dataesr/scientific-paragraphs-categorization huggingface dataset:
Since it is stored as a dense matrix, this inversion system is at present limited to about a month of observations. A description of how to get the code is available in appendix Appendix A. The above calculations consider only the requirements to produce an estimate of the posterior mean: specifying the full posterior distribution requires also the posterior covariance. Storing the posterior covariance requires the same prohibitive amount of storage as the prior covariance, so approximations are needed. The method chosen here is to aggregate the fluxes to a coarser resolution in time and in space, specifically 7 d temporal resolution and 108 km spatial resolution and represent the covariances only on that reduced grid. Similar methods are suggested by  Yadav and Michalak (2013)  and  Bennett (2002).
The inversion package described in this paper provides functions to calculate reduction and prolongation operators able to modify the spatial parts of the background error covariance matrix B and observation operator H for lower spatial resolution, but relies on the capabilities of the python package XArray for reducing the temporal resolution  (Hoyer & Hamman, 2017)  for ease of implementation and to avoid duplication of effort. The calculated reduction operator is a simple arithmetic mean within each of the coarser-resolution grid cells. The prolongation operator used here fills the whole of an averaged region with the average of that region. The inversion functions in this framework can take the lower-resolution observation operator and background error covariance matrix as extra arguments and will use them to produce the posterior covariance estimate at the reduced resolution.
where the hat denotes the Fourier transform of the symbol  (Eq. 1. 14. 5 DLMF, 2019). Using this approach, the correlation operator can be represented using only the spectral coefficients of the correlation function, which take up about the same space as the fluxes, and matrix-vector products can be calculated using the FFT, which is much faster than the matrix multiplication  (Cooley & Tukey, 1965; Gentleman & Sande, 1966; Stockham, 1966) : the code for this paper uses the pyFFTW interface to the implementations in the FFTW library  (Frigo & Johnson, 2005; Gomersall et al. , 2016). This method uses the projected map coordinates to compute distances rather than using the proper greatcircle distances. The assumption that the domain is doubly periodic in space, required by the FFT, is avoided by embedding the physical domain in a computational domain at least twice as large as the physical domain  (Nowak et al.
By the same token, the fraternal-twin posterior changes much more from day to day, in accordance with the shorter correlation time scale. Both parts are exactly as allowed by the prior error correlations; this underscores the importance of the prior covariance in determining the output of the inversion, and the need for data-driven error covariance structures. The inversion of the eighty prior mean estimates was accomplished with a single run of the inversion code for each experiment, which shared the value of HBH T + R among the calculations required for the eighty posterior mean estimates and the reducedresolution posterior covariance matrix. As a note, the updates to each prior mean estimate are independent of the other members of the ensemble. The posterior covariance matrix A red depends only on B, H, and R, and so is the same for all the realizations, and was only calculated twice: once with an attempt to account for aggregation error and once without.
, 2009a). This inability to match both grid point variances and topdown continental uncertainty estimates seems to indicate the assumed correlation model is oversimplified, and should be examined more carefully. (Wilson, 2006; Heroux & Willenbring, 2009; Heaton & Carver, 2015) ; the tests for this package can be run from the root directory using python setup. py test or tox. The new LPDM postprocessing software, written in IDL and python, is available on GitHub through the PSU-Inversion organization at https://github. com/psu-inversion/ LPDM-postprocessing c1 under a three-clause BSD license  (Morin et al. , 2012). The influence functions used in this study are made available through the PSU DataCommons  (Wesloh & Lauvaux, 2019).
Acknowledgments Many thanks to  Sha Feng  and  Klaus Keller  for extensive feedback improving the focus and presentation of the figures. Plots were generated using Matplotlib, Cartopy, and XArray on Python 3. 6. 4,with coastlines and borders using Natural Earth data (Hunter, 2007; Met Office, 2010-2015; Hoyer & Hamman , 2017;van Rossum, 1995). Extensive use was made of  Numpy and Scipy  for the low-level arithmetic and linear algebra, and of FFTW via pyFFTW for Fourier transforms (Oliphant, 2006b;Jones et al. , 2001-; Virtanen et al. , 2019;Gomersall et al. , 2016; Frigo & Johnson ,  2018 ,  2005 ). The WRF simulation is available at Lauvaux and Butler (2016). The baseline fluxes were obtained from the prior biological fluxes of  CMS-Flux  (Liu et al. , 2014) and are available as NASA Carbon Monitoring System (2013).
This work was funded by the  NASA   ACT-America project , the  Gulf Coast Intensive (GCI)  project, the  Dr. Dennis W. and  Dr. Joan S. Thomson   Distinguished Graduate Fellowship , and the  Anne C. Wilson Graduate Fellowship. ACT -America project is a NASA Earth Venture Suborbital 2  project funded by  NASA's Earth Science Division , Grant  NNX15AG76G  to  Penn State. The GCI was supported by  NASA   Terrestrial Carbon Cycle program , Grant  NNX14AJ17G. (2010,  11 ). Atmospheric inversions for estimating CO 2 fluxes: methods and perspectives. Climatic Change ,  103  ( 1-2 ),  69-92. doi: -24-manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES).
It involves the Bqt1-2 meiotic telomere adaptor that connects the Taz1-Rap1 telomere protein to the Sad1 SUN domain protein in a complex with the INM proteins Btq3-4,  [25] [26] [27] [28] [29]  (Fig. 1b-c ). No protein sequence similarity between these yeast telomere adaptor proteins and those of mice has been, detected, however. The high divergence between yeast and mouse telomere adaptor proteins makes it unclear how conserved are the mechanisms mediating the dynamic anchoring of meiotic telomeres to the NE. To probe the origin of the murine TERB1-TERB2-MAJIN complex, we used computational methods to identify their putative orthologs in public databases and subjected candidates to expression studies. Our results indicate that the TERB1-TERB2-MAJIN complex is evolutionarily ancient and that dates back to the common ancestor of metazoans.
TERB1, TERB2, and MAJIN are ancestral metazoans proteins To identify candidate TERB1, TERB2 and MAJIN homologs in other taxa, we carried out a bioinformatic screen of public sequence databases using PSI-BLAST  [30]. Our survey of public sequence databases identified homologs of the mouse meiotic telomere complex proteins TERB1, TERB2, and MAJIN mainly in metazoans (Supplementary Information, Table  S1 , S2 S3, and S4). Most sequences were obtained from Deuterostomes and especially in the Vertebrata, but candidates were also readily identified in Cephalochordata, Echinodermata, and Hemichordata. Beside the Deuterostomes, homologs were also detected in the Lophotrochozoa principally Mollusca, Annelida, and Brachiopoda. Only a few putative homologs were found among Ecdysozoans in the Priapulida and Arthropoda clades.
Data mining The non-redundant protein database from the NCBI (https://www. ncbi. nlm. nih. gov/) was used to retrieve homologs of mice TERB1 (NP_851289), TERB2 (NP_ 083190), and MAJIN (NP_001159391) using PSI-BLAST (options: substitution matrix = BLOSUM45, word size = 3)  [30]. Iterations were repeated for newly detected homolog sequences until convergence. Genomic sequences available at the NCBI (e. g. genome, est. , tsa) and ensembl databases, were checked with the TBLASTN algorithm using the BLOSUM45 matrix. All retrieved sequences were used for reciprocal BLAST tests to ensure that they represented putative homologues of TERB1, TERB2, and MAJIN proteins and not false positives. Hydra vulgaris TERB1, TERB2, and MAJIN sequences obtained from this study (see below) were included in the analysis.
Sequence alignment and phylogenetic tree construction The retrieved sequences were aligned using PROMALS3D  [47]  which takes into account data from structural information for better understanding of sequence-structurefunction relationships in distant homologues. Available structures from the Protein Data Bank (PDB)  [48]  for TERB1 (: 1x58_chainA and 6j07_chainB), TERB2 (6j07_ chainA) and MAJIN (6j08_chainA) were uploaded in PRO-MALS3D. Annotations of the sequence alignment were designed using ESPript3  [49]. Protein motifs and functional domains were examined through the Eukaryotic Linear Motif (ELM) (http://elm. eu. org/index. html) [50]  and Superfamily web server (http://supfam. org/) [51]  respectively. For phylogenetic analyses, we selected a taxonomically balanced subset of homologous sequences which represent a wide range of animal phyla (Supplementary Information, Table  S1 , Table  S3 , and Table  S4 ).
The sequences were aligned with MAFFT v7. 309 with the accurate option L-INS-I. The resulting multiple alignments were trimmed with BMGE ("Block Mapping and Gathering with Entropy" software) v. 1. 12 (option -m BLOSUME45)  [52]. A Bayesian tree was computed with MrBayes v3. 2. 6  [53]  with a mixed model of amino acid substitution including a gamma distribution (4 discrete categories) MrBayes was run with four chains for 1 million generations and trees were sampled every 100 generations. To construct the consensus tree, the first 2000 trees were discarded as "burn in". The final trees were drawn with iToL v4  [54].
The cDNA amplification was performed with Phusion polymerase (Thermo-Fisher). PCR products were visualized on 1% agarose gel (peqLab) to verify size (Supplementary Information, Fig. S7 ), purified with a NucleoSpin Gel and PCR Clean-up Kit (Macherey-Nagel) and inserted into the pSC-A-amp/kan plasmid using a StrataClone PCR Cloning Kit (Agilent Technologies). The plasmids were purified using a NucleoSpin® Plasmid kit (Macherey-Nagel) kit and verified by automated sequencing. To verify the obtained full-length or nearly full-length of cDNA, single read sequences from independent cloning were compared with the transcript reference sequence. The expression studies were performed by RT-PCR using an intron spanning primer set (Supplementary Information, Table  S5 ) designed the genomic annotations of Hydra vulgaris, TERB1 (Genbank ID: NW_ 004171015), TERB2 (Genbank ID: NW_0041710153) and MAJIN (Genbank ID: NW_004173123).
Acknowledgements We especially thank the  DAAD (Germany)  for granting I. d. C's  PhD fellowship  and  DFG  grant  Be1168/8-1  to  R. B  for supporting this study. We also thank  Thomas Bosch  (Kiel) and his group for their support by providing Hydra cultures,  Manfred Alsheimer  (Würzburg) and  José Sotelo-Silveira  ( Montevideo ) for generous advice with the experimental design and for helpful discussions,  Elisabeth Meyer-Natus  ( Würzburg ) for excellent technical assistance,  Isabell Köblitz  ( Würzburg ) for advice with in situ hybridization techniques,  Elena Bencurova  and  Brooke Morriswood  ( Würzburg ) for critical reading of the manuscript.
Sample We tested the theoretical model empirically using a sample composed of the 100 firms from Actualidad Economica's "Great Place to Work 2015" database. Actualidad Economica (http://www. actualidadeconomica. com/) is a top business magazine that provides several databases every year with information on "sales, innovation effort, employer brand value, and executive compensation for the most admired firms in Spain"  (Benitez et al. , 2018d, p. 512 ). These databases have been used in prior IS research (e. g. ,  Benitez & Walczuch, 2012)  Conversely, 83% of users in Spain interact with firms via social media (IAB Spain, 2017).
Social media capability Social media capability was operationalized as a composite second-order construct composed of three dimensions (Facebook capability, Twitter capability, and blog capability  [Benitez et al. , 2018a; Culnan et al. , 2010] ) using data collected in 2015, and as composite at first-order level  (Benitez et al. , forthcoming; Henseler et al. , 2016). We measured social media capability based on the validated measurement scheme developed by  Benitez et al. (2018a)  and  Braojos et al. (2019). We thus measured Facebook capability as a composite first-order construct built from number of events (both past and future), experience, and updates with data gathered from the Facebook profile of the firm. We measured Facebook experience by average number of months the firm had had presence on this social platform.
Updates were measured with scores from "1: Low" to "5: High" level of content updating on the Facebook page, assigning the firm a value of 1 if it had commented on Facebook more than one month ago, 2 if in the last month, 3 if two weeks ago, 4 if in the last week, and 5 if in the last two days  (Benitez et al. , 2018a; Braojos et al. , 2019). We measured Twitter capability as a composite first-order construct through time spent posting tweets, experience, and updates using information collected from firm's Twitter site and the Twopcharts database (http://twopcharts. com/). Time spent posting tweets was measured as the average number of hours the firm spent posting tweets. The other two indicators (i. e. , experience and updates) were measured following the process used for the Facebook capability indicators on experience and updates  (Benitez et al.
, 2018a). Blog capability is a composite first-order construct determined by firm's experience and updates on its corporate blogs  (Braojos et al. , 2019). Blog experience and updates were assessed following the same process as Facebook and Twitter, using data gathered from the firm's blog site(s). Social media capability indicates the firm's proficiency in selecting, using, and leveraging Facebook, Twitter, and corporate blogs to implement business activities  (Benitez et al. , 2018a; Braojos et al. , 2019). Our measures of social media capability have been proposed and validated in prior IS research  (Benitez et al. , 2018a; Braojos et al. , 2019) , and are consistent with conceptualization of social media capability. Facebook, Twitter, and blogs are three very important external social media that companies use and leverage for implementing business initiatives  (Culnan et al.
Control variables We controlled for the following variables: firm size, industry, firm age, and advertising spending on employer reputation. Since larger firms are more likely to have more financial resources to invest in employer reputation activities  (Fombrun & Shanley, 1990) , employer reputation may depend on firm size. Because larger firms tend to be better known, their practices usually also have higher impact and spread faster in society. Thus, best-in-class human resources management practices tend to be more developed and to have a higher impact on employer reputation in large firms than in small ones. We therefore controlled for firm size in employer reputation, computing firm size as the natural logarithm of number of employees per firm  (Benitez & Walczuch, 2012) , using information collected in 2015 from the COMPUSTAT database.
Corporate blog We also controlled for industry on employer reputation, measured through a dummy variable where 0 corresponds to "Manufacturing firm", and 1 to "Service firm"  (Liu et al. , 2013) , using data gathered from the firm's website. We controlled for firm age on employer reputation. Older firms have more experience designing, executing, and leveraging human resources management practices to build employer reputation than do younger firms, and time and experience can be critical in building trust and reliability among firms and their environment  (Rhee & Valdez, 2009). Firm age was measured as the natural logarithm of the number of years the firm had operated in its industry in 2015  (Thornhill & Amit, 2003) , using data collected from the SABI (https://sabi. bvdinfo. com/) database, which provides information on financial characteristics of Spanish and Portuguese firms  (Benitez et al.
Empirical analysis and results To test the research model, we ran partial least squares (PLS) path modeling  (Ringle et al. , 2012)  with the statistical software "ADANCO 2. 0. Professional" for Windows (http://www. composite-modeling. com)  (Henseler & Dijkstra, 2015). PLS is suitable in this research primarily for the following reasons. First, PLS is a "full-fledged" structural equation modeling (SEM) approach appropriate for testing exact model fit in both confirmatory and explanatory research  (Benitez et al. , forthcoming; Hair et al. , 2012; Henseler et al. , 2016). Second, since all constructs were specified as composite, PLS is optimal in that it produces consistent estimations of composite models  (Henseler et al. , 2014; Rigdon et al. , 2014). Third, PLS obtains more accurate results when evaluating complex models than do covariance-based SEM techniques  (Ajamieh et al.
Robustness test Our findings may be biased by the time chosen to measure the study constructs  (Braojos et al. , 2019). To test the robustness of time selection, we estimated an additional model (see Figure  2  and Table  4 ). Since we measured employer reputation through a construct composed of the natural logarithm of the firm's score for employer reputation in  2015, 2016, 2017, and 2018 , we collected information from the Actualidad Economica database during these years. This robustness test confirms that the empirical analysis supports our theory. We also repeated the comparative sub-group analysis from subsection 4. 4. (social media vs. advertising spending) with a composite for employer reputation for the years 2015-2018. The difference between the beta coefficient for firms with less-developed social media capability (β = -0.
CSR activities construct was measured as the natural logarithm of the firm's score of CSR activities, with information collected from the "Monitor Empresarial de Reputacion Corporativa" (MERCO) database (http://www. merco. info/es/) in 2014. MERCO is one of the best-known databases and tools worldwide to evaluate the reputation of Spanish and Latin American firms based on a multi-source , chief communication officers, and CSR experts). Our unique manipulation was to estimate the natural logarithm of the CSR activities score. The construct CSR activities refers to the social, environmental, ethical, and philanthropic activities performed voluntarily by the firm. We measure CSR activities through natural logarithm of each firm's score for CSR activities from MERCO database. The MERCO database determines this score by evaluating employee relations (social activity), ethical commitment, transparency, and good governance (ethical activities), environmental and climate change commitment (environmental activities), and community contribution (philanthropic activities) for each firm.
Conceptualization and measurement of the construct CSR activities thus align well. 1 Employer reputation is the key endogenous variable in the proposed model. It is a single-measure construct calculated as the natural logarithm of the firm's score for employer reputation, collected from the Actualidad Economica database in 2015. Because CSR activities can take time to affect employer reputation, we lagged the measure for CSR activities one year. 2The Actualidad Economica database includes the 100 best firms in which to work in Spain in 2015, based on a fine-grained examination of overall employer reputation for each firm. The database assigns the firm an employer reputation score ranging from 0 to 1000, determined by examining compensation, talent management, work environment,.
Joshi et al. , 2010). We used convenience sampling due to the rich data available. The firms in the sample averaged 84164 employees [standard deviation (S. D. ) = 111768. 020]. As a context of study, Spain is particularly interesting because Spanish companies have a high maturity level and social media usage. In 2017, 49. 6% Spanish firms used social media for business activities. Specifically, 94. 4% firms used Facebook or LinkedIn, and 40. 6% microblogs (e. g. , Twitter) and corporate blogs(INE, 2017). Social media included in reputable rankings like the one employed in the present study (Benitez & Walczuch, 2012; Firm size Bharadwaj, 2000; capability CV H2 (+) CV Industry CSR Employer activities H1 (+) reputation CV Firm age CV Advertising spending firms included in the Actualidad Economica database were used in this study.
The firms come from 19 different industries: food (14, 14%), IT (14, 14%), insurance (12, 12%), consulting (11, 11%), energy (9, 9%), finance (9, 9%), pharmaceuticals (6, 6%), tourism and transport (5, 5%), and others (11 industries). Actualidad Economica's "Great Place to Work 2015" database (hereafter, the Actualidad Economica database) includes the 100 best firms in which to work in Spain in 2015, based on fine-grained evaluation conducted by independent human resources experts and consultants. This evaluation was based on a survey and multiple interviews that measured and evaluated compensation, talent management, work environment, training, and employee opinion for each firm. All (20, 20%). The firms in the sample had more than 100 employees and had run the business for at least five years in Spain.
Conceptualization and measurement of the construct CSR activities thus align well. 1 Employer reputation is the key endogenous variable in the proposed model. It is a single-measure construct calculated as the natural logarithm of the firm's score for employer reputation, collected from the Actualidad Economica database in 2015. Because CSR activities can take time to affect employer reputation, we lagged the measure for CSR activities one year. 2The Actualidad Economica database includes the 100 best firms in which to work in Spain in 2015, based on a fine-grained examination of overall employer reputation for each firm. The database assigns the firm an employer reputation score ranging from 0 to 1000, determined by examining compensation, talent management, work environment, 3. 2. 3. Employer reputation Tang et al.
(2018)ed of 5 evaluations and 12 information sources. This database assigns CSR activities scores from 1 to 10000 based on careful examination of CSR activities in the firm. The MERCO database adopts a multidimensional approach, constructing the CSR activities score from five dimensions: ethical commitment, transparency and good governance, employee relations, commitment to environmental and climate change, and community contribution. Our measure of CSR activities is consistent with that used byLee et al. (2013)andTang et al. (2018), which has seven domains: "community, corporate governance, diversity, employee relations, environment, human rights, and product"(Lee et al. , 2013, p. 797). MERCO includes information from a large number of firm stakeholders (steering committees, financial analysts, non-governmental organization agents, union members, customer association members, business and IT professorstraining, and employee opinion.
Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors.