cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19243899.v3
title: Air cargo load and route planning in pickup and delivery operations

description: Military aviation faces risks of cargo unbalancing due to the urgency required on loading for rapid take-off and mission accomplishment, especially in times of crisis, armed conflict or public calamity. We model and solve the problem of planning the loading of an aircraft according to utility score, weight and balance principles, confer agility to pallet assembly under safety requirements, and also serving multiple bases in a tour of simultaneous Pickup and Delivery at intermediate airfields. This research result may be applicable by military and also by commercial companies in dynamic environments, especially on handling catastrophic events, sometimes as a government contractor. This problem encompasses four sub-problems: Air Palletization, Weight and Balance, Pickup and Delivery, and Sequencing. This hard problem, named Military Air Cargo Load Planning Problem, is mathematically modeled in real scenarios, using a standardized pallet, considering the possible presence of troops, ensures that torque and center of gravity constraints are obeyed, and each item is delivered to its destination. In our approach, we carry out experiments with a commercial solver, four well known meta-heuristics, and a proposed heuristic, on benchmarks based on statistical data from the Brazilian Air Force.
DOI: 10.5519/qd.3k4esbre
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (76 records)
DOI: 10.21227/6fj0-7746
title: Labeled Dataset with extracted features

description: Technical question-answering sites like Stack Overflow are gaining enormous attention from the practitioners of specialized fields to exchange their programming knowledge. They ask questions on different topics, having various levels of difficulty and complexity. To answer such questions, all practitioners do not have the same level of expertise on those topics. However, the existing approach of Stack Overflow does not consider the difficulty and primarily filters out the questions based on topics only. For this reason, a large percentage of questions fail to attract the attention of appropriate users, resulting in questions having no answer or a significant delay in response time. To address these limitations, we incorporate three models, namely TF-IDF, LDA, and Doc2Vec, to extract semantic and context-dependent features that can measure the difficulty of questions. Each of these models is used with different classifiers along with other features to classify the questions based on difficulty. Extensive experiments on different datasets exhibit the effectiveness of our models, and the Doc2Vec outperforms the other models. We also discovered that the contextual features are correlated with question difficulty, and one subset of features outperforms others. The proposed approach can be beneficial for building an automatic tagger based on question difficulty.
DOI: 10.24378/exe.4065
title: Pliocene-Pleistocene evolution of the Laurentide Ice Sheet and North Atlantic ocean circulation (Appendix A and Appendix B)

description: Appendix A and Appendix B for the Doctoral thesis "Pliocene-Pleistocene evolution of the Laurentide Ice Sheet and North Atlantic ocean circulation".
description: Appendix A & B
description: The thesis associated with this dataset is located in ORE at: http://hdl.handle.net/10871/129984
DOI: 10.5519/qd.jpj8y5k5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (49534 records)
DOI: 10.6084/m9.figshare.19169720.v1
title: Supplementary Material for: Silk-based matrices and c-Kit positive cardiac progenitor cells for a cellularized silk fibroin scaffold: study of an in vivo model

description: The production of a cellularized silk fibroin scaffold is very difficult because it is actually impossible to differentiate cells into a well-organized cardiac tissue. Without vascularization, not only do cell masses fail to grow, but they may also exhibit an area of necrosis, indicating a lack of oxygen and nutrients. In the present study, we used the so-called tyrosine protein kinase kit (c-kit)-positive cardiac progenitor cells (CPCs) to generate cardiac cellularized silk fibroin scaffolds, multipotent cells isolated from the adult heart to date that can show some degree of differentiation toward the cardiac phenotype. To test their ability to differentiate into the cardiac phenotype in vivo as well, CPC and collagen organoid-like masses were implanted into nude mice and their behavior observed. Since the three-dimensional structure of cardiac tissue can be preserved by scaffolds, we prepared in parallel different silk fibroin scaffolds with three different geometries and tested their behavior in three different models of immunosuppressed animals. Unfortunately, CPC cellularized silk fibroin scaffolds cannot be used in vivo. CPCs implanted alone or in collagen type I gel were destroyed by CD3+ lymphocytes’ aggregates, whereas the porous and partially oriented scaffolds elicited a consistent foreign body response characterized by giant cells. Only the electrospun meshes were resistant to the foreign body reaction. In conclusion, c-kit-positive CPCs, although expressing a good level of cardiac differentiation markers in vitro with or without fibroin meshes, are not suitable for an in vivo model of cardiac organoids because they are degraded by a T-cell-mediated immune response. Even scaffolds, which may preserve the survival of these cells in vivo, also induced a host response. However, among the tested scaffolds, the electrospun meshes (F-scaffold) induced a lower response compared to all the other tested structures.
DOI: 10.6084/m9.figshare.19169720
title: Supplementary Material for: Silk-based matrices and c-Kit positive cardiac progenitor cells for a cellularized silk fibroin scaffold: study of an in vivo model

description: The production of a cellularized silk fibroin scaffold is very difficult because it is actually impossible to differentiate cells into a well-organized cardiac tissue. Without vascularization, not only do cell masses fail to grow, but they may also exhibit an area of necrosis, indicating a lack of oxygen and nutrients. In the present study, we used the so-called tyrosine protein kinase kit (c-kit)-positive cardiac progenitor cells (CPCs) to generate cardiac cellularized silk fibroin scaffolds, multipotent cells isolated from the adult heart to date that can show some degree of differentiation toward the cardiac phenotype. To test their ability to differentiate into the cardiac phenotype in vivo as well, CPC and collagen organoid-like masses were implanted into nude mice and their behavior observed. Since the three-dimensional structure of cardiac tissue can be preserved by scaffolds, we prepared in parallel different silk fibroin scaffolds with three different geometries and tested their behavior in three different models of immunosuppressed animals. Unfortunately, CPC cellularized silk fibroin scaffolds cannot be used in vivo. CPCs implanted alone or in collagen type I gel were destroyed by CD3+ lymphocytes’ aggregates, whereas the porous and partially oriented scaffolds elicited a consistent foreign body response characterized by giant cells. Only the electrospun meshes were resistant to the foreign body reaction. In conclusion, c-kit-positive CPCs, although expressing a good level of cardiac differentiation markers in vitro with or without fibroin meshes, are not suitable for an in vivo model of cardiac organoids because they are degraded by a T-cell-mediated immune response. Even scaffolds, which may preserve the survival of these cells in vivo, also induced a host response. However, among the tested scaffolds, the electrospun meshes (F-scaffold) induced a lower response compared to all the other tested structures.
DOI: 10.6084/m9.figshare.19786552
title: Supplementary Material for: The Effect of Delivery Systems on the Induction of T Helper 1 Cell Response to an ESAT6-Like Protein Rv3619c and Identification of its Immunodominant Peptides

description: Rv3619c is an immunodominant Mycobacterium tuberculosis-specific antigen and belongs to the ESAT6-family of proteins. Delivery systems are needed to deliver such strong antigen in animal model and induce protective immune responses. Hypothesis. This study determined the effect of chemical adjuvants (IFA and Alum), mycobacteria, and a DNA plasmid as delivery systems on the induction of protective Th1 (IFN-ɣ), and pathologic Th2 (IL-5) and Treg (IL-10) cytokine responses to Rv3619c and its peptides. The Rv3619c gene was amplified from the genomic DNA of M. tuberculosis and cloned into appropriate vectors for expression in Escherichia coli, Mycobacterium smegmatis, and eukaryotic cells. Spleen cells from the mice immunized with Rv3619c using different delivery systems were stimulated in vitro with synthetic peptides (P1 to P6) of Rv3619c, and secretions of cytokines were estimated by ELISA. The results showed that the recombinant M. smegmatis and DNA plasmid induced the secretion of protective cytokine IFN-ɣ in response to peptide-pool of Rv3619c and all the individual peptides, whereas Rv3619c/IFA induced the secretion of IFN-ɣ in response to the peptide pool, and the peptides P5 and P6. However, the secretions of pathologic cytokines IL-5 and IL-10 were induced to none of the peptides with the delivery systems used. These results show that Rv3619c is a major antigen of M. tuberculosis with multiple immunogenic epitopes but the immune responses to individual epitopes can vary based on delivery systems used.
DOI: 10.5281/zenodo.6665932
title: The Good First Issue Recommendation Dataset from "GFI-Bot: Automated Good First Issue Recommendation on GitHub"

description: This is a good first issue (GFI) recommendation dataset created from the GFI-Bot project (https://github.com/osslab-pku/gfi-bot). For more information about the GFI recommendation problem and GFI-Bot, please check our publications: Wenxin Xiao, Hao He, Weiwei Xu, Xin Tan, Jinhao Dong, and Minghui Zhou. 2022. Recommending Good First Issues in GitHub OSS Projects. In Proceedings of the 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 21–29, 2022. ACM. https://hehao98.github.io/files/2022-recgfi.pdf Hao He, Haonan Su, Wenxin Xiao, Runzhi He, and Minghui Zhou. 2022. GFI-Bot: Automated Good First Issue Recommendation on GitHub. Currently Under Review at the ESEC/FSE 2022 Demonstration Track. https://hehao98.github.io/files/2022-gfibot.pdf The dataset is a MongoDB dump and needs to be restored to a MongoDB instance before use. This can be done via the official <code>mongorestore</code> tool by running a command like this in the <code>dataset/</code> folder: <pre><code class="language-bash">mongorestore --uri={{ your mongodb url }} --gzip </code></pre> In the <code>gfibot.dataset</code> collection, each document describes the state of an issue at a certain time (either at the time of issue creation or at the time of issue resolution). The <code>resolver_commit_num</code> is the ground truth label (i.e., # of commits the issue resolver has made in the repository before issue resolution, excluding commits for resolving the issue itself; <code>resolver_commit_num = 0</code> means the resolver is someone completely new to the repository). The remaining fields can be used as features or further analyzed to derive new features. This dataset can be used to evaluate new GFI recommendation approaches. We hope it will be helpful in advancing GFI recommendation research and other future studies on open-source software onboarding.
DOI: 10.5281/zenodo.4307231
title: Bathymetric data for Mulargia reservoir (Sardinia, Italy)

description: This dataset includes bathymetric data for Mulargia reservoir (Sardinia), which were extracted from a raster dataset of 30 m x 30 m resolution that contained three fields: latitude (UTM 32N), longitude (UTM 32N) and elevation (meters). Three different database sources were combined and interpolated for the production of the bathymetric raster: the Shuttle Radar Topography Mission (SRTM) digital elevation model, a military map (19/9/1882, No.1012), and data on water level variations from 1985 to 2016.
DOI: 10.5281/zenodo.4307230
title: Bathymetric data for Mulargia reservoir (Sardinia, Italy)

description: This dataset includes bathymetric data for Mulargia reservoir (Sardinia), which were extracted from a raster dataset of 30 m x 30 m resolution that contained three fields: latitude (UTM 32N), longitude (UTM 32N) and elevation (meters). Three different database sources were combined and interpolated for the production of the bathymetric raster: the Shuttle Radar Topography Mission (SRTM) digital elevation model, a military map (19/9/1882, No.1012), and data on water level variations from 1985 to 2016.
DOI: 10.6084/m9.figshare.20101862.v1
title: Supplementary Tables_An immunoinformatics approach MEV against CCHFV.pdf

description: Supplementary Tables
DOI: 10.6084/m9.figshare.20101862
title: Supplementary Tables_An immunoinformatics approach MEV against CCHFV.pdf

description: Supplementary Tables
DOI: 10.6084/m9.figshare.20101853
title: Agri

description: agri
DOI: 10.6084/m9.figshare.20101853.v1
title: Agri

description: agri
DOI: 10.5281/zenodo.6445997
title: Widespread increasing vegetation sensitivity to soil moisture

description: This repository contains the datasets used in the research article "Widespread increasing vegetation sensitivity to soil moisture". The repository contains the following folders: 1) demo_data.zip - contains all the raw datasets used for training the random forests and inferring sensitivity analysis using Shapley Additive Explanations method. 2) fig_data.zip - contains all the processed data and additional datasets for creating main figures in the article. Formats: All scripts are in the programming language Python. The datasets are in the NumPy array format. The codes related to the research article are available in the following repository: https://doi.org/10.5281/zenodo.6554966
DOI: 10.5281/zenodo.6445996
title: Widespread increasing vegetation sensitivity to soil moisture

description: This repository contains the datasets used in the research article "Widespread increasing vegetation sensitivity to soil moisture". The repository contains the following folders: 1) demo_data.zip - contains all the raw datasets used for training the random forests and inferring sensitivity analysis using Shapley Additive Explanations method. 2) fig_data.zip - contains all the processed data and additional datasets for creating main figures in the article. Formats: All scripts are in the programming language Python. The datasets are in the NumPy array format. The codes related to the research article are available in the following repository: https://doi.org/10.5281/zenodo.6554966
DOI: 10.5517/ccdc.csd.cc1zdw9k
title: CCDC 1829629: Experimental Crystal Structure Determination

description: Related Article: Polly L. Arnold, Tatsumi Ochiai, Francis Y. T. Lam, Rory P. Kelly, Megan L. Seymour, Laurent Maron|2020|Nature Chemistry|12|654|doi:10.1038/s41557-020-0457-9
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.6670116
title: Plant-derived catechols are substrates of TonB-dependent transporters and sensitize Pseudomonas aeruginosa to siderophore-drug conjugates

description: The dataset contains raw data used to generate the figures of the associated mansucript
DOI: 10.6084/m9.figshare.20101841
title: Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study [Registered Report Stage 1 Protocol]

description: ABSTRACT: The timing of puberty may have a substantial impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Some preliminary evidence suggests that this relationship is causal, but replication and an investigation of the broader generalisability of this finding is warranted. In this Registered Report, we will triangulate different causal inference methods using a new wave of data from the Norwegian Mother, Father and Child Cohort Study (MoBa). We will investigate: (1) to what extent age at menarche is associated with adolescent depression; (2) if associations extend to other domains of mental health; and (3) whether links between age at menarche and mental health are likely to be causal. The findings will elucidate the impact of pubertal timing on mental health and may help inform early detection and prevention. ITEMS: Additional file 1: design table.pdf; Additional file 2: supplementary methods.pdf; Additional file 3: psychometric properties of sympton scales.pdf; Additional file 4: variable overview.pdf; Additional file 5: overview of ALSPAC and MoBa variables for replication; Additional file 6: summary of arrays and batching in genotyping.pdf; Additional file 7: Stage 1 RR Supplementary code.pdf; Additional file 8: results of power analyses.pdf; Letter from data controller.pdf; Stage 1 RR age at menarche.pdf
DOI: 10.6084/m9.figshare.20101841.v2
title: Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study [Registered Report Stage 1 Protocol]

description: ABSTRACT: The timing of puberty may have a substantial impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Some preliminary evidence suggests that this relationship is causal, but replication and an investigation of the broader generalisability of this finding is warranted. In this Registered Report, we will triangulate different causal inference methods using a new wave of data from the Norwegian Mother, Father and Child Cohort Study (MoBa). We will investigate: (1) to what extent age at menarche is associated with adolescent depression; (2) if associations extend to other domains of mental health; and (3) whether links between age at menarche and mental health are likely to be causal. The findings will elucidate the impact of pubertal timing on mental health and may help inform early detection and prevention. ITEMS: Additional file 1: design table.pdf; Additional file 2: supplementary methods.pdf; Additional file 3: psychometric properties of sympton scales.pdf; Additional file 4: variable overview.pdf; Additional file 5: overview of ALSPAC and MoBa variables for replication; Additional file 6: summary of arrays and batching in genotyping.pdf; Additional file 7: Stage 1 RR Supplementary code.pdf; Additional file 8: results of power analyses.pdf; Letter from data controller.pdf; Stage 1 RR age at menarche.pdf
DOI: 10.6084/m9.figshare.20101841.v1
title: Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study [Registered Report Stage 1 Protocol]

description: ABSTRACT: The timing of puberty may have a substantial impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Some preliminary evidence suggests that this relationship is causal, but replication and an investigation of the broader generalisability of this finding is warranted. In this Registered Report, we will triangulate different causal inference methods using a new wave of data from the Norwegian Mother, Father and Child Cohort Study (MoBa). We will investigate: (1) to what extent age at menarche is associated with adolescent depression; (2) if associations extend to other domains of mental health; and (3) whether links between age at menarche and mental health are likely to be causal. The findings will elucidate the impact of pubertal timing on mental health and may help inform early detection and prevention. ITEMS: Additional file 1: design table.pdf; Additional file 2: supplementary methods.pdf; Additional file 3: psychometric properties of sympton scales.pdf; Additional file 4: variable overview.pdf; Additional file 5: overview of ALSPAC and MoBa variables for replication; Additional file 6: summary of arrays and batching in genotyping.pdf; Additional file 7: Stage 1 RR Supplementary code.pdf; Additional file 8: results of power analyses.pdf; Letter from data controller.pdf; Stage 1 RR age at menarche.pdf
DOI: 10.5281/zenodo.6670181
title: Paelopatides confundens decontaminated gx

description: .
DOI: 10.5281/zenodo.6670180
title: Paelopatides confundens decontaminated gx

description: .
DOI: 10.6084/m9.figshare.20101916.v1
title: Supplementary Dataset

description: Supplementary Datasets
DOI: 10.6084/m9.figshare.20101916
title: Supplementary Dataset

description: Supplementary Datasets
DOI: 10.5281/zenodo.6670104
title: Exploratory Topic Modelling Using Python Dataset - EHRI-3

description: In the EHRI-3 project, we are investigating tools and methods that historical researchers and scholars can use to better understand, visualise, and interpret the material held by our partner archives. This dataset accompanies a tutorial exploring a technique called topic modelling in the context of a Holocaust-related historical collection. We were on the lookout for datasets that would be easily accessible and, for convenience, predominantly in English. One such dataset was the United States Holocaust Memorial Museum’s (USHMM) extensive collection of oral history testimonies, for which there are a considerable number of textual transcripts. The museum’s total collection consists of over 80,703 testimonies, 41,695 of which are available in English, with 2,894 of them listing a transcript. Since there is not yet a ready-to-download dataset that includes these transcripts, we had to construct our own. Using a web scraping tool, we managed to create a list of the links pointing to the metadata (including transcripts) of the testimonies that were of interest to us. After obtaining the transcript and other metadata of each of these testimonies, we were able to create our dataset and curate it to remove any unwanted entries. For example, we made sure to remove entries with restrictions on access or use. We also removed entries with transcripts that consisted only of some automatically generated headers and entries which turned out to be in languages other than English. The remaining 1,873 transcripts form the corpus of this tutorial — a small, but still decently sized dataset. The process that we followed to put together this dataset is detailed in the Jupyter Notebook accompanying this post, which can be found in this Github repository.<br> Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
description: Credits: The transcripts that form the corpus in this tutorial were obtained through the United States Holocaust Memorial Museum (USHMM).
DOI: 10.5281/zenodo.6670200
title: Virgularia gustaviana decontaminated gx

description: .
DOI: 10.5281/zenodo.6670199
title: Virgularia gustaviana decontaminated gx

description: .