dataesr/scientific-paragraphs-categorization huggingface dataset:
NIRCam WFSS Data Reduction We used the CALWEBB stage 1 pipeline to calibrate the detector-level signals and ramp fitting for individual NIRCam WFSS exposures. After this step, we subtracted the 1/f noise pattern using the same routines that are used for the NIRCAM direct image processing, but we only subtracted the stripes along columns, since the spectra are dispersed along rows for grism R. We then performed flat-fielding of the WFSS exposures using direct imaging flat reference files, since the WFSS flat reference files are not available. We also assigned WCS information for individual files based on the distortion reference files in CRDS using the assign_wcs routine in the CALWEBB pipeline. We measured astrometric offsets between each of the SW images (i. e. , the exposures taken simultaneously with WFSS exposures) and the fully calibrated F356W-band mosaic.
The measured offsets were applied to the spectral tracing model in a later stage when tracing objects. All further data processing steps after this stage were performed using our custom scripts as detailed below. In the standard CALWEBB pipeline, the WFSS background subtraction is performed by scaling the theoretical background to that observed in each individual integration. However, the accuracy of the theoretical background has not been fully characterized because of limited existing in-flight calibrations. To resolve this issue, we constructed median background models based on all ASPIRE observations obtained at similar times, which were scaled and subtracted from individual WFSS exposures. Before extracting spectra from WFSS observations, we need to construct the spectral tracing models, dispersion models, and sensitivity functions.
For the second version, we first extracted 2D spectra for each source from each individual exposure and then stacked the 2D spectra after registering them to a common wavelength and spatial grid following the histogram2D technique implemented in the PypeIt software  (Prochaska et al. 2020 ) to avoid interpolations. We then extracted 1D spectra from the stacked 2D spectra using both boxcar and optimal extraction algorithms. We used an aperture diameter of 5 pixels (0 315) for the boxcar spectral extraction. The pixel scales for both 1D and 2D spectra are resampled to be 10 Å pixel -1. During the 1D spectral extraction process for both methods, we performed iterative background subtraction to subtract off the background residuals. We note that the two spectra sets agree well with each other, and we only used the second approach in this work by considering that the profile fitting used for optimal extraction is slightly better characterized in the stacked 2D spectra for very faint galaxies.
a Galaxies spectroscopically confirmed from the ASPIRE program will be named as ASPIRE-JHHMMXDD-TT-NNN, where JHHMMXDD represents the quasar field name, TT denotes the galaxy type (i. e. , O3 for [O III] emitters, HA for Hα emitters, and so on), and NNN represents the galaxy ID number. b The redshift uncertainties of the galaxies are dominated by systematic wavelength zero-point offsets of the current spectral dispersion model, which would be improved with more JWST in-flight calibrations. To be conservative, we budget Δz = 0. 003 for all galaxies identified in this work. expect to have a galaxy overdensity close to 30 within a smaller volume. Additionally, the field galaxy density could be overestimated, given that this field contains two galaxy overdensities at z = 5. 4 and 6. 2. These estimates indicate that J0305-3150 traces one of the most overdense structures known in the early universe (e.
2014) , TNG100  (Pillepich et al. 2018 ), TNG300, EAGLE, SIMBA, Astrid  (Bird et al. 2022; Ni et al. 2022) , and BlueTides. These numbers significantly decrease when only galaxies with M å 10 8. 5 or 10 9 M e are detectable in the SMBH field of view, making the detection of overdensities particularly challenging. These comparisons indicate that the most massive BHs in cosmological simulations are usually traced by galaxy overdensities but with a broad range of galaxy numbers. In addition, shallow observations (i. e. , only sensitive to galaxies with M å  10 9 M e ) could easily miss galaxy overdensities limited by the number of galaxies in the quasar fields. The completion of the ASPIRE program will enable a more systematic comparison between a large sample of quasar fields and the cosmological simulations by investigating galaxy numbers, galaxy velocity distribution, and quasar properties, which will deliver a more comprehensive understanding of the environment of the earliest SMBHs.
Acknowledgments F. W. is thankful for the support provided by  NASA  through  NASA   Hubble Fellowship  grant No. HST-HF2-51448. 001- A awarded by the  Space Telescope Science Institute , which is operated by the  Association of Universities for Research in Astronomy, Inc. , under  NASA  contract  NAS5-26555. F. S. and E. E. acknowledge funding from  JWST /NIRCam contract to the University of Arizona  NAS5-02105. J. T. S. acknowledges funding from the  European Research Council (ERC)   Advanced Grant program  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No. 885301 ). L. B. acknowledges support from  NSF  award  AST-1909933  and  NASA  award No. 80NSSC22K0808. S. B. acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (grant agreement No.
740246  " Cosmic Gas "). L. C. acknowledges support by grant  PIB2021-127718NB-I00  from the  Spanish Ministry of Science and Innovation/State Agency of Research   MCIN/AEI/10. 13039/ 501100011033. M. H. acknowledges support from the  Zentrum für Astronomie der Universität Heidelberg  under the  Gliese  Fellowship. Z. H. acknowledges support from  US NSF  grant  AST-2006176. H. D. J. was supported by the  National Research Foundation of Korea (NRF)  funded by the  Ministry of Science and ICT (MSIT) of Korea  (Nos. 2020R1A2C3011091 ,  2021M3F7A1084525 ,  2022R1C1C2013543 ). G. K. is partly supported by the  Department of Atomic Energy (Government of India)  research project with project identification No. RTI 4002  and the  Max Planck Society  through a  Max Planck Partner  Group. A. L. acknowledges funding from  MIUR  under grant  PRIN 2017-MB8AEZ.
Methods. We performed a survey of the cluster at 120-168 MHz using the LOw-Frequency ARray (LOFAR). We imaged a 132 deg 2 region of the cluster, reaching an order-of-magnitude greater sensitivity than existing wide-field radio surveys of this field at three times higher spatial resolution compared to other low-frequency observations. We developed a tailored data processing strategy to subtract the bright central radio galaxy M 87 from the data. This allowed us to correct for systematic effects due to ionospheric variation as a function of time and direction. Results. In the final mosaic, which has a resolution of 9 ′′ × 5 ′′ , we reach a median noise level of 140 µJy beam -1 inside the virial radius and 280 µJy beam -1 for the full area. We detect 112 Virgo member galaxies and 114 background galaxies.
In at least 18 cases, the radio morphology of the cluster member galaxies shows clear signs of ram-pressure stripping. This includes three previously unreported candidates. In addition, we reveal previously undiscovered tails of 150 kpc in length from a previous epoch of AGN activity for NGC 4472 (M 49). While no cluster-scale diffuse radio sources are discovered, we find the presence of an extended radio signature of the W ′ group. This feature is coincident with an X-ray filament detected with SRG/eROSITA in the outskirts of the cluster. We speculate that this emission is synchrotron radiation, which could be related to shocks or turbulence from accretion processes. Conclusions. The data published in this paper serve as a valuable resource for future studies. In the follow-up work of the ViCTORIA project, we will use these data for an analysis of environmental effects on the radio properties of star-forming galaxies in Virgo.
To derive these factors, we created a LOFAR source catalog for each Virgo field using the Python Blob Detector and Source Finder (PyBDSF,  Mohan et al. 2015)  and only considered sources with: no neighbor within 30 ′′ ; a major axis of less than 25 ′′ ; and a significance of at least 5σ. The final correction factors we found were applied to the fields during mosaicing, ultimately placing our survey on the scale of the 6C survey, which in turn is aligned with the flux density scale of  Roger et al. (1973). In the mosaicing procedure, pixels were weighted according to the primary beam response as well as the central noise level of the corresponding field. We also excluded all areas with a primary beam attenuation factor of below 0. 3. In the final mosaic, we restore the clean components of M 87 that were subtracted in the peeling pipeline.
Discussion A dedicated scientific analysis of the radio data presented here will be the subject of follow-up work by our team, including a study of the radio-star formation rate(SFR) relation and the ram-pressure stripped objects in Virgo. However, here we present highlights and a brief initial discussion of radio sources that 5 https://lofar-surveys. org/virgo_survey. html are noteworthy either due to their environmental interaction or because they otherwise belong to a class of objects that is of particular interest in the radio continuum, such as giant ellipticals or dwarf galaxies. See Appendix A for an image atlas of all the galaxies.
Acknowledgements. H. E. acknowledges support by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)  under project number  427771150. M. B. acknowledges support from the  Deutsche Forschungsgemeinschaft under Germany's Excellence Strategy -EXC 2121 "Quantum Universe" -390833306. A. I. acknowledges financial support from the  European Research Council (ERC) programme  (grant agreement No. 833824 ). D. J. B. acknowledges funding from the  German Science Foundation DFG , via the  Collaborative Research Center SFB1491 'Cosmic Interacting Matters -From Source to Signal'. A. I. acknowledges the  INAF founding program  ' Ricerca Fondamentale 2022 ' (PI:  A. Ignesti ). R. Jv. W. acknowledges support from the  ERC   Starting Grant ClusterWeb 804208. E. B. acknowledges financial support from the  European.
Sect. 4 discusses the accuracy of KF2023 compared to the reference calculations. The Conclusion summarizes the results of our study. Appendix A contains technical details of the code and recommendations for its implementing and usage in GCMs. 2 Method and technical approach. The ALI-ARMS code New routine for calculating the non-LTE 15 µm CO 2 cooling we present is the optimized version of our basic ALI-ARMS model and code  (Kutepov et al. , 1998; Feofilov and Kutepov, 2012) , which utilizes two advanced techniques: (1) the ALI technique for the solution of the non-LTE problem, and (2) the ODF technique for optimizing the radiative transfer calculations. In this section, we outline these techniques and the current status and latest applications of ALI-ARMS code.
, 2015)  and for explaining the nighttime CO 2 4. 3 µm limb emission enhancement caused by recently discovered new channel of energy transfer from OH(ν) to CO 2. Earlier, the ALI-ARMS code was used  (Kutepov et al. , 2006)  to pinpoint an important missing process of strong V-V coupling between the isotopes in the CO 2 non-LTE model of the SABER operational algorithm, and to modeling the H 2 O 6. 3 µm emission and the H 2 O density retrievals in the MLT from the SABER 6. 3 µm limb radiances  (Feofilov et al. , 2009). As we show below, the ALI-ARMS code also provides an efficient way of calculating the 15 µm CO 2 cooling/heating in the GCMs. 3 New routine for the CO 2 cooling calculations.
The sum in (3) goes along all CO 2 transitions in the model. In withing the code), which are required for each calculation part. We performed this study at two different machines, with x86 64-bit Intel and Intel Xeon Gold processors operating at 2. 2 and 2. 5 GHz, respectively. We compiled the ALI-ARMS code with the help of a standard gcc compiler and we ran it on a single processor. We provide the results only for one 2. 2 GHz Intel processor; the timing for the second processor is roughly 1. 4 times shorter. Compared to the reference code, we ran the routine using the convergence criterion 1. 0e-2 instead of 1. 0e-4. This allowed reducing the number of iterations by a factor of about 2 without sacrificing the accuracy. Similar to the study by  Hubeny and Mihalas (2015) , we found that time T required for any procedure like the radiative transfer equation solution or matrix inversion may be presented as T = CN, (4) where N is the number of operations.
Conclusions We present the new KF2023 routine for calculating the non-LTE CO 2 15 µm radiative cooling/heating in the middle and upper atmosphere. The routine provides high accuracy cooling rates above 20 km in a broad range of atmospheric input variations for any temperature distributions including those disturbed by strong micro-and meso-scale strictures and is the optimized version of the ALI-ARMS reference model and research code  (Feofilov and Kutepov, 2012) , which rigorously solves the non-LTE in CO 2 , N 2 , O 2 coupled by intensive vibrational-vibrational energy exchanges. It relies on advanced techniques of exact non-LTE problem solution (ALI-algorithm) and the molecular band radiative transfer treatment (ODF-technique). Using these methods, we achieved about ∼1000 times acceleration compared to the standard matrix/line-by-line solution of the same non-LTE problem without sacrificing the accuracy.
Following the discussion in Sect. 4 the routine may generally work with any upper and lower boundary, however it is nor recommended putting the upper boundary below ∼ 110 km since it causes increasing calculations errors due to not accounting for the upper atmospheric layers as well as placing the lower boundary below ∼ 20 km because of increasing errors caused by not accounting for the line overlapping in a current version of the ODF approach. The module requires geometrical altitudes to calculate radiative transfer and an equidistant altitude grid, which guaranties exact solution of the radiative transfer equation. The user may define any grid step including very fine one, which allows resolving micro-scale temperature disturbances. The calculation time of the routine linearly depends on the number of grid points N D compared to matrix algorithms, where the time ∼ N 3 D , see expressions (4 -10).
Code availability. The current version of the routine code is available at https://doi. org/10. 5281/zenodo. 8005028 Author contributions. Within more than 20 year of collaboration of both authors on the development of the ALI-ARMS code, which optimized version NLTE15µmCool-E is presented here, AK contributed most in the development of the ALI and ODF methodologies, he also wrote the manuscript draft supported by AF. AF contributed most to the development of the ALI-ARMS physical model, designed and implemented in the code the ODF based routines for radiative transfer treatment, performed all calculations presented in this paper as well as the detailed analysis of the routine computational performance.
Sample collection Patient tumor samples and retrospective clinical information were provided by multiple national and international collaborating centers and collected at the Department of Neuropathology of the University Hospital Heidelberg (Heidelberg, Germany) and German Cancer Research Center (DKFZ, Heidelberg, Germany). Sample selection was based on unsupervised visualization (t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP)) of genome-wide DNA methylation array data that revealed a molecularly distinct group of tumors forming a cluster separate from all established tumor types. In addition, two further CNS tumor samples harboring a CIC::LEUTX fusion that have already been published were included into subsequent molecular profiling  10.
DNA methylation array processing and copy number profiling Genome-wide DNA methylation profiling of all samples was performed using the Infinium MethylationEPIC (EPIC) BeadChip (Illumina, San Diego, CA, USA) or Infinium HumanMethylation450 (450k) BeadChip array (Illumina) according to the manufacturer's instructions and as previously described  9. Raw data were generated at the Department of Neuropathology of the University Hospital Heidelberg, the Genomics and Proteomics Core Facility of the DKFZ or at respective international collaborator institutes, using both fresh-frozen and FFPE tissue samples. All computational analyses were performed in R version 4. 6. 1 (R Development Core Team, 2020; https://www. R-project. org). Copy number variation analysis from 450k and EPIC methylation array data was performed using the conumee Bioconductor package version 1.
12. 0. Summary copy number profiles to display rates of copy number gains and losses per DNA methylation class were generated using an in-house R script (https://github. com/ dstichel/CNsummaryplots). Focal copy number alterations were called based on manual review of the log2 ratio plots for each sample. Raw signal intensities were obtained from IDAT-files using the minfi Bioconductor package version 1. 21. 4  26. Illumina EPIC and 450k samples were merged to a combined data set by selecting the intersection of probes present on both arrays (combineArrays function, minfi). Each sample was individually normalized by performing a background correction (shifting of the 5% percentile of negative control probe intensities to 0) and a dye-bias correction (scaling of the mean of normalization control probe intensities to 10,000) for both color channels.
Subsequently, a correction for the array type (450k/EPIC) was performed by fitting univariable, linear models to the log2-transformed intensity values (removeBatchEffect function, limma package version 3. 30. 11). The methylated and unmethylated signals were corrected individually. Beta-values were calculated from the retransformed intensities using an offset of 100 (as recommended by Illumina). All samples were checked for duplicates by pairwise correlation of the genotyping probes on the 450k/EPIC array. To perform unsupervised nonlinear dimension reduction, the remaining probes after standard filtering 9 were used to calculate the 1-variance weighted Pearson correlation between samples. The resulting distance matrix was used as input for t-SNE analysis (Rtsne package version 0. 13). The following non-default parameters were applied: is_distance = T, theta = 0, pca = F, max_iter = 10,000, perplexity = 30.
RNA sequencing and analysis RNA sequencing for the purpose of gene fusion detection of samples for which RNA of sufficient quality and quantity was available (n = 8) was performed as previously described  28. In brief, RNA sequencing libraries were prepared using the TruSeq RNA Library Prep for Enrichment kit (Illumina) and paired-end reads were sequenced on a NextSeq 500 or NovaSeq 6000 instrument (Illumina). After adapter trimming, reads were aligned to the human genome (GRCh37) with the STAR aligner  29  and counted using RSEM  30. Fastq files from transcriptome sequencing were used for de novo annotation of fusion transcripts using the Arriba (v1. 2. 0) algorithm  31  with standard parameters, which removes recurrent alignment artifacts, transcript variants also observed in normal tissue, reads with low sequence complexity, and events with short anchors or breakpoints in close proximity or a low number of supporting reads relative to the overall number of predicted events in a gene.
DATA AVAILABILITY DNA methylation data generated during this study has been deposited in NCBIs Gene Expression Omnibus (GEO, http://www. ncbi. nlm. nih. gov/geo) under accession number GSE223546. DNA methylation data used as a reference has been deposited under accession number GSE90496. Consent for public data sharing of sequencing data was not obtained from the patients, so datasets are available upon IRB-approved collaboration from the corresponding author (PS) and will only be shared for research-related, non-commercial purposes. The remaining data are available within the article and supplementary material.
ACKNOWLEDGEMENTS The authors thank  L. Dörner  and  L. Hofmann  for excellent technical assistance, and the  DKFZ Genomics and Proteomics Core Facility  for support in DNA methylation analysis. This study was supported by the  Hertie Network of Excellence in Clinical Neuroscience. P. Sievers is supported by the  Else Kröner Fresenius Stiftung  and a fellow of the  Hertie Academy of Excellence in Clinical Neuroscience.
Recent advances in paleogenomic techniques are transforming our understanding of past cultivar diversity by providing valuable datasets for the study of heirloom plants in Antiquity  (20, 21). For example, ancient DNA (aDNA) extracted from French grape pips showed that the pedigree of some Western European heritage cultivars is rooted in medieval and Roman times  (22). Remarkably, one 900-y-old specimen was identified as the genetic clone of Savagnin Blanc, a popular French cultivar, offering evidence of centuries of uninterrupted clonal propagation. Here, we report the results of target-enriched genome-wide sequencing on DNA extracted from ancient grape pips found in a sealed stone-built room in the ancient settlement of Avdat (Oboda) in the Negev Highlands  (23). The architectural style in the compound is Byzantine and affronts a cave dwelling space featuring Early Christian monastic wall paintings.
Above the Byzantine period floor, thick accumulations of desiccated dung with abundant uncharred grape pips were dated to the Early Islamic period (SI Appendix, Table  S1 ). To expand our research, we also sequenced modern indigenous cultivars and feral and wild grapes collected from across Israel. Comparative analyses of the modern and ancient datasets and of sequenced cultivars from around the world provided insights into the genetic legacy of the Late Antiquity grapes. Moreover, we discovered that one of the ancient specimens can be linked with an excellent winemaking grape lineage whose progenies are still cultivated today.
Results DNA of Archaeological and Modern Native Samples. We extracted 16 archaeological grapevine pips from four archaeological sites in Israel (Fig. 1  and SI Appendix, Chapter 1 and Tables  S1  and S4 ). Six pips successfully yielded DNA and were halved. One half was used for DNA extraction and the other half for radiocarbon dating. The radiocarbon dates ranged from the end of the seventh to tenth centuries CE (SI Appendix, Table  S1 ). Eventually, five pips were used in this study. Nucleotide misincorporation patterns  (24, 25)  and read length distributions observed in the sequenced data were consistent with those expected of degraded DNA. We also sampled and sequenced the young leaf tissues of 33 wild and domesticated grapevine varieties from across Israel. Eventually, nine unique samples were used in this study (Fig.
1  and SI Appendix, Tables  S2  and S5 ). The ancient and modern samples were target enriched for 10,000 single-nucleotide polymorphisms (SNPs)  (28)  and then sequenced. We added the genotypes of hundreds of accessions from the GrapeRefSeq diversity panels  (28, 29)  and other publicly available grape genomes from several National Center for Biotechnology Information (NCBI) projects  (19, 30, 31)  (SI Appendix, Table  S3 ). Due to the high variability in quality among the ancient samples, we decided to create two separate datasets that either maximized the number of SNPs in the analyses (6,928 SNPs and three ancient samples; coverage X10-X40) or maximized the number of the archaeological samples (1,032 SNPs and five ancient samples; coverage X4. 6 -X59). See SI Appendix, Tables  S1  and S4  for more details.