highlighted in Fig. 2c. The best-supported topology was that of our concatenated dataset for protein-coding genes (Fig. 2a ; Tree1 with 1007/10827 genes), showing a sister group relationship between Chiroptera and Fereuungulata, which is also supported by the CNEs (Fig. 2b ). This suggests that the majority of the genome supports a sister relationship between Chiroptera and the other Scrotifera. That said, there were four other topologies that had support from >800 genes (Tree14 883/10827; Tree04 865/10827; Tree15 820/10827; Tree13 806/10827) (Fig. 2c ). However, even with similar support levels for several topologies, the phylogenetic position for Chiroptera is pectinate on the most common gene tree and does not qualify as anomalous.
To overcome these biases, we performed a series of compatibility analyses on each gene partition and across the supermatrix at 1 st , 2 nd and 3 rd codon sites; 1 st + 2 nd codon sites; 1 st + 2 nd + 3 rd codon sites; amino acids, assuming a 4-state alphabet for nucleotides and a 20 state-alphabet for amino acids (see supplementary methods section 4. 2). We excluded all alignments for which evidence of saturation of substitutions and thus decay of the historical signal was detected by SatuRation 1. 0 (https://github. com/lsjermiin/SatuRationSatuRation). Furthermore, we excluded all alignments for which model mis-specification due to evolution under non-homogeneous conditions was detected by the matched-pairs test of symmetry  50  implemented in Homo 2. 0 (https://github. com/lsjermiin/Homo2.
Acknowledgements This work was supported by the  Max Planck Society , the  German Research Foundation  ( HI 1423/3-1 ), and by  European Research Council   Research Grant  ( ERC-2012-StG311000 ). SCV was funded by a  Max Planck Research Group Award , and a  Human Frontiers Science Program (HFSP)   Research grant  ( RGP0058/2016 ). GJ/ECTfunding from  Royal Society/Royal Irish Academy  cost share programme. LMD was supported, in part, by  NSF -DEB 1442142  and  1838273 , and  NSF-DGE 1633299. DAR was supported, in part, by  NSF -DEB 1838283. The authors would like to thank  Stony Brook Research Computing  and  Cyberinfrastructure , and the  Institute for Advanced Computational Science at Stony Brook University  for access to the high-performance SeaWulf computing system, which was made possible by a  National Science Foundation  grant (# 1531492 ).
ECT was funded by a  European Research Council   Research Grant  ( ERC-2012-StG311000 ),  UCD Wellcome Institutional Strategic Support Fund , financed jointly by  University College Dublin  and  SFI-HRB-Wellcome Biomedical Research Partnership  (ref  204844/Z/16/Z ) and  Irish Research Council Consolidator Laureate Award. EDJ and OF were funded by the  Rockefeller University  and the  Howard Hughes Medical Institute. We thank the  Long Read Team of the DRESDEN-concept Genome Center ,  DFG NGS Competence Center, c/o Center for Molecular and Cellular Bioengineering (CMCB) ,  Technische Universität Dresden, Dresden, Germany ,  Sven Kuenzel  and his team of the  Max-Planck Institute of Evolutionary Biology in Ploen, Germany , the members of the  Vertebrate Genomes Laboratory at The Rockefeller University, New York, US  for their support.
Data availability statement All data generated or analysed during this study are included in this published article and its supplementary information files. All genomic and transcriptomic data are publicly available for visualization and download via the open-access Bat1K genome browser (https://genomepublic. pks. mpg. de). In addition, the assemblies have been deposited in the NCBI database and GenomeArk (https://vgp. github. io/genomeark/). Accession numbers for all data deposits can be found in the supplementary information files of this article.
QTL positions The positions of the QTL were drawn independently with a density proportional to the gene density of each species (taking gene distributions without transposable elements; see FigS2 for the gene distribution of B. rapa and FigS3 for O. sativa). Gene physical positions were downloaded from public databases (for O. sativa: https://rapdb. dna. affrc. go. jp/ download/irgsp1. html, file "Gene structure information in GFF format" for the computationally predicted genes; and for B. rapa: http:// brassicadb. org/brad/datasets/pub/BrassicaceaeGenome/Brassica_rapa/ V3. 0/, file Brapa_genome_v3. 0_genes. gff3. gz). QTL physical positions were thus sampled at random among the gene physical positions, for each replicate of our simulations. As only genetic positions in centi-Morgans were used during simulations, we had to convert the QTL physical positions into their genetic positions by using the genetic map for each situation (normal, HR, and boosted recombinations for both O.
(2016)  wondered about the use of increased recombination for genomic selection programs and speculated that large datasets would be needed. Indeed, the calibration of genomic selection models is dependent on genomic blocks shared across individuals in the population; increasing recombination reduces the sizes of these blocks. Consequently, the calibration of the genomic selection model is made more difficult and more importantly, the predictive power of the model decreases faster as one accumulates crossovers throughout generations. Nevertheless, our results show a benefit of increased recombination for genomic selection programs even when using a relatively modest training population of 250 individuals. We did observe as anticipated that the accuracy of genomic prediction was reduced under increased recombination (faster break-down of the linkage blocks).
ACKNOWLEDGMENTS We thank  S. Mezmouk ,  E. Jenczewski ,  J. C. Motamayor ,  D. Livingston ,  C. E. Durel  and  R. Mercier  for constructive comments and discussion. This work has benefited from a  French State grant  ( LabEx Saclay Plant Sciences-SPS ,  ANR-10-LABX-0040-SPS ), managed by the  French National Research Agency  under an " Investments for the Future" program  ( ANR-11-IDEX-0003-02 ) and KWS, MARS, and Secobra which co-funded the salary of ET and  Ecole Doctorale FIRE -Program Bettencourt  for support.