cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.18461609.v1
title: Annual global forest gain maps from 1984 to 2020

description: Forest cover is rapidly changing at the global scale as a result of land-use change (principally deforestation in many tropical regions and afforestation in many temperate regions) and climate change. However, a detailed map of global forest gain is still lacking at fine spatial and temporal resolutions. In this study, we developed a new automatic framework to map annual forest gain across the globe, based on Landsat time series, the LandTrendr algorithm and the Google Earth Engine (GEE) platform. First, samples of stable forest collected based on the Global Forest Change product (GFC) were used to determine annual Normalized Burn Ratio (NBR) thresholds for forest gain detection. Secondly, with the NBR time-series from 1982 to 2020 and LandTrendr algorithm, we produced dataset of global forest gain year from 1984 to 2020 based on a set of decision rules. Our results reveal that large areas of forest gain occurred in China, Russia, Brazil and North America, and the vast majority of the global forest gain has occurred since 2000. The new dataset was consistent in both spatial extent and years of forest gain with data from field inventories and alternative remote sensing products. Our dataset is valuable for policy-relevant research on the net impact of forest cover change on the global carbon cycle and provides an efficient and transferable approach for monitoring other types of land cover dynamics.
DOI: 10.6084/m9.figshare.20011906.v1
title: The Future Digital Work Force: Robotic Process Automation (RPA)

description: Abstract The Robotic Process Automation (RPA) is a new wave of the future technologies. Robotic Process Automation is one of the most advanced technologies in the area of computers science, electronic and communications, mechanical engineering and information technology. It is a combination of both hardware and software, networking and automation for doing things very simple. In this light, the research manuscript investigated the secondary data - which is available in google, academic and research databases. The investigation went for totally 6 months, i.e., 1-1-2018 to 30-6-2018. A very few empirical articles, white papers, blogs and were found RPA and came across to compose this research manuscript. This study is exploratory in nature because of the contemporary phenomenon. The keywords used in searching of the database were Robotic Process Automation, RPA, Robots, Artificial Intelligence, Blue Prism. The study finally discovered that Robots and Robotic Process Automation technologies are becoming compulsory as a part to do business operations in the organizations across the globe. Robotic Process Automation can bring immediate value to the core business processes including employee payroll, employee status changes, new hire recruitment and on boarding, accounts receivable and payable, invoice processing, inventory management, report creation, software installations, data migration, and vendor on boarding etc. to name a few applications. Besides, the Robotic Process Automation has abundant applications including healthcare and pharmaceuticals, financial services, outsourcing, retail, telecom, energy and utilities, real estate and FMCG and many more sectors. To put in the right place of RPA in business operations, their many allied technologies are working at the background level, artificial intelligence, machine learning, deep learning, data analytics, HR analytics, virtual reality (second life), home automation, blockchain technologies, 4D printing etc. Moreover, it covers the content of different start-ups companies and existing companies - their RPA applications used across the world. This manuscript will be a good guideline for the academicians, researchers, students, and practitioners to get an overall idea.
DOI: 10.6084/m9.figshare.27132144.v1
title: MLR 识别

description: 一种基于伪标记的智能多车道道路识别方法
DOI: 10.6084/m9.figshare.28720523.v1
title: Additional file 1 of Retand LTR-retrotransposons in plants: a long way from pol to 3’LTR

description: Additional file 1. Species and genome assembly accession numbers used. Taxonomic information is retrieved from The Plant Tree of Life.
DOI: 10.6084/m9.figshare.28847258.v1
title: Phylogenetic diversity and community structure of Planctomycetota from plant biomass-rich environments

description: The data associated with this project include files used for Planctomycetota community analysis based on 16S rRNA gene amplicons, generated using custom primers and sequenced on the Illumina platform. The tables and OTU sequences provided here were used in the analysis presented in the research article entitled: Phylogenetic diversity and community structure of Planctomycetota from plant biomass-rich environments.The document "Otu_sequences" contains OTU sequences assigned to Planctomycetota.The document "count_table" contains a matrix showing the number of normalized reads per sample for each planctomycetotal OTU.
DOI: 10.17632/pp2sw5j4kt
title: Replication data: The Short and Long-Run Effects of International Environmental Agreements on Trade

description: The zip folder contains the data and codes to reproduce the results presented in the paper "The Short and Long-Run Effects of International Environmental Agreements on Trade" published in the Journal of International Economics. 

Please consult the README.pdf file before running the programs in Stata.
DOI: 10.17632/syg24p87mt
title: Data for: A Metasomatized 18O-rich Veined Lithospheric Mantle Source for Ultrapotassic Magmas
DOI: 10.17870/bathspa.7784426.v2
title: Re-writing the machinic anthropocene - Book: The Signal and the rock (2017)

description: ‘Re-writing the Machinic Anthropocene’ asks how speculative fictional methods can be used within the field of media art, to expose the materialities of digital technologies and to bring into view non human 'voices' and perspectives.<br><b>This item</b> contains documentation of the artist's book The Signal and the rock (2017). This book was presented alongside the exhibition at the Stanley Picker Gallery in 2017 and is designed to accompany the final audio work Re-writing the overcode (2017). The Signal and the rock operates as a form of fictive hyperobject, expanding on the function and the contents of the film and audio work and building on the strategies and methods of the practice via a series of cross-referenced notes from a wide variety of sources.<br>The book is significant as it enlists a set of non human fictive characters to highlight the non human perspectives and materialities of digital technologies, including characters such as the 'Digital Image' and the 'Mountain Gorilla' as well as decomposing electrical components located below an e-waste site. In the final part of the book a manifesto is outlined which directly engages with the research questions by employing fiction to re-write relations between man made machines, their raw materials and the earth.<br><b>All materials are owned and produced by Charlie Tweed and displayed with permission. The items remain in Copyright to Charlie Tweed and may not be reused or distributed.</b><b><br></b><b>Material in this item is under copyright and not to be used or shared without permission of the author and artist. Use of this repository acknowledges cooperation with its policies</b>.<br><br><br>
DOI: 10.6084/m9.figshare.18094043.v1
title: Solar photovoltaic annotations for computer vision related to the "Classification Training Dataset for Crop Types in Rwanda" drone imagery dataset

description: This dataset contains annotations (i.e. polygons) for solar photovoltaic (PV) objects in the previously published dataset "Classification Training Dataset for Crop Types in Rwanda" published by RTI International (DOI: 10.34911/rdnt.r4p1fr [1]). These polygons are intended to enable the use of this dataset as a machine learning training dataset for solar PV identification in drone imagery. Note that this dataset contains ONLY the solar panel polygon labels and needs to be used with the original RGB UAV imagery “Drone Imagery Classification Training Dataset for Crop Types in Rwanda” (https://mlhub.earth/data/rti_rwanda_crop_type). The original dataset contains UAV imagery (RGB) in .tiff format in six provinces in Rwanda, each with three phases imaged and our solar PV annotation dataset follows the same data structure with province and phase label in each subfolder.<b><br></b>Data processing:Please refer to this Github repository for further details: https://github.com/BensonRen/Drone_based_solar_PV_detection. The original dataset is divided into 8000x8000 pixel image tiles and manually labeled with polygons (mainly rectangles) to indicate the presence of solar PV. These polygons are converted into pixel-wise, binary class annotations.<b><br></b>Other information:1. The six provinces that UAV imagery came from are: (1) Cyampirita (2) Kabarama (3) Kaberege (4) Kinyaga (5) Ngarama (6) Rwakigarati. These original data collections were staged across 18 phases, each collected a set of imagery from a given Province (each provinces had 3 phases of collection). We have annotated 15 out of 18 phases, with the missing ones being: Kabarama-Phase2, Kaberege-Phase3, and Kinyaga-Phase3 due to data compatibility issues of the unused phases.2. The annotated polygons are transformed into binary maps the size of the image tiles but where each pixel is either 0 or 1. In this case, 0 represents background and 1 represents solar PV pixels. These binary maps are in .png format and each Province/phase set has between 9 and 49 annotation patches. Using the code provided in the above repository, the same image patches can be cropped from the original RGB imagery.3. Solar PV densities vary across the image patches. In total, there were 214 solar PV instances labeled in the 15 phase.<b><br></b>Associated publications:“Utilizing geospatial data for assessing energy security: Mapping small solar home systems using unmanned aerial vehicles and deep learning” [https://arxiv.org/abs/2201.05548]<br>This dataset is published under CC-BY-NC-SA-4.0 license. (https://creativecommons.org/licenses/by-nc-sa/4.0/)
DOI: 10.6084/m9.figshare.25596786.v1
title: Is ChatGPT Trusted like a Human? Comparing Human-Human and Human-AI Trust-Related Interactions

description: Artificial Intelligence (AI) agents represent a new class of social actors in social and economic systems. To facilitate harmonious relationships in human-AI societies we must understand how people perceive and build impressions of AI agents. The present research explores trust-related human-AI interactions, compared with human-human interactions, in the context of two fundamental dimensions of social cognition, i.e., warmth and competence. The results of two experimental studies (N = 802) show that AI agents elicit social cognition judgments similar to humans, but the levels of trust and the relationships between warmth / competence and trust are different for AI and human trustees.
DOI: 10.6084/m9.figshare.26763280.v1
title: Genesis of Seismic Gap of the 2008 Wenchuan and 2022&2013 Lushan Earthquakes: Insight from 3d Electrical Structure

description: The files is the dataset for the manuscript entitled 'Genesis of Seismic Gap of the 2008 Wenchuan and 2022&2013 Lushan Earthquakes: Insight from 3d Electrical Structure' by Wang et al., including data file(FullZ_1005.dat), Model file(RHO100.rho), and model covariance file(cov03.cov).
DOI: 10.6084/m9.figshare.28216202.v1
title: Prospective contingency explains behavior and dopamine signals during associative learning, Qian et al., 2025

description: Code and Data for Prospective contingency explains behavior and dopamine signals during associative learningAbstract: <b>Abstract</b>Associative learning depends on contingency, the degree to which a stimulus predicts an outcome. Despite its importance, the neural mechanisms linking contingency to behavior remain elusive. Here we examined the dopamine activity in the ventral striatum – a signal implicated in associative learning – in a Pavlovian contingency degradation task in mice. We show that both anticipatory licking and dopamine responses to a conditioned stimulus decreased when additional rewards were delivered uncued, but remained unchanged if additional rewards were cued. These results conflict with contingency-based accounts using a traditional definition of contingency or a novel causal learning model (ANCCR), but can be explained by temporal difference (TD) learning models equipped with an appropriate inter-trial-interval (ITI) state representation. Recurrent neural networks trained within a TD framework develop state representations like our best ‘handcrafted’ model. Our findings suggest that the TD error can be a measure that describes both contingency and dopaminergic activity.
DOI: 10.6084/m9.figshare.c.3665833_d5.v1
title: Additional file 2: of Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress

description: Phenotypic measurements of seedling upon heat and cold stress on 300 sorghum association panel. (XLSX 50Â kb)
DOI: 10.6084/m9.figshare.1367639.v1
title: 2013 Northwest Greenland Lake Depths from Landsat 8

description: This dataset contains information on supraglacial lake depths calculated from Landsat 8 imagery using an range of methods. Results to be published in Pope et al. (The Cryosphere). Methods to be published in Pope et al. (Computers and Geosciences). Lake depths are in mm.
DOI: 10.6084/m9.figshare.28794725.v2
title: <b>Data SLR </b><b>Safety Performance on Competitive Advantage</b>

description: This repository contains the dataset used for the systematic literature review (SLR) on the relationship between safety performance and competitive advantage in the shipping industry, following the PRISMA methodology.
DOI: 10.4121/uuid:c3f3ba2d-e81e-4274-87c7-882fa1dbab0d
title: BPI Challenge 2016: Werkmap Messages

description: BPI Challenge 2016. This particular file contains the activity log for Werkmap Messages. Parent item: BPI Challenge 2016 UWV (Employee Insurance Agency) is an autonomous administrative authority (ZBO) and is commissioned by the Ministry of Social Affairs and Employment (SZW) to implement employee insurances and provide labour market and data services in the Netherlands. The Dutch employee insurances are provided for via laws such as the WW (Unemployment Insurance Act), the WIA (Work and Income according to Labour Capacity Act, which contains the IVA (Full Invalidity Benefit Regulations), WGA (Return to Work (Partially Disabled) Regulations), the Wajong (Disablement Assistance Act for Handicapped Young Persons), the WAO (Invalidity Insurance Act), the WAZ (Self-employed Persons Disablement Benefits Act), the Wazo (Work and Care Act) and the Sickness Benefits Act. The data in this collection pertains to customer contacts over a period of 8 months and UWV is looking for insights into their customers' journeys. Data has been collected from several different sources, namely: 1) Clickdata from the site www.werk.nl collected from visitors that were not logged in, 2) Clickdata from the customer specific part of the site www.werk.nl (a link is made with the customer that logged in), 3) Werkmap Message data, showing when customers contacted the UWV through a digital channel, 4) Call data from the callcenter, showing when customers contacted the call center by phone, and 5) Complaint data showing when customers complained. All data is accompanied by data fields with anonymized information about the customer as well as data about the site visited or the contents of the call and/or complaint. The texts in the dataset are provided in both Dutch and English where applicable. URL's are included based on the structure of the site during the period the data has been collected. UWV is interested in insights on how their channels are being used, when customers move from one contact channel to the next and why and if there are clear customer profiles to be identified in the behavioral data. Furthermore, recommendations are sought on how to serve customers without the need to change the contact channel.
DOI: 10.6084/m9.figshare.11518017.v1
title: GLASER

description: (1): Analyzed internal transactions of attacked Parity wallet contracts.(2): Analyzed normal transactions of attacked Parity wallet contracts.(3-4): Analyzed internal transactions of malicious DoS contracts.(5): Analyzed normal transactions of malicious DoS contracts.(6-7): Analyzed internal transactions of meaningless contracts.(8): Analyzed normal transactions of meaningless contracts.(9-10): Analyzed internal transactions of stack/opcode error contracts.(11): Analyzed normal transactions of stack/opcode error contracts.(12): Analyzed transactions of DoS EOAs.(13): Analyzed internal transactions of empty accounts.(14): Analyzed normal transactions of empty accounts.<br><b>BibTeX citation:</b><br>@inproceedings{li2020glaser,title={Characterizing Erasable Accounts in Ethereum},author={Li, Xiaoqi and Chen, Ting and Luo, Xiapu and Yu, Jiangshan},booktitle={Proceedings of the 23rd Information Security Conference (ISC)},year={2020}}<br>
DOI: 10.6084/m9.figshare.13084805.v1
title: Data from Jacobs et al., Current Biology "Cortical state fluctuations during sensory decision making"

description: Please follow the links below to get to the actual data.<br>The data is organised into three categories (one link for each):- Behaviour- Pupil- WidefieldEach link contains zipped folders with the datasets organised by experimental subject. Most subjects were recorded from on multiple days, which form subfolders within the subject folder. Within a day, there may have been several experiments, which are again contained in subfolders within the day folder. The companion code (https://github.com/eakjacobs/Jacobs_et_al_CurrentBiology) is structured according to this data organisation.<br>If downloading all data (behaviour, widefield and pupil) to analyse them jointly, please keep the datasets organised into their own folders (ie, behaviour, widefield and pupil) as this is the organisation the companion code expects.<br>Both behaviour and widefield data come in different formats; the companion code can handle all of them and transforms them into a standard format as part of the preprocessing (which can be saved if desired). If there are any problems with this, please raise an issue on GitHub and I will look into it.Please also note that because the data provided is in raw format, the timestamps of the behaviour, pupil and widefield data are not aligned yet; the companion code takes care of this.<br>The behavioural data can be found at: https://doi.org/10.5522/04/13176959<br>The widefield data can be found at: https://doi/org/10.5522/04/13194452<br>The pupil data can be found at: https://doi.org/10.5522/04/13194155<br>The data from the simultaneous widefield and neuropixels recordings can be found at: https://figshare.com/articles/dataset/ctx_wf_traces_mat/13118435 & https://figshare.com/articles/dataset/muscimol_traces_mat/13122521<br>The neuropixels data can be found at: https://figshare.com/articles/steinmetz/9598406
DOI: 10.6084/m9.figshare.14553003.v1
title: Supplementary Material for: Cortisol Circadian Rhythm and Insulin Resistance in Muscle: Effect of Dosing and Timing of Hydrocortisone Exposure on Insulin Sensitivity in Synchronized Muscle Cells

description: <b><i>Introduction/Aim:</i></b> Circadian clock disruption is emerging as a risk factor for metabolic disorders, and particularly, alterations in clock genes circadian expression have been shown to influence insulin sensitivity. Recently, the reciprocal interplay between the circadian clock machinery and hypothal­amus-pituitary-adrenal axis has been largely demonstrated: the circadian clock may control the physiological circadian endogenous glucocorticoid (GC) secretion and action; GCs, in turn, are potent regulators of the circadian clock and their inappropriate replacement has been associated with metabolic impairment. The aim of the current study was to investigate in vitro the interaction between the timing-of-the-day exposure to different hydrocortisone (HC) concentrations and muscle insulin sensitivity. <b><i>Methods:</i></b> Serum-shock synchronized mouse skeletal muscle C2C12 cells were exposed to different HC concentrations resembling the circulating daily physiological cortisol profile (standard cortisol profile) and the circulating daily cortisol profile that reached in adrenal insufficient (AI) patients treated with once-daily modified-release HC (flat cortisol profile) and treated with thrice-daily conventional immediate-release HC (steep cortisol profile). The 24 h spontaneous oscillation of the clock genes in synchronized C2C12 cells was used to align the timing for in vitro HC exposure (<i>Bmal1</i> acrophase, midphase, and bathyphase) with the reference times of cortisol peaks in AI patients treated with IR-HC (8 a.m., 1 p.m., and 6 p.m.). A panel of 84 insulin sensitivity-related genes and intracellular insulin signaling proteins were analyzed by RT-qPCR and Western blot, respectively. <b><i>Results:</i></b> The steep profile, characterized by a higher HC exposure during <i>Bmal1</i>bathyphase, produced significant downregulation in 21 insulin sensitivity-related genes including <i>Insr, Irs1, Irs2, Pi3kca,</i> and <i>Adipor2</i>, compared to the flat and standard profile. Reduced intracellular IRS1 Tyr608, AKT Ser473, AMPK Thr172, and ACC Ser79 phosphorylations were also observed. <b><i>Conclusions:</i></b> The current study demonstrated that late-in-the-day cortisol exposure modulates insulin sensitivity-related gene expression and intracellular insulin signaling in skeletal muscle cells.
DOI: 10.6084/m9.figshare.3527750.v1
title: Appendix B. A global model predicting log-transformed bird species richness.

description: A global model predicting log-transformed bird species richness.
DOI: 10.6084/m9.figshare.21387396.v1
title: Data of testing system

description: Data of testing system
DOI: 10.6084/m9.figshare.24972801.v1
title: Impact of the Turbulent Vertical Mixing on Chemical and Cloud Species in the Venus Cloud Layer

description: Data from the paper <i>Impact of the Turbulent Vertical Mixing on Chemical and Cloud Species in the Venus Cloud Layer</i> The outputs are one time step between 37 and 78 km of altitude.EqNight.nc is for the Equator case at midnight<br>EqNoon.nc is for the Equator case at noon<br>75Night.nc is for the 75° of latitude case at midnight<br>75Noon.nc is for the 75° of latitude case at noon<br>The Altitude*.txt files are the corresponding altitude leves for each cases.<br>The variable are :PTOT : Pressure (Pa)<br>T : Potential temperature (K) - 735 K<br>U : Zonal wind (m/s)<br>V: Meridionnal wind (m/s)<br>W : Vertical wind (m/s)and the mixing ratio for the species in kg/kg<br><br>More information about the file is available with the command "ncdump -h ./X.nc"
DOI: 10.6084/m9.figshare.7218497.v1
title: Dataset: Fitbits, field-tests, and grades. The effects of a healthy and physically active lifestyle on the academic performance of first year college students.

description: The data were collected during the Fall semester of 2017 from 581 freshmen enrolled at Oral Roberts University in a class entitled “Introduction to Whole Person Education” which has a required health and physical exercise component consisting of: Steps and Active Minutes goals, a 1-mile field test, and a lifestyle assessment survey. Students utilize a Fitbit to help keep track of their steps and active minutes which are synced with the course gradebook. The student’s semester grade point average was added once the semester was complete. As the grades were retrieved and stored, the dataset was de-identified to ensure confidentiality.
DOI: 10.6084/m9.figshare.27283119.v4
title: Supplementary Table of "<b>Genomic Selection and wssGWAS of Sheep Body Weight and Milk Yield: Imputing Low-Coverage Sequencing Data with Similar Genetic Background Panels"</b>

description: Supplementary Table of "<b>Genomic Selection and wssGWAS of Sheep Body Weight and Milk Yield: Imputing Low-Coverage Sequencing Data with Similar Genetic Background Panels"</b>