cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22191718.v1
title: Mushrooming GPS-tracks 2015-2017

description: Dataset accompanying our submission <em>Beyond their paths: what do ecological cues reveal about mushroom gatherers’ decision making?</em> <strong>Hunter Gatherer Research</strong> <strong>6(1–2): 169–186</strong>. https://doi.org/10.3828/hgr.2023.5 <br> <strong>clave_id</strong>: character string that uniquely identifies mushrooming trips by date and gatherer. The first section “Ruta” stands for pathway, the second section denotes the last two digits of the year, the month and day (yymmdd), and the third section describes the gatherer by sex (H, hombre – man or M, mujer –, woman) and his/her numeric label. <strong>timeloc</strong>: local time given by date (yyyy-mm-dd) and time (hh:mm:ss). <strong>east</strong>: numeric, indicates displacement in meters (m) to the East from an unknown point of origin. <strong>north</strong>: numeric, indicates displacement in meters (m) to the North from an unknown point of origin. <strong>ele</strong>: numeric, elevation in meters (m) above sea level. <strong>point</strong>: categorical, type of GPS register, either trackpoint (automatically recorded as programmed) or waypoint (manual annotation made while searching). <strong>tipo_encuentro</strong>: categorical, denotes either the type of ecological cue (traces, exploration, or memory) followed by the gatherer or the searching outcome (harvest, failed harvest). <strong>nom_hongo</strong>: categorical, indicates the local name of the mushroom associated with each tipo_encuentro. Not available cases are indicated with NA. See main text for full list of scientific generic and species names. <strong>num_esporoc</strong>: numeric, total carpophores associated with each tipo_encuentro. Not available cases are indicated with NA. <strong>dist</strong>: numeric, Euclidean distance in meters (m) between each consecutive pair of geographic coordinates. <strong>secs</strong>: numeric, time difference in seconds between each consecutive pair of time recordings. EDITING NOTE: we fixed and replaced a former version of "tyw_beyond.csv" where a pathway labeled as <em>Ruta_150823</em> cointained data from a different date and gatherer. All pathways are unique now.
DOI: 10.6084/m9.figshare.28768049.v1
title: Data and R Code for Trait Variation and Environmental Drivers in<i>"</i><b><i>Community functional traits shift under long-term nitrogen addition: Roles of intraspecific trait variability and species turnover</i></b><i>"</i>

description: This dataset contains raw and processed data, along with R scripts used to generate Figures 1–6 in the manuscript titled <i>"</i><b><i>Community functional traits shift under long-term nitrogen addition: Roles of intraspecific trait variability and species turnover</i></b><i>"</i>. The study explores the trait-based responses of plants to nitrogen addition, using linear regression models, structural equation modeling, and Sum of squares decomposition analysis. Each figure is associated with a dataset (<code>.xlsx</code>) and corresponding R script(s) for full reproducibility.
DOI: 10.6084/m9.figshare.12366029.v1
title: 关于上海市社区泛在健康服务平台使用意愿及影响因素的调查问卷

description: 关于上海市社区泛在健康服务平台使用意愿及影响因素的调查问卷
DOI: 10.6084/m9.figshare.28595492.v1
title: Data for Bats provide valuable services in conventional apple orchards

description: These data include fecal sample information, dietary composition, bat activity and moth abundance, and economic calculations of bat ecosystem service value.
DOI: 10.6084/m9.figshare.5285269.v1
title: Mycoplasma genitalium annotated assemblies

description: This is a collection of 28 Mycoplasma genitalium annotated assemblies. The de novo assemblies were created with velvet, and annotated with Prokka.
DOI: 10.17632/h5j5rvrz2r
title: Domination Chain with Weighted Parameters (Coq files)

description: This code contains a formal description of basic facts about Graph Theory and Domination Theory in the language Coq/Ssreflect. It is called DomTheory and consists of: *) The proof that the sum of degrees equals the cardinal of the edge set. *) Definitions and results about open and closed neighborhoods, stable sets, dominating sets, irredundant sets, hereditary and superhereditary properties, maximal/minimal sets and sets of maximum/minimum weight. *) The (weighted version of the) Cockayne-Hedetniemi domination chain. *) Examples of proofs with domination parameters on complete graphs. This code also contains: *) A browsable version made with the tool CoqDocJS, with some ''pretty-print'' symbols (like empty set, summation and set comprehension) added later. *) A solver that computes the (unweighted and weighted versions of) parameters gamma, ii, alpha, Gamma and IR. *) (experimental) The solver also generates a Coq file with a proof of alpha(G) &gt;= k, where k is the size of the best stable set found during the optimization. *) A set of instances.
DOI: 10.17632/j3k6bmnczt
title: A program to evaluate vibrationally inelastic collisional cross sections of atom-diatom systems

description: Title of program: EDWAVE Catalogue Id: AAXV_v1_0 Nature of problem The program EDWAVE calculates the vibrationally inelastic excitation and relaxation cross sections resulting from collisions between an atom and a diatomic molecule. Versions of this program held in the CPC repository in Mendeley Data AAXV_v1_0; EDWAVE; 10.1016/0010-4655(87)90095-6 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/sgk8stfdcn
title: Grey Falcon heat dissipation behaviour at T≥30ºC

description: Observations of Grey Falcons in the wild showing heat dissipation behaviour at air temperatures of 30ºC and higher. For further information and details refer to Schoenjahn, J., Chris R Pavey, Gimme H Walter. 2021. A true desert falcon that displays delayed onset of heat dissipation. Journal of Arid Environments.
DOI: 10.17632/t8d627cxb4
title: Publications on the Financial incentives

description: All 1546 scientiﬁc publications on the topic of Financial incentives were refined by Scopus to the “Economics, Econometrics and Finance” and “Business, Management and Accounting” categories.
DOI: 10.17632/zd2z3gg228
title: EEG Recordings of Mental Commands

description: Research Hypothesis: The research hypothesis posits that discernible patterns exist in the EEG (Electroencephalogram) recordings of individuals aged between 18 and 25 while performing mental commands related to lifting, dropping, pulling, pushing, and moving right. The study suggests that distinct neural signatures corresponding to each mental command can be observed in the EEG data. Data Collection: The dataset comprises 30 raw EEG recordings obtained from participants aged 18 to 25, ensuring they had no prior head injuries or illnesses. Participants were presented with a visual cue in the form of a box, and they were instructed to imagine performing specific mental commands. The experimental protocol involved a series of mental commands, each lasting for 3 minutes, separated by 10-second breaks. The sequence of mental commands included lifting, dropping, pulling, pushing, and moving right. Procedure: 1. Lift Command (3 minutes): Participants were shown a box and instructed to mentally focus on the concept of lifting for 3 minutes, followed by a 10-second break. 2. Drop Command (3 minutes): Similar to the lift command, participants mentally concentrated on the act of dropping for 3 minutes, again followed by a 10-second break. 3. Pull Command (3 minutes): Participants mentally engaged in the concept of pulling for 3 minutes, with a subsequent 10-second break. 4. Push Command (3 minutes): The mental task shifted to pushing for another 3 minutes, followed by a 10-second break. 5. Move Right Command (3 minutes): Participants were instructed to mentally command a movement to the right for 3 minutes, concluding with a 10-second break. Interpretation of Data: The analysis of the raw EEG data aims to identify specific neural patterns associated with each mental command. Given the presentation of a visual cue (the box), changes in electrical brain activity during different mental tasks are anticipated. Analysis methods may include time-frequency decomposition, event-related potentials (ERPs), or machine learning techniques to reveal patterns unique to each command. Future Directions: The dataset opens avenues for further investigations, such as exploring the development of brain-computer interfaces (BCIs) for command recognition based on EEG signals. Additionally, correlations between individual differences (e.g., cognitive abilities) and EEG patterns could be explored to enhance our understanding of the neural correlates of mental commands in this specific age group. In conclusion, this dataset, which includes the visual cue of a box, offers valuable insights into the neural dynamics associated with mental commands. It has the potential to advance our understanding of cognitive processes and contribute to the development of applications in brain-computer interface technology.
DOI: 10.6084/m9.figshare.24087150.v1
title: Book1.xlsx

description: demo
DOI: 10.6084/m9.figshare.28827314.v1
title: Data for article: <i>Does Excellence Correspond to Universal Inequality Level?</i>

description: <i>Does excellence correspond to a universal level of inequality?;</i> Soumyajyoti Biswas, Bikas K. Chakrabarti, Asim Ghosh, Sourav Ghosh, Máté Józsa, and Zoltán Néda.As the filename suggests, <i>All-Np-Nc-h-Q-g-k-b-S.dat</i> contains data on various metrics computed for 126,067 scientists with at least 100 publications (for detailed citation data, see this dataset).<i>Nobel-Np-Nc-h-Q-g-k-b-S.dat</i> contains the same metrics calculated for 77 Nobel Laureates, each with at least 100 publications. Citation counts of Nobel Laureates for specific years are provided in the <i>nobel-data</i> folder, with each filename indicating the year and the category: <i>eco</i> (economics), <i>chem</i> (chemistry), <i>med</i> (medicine), and <i>phys</i> (physics).Metrics:<b>Np</b> = number of publications<b>Nc</b> = total number of citations<b>h</b> = Hirsch index<b>Q</b> = Q-factor (maximum citations / mean citations)<b>g</b> = Gini index<b>k</b> = Kolkata index<b>b</b> = scale parameter of the fitted Tsallis-Pareto (Lomax II) distribution (see the article for more details).<b>S</b> = Shannon differential entropy of the distribution
DOI: 10.6084/m9.figshare.3560841.v1
title: Appendix B. Description of the generalized linear mixed model (GLMM) presented for comparison with the demographic model.

description: Description of the generalized linear mixed model (GLMM) presented for comparison with the demographic model.
DOI: 10.6084/m9.figshare.4233314.v1
title: Results of ANCOVA analysis and pairwise comparison from The influence of aspect ratio and stroke pattern on force generation of a bat-inspired membrane wing

description: Table A: MATLAB's Statistical Toolbox was used to perform an ANCOVA analysis was used to calculate linear regression fits for the dependency of the coefficient of lift and coefficient of drag on velocity ratio (figure 8). This table summarises the results of testing for the similarity of the linear regressions that fit the individual data sets of the five different models to a linear regression that would fit the data of all models combined. Presented are the deviation of the slopes of the individual fits from the slope of the regression that would fit all data. P-values of p~\textgreater~0.05 indicate that the slope of the individual set is not different from the slope of the regression of all data with a probability of 95%. Table B: P-values (rounded to two decimal places) of the pairwise comparisons of the slopes of the regression lines among the five models. The slopes of the regression lines were tested separately for coefficient of lift and drag of downstoke and upstroke, respectively.
DOI: 10.6084/m9.figshare.5048062.v1
title: The future cost of electrical energy storage based on experience rates:dataset

description: Corresponding paper: O. Schmidt, A. Hawkes, A. Gambhir & I. Staffell. The future cost of electrial energy storage based on experience rates. Nat. Energy 2, 17110 (2017).<br><br>Link to the paper: http://dx.doi.org/10.1038/nenergy.2017.110<br>This dataset compiles cumulative capacity and product price data for electrical energy storage technologies, including the respective regression parameters to construct experience curves. <br><br>Please see the paper for a full discussion on experience curves for electrical energy storage technologies and associated analyses on future cost, cumulative investment requirements and economic competitiveness of storage.<br><br>The dataset also presents the underlying data for Figures 1 to 5 and Supplementary Figures 2 and 3 of the paper.<br>
DOI: 10.21954/ou.se.25650729.v1
title: Enhanced Classification Scheme for STEM Online laboratories

description: This file provides a glossary of online laboratory terms developed during the eSTEeM project 'An investigation into the breadth of learning objectives developed in STEM online laboratories'<br>
DOI: 10.6084/m9.figshare.12366440.v1
title: Supplementary Material for: Long-Term Occupational Sleep Loss and Post-Retirement Cognitive Decline or Dementia

description: Introduction: Recent evidence suggests that poor sleep is a risk factor that contributes to the development of Alzheimer’s disease (AD). Most studies have focused on short-term effects of sleep deprivation on cognitive function, whereas longitudinal studies are limited to self-reported sleep and the risk of later-life dementia. Because sleep loss could be an early manifestation of neurodegenerative disease, reverse causality in these studies cannot be excluded. Objective: In this explorative, observational study, we investigated the effects of extended periods of extrinsically (work-related) caused sleep loss on later-life cognitive function, early dementia symptoms, and current sleep quality. Methods: We approached a community of retired male maritime pilots (approx. n = 500) through a newsletter. We investigated 50 respondents (mean age 71.7 years ± 7.7), with a history of &gt; 25 years of work on irregular schedules, which resulted in extended periods of sleep loss. Validated questionnaires on cognitive complaints (Cognitive Failure Questionnaire [CFQ]), early dementia symptoms (Early Dementia Questionnaire [EDQ]), current sleep quality (Pittsburgh Sleep Quality Index [PSQI] and sleep-wake diaries), quality of life (QoL, EQ-5D), and mood (Hospital Anxiety and Depression Scale [HADS]) were administered by a single investigator (J.T.), who also completed an observer rating of cognitive function. Results: Scores on the CFQ, EDQ, PSQI, EQ-5D, and HADS were within normal ranges adjusted for age, sex, and education. The observer rating was not indicative of cognitive decline. Conclusion: We found no evidence that long-term exposure to work-related sleep loss had resulted in cognitive decline or early dementia symptoms in this sample of retired maritime pilots.
DOI: 10.6084/m9.figshare.13079537.v1
title: qPCR data.xlsx

description: This dataset is qPCR Ct data for "Salinomycin inhibits proliferative vitreoretinopathy formation in a mouse model".<b></b>
DOI: 10.6084/m9.figshare.22269091.v1
title: Aortic Dissection Dataset and Segmentations

description: This dataset consists of a type B Aortic Dissection (AD) CTA collection with true and false lumen expert annotations. It can be used for the development of AI-based algorithms for an automatic segmentation of ADs.<br><br>For a review about the detection, segmentation, simulation and visualization of Aortic Dissections, please see:Pepe A, Li J, Rolf-Pissarczyk M, Gsaxner C, Chen X, Holzapfel GA, Egger J. Detection, segmentation, simulation and visualization of aortic dissections: A review. Medical image analysis. 2020 Oct 1;65:101773.<br>Cite as:[1] Christian Mayer<i>, </i>Antonio Pepe, Sophie Hossain, Barbara Karner, Melanie Arnreiter, Jens Kleesiek, Johannes Schmid, Michael Janisch, Hannes Deutschmann, Michael Fuchsjäger, Daniel Zimpfer, Jan Egger, Heinrich Mächler. Aortic Dissection Dataset and Segmentations. figshare, 2024. DOI: 10.6084/m9.figshare.22269091<br>[2] Christian Mayer<i>, </i>Antonio Pepe, Sophie Hossain, Barbara Karner, Melanie Arnreiter, Jens Kleesiek, Johannes Schmid, Michael Janisch, Hannes Deutschmann, Michael Fuchsjäger, Daniel Zimpfer, Jan Egger, Heinrich Mächler. Type B Aortic Dissection CTA Collection with True and False Lumen Expert Annotations for the Development of AI-based Algorithms. Scientific Data, Nature Portfolio 2024.
DOI: 10.6084/m9.figshare.24793836.v1
title: Assembled_genomes

description: Assembled genomes<br>
DOI: 10.6084/m9.figshare.29104898.v1
title: [<sup>11</sup>C]acetylacetate ([<sup>11</sup>C]AcAc)

description: Time List and Cassette Layout for the synthesis of Carbon-11 acetylacetate (AcAc)
DOI: 10.6084/m9.figshare.12110616.v1
title: The effects of Piper sarmentosum aqueous extracts on zebrafish (Danio rerio) embryos and caudal fin tissue regeneration

description: We have determined zebrafish (<i>Danio rerio</i>) embryo toxicities and caudal fin tissue regeneration in the presence of <i>P. sarmentosum</i> aqueous extracts
DOI: 10.6084/m9.figshare.19641654.v1
title: AGB of managed grasslands in China

description: This is a dataset associating with a MS submitted to the journal of <em>Scinece China: Life Sciences, </em>entitled " Opportunity to enhance grassland above-ground biomass potential through managed grassland establishment in China", by Guocheng Wang and his coauthors.
DOI: 10.6084/m9.figshare.25040543.v1
title: HUST-OBS

description: Oracle Bone Script data collected by VLRLab of HUST
DOI: 10.6084/m9.figshare.25460755.v4
title: STRIDE (Sensor Technologies for Road Insights and Driving Evaluation) Dataset

description: The dataset is a comprehensive collection of sensor data captured from various sources, including accelerometer, gyroscope, magnetometer, GPS, gravity sensor, orientation sensor, and sensors for measuring total acceleration, uncalibrated magnetometer readings, uncalibrated gyroscope readings, and uncalibrated accelerometer readings. This diverse range of sensors has recorded a wide array of parameters, such as acceleration force, gravitational force, rate of rotation, raw acceleration data without bias compensation, magnetic field strength, uncompensated rate of rotation, and angles around the x, y, and z axes.Furthermore, the GPS sensor has captured data on bearing accuracy, speed accuracy, vertical precision, horizontal accuracy, vehicle speed, altitude, longitude, and latitude. This extensive collection of parameters ensures a comprehensive understanding of road conditions and various driving patterns.The dataset aims to promote collaboration, foster further exploration, and facilitate the development of innovative ideas in the field of intelligent transportation systems. By making this real-time data on road conditions available to the community, the dataset offers numerous benefits, including enhanced monitoring capabilities, improved safety, better infrastructure maintenance, optimized traffic management, and data-driven urban planning and decision-making.<br><br><b>Driving</b><b> Behavior</b><b>│</b><b> </b><b>├</b><b>───</b><b>1. Aggressive</b><b>│</b><b> </b><b>├</b><b>───</b><b>2. Aggressive</b><b>│</b><b> </b><b>├</b><b>───</b><b>3. Standard</b><b>│</b><b> </b><b>├</b><b>───</b><b>4. Standard</b><b>│</b><b> </b><b>└───5. Slow</b><b>│</b><b> </b><b>└───6. Slow</b><b>Road Anomalies</b><b>├</b><b>───</b><b>1. Bump</b><b>├</b><b>───</b><b>10. Pothole</b><b>├</b><b>───</b><b>11. Pothole</b><b>├</b><b>───</b><b>12. Pothole</b><b>├</b><b>───</b><b>13. Pothole</b><b>├</b><b>───</b><b>14. Pothole</b><b>├</b><b>───</b><b>15. Pothole</b><b>├</b><b>───</b><b>16. Pothole</b><b>├</b><b>───</b><b>17. Pothole</b><b>├</b><b>───</b><b>2. Bump</b><b>├</b><b>───</b><b>3. Bump</b><b>├</b><b>───</b><b>4. Bump</b><b>├</b><b>───</b><b>5. Bump</b><b>├</b><b>───</b><b>6. Bump</b><b>├</b><b>───</b><b>7. Bump</b><b>├</b><b>───</b><b>8. Bump</b><b>└───9. Bump</b><br><br><br><br><br><b>C:</b><b>Driving</b><b> Behavior</b><b>1.</b><b>1.</b><b> </b><b>Aggressive</b><b>Accelerometer.csv</b><b>AccelerometerUncalibrated.csv</b><b>Gravity.csv</b><b>Gyroscope.csv</b><b>GyroscopeUncalibrated.csv</b><b>Location.csv</b><b>Magnetometer.csv</b><b>MagnetometerUncalibrated.csv</b><b>Metadata.csv</b><b>Orientation.csv</b><b>TotalAcceleration.csv</b><br><br><br><br><br><br><br>
DOI: 10.6084/m9.figshare.5129239.v1
title: Supplementary Material for: Jules-Auguste Soury (1842-1915): A Centennial Call to Mind

description: Jules-Auguste Soury (1842-1915), a Parisian theorist and historian of science, was the author of ‘The Central Nervous System', one of the most comprehensive and original accounts, until 1900, of the history of brain research. A contemporary of Jules Déjerine (1849-1917), Santiago Ramón y Cajal (1852-1934), and other pioneers of neurology, with whom he maintained contact, Soury is a rare case of a French philosopher with solid foundations in neuroanatomy and neurophysiology. A quaint savant, Soury has been depicted as a strange hybrid produced by nature. His odd personality was coupled with an elegance, solidity and thoroughness in his neurological works. His prodigious facility for assimilating and discoursing the ideas of others has been somewhat clouded by his lamentable ideological tenets. Nevertheless, in his neurological writings, he bequeathed a unique anatomical and physiological history of intelligence, a natural history of the human mind or, as he conceived it, a neurophilosophical sketch of the universe considered a cerebral phenomenon.
DOI: 10.17632/hcd2c3n9tc
title: Collagen I induces preeclampsia-like symptoms by suppressing proliferation and invasion of trophoblasts.Yinglin FENG et al.

description: Availabitily of data and material
DOI: 10.17632/nmhh2rtfn7
title: Fortran User Subroutine (UMAT) for Abaqus.

description: This dataset contains the Fortran code for the user subroutine (UMAT) used in the article "A thermo-elasto-viscoplastic model for polymers" (https://doi.org/10.1016/j.jmps.2018.11.018) by Joakim Johnsen, Arild Holm Clausen, Frode Grytten, Ahmed Benallal and Odd Sture Hopperstad. The dataset also includes an example input file for a thermomechanical axisymmetric uniaxial tensile test built for Abaqus 6.14-4. Note that you need to link Abaqus to a Fortran compiler in order to run the model with the user subroutine. The following properties must be given in the material card: -- PART A PROPERTIES PROPS(1) : Initial shear modulus Part A PROPS(2) : Temperature sensitivity of shear modulus in Part A PROPS(3) : Activation enthalpy for alpha relaxation PROPS(4) : Activation volume for alpha relaxation PROPS(5) : Reference plastic strain rate for alpha relaxation (give as natural logarithm value) PROPS(6) : Parameter governing evolution of reference plastic strain rate for alpha relaxation PROPS(7) : Activation enthalpy for beta relaxation PROPS(8) : Activation volume for beta relaxation PROPS(9) : Reference plastic strain rate for beta relaxation (give as natural logarithm value) PROPS(10) : Parameter governing evolution of reference plastic strain rate for beta relaxation PROPS(11) : Boltzmann's constant PROPS(12) : Universal gas constant PROPS(13) : Reference temperature PROPS(14) : Tolerance used in convergence criterion PROPS(15) : Maximum number of iterations in the semi-implicit integration -- PART B PROPERTIES PROPS(16) : Initial shear modulus Part B PROPS(17) : Bulk modulus PROPS(18) : Locking stretch PROPS(19) : Thermal expansion coefficient --- COMMON PROPERTIES PROPS(20) : Density PROPS(21) : Specific heat capacity PROPS(22) : Factor controlling substepping