cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rryf548b6p
title: Herbal Leaf Repository Unveiling Nature's Pharmacy

description: This database contains a comprehensive collection of images showcasing both healthy and diseased leaves of Curry tree (Scientific name: Murraya koenigii), Neem (Scientific name: Azadirachta indica), Longevity spinach (Scientific name: Gynura), Red spinach (Scientific name: Amaranth Dubius) and Holy Basil (Scientific name: Ocimum tenuiflorum). All the images featured in this database were taken by the creators directly from fields situated in the Ranaghat district of West Bengal, India.
The images within this database feature detailed backgrounds, including elements such as weeds, soil, and sections of other plants. The main goal of creating this database is to provide a wide range of labelled foliage images of diverse plant species. These images are designed for training deep neural networks to classify them automatically into different plant categories. By incorporating foliage images with complex backgrounds and captured under various lighting conditions, this database enhances its ability to effectively train deep neural networks, enabling precise real-world identification for the specified task.
The images in this database were taken using mobile phones, specifically the Samsung Galaxy S20 FE 5G with the following camera specifications: a 12MP (Dual Pixel) OIS F 1.8 Wide Rear Camera, an 8MP OIS Tele Camera, and a 12MP Ultra-Wide 30X Space Zoom. Additionally, images were captured using the Redmi Note 9 Pro Max, which features a camera array comprising 64MP+8MP+5MP+2MP, utilizing Artificial Intelligence (AI) technology.
DOI: 10.25403/upresearchdata.28322483.v1
title: Perceived value of artificial intelligence by public sector blue-collar worker in the Johannesburg Metropolitan Public Sector (JMPS)

description: The purpose of this study was to explore the perceived value of AI by public sector blue-collar workers in the Public Sector. The study opted for a quantitative survey method for data collection using both online cross-sectional closed-question, and paper-form questionnaires. Three main hypotheses were utilised to investigate the relationship between the general attitudes of different subgroups of blue-collar workers and their willingness to adopt AI usage towards the enhancement of service delivery. Four other hypotheses tested the relationship between service delivery, AI, and Human Resource (HR) management support for AI education. The sample consisted of 205 workers. The Statistical Package for Social Sciences was used to capture and analyse the collected data. The descriptive statistics analysis showed that the data was reliable, consistent, and valid between a 95 and 99% confidence limit. The willingness to adopt AI usage constructs versus the information, communication, and technology automation factor in the human resources management support construct showed poor Pearson’s and poor Spearman correlation coefficients. Blue-collar workers showed unwillingness towards automation and the use of AI in routine jobs at the workplace. There was a positive attitude towards the use of AI to enhance perceived value, provided it is not used for blue-collar workers' routine jobs.
DOI: 10.6084/m9.figshare.105431.v1
title: THE TOPLINE EDITION OF THE 2012 UC, BIORAFT AND NPG LAB SAFETY SURVEY DATA

description: All data were anonymized and the UC Center for Laboratory Safety (UCCLS) and BioRAFT, who commissioned the study, shared overview results with <em>Nature</em>. Nature Publishing Group, who co-launched the survey, then conducted its own analysis to pick out significant trends. UCCLS and BioRAFT have permitted publication of overview data but are retaining the raw dataset for more closer analysis in 2013.
DOI: 10.6084/m9.figshare.9337481.v2
title: Sri Lanka Compost Characteristics (March 2019)

description: Compost samples were collected in March 2019 from 19 composting facilities in Sri Lanka's Western and Southern Provinces. Each sample was a composite of multiple samples collected from finished compost piles in a systematic pattern. Samples were stored in a cooler with ice packs during transport and sampling equipment was disinfected between facilities. All analyses were conducted at the Industrial Technology Institute in Colombo, Sri Lanka, with the exception of % moisture for 9 of the 19 samples (measured at Sabaragamuwa University of Sri Lanka). Dr. Roy led the sampling trip, with coordination assistance from Drs. Esham and Otoo. In adherence to the project plan and information sheet approved by IRB at the University of Vermont, this dataset does not include facility identifying information, and data have been randomized so that they do not reflect the order in which samples were collected. These data will eventually be published as part of a study on compost nutrient supply and crop nutrient demand across urban-to-rural gradients nationwide in Sri Lanka.
DOI: 10.17632/dhcf8jbhd4
title: Chen_et_al_Molecular_Cell

description: Raw_Images
DOI: 10.6084/m9.figshare.12940052.v1
title: Supplementary data and scripts from Winbush and Singh (2020)

description: Contains supplementary data and relevant scripts for the manuscript:<br>Genomics of recombination rate variation in temperature-evolved <i>Drosophila melanogaster</i> populations.<br>
DOI: 10.6084/m9.figshare.28321559.v2
title: CGFlow supplementary data

description: Contains preprocessed CrossDock dataset for training pose prediction and the pretrained pose prediction model. <br><br>
DOI: 10.6084/m9.figshare.5687551.v1
title: Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning

description: Experimental data (successful and failed experiments) along with the Curie temperature measurement data.
DOI: 10.6084/m9.figshare.7038836.v1
title: Recent (post-1930) changes in the extent of subtidal seagrass (<i>Zostera muelleri</i>) beds of the eastern Bay of Islands, New Zealand

description: The surface areas of 12 subtidal seagrass <i>Zostera muelleri</i> beds at the islands and adjacent mainland shores of the eastern Bay of Islands (35° 12′ S, 174° 10′ E), New Zealand were estimated from aerial images. It appears that little subtidal seagrass existed until after the early-1950s, so significant beds here may be a relatively recent biome. Possible explanations for recent emergence of subtidal seagrass include that debilitating periods of turbid water and pulses of sedimentation associated with the land clearances of the late 1800s had worked through the marine ecosystem. An overall peak in seagrass-cover in the 1960s to 1980s was followed by declines in several beds in the 1990s to 2000s, with recovery since. The temporal presence of seagrass was well-correlated among the three mainland beds, and moderately well among the south-facing beds on the islands, consistent with mechanisms driving seagrass establishment and persistence operating at reasonably broad scales.
DOI: 10.60893/figshare.apl.28369115.v1
title: Supplementary Materials

description: Supplementary Materials
DOI: 10.17632/6bmcjn5s3c
title: Dataset of Named Entity Recognition for Uzbek language (11,000+)

description: As part of the study, an annotated corpus of the Uzbek language was created for training and evaluating named entity recognition models. The corpus includes 11,634 sentences (99408 words) collected from various sources:
• Legislative acts and legal documents: The bulk of the data was extracted from the publicly available lex.uz database, which contains official texts that are highly literate and have a formal language structure.
• Manually created sentences: To increase the number of named entities in sentences and ensure diversity, author's sentences were developed containing several entities of different types. This enriched the corpus with complex structures and increased the efficiency of model training.
Data annotation was carried out manually using the BIOES scheme, which provides detailed marking of boundaries and types of named entities. All abstracts were reviewed by Uzbek language experts to ensure accuracy and consistency of data.
DOI: 10.6084/m9.figshare.16617901.v1
title: RNA sequencing breast cancer patient data from TCGA

description: RNA sequencing breast cancer patient data from TCGA website.
DOI: 10.6084/m9.figshare.21076750.v1
title: supplemental file for peer review.pdf

description: <strong>Supplemental material: Metabolic Efficacy of Time-Restricted Eating in Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Trials</strong>
DOI: 10.6084/m9.figshare.28250960.v1
title: Data for "Integrating neural operators with diffusion models improves spectral representation in turbulence modeling" (Kolmogorov Flow Case)

description: The dataset consists of 1000 trajectories of the Kolmogorov Flow, simulated using the publically available pseudo-spectral solver provided in FNO's Github Repository - https://github.com/neuraloperator/physics_informed/blob/d1835d1e6ee9d7969455ceb36040389a23d04d85/solver/legacy_solver.py#L68The dataset has the shape - [n_samples=1000, nx=128, ny=128, nt=201]
DOI: 10.6084/m9.figshare.28815389.v1
title: 20250211_SPIRIT_Checklist.doc

description: SPIRIT_Checklist
DOI: 10.25375/uct.26942134.v5
title: ESRG Hourly Demand Model v2025 by Province

description: Spreadsheet tool, which helps user construct hourly demand profiles to 2050 for South Africa, for a given set annual energy projections by sector and calibrated profiles by sector.Model calibrated to 2017 data and uses SATIMGE commit: 75aac7f718addb9766ae46e9702d95660b89271bIncludes some preliminary projections for distributed PV. This can be included or excluded by the user, as well as other onsite generators such as Sasol gas turbines, and exports.<br><br>This version was used to do a simple downscaling to Eskom Supply Areas (Provinces + Hydra), done here:<br>https://github.com/GregoryIreland/Demand-Spatialization-South-Africa<br>
DOI: 10.6084/m9.figshare.12886778.v2
title: Data Set ADHD, ASD and Control all variables

description: Raw DWT coefficients and subject data used in the analysis
DOI: 10.6084/m9.figshare.1541129.v2
title: Gender and Eye Colour of Twenty Individuals

description: The gender and eye colour of a sample size of twenty participants was collected on September 14, 2015, between 2:30 PM and 5:30 PM at York University. Partners in data collecting included Abera, Elaine, and Sufyan. Data was collected by asking twenty participants what their gender was (either male or female), and their eye colour (categorized into five sections explained in the meta-data). The primary goal of data collection was for educational purposes.
DOI: 10.17632/8xtcr9pn6h
title: Structural insights into the ion selectivity of the MgtE channel for Mg2+ over Ca2+

description: SDS–PAGE gel pictures for Figure S2
DOI: 10.17632/bn2ptzr5p6
title: Cuestionario para la evaluación de un proyecto educativo universitario para el desarrollo sostenible

description: Se trata del cuestionario utilizado para el estudio "Metodología para la evaluación de un proyecto educativo universitario para el desarrollo sostenible" en que se basa un artículo de investigación publicado en Paradigma: Revista de Investigación Educativa 27(43):9-30. DOI: 10.5377/paradigma.v27i43.9874 LicenseCC BY-NC-ND 4.0
DOI: 10.6084/m9.figshare.12196728.v1
title: Materials Project structures (04-24-20)

description: Materials Project structures for materials with no f-block elements, download on 04-24-20. Additional thermodynamic data from first-principles calculations (formation energy, energy above convex hull, etc.) is also included.
DOI: 10.6084/m9.figshare.21091702.v1
title: Karyotype projections of eudicots

description: Karyotype projections of eudicots<br> column 1 is the name of chromsome column 2 is the beginning of the projection in chromosome column 3 is the end of the projection in chromosome column 4 is the color used column 5 is used to identify copies
DOI: 10.6084/m9.figshare.24093792.v1
title: Figure data and model files for VO2-metal metasurface modulator

description: VO2 modulator all figs.xlsx contains all x-y figure data used in our publication.squareringFSS-VO2-TiO2_001mesh_backward.fsp is our lumerical FDTD model for backwards illumination<br>squareringFSS-VO2-TiO2_001mesh_forward.fsp is our lumerical FDTD model for forwards illuminationModeling_isolation behavior.mph is our COMSOL heat transfer model.
DOI: 10.6084/m9.figshare.3555402.v1
title: Appendix C. Detailed results for mixed model analysis and tests of bias.

description: Detailed results for mixed model analysis and tests of bias.
DOI: 10.6084/m9.figshare.11967921.v1
title: L2 Section, Sample 24. 81 Year Old Female

description: A 3 mm thick para-sagittal slice of L2 vertebra from an 81 year old female embedded in PMMA then micro-milled block surfaces carbon coated for quantitative 20kV BSE SEM.<br><br>Later polished to remove coating and then imaged with high-contrast X-Ray Micro-tomography at 90 kV with 30 micron voxel size.
DOI: 10.6084/m9.figshare.12089652.v1
title: Atlas of 30 Human Brain Bundles in MNI space

description: This is a dataset to be used by the RecoBundles algorithm to automatically extract anatomically relevant bundles from tractograms. RecoBundles is available in DIPY (http://dipy.org). The algorithm is explained in the paper:<br><br>Garyfallidis, Eleftherios, et al. "Recognition of white matter bundles using local and global streamline-based registration and clustering." NeuroImage 170 (2017): 283-297.<br>https://www.ncbi.nlm.nih.gov/pubmed/28712994<br>This dataset is curated from the dataset explained in the following paper:<br>Yeh, Fang-Cheng, et al. "Population-averaged atlas of the macroscale human structural connectome and its network topology." NeuroImage 178 (2018): 57-68.<br>https://www.sciencedirect.com/science/article/pii/S1053811918304324<br>All the bundles and trk (Trackvis) files are in MNI space ICBM 2009a.<br>Do contact the DIPY developers at https://gitter.im/nipy/dipy if you need the bundles at ICBM 2009c space.<br>For the Fornix (F) both left and right sides are included in one file. It is possible to easily separate them if you need to. Send an e-mail to dipy@python.org to learn how.<br>If you use this dataset please cite Garyfallidis et al. 2017 and Yeh et al. 2018 (see above).<br>Research reported in this publication was supported primarily by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R01EB027585.<br><br><br><br>Happy RecoBundling!<br>
DOI: 10.6084/m9.figshare.21370236.v5
title: PSY-COVID-1, Study of University Students Dataset

description: These are the two datasets extracted from the PSY-COVID-1 study for the analysis of the university students's mental health. Dataset labelled "Dataset PSY-COVID university students " contains only data of 7601 from 6 Ibero-American countries (Argentina, Colombia, Ecuador, Spain, Mexico, and Uruguay). Dataset labelled "Dataset PSY-COVID university students & country-matched general population" contain data from the same participants in the first dataset plus a sample of 51211 from the general population of the same 6 countries.
DOI: 10.6084/m9.figshare.24881844.v1
title: Data from Pyrogeography in Flux

description: Data associated with CX Cunningham, G. Williamson, RH Nolan, L Teckentrup, MM Boer, DMJS. Bowman. (2024) Pyrogeography in flux: reorganisation of Australian fire regimes in a hotter world. <i>Global Change Biology</i><b>Data:</b>Data to run the analyses delineating Australia's pyroregions: <i>"fireMetricStack_20230821.tiff",</i> <i>"npp_mean.tif"</i>, and <i>"NDVI_diff.tif"</i>Folder containing files used to define study area and grid resolution: <i>"</i><i>G</i><i>rid templates</i><i>"</i>Historical climate data: <i>"AUS_wc2.1_30s_bio.tif"</i>Folder containing projected climate data under three scenarios: <i>"</i><i>Future climate protections</i><i>"</i>
DOI: 10.17632/352hc4rjhf
title: Computed geometrical descriptors of drug-linker moieties

description: The particle size of the drug-linker moieties in currently approved antibody-drug conjugates is not available in the literature at the time of writing. I had expected it to be in the nanoscale, on the basis of known structures and average bond lengths. To confirm this hypothesis, I carried out a computational study in MarvinSketch. This dataset contains structure (.mrv) and image (.png) files. The .mrv files represent the final structures of the drug-linker moieties. The .png files are screenshots of the results obtained using the Geometrical Descriptors plugin in MarvinSketch. The computed geometrical descriptors are the Dreiding energy, MMFF94 energy, minimal projection area, maximal projection area, minimal projection radius, maximal projection radius, maximal distance perpendicular to the maximal area, maximal distance perpendicular to the minimal area, van der Waals volume. Information on how to interpret these parameters is available at https://docs.chemaxon.com/display/docs/calculators_geometrical-descriptors-plugin.md. Among these parameters, two from which the diameter of a drug-linker can be estimated are the maximal distance perpendicular to the minimal area and the maximal distance perpendicular to the minimal area; these distances are in the nanoscale for all drug-linker moieties, confirming the original hypothesis. 
These files can be used in future theoretical and computational studies.
The .png files can be opened with a picture display software.
The .mrv files can be opened in MarvinSketch, but other chemical editors may recognize them as well.
DOI: 10.17632/ybcvvmtcn9
title: Source data

description: Source data for figures in the related paper, including raw data underlying graphs and uncropped versions of gels or blots presented in the figures
DOI: 10.6084/m9.figshare.12200522.v1
title: Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus interaction

description: <b>Supplemental tables for the manuscript titled “Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus interaction”.</b><b> </b>
DOI: 10.6084/m9.figshare.24369109.v1
title: Annotation result of Orobanche coerulescens

description: Annotation result of Orobanche coerulescens
DOI: 10.17632/bpbsfs26td
title: IMAGE SET FOR FLOWER DETECTION IN APPLE TREES

description: This dataset is composed of 58 apple tree images. They were taken during full bloom in an apple orchard located at National Institute of Agricultural Technology (INTA) Experimental Station, General Roca, Argentina (39° 1’ 34’’ S; 67° 44’ 24.6’’ W).The orchard was established in 2000 with ‘Red Chief’ cultivar apple trees grafted on MM111 rootstock .Trees were planted in a total area of 0.8 ha at a distance of 1.5m between trees by 4m between rows and were trained as espalier. A few days before full bloom, images were obtained from 32 trees, under two conditions: i) natural daylight between 10 am and 13 pm, ii) at night with the artificial flash light of the camera. A black curtain was unfolded behind the trees when images were obtained under daylight conditions in order to avoid interference from neighboring trees. All images were taken with an RGB digital camera (14.1 MP) at approximately 3.0 m from the tree in a 90° angle to the row. An object of known dimensions (a 15x15 cm square) was placed in each tree as a scale reference. Simultaneously, all the flowers on each tree were manually counted. Images taken by using different proximal sensors can be used to estimate the number of flowers or fruits in trees. The accuracy of those methods have been studied and tested by many researchers during the past few years with encouraging results. Since manual counting method in fruit crops is a time-consuming labor and also lead to inaccurate results, image analysis could be used as an alternative procedure. The use of images could provide reliable and consistent data.
DOI: 10.6084/m9.figshare.21183775.v1
title: data

description: Data to generate figures of manuscript '<strong>DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits'</strong>
DOI: 10.6084/m9.figshare.25037045.v4
title: Movie annotations for: Multimodal single-neuron, intracranial EEG, and fMRI brain responses during movie watching in human patients

description: Movie annotations for the manuscript: "Multimodal brain responses during movie watching: single-neuron, intracranial EEG, and fMRI in human patients"Authors: Umit Keles, Julien Dubois, Kevin J. M. Le, J. Michael Tyszka, David A. Kahn, Chrystal M. Reed, Jeffrey M. Chung, Adam N. Mamelak, Ralph Adolphs, Ueli RutishauserAbstract: We present a multimodal dataset of intracranial recordings, fMRI, and eye tracking in 20 participants during movie watching. Recordings consist of single neurons, local field potential, and intracranial EEG activity acquired from depth electrodes targeting the amygdala, hippocampus, and medial frontal cortex implanted for monitoring of epileptic seizures. Participants watched an 8-min long excerpt from the video "Bang! You're Dead" and performed a recognition memory test for movie content. 3 T fMRI activity was recorded prior to surgery in 11 of these participants while performing the same task. This NWB- and BIDS-formatted dataset includes spike times, field potential activity, behavior, eye tracking, electrode locations, demographics, and functional and structural MRI scans. For technical validation, we provide signal quality metrics, assess eye tracking quality, behavior, the tuning of cells and high-frequency broadband power field potentials to familiarity and event boundaries, and show brain-wide inter-subject correlations for fMRI. This dataset will facilitate the investigation of brain activity during movie watching, recognition memory, and the neural basis of the fMRI-BOLD signal.This dataset accompanies the following data descriptor: Keles, U., Dubois, J., Le, K.J.M., Tyszka, J.M., Kahn, D.A., Reed, C.M., Chung, J.M., Mamelak, A.N., Adolphs, R. and Rutishauser, U. Multimodal single-neuron, intracranial EEG, and fMRI brain responses during movie watching in human patients. Sci Data 11, 214 (2024). https://doi.org/10.1038/s41597-024-03029-1Related code: https://github.com/rutishauserlab/bmovie-release-NWB-BIDSIntracranial recording data: https://dandiarchive.org/dandiset/000623fMRI data: https://openneuro.org/datasets/ds004798/<br>
DOI: 10.6084/m9.figshare.3521216.v1
title: Appendix C. Literature summary of papers investigating global transcript expression in Daphnia.

description: Literature summary of papers investigating global transcript expression in Daphnia.
DOI: 10.17632/tgrhbvgrdc
title: Photo-Realistic Traffic Scene Datasets: Real and Synthetic Perspectives

description: This dataset provides a comprehensive collection of traffic scene datasets, categorized into three main groups: Traffic Scene Datasets, Top-View Datasets, and Depth Datasets. Each group includes both real-world and synthetic datasets, designed to support research in autonomous driving and computer vision. These datasets are intended to assist in various research areas, such as road user detection, top-view traffic analysis, traffic pattern recognition, depth information extraction, and infrastructure monitoring using aerial views in urban environments.
DOI: 10.17632/v3wgx8pm5y
title: embryonic tooth germ scRNA and ST

description: single cell and spatial transcriptomics of human embryonic tooth germ