dataesr/scientific-paragraphs-categorization huggingface dataset:
MODELS OF THE 2MM UNIVERSE We make use of several cosmological semi-empirical and empirical models of the 2 mm-luminous Universe to draw comparisons with the MORA dataset. A brief description of each model dataset follows. First, we compare to the Simulated Infrared Dusty Extragalatic Sky (SIDES) model  (Bethermin et al. 2017) , which builds galaxies' SEDs from their stellar masses and star formation rates (assuming a bimodal population of main sequence galaxies and starbursts) and which updates the 2SFM (2 Star Formation Modes) galaxy evolution model  (Béthermin et al. 2012; Sargent et al. 2012)  to analyze the impact of clustering on IR map analysis. The 2SFM model posits that there is a bimodal population of star forming galaxies: those that are on the main sequence and starbursts that have elevated specific star formation rates; the 2SFM model uses this framework to model all galaxies.
We make use of the full SIDES 2 deg 2 lightcone in our analysis, both to sample cosmic variance and understand possible trends for 2 mm-selected galaxies on angular scales larger than the MORA survey. Second, we compare our results to the Shark semianalytic model of galaxy formation  (Lagos et al. 2018). By using the SED code ProSpect  (Robotham et al. 2020)   12  and the radiative transfer analysis of the EA-GLE hydrodynamical simulations of  Trayford et al. (2020) , the Shark model was successfully able to predict the ultraviolet to far-infrared emission of galaxies over a wide range assuming a universal IMF  (Lagos et al. 2019)   13. Lagos et al. (2020)  presents detailed predictions for the (sub-)millimeter galaxy population, including 2 mm number counts and redshift distributions. We make use of the full 108 deg 2 Shark lightcone for our comparisons.
The 'dust poor' Universe effectively translates to a very minor contribution of intense, dusty starbursts to cosmic star formation beyond z > ∼ 5 (<10%), while they would dominate cosmic star formation at similar epochs in the 'dust rich' Universe (>90%). These models are built to capture two extremes. Zavala et al. (2018a)  uses 3 mm number counts from the ALMA archive to argue for a solution between these two extremes. Our accompanying paper,  Zavala et al. (2021)  presents an update to  Zavala et al. (2018a)  using MORA 2 mm number counts, updated 3 mm archival counts, as well as deep 1 mm number counts from the ASPECS survey  (Aravena et al. 2020; González-López et al. 2019 , 2020). The expanded dataset used to constrain the model in  Zavala et al. (2021)  relative to  Zavala et al. (2018a)  has resulted in a change of the predicted z > ∼ 2 evolution of Φ , the number density of DSFGs at early times, from Φ ∝ (1 + z) -4.
The median redshift of 2 mm-selected galaxies has been measured twice before in the literature, using the GISMO instrument on the single-dish IRAM 30 m telescope. Staguhn et al. (2014)  measure a median redshift of z 2mm = 2. 9 ± 0. 9 for sources in the GISMO Deep Field in GOODS-N while  Magnelli et al. (2019)  measure a median redshift of z ∼ 4, though only for five sources and four sources respectively with S/N>4. Both are in agreement with our measured median redshift of z 2mm = 3. 6 +0. 4  -0. 3. Figure  5  also shows the predicted cumulative redshift distributions for the MORA dataset from several models in the literature, described in § 4. For all models, we have generated the cumulative redshift distribution by sampling simulations over the 184 arcmin 2 area of the MORA survey. Some of the models have been simulated over larger areas (e.
g. Shark, SIDES, and UniverseMachine) while the  Casey et. al. and Zavala et. al. empirical models have multiple realizations the same size of the MORA survey. Sources in each model dataset then have an RMS noise assigned to them following the heterogeneous distribution of RMS noise in the MORA maps to best mimic the data. We retain simulated sources that were detected at or above 5σ significance. Sources in these simulations are assumed to be point sources, as the probability of them being spatially resolved on scales larger than 1. 5≈10 kpc is unlikely at these redshifts. This procedure is repeated 1000 times to constrain the uncertainties in the total number of selected sources and their redshift distribution. The   5  shows four models, one of which is the updated empirical model from our accompanying paper, Z21.
Contribution to the SFRD The question of DSFGs' contribution to the cosmic star-formation rate density at early times has been difficult to constrain. However, the MORA Survey's design is meant to effectively filter out lower redshift DSFGs, enabling direct measurement of the obscured galaxy contribution to the SFRD. For example, the contrast between a "dust poor" universe (e. g. Koprowski et al. 2017; Dudzevičiūtė et al. 2020 ) and a "dust rich" universe  (Rowan-Robinson et al. 2016; Gruppioni et al. 2020)  would result in very different manifestations of the MORA dataset; the former predicts < ∼ 15 sources with median redshift z ∼ 3. 4, and the latter predicts > ∼ 50 sources with a median redshift of z ∼ 5. 4. So what does our dataset imply for the SFRD? We provide direct estimates of the MORA sample's contribution to cosmic star-formation in Figure  12.
It is an effective, and observationally cheap filter through which needles (z > 4 DSFGs) can be spotted in the haystack (dominated by 1 < z < 3 DSFGs), complementing 2 mm blank field surveys like MORA. Lastly, extentions of MORA stand to make significant progress; over the next year, MORA is approved for observations to expand coverage over 0. 2 deg 2 (within the COSMOS-Webb survey footprinto) to the same depth of our current mosaics. These data will likely lead to the discovery of ∼20 DSFGs at z > 4 and enable more detailed studies of DSFG clustering.
Furthermore, the extrapolated characteristics of MORA DSFGs' descendants are also well aligned with detected quiescent populations, all well established with stellar masses >10 11 M above z > 2. 6. Our MORA data hints at a possible higher value for the galaxy-integrated dust emissivity index, β, than is often assumed in the literature: the sample has a measured β = 2. 2 +0. 5 -0. 4 vs β = 1. 8. We recommend future works modeling SEDs of high-z DSFGs adopt a value of β ≈ 2 as needed in lieu of direct constraints. The final frontier of this work would lead to the detection of the Universe's first dusty galaxies, the home of the Universe's first substantial dust reservoirs. Do such systems exist beyond z > 7? z > 8? While MORA has taken a tantalizing first step in completing the census of high-z DSFGs, we know higher redshift DSFGs (specifically, three with SFR > ∼ 100 M yr -1 ) do exist than are found in this work (e.
In addition, CMC acknowledges support from the  Research Corporation for Science Advancement  from a 2019  Cottrell Scholar Award  sponsored by  IF/THEN , an initiative of  Lyda Hill Philanthropies. The  Flatiron Institute  is supported by the  Simons Foundation. MT acknowledges the support from grant  PRIN MIUR 2017. ET acknowledges support from  CATA-Basal   AFB-170002 ,  FONDECYT Regular  grant  1190818 ,  ANID  Anillo  ACT172033  and  Millennium Nucleus   NCN19 058  (TITANs). MA acknowledges support from  FONDE-CYT  grant  1211951 , " CONICYT+PCI+INSTITUTO MAX PLANCK DE ASTRONOMIA MPG 190030 " and " CONICYT+PCI+REDES 190194. "The Cosmic Dawn Center (DAWN) is funded by the  Danish National Research Foundation  under grant No. 140. ST and JW acknowledge support from the  European Research Council (ERC)   Consolidator Grant funding scheme  (project  ConTExt , grant No.
We note that alternate band 4 ALMA spectral line observations of MORA-1 exist under the source name 'GalD' in program 2018. 1. 01824. S; however, the tuning would only capture CO(6-5) from redshifts z = 3. 65 -3. 77 and z = 4. 06 -4. 20. No CO line is detected in the dataset to a depth of 1σ ∼0. 4 mJy/beam in 100 km/s channels.
Curve-based intra-frame prediction The core contribution of this work is a novel approach to compute intra-frame predicted blocks. Each sample in a predicted block is subject to a displacement operation, based on the sample position together with a curve-offset. The idea is to offer a refined prediction model that can represent additional texture characteristics. Our model was inserted in the HEVC reference software for evaluation, extending the HEVC intra-frame predictor with additional modes. Eqs. (  5 )-(  10 )  [34]  demonstrate how HEVC computes samples for vertical and horizontal angular prediction modes. Eq. (  5 ) and Eq. (  8 ) perform linear interpolation using the two closest reference samples in the prediction direction to compute samples  for vertical and horizontal modes, respectively.
With  = 32, 45. 34% and 54. 66% of the samples are non-curved and curved modes, respectively. For  = 2, 66 additional angular modes are available, and these modes are used to encode 25. 95% of the samples. The number of encoded samples for different  values is shown in Fig. 7 , considering the results for the Random-Access configuration and samples encoded with Planar and DC modes. The addition of angular modes with curves causes a reduction in the utilization of conventional HEVC intra-frame prediction modes, more prominently for the angular modes. Fig. 7  illustrates that the use of curved modes grows quickly for low values of , and when  > 8, the use of additional curves offers little additional benefits. It is important to emphasize that Planar and DC indicate individual modes, where Angular and Curved indicate a group of modes.
Comparison with state-of-the-art We compare our results for  ≤ 8 with state-of-the-art regarding improvements to HEVC intra-frame prediction since our method was evaluated using this standard as the baseline. We analyzed the works of  [31] , which employed HM 16. 9, for MRL and its Fast variant (MRL Fast), along with Chen's improved intra-prediction encoding  [28] , which employed HM 12. 0. The difference in terms of HM software versions does not allow a totally precise comparison, but this comparison is still possible, since all works are using the CTCs and all HM versions implement the same intra-prediction tools. Table  5  shows the experimental results of our work and the state-of-the-art. Although we would like to compare our model for both coding configurations, the related works only provided results regarding All-Intra-8, while the Random-Access results are absent.
Conclusion and future work This article presented a novel sample displacement model for intraframe prediction in current and future video coding standards. Our model enables a PU to represent curved textures instead of typical straight lines, offering better prediction quality with lowered residual energy. We implemented our proposal inside the HEVC reference software as a new set of intra-frame prediction modes to be applied together with the default angular modes. The experiments unveiled that the new curved modes increased the encoding efficiency, especially when All-Intra-8 and All-Intra-10 configurations are considered. The use of a low amount of curve displacements offers a good trade-off in BD-Rate gains versus the encoding complexity required by our method, with  ≤ 6 offering the most promising results.
Locus see Table  1  for details). Two of these were not significantly associated with any other aortic traits: rs6724315 in PRKCE and rs10857614 in ARHGAP22. , NES= 0. 58), providing additional evidence for its biological relevance. We compared our association results for aortic areas with those reported for aortic diameters in recent preprints  30, 31  based on the same UK Biobank imaging dataset, but using different methods and metrics for aortic dimensions. We replicated 73 of the previously reported genome-wide significant association loci and added associations for two clinically relevant phenotypes (ascending and descending aortic distensibility) to identify a further 31 novel associations. Only four of the previously reported SNPs did not replicate. Inspection of the loci for SNPs that were significant in the analysis by Pirruccello et al  30  , but not in our own, generally showed SNP p-value signals near the genome-wide significance threshold (p<5x10  -8  ) in our analysis.
Data The UK Biobank cardiac magnetic resonance imaging (CMR) was conducted using a rigorously controlled acquisition protocol  76. The mean age at the time of CMR was 64 ± 8 years (range 45-82, 49% of participants were male). Exclusion criteria for imaging included a range of relative contraindications to magnetic resonance imaging scanning as well as childhood onset disease and pregnancy. Aortic cine images were acquired using transverse bSSFP sequence at the level of the pulmonary trunk and right pulmonary artery on clinical wide bore 1. 5 Tesla scanners (MAGNETOM Aera, Syngo Platform VD13A, Siemens Healthcare). Each cine image sequence consists of 100 time frames. The typical image size is 240x196 pixel with the spatial resolution of 1. 6x1. 6 mm 2. Brachial blood pressure was obtained using a manual sphygmomanometer and converted into central blood pressure for the distensibility calculations by applying a brachial-toaortic transfer function using the Vicorder software  76.
Genomic analyses We performed stage 1 GWAS on six imaging phenotypes (AAmax, AAmin, DAmax, DAmin, AAdis and DAdis). Outliers with phenotype values >4 standard deviations (SDs) from the mean were excluded to ensure we did not include patients with undiagnosed aortic aneurysm in our results. After exclusions for image quality control, outlying BMI (<15 or >40), stage IV hypertension, missing covariates, diagnosis of aortic disease and non-white ethnicity, 4,406 participants were excluded leaving 32,590 individuals for the GWAS of AAmax, AAmin, DAmax, and DAmin, and 29,895 for the GWAS of AAdis and DAdis (the latter figure is lower due to more missing contemporaneous blood pressure recording data and incomplete imaging sets). See Supplementary Figure  S1  for more details on exclusions. After exclusions, we rank-normalised the distensibility phenotypes due to the non-normal distribution of the distensibility phenotypes (Supplementary Figure  S2 ).
Finally, proximal LD blocks of independent significant SNPs with less than 250kb distance were merged and considered as a single genomic locus. To consolidate genomic loci across different traits, the merge function implemented in bedtools was applied  79. For the association of SNPs with genes, biological processes and tissue expression, we applied the SNP2GENE function implemented in FUMA to the summary SNP statistics. For the positional mapping of SNPs to genes, a maximal distance of 10kB was set. eQTL mapping was performed based on the aorta tissue samples in GTEx v8 using only gene pairs with significant SNPs (with the default settings of FDR < 0. 05 or p value < 1e -3 ). 3D chromatin interaction mapping was based on HiC aorta data (GSE87112) within a promotor region window of 250bp upstream and 500bp downstream from the transcriptional start site and a threshold for significant loops of FDR < 1e -6.
Enhancer and promotor regions were annotated using the aorta epigenome (E065) from the Roadmap Epigenome Project (http://www. roadmapepigenomics. org/). MAGMA (Multi-marker Analysis of GenoMic Annotation) was employed to obtain the significance of individual genes with the specificity of tissue expression based on 54 types in GTEx v8 and the association with 10,678 gene sets from MsigDB v6. 2 (with 4761 curated gene sets and 5917 GO categories). Further annotation of significant SNPs and loci was performed manually with SNP lookups in GTEx v8  29  ; normalised effect sizes are reported from this dataset using "Artery-Aorta" for the main analysis and including other arterial tissue types ("Artery -Tibial" and "Artery -Coronary") where stated. For Gene Ontology (GO) enrichment analysis, the Data-driven Expression Prioritized Integration for Complex Traits (DEPICT) software was applied (v1 beta rel194, www.
broadinstitute. org/depict), which is based on probabilistic memberships of genes across reconstituted gene sets  80  For LDbased clumping by PLINK  81  , which precedes the DEPICT analysis, a p-value threshold of 10 -5 , a distance threshold of 500kb and a LD threshold of 0. 1 was set (following the recommendations on the DEPICT website). Note that DEPICT excludes any SNPs in the HLA region, on a sex chromosome, or not found in the 1000 Genomes Project data. Comparisons between our data and those reported by Pirruccello et al  30. and Tcheandjieu et al  31  were made using the lead SNPs and corresponding beta-values. To assess the degree of convergence of their studies with our results, lead SNPs were assigned to a genomic locus found in our study if they were within the locus or a 250kb distance interval.
Co-expression analysis Co-expression networks for aortic phenotypes were derived using a single cell RNA-seq (scRNAseq) data set for primate arteries  34. The data were obtained from Gene Expression Omnibus (accession number GSE117715) and included read counts for over 9000 single cells from aortas and coronary arteries of 16 Macaca fascicularis. Low abundance genes were removed if they had read counts of less than 5% of the cells, leaving a total of 9903 genes for further analysis. The Bioconductor package scater was applied to compute log-transformed normalised expression values from the count matrix  83. Subsequently, correlation of expression and its significance was derived using the correlatePairs function of the Bioconductor scran package, which calculated modified Spearman correlation coefficients and derived their significance using a permutation approach  84.
A basal co-expression network was constructed using gene pairs with significant correlation (FDR < 0. 01) and a minimum Spearman correlation coefficient rho of 0. 1 or 0. 2. Subsequently, subnetworks for imaging phenotypes were derived by retrieving gene pairs with at least one gene associated by MAGMA or FUMA with the specific phenotype. Functional enrichment of genes connected with variants identified on GWAS was carried out using overrepresentation enrichment analysis implemented in the Bioconductor clusterProfiler package  85. The background gene set (or universe) was defined by the genes covered by the scRNA-seq data after exclusion of low abundance genes.
In addition to IVW, WM, and MR-Egger, we implemented R package RadialMR (available through CRAN repositories)  91. A p-value < 0. 01 correcting for 6 tests (for the 6 aortic traits) was considered significant. In the presence of heterogeneity (PHet<0. 01, Cochran's Q statistic) due to horizontal pleiotropy, RadialMR was used in the identification of pleiotropic SNPs that have the largest contribution to the global Cochran's Q statistic by regressing the predicted causal estimate against the inverse variance weights. After excluding influential outlier SNPs, the IVW test was repeated along with MR-Egger regression in which the regression model contains the intercept term representing any residual pleiotropic effect  92. Non-significant MR-Egger intercept was used as an indicator to formally rule out horizontal pleiotropy.
MR phenome-wide association studies (MR-PheWAS) We performed an MR-PheWAS using data from UK Biobank participants who did not undergo aortic imaging to assess the effects of aortic traits on clinical disease classifications. Using the PheWAS package (https://github. com/PheWAS/PheWAS), we mapped 1,157 phecodes with more than 200 cases from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM). 94 For each aortic imaging phenotype, we selected SNPs with a p-value<5×10 -8 and minor allele frequency > 0. 05 from the single trait GWAS for AAmax, AAmin, DAmax, and DAmin, and from the multi trait GWAS for AAdis and DAdis. Given that we considered a large number of phecodes as the outcome in the MR-PheWAS analysis with the number of cases ranging from 201 to 116,879 (median=1,353), we used a more stringent LD threshold for independent SNPs (r 2 <0.
ACKNOWLEDGEMENTS PMM acknowledges generous personal and research support from the  Edmond J Safra Foundation and Lily Safra , a  National Institute for Health Research (NIHR) Senior Investigator Award , the  UK Dementia Research Institute  and the  NIHR Biomedical Research Centre at Imperial College London. CF acknowledges generous support from the  BHF Imperial Centre of Research Excellence   RE/18/4/34215. This research has been conducted using the UK Biobank Resource under Application Number  18545. PE is director of the  Medical Research Council (MRC) Centre for Environment and Health  and acknowledges support from the  MRC  ( MR/L01341X/1 ;  MR/ S019669/1 ). PE is director of the  Health Protection Research Unit in Chemical and Radiation Threats and Hazards , funded by the  NIHR. PE also acknowledges support from the  NIHR Imperial Biomedical Research Centre , the  Imperial College British Heart Foundation Centre for Research Excellence  ( RE/18/4/34215 ), the  UK Dementia Research Institute at Imperial College London  ( MC_PC_17114 ), and  Health Data Research UK for London.
ALLOZITHRO trial: Bayesian sequential analyses The ALLOZITHRO trial (NCT01959100) was a multicenter doubleblind placebo-controlled randomized phase 3 trial, which aimed to evaluate the efficacy of azithromycin in the prevention of airflow decline in patients after hematopoietic stem cell transplant (HSCT)  [13]. Bronchiolitis obliterans syndrome, which results in airflow decline and respiratory function impairment is a known complication of HSCT, related to chronic graft-versus-host disease (GvHD). The trial randomized 465 patients, 231 in the azithromycin arm and 234 in the placebo arm, between February 2014 and August 2015. The primary endpoint was airflow-decline free (AFD-free) survival at 24 months after randomization as the time from randomization to decline in the respiratory function or death of any cause.
Respiratory function was assessed every 6 months, by plethysmography (with preand post-bronchodilator spirometry). Observations were censored at the date of last follow-up, in patients without events. It was expected that azithromycin would have a protective effect on the respiratory function and therefore an improved AFD-free survival, resulting in a postulated log () = log (0. 64) under the alternative, assuming a constant effect over the follow-up (that is, proportional hazards (PH)). Unexpectedly, the trial was terminated prematurely on December 26, 2016 after the trial Data Safety Monitoring Board (DSMB) alerted on an imbalance in the number of hematological relapses across randomization arms  [13]. At that time, enrollment was complete but treatment and follow-up were still on-going for 122 patients.
CLL7-SA trial: Incorporating historical data The CLL7-SA trial (NCT00645606) was a multicenter randomized open-label phase 3 trial that was conducted to evaluate the efficacy of 2-year rituximab (RTX) maintenance therapy in elderly patients with previously untreated chronic lymphocytic leukemia (CLL), compared to standard of care (SoC) observation (watchful waiting)  [14]. The primary endpoint was progression free survival (PFS). Assuming a 32% relative improvement with RTX in the 36-month PFS (66% vs. 50%,  = 0. 6), a sample size of 161 events from 542 patients, accounting for 25% drop-out rate during the induction part of the CLL therapy, was computed according to the O'Brien and Fleming design. One interim analysis was planned, after 121 events (75% of 161) had been observed. The inclusion period started on June 10, 2008, and ended on August 14, 2014.