cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20338536.v5
title: TNBC Data from Wu et al, 2021

description: Anndata format of the TNBC data set generated by Wu et al, 2021, together with inferred cytokine activity, as described in Dimitrov et al, 2022.<br> <br> <br> Wu, S.Z., Al-Eryani, G., Roden, D.L., Junankar, S., Harvey, K., Andersson, A., Thennavan, A., Wang, C., Torpy, J.R., Bartonicek, N. and Wang, T., 2021. A single-cell and spatially resolved atlas of human breast cancers. <em>Nature genetics</em>, <em>53</em>(9), pp.1334-1347.<br> <br> Dimitrov, D., Türei, D., Garrido-Rodriguez, M., Burmedi, P.L., Nagai, J.S., Boys, C., Ramirez Flores, R.O., Kim, H., Szalai, B., Costa, I.G. and Valdeolivas, A., 2022. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. <em>Nature Communications</em>, <em>13</em>(1), pp.1-13.
DOI: 10.5519/qd.cogy7ql2
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (6229 records)
DOI: 10.5281/zenodo.6965553
title: Location Decision

description: This dataset gathers the replies of a conjoint experiment conducted online on 1'596 respondents leading to 15'960 cases in total.<br> The data assess what drives immigrants' intentions as regards residential location choice and, thus, comprise different factors playing a role in residential location choice (e.g. political factors, access to nature, living costs, public transport, facilities). Each respondent had to decide in which commune s/he would better settle in. In total, 5 vignettes comparing two municipalities were presented to respondent.
DOI: 10.5281/zenodo.6965552
title: Location Decision

description: This dataset gathers the replies of a conjoint experiment conducted online on 1'596 respondents leading to 15'960 cases in total.<br> The data assess what drives immigrants' intentions as regards residential location choice and, thus, comprise different factors playing a role in residential location choice (e.g. political factors, access to nature, living costs, public transport, facilities). Each respondent had to decide in which commune s/he would better settle in. In total, 5 vignettes comparing two municipalities were presented to respondent.
DOI: 10.6084/m9.figshare.20448249
title: RAW DATA TAMBAHAN NATA DE CAULERPA.xlsx

description: RAW Data for Nata De Caulerpa: <strong>Amelioration of Nutritional Status Biomarker in Malnourished Rats by Fermented Sea grapes: A Randomized Preclinical Study</strong>
DOI: 10.6084/m9.figshare.20448249.v1
title: RAW DATA TAMBAHAN NATA DE CAULERPA.xlsx

description: RAW Data for Nata De Caulerpa: <strong>Amelioration of Nutritional Status Biomarker in Malnourished Rats by Fermented Sea grapes: A Randomized Preclinical Study</strong>
DOI: 10.6084/m9.figshare.19870228
title: Plant_height_measurements_across_all_years

description: In total, 384 (96 x 4) individual plants out of approximately 20,000 (5,000 x 4) plants were measured in all four subpopulations. Based on these single plant height measurements, a truncation threshold corresponding to approximately the 5% shortest or 5% tallest plants were calculated for each subpopulation. Two subpopulations were selected for short plants, and two were selected for tall plants. Only the ~ 5% shortest/tallest plants from each subpopulation were harvested as females to generate the next generation. This procedure was repeated in 2017, 2018 and 2020. Ultimately, we generated four experimentally evolved subpopulations, two comprised of short-selected plants and two comprised of tall-selected plants. The plant height measurements from all those 384 single plants in 2016, 2017, 2018 and 2020 are contained in this data set.
DOI: 10.6084/m9.figshare.19870228.v1
title: Plant_height_measurements_across_all_years

description: In total, 384 (96 x 4) individual plants out of approximately 20,000 (5,000 x 4) plants were measured in all four subpopulations. Based on these single plant height measurements, a truncation threshold corresponding to approximately the 5% shortest or 5% tallest plants were calculated for each subpopulation. Two subpopulations were selected for short plants, and two were selected for tall plants. Only the ~ 5% shortest/tallest plants from each subpopulation were harvested as females to generate the next generation. This procedure was repeated in 2017, 2018 and 2020. Ultimately, we generated four experimentally evolved subpopulations, two comprised of short-selected plants and two comprised of tall-selected plants. The plant height measurements from all those 384 single plants in 2016, 2017, 2018 and 2020 are contained in this data set.
DOI: 10.6084/m9.figshare.19794673
title: Exploring language proficiency through Recurrence Quantification Analysis (RQA)

description: Recurrence Quantification Analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. By manipulating a writing task (writing in L1 or a foreign language), and using language proficiency and typing skill information, we aimed to illustrate how outcome measures of RQA can be understood as skill-driven constraints on keyboard typing performance. We assumed more fluent and skilled writing to reveal more structured typing time series patterns. Accordingly, we expected writing in a well-mastered first language to coincide with higher values in relevant RQA measures in contrast to writing in a foreign language. Further, we expected typing patterns to reveal more regularities whenever conventional variables exploring pauses, bursts, or revisions indicate more fluent writing processes. 40 native German students (Mage = 23.8, SD = 3.04, 19 female) performed two standardized writing assignments, one in German and one in English in a counterbalanced within-subjects design. To reduce learning effects while maintaining the comparability of each task design, we developed two prompted writing assignments that featured the description of two different aspects: a known procedure, the preparation of a meal, and a known and visible object, the flat the participants currently lived in. Further, we assessed language proficiency levels with a standardized cloze test and typing skills with a standardized copy task. The data was derived from keystroke logging protocols, recorded with Inputlog 8 (www.inputlog8.net). The log files were individually time-filtered using the pre-processing time filter of Inputlog to remove noise at the beginning and the end of each writing process and analyze the actual text production from the first to the last character or revision only. The resulting data set was used for a pause, burst, and revision analysis (with a pause threshold &gt; 2000ms), and RQA. RQA was performed using the crqa-package in R (Coco & Dale, 2014). The pause time between each keystroke served as the target event for RQA.The delay and the embedding parameters were estimated based on the AMI and FNN functions for each time series. Averaging the obtained values resulted in a delay parameter <em>t</em> = 1, and an embedding parameter <em>m</em> = 7. Furthermore, we chose a threshold parameter <em>r</em> = 300, yielding an average recurrence rate between 1 % and 5 % across time series. After, we computed the most common RQA measures: recurrence rate, determinism rate, average diagonal line length, maximum diagonal line length, entropy, laminarity, and trapping time. <br> <br> <br>
DOI: 10.6084/m9.figshare.19794673.v1
title: Exploring language proficiency through Recurrence Quantification Analysis (RQA)

description: Recurrence Quantification Analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. By manipulating a writing task (writing in L1 or a foreign language), and using language proficiency and typing skill information, we aimed to illustrate how outcome measures of RQA can be understood as skill-driven constraints on keyboard typing performance. We assumed more fluent and skilled writing to reveal more structured typing time series patterns. Accordingly, we expected writing in a well-mastered first language to coincide with higher values in relevant RQA measures in contrast to writing in a foreign language. Further, we expected typing patterns to reveal more regularities whenever conventional variables exploring pauses, bursts, or revisions indicate more fluent writing processes. 40 native German students (Mage = 23.8, SD = 3.04, 19 female) performed two standardized writing assignments, one in German and one in English in a counterbalanced within-subjects design. To reduce learning effects while maintaining the comparability of each task design, we developed two prompted writing assignments that featured the description of two different aspects: a known procedure, the preparation of a meal, and a known and visible object, the flat the participants currently lived in. Further, we assessed language proficiency levels with a standardized cloze test and typing skills with a standardized copy task. The data was derived from keystroke logging protocols, recorded with Inputlog 8 (www.inputlog8.net). The log files were individually time-filtered using the pre-processing time filter of Inputlog to remove noise at the beginning and the end of each writing process and analyze the actual text production from the first to the last character or revision only. The resulting data set was used for a pause, burst, and revision analysis (with a pause threshold &gt; 2000ms), and RQA. RQA was performed using the crqa-package in R (Coco & Dale, 2014). The pause time between each keystroke served as the target event for RQA.The delay and the embedding parameters were estimated based on the AMI and FNN functions for each time series. Averaging the obtained values resulted in a delay parameter <em>t</em> = 1, and an embedding parameter <em>m</em> = 7. Furthermore, we chose a threshold parameter <em>r</em> = 300, yielding an average recurrence rate between 1 % and 5 % across time series. After, we computed the most common RQA measures: recurrence rate, determinism rate, average diagonal line length, maximum diagonal line length, entropy, laminarity, and trapping time. <br> <br> <br>
DOI: 10.5281/zenodo.6973316
title: Renaissance Benchmark Results for OpenJDK, HotSpot and GraalVM

description: The Renaissance Benchmark Suite is an open source collaborative benchmark project where the community can propose and improve benchmark workloads. This archive contains a collection of benchmark results collected on multiple JVM implementations.<br> <br> The measurements in this archive were collected using Renaissance 0.14.1, OpenJDK 11.0.16, OpenJDK 17.0.4, HotSpot 11.0.16, HotSpot 17.0.4 and GraalVM 22.2.
DOI: 10.5281/zenodo.6973315
title: Renaissance Benchmark Results for OpenJDK, HotSpot and GraalVM

description: The Renaissance Benchmark Suite is an open source collaborative benchmark project where the community can propose and improve benchmark workloads. This archive contains a collection of benchmark results collected on multiple JVM implementations.<br> <br> The measurements in this archive were collected using Renaissance 0.14.1, OpenJDK 11.0.16, OpenJDK 17.0.4, HotSpot 11.0.16, HotSpot 17.0.4 and GraalVM 22.2.
DOI: 10.48366/r209290
title: Overview of the motion trajectories datasets

description: Evaluating the performance of a motion prediction algorithm requires choosing appropriate testing scenarios and accuracy metrics, as well as studying the method’s robustness against various variables, such as the number of interacting agents or amount of maneuvering in the data. Depending on the application area, the testing scenario maybe an intersection, a highway, a pedestrian crossing, shared urban street with heterogeneous agents, a home environment, or a crowded public space. Existing datasets, summarized in this comparison
DOI: 10.5281/zenodo.6973274
title: Some research data on magnetic unstable zone

description: This file set contains data for each image in the study of magnetic unstable zone
DOI: 10.6084/m9.figshare.20438595
title: Predicting the distribution of plant associations under climate change: A case study on Larix gmelinii in China

description: We used a Maxent model and the ArcGIS software to project the potential geographical distribution of <em>L. gmelinii</em> associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. The causes of for the changes in spatial distribution were analyzed using multinomial logistic regression analysis.
DOI: 10.6084/m9.figshare.20438595.v1
title: Predicting the distribution of plant associations under climate change: A case study on Larix gmelinii in China

description: We used a Maxent model and the ArcGIS software to project the potential geographical distribution of <em>L. gmelinii</em> associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. The causes of for the changes in spatial distribution were analyzed using multinomial logistic regression analysis.
DOI: 10.23729/9ed5b893-eef9-4792-9f05-c59919d65758
title: 3D Library Set 3 Preview

description: Third set of structures for the GTK 3D structure library, intended to act as a database for geoinspired design projects. Samples are scanned only to add their structure to the library, with no other direct research interest. Preview of PAS dataset https://doi.org/10.23729/b85f3e7a-4ebd-4a90-b811-8ee390cc1121 Collective preview entry: https://doi.org/10.23729/a0df5931-b5da-49dd-8369-f54928bd23a7
DOI: 10.5281/zenodo.6674852
title: Biogenic signals from plastids and their role in chloroplast development

description: <strong>Chloroplast Defective Mutants</strong> The mutant collection was done starting from the Myouga et al (2013) chloroplast database. All the genes in their list were confirmed or removed, depending on the updated and available information in literature.<br> Genes not present in the Myouga database were taken from literature, based on the tables from the two publications from Tadini et al (2020). Additional genes were searched in the literature. Table structure. Detailed information for the mutant characterisation were taken from the main plant databases (TAIR and UniProt) and the corresponding literature.<br> The table is structured in a way to give an insight into the molecular function of the gene and a description of the mutant phenotype (for both if information was available).<br> The worksheet "Chloroplast Defective Mutants" contains all the mutants sorted by locus.<br> The worksheet "Mutants included in Fig.1" depicts all mutants with impairment in essential processes for chloroplast biogenesis and their phenotype is schematically represented with coloured squares in Figure 1.<br> The last worksheet contains the pie charts, in which the impacts of the main biological functions on the phenotype are visualized. References: -Myouga F, Akiyama K, Tomonaga Y, Kato A, Sato Y, Kobayashi M, Nagata N, Sakurai T, Shinozaki K. The Chloroplast Function Database II: a comprehensive collection of homozygous mutants and their phenotypic/genotypic traits for nuclear-encoded chloroplast proteins. Plant Cell Physiol (2013) http://di.org/0.1093/pcp/pcs171<br> -Tadini L, Jeran N and Pesaresi P, GUN1 and Plastid RNA Metabolism: Learning from Genetics. Cells (2020), 9(10), 2307; https://doi.org/10.3390/cells9102307<br> -Tadini L, Jeran N, Peracchio C, Masiero S, Colombo M and Pesaresi P, The plastid transcription machinery and its coordination with the expression of nuclear genome: Plastid-Encoded Polymerase, Nuclear-Encoded Polymerase and the Genomes Uncoupled 1-mediated retrograde communication. Phil. Trans. R. Soc. (2020) http://doi.org/10.1098/rstb.2019.0399
description: {"references": ["Myouga F, Akiyama K, Tomonaga Y, Kato A, Sato Y, Kobayashi M, Nagata N, Sakurai T, Shinozaki K. The Chloroplast Function Database II: a comprehensive collection of homozygous mutants and their phenotypic/genotypic traits for nuclear-encoded chloroplast proteins. Plant Cell Physiol\u00a0(2013)\u00a0http://di.org/0.1093/pcp/pcs171", "Tadini L,\u00a0Jeran N and Pesaresi P,\u00a0GUN1 and Plastid RNA Metabolism: Learning from Genetics.\u00a0Cells\u00a0(2020),\u00a09(10), 2307;\u00a0https://doi.org/10.3390/cells9102307", "Tadini L, Jeran N, Peracchio C, Masiero S, Colombo\u00a0M and Pesaresi P, The plastid transcription machinery and its coordination with the expression of nuclear genome: Plastid-Encoded Polymerase, Nuclear-Encoded Polymerase and the Genomes Uncoupled 1-mediated retrograde communication.\u00a0Phil. Trans. R. Soc. (2020)\u00a0http://doi.org/10.1098/rstb.2019.0399"]}
DOI: 10.5281/zenodo.6674851
title: Biogenic signals from plastids and their role in chloroplast development

description: <strong>Chloroplast Defective Mutants</strong> The mutant collection was done starting from the Myouga et al (2013) chloroplast database. All the genes in their list were confirmed or removed, depending on the updated and available information in literature.<br> Genes not present in the Myouga database were taken from literature, based on the tables from the two publications from Tadini et al (2020). Additional genes were searched in the literature. Table structure. Detailed information for the mutant characterisation were taken from the main plant databases (TAIR and UniProt) and the corresponding literature.<br> The table is structured in a way to give an insight into the molecular function of the gene and a description of the mutant phenotype (for both if information was available).<br> The worksheet "Chloroplast Defective Mutants" contains all the mutants sorted by locus.<br> The worksheet "Mutants included in Fig.1" depicts all mutants with impairment in essential processes for chloroplast biogenesis and their phenotype is schematically represented with coloured squares in Figure 1.<br> The last worksheet contains the pie charts, in which the impacts of the main biological functions on the phenotype are visualized. References: -Myouga F, Akiyama K, Tomonaga Y, Kato A, Sato Y, Kobayashi M, Nagata N, Sakurai T, Shinozaki K. The Chloroplast Function Database II: a comprehensive collection of homozygous mutants and their phenotypic/genotypic traits for nuclear-encoded chloroplast proteins. Plant Cell Physiol (2013) http://di.org/0.1093/pcp/pcs171<br> -Tadini L, Jeran N and Pesaresi P, GUN1 and Plastid RNA Metabolism: Learning from Genetics. Cells (2020), 9(10), 2307; https://doi.org/10.3390/cells9102307<br> -Tadini L, Jeran N, Peracchio C, Masiero S, Colombo M and Pesaresi P, The plastid transcription machinery and its coordination with the expression of nuclear genome: Plastid-Encoded Polymerase, Nuclear-Encoded Polymerase and the Genomes Uncoupled 1-mediated retrograde communication. Phil. Trans. R. Soc. (2020) http://doi.org/10.1098/rstb.2019.0399
description: {"references": ["Myouga F, Akiyama K, Tomonaga Y, Kato A, Sato Y, Kobayashi M, Nagata N, Sakurai T, Shinozaki K. The Chloroplast Function Database II: a comprehensive collection of homozygous mutants and their phenotypic/genotypic traits for nuclear-encoded chloroplast proteins. Plant Cell Physiol\u00a0(2013)\u00a0http://di.org/0.1093/pcp/pcs171", "Tadini L,\u00a0Jeran N and Pesaresi P,\u00a0GUN1 and Plastid RNA Metabolism: Learning from Genetics.\u00a0Cells\u00a0(2020),\u00a09(10), 2307;\u00a0https://doi.org/10.3390/cells9102307", "Tadini L, Jeran N, Peracchio C, Masiero S, Colombo\u00a0M and Pesaresi P, The plastid transcription machinery and its coordination with the expression of nuclear genome: Plastid-Encoded Polymerase, Nuclear-Encoded Polymerase and the Genomes Uncoupled 1-mediated retrograde communication.\u00a0Phil. Trans. R. Soc. (2020)\u00a0http://doi.org/10.1098/rstb.2019.0399"]}
DOI: 10.5281/zenodo.6973353
title: Dataset of micromagnetic simulations on magnetic unstable zone (#2022JB024876)

description: The files attached below are all the raw data that support the figures in paper #2022JB024876.
DOI: 10.6084/m9.figshare.19666521.v1
title: Guerrini et al. Supplemental Table S1

description: Table listing genes associated with DEEs
DOI: 10.6084/m9.figshare.17694728.v1
title: Guerrini et al. Supplemental Table S2.xlsx

description: Supplemental Table S2. Clinical trials on Dravet syndrome.
DOI: 10.5281/zenodo.6973367
title: Draft Genome sequencing of Nocardia sp. strain WB46 Isolated from Salix purpurea Growing in a Site Chronically Contaminated by Petroleum Hydrocarbons

description: Assembled contigs of the genome of <em>Nocardia</em> sp. strain WB46 isolated from <em>the rhizosphere of Salix purpurea </em>growing in a site chronically contaminated by petroleum hydrocarbons located at Varennes, Qubec, Canada.
DOI: 10.5281/zenodo.6973366
title: Draft Genome sequencing of Nocardia sp. strain WB46 Isolated from Salix purpurea Growing in a Site Chronically Contaminated by Petroleum Hydrocarbons

description: Assembled contigs of the genome of <em>Nocardia</em> sp. strain WB46 isolated from <em>the rhizosphere of Salix purpurea </em>growing in a site chronically contaminated by petroleum hydrocarbons located at Varennes, Qubec, Canada.
DOI: 10.5258/soton/d2291
title: Dataset for paper titled Experimental observations on turbulent boundary layers subjected to a step-change in surface roughness

description: This dataset supports the publication: "Experimental observations on turbulent boundary layers subjected to a step-change in surface roughness", Melika Gul and Bharathram Ganapathisubramani, Journal of Fluid Mechanics, 2022 DOI: doi:10.1017/jfm.2022.608 The data is presented for each figure containing important data in the paper (filenames are given accordingly). Using the data provided and normalisation parameters (where applicable), the plots in the paper could be reproduced. The quantities that are presented in the plots are explained in the Definition sheet of each data file. Further Information regarding the data files: 1. Common data for the data sets is provided in CommonData.xlsx. 2. Data for figure 2 is given in Fig2.xlsx. 3. Data for figure 3 is given in Fig3.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 4. Data for figure 4 is given in Fig4.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 5. Data for figure 5 is given in Fig5.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 6. Data for figure 6 is given in Fig6.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 7. Data for figure 7 is given in Fig7.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 8. Data for figure 8 is given in Fig8.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 9. Data for figure 9 is given in Fig9.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 10. Data for figure 10 is given in Fig10.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns in each sheet. 11. Data for figure 11 is given in Fig11.xlsx. The subfigures are presented in separate sheets, while comparison of cases in each subfigure is presented in different columns or rows in each sheet. Date of data collection: 07/2019 Licence: CC BY Related projects:EP/P009638/1 and EP/R034370/1
DOI: 10.5281/zenodo.6973422
title: Dataset of micromagnetic simulations on magnetic unstable zone (#2022JB024876)

description: The files attached below are all the raw data that support the figures in paper #2022JB024876.