cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14963730.v10
title: Epoch data

description: The epoch data are a fieldtrip format structure, all epochs are aligned with fixation onset to a given word, with the length of one second.Epochs were named as the combination of acquizaton date, subject code, and data type. Epochs that ended with 'Targ60' are from the first sentence set; ended with 'JEP60' are from the second sentence set (adapted from Degno et al. 2019, Journal of Experimental Psychology); ended with 'BL' were the baseline period of the first sentence set.<br>This filed 'trialinfo' is the information about each trial, the header of all columns are as followings:1- sentence_id: sentence number for this epoch2- word_loc: the location of the current word in a sentence3- loc2targ:location distance between the current word and target word; loc2targ for pre-target, target, post-target are -1, 0, and 14- word_freq: CELEX frequency 5- word_length6- saccade2this_duration: saccade duration toward this word7- fixation_on_MEG: MEG trigger for fixation onset to this word8- fixation_duration 9- NextOrder: next word location minus the current word location; negative value indicates saccade backward to the previous words10- FirstPassFix: whether this fixation is the first for this word or not11- PreviousOrder: previous word location minus the current word location; negative value indicates saccade forward to the next words12- SentenceCondition: the current word is in a sentence with high or low frequency target word; 1 -- low, 2 -- high13- PupilSize: averaged pupil size during this fixation<br>
DOI: 10.6084/m9.figshare.2068602.v2
title: A Bootstrap Metropolis–Hastings Algorithm for Bayesian Analysis of Big Data

description: Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their computer-intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. In this article, we propose the so-called bootstrap Metropolis–Hastings (BMH) algorithm that provides a general framework for how to tame powerful MCMC methods to be used for big data analysis, that is, to replace the full data log-likelihood by a Monte Carlo average of the log-likelihoods that are calculated in parallel from multiple bootstrap samples. The BMH algorithm possesses an embarrassingly parallel structure and avoids repeated scans of the full dataset in iterations, and is thus feasible for big data problems. Compared to the popular divide-and-combine method, BMH can be generally more efficient as it can asymptotically integrate the whole data information into a single simulation run. The BMH algorithm is very flexible. Like the Metropolis–Hastings algorithm, it can serve as a basic building block for developing advanced MCMC algorithms that are feasible for big data problems. This is illustrated in the article by the tempering BMH algorithm, which can be viewed as a combination of parallel tempering and the BMH algorithm. BMH can also be used for model selection and optimization by combining with reversible jump MCMC and simulated annealing, respectively. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.25111916.v1
title: Production_2021

description: This file contains resource production data from USGS and BGS for the year 2015 to 2021 for the 48 resources considered in ESSENZ and ESSENZ+.
DOI: 10.6084/m9.figshare.22645357.v1
title: Pre-processed data for the study Gherardini et al.

description: Preprocessed structural connectome and preprocessed protein deposition from datasets from the ADNI
DOI: 10.6084/m9.figshare.7011524.v2
title: Depth-to-Bedrock Map of China

description: Depth-to-bedrock maps of China at three spatial resolution:100 meters, 1 kilometers, and 10 kilometer.Uncertainty map of prediction at at three spatial resolution:100 meters, 1 kilometers, and 10 kilometer.
DOI: 10.17632/2j5hs3xs96
title: Soil properties after 36 years of N fertilization 

description: Modern agricultural systems rely on inorganic nitrogen (N) fertilization to enhance crop yields, but its overuse may negatively affect soil properties. Our objective was to investigate the effect of long-term N fertilization on key soil physical and chemical properties under continuous corn [Zea mays L.] (CCC) and both the corn (Cs) and soybean [Glycine max L. Merr.] (Sc) phases of a corn-soybean rotation. Research plots were established in 1981 with treatments arranged as a split-plot in a randomized complete block design with three replications. The main plot was crop rotation (CCC, Cs, and Sc), and the subplots were N fertilizer rates of 0 kg N ha-1 (N0, controls), and 202 kg N ha-1, and 269 kg N ha-1 (N202, and N269, respectively). The dataset accompanies publications listed in the references section.
DOI: 10.17632/fd7rgfkmcm
title: Survey dataset on the effect and mitigation measures: Construction delays in Hargeisa

description: Dataset explores the associated effect of construction project delays and the possible mitigating measures that can proffer solutions to delays in the completion of road and building construction projects in Hargeisa.
DOI: 10.17632/ps6hfypmn4
title: Data for: Effects of Structural System and Site Classification on Water Footprint of Residential Buildings

description: This gives water footprint data required to assess the water footprint of building structures.
DOI: 10.6084/m9.figshare.19137311.v1
title: tidal model

description: 2007年南黄海（118°42′～120°47′、34°32′～36°28′）潮汐模拟
DOI: 10.6084/m9.figshare.24137280.v1
title: Data and code shared for NGS

description: Code and data for the paper “Global crop production increase by soil organic carbon”Code authors: Dominic Woolf and Yuqing MaCode contact by domwoolf@gmail.com or yuqingma0114@gmail.comData authors: Mingsheng Fan, Yuqing Ma, Rong Li, Lei QiaoData contact by fanms@cau.edu.cnDescription: R scripts and data to quantify the causal effect of soil organic carbon (SOC) on crop yield of the three major crops (maize, wheat and rice). The R script and data aim to achieve three contents: (1) quantify the causal effect of SOC on crop yield; (2) analyze the major drivers of soil organic carbon yield gap; (3) make global extrapolation of SOC yield gap for the three studied crops.***Please install the necessary packages using the R script “Load Packages.R”.<br>1. Causal effect of SOC on crop yield(1) “Causal effect of SOC on crop yield by Random Forest.R”: R script used to establish the causal effect of SOC on crop yield by partial dependence using Random Forest.(2) “Causal effect of SOC on crop yield by Causal Forest.R”: R script used to estimate the effect size of SOC on crop yield by casual forest.(3) “Causal effect of SOC on crop yield under different N levels.R”: R script used to establish the casual effect of SOC on crop yield under different nitrogen input levels.(4) “Causal effect of SOC on crop yield under climate zones”: R script used to establish the casual effect of SOC on crop yield under global climate zones.(5) “data.csv”: CSV data used in this section.<br>2. Drivers of SOC yield gap(1) “Calculating SOC yield gap.R”: R script used to estimate SOC yield gap for each field trial.(2) “Determination of drivers for the SOC yield gaps.R”: R script used to quantify the driver of SOC yield gap based on field trial data by Random Forest.(3) “data.csv”: CSV data used in this section.<br>3. Global extrapolation of SOC yield gap(1) “Determination of coefficient and index of agreement for global extrapolation model.R”: R script used to analyze the model performance for global extrapolation(2) “Leave one out cross-validation to estimate prediction uncertainty for global extrapolation.R”: R script used to estimate the standard errors of predicted SOC yield gaps derived from global extrapolation models.(3) “Technical potential for global extrapolation.R”: R script used to estimate global yield increase under technical potential to increase SOC.(4) ”10.Unconstrained increase for global extrapolation.R”: R script used to estimate global yield increase under unconstrained increase in SOC.(5) “data.csv”: CSV data used in this section.(6) “Maize global data.csv”: The distribution of global maize cropping area used to estimate global maize yield increase derived from SOC.(7) “Wheat global data.csv”: The distribution of global wheat cropping area used to estimate global wheat yield increase derived from SOC.(8) “Rice global data.csv”: The distribution of global rice cropping area used to estimate global rice yield increase derived from SOC.
DOI: 10.6084/m9.figshare.28138343.v1
title: Data from "A Historical Misstep: Niche Shift to Specialisation Is Pushing Insular Ginger Towards an Evolutionary Dead End"

description: Niche specialisation is a double-edged sword as it aids species in adapting to a particular environment but makes them more susceptible to environmental change, which may result in species extinction. Although it has long been debated whether niche specialisation necessarily falls into an 'evolutionary dead end', empirical evidence from a population genetics perspective remains scant, especially when comparing both ecological generalists and specialists simultaneously. In this study, we scrutinised two Taiwan endemic gingers (<i>Zingiber pleiostachyum</i> and <i>Z. shuanglongense</i>) to evaluate how their contrasting patterns in niche breadth evolution have shaped their evolutionary trajectories. We utilised a genome-wide sequencing approach to investigate the demographic histories of each species, assess their maladaptation to future climate change, and estimate their mutational loads. Our results revealed distinct demographic histories between these two gingers. <i>Z. shuanglongense</i>, as the specialist, despite an initial increase during the Last Glacial Maximum (~22 Kya), has been subjected to a long-term decrease in effective population size (<i>Ne</i>), while <i>Z. pleiostachyum</i> is on the contrary increasing, leading to a significantly larger current <i>Ne</i>. Furthermore, ecological specialists are much more vulnerable to future climate change and exhibit greater drift-associated deleterious mutations compared to generalists, directly affecting species' fitness. This study strongly supports the idea that the transition in niche breadth towards specialisation will push <i>Z. shuanglongense</i> perilously close to extinction and also sheds light on species conservation within limited migratory space.
DOI: 10.6084/m9.figshare.28346942.v1
title: KEGG_build_2025-02-04

description: An archived version of the KEGG data directory for use in anvi'o. Can be set up on a computer with an anvi'o installation using the command `anvi-setup-kegg-data --kegg-archive KEGG_build_2025-02-04_4039c79d9c82.tar.gz` (specify a --kegg-data-dir to avoid overriding the default KEGG data directory, if one exists).This KEGG snapshot includes 501 modules, 57 BRITE hierarchies, and 1,334 HMMs for stray KOs (KOs without bit score thresholds provided by KEGG). It does not contain pathway map files.Contains MODULES.db version 4.<br>Hash value of the database is 4039c79d9c82
DOI: 10.6084/m9.figshare.29066417.v1
title: genome_assemblies.tar.gz

description: Staphylococcus epidermidis whole genome sequences. Isolates used for characterising host-range of Staphylococcus epidermidis sepunaviruses.
DOI: 10.6084/m9.figshare.4287704.v1
title: Homo_sapiens.GRCh38.86.chromosomes.gtf.tar.gz

description: This is a demo data for GFFview containing complete annotation information of human chromosomes in GTF format, which totally has 1,713,977 line records.<br>
DOI: 10.6084/m9.figshare.5125093.v1
title: Butaite_etal_Nat.Commun.2017_Siderophore_cheating_in_natural_pseudomonads_Data.xlsx

description: Data used for statistical analyses and to generate graphs for the paper. More detailed description is provided in the file.<br>
DOI: 10.6084/m9.figshare.8479349.v1
title: Nucleotide diversity

description: Per gene nucleotide diversity across the meadow for each population.<br>
DOI: 10.60893/figshare.jcp.25884136.v1
title: Supporting Information

description: Supporting Information file
DOI: 10.6084/m9.figshare.14560593.v1
title: Block Design Measurements Review Table

description: Literature review of block design task studies
DOI: 10.6084/m9.figshare.27433035.v1
title: Axiovert200.zip

description: SLiMIA (Spheroid Light Microscope Image Atlas) provides light microscopy images (and manual segmentations/ground truths) of spheroids from 50 cell lines, 9 culture media, 4 formation methods and multiple seeding densities.This folder contains specifically the images obtained with an Axiovert 200 light microscope.
DOI: 10.6084/m9.figshare.28191218.v1
title: Data.xlsx

description: <b>Dataset on Attitudes of Bangladeshi Medical Students Towards Artificial Intelligence in Medicine and Radiology</b>This dataset is part of a study examining the knowledge, perceptions, and attitudes of Bangladeshi undergraduate medical students towards artificial intelligence (AI) applications in medicine and radiology. The data was collected through a web-based cross-sectional survey conducted between September 7 and October 14, 2024. A structured questionnaire was designed to assess various aspects, including demographic details, familiarity with AI technologies, sources of AI-related knowledge, and attitudes toward AI's role in healthcare.Key features of the dataset include:<b>Demographics:</b> Age, gender, and self-reported tech-savviness of participants.<b>AI Awareness and Knowledge:</b> Levels of familiarity with AI applications in radiology and medicine and understanding of underlying technologies.<b>Sources of AI Information:</b> Contributions from mass media, social media, formal education, and peer discussions.<b>Attitudes Toward AI:</b> Insights into perceptions of AI's impact on radiology and medicine, concerns about AI replacing physicians, and enthusiasm for AI integration into medical curricula.<b>Statistical Analyses:</b> Results of subgroup comparisons (e.g., by gender and tech-savviness) and Likert-scale responses.The dataset provides comprehensive information on 330 participants, offering valuable insights for researchers, educators, and policymakers interested in AI adoption in medical education and healthcare.<b>Ethics Approval:</b><br>The study received approval from the FSIT Research Ethics Committee, Daffodil International University (Code: DIU/DoR/2023/11/1). Participation was voluntary, with informed consent obtained.<br><b>File Format:</b><br>The dataset is available in XLSX, along with the questionnaire used for data collection.
DOI: 10.6084/m9.figshare.3543767.v1
title: Appendix B. Equations for calculating Chao 2 species-richness estimators.

description: Equations for calculating Chao 2 species-richness estimators.
DOI: 10.17632/g5d274b9pb
title: Dataset for 'Region-specific nutritious, environmentally friendly, and affordable diets in India'

description: This dataset provides the data for the manuscript titled 'Region-specific nutritious, environmentally friendly, and affordable diets in India'. Following Tables S1-S6 are provided: Table S1. Ratio of current daily per capita nutrient intake and its recommended daily allowance (RDA) for each state. A ratio higher than one indicates that nutrient intake is sufficient and below one indicates nutrient deficiency. For optimized diet, all ratios are equal to or above one and hence not shown. Table S2. Environmental footprints of daily per capita curent (obs) and optimized (opt) diets of each state (both urban and rural areas). Footprints exceeding daily per capita planetary boundaries are marked in red. Table S3. Required changes in the intake of food items to achieve sustainable diet in each state. Difference between optimum and current intake amounts (in grams per capita per day) are shown for each of the 111 food items. PDS is public distribution system under which an item (rice, wheat, sugar) is sold by government at subsidized rates to poor. Required intake changes in 19 broad food groups are also shown. Table S4. Values of dietary sustainability metrics per state for current (obs) and optimized (opt) diets. The metrics are mean nutrient deficiency (MND, Eq. 2), mean environmental ratio (MER, Eq. 3), % expenditure on food (PEF, Eq. 4) and % departure from current diets (Eq. 5). See equations 2-5 in Experimental procedure section in the main text for details and Figure 1 for visual representation. Table S5. To aid the readers in making inferences from results presented in Figure 3 and Figure S5, we have now added Supplementary Table S5 showing in which quadrant does each of the food item lie for each nutrient-environment domain combination through a color code. For example, the first quadrant food items (which are low on price and environmental footprint) are coded green. The second quadrant food items (low in price but high in environmental footprint) are coded in yellow. The fourth quadrant food items (high in price but low in environmental footprint) are coded in orange. Finally, the third quadrant food items (high in price and high in environmental footprint) are coded in red. This way the reader can easily identify how sustainable is each food item for a particular nutrient-environmental domain combination. Table S6. Yield gaps (in %) of 25 Indian crops gathered from different sources. Filling these gaps would ensure the current cropland extent in India (~1.6 million km2) is enough to feed all citizens with the sustainable diet identified in this study.
DOI: 10.17632/wyjm5mv87b
title: Data for: Effect of ionising radiation on the mechanical and structural properties of 3D printed plastics.

description: Analysis of 3d printed plastics: PLA, ABS, Nylon, TPU, PC, CPE, CPE+. Irradiated in the 0.5-5.2 MeV region. Data from samples irradated at various dose levels Stress-strain plots FTIR spectroscopy Raman spectroscopy Chemical structures
DOI: 10.6084/m9.figshare.26135500.v1
title: Supplementary Material for: Omics-based investigation on mechanisms controlling cellular internalization of keratin monomers during biodegradation by Stenotrophomonas maltophilia DHHJ

description: Introduction: The global poultry industry produces millions of tons of waste feathers every year, which can be degraded to make feed, fertilizer, and daily chemicals. However, feather degradation is a complex process that is not yet fully understood. This results in low degradation efficiency and difficulty in industrial applications. Omics-driven system biology research offers an effective solution to quickly and comprehensively understand the molecules and mechanisms involved in a metabolic pathway. Methods: In the early stage of this process, feathers are hydrolyzed into water-soluble keratin monomers. In this study, we used high-throughput RNA-seq technology to analyze the genes involved in the internalization and degradation of keratin monomers in S. maltophilia DHHJ strain cells. Moreover, we used Co-IP with LC-MS/MS technology to search for proteins that interact with recombinant keratin monomers. Results: We discovered TonB transports and molecular chaperones associating with the keratin monomer, which may play a crucial role in the transmembrane transport of keratin. Meanwhile, multiple proteases belonging to distinct families were identified as binding partners of keratin monomers, among which ATPases associated with diverse cellular activities (AAA+) family proteases are overrepresented. Four genes, including JJL50_15620, JJL50_17955 (TonB-dependent receptors), JJL50_03260 (ABC transporter ATP-binding protein), and JJL50_20035 (ABC transporter substrate-binding protein), were selected as representatives for determining their expressions under different culture conditions using qRT-PCR and they were found to be upregulated in response to keratin degradation consistent with the data from RNA-seq and Co-IP. Conclusion: This study highlights the complexity of keratin biodegradation in S. maltophilia DHHJ, in which multiple pathways are involved such as protein folding, protein transport, and several protease systems. Our findings provide new insights into the mechanism of feather degradation.
DOI: 10.6084/m9.figshare.28829042.v2
title: Dataset of tardigrade species and environmental variables across a vehicular traffic gradient in Argentina

description: This dataset includes information on tardigrade communities (<i>fauna.xlsx</i>) and environmental variables (<i>vars.xlsx</i>) collected across three traffic intensity categories (high, medium, low) in Salta, Argentina. The study explores how vehicular traffic impacts tardigrade species composition and diversity, taking into account both microhabitat conditions (temperature, moisture, pH, bark thickness, light intensity, and the percentage of lichen, moss, and bare bark cover) and air pollution indicators (wind speed, noise levels, PM2.5, PM10, and vehicular traffic).The accompanying R script was used to statistically analyze these data and assess the influence of traffic-related pollution and seasonal variation on urban tardigrade diversity. Specifically, the analyses examine patterns in alpha diversity, species composition, and beta diversity partitioning, in relation to both microhabitat and air pollution variables.
DOI: 10.6084/m9.figshare.6834083.v1
title: SupplementaryData1.tar.gz

description: This zip file contains the data used to validate Haplosaurus. It contains a directory for each test gene in which there is the original GTF file and its Tabix index, the original FASTA file, a log file describing each applied test case and two directories: "hap" which contains a FASTA and GFF file per generated haplotype and "vcf" which contains a Tabix indexed VCF file per test case.<br>
DOI: 10.17632/rnhz3fvbj2
title: Surgical Waste Dataset

description: Please cite our paper titled 'A Computer Vision-based System for Surgical Waste Detection'



 Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130366 



The dataset is built based on real-time images from our surroundings including roads, beaches, water, maintenance holes and so on. Several images of the dataset are synthetic. Moreover, most of them are natural. Some images are taken using the Samsung Galaxy A51 smartphone camera and the rest of the images are taken from internet mining. Images are chosen from close range and distance range to make the dataset a distance variant. The angle variation left, right, back and top angle images are taken. The dataset comprises diverse gesture conditions such as curling and kneeling. At the time of image collection, this study tries to take different types of colored masks and gloves. The color variation of the mask is white, sky blue, pink, black and others. Different types of masks are included surgical, N95, Cone-style, KN95 and so on. Surgical gloves also have blue, white, black and pink colors. Transparent gloves are included with more eagerness to make the system as robust and reliable underwater as well as an object floating on the water condition. According to the above criteria, 1153 images are collected from different internet sources and smartphones camera.
DOI: 10.6084/m9.figshare.24162060.v1
title: Users (users.csv)

description: This file presents information about the profile of users that participated in the study.