cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30740195.v1
title: Data from "Predicting future grant amounts using topic-level features"

description: Data from the research paper "Predicting future grant amounts using topic-level features", presented at the 29th STI-ENID conference in Bristol, UK, September 4, 2025.The file contains 1106 rows (excluding the header) and 21 columns, in a tab-separated format (.tsv). The columns are listed below. Note:Each row corresponds to one (level 3) topicAll observations are aggregated at this levelThe level 1 topics were used as a grouping variable in the analysisLag: this is a lagged panel dataset. The variable <i>total_lagged_eur</i> was calculated for the time-period 2021 to 2023 (inclusive), while the other variables were calculated for the years 2015 to 2020 (inclusive).<br>topic_label (str): a level 3 (ANZSRC FoR) category for_l1 (str): a level 1 (ANZSRC FoR) categorysize (int): number of publications in the level 3 topictif (float): topic impact factorn_policy_doc_citations (int): number of citations from policy documents to papers in the topicn_clinical_trial_citations (int): number of clinical trials linked to the topicn_patent_citations (int): number of citations from patents to papers in the topictotal_lagged_eur (float): the fractional, lagged grant amount in euros for the topic log_total_lagged_eur (float): natural logarithm of <i>total_lagged_eur</i>log_size (float): natural logarithm of <i>size</i>log_policy (float): natural logarithm of <i>n_policy_doc_citations</i>log_trials (float): natural logarithm of <i>n_clinical_trial_citations</i>log_patents (float): natural logarithm of <i>n_patent_citations</i>n_l3_siblings (int): the number of other level 3 topics that belong to the same level 2 parent topictotal_authors (int): total author contributions, calculated by summing the total number of authors per paper in the topicun_authors (int): the total number of unique authors publishing in the topicauthor_ttr (float): <i>un_authors</i> divided by <i>total_authors</i>, in analogy with the type-token ratio in linguisticspreds (float): predicted log grant amounts, using a linear mixed-effects regression modelpred_obs_diff (float): difference between observed grant sum and the predicted sumsd2diff (bool): boolean indicating whether <i>pred_obs_diff</i> is greater (true) than 2 standard deviations from the mean or not (false)ou_funded (str): a string indicating if the topic is over-funded (labelled "Over") or under-funded (labelled "Under") when comparing the predicted funding (<i>preds</i>) with the actual funding amount. The majority of topics have predicted values very close to the observed funding values (labelled "Expected")For details about the topic data, see: https://www.researchsquare.com/article/rs-6529718/v1. The other datapoints are calculated based on the <i>Dimensions</i> database.<br>
DOI: 10.5281/zenodo.17775805
title: The positive effects of canopy openness across post-disturbance management on insect diversity

description: This data set contains metabarcoding data of insects from forest sites in Bavaria, Germany, a phlyogenetic tree for all OTUs and R code to calculate taxonomic and phylogenetic diversity. The code contains models used in the publication by Kortmann et al. 2025 in Biological Conservation.
DOI: 10.5281/zenodo.17775804
title: The positive effects of canopy openness across post-disturbance management on insect diversity

description: This data set contains metabarcoding data of insects from forest sites in Bavaria, Germany, a phlyogenetic tree for all OTUs and R code to calculate taxonomic and phylogenetic diversity. The code contains models used in the publication by Kortmann et al. 2025 in Biological Conservation.
DOI: 10.15468/dl.kem5x6
title: Occurrence Download

description: A dataset containing 5936 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Castanediella",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5936 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020091-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.20387/bonares-310w-sna1
title: Phenotypic traits, drought responses, and growth parameters of 38 temperate maize varieties under well-watered and drought-stressed conditions in a greenhouse experiment

description: Plant traits of 38 temperate maize varieties from a greenhouse experiment were derived. The plant traits encompass three major types of parameters: 1) phenotypic traits, such as biomass weight and biomass allocation, used for deriving phenotypic plasticity, 2) drought responses, parameters that indicate the sensitivity of plant response to soil drying, 3) growth parameters, referring to the projected area of plant measured throughout the experiment. The data were derived from the biomass samples harvested at the end of the experiment, as well as from the visible light images collected at the interval of 1–2 days with the high-throughput phenotyping facility. The 38 maize varieties include landraces, hybrids, and open-pollinated varieties from Central Europe.
The maize plants were grown in mesocosms and replicated four times per variety per treatment. Each mesocosm contained two plants, and the mean value of the two plants was taken for each parameter in this dataset. Drought treatment was applied on half of the plants 37 days after sowing by stopping irrigation. The other half of the plants were well-watered, with the mean soil water potential −60 hPa.


Research domain: Plant Cultivation and Agricultural Technology

Research question: 1)	What are the most plastic and the least plastic traits of temperate maize under drought stress?
2)	How do phenotypic plasticity, drought responsiveness, and drought tolerance correlate with one another?
3)	Do landraces differ from modern varieties in terms of phenotypic plasticity, drought responsiveness, and drought tolerance?
DOI: 10.6084/m9.figshare.28604886
title: Inference on multicomponent stress-strength model using progressively censored data from exponentiated Pareto distribution

description: This article deals with the Bayesian and classical estimation approaches for the reliability of stress-strength of a multicomponent system assuming both the stress and strength variables follow exponentiated Pareto distribution independently based on the progressively censored data. In the classical estimation, the maximum likelihood estimate, asymptotic confidence and two bootstrap confidence intervals boot-t \amp boot-p are constructed for multicomponent stress-strength (MSS) reliability. In the Bayesian estimation, the Bayes estimates under the squared error loss function using Markov chain Monte Carlo (MCMC) techniques are obtained. The highest posterior density credible interval based on the MCMC method of the MSS reliability are constructed. The different estimates obtained are compared using a Monte Carlo simulation study which is carried out for various sample sizes and different censoring schemes. Two different real data sets are studied to illustrate the real-life applications of the study. Finally, the conclusions based on the study with the future scope of the work are provided.
DOI: 10.6084/m9.figshare.28604886.v1
title: Inference on multicomponent stress-strength model using progressively censored data from exponentiated Pareto distribution

description: This article deals with the Bayesian and classical estimation approaches for the reliability of stress-strength of a multicomponent system assuming both the stress and strength variables follow exponentiated Pareto distribution independently based on the progressively censored data. In the classical estimation, the maximum likelihood estimate, asymptotic confidence and two bootstrap confidence intervals boot-t \amp boot-p are constructed for multicomponent stress-strength (MSS) reliability. In the Bayesian estimation, the Bayes estimates under the squared error loss function using Markov chain Monte Carlo (MCMC) techniques are obtained. The highest posterior density credible interval based on the MCMC method of the MSS reliability are constructed. The different estimates obtained are compared using a Monte Carlo simulation study which is carried out for various sample sizes and different censoring schemes. Two different real data sets are studied to illustrate the real-life applications of the study. Finally, the conclusions based on the study with the future scope of the work are provided.
DOI: 10.15468/dl.vfrve6
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "OccurrenceStatus is Present",
 "TaxonKey is Suregada lanceolata"
 ]
}

 The dataset includes 68 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020093-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/vnkn-t830
title: "Efficient-Empathy"

description: "Empathy is a fundamental pillar of human social intelligence and a critical requirement for the development of human-centered artificial general intelligence (AGI). While large language models (LLMs) have shown remarkable general-purpose capabilities, their empathetic reasoning remains limited, largely due to the scarcity of high-quality training data. Prior work in empathetic modeling often relies on shallow emotional cues or architectural enhancements, overlooking the heterogeneous and multi-dimensional nature of empathy itself. In this work, we propose a data-efficient empathy learning framework that integrates insights from psychology\u2014specifically, the dual dimensions of sensibility and rationality\u2014as guiding criteria for high-quality data selection. Our approach leverages LLMs to automatically score and filter empathy dialogues, constructing curated datasets that prioritize emotionally grounded and cognitively coherent responses. We then train specialized sensibility and rationality experts, and dynamically combine their capabilities via a Mixture-of-Experts (MoE) model. Empirical results demonstrate that our framework not only achieves state-of-the-art empathetic generation but does so using significantly fewer data samples, affirming the importance of quality-driven data selection for scaling empathetic AGI. "
DOI: 10.15468/dl.r4wcy6
title: Occurrence Download

description: A dataset containing 772 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptothyrium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 772 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020095-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2my61v
title: CCDC 2441127: Experimental Crystal Structure Determination

description: Related Article: Firas KRICHEN, Siwar WALHA, Sandy AUGUSTE, Jérôme LHOSTE|2026|J.Mol.Struct.|1353||doi:10.1016/j.molstruc.2025.144624
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.cc2my6xq
title: CCDC 2441154: Experimental Crystal Structure Determination

description: Related Article: Ilya V. Okladnikov, Roman S. Malykhin, Vladislav K. Lesnikov, Alexey Yu. Sukhorukov|2025|Org.Lett.|||doi:10.1021/acs.orglett.5c04140
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.cc2my6yr
title: CCDC 2441155: Experimental Crystal Structure Determination

description: Related Article: Ilya V. Okladnikov, Roman S. Malykhin, Vladislav K. Lesnikov, Alexey Yu. Sukhorukov|2025|Org.Lett.|||doi:10.1021/acs.orglett.5c04140
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: 10.5281/zenodo.17669816
title: BIOSPHERE measurement campaign from January 2024 to March 2024 and in May 2024: Effects of the solar events on the radiation belts, UV radiation and ozone in the atmosphere: dataset

description: This is part of the data presented in the paper "BIOSPHERE measurement campaign from January 2024 to March 2024 and in May 2024: Effects of the solar events on the radiation belts, UV radiation and ozone in the atmosphere". 

-> The EPT files contain the differential flux observed by the energetic particle telescope (EPT)  from January 1st 2024 to March 31th 2024. Differential fluxes are given in [(s cm² sr MeV)^-1].

-> The OMNI file contains the some of the data from the omni database fir the corresponding period.-> The mls file contains the ozone data from the MLS/AURA stored in a netcdf file that can be easily read with the xarray python library.

More data can be found at:

Omni data are provided by https://omniweb.gsfc.nasa.gov/html/ow_data.htmlMLS/Aura data of ozone are accessible at https://disc.gsfc100.nasa.gov/datasets/ML2O3_005/summaryEPT data are publicly available on the Space Situational Awareness website of ESA http://swe.ssa.esa.int/space-radiation

 

Project: 21GRD02 BIOSPHERE The project (21GRD02 BIOSPHERE) has received funding from the European Partnership on Metrology, co-financed by the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States. Funded by the European Union.
DOI: 10.5517/ccdc.csd.cc2mygkm
title: CCDC 2441391: Experimental Crystal Structure Determination

description: Related Article: Zhuo Gao, Jiaoyang Gao, Kang Li, Haibo Fan, Feng Teng, Hui Jiang, Xuexia He, Peng Hu|2025|Cryst.Growth Des.|||doi:10.1021/acs.cgd.5c01353
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.cc2mygln
title: CCDC 2441392: Experimental Crystal Structure Determination

description: Related Article: Zhuo Gao, Jiaoyang Gao, Kang Li, Haibo Fan, Feng Teng, Hui Jiang, Xuexia He, Peng Hu|2025|Cryst.Growth Des.|||doi:10.1021/acs.cgd.5c01353
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.cc2myzl5
title: CCDC 2441888: Experimental Crystal Structure Determination

description: Related Article: Masayuki Iwabuchi, Miku Yoshida, Daichi Ando, Shigeki Mori, Tetsuo Okujima, Ryuta Sekiguchi, Shunji Ito, Masafumi Yasunami, Taku Shoji|2025|J.Org.Chem.|||doi:10.1021/acs.joc.5c01664
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.cc2myzn7
title: CCDC 2441890: Experimental Crystal Structure Determination

description: Related Article: Masayuki Iwabuchi, Miku Yoshida, Daichi Ando, Shigeki Mori, Tetsuo Okujima, Ryuta Sekiguchi, Shunji Ito, Masafumi Yasunami, Taku Shoji|2025|J.Org.Chem.|||doi:10.1021/acs.joc.5c01664
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.cc2myzq9
title: CCDC 2441892: Experimental Crystal Structure Determination

description: Related Article: Masayuki Iwabuchi, Miku Yoshida, Daichi Ando, Shigeki Mori, Tetsuo Okujima, Ryuta Sekiguchi, Shunji Ito, Masafumi Yasunami, Taku Shoji|2025|J.Org.Chem.|||doi:10.1021/acs.joc.5c01664
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.cc2mzw5p
title: CCDC 2442743: Experimental Crystal Structure Determination

description: Related Article: Ilya V. Okladnikov, Roman S. Malykhin, Vladislav K. Lesnikov, Alexey Yu. Sukhorukov|2025|Org.Lett.|||doi:10.1021/acs.orglett.5c04140
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.cc2n08zy
title: CCDC 2443140: Experimental Crystal Structure Determination

description: Related Article: Si-Jie Fan, Ying-Long Wang, Guo Wang, Gui-Xiong Guo, Zhong-Feng Li, Hong-Liang Han, Li-Xiong Dai, Jian-Ming Liu, Yue-Bing Feng, Yun Tang, Qiong-Hua Jin|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c03482
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.cc2n0pt6
title: CCDC 2443538: Experimental Crystal Structure Determination

description: Related Article: Masanori Wakizaka, Tairiku Fujino, Xin Zheng, Shin-ichiro Noro|2025|Cryst.Growth Des.|||doi:10.1021/acs.cgd.5c00823
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.cc2n10tk
title: CCDC 2443848: Experimental Crystal Structure Determination

description: Related Article: Naoki Ito, Toshio Nishino, Jérôme Cuny, Shohei Katao, Kazuma Yasuhara, Gwénaël Rapenne|2025|ACS Org. Inorg. Au|||doi:10.1021/acsorginorgau.5c00100
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.cc2n10vl
title: CCDC 2443849: Experimental Crystal Structure Determination

description: Related Article: Naoki Ito, Toshio Nishino, Jérôme Cuny, Shohei Katao, Kazuma Yasuhara, Gwénaël Rapenne|2025|ACS Org. Inorg. Au|||doi:10.1021/acsorginorgau.5c00100
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.cc2n111t
title: CCDC 2443855: Experimental Crystal Structure Determination

description: Related Article: Gui-Xin Yan, Er-Xia Chen, Jin-Xia Yang, Jian Zhang, Qipu Lin|2025|Angew.Chem.,Int.Ed.|64|e202509996|doi:10.1002/anie.202509996
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.cc2n112v
title: CCDC 2443856: Experimental Crystal Structure Determination

description: Related Article: Gui-Xin Yan, Er-Xia Chen, Jin-Xia Yang, Jian Zhang, Qipu Lin|2025|Angew.Chem.,Int.Ed.|64|e202509996|doi:10.1002/anie.202509996
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.cc2jwp59
title: CCDC 2350301: Experimental Crystal Structure Determination

description: Related Article: Yuji Isshiki, Donglin Li, Saranyan Vijayaraghavan, Kewei Sun, Huynh Thien Ngo, Luiza Buimaga-Iarinca, Yoshitaka Matsushita, Edward A Neal, Cristian Morari, Jonathan P Hill, Shigeki Kawai|2025|J.Phys.Chem.Lett.|16|11833|doi:10.1021/acs.jpclett.5c03174
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.