cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25387/g3.14798436.v1
title: Supplemental Material for Xiao et al., 2021

description: Supplementary materials.Figure S1. Pipeline for the array design steps.Figure S2. GenomeStudio genotyping results. Figure S3. Characteristics of Bnapus50K.Figure S4. Phylogenetic analysis of 171 cultivars of B. napus 171 based on Bnapus50K genotyping.Table S1. Plant materials and experiments.Table S2. Data for 42,090 probes on the Bnapus50K array.Table S3. Genotyping results for 171 rapeseed cultivars.Table S4. The genetic distance matrix for 171 rapeseed cultivars.Table S5. Chromosomal distribution of genome-specific SNP markers (Darmor-bzh v4.1).Table S6. Functional probes on the Bnapus50K array.Table S7. List of verified high quality functional probes.Table S8. Detection results from probes for the herbicide-resistance gene epsps-ih.<br><br>
DOI: 10.25387/g3.14798436
title: Supplemental Material for Xiao et al., 2021

description: Supplementary materials.Figure S1. Pipeline for the array design steps.Figure S2. GenomeStudio genotyping results. Figure S3. Characteristics of Bnapus50K.Figure S4. Phylogenetic analysis of 171 cultivars of B. napus 171 based on Bnapus50K genotyping.Table S1. Plant materials and experiments.Table S2. Data for 42,090 probes on the Bnapus50K array.Table S3. Genotyping results for 171 rapeseed cultivars.Table S4. The genetic distance matrix for 171 rapeseed cultivars.Table S5. Chromosomal distribution of genome-specific SNP markers (Darmor-bzh v4.1).Table S6. Functional probes on the Bnapus50K array.Table S7. List of verified high quality functional probes.Table S8. Detection results from probes for the herbicide-resistance gene epsps-ih.<br><br>
DOI: 10.5519/qd.p4lxl2p5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (150 records)
DOI: 10.6073/pasta/4c2277f74a3756ab87b3592d6e8d793c
title: Periodic Degassing Rhythms in Three Mineral Springs in the Neuwied Basin, Germany 2016

description: We present a geochemical dataset acquired during continual sampling over 7 months (bi-weekly) and 4 weeks (every 8 hours) in the Neuwied Basin, a part of the East Eifel Volcanic Field (EEVF, Germany). We used a combination of geochemical, geophysical, and statistical methods to describe and identify potential causal processes underlying the correlations of degassing patterns of CO2, He, Rn, and tectonic processes in three investigated mineral springs (Nette, Kärlich and Kobern). We provide for the first time, temporal analyses of periodic degassing patterns (1 day and 2-6 days) in springs. The temporal fluctuations in cyclic behavior of 4–5 days that we recorded had not been observed previously but may be attributed to a fundamental change in either gas source processes, subsequent gas transport to the surface, or the influence of volcano-tectonic earthquakes. Periods observed at 10 and 15 days may be related to discharge pulses of magma in the same periodic rhythm. We report the potential hint that deep low-frequency (DLF) earthquakes might actively modulate degassing. Temporal analyses of the CO2-He and CO2-Rn couples indicate that all springs are interlinked by previously unknown fault systems. The volcanic activity in the EEVF is dormant but not extinct. To understand and monitor its magmatic and degassing systems in relation to new developments in DLF-earthquakes and magmatic recharging processes and to identify seasonal variation in gas flux, we recommend continual monitoring of geogenic gases in all available springs taken at short temporal intervals.
DOI: 10.5517/ccdc.csd.cc245zfr
title: CCDC 1971954: Experimental Crystal Structure Determination

description: Related Article: Xue-Hong Li, Jun-Fang Gong, Mao-Ping Song|2021|Org.Biomol.Chem.|19|5876|doi:10.1039/D1OB00656H
DOI: 10.5517/ccdc.csd.cc24cx2j
title: CCDC 1977647: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cx3k
title: CCDC 1977648: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cx5m
title: CCDC 1977650: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cx6n
title: CCDC 1977651: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cx8q
title: CCDC 1977653: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cxdv
title: CCDC 1977657: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24cxhy
title: CCDC 1977660: Experimental Crystal Structure Determination

description: Related Article: Xin Xu, Chenguang Luo, Haoqiang Zhao, Yixiao Pan, Xin Zhang, Jiajie Li, Lijin Xu, Ming Lei, Patrick J. Walsh|2021|Chem.-Eur.J.|27|8811|doi:10.1002/chem.202101074
DOI: 10.5517/ccdc.csd.cc24y5pz
title: CCDC 1994251: Experimental Crystal Structure Determination

description: Related Article: Chi-Shin Wang, Yu-Chen Wei, Ming-Lun Pan, Cheng-Ham Wu, Pi-Tai Chou, Yao-Ting Wu|2021|Chem.-Eur.J.|27|8678|doi:10.1002/chem.202100234
DOI: 10.5517/ccdc.csd.cc24y5q0
title: CCDC 1994252: Experimental Crystal Structure Determination

description: Related Article: Chi-Shin Wang, Yu-Chen Wei, Ming-Lun Pan, Cheng-Ham Wu, Pi-Tai Chou, Yao-Ting Wu|2021|Chem.-Eur.J.|27|8678|doi:10.1002/chem.202100234
DOI: 10.5517/ccdc.csd.cc24y5r1
title: CCDC 1994253: Experimental Crystal Structure Determination

description: Related Article: Chi-Shin Wang, Yu-Chen Wei, Ming-Lun Pan, Cheng-Ham Wu, Pi-Tai Chou, Yao-Ting Wu|2021|Chem.-Eur.J.|27|8678|doi:10.1002/chem.202100234
DOI: 10.5517/ccdc.csd.cc24y5s2
title: CCDC 1994254: Experimental Crystal Structure Determination

description: Related Article: Chi-Shin Wang, Yu-Chen Wei, Ming-Lun Pan, Cheng-Ham Wu, Pi-Tai Chou, Yao-Ting Wu|2021|Chem.-Eur.J.|27|8678|doi:10.1002/chem.202100234
DOI: 10.5517/ccdc.csd.cc2526wc
title: CCDC 1998132: Experimental Crystal Structure Determination

description: Related Article: Manuel A. Roque-Ramires,  Longzhu Shen,  Ronan Le Lagadec|2020|Eur.J.Inorg.Chem.|2020|2700|doi:10.1002/ejic.202000425
DOI: 10.5517/ccdc.csd.cc252c0n
title: CCDC 1998260: Experimental Crystal Structure Determination

description: Related Article: Karolína Salvadori, Ludmila Šimková, Ivana Císařová, Jan Sýkora, Jiří Ludvík, Petra Cuřínová|2020|ChemPlusChem|85|1401|doi:10.1002/cplu.202000326
DOI: 10.5517/ccdc.csd.cc252c1p
title: CCDC 1998261: Experimental Crystal Structure Determination

description: Related Article: Karolína Salvadori, Ludmila Šimková, Ivana Císařová, Jan Sýkora, Jiří Ludvík, Petra Cuřínová|2020|ChemPlusChem|85|1401|doi:10.1002/cplu.202000326
DOI: 10.5517/ccdc.csd.cc252c2q
title: CCDC 1998262: Experimental Crystal Structure Determination

description: Related Article: Karolína Salvadori, Ludmila Šimková, Ivana Císařová, Jan Sýkora, Jiří Ludvík, Petra Cuřínová|2020|ChemPlusChem|85|1401|doi:10.1002/cplu.202000326
DOI: 10.5517/ccdc.csd.cc252c3r
title: CCDC 1998263: Experimental Crystal Structure Determination

description: Related Article: Karolína Salvadori, Ludmila Šimková, Ivana Císařová, Jan Sýkora, Jiří Ludvík, Petra Cuřínová|2020|ChemPlusChem|85|1401|doi:10.1002/cplu.202000326
DOI: 10.5517/ccdc.csd.cc252rvw
title: CCDC 1998658: Experimental Crystal Structure Determination

description: Related Article: Markus Lerch, Markus Weitzer, Tim-Daniel J. Stumpf, Larissa Laurini, Alexander Hoffmann, Jonathan Becker, Andreas Miska, Richard Göttlich, Sonja Herres-Pawlis, Siegfried Schindler|2020|Eur.J.Inorg.Chem.|2020|3143|doi:10.1002/ejic.202000462
DOI: 10.5517/ccdc.csd.cc252rwx
title: CCDC 1998659: Experimental Crystal Structure Determination

description: Related Article: Markus Lerch, Markus Weitzer, Tim-Daniel J. Stumpf, Larissa Laurini, Alexander Hoffmann, Jonathan Becker, Andreas Miska, Richard Göttlich, Sonja Herres-Pawlis, Siegfried Schindler|2020|Eur.J.Inorg.Chem.|2020|3143|doi:10.1002/ejic.202000462
DOI: 10.5517/ccdc.csd.cc252h4x
title: CCDC 1998388: Experimental Crystal Structure Determination

description: Related Article: Amr El-Demerdash,  Ludmila Ermolenko,  Emmanuelle Gros,  Pascal Retailleau,  Binh Nguyen Thanh,  Anne Gauvin-Bialecki,  Ali Al-Mourabit|2020|Eur.J.Org.Chem.|2020|5677|doi:10.1002/ejoc.202000744
DOI: 10.5517/ccdc.csd.cc2531fs
title: CCDC 1998924: Experimental Crystal Structure Determination

description: Related Article: Marius Bayer,  Simon Stocker,  Cäcilia Maichle-Mössmer,  Thomas Ziegler|2020|Eur.J.Org.Chem.|2020|4347|doi:10.1002/ejoc.202000615
DOI: 10.5517/ccdc.csd.cc2531ly
title: CCDC 1998929: Experimental Crystal Structure Determination

description: Related Article: Fumitoshi Yagishita,  Keita Hoshi,  Yasushi Yoshida,  Shoko Ueta,  Keiji Minagawa,  Yasushi Imada,  Yasuhiko Kawamura|2020|Eur.J.Org.Chem.|2020|235|doi:10.1002/ejoc.202001200
DOI: 10.5517/ccdc.csd.cc2531q2
title: CCDC 1998933: Experimental Crystal Structure Determination

description: Related Article: Fumitoshi Yagishita,  Keita Hoshi,  Yasushi Yoshida,  Shoko Ueta,  Keiji Minagawa,  Yasushi Imada,  Yasuhiko Kawamura|2020|Eur.J.Org.Chem.|2020|235|doi:10.1002/ejoc.202001200
DOI: 10.5517/ccdc.csd.cc2531r3
title: CCDC 1998934: Experimental Crystal Structure Determination

description: Related Article: Fumitoshi Yagishita,  Keita Hoshi,  Yasushi Yoshida,  Shoko Ueta,  Keiji Minagawa,  Yasushi Imada,  Yasuhiko Kawamura|2020|Eur.J.Org.Chem.|2020|235|doi:10.1002/ejoc.202001200
DOI: 10.5517/ccdc.csd.cc2538k4
title: CCDC 1999145: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538l5
title: CCDC 1999146: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538m6
title: CCDC 1999147: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538n7
title: CCDC 1999148: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538p8
title: CCDC 1999149: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538q9
title: CCDC 1999150: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538rb
title: CCDC 1999151: Experimental Crystal Structure Determination

description: Related Article: Michael T. Whitelaw, Alan R. Kennedy, R. E. Mulvey|2020|Eur.J.Inorg.Chem.|2020|2912|doi:10.1002/ejic.202000434
DOI: 10.5517/ccdc.csd.cc2538sc
title: CCDC 1999152: Experimental Crystal Structure Determination

description: Related Article: Artem Semakin,  Yulia Nelyubina,  Sema Ioffe,  Alexey Sukhorukov|2020|Eur.J.Org.Chem.|2020|6723|doi:10.1002/ejoc.202000832
DOI: 10.15468/znsq3a
title: Revision of Ommatius Wiedemann (Diptera: Asilidae). IV. Pygommatius subgen. nov. with twenty-five Afrotropical species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Scarbrough, Aubrey G., Marascia, Claudio G. (2003): Revision of Ommatius Wiedemann (Diptera: Asilidae). IV. Pygommatius subgen. nov. with twenty-five Afrotropical species. Zootaxa 228 (1): 1-94, DOI: 10.11646/zootaxa.228.1.1, URL: http://biotaxa.org/Zootaxa/article/view/zootaxa.228.1.1
DOI: 10.6073/pasta/4a05dcf294d6196474aa8fa6efd70810
title: R Code and Images for Developing a Spatial Concordance Coefficient at Harvard Forest 2010

description: Concordance correlation coefficients have been developed in a variety of different contexts. This problem has been widely addressed in a non-spatial context, but here we consider a coefficient that for a fixed spatial lag allows the comparison of two spatial sequences (e.g., images). We define a spatial concordance coefficient for second-order stationary processes.
DOI: 10.6084/m9.figshare.14763504
title: Data from: "Location probing by males complicates sexual dynamics and successful mate-guarding in squid groups"

description: Data from Egypt (2019) and Indonesia (2013) detailing the number of location probing events by males and egg-laying events by females, including a presence/absence variable for each.<br>
DOI: 10.6084/m9.figshare.14763504.v1
title: Data from: "Location probing by males complicates sexual dynamics and successful mate-guarding in squid groups"

description: Data from Egypt (2019) and Indonesia (2013) detailing the number of location probing events by males and egg-laying events by females, including a presence/absence variable for each.<br>
DOI: 10.6084/m9.figshare.13611155
title: Data from 'Regional Photometric Models of Asteroid (101955) Bennu'

description: Reginal photometric models of asteroid Bennu, as described in "Regional Photometric Modeling of Asteroid (101955) Bennu" by Golish et al. (2021).<br>See Golish2021_PSJ_README.pdf for information on data structure.
DOI: 10.6084/m9.figshare.13611155.v1
title: Data from 'Regional Photometric Models of Asteroid (101955) Bennu'

description: Reginal photometric models of asteroid Bennu, as described in "Regional Photometric Modeling of Asteroid (101955) Bennu" by Golish et al. (2021).<br>See Golish2021_PSJ_README.pdf for information on data structure.
DOI: 10.6073/pasta/fd41f713b04bcd2859be1ecfcdda93c0
title: Northern Range Limit of Aphaenogaster picea in Maine 2015

description: Low temperatures at poleward range margins of terrestrial species tend to match cold tolerance limits, suggesting that range boundaries may be set by evolutionary constraints on cold physiology. The northeastern woodland ant, Aphaenogaster picea, occurs up to approximately 45 °N in central Maine. We combined presence-absence surveys with regression-tree analysis to characterize its northern range limit, and assayed two measures of cold tolerance operating on different time-scales to determine whether and how marginal populations adapt to environmental extremes. The boundary was predicted primarily by temperature, but low winter temperatures did not emerge as the primary correlate of species occurrence. Low summer temperatures and high seasonal variability predicted absence above the boundary, whereas high mean annual temperature (MAT) predicted presence in southern Maine. Locations between these zones formed an east-west band where presence was conditional on precipitation. In contrast, assays of cold tolerance across multiple sites indicated substantial local adaptation of cold tolerance at the range edge, with a 4-minute reduction in chill-coma recovery time across a 2-degree reduction in MAT. Baseline tolerance and capacity for additional plastic cold-hardening shifted in opposite directions, with hardening capacity approaching zero at the coldest sites. This trade-off suggests that populations at range edges may adapt to colder temperatures through genetic assimilation of plastic responses, potentially constraining further adaptation and range expansion.
DOI: 10.3886/e120321v8-91100
title: Global Reactions to COVID-19 on Twitter: A Labelled Dataset with Latent Topic, Sentiment and Emotion Attributes

description: This project aims to present a large dataset for researchers to discover public conversation on Twitter surrounding the COVID-19 pandemic. As strong concerns and emotions are expressed in the publicly available tweets, we annotated seventeen latent semantic attributes for each public tweet using natural language processing techniques and machine-learning based algorithms. The latent semantic attributes include: 1) ten attributes indicating the tweet’s relevance to ten detected topics, 2) five quantitative attributes indicating the degree of intensity in the valence (i.e., unpleasantness/pleasantness) and emotional intensities across four primary emotions of fear, anger, sadness and joy, and 3) two qualitative attributes indicating the sentiment category and the most dominant emotion category, respectively.
description: Twitter posts.
DOI: 10.6084/m9.figshare.14828535
title: Microsatellites dataset

description: Microsatellites used in a study of tree frog populations in the Chernobyl exclusion zone<br>
DOI: 10.15468/zwb7zj
title: The type specimens of sawflies (Hymenoptera: Symphyta) of the Museo Nacional de Ciencias Naturales, Madrid

description: This dataset contains the digitized treatments in Plazi based on the original journal article Taeger, Andreas, París, Mercedes, Nieves-Aldrey, Jose Luis (2014): The type specimens of sawflies (Hymenoptera: Symphyta) of the Museo Nacional de Ciencias Naturales, Madrid. Zootaxa 3790 (1): 103-138, DOI: http://dx.doi.org/10.11646/zootaxa.3790.1.5
DOI: 10.6073/pasta/5ab536ec71d31f452418189a7b4c52a5
title: Carbon Budget at the Harvard Forest 1992-2015

description: How, where, and why carbon (C) moves into and out of an ecosystem through time are long-standing questions in biogeochemistry. Here, we bring together hundreds of thousands of C-cycle observations at the Harvard Forest in central Massachusetts, USA, a mid-latitude landscape dominated by 80–120-year-old closed-canopy forests. These data answered four questions: (i) where and how much C is presently stored in dominant forest types; (ii) what are current rates of C accrual or loss; (iii) what biotic and abiotic factors contribute to variability in these rates; and (iv) is climate change affecting the forest’s C cycle? Harvard Forest is an active C sink resulting from forest regrowth following land abandonment. Soil and tree biomass comprise nearly equal portions of existing C stocks. Net primary production (NPP) averaged 750–970 g C m-2 yr-1; belowground NPP contributed 30–60% of the total. Mineral soil C measured in the same inventory plots in 1992 and 2013 were too heterogeneous to detect change in soil-C pools; however, radiocarbon data suggest a small but persistent sink of 10–30 g C m-2 yr-1. Net ecosystem production (NEP) in hardwood stands averaged ~300 g C m-2 yr-1. NEP in hemlock-dominated forests averaged ~450 g C m-2 yr-1 prior to infestation by the hemlock woolly adelgid (HWA) in 2013, and then became a net C source. Stand dynamics and climate change in the last three decades enhanced the C sink in hardwood stands; NPP increased 26% between 2000–2014 (p = 0.02) and NEP increased 93% between 1992–2015 (p = 0.13). Compared to long-term global change experiments at the Harvard Forest, the C sink in regrowing biomass equaled or exceeded C cycle modifications imposed by soil warming, N saturation, and hemlock removal. Median forest biomass in the surrounding ecoregion was only 78% of that at the Harvard Forest due to higher timber harvesting rates across the region. Results of this synthesis and comparison to simulation models suggest that forests across the region are likely to accrue C for decades to come but may be disrupted if the frequency or severity of disturbance increases.
DOI: 10.6084/m9.figshare.14039369.v1
title: Supplementary code, raw data and figure plots from "Quantitative mapping of dense microtubule arrays in mammalian neurons"

description: Supplementary code, raw data and figure plots from the paper:<br><i>"Quantitative mapping of dense microtubule arrays in mammalian neurons"</i><br>Eugene A. Katrukha, Daphne Jurriens, Desiree Salas Pastene, Lukas C. Kapitein <br><br>
DOI: 10.23641/asha.14880360
title: Nonword repetition in Arabic-speaking children (Taha et al., 2021)

description: <b>Purpose: </b>This study evaluates the effectiveness of a nonword repetition (NWR) task in discriminating between Palestinian Arabic–speaking children with developmental language disorder (DLD) and age-matched typically developing (TD) children.<b>Method: </b>Participants were 30 children with DLD aged between 4;0 and 6;10 (years;months) and 60 TD children aged between 4;0 and 6;8 matched on chronological age. The Arabic version of a Quasi-Universal NWR task was administered. The task comprises 30 nonwords that vary in length, presence of consonant clusters (CCs) and wordlikeness ratings. Responses were scored using an item-level scoring method to assess the diagnostic accuracy of the task. Receiver operating characteristic curve analysis was conducted to determine the best cutoff point with the highest sensitivity and specificity values, and likelihood ratios were calculated.<b>Results: </b>Children with DLD scored significantly lower on the NWR task than their age-matched TD peers. Only the DLD group was influenced by the phonological complexity of the nonwords, with nonwords with two CC being more difficult than nonwords with no or only one CC. For both groups, three-syllable nonwords were repeated less accurately than two- and one-syllable nonwords. Also, high word-like nonwords were repeated more accurately than nonwords with low wordlikeness ratings. The best cutoff score had sensitivity and specificity of 93% and highly informative likelihood ratios.<b>Conclusions: </b>NWR was an area of difficulty for Palestinian Arabic–speaking children with DLD. NWR showed excellent discriminatory power in differentiating Arabic-speaking children diagnosed with DLD from their age-matched TD peers. NWR appears to hold promise for clinical use as it is a useful indicator of DLD in Arabic. These results need to be further validated using population-based studies.<br><b>Supplemental Material S1. </b>Individual raw scores for the TD and DLD groups on the background measures and the Arabic version of the QU-LITMUS-NWR.<br><b>Supplemental Material S2.</b> Summary of model fitting.<br>Taha, J., Stojanovik, V., & Pagnamenta, E. (2021). Nonword repetition performance of Arabic-speaking children with and without developmental language disorder: A study on diagnostic accuracy.<i> Journal of Speech, Language, and Hearing Research</i>. Advance online publication. https://doi.org/10.1044/2021_JSLHR-20-00556