cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18167/dvn1/g9pjjj
title: Dataset on the selection between healthy or Fusarium wilt diseased banana plant material by Cosmopolites sordidus, experiments in Costa Rica

description: This dataset is corresponding to an experiement that aimed at understanding whether Cosmopolites sordidus is preferentially attracted by Fusarium oxysporum f‧sp. cubense race 1 contaminated banana plants material than Foc-free ones. The relative attraction of healthy and Foc contaminated Gros Michel banana bulbs and pseudostems, as well as pure culture of Foc was measured using four-armed olfactometers. Males and females were studied separately. After storage in a dark room, weevils where were introduced in the central chamber of olfactometers. At 15 minutes, the orientation of each of the weevils was determined according to the food source placed in each of the chambers of the olfactometer. Overall, 560 olfactometer experiments were carried out.
DOI: 10.5281/zenodo.10025251
title: Ensemble of initial conditions for Hydro-ABC
DOI: 10.5281/zenodo.10025250
title: Ensemble of initial conditions for Hydro-ABC
DOI: 10.5281/zenodo.10025272
title: whatsnext-scores

description: This dataset contains production variability scores as described in the following paper:

Mario Giulianelli, Joris Baan, Wilker Aziz, Raquel Fernández, and Barbara Plank. 2023. What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.
We make these scores available to facilitate the reproducibility of our experiments, which can be found at https://github.com/dmg-illc/nlg-uncertainty-probes.
DOI: 10.5281/zenodo.10025271
title: whatsnext-scores

description: This dataset contains production variability scores as described in the following paper:

Mario Giulianelli, Joris Baan, Wilker Aziz, Raquel Fernández, and Barbara Plank. 2023. What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.
We make these scores available to facilitate the reproducibility of our experiments, which can be found at https://github.com/dmg-illc/nlg-uncertainty-probes.
DOI: 10.5281/zenodo.10006413
title: AltGen: 1.3M Plausible Alternatives From Neural Text Generators

description: AltGen: 1.3M Plausible Alternatives From Neural Text Generators
The AltGen dataset contains 1.3 million English texts generated by neural language generators conditioned on contexts from three corpora of acceptability judgements and two corpora of reading times. 
For each corpus, each text generator, and each sampling algorithm,100 generations are sampled—for a total of 1,257,300 generations. Details about the language generators and the corpora are presented in a paper published at EMNLP 2023 (in particular, Section 4). Please cite this paper if you use any version of the dataset in your work:

Mario Giulianelli, Sarenne Wallbridge, and Raquel Fernández. 2023. Information Value: Measuring Utterance Predictability as Distance from Plausible Alternatives. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.
The files are in jsonl format and include a context_id field, which allows retrieving the relevant entry from the original corpus, and the alternatives field, which contains the language model generations. Please note that the alternatives are not post-processed (see code and footnote 2 in the paper for further details). Filenames are built as follows: DecodingAlgorithm_DecodingParameter-nNumAlternatives-maxlen_MaxGenerationLength-sep_Separator.jsonl.
DOI: 10.5281/zenodo.10006412
title: AltGen: 1.3M Plausible Alternatives From Neural Text Generators

description: AltGen: 1.3M Plausible Alternatives From Neural Text Generators
The AltGen dataset contains 1.3 million English texts generated by neural language generators conditioned on contexts from three corpora of acceptability judgements and two corpora of reading times. 
For each corpus, each text generator, and each sampling algorithm,100 generations are sampled—for a total of 1,257,300 generations. Details about the language generators and the corpora are presented in a paper published at EMNLP 2023 (in particular, Section 4). Please cite this paper if you use any version of the dataset in your work:

Mario Giulianelli, Sarenne Wallbridge, and Raquel Fernández. 2023. Information Value: Measuring Utterance Predictability as Distance from Plausible Alternatives. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics.
The files are in jsonl format and include a context_id field, which allows retrieving the relevant entry from the original corpus, and the alternatives field, which contains the language model generations. Please note that the alternatives are not post-processed (see code and footnote 2 in the paper for further details). Filenames are built as follows: DecodingAlgorithm_DecodingParameter-nNumAlternatives-maxlen_MaxGenerationLength-sep_Separator.jsonl.
DOI: 10.5517/ccdc.csd.cc23yl5v
title: CCDC 1964847: Experimental Crystal Structure Determination

description: Related Article: Garam Choi, Ha Eun Kim, Sunjoo Hwang, Hanna Jang, Won-jin Chung|2020|Org.Lett.|22|4190|doi:10.1021/acs.orglett.0c01258
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: 10.57745/85ahzv
title: DataPYCALAB2019.docx

description: Synthèse des données aux différentes stations d’observation
DOI: 10.57745/oaau5n
title: SyntèseDataEau.tab

description: Synthèse des données obtenues pour les analyses de l'eau.
DOI: 10.57745/imo2yk
title: SynthèseBryo_Oct2018_MaiMars2019.tab

description: Synthèse des données obtenues pour les analyses des bryophytes- sessions Octobre 2018 -mars et mai 2019
DOI: 10.57745/rob5om
title: SynthèseBryoJuillet2018.xlsx

description: Synthèse des données obtenues pour les analyses des bryophytes - Juillet 2018
DOI: 10.15131/shef.data.21608490
title: Metabolomics datasets

description: Metabolomics datasets as follows: Metabolomics MDA CAF-CDM vs plastic: Non-targeted metabolomics analysis of metabolistes extracted from breast cancer cells (MDA-MB-231), grown on plastic or cancer associate fibroblasts (CAF)-generated cell derived matrix for 6 days under amino acid starvation. Metabolomics MDA coll vs plastic: MDA-MB-231 breast cancer cells grown on collagen I or plastic for 6 days under amino acid starvation. Non-targeted metabolomics dataset. Metabolomics CA1 collagen vs plastic: Non-targeted metabolomics analysis of metabolistes extracted from breast cancer cells (MCF10CA1), grown on plastic or collagen I for 6 days under amino acid starvation. Metabolomics matrigel MDA: MDA-MB-231 cells were seeded on matrigel or plastic and grown under amino acid starvation of 6 days. Metabolites were extracted and analysed by non-targeted mass spectrometry.
DOI: 10.15131/shef.data.21608490.v1
title: Metabolomics datasets

description: Metabolomics datasets as follows: Metabolomics MDA CAF-CDM vs plastic: Non-targeted metabolomics analysis of metabolistes extracted from breast cancer cells (MDA-MB-231), grown on plastic or cancer associate fibroblasts (CAF)-generated cell derived matrix for 6 days under amino acid starvation. Metabolomics MDA coll vs plastic: MDA-MB-231 breast cancer cells grown on collagen I or plastic for 6 days under amino acid starvation. Non-targeted metabolomics dataset. Metabolomics CA1 collagen vs plastic: Non-targeted metabolomics analysis of metabolistes extracted from breast cancer cells (MCF10CA1), grown on plastic or collagen I for 6 days under amino acid starvation. Metabolomics matrigel MDA: MDA-MB-231 cells were seeded on matrigel or plastic and grown under amino acid starvation of 6 days. Metabolites were extracted and analysed by non-targeted mass spectrometry.
DOI: 10.14278/rodare.2454
title: Data publication: EE+GENTOP approach with swirling flow/2 FLuid 3 Phase simulation

description: DATA: EE/GENTOP Simulation in twisted/rifle pipe considering swirling flow & 2 Fluid 3 Phase flow simulation
DOI: 10.14278/rodare.2455
title: Data publication: EE+GENTOP approach with swirling flow/2 FLuid 3 Phase simulation

description: DATA: EE/GENTOP Simulation in twisted/rifle pipe considering swirling flow & 2 Fluid 3 Phase flow simulation
DOI: 10.17632/wyg77x6n66.1
title: Study on Multi-water Sources Allocation Based on Multi-scenario potential tapping under Extreme Drought: An Example from the Yellow River Water Supply Area in Henan

description: The water supply of water resources allocation under extreme drought is insufficient, and the limited available water resources make it urgent to tap the potential of water supply. In this paper, the Yellow River water supply area in Henan Province is taken as an example to study the multi-water source allocation under extreme drought. According to the Palmer Drought Severity Index (PDSI), the extreme drought years are selected, and the water supply and demand balance in the extreme drought years is analyzed, and the water shortage degree of each water supply area is obtained. In this paper, unconventional water, flood resource utilization and elastic exploitation of groundwater are used as potential water sources. Different water supply scenarios are set up according to different potential tapping measures, and multi-scenario supply increase under extreme drought is explored. A multi-water source allocation model with the goal of minimizing water shortage is constructed, and a multi-scenario supply increase allocation scheme is proposed, which provides a basis for the study of water supply increase allocation to alleviate the drought degree of the the Yellow River Water Supply Area in Henan. Through the Multi-scenario potential tapping of multiple water sources, the existing potential water volume can be maximized, which is conducive to reducing the water supply pressure and water use restrictions of conventional water sources, improving the support capacity and guarantee capacity of water resources, and reducing the economic and social development bottlenecks caused by extreme drought.
DOI: 10.17632/76m24zdxcb.1
title: Gujarati News Article Text Dataset

description: The Gujarati News Article Text Dataset (GNATD) is a comprehensive collection of meticulously curated news articles in the Gujarati language. This dataset encompasses a diverse range of topics, including politics, economics, culture, sports, entertainment, and more, providing a rich and varied corpus of information in Gujarati. This dataset is a valuable resource for researchers and developers working on natural language processing (NLP) tasks and machine learning applications specifically in the context of the Gujarati language.
DOI: 10.17632/kzgmy58n23.1
title: Gut microbiota-derived α-linoleic acid mitigates intestinal inflammation induced by oral infection with Toxoplasma gondii 

description: Toxoplasma gondii (T. gondii) can cause serious zoonotic disease. Oral infection of cysts is the main transmission route of T. gondii and there is a lack of safe and effective anti-T. gondii drugs. It has been reported that T. gondii can significantly alter the structure and metabolism of gut microbiota, thereby affecting the process of T. gondii infection. Probiotics have been shown to be effective in the treatment of T. gondii infection; however, there is still limited systematic research on the action and mechanism of gut microbiota and its metabolites that regulate intestinal inflammation caused by T. gondii infection. In our previous study, it was found that α-AMY gene is essential for maintaining chronic infection, and the virulence between α-AMY knockout and wild-type cysts was significantly different. Based on the α-AMY knockout cyst, we proposed a scientific hypothesis that the severity of T. gondii infection in different strains is closely related to the gut microbiota from the perspective of the interaction between gut microbiota and T. gondii infection. This project intends to analyze and identify the key gut microbiota and metabolites that affect the process of T. gondii infection using a multi-omics approach combining 16S rRNA sequencing and metabolomics, and to further elucidate the mechanism of action of gut microbiota and their metabolites in regulating intestinal inflammation caused by T. gondii infection through the TLR4/MyD88/NF-κB pathway, which will provide important guiding significance for the development of drugs to treat toxoplasmosis.
DOI: 10.17632/kzgmy58n23.2
title: Gut microbiota-derived α-linoleic acid mitigates intestinal inflammation induced by oral infection with Toxoplasma gondii

description: Toxoplasma gondii (T. gondii) can cause serious zoonotic disease. Oral infection of cysts is the main transmission route of T. gondii and there is a lack of safe and effective anti-T. gondii drugs. It has been reported that T. gondii can significantly alter the structure and metabolism of gut microbiota, thereby affecting the process of T. gondii infection. Probiotics have been shown to be effective in the treatment of T. gondii infection; however, there is still limited systematic research on the action and mechanism of gut microbiota and its metabolites that regulate intestinal inflammation caused by T. gondii infection. In our previous study, it was found that α-AMY gene is essential for maintaining chronic infection, and the virulence between α-AMY knockout and wild-type cysts was significantly different. Based on the α-AMY knockout cyst, we proposed a scientific hypothesis that the severity of T. gondii infection in different strains is closely related to the gut microbiota from the perspective of the interaction between gut microbiota and T. gondii infection. This project intends to analyze and identify the key gut microbiota and metabolites that affect the process of T. gondii infection using a multi-omics approach combining 16S rRNA sequencing and metabolomics, and to further elucidate the mechanism of action of gut microbiota and their metabolites in regulating intestinal inflammation caused by T. gondii infection through the TLR4/MyD88/NF-κB pathway, which will provide important guiding significance for the development of drugs to treat toxoplasmosis.
DOI: 10.17632/c7c26gwf3g.1
title: Survey data on the socio-economic characteristics and electric vehicle perceptions of paratransit owners and drivers in South Africa

description: The survey data contain information on the socio-economic characteristics and electric vehicle (EV) perception of paratransit owners and drivers in South Africa. The data was collected to address knowledge gaps and inform policy-making in paratransit electrification. The data were collected by distributing a Microsoft Forms survey questionnaire among paratransit owners and drivers in the Western Cape province of South Africa. The questions in the survey were designed to gain information, and to provide information on the latent constructs of the behavioral framework constructed in “Electric vehicle adoption intention among paratransit owners and drivers in South Africa”. The data were used in “Electric vehicle adoption intention among paratransit owners and drivers in South Africa” to shed light on the attitudes, barriers, and enablers to EV adoption in the paratransit sector, providing insights for targeted interventions and promoting sustainable mobility. The data can be re-used for more in-depth studies of , as well as comparative studies assessing the socio-economic profiles and EV perceptions of paratransit owners and drivers in South Africa vs. other regions, and longitudinal studies benchmarking changes in EV perceptions in these demographics over time. Comparative studies could identify regional variations, cultural influences, and policy implications for promoting EV adoption in different contexts, and longitudinal studies can assess the effectiveness of interventions, policy changes, or technological advancements on EV adoption in the paratransit sector over time. See “Electric vehicle adoption intention among paratransit owners and drivers in South Africa” for more information.
DOI: 10.17632/c7c26gwf3g.2
title: Survey data on the socio-economic characteristics and electric vehicle perceptions of paratransit owners and drivers in South Africa

description: The survey data contain information on the socio-economic characteristics and intention of electric vehicle (EV) adoption amongst paratransit owners and drivers, to address knowledge gaps and inform policy-making in paratransit electrification. The data were collected by distributing a Microsoft Forms survey questionnaire among paratransit owners and drivers in and around Cape Town, South Africa. The questions in the survey were designed to gain information, and to provide information on the latent constructs of the behavioral framework constructed in “Electric vehicle adoption intention among paratransit owners and drivers in South Africa”. The data were used in the aforementioned paper to shed light on the attitudes, barriers, and enablers to EV adoption in the paratransit sector, providing insights for targeted interventions and promoting sustainable mobility. The data can be re-used for more in-depth studies of, as well as comparative studies assessing the socio-economic profiles and EV perceptions of paratransit owners and drivers in vs. other regions, and longitudinal studies benchmarking changes in EV perceptions in these demographics over time. Comparative studies could identify regional variations, cultural influences, and policy implications for promoting EV adoption in different contexts, and longitudinal studies can assess the effectiveness of interventions, policy changes, or technological advancements on EV adoption in the paratransit sector over time.
DOI: 10.17632/kvp9p9z2jp.1
title: Comparison of Lakes with Hypersaline, Heliothermic, sub-surface Oxygen Maxima

description: The data set is a comparison of Meromictic Lakes which exhibit at least few characteristics among hyper-salinity, sub-surface temperature maxima (heliothermic) ,sub-surface oxygen maxima(metalimnitic) and oxygen supersaturation. Very few such lakes are reported so far with about thirty (30) lakes world wide which are meromictic and heliothermic. . Meromictic lakes are highly stratified which exhibit meromixis, a condition in which a lake does not mix completely. Nine such lakes are reported in Asia and this data reports first time from India, Pulicat lake which has all these characteristics. Interestingly, the embedded meromixis still sustains some species withstanding the large ranges of temperature and salinity in this region of Pulicat. the Pulicat Lake in southern India that attracts various aquatic, migratory birds like Greater & Lesser Flamingoes, Pelicans, Terns, Teals, Grey heron, Open Bill Stork, Black-Headed Ibis, spot-Billed ducks, painted stork and little Egret. The lake is a habitat 88 species of birds which include more than 5 endangered and threatened species. The salinity of the lagoon is extremely fluctuating, shifting regimes from fresh to hypersaline on seasonal scales. recording a maximum of 191 ppt. Such high salinity in the Pulicat have so far not been reported.
DOI: 10.17632/mpnkzz69y7.1
title: Research Data for "Composition and pressure effects on equilibrium oxygen fractionations in garnets"

description: This is the supporting material for the article "Composition and pressure effects on equilibrium oxygen fractionations in garnets: Implication from high-temperature and high-pressure Raman spectra". It includes the in situ high-pressure and high-temperature Raman spectra in both raw (.l6s) and readable (.txt) format.
DOI: 10.17632/2v2mnbzykt.1
title: Suello et al. 2023, STOTEN, Data

description: Article Title: Rising sea levels help mitigate climate warming through increased carbon sequestration in salt marsh sediments
DOI: 10.17632/twpv7hhmgb.1
title: Plumbago Zeylanica (Chitrak) Leaf Image Dataset

description: The Plumbago Zeylanica (Chitrak) Leaf Image Dataset is a collection of high-resolution images capturing leaves of the medicinal plant Plumbago zeylanica. The dataset is partitioned for training and testing machine learning models. This resource is significant for botanical studies, herbal medicine research, and environmental analyses. Proper citation is essential for its use in scientific research.
DOI: 10.17632/twpv7hhmgb.2
title: Plumbago Zeylanica (Chitrak) Leaf Image Dataset

description: The Plumbago Zeylanica (Chitrak) Leaf Image Dataset is a collection of high-resolution images capturing leaves of the medicinal plant Plumbago zeylanica. The dataset is partitioned for training and testing machine learning models. This resource is significant for botanical studies, herbal medicine research, and environmental analyses. Proper citation is essential for its use in scientific research.
DOI: 10.17632/f3ftpd7xpg.2
title: MABSA: Malayalam Aspect Based Sentiment Analysis Dataset

description: MABSA is a curated aspect-based sentiment analysis dataset on the South Indian language Malayalam over the movie review domain. This dataset contains 4000 movie reviews in Malayalam and its sentiment labels for nine target aspects: direction, acting, songs, screenplay, story, casting, editing, cinematography, and BGM (background music). Each aspect in the review is mapped to one of the three sentiment classes, which are positive, negative, or neutral. These three sentiment classes are numerically represented as 1, 0, and 0.5, respectively. Movie reviews in Malayalam are collected through two methods, where the first method uses the Google survey tool to collect reviews from people, and the second method manually gathers movie reviews from various pages and groups on different social media platforms like Facebook, YouTube, and IMDb. The MABSA dataset consists of 4000 Malayalam movie reviews and a total of 5707 aspects manually annotated with its sentiment orientation.
DOI: 10.17632/f3ftpd7xpg.3
title: MABSA: Malayalam Aspect Based Sentiment Analysis Dataset

description: MABSA is a curated aspect-based sentiment analysis dataset on the South Indian language Malayalam over the movie review domain. This dataset contains 4000 movie reviews in Malayalam and its sentiment labels for nine target aspects: direction, acting, songs, screenplay, story, casting, editing, cinematography, and BGM (background music). Each aspect in the review is mapped to one of the three sentiment classes, which are positive, negative, or neutral. These three sentiment classes are numerically represented as 1, 0, and 0.5, respectively. Movie reviews in Malayalam are collected through two methods, where the first method uses the Google survey tool to collect reviews from people, and the second method manually gathers movie reviews from various pages and groups on different social media platforms like Facebook, YouTube, and IMDb. The MABSA dataset consists of 4000 Malayalam movie reviews and a total of 5707 aspects manually annotated with its sentiment orientation. Dataset files include both with and without English translations of Malayalam movie reviews. A copy of the Google form file is attached along with the MABSA dataset.