cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26151751.v1
title: Supplementary data supporting the revised article "Comparative Genomics of <i>Metarhizium brunneum</i> strains V275 and ARSEF 4556: Unravelling intraspecies Diversity" submitted to G3(Bethesda) journal

description: Entomopathogenic fungi (EPF) belonging to the Order Hypocreales are renowned for their ability to infect and kill insect hosts, while their endophytic mode of life and the beneficial rhizosphere effects on plant hosts have only been recently recognised. Understanding the molecular mechanisms underlying their different lifestyles could optimise their potential as both biocontrol and biofertilizer agents, as well as the wider appreciation of niche plasticity in fungal ecology. This study describes the comprehensive Whole Genome Sequencing (WGS) and analysis of one of the most effective entomopathogenic and endophytic EPF strains, <i>Metarhizium brunneum</i> V275 (commercially known as Lalguard Met52), achieved through Nanopore and Illumina reads. Comparative genomics for exploring intra-species variability and analyses of key gene sets was conducted with a second effective EPF strain, <i>M. brunneum</i> ARSEF 4556<i>. </i>The search for strain- or species- specific genes was extended to <i>M. brunneum</i> strain ARSEF 3297 and other species of genus <i>Metarhizium</i>, to identify molecular mechanisms and putative key genome adaptations associated with mode of life differences.<i> </i>Genome size differed significantly, with <i>M. brunneum</i> V275 having the largest genome amongst <i>M. brunneum</i> strains sequenced to date. Genome analyses revealed an abundance of plant-degrading enzymes, plant colonization-associated genes and intriguing intraspecies variations regarding their predicted secondary metabolic compounds and the number and localization of Transposable Elements. The potential significance of the differences found between closely related endophytic and entomopathogenic fungi, regarding plant growth-promoting and entomopathogenic abilities, are discussed, enhancing our understanding of their diverse functionalities and putative applications in agriculture and ecology.
DOI: 10.17632/3x6n7pygz6
title: A Solar Thermal Storage System Aspen Plus Dynamic Model with Control 

description: This Aspen Plus Dynamic file contains the code to simulate a solar thermal storage system dynamically using solar insolation and ambient temperature as forcing functions. The user should download and install the custom unit operations provided for the stratified tank and solar collector which are available online (http://dx.doi.org/10.17632/pv4znnnv3j.1). Detailed instructions for activating the installed components are available in the “Computer Based Training” section of the Aspen Custom Modeler Jump Start (Tremblay & Peers, 2015).  See "Read Me" file for details regarding dynamic model use.
DOI: 10.17632/w4hp2rb2tz
title: Multi-Objective optimisation of the European power system by 2050: Datasets and Supplementary Materials

description: ******************* Please view the README.txt file for detailed documentation of data. ******************** Title: Multi-Objective optimisation of the European power system by 2050: Datasets and Supplementary Materials Version: 1.0 Date of Release: XX/XX/2019 Identifier: doi:10.17632/w4hp2rb2tz.1 Permalink: http://dx.doi.org/10.17632/w4hp2rb2tz.1 Associated publication: Louis, JN, Allard, S, Kotrotsou, F, Debusschere, V (2019) "Multi-Objective optimisation of the European power system by 2050." Energy. doi:10.1016/j.energy.2019.116539 Link to publication: http://dx.doi.org/10.1016/j.energy.2019.116539 Suggested citation: Please reference the associated publication above when using any datasets or materials described in the README file. Contact information: Jean-Nicolas Louis, University of Oulu, Oulu, Finland, jean-nicolas.louis@oulu.fi or jeannicolas.louis@gmail.com Dates of data modelisation: 2000 - 2050 Geographic location: Europe 24: Austria, Belgium, Bulgaria, Switzerland, Czech Republic, Germany, Denmark, Spain, Finland, France, Great-Britain, Greece, Hungary, Ireland, Italy, Luxembourg, The Netherlands, Norway, Poland, Portugal, Romania, Sweden, Slovakia, Slovenia Time resolution: Year. Hours of the day data were not made available due to size restriction but can be obtained on demand. Format: All data are stored in an XML format. XML data can be parsed in any parser for accessing the database. This directory contains the following datasets and supplementary materials: A summary of all the files has been compiled and stored in the "Individual Files Description.txt" file SUPPLEMENTARY TEXT AND FIGURES
DOI: 10.6084/m9.figshare.25188650.v2
title: BILBI model data for SSP1/RCP2.6 and SSP5/RCP8.5

description: This folder provides the data needed to calculate the proportion of species persisting based on the BILBI model (Hoskins et al 2020) using the climate and land-use projections described in (Di Marco et al 2019) at different spatial scales.<br>Di Marco, M. <i>et al.</i> Projecting impacts of global climate and land-use scenarios on plant biodiversity using compositional-turnover modelling. <i>Global Change Biology</i> <b>25</b>, 2763–2778 (2019).Hoskins, A. J. et al. BILBI: Supporting global biodiversity assessment through high-resolution macroecological modelling. <i>Environmental Modelling and Software</i> 132, 104806 (2020)<br>
DOI: 10.6084/m9.figshare.4868399.v1
title: Pisum sativum (a) - CRootBox parameter file

description: CRootbox parameter file for Pisum sativum (a).<br><br>from:<br><br>Modelling the root system architecture of Poaceae. Can we simulate integrated traits from morphological parameters of growth and branching? Pages L, Picon-Cochard C New Phytologist, 204, 149-158, 2014
DOI: 10.17632/jmrv4t94mj
title: Data from Characterization and Risk Assessment of Nanoparticle Emissions from 3D Printing with PLA+GO Filament: A Pilot Study According to European Standards

description: Data from aerosol sampling devices such as Aerosol Particle Sizer APS (APS 3321-TSI), Condensation Particle Counters (CPC 3786-TSI, P-TRAK 8525-TSI) and Cascade Impactor SKC Sioutas for the measurement of particles and nanoparticles released to the environment when using a 3D printer with PLA opped with Graphene Oxide as filament, as well as the results from the ARIMA test performed on them. 
Each sheet from the dataset is named after the Figure from the article that uses this data.
DOI: 10.6084/m9.figshare.13011263.v1
title: data.xlsx

description: <b>Date for the publication </b><b>Validation of quantitative assessment of </b><b>indocyanine</b><b> green fluorescent imaging in </b><b>a</b><b> one-vessel model. </b><b></b>
DOI: 10.17632/447dppnf9h
title: Water Quality Parameters for Lettuce Aquaponic System using IoT Sensors

description: This dataset contains water quality parameters collected from a lettuce aquaponic system using IoT sensors during the period of January-March 2023. The dataset includes measurements of water pH, Total Dissolved Solids (TDS), and water temperature with dynamic sampling intervals.
Dataset Specifications:

Period: January-March 2023
Total records: 118,286
Format: CSV
Parameters: timestamp, water_pH, TDS, water_temp
Sampling interval: Dynamic sampling with intervals ranging from 1 to 9 minutes, adjusted based on system conditions
Value ranges:

pH: 6.5 - 8.5
TDS: 200-400 ppm
Temperature: 23-26°C
DOI: 10.17632/xgghkjvw2m
title: RNA-seq data for "pLxIS-containing domains are biochemically flexible regulators of interferons and metabolism"

description: Bulk RNA-sequencing data of iBMDMs expressing STING, TRIF, MAVS, IRSp53, and GMIP nanomachines and stimulated with B/B. Please see the publication "pLxIS-containing domains are biochemically flexible regulators of interferons and metabolism" by Landau et al. for more details.
DOI: 10.17632/83ht2kc8xt
title: First-principles calculations of specular reflection of high-energy electrons during the two-dimensional crystal growth

description: RHEED_DIFF_2D is an open-source software capable of performing qualitative numerical simulations of changes to the intensity of RHEED oscillations in the function of the layer deposited, employing various models of scattering crystal potential for heteroepitaxial structures of bcc (001) films nucleated on a fcc (001) surface, including the possible existence of various diffuse scattering models through the layer parallel to the surface. This model can be used for interpreting data weakly dependent on the azimuth of the incident electron beam direction and for 2D monolayer-by-monolayer growth modes. The program does not use any external data sources.
DOI: 10.17632/czbvhmzwm3
title: Probability of Automation of Occupations 2036

description: We used a similar CBTC methodology to Frey and Osborne (2017), Autor and Dorn (2013), and Caines et al. (2017). The US Department of Labor’s Dictionary of Occupations Titles (DOT) classification system and the 2010 Standard Occupation System (SOC), which allowed for the respective data sets to be cross-referenced. The 2010 SOC system classified 840 detailed occupations with similar job duties, skills, education and training into 461 broad occupations, 9 minor occupations and 23 major groups (U.S. Bureau of Labor Statistics, 2010). We also used a secondary data set, namely US Occupational Employment Statistics (OES) data as it contained detailed occupational descriptions and employment statistics per occupation for the US economy, broken down per industry according to the NAICS classification system. The NAICS is an industry classification system that grouped organisations into industries based on similarities in production processes. It used a six-digit coding system to classify all economic activities in the US across 20 industry sectors and 1 057 detailed industries (U.S. Office of Management and Budget, 2017). Employment data was classified according to the 2010 SOC system that contained 820 occupations. With the emergence of new roles and reclassification of the SOC system over the same duration, certain classifications needed to be cross-referenced (“crosswalked”) to provide comparable figures across different years. In their studies, Frey and Osborne (2017), Caines et al. (2017) and Autor and Dorn (2013) aggregated the occupations slightly differently. For example, Frey and Osborne (2017) aggregated specific “postsecondary teaching” occupations into a single category and omitted occupations containing “all other”, whilst Caines et al. (2017) omitted selected “farm and agricultural” occupations. In total, Frey and Osborne (2017) calculated the probability of job automation for 702 occupations. Autor and Dorn (2013) calculated job routineness for 330 aggregated occupations. Caines et al. (2017) calculated job complexity for 315 aggregated occupations. Our approach combined and cross-referenced all of the above-mentioned data sets to produce a total of 291 occupations for the analysis. In projecting the change in workforce structure from 2016 to 2036, the 2016 OES employment numbers were adjusted for the “probability of job automation” at an occupational level, and aggregated to illustrate the relative change in workforce structure for the entire US economy. Occupations which did not have a corresponding measure of “probability of job automation” were omitted from the analysis. After omissions, this analysis represented 96.3% of the US workforce in 2016.
DOI: 10.6084/m9.figshare.26789080.v1
title: Evidence table (with all screened articles)

description: This dataset includes a total of 2,011 publications that were screened, with 249 articles meeting the inclusion criteria and subsequently reviewed. The search strategy and the inclusion criteria used for selecting these articles are detailed in the study protocol (Cozzolino C, Mao S, Baldo V. PROSPERO. Artificial Intelligence for surveillance of healthcare-associated infections. CRD42024524497. 2024)
DOI: 10.17632/3mhh3tk22z
title: Career orientation, career engagement and goal achievement

description: This is the dataset for a study that examined the career orientation, career engagement and goal achievement of national service persons in Ghana. In the study, it was hypothesized that career orientation of national service persons relates positively to their career engagement, learning goal orientation and performance goal orientation. It was also hypothesized that learning and performance goal orientations both relates to career engagement and they would both in turn, mediate the relations between career orientation and career engagement. Following the data analysis using PLS-SEM procedures, there was no evidence to reject any of the hypothesis. Additionally, a multigroup analysis revealed that there was a significant difference in the mediating role of performance goal orientation in the relation between career orientation and career engagement of female and male national service persons.
DOI: 10.17632/7thwn6rxbd
title: From the Emoji to the Conversion: Looking Behind Consumers’ Reactions Online

description: We have used this dataset to measure the interplay between exposure to emoji on one side and positive affect, purchase intent, campaign effectiveness, click-through rate (CTR), and return on advertisement spent (ROAS). The dataset consists of two studies whereby study I is based on the self-administered survey, while the follow-up study has an experimental 2x2 between-subjects design. Additionally, we observed gender differences in terms of emoji exposure and purchase intent.
DOI: 10.17632/md8jp9ny9z
title: Mid-19th-century building structure locations in Galicia and Austrian Silesia under the Habsburg Monarchy

description: The dataset presents a reconstruction of mid-19th-century building structure locations in former Galicia and Austrian Silesia (parts of the Habsburg Monarchy), located in present-day Czechia, Poland and Ukraine and covering more than 80 000 km2. Our reconstruction was based on a homogeneous series of detailed Second Military Survey maps (1:28,800), which were the result of cadastral mapping (1:2,880) generalization. The dataset consists of two kinds of building structures based on the original map legend – residential and outbuildings (mainly farm-related buildings), and contains more than 1.3 million objects. The dataset’s accuracy was assessed quantitatively and qualitatively using independent data sources and may serve as an important input in studying long-term socio-economic processes and human-environmental interactions or as a valuable reference for continental settlement reconstructions. Additionally, a separate polygon layer of districts covering the entire study area, including a set of uncertainty-related attributes was added to the dataset. Acknowledgments This research was funded by the Ministry of Science and Higher Education, Republic of Poland under the frame of “National Programme for the Development of Humanities” 2015–2020, as a part of the GASID project (Galicia and Austrian Silesia Interactive Database 1857–1910, 1aH 15 0324 83).
DOI: 10.17632/2dyxncgw7j
title: Good and Bad classification of Citrus sinensis

description: Here's a data description within 3000 characters for your project titled "Good and Bad Classification of Oranges":-


Project Title: Good and Bad Classification of Oranges

Dataset Description:-

This dataset is designed for a binary classification task aimed at distinguishing between good and bad quality oranges based on visual or measurable characteristics. It contains a total of 2000 samples, split evenly into:

1000 good orange samples

1000 bad orange samples

Each sample represents an individual orange, captured or measured through consistent methods to ensure quality and comparability.

Class Definitions:-

Good Orange:- An orange that meets criteria such as ripeness, vibrant color, uniform shape, lack of surface damage or mold, proper size, and firmness. These are suitable for sale and consumption.

Bad Orange:- An orange exhibiting qualities such as over-ripeness, under-ripeness, discoloration, mold growth, deformation, bruising, or soft/rotten spots, making them unsuitable for consumer use.


Features (may include, depending on data type):-

Visual Features:- Color histograms, texture, shape parameters, presence of defects or spots.

Physical Features:- Weight, diameter, firmness level.

Image Data (if applicable):- High-resolution images under uniform lighting and background.

Label:-Binary label indicating class: 1 for good, 0 for bad.

Data Collection Method:- Samples were collected from a variety of sources including local markets, farms, and storage facilities to include a diverse representation of both good and bad oranges. If image-based, photos were taken using a consistent camera setup. If physical measurements are involved, instruments like calipers, scales, and firmness testers were used.

Purpose of the Dataset:- The dataset is intended for machine learning model development and evaluation in tasks such as:

Quality control automation

Agricultural product grading

Computer vision-based fruit sorting systems


Applications:-

Deployment in smart sorting machines in fruit processing units

Mobile or embedded quality inspection tools

Consumer applications for home use to detect fruit quality

Dataset Format:

If structured data:-CSV or Excel format with each row as a sample and columns as features plus label

If image data:- Folder structure with labeled directories (e.g., /good/ and /bad/) or metadata file containing image names and labels

Ethical Considerations:- The dataset only contains non-personal, agricultural data. Usage should be aligned with fair and transparent machine learning practices, especially in agricultural automation that may impact farmers' livelihood.

Let me know if you need this description tailored for a report, website, or presentation format.
DOI: 10.6084/m9.figshare.14744319.v2
title: Data for the study

description: The data of 311 surveys divided into distinct factors: GR, GC, WOM, BE, PI, BA, PR and BC. The data would be analyzed with the method of Partial Least Square structural equation model (PLS-SEM) using SmartPLS software version 3.2.8 to get the results in this study.
DOI: 10.6084/m9.figshare.12314777.v2
title: Bison conservation timeline

description: Stacked history timeline since 1800 CE of bison population, bison ownership, average carcass price, and bison system socio-ecological events. A) Log bison population (log10; gray bars (Hornaday 1889, Garretson 1918, 1926). B) Bison ownership shows the relative share of bison population by sectors of Tribal nations (white bars), US government (‘public’, black bars), Non-governmental organizations like zoos (‘NGO’, navy bars), and private entities (light blue bars). C) Average carcass price of bison (red line) with all prices corrected to 2018 equivalent dollars (U.S. Bureau of Labor Statistics 2020) since 1820 CE (Hornaday 1889, USDA 2020). D) Conservation events ranging across domains of natural (brown), social (yellow), economic (green), legislation about bison (authorization, blue), and recovery efforts (implementation, gray). All supporting data are availble here.
DOI: 10.6084/m9.figshare.8264084.v1
title: Microplastics ingestion and heterotrophy in thermally stressed corals. Ingestion rate data

description: Ingestion rates determined by dissection for number of microplastics and Artemia ingested per 200 polyps by Montipora capitata and Pocillopora damicornis. 4 separate files: micorplastics ingestion by M. capitata; microplastics ingestion by P. damicornis; Artemia ingestion by M. capitata; Artemia ingestion by P. damicornis.<br>
DOI: 10.17632/pbgscy3ptg
title: Machine Learning Interatomic Potentials Enable First-Principles Multiscale Modeling of Lattice Thermal Conductivity in Graphene/Borophene Heterostructures

description: Data for manuscript entitled: "Machine Learning Interatomic Potentials Enable First-Principles Multiscale Modeling of Lattice Thermal Conductivity in Graphene/Borophene Heterostructures". Please find the "Supporting information.pdf" for more details.
DOI: 10.17632/nmzz3w7pwd
title: Data Analytics

description: The structure and scale of the data align with published findings from regional studies to support the development and testing of predictive models.
DOI: 10.17632/vw8k79tmr6
title: DWR-drag: A new generation software for the double wall-ring interfacial shear rheometer's data analysis

description: The double wall-ring (DWR) rotational configuration is nowadays the instrument of choice regarding interfacial shear rheometers (ISR) in rotational configurations. Complex numerical schemes must be used in the analysis of the output data in order to appropriately deal with the coupling between interfacial and bulk fluid flows, and to separate viscous and elastic contribution or the interfacial response. We present a second generation code for analyzing the interfacial shear rheology experimental results of small amplitude oscillatory measurements made with a DWR rotational rheometer. The package presented here improves significantly the accuracy and applicability range of the previous available software packages by implementing: i) a physically motivated iterative scheme based on the probe's equation of motion, ii) an increased user selectable spatial resolution, and iii) a second order approximation for the velocity gradients at the ring surfaces. Moreover, the optimization of the computational effort allows, in many cases, for on-the-fly execution during data acquisition in real experiments.
DOI: 10.17632/9dbrmfzt97
title: The Economic Cost Of A Hurricane: A Case Study Of Puerto Rico and Hurricane Georges 1998 Using Synthetic Control Method

description: This data was used to conduct the research titled under the same name.
DOI: 10.17632/dskmk9cb8g
title: Ankle joints

description: Xray ankle joints
DOI: 10.17632/f7m6495v55
title: CNIR_DMD-optofMRI

description: Original codes and sample data from Kim et al. 2023, Neuron, "Whole-brain mapping of effective connectivity by fMRI with cortex-wide patterned optogenetics" (In press). The procedure described here is for generating subject-specific optogenetic stimulus pattern based on Allen mouse brain atlas  (https://atlas.brain-map.org/), by coregistration between the Atlas, brain structural MR image and optical fluorescence image from a mouse. The generated patterns are transferred to a digital micromirror device (DMD) and then projected onto a thinned-skull-prepared mouse brain.
DOI: 10.17632/f8d7x9zm2r
title: Dataset of factors affecting Teacher Performance

description: This dataset (survey instrument) factors affecting Teacher Performance in Public High Schools of Purwakarta Regency. The instrument is adapted, re-translated and validated. Data was obtained from 260 responses.
DOI: 10.17632/rf5jr78wy7
title: MATTER pressure regulator

description: MATTER pressure regulator source files
DOI: 10.17632/w8njshybth
title: ANACD-Arabic-News-Article-Classification-Dataset

description: The dataset is for NLP tasks and it has been described in our paper titled "Optimisation of Arabic Text Classification Using a Joint SVM and Word Embedding Models on a Novel Arabic Text Dataset"
DOI: 10.6084/m9.figshare.25722426.v1
title: Body temperature recordings

description: Raw peripheral body temperature recordings (1s resolution) recorded using thermal imaging cameras. File names correspond to the date the recording was saved and the camera number (1-4); each file contains the temperature data for two mice over 24 hours. Recordings run from 7am-7am.Files 230920_x contain temperature data during ad libitum feeding conditions which was used as a baseline for data analysis. The remaining files show temperature data over the course of food restriction.Files from 111020 are missing due to a techinical error with the cameras.