cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7898321
title: Epigenetic and transcriptional landscape of stress memory in woodland strawberry

description: Bedfiles of differentially methylated regions (DMRs) that were detected in stressed mother plants (M) and their (themselves unstressed) clonal daughter plants that were formed <em>via</em> stolon formation (St1, St2, St3). The M plants were grown and sampled <em>in vitro</em> and the St1, St2, St3 plants in the green house. The DMRs were called using the the EpiDiverse/dmr bioinformatic analysis pipeline (Nunn et al., 2021). <strong>Stress assays <em>in vitro</em></strong> One-month-old seedlings were transferred to a fresh MS media and growth chambers at 24<sup>o</sup>C/21<sup>o</sup>C (day/night),16 h light/8 h dark, as control conditions<em>. </em>For heat-stress, plants were exposed to 30<sup>o</sup>C (day/night) for one week followed by 2 days of recovery (24<sup>o</sup>C/21<sup>o</sup>C) on fresh medium as well as the control plants. Then, the plates were transferred to 37<sup>o</sup>C (day/night) for 1 week with 2 recovery days (Figure 1A). We sampled aerial parts of plants for the molecular analyses. To reduce variability resulting from individual plants, three biological replicates of 5 pooled plants were collected per condition. Samples were harvested in 1.5 mL tubes between 9:00-11:00 a.m. and immediately frozen in liquid nitrogen and stored at -80<sup>o</sup>C until required. <strong>Greenhouse propagation assays</strong> <em>In vitro</em> plants after heat and control treatment were transferred to soil (one plant per pot) in square plastic pots (size: 12x12x10 cm) and to a greenhouse with long day conditions (24<sup>o</sup>C/21<sup>o</sup>C day/night and 60%-70% humidity). Twelve mother plants (M) from control (CM; n=12) and heat-stress (HM; n=12) conditions were used for asexual propagation. From each mother plant, the two first stolons (St) were kept for producing the daughter plants of the first asexual propagation (St1) in individual pots. After two weeks, following root formation, the stolons were cut to get independent daughter plants from their mother plant (M). This process was continued until St3. The DMRs can also be visualized here: https://jbrowse.agroscope.info/jbrowse/?data=fragaria_sub And the raw bisulfite sequencing data can be found here: https://www.ebi.ac.uk/ena/browser/text-search?query=ERP135585 How many daughter plants per stolon? One stolon produce a chain of daughter plants.
DOI: 10.3886/e183963v2
title: Data and Code for: Mental Models and Transfer Learning

description: Variables<br>1. i: Subject ID number (1 to 64)<br>2. Parameterization: 1 or 2, where 1 is the parameterization with p=0.15 and q=0.8 and 2 is the parameterization with p=0.95 and q=0.85<br>3. Round: Round within the parameterization. Parameterization 1 includes Round 1 and Round 200. Parameterization 2 is only asked in one round4. Belief_Pos: Posterior Belief after a positive signal (Possible values: 0 to 100)5. Belief_Neg: Posterior Belief after a negative signal (Possible values: 0 to 100)
DOI: 10.6084/m9.figshare.23222840
title: File - Distance Education

description: Data for online learning in Vietnam.
DOI: 10.6084/m9.figshare.23222840.v1
title: File - Distance Education

description: Data for online learning in Vietnam.
DOI: 10.7281/t1/nh6egh/bln9nj
title: SupplementalMaterial_JCEM_27June2020.docx

description: Four supplemental figures for the related article.
DOI: 10.6084/m9.figshare.21184734
title: Assessing diversity and ecosystem services of trees in educational institutions: A case study of a university campus from the Global South

description: The university campuses in the Global South (low- and middle-income countries of the world) harbour a significant proportion of the trees outside forests which furnish precious ecosystem services. In this study, we conducted field surveys to document the tree flora in the campus of Maharshi Dayanand University, Rohtak (Haryana), India. We documented 35,184 trees belonging to 66 species in 29 families from the campus. <i>Eucalyptus globulus</i> was the most dominant tree species with 13,932 individuals and Fabaceae was the most speciose family. Nearly 60% of tree species in the campus were native. The mean height (m) and circumference at breast height (cm) for the tree flora were 6.51 ± 0.21 and 50.93 ± 1.11, respectively. The overall tree density on the campus was around 140 trees/ha, mean density 2.11 ± 0.87, and the average basal area 0.021 ± 0.0009 m<sup>2</sup>/tree. The values for Simpson’s, Shannon, Margalef’s and Pielou’s evenness indices were 0.18, 2.51, 6.21 and 0.6 respectively. The campus trees provide valuable ecosystem services with food and medicinal uses, ornamental and shade values being the dominant. Our findings will guide policy on urban environmental sustainability in the educational campuses in India – the second most populous country in the Global South.
DOI: 10.6084/m9.figshare.21184734.v1
title: Assessing diversity and ecosystem services of trees in educational institutions: A case study of a university campus from the Global South

description: The university campuses in the Global South (low- and middle-income countries of the world) harbour a significant proportion of the trees outside forests which furnish precious ecosystem services. In this study, we conducted field surveys to document the tree flora in the campus of Maharshi Dayanand University, Rohtak (Haryana), India. We documented 35,184 trees belonging to 66 species in 29 families from the campus. <i>Eucalyptus globulus</i> was the most dominant tree species with 13,932 individuals and Fabaceae was the most speciose family. Nearly 60% of tree species in the campus were native. The mean height (m) and circumference at breast height (cm) for the tree flora were 6.51 ± 0.21 and 50.93 ± 1.11, respectively. The overall tree density on the campus was around 140 trees/ha, mean density 2.11 ± 0.87, and the average basal area 0.021 ± 0.0009 m<sup>2</sup>/tree. The values for Simpson’s, Shannon, Margalef’s and Pielou’s evenness indices were 0.18, 2.51, 6.21 and 0.6 respectively. The campus trees provide valuable ecosystem services with food and medicinal uses, ornamental and shade values being the dominant. Our findings will guide policy on urban environmental sustainability in the educational campuses in India – the second most populous country in the Global South.
DOI: 10.6084/m9.figshare.19152145
title: The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil

description: Among the models applied to analyze survival data, a standout is the inverse Gaussian distribution, which belongs to the class of models to analyze positive asymmetric data. However, the variance of this distribution depends on two parameters, which prevents establishing a functional relation with a linear predictor when the assumption of constant variance does not hold. In this context, the aim of this paper is to re-parameterize the inverse Gaussian distribution to enable establishing an association between a linear predictor and the variance. We propose deviance residuals to verify the model assumptions. Some simulations indicate that the distribution of these residuals approaches the standard normal distribution and the mean squared errors of the estimators are small for large samples. Further, we fit the new model to hospitalization times of COVID-19 patients in Piracicaba (Brazil) which indicates that men spend more time hospitalized than women, and this pattern is more pronounced for individuals older than 60 years. The re-parameterized inverse Gaussian model proved to be a good alternative to analyze censored data with non-constant variance.
DOI: 10.6084/m9.figshare.19152145.v1
title: The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil

description: Among the models applied to analyze survival data, a standout is the inverse Gaussian distribution, which belongs to the class of models to analyze positive asymmetric data. However, the variance of this distribution depends on two parameters, which prevents establishing a functional relation with a linear predictor when the assumption of constant variance does not hold. In this context, the aim of this paper is to re-parameterize the inverse Gaussian distribution to enable establishing an association between a linear predictor and the variance. We propose deviance residuals to verify the model assumptions. Some simulations indicate that the distribution of these residuals approaches the standard normal distribution and the mean squared errors of the estimators are small for large samples. Further, we fit the new model to hospitalization times of COVID-19 patients in Piracicaba (Brazil) which indicates that men spend more time hospitalized than women, and this pattern is more pronounced for individuals older than 60 years. The re-parameterized inverse Gaussian model proved to be a good alternative to analyze censored data with non-constant variance.
DOI: 10.6084/m9.figshare.23220998
title: <strong>Mediterranean springs: keystone ecosystems and biodiversity refugia threatened by global change</strong>

description: Dataset and R code to perform the analyses shown in the manuscript: <strong>Mediterranean springs: keystone ecosystems and biodiversity refugia threatened by global change</strong> This item contains two R scripts. The file "springs_betadiver_figshare.R" contains code to reproduce the results shown in Figure 2. The file "springs_et_piezo_analysis_figshare.R" contains the code to reproduce the results shown in Figures 7 and Figure S1.
DOI: 10.6084/m9.figshare.23220998.v1
title: <strong>Mediterranean springs: keystone ecosystems and biodiversity refugia threatened by global change</strong>

description: Dataset and R code to perform the analyses shown in the manuscript: <strong>Mediterranean springs: keystone ecosystems and biodiversity refugia threatened by global change</strong> This item contains two R scripts. The file "springs_betadiver_figshare.R" contains code to reproduce the results shown in Figure 2. The file "springs_et_piezo_analysis_figshare.R" contains the code to reproduce the results shown in Figures 7 and Figure S1.
DOI: 10.5281/zenodo.7974579
title: Datasets related to the Eggsplorer rapid plant–insect resistance determination tool, using an automated whitefly egg quantification algorithm

description: These datasets support the data provided directly in the scientific publication titled "Eggsplorer: a rapid plant–insect resistance determination tool using an automated whitefly egg quantification algorithm", published in the BMC Plant Methods journal. The figures and tables included in the datasets highlight various materials and methods employed to build a proof-of-concept of the Eggsplorer tool. These included whitefly assays, leaf image acquisitions, an automatic egg quantification algorithm, image pre-processing, object detection and image stitching, detection post-processing, algorithm evaluation and software programming. The provided figures and tables in the datasets are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication. This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000570.
DOI: 10.5281/zenodo.7974578
title: Datasets related to the Eggsplorer rapid plant–insect resistance determination tool, using an automated whitefly egg quantification algorithm

description: These datasets support the data provided directly in the scientific publication titled "Eggsplorer: a rapid plant–insect resistance determination tool using an automated whitefly egg quantification algorithm", published in the BMC Plant Methods journal. The figures and tables included in the datasets highlight various materials and methods employed to build a proof-of-concept of the Eggsplorer tool. These included whitefly assays, leaf image acquisitions, an automatic egg quantification algorithm, image pre-processing, object detection and image stitching, detection post-processing, algorithm evaluation and software programming. The provided figures and tables in the datasets are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication. This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101000570.
DOI: 10.5517/ccdc.csd.cc273lzy
title: CCDC 2059050: Experimental Crystal Structure Determination

description: Related Article: Britta Glowacki-Pallach, Michael Lutter, Dieter Schollmeyer, Wolf Hiller, Viatcheslav Jouikov, Klaus Jurkschat|2023|Inorg.Chem.|62|7662|doi:10.1021/acs.inorgchem.2c04242
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc273m00
title: CCDC 2059051: Experimental Crystal Structure Determination

description: Related Article: Britta Glowacki-Pallach, Michael Lutter, Dieter Schollmeyer, Wolf Hiller, Viatcheslav Jouikov, Klaus Jurkschat|2023|Inorg.Chem.|62|7662|doi:10.1021/acs.inorgchem.2c04242
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27tsvq
title: CCDC 2080374: Experimental Crystal Structure Determination

description: Related Article: E.G. Sundararaman, R. Elancheran, M.N. Arumugham|2023|J.Mol.Struct.|1287|135736|doi:10.1016/j.molstruc.2023.135736
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.23098253.v1
title: TableS3 Bulk RIN.xlsx

description: <strong>Table S3:</strong> Bulk kidney RNA-seq RNA integrity numbers and concentration.
DOI: 10.6073/pasta/ab4606ff134e709c3b2cad6055d99b1f
title: Hourly Meteorological Data for the Virginia Coast Reserve LTER 1989-present

description: Data from VCR/LTER meteorological stations is listed in comma-separated-value (CSV) files by year. A combined file for all years is also available, sorted by station, date and time, however, unlike the annual files, this combined file is too large for most spreadsheets to handle. A compressed copy of all the .CSV files is included in a single .ZIP file for users who wish to conveniently download a copy of all the data.
DOI: 10.6084/m9.figshare.23223347
title: AUCell values regulons B-cells tonsil atlas

description: This file contains the AUCell values calculated by pySCENIC for the different regulons inferred in B-cells of the tonsil atlas
DOI: 10.5281/zenodo.7973395
title: CausalOrca: An ORCA-based Diagnostic Dataset for Causally-aware Multi-agent Trajectory Prediction

description: CausalOrca is a synthetic diagnostic dataset created through controlled simulations. It is designed to provide annotations of ground-truth causal effects and fine-grained agent categories for social interactions in multi-agent scenarios. The dataset is constructed using a modified RVO2 simulator and incorporates the ORCA optimization-based collision avoidance algorithm known for crowd simulation. With full control over scene configurations, the dataset enables the collection of motion behaviors in paired scenes before and after agent removal, generating a large set of counterfactual pairs with annotations of ground-truth causal effects. CausalOrca can serve as a valuable resource for studying and developing causally-aware neural representations of social interactions and trajectory prediction models. Please see the GitHub repository for a more detailed description of the dataset, including dataset statistics and documentation on how to use, visualize, and generate the data.
DOI: 10.5281/zenodo.7973394
title: CausalOrca: An ORCA-based Diagnostic Dataset for Causally-aware Multi-agent Trajectory Prediction

description: CausalOrca is a synthetic diagnostic dataset created through controlled simulations. It is designed to provide annotations of ground-truth causal effects and fine-grained agent categories for social interactions in multi-agent scenarios. The dataset is constructed using a modified RVO2 simulator and incorporates the ORCA optimization-based collision avoidance algorithm known for crowd simulation. With full control over scene configurations, the dataset enables the collection of motion behaviors in paired scenes before and after agent removal, generating a large set of counterfactual pairs with annotations of ground-truth causal effects. CausalOrca can serve as a valuable resource for studying and developing causally-aware neural representations of social interactions and trajectory prediction models. Please see the GitHub repository for a more detailed description of the dataset, including dataset statistics and documentation on how to use, visualize, and generate the data.
DOI: 10.5519/qd.f2fo965f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (80 records)
DOI: 10.5517/ccdc.csd.cc2dbw1p
title: CCDC 2214982: Experimental Crystal Structure Determination

description: Related Article: Cheng Liu, Kaiqi Ye, Huan Xiao, Yuan Yue, Jingbo Sun, Ran Lu|2023|J.Mater.Chem.C|11|6635|doi:10.1039/D3TC00740E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dbw2q
title: CCDC 2214983: Experimental Crystal Structure Determination

description: Related Article: Cheng Liu, Kaiqi Ye, Huan Xiao, Yuan Yue, Jingbo Sun, Ran Lu|2023|J.Mater.Chem.C|11|6635|doi:10.1039/D3TC00740E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dbw3r
title: CCDC 2214984: Experimental Crystal Structure Determination

description: Related Article: Cheng Liu, Kaiqi Ye, Huan Xiao, Yuan Yue, Jingbo Sun, Ran Lu|2023|J.Mater.Chem.C|11|6635|doi:10.1039/D3TC00740E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dbw4s
title: CCDC 2214985: Experimental Crystal Structure Determination

description: Related Article: Cheng Liu, Kaiqi Ye, Huan Xiao, Yuan Yue, Jingbo Sun, Ran Lu|2023|J.Mater.Chem.C|11|6635|doi:10.1039/D3TC00740E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dlgwc
title: CCDC 2222293: Experimental Crystal Structure Determination

description: Related Article: Kenta Maeda, Sayaka Ohrui, Akihisa Tokuda, Yasuyuki Nagumo, Naoshi Yamamoto, Ryuji Tanimura, Tsuyoshi Saitoh, Noriki Kutsumura, Hiroshi Nagase|2023|Org.Lett.|25|3407|doi:10.1021/acs.orglett.3c00956
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dq7v7
title: CCDC 2225919: Experimental Crystal Structure Determination

description: Related Article: Kai Oberdorf, Pauline Pfister, Patrick Grenzer, Jacqueline Ramler, Anna Hanft, Andreas Stoy, Xiulan Xie, Crispin Lichtenberg|2023|Organometallics|42|885|doi:10.1021/acs.organomet.2c00629
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dq7w8
title: CCDC 2225920: Experimental Crystal Structure Determination

description: Related Article: Kai Oberdorf, Pauline Pfister, Patrick Grenzer, Jacqueline Ramler, Anna Hanft, Andreas Stoy, Xiulan Xie, Crispin Lichtenberg|2023|Organometallics|42|885|doi:10.1021/acs.organomet.2c00629
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dq7x9
title: CCDC 2225921: Experimental Crystal Structure Determination

description: Related Article: Kai Oberdorf, Pauline Pfister, Patrick Grenzer, Jacqueline Ramler, Anna Hanft, Andreas Stoy, Xiulan Xie, Crispin Lichtenberg|2023|Organometallics|42|885|doi:10.1021/acs.organomet.2c00629
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dq7yb
title: CCDC 2225922: Experimental Crystal Structure Determination

description: Related Article: Kai Oberdorf, Pauline Pfister, Patrick Grenzer, Jacqueline Ramler, Anna Hanft, Andreas Stoy, Xiulan Xie, Crispin Lichtenberg|2023|Organometallics|42|885|doi:10.1021/acs.organomet.2c00629
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.