cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1243200.v3
title: Schroer_and_Wood_2015_Evolution_character_displacement_fossil_hominins_v1

description: PREFERRED CITATION: Schroer K and Wood B. 2015. The role of character displacement in the molarization of hominin mandibular premolars. Evolution. DOI: 10.1111/evo.12672. Title: Schroer_and_Wood_2015_Evolution_character_displacement_fossil_hominins_v1 Version number: 1 Date (ISO) original data publication: 5/5/15 Dates (ISO) data collection: 01/01/12-01/01/14 Date (ISO) online publication: 5/5/15 Companion manuscript title: "The role of character displacement in the molarization of hominin mandibular premolars" Companion manuscript journal: Evolution Primary collector of data: Kes Schroer Co-authors: Bernard Wood Research assistants: Kristen Ramirez, Christine Foltz Short description: Measurements of the lower fourth premolar (P4) from fossil hominins for character displacement analysis. Rows: 64 (header = TRUE) Columns: 15 Empty cell label: NA Variables: I, T, L, Intrx, Taxon, logmd, logbl, logarea, Randomly.selected?, ACC, Specific.taxon, P4MD, P4BL, P4AREA, P4AREACALC ==================== I, T, L, and Intrx: variables of the input matrix. “I” is Intercept and is always 1. “T” is “Taxon” and is encoded “1” for one taxon and “-1” for the other. “L” is location and is “1” for the sympatrix taxa and “-1” for the allopatric taxa. “Intrx” is the interaction of T and L and simply multiples these two values. Taxon: placement of each specimen in one of four categories: EA.Homo, EA.Paranthropus, O.Homo, or S.Paranthropus. Categories are mutually exclusive. “EA” stands for East Africa, “O” stands for other, and the “S” in S.Paranthropus stands for South Africa. logmd, logbl, and logarea: the natural logs of the measurements P4MD, P4BL, and P4AREACALC. Randomly.selected: whether or not a specimen was randomly selected by the custom R script for character displacement analysis (see manuscript for more details). “Yes” indicates that the specimen was selected and “NA” indicates that the specimen was not. ACC: specimen number assigned by the host museum Specific.taxon: genus and species name P4MD: mesiodistal diameter of the lower fourth premolar, in millimeters P4BL: buccolingual diameter of the lower fourth premolar, in millimeters P4AREA: area of the occlusal surface of the lower fourth premolar, calculated through a resampled outline in the digitization program tpsDIG (see manuscript for more details). Some fossil specimens were not available for this measure, in which case P4AREA is filled with “NA.” P4AREACALC. For fossil specimens without a P4AREA measurement, P4MD and P4BL are multiplied to give an estimate of P4AREA. P4AREA and P4AREACALC are the same for specimens available for measurements in tpsDIG.
DOI: 10.17632/kpm9r53srw
title: Data for Formulation of an Innovative Model for the Bioeconomy: Unraveling the Secrets of a Sustainable Future

description: This dataset contains the components utilized in a comprehensive literature review and theoretical modeling study on the bioeconomy. The dataset includes references to academic articles and publications relevant to the bioeconomy, as well as supplementary materials such as tables, diagrams, and models developed during the study. Additionally, the dataset includes information on the database accessed for literature review purposes, which was sourced from Scopus. The materials in this dataset serve as the foundation for the theoretical framework constructed in the study, offering insights into the dynamics and interrelationships within the bioeconomy domain. Researchers interested in exploring the sources consulted or utilizing the theoretical model developed in this study are encouraged to access the dataset for further analysis and reference.
DOI: 10.6084/m9.figshare.27612280.v1
title: Appendix from Kelp forests versus urchin barrens: A comparison of ecosystem functions and services provided by two alternative stable marine habitats.

description: Appendix 1: PRISMA Figure; Appendix 2: Additional Search Terms; Appendix 3: Literature Search Results
DOI: 10.17632/yv3v3rs88d
title: THE ICT COMPETENCY OF PRE-SERVICE TEACHER IN VIETNAM 

description: Using the Information and Communication Technology competency framework of UNESCO, the research surveyed 1698 4th-year pre-service teachers from 10 provinces in 3 regions of Vietnam.
DOI: 10.6084/m9.figshare.1292944.v1
title: Serving First in Isolation Increases Vegetable Intake among Elementary Schoolchildren

description: Dataset for studies. A separate worksheet is present for each of the three studies. On each worksheet, the cell in the first row in each column contains a comment that describes that data element.
DOI: 10.6084/m9.figshare.14442251.v1
title: GSE81861

description: Colorectal cancer cells sequenced from humans.<br>
DOI: 10.6084/m9.figshare.3452639.v1
title: Supplementary Material for: Characterization of Integrons and Sulfonamide Resistance Genes among Bacteria from Drinking Water Distribution Systems in Southwestern Nigeria

description: <b><i>Background:</i></b> The emergence of antibiotic resistance among pathogenic bacteria in clinical and environmental settings is a global problem. Many antibiotic resistance genes are located on mobile genetic elements such as plasmids and integrons, enabling their transfer among a variety of bacterial species. Water distribution systems may be reservoirs for the spread of antibiotic resistance. <b><i>Materials and Methods:</i></b> Bacteria isolated from raw, treated, and municipal tap water samples from selected water distribution systems in south-western Nigeria were investigated using the point inoculation method with seeded antibiotics, PCR amplification, and sequencing for the determination of bacterial resistance profiles and class 1/2 integrase genes and gene cassettes, respectively. <b><i>Results:</i></b><i>sul1,</i><i>sul2,</i> and <i>sul3</i> were detected in 21.6, 27.8, and 0% of the isolates, respectively (n = 162). Class 1 and class 2 integrons were detected in 21.42 and 3.6% of the isolates, respectively (n = 168). Genes encoding resistance to aminoglycosides <i>(aadA2, aadA1,</i> and <i>aadB),</i> trimethoprim <i>(dfrA15, dfr7,</i> and <i>dfrA1),</i> and sulfonamide <i>(sul1)</i> were detected among bacteria with class 1 integrons, while genes that encodes resistance to strepthothricin <i>(sat2)</i> and trimethoprim <i>(dfrA15)</i> were detected among bacteria with class 2 integrons. <b><i>Conclusions:</i></b> Bacteria from these water samples are a potential reservoir of multidrug-resistant traits including sul genes and mobile resistance elements, i.e. the integrase gene.
DOI: 10.6084/m9.figshare.20141213.v1
title: train_dataset.csv

description: ## 1 FILE CONTENTS ############################################# 2101 x 40006 values: - 1 header row, which corresponds to the 40002 resolved wavelengths and 4 element names (Cr, Mn, Mo, and Ni). - 2100 spectra (rows): 50 spectra of 42 distinct targets. <br> Note that the dataset occupies significantly less RAM when loaded than the file's disk sizes (cca. 50 %). <br> Note that the column names may be modified by the software/library used for processing the spectra. Hence, we advise increased caution when extracting the wavelengths. Alternatively, you can use the wavelength values provided separately in the wavelengths.csv file. <br> ## 2 DATA ACQUISITION ############################################# <br> The dataset was collected from metallic targets. Each target's surface was homogenized using a 800 grid sandpaper and cleaned with isopropyl alcohol using paper towels. The targets were sampled at distinct spots in single-shot mode, collecting a single spectrum from each individual spot. There are a total of 50 spectra available for each target. <br> A 1064 nm Nd:YAG laser was used for ablation with a pulse energy of 95 mJ, 10 ns pulse width. The laser pulse was focused into a spot with a diameter of 0.2 mm. <br> The collected emission was resolved with an echelle spectrograph in the 240--1000 nm spectral range (40002 resolved wavelength values), resolving power {\lambda} / {\Delta\lambda} = 6000. <br> The resolved emission was recorded using an EMCCD camera with a 1.5 us delay and 50 us gate width (exposition time). <br> The spectra were not intensity calibrated! This, in combination with the long gate width is part of the challenge.
DOI: 10.6084/m9.figshare.29094977.v1
title: teachers study

description: teachers study
DOI: 10.6084/m9.figshare.7297565.v4
title: Henry et al., cannabis genetic data (VCF and CSV) for 1409 SNP and 38 highly informative SNPs along with Neighbour joining tree (Supplentarry Figure 1), as well as chemotypic data for the same accessions (Supplementary Table 1).

description: Two VCF (and CSV) files containing 1409 SNPs and 38 highly informative SNPs to predict terpenoid expression and inform individual identification in vegetative cannabis accessions.<br>Supplementary Table 1. Chemotypic data for 70 accessions used in this study. RSPID numbers can be entered into http://kannapedia.net to retrieve original submission and individual VCF files from MGC.<br>Supplementray Figure 1. NJ-tree of the 70 accessions demonstrating lack of confidence in strain names vs clustering of accessions.
DOI: 10.6084/m9.figshare.1084362.v1
title: Keywords: Diseases

description: 106 disease names crawled from wrongdiagnosis.com
DOI: 10.6084/m9.figshare.2007426.v1
title: Melting Point and Pyrolysis Point Data for Tens of Thousands of Chemicals

description: We have developed a pipeline for the automated extraction and annotation of chemical data from published patents. Almost 300,000 data points have been collected and used to develop models to predict melting and pyrolysis (decomposition) points using tools available on the OCHEM modeling platform (http://ochem.eu). <br>Two data sets are associated with the resulting publication authored by Tetko et al. "<b>The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from patents</b>". Details are on Kudos at https://www.growkudos.com/publications/10.1186%252Fs13321-016-0113-y
DOI: 10.6084/m9.figshare.23691660.v1
title: A longitudinal analysis of selective motor control during gait in individuals with cerebral palsy and the relation to gait deviations data 160723.xlsx

description: The dataset of this study: "A longitudinal analysis of selective motor control during gait in individuals with cerebral palsy and the relation to gait deviations"
DOI: 10.6084/m9.figshare.28723568.v1
title: data set for study titled <b>Personality, Mental Wellbeing, and Resilience as Predictors of ProQOL in Mental Health Nurses</b>

description: This study explores the impact of personality traits, mental well-being, and resilience on the professional quality of life (ProQOL) of mental health nurses working in private hospitals in India. With an emphasis on burnout, compassion satisfaction, and secondary traumatic stress, the research seeks to identify predictive factors that influence nurses' job satisfaction and emotional well-being. The study utilizes a cross-sectional design, with a sample of 282 mental health nurses. Data was collected using standardized instruments including the Big Five Inventory, WHO-5 Well-Being Index, Brief Resilience Scale, and the ProQOL Scale. The results demonstrate that extraversion, agreeableness, and resilience positively predict compassion satisfaction, while neuroticism is a significant predictor of burnout and secondary traumatic stress. Mental well-being and resilience also play crucial roles in mitigating burnout and secondary traumatic stress. Cluster analysis reveals distinct psychological profiles among nurses, highlighting the need for tailored interventions to improve ProQOL. This research provides actionable insights for enhancing the well-being of mental health nurses through targeted psychological interventions, improving organizational support, and addressing systemic issues within the healthcare environment.
DOI: 10.17632/mdk37zw86g
title: An atomic Gaussian-type orbital roothaan-hartree-fock program

description: Title of program: HSCF Catalogue Id: AAFI_v1_0 Nature of problem The non-relativistic Roothan-Hartree-Fock equations are set up and solved using an analytical basis of Gaussian-type orbitals. This provides atomic total energies and orbital energies in a given basis set which may be further used in analyzing results obtained in molecular calculations using the same basis set. Versions of this program held in the CPC repository in Mendeley Data AAFI_v1_0; HSCF; 10.1016/0010-4655(83)90098-X This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/zx3kjzc3yx
title: MHCflurry 2.0: Improved pan-allele prediction of MHC Class I-presented peptides by incorporating antigen processing

description: Computational prediction of the peptides presented on MHC class I proteins is an important tool for studying T cell immunity. The data available to develop such predictors has expanded with the use of mass spec to identify naturally-presented MHC ligands. In addition to elucidating binding motifs, the identified ligands also reflect the antigen processing steps that occur prior to MHC binding. Here, we developed an integrated predictor of MHC I presentation that combines new models for MHC I binding and antigen processing. Considering only peptides first predicted by the binding model to bind strongly to MHC, the antigen processing model is trained to discriminate published mass spec-identified MHC I ligands from unobserved peptides. The integrated model outperformed the two individual components as well as NetMHCpan 4.0 and MixMHCpred 2.0.2 on held-out mass spec experiments. Our predictors are implemented in the open source MHCflurry package, version 2.0 (github.com/openvax/mhcflurry). See the paper at: https://doi.org/10.1016/j.cels.2020.06.010 Data S1. MULTIALLELIC benchmark dataset with predictions (CSV, gzipped). Data S2. MONOALLELIC benchmark dataset with predictions (CSV, gzipped). Data S3. Training data for MHCflurry 2.0 binding affinity (BA) predictor (CSV). Data S4. Training data for the variant of MHCflurry BA evaluated on the MONOALLELIC benchmark in Fig. S2 (CSV). Data S5. Training data for MHCflurry 2.0 antigen processing (AP) predictors (CSV). Data S6. Training data for MHCflurry 2.0 presentation score (PS) predictors (CSV).
DOI: 10.6084/m9.figshare.14914773.v1
title: Dataset of seized wildlife and their intended uses

description: Dataset and code from "Dataset of seized wildlife and their intended uses", by Stringham OC, Moncayo S, Thomas E, Heinrich S, Toomes A, Maher J, Hill KGW, Mitchell L, Ross JV, Cassey P. Submitted to peer review, PDF for pre print forthcoming.<br>
DOI: 10.6084/m9.figshare.27276828.v1
title: Held, Bisen, Zandawala et al. 2025

description: Primary data of Held, Bisen, Zandawala et al. 2025 "Aminergic and peptidergic modulation of Insulin-Producing Cells in Drosophila".
DOI: 10.6084/m9.figshare.28113341.v1
title: Borderline resectable Esophageal cancer ;Scoping Review Protocol.docx

description: Esophageal cancer is a significant global health concern, characterized by high morbidity and mortality rates. The concept of borderline resectable (BR) esophageal cancer is less clearly defined than in other malignancies, such as pancreatic cancer. This ambiguity impacts diagnostic approaches, treatment decisions, and patient outcomes. This scoping review aims to map the existing literature on BR esophageal cancer to identify gaps and provide direction for future research.
DOI: 10.6084/m9.figshare.6016325.v1
title: Raw DIDSON Dataset by Fish Species

description: This dataset contains raw, acoustic DIDSON data collected from an extended surveillance period. Short clips of data that contain fish of known species are also present. This data could be used to create computational fish classification or tracking algorithms for DIDSON data.
DOI: 10.17632/d9gtv85dw5
title: IFRI Multiple Benefits from Forest Commons

description: IFRI research program is a network of collaborative research centres across North and South America, Africa, Asia, and Europe with a focus on case studies and analyses of local forest governance and forest resource outcomes in diverse socio‐political, ecological, and institutional contexts. IFRI sites are broadly representative of forests and the range of forest management regimes that exist in human‐dominated landscapes throughout the tropics (Congo Basin in Central Africa, Amazon Basin across nine Latin American countries, and Borneo across Indonesia and Malaysia). The dataset used for this analysis was drawn from the October 2018 compiled version of the full IFRI Database covering 1028 forests and villages in 26 countries. Our criteria for case selection excluded forests outside of the low‐income tropics, forests less than 5ha, and those with absent plot vegetation data. In cases where a forest had longitudinal data, we used the visit date with the most recent plot data available. These exclusions yielded a dataset of 314 forests in 15 countries located across Asia, Africa, and Latin America. Biomass, Biodiversity & Livelihoods We tested for pairwise strength of associations between our three benefits – Biomass, Biodiversity, and Livelihoods and a set of explanatory variables: Forest Size, Elevation, Population, Literacy, Food self-consumption (average number of months that households consume self-produced food), Commercial Value, Distance to market, Presence of association (Yes/No), Rulemaking (participation of local communities in making formal rules regarding governance of the forest), and Illegal Harvesting (None to Rampant). For each forest commons in our data, forest vegetation and biophysical data was collected in ~30 plots of 10 meters radius randomly distributed across the forest. We calculated the basal area of trees with a diameter greater than 10 cm at breast height. We calculated the non‐parametric Chao1 estimator of tree species richness as a proxy indicator for overall forest biodiversity using EstimateS. We measure livelihood contributions of forest commons by an index extracted through factor analysis of the proportions of (i) firewood, (ii) fodder, and (iii) timber for domestic use that each forest provides to local users. Using wards-linkage hierarchical clustering, we generated nested classes for 314 forests with Biomass, Biodiversity and Livelihoods as the component dimensions. Each cluster has observations that are similar to each other with respect to Biomass, Biodiversity, and Livelihoods, and dissimilar to forest commons in the other four clusters on the three dimensions. We divided the sample into five distinct groups; Sustainable Forests (119), Carbon Forests (23), Conservation Forests (88), Subsistence Forests (57), and Degraded Forests (27).
DOI: 10.17632/jh8b2rh8nz
title: Dataset used to infer regional slope stability , NW Himalaya

description: The study area concerning the data set is located between the 31˚36′1″ N, 78˚26′ 47″ E and 31˚27′10″ N, 77˚38′ 20″ E in Satluj River valley, NW Himalaya. This region has been subjected to spatio-temporal varying tectonic stress, owing to continent-continent collision orogeny, resulting in a diverse set of joints. This data is a part of a larger dataset that was compiled to infer the potential landslide damming in Satluj valley, NW Himalaya. The data set includes joint mapping data, values of input parameters that are used in the Finite Element Method based slope stability evaluation, and a table comprising all the landslide related details. Rock mass joint data (Supplementary Table 1) was collected in the field. Rock/soil samples, collected from each landslide, were analysed in the National Geotechnical Facility and Wadia Institute of Himalayan Geology, India. These values were used in models to evaluate slope stability of different types of landslides. Procedure described in the relevant Indian Standard (IS) codes was followed for the laboratory analyses. Such data set can be utilized to infer the pattern of rock mass joints in continent-continent collision orogeny on regional scale. At slope level, it can be inferred as a controlling parameter. The values of input parameters used in the FEM models (Supplementary Table 2) can be utilized as a reference for different types of rock mass and soil. Supplementary Table 3 comprises the following details related to the landslides; Type, Area, volume, Human population in the vicinity, Factor of safety, Total displacement, Morphological Obstruction Index, Hydro-morphological Dam Stability Index (HDSI).
DOI: 10.6084/m9.figshare.25040669.v1
title: Data for "<i>Contrasting coordination of non-structural carbohydrates with leaf and root economics strategies of alpine coniferous forests</i>"

description: Through examining NSC and key economic traits in fine roots and leaves across alpine coniferous populations on the eastern Tibetan Plateau, we observed contrasting coordination of NSC with economics traits in leaves and roots. Sampling was performed at 90 coniferous forest stands distributed across the study area, including 26 <i>Abies</i> populations, 10 <i>Larix</i> populations, 37 <i>Picea</i> populations, and 17 <i>Pinus</i> populations.
DOI: 10.6084/m9.figshare.28681487.v1
title: Supplementary Data 1.xlsx

description: Differential transcriptomes of <i>M.luminyensis </i>CZDD1 in coculture with <i>C. malenominatum</i> CZB5 vs its H<sub>2</sub>-dependent methylotrophic culture
DOI: 10.17632/33w7jd3nsz
title: matching recombination indirect comparisons and network meta-analysis between syndrome differentiation-based acupuncture or not for primary insomnia

description: To evaluate the importance of point selection based on syndrome differentiation by re-analyzing the trials' results in treating primary insomnia with acupuncture. We systematically searched 9 databases for eligible trials. Two authors extracted data independently from citations, interventions, and outcomes. Since the "treatment acupuncture" and "control acupuncture" data compared in this study were from different trials, we matched the data in a 1:1 ratio and minimized heterogeneity between the paired groups. Matching factors included age, sex ratio, and the baseline Pittsburgh Sleep Quality Index (PSQI) score. Meta-analyses were performed using Revman 5.4 software. Effect estimation presented continuous data with a standard mean difference (SMD) with a 95% confidence interval (CI). Besides the recombination indirect comparison, STATA 15.0 was used for network meta-analysis of all included trials. In this dataset, we summarized all the information from 172 included trials, including the main data needed for our meta analysis.
DOI: 10.6084/m9.figshare.16974712.v1
title: Table S7.xlsx

description: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results of apoptosis-related genes.
DOI: 10.6084/m9.figshare.20018729.v1
title: Data of Digitalization and poverty in MENA countries

description: The file contains that data of poverty and ICT in selected MENA and emerging countries from 1990 to 2019
DOI: 10.6084/m9.figshare.20531958.v1
title: Human_Phenotype_Ontology

description: All files from the preprocessed Human Phenotype Ontology (HPO). *_annot.csv: Files containing annotation for the HPO terms. *_genes.txt: Files containing list of genes that could be mapped to the ontology. *_graph.json: Dict with mapping children -&gt; parent *_desc_genes.json: Dict with mapping term -&gt; all descendant genes *_masks.pickle: Binary masks used to initialize the decoder wiring of OntoVAE. *_trimmed_*: trimmed version of a file, for HPO, thresholds of 10 and 1000 were used.