cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/bkdkc4n835.1
title: Guava Fruit Disease Dataset

description: Guava (Psidium guajava) is a vital crop in Bangladesh and South Asia. It is rich in vitamin C, fiber, and other nutrients. However, guava production is declining due to disease. Early detection of infections is essential to protect the harvest. With the rise of expert systems, automatic disease detection can mitigate these losses. This dataset focuses on guava fruit, providing images categorized into three classes: Anthracnose, Fruit Flies, and Healthy fruits. The images, collected from orchards in Rajshahi and Pabna, Bangladesh, were captured in July when fruits were ripening and were most prone to disease. The images were then verified by a plant pathologist. The dataset is intended to support research in image processing and machine learning, aiming to develop systems for early disease detection. Such systems can significantly reduce economic losses and improve guava yields.

The dataset includes 473 images of guava fruits. The original photos vary in size and format. Each was preprocessed to 512 x 512 pixels for consistency. 

Image Information:
- Dimensions: 512 x 512 pixels
- Color Mode: RGB
- Format: PNG
- File Size: 300 - 500 KB

The dataset covers three main classes: Anthracnose, Fruit Flies, and Healthy fruits. These are common conditions in guava farming. Images underwent preprocessing steps such as unsharp masking and CLAHE. The preprocessed images are augmented to increase in number to 3,784 image data. The following tree shows the distribution of images across three subsets:

Dataset
│
├── train (2,647 images)
│ ├── Anthracnose
│ ├── Fruit Flies
│ └── Healthy fruits
│
├── test (382 images)
│ ├── Anthracnose
│ ├── Fruit Flies
│ └── Healthy fruits
│
└── val (775 images)
 ├── Anthracnose
 ├── Fruit Flies
 └── Healthy fruits
DOI: 10.15468/dl.z4uze9
title: Occurrence Download

description: A dataset containing 616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Podocarpus latifolius (Thunb.) R.Br. ex Mirb.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 616 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009280-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zm33cdndxs.2
title: Elsevier OA CC-BY Corpus

description: This is a corpus of 40k (40,001) open access (OA) CC-BY articles from across Elsevier’s journals represent the first cross-discipline research of data at this scale to support NLP and ML research. This dataset was released to support the development of ML and NLP models targeting science articles from across all research domains. While the release builds on other datasets designed for specific domains and tasks, it will allow for similar datasets to be derived or for the development of models which can be applied and tested across domains.
DOI: 10.17632/nz96v5spbf.2
title: Data for: Dataset of white spot disease affected shrimp farmers disaggregated by the variables of farm site, environment, disease history, operational practices, and saline zones

description: Contrivance of data-set Among the aquaculture species in Bangladesh, shrimp is the most vulnerable to disease, specifically to White Spot Disease (WSD) that causes complete loss of entire farm production. Al almost every year. Due to the outbreak of WSD caused by White Spot Syndrome Virus (WSSV), the Asian shrimp farming sector lost USD 20 billion in 2018, of which a lion share was from Bangladesh (Davies, 2019). In the condition of both vertical and horizontal transmission of WSSV, there is no effective treatment for vertical transmission whereas horizontal transmission can be mitigated by taking some management measures within the farming practices. An extensive review of literature, and field studies and observations were conducted to identify the variables linked to the risk factors of WSD, and accordingly, the google featured questionnaire was developed for the survey. The survey was conducted using android mobile phone with 233 shrimp farmers in Khulna, Bagerhat and Satkhira districts of Bangladesh. This dataset has been analyzed through multivariate statistical analysis to identify the risk factors of WSD and the results were published in a journal article. The results are likely to be useful for policymakers and development organizations to reduce the impacts of WSD on shrimp farming in Bangladesh. Potentials of the data-set This dataset has a large number of variables, some of which can be reclassified to develop nominal/categorical/dependent variables, and can be used for further statistical analysis. The dataset has also the GPS coordinates of all the 233 farms individually which can be used for spatial and longitudinal analysis in the future. The dataset reposited here in the Mendeley will be useful as the baseline data for analyzing the changes of shrimp farming in the coming years in Bangladesh.
DOI: 10.17632/vbkscdgdbd.1
title: Data and code for study "Effect of changes in population density and crop productivity on farm households in Malawi"

description: Author to who correspondence may be addressed: Adam Komarek (https://orcid.org/0000-0001-5676-3005) Most recent edit: April 1st, 2019 Details: the zip file 'analysis.zip' has two main folders for the code and data required to replicate the results in the study "Effect of changes in population density and crop productivity on farm households in Malawi". The study DOI is https://doi.org/10.1111/agec.12513. Study authors are Adam M. Komarek and Siwa Msangi 1) a folder 'gams' that requires six steps to run the GAMS model. The GAMS model was run on GAMS version 24.8.5 The GAMS model is the DAHBSIM (Dynamic Agricultural Household Bio-Economic Simulation Model) Six steps: I. ensure all files and folders inside the folder 'gams' are inside the same one folder II. open project file 'model.gpr' inside 'gams' folder III. open settings.gms. The directory settings are on lines 17 to 21, no need to write out the file paths as '$setglobal filelocation' sets the file path to wherever model.gpr is located IV. open and run 'set_database.gms' in gams\model, to ensure the database is there V. open and run 'gen_baseline.gms' in gams\model, this runs the baseline model and the scenarios using the toggle on L199, if needed include 's=dahbsim rf=dahbsim' in the command line without the single quotation marks VI. scenario data in \gams\data_raw\cropcoef_raw.xlsx and scenario code in gams\model\scenario_model.gms 2) a folder 'r' with five main items that include the R project and four main folders: I. 'cropProdMWI.Rproj' is the R project. It must be opened to set the project directory, which is needed to read in the data II. the R scripts are in the folder 'scripts'. There are 7 scripts, which are ordered sequentially III. the folder 'data' contains the data used in the scripts IV. output from the scripts are in the folder 'output' V. livestock data, relevant for manure application, are in the folder 'livestock'
DOI: 10.17632/b6kvr4bzxp.1
title: Overexpression of AMP-activated kinase sensitizes Sorafenib-resistant Hepatocellular cancer cells and decreases stem cell markers

description: Data used to generate figures of the paper by Bort A, Sánchez BG, Mateos-Gómez PA, Vara-Ciruelos D, Rodríguez-Henche N, Díaz-Laviada I. “Targeting AMP-activated kinase impacts hepatocellular cancer stem cells induced by long-term treatment with sorafenib” Mol Oncol. 2019 May;13(5):1311-1331. doi: 10.1002/1878-0261.12488. In this study we demonstrate that the AMP-activated kinase AMPK reverse the Cancer Stem cell features of Hepatocellular CSC.
DOI: 10.17632/bmv9kxkzg3.1
title: FaVAD: A software workflow for characterization and visualizing of defects in crystalline structures

description: The analysis of defects and defect dynamics in crystalline materials is important for fundamental science and for a wide range of applied engineering. With increasing system size the analysis of molecular-dynamics simulation data becomes non-trivial. Here, we present a workflow for semi-automatic identification and classification of defects in crystalline structures, combining a new approach for defect description with several already existing open-source software packages. Our approach addresses the key challenges posed by the often relatively tiny volume fraction of the modified parts of the sample, thermal motion and the presence of potentially unforeseen atomic configurations (defect types) after irradiation. The local environment of any atom is converted into a rotation-invariant descriptive vector (‘fingerprint’), which can be compared to known defect types and also yields a distance metric suited for classification. Vectors which cannot be associated to known structures indicate new types of defects. As proof-of-concept we apply our method on an iron sample to analyze the defects caused by a collision cascade induced by a 10 keV primary-knock-on-atom. The obtained results are in good agreement with reported literature values.
DOI: 10.17632/pdtyb7df6z.1
title: Bengali Social Media Depressive Dataset (BSMDD)

description: Our dataset, BSMDD, was collected from various open social media platforms and translated and annotated by native Bengali speakers with expertise in both language and mental health. It contains 21,910 cleaned samples, including 10,961 labeled as Depressed and 10,949 as Non-Depressed. The dataset is publicly accessible, providing a valuable resource for further research in depression detection in Bengali social media content. The expert annotation process, conducted by professionals, ensures high validity, making BSMDD particularly important for advancing mental health research through social media analysis.
DOI: 10.17632/ww6b5n327m.1
title: Mendeley supplemental table I. ICD-10 diagnosis codes for defining baseline comorbidities

description: Mendeley supplemental table I. for "The risk of COVID-19 infection in patients with atopic dermatitis - a retrospective cohort study"
DOI: 10.17632/3426b5mt3t.1
title: Public Perceptions on COVID-19: The Spiral of Silence Logic among Facebook Users in Armenia

description: The data was collected in frames of an online survey conducted on the Facebook platform, using Google forms, in the period of June 1 - June 20, 2020. The data confirms three elements of the SoS as applied to the communicative behavior of Facebook users in Armenia. First, we identified a gap between the majority’s opinion about state policies and requirements to public conduct in the pandemic and their actual mass behavior. The majority prefers not to contradict the state policies and requirements in public discussions (on Facebook), as well as report their loyalty to the officially stated rules as well as appropriate behavior while being surveyed. On the other hand, the inappropriate public behavior and massive violations of the lockdown rules are considered to be the main cause of the spread of the virus in Armenia according to the state bodies responsible for tackling the pandemic. According to the SoS logic, people in their majority are well informed about requirements to public conduct in the pandemic but don’t follow the rules, and being aware of sanctions, they hide their real opinion and either prefer to openly agree with the official position, or break the rules silently (keep silence). Second, there is a strong correlation between perceptions of the users regarding the opinion environment among their Facebook ‘friends’, and their preference for posting on their opinion, as well as commenting on others’ posts. If the communicative environment is perceived as rather contradictory to the user’s opinion and in a lesser sense as diverse, the essential part of the users surveyed prefer not to post and not to comment on others’ opinion. Female users of Facebook in Armenia are more active commenters than men, but their activity is mostly limited by the circle of familiar people whose opinion is more predictable in advance, and not threatening to their personal reputation, compared to that of the strangers.
DOI: 10.17632/rxbh297tph.3
title: Numerical Investigation on Deteriorated Heat Transfer of Supercritical Water Flowing Upward in Tubes with Variable Cross-sectional Geometries

description: To mitigate Deteriorated Heat Transfer (DHT) of Supercritical Water (SCW) upward flow, tubes with variable cross-sectional geometries are numerically investigated. Three types of variable cross-sectional geometries: converging channel, diverging channel, and periodic geometries, are modelled. Results of wall temperature in the smooth channel are compared with experimental data, and good agreements are obtained. The wall temperature effects of convergent and divergent channels of various proportions and periodic geometries of various amplitudes are investigated. Thermo-Hydraulic Performance Evaluation Criterion (PEC) is proposed to evaluate the performance of the studied geometries using dimensionless parameters Nu/Nu0, f/f0, and PEC = (Nu/Nu0)/(f/f0)1/3. The results indicated that the convergent channels suppress and delay DHT downstream, while opposite effects are observed for divergent channels. Periodic geometries, which have alternating convergent and divergent sections, suppress DHT with minimal pressure drop. 1st temperature peak is reduced by 200 K with 1 mm of outlet radius reduction for the convergent channel. Average PEC is enhanced by 60% with 0.5 mm A of periodic geometry. It is discovered that the convergent section can suppress DHT, and the mitigation effect is proportional to the size of convergence. It is concluded that, since the DHT caused by buoyancy-induced flow laminarization has flattened the cross-sectional velocity profile, the convergent section reverts the laminarization to the normal velocity profile by the nozzle acceleration effect. Nozzle acceleration also increases Turbulent Kinetic Energy (TKE) in the boundary layer which further enhances turbulent heat transfer.
DOI: 10.17632/jzdj6h7gms.2
title: Creating a white blood cell dataset for segmentation

description: The KRD-WBC dataset consists of 600 images, each sized at 512x512 pixels, accompanied by corresponding ground truth images of the same dimensions. The dataset was gathered from Nanakali and Bio lab in Erbil city, located in the Kurdistan region of Iraq. It includes images of White Blood Cells (WBCs) categorized into five distinct subtypes: Neutrophils, Lymphocytes, Monocytes, Eosinophils, and Basophils. This dataset is valuable for medical and biological research, enabling the study and analysis of different WBC subtypes.
DOI: 10.17632/mhkwz9jfzs.1
title: Data for: Comparative Study of Roundness Evaluation Algorithms for Coordinate Measurement and Form Data

description: The data contain 10 data set representing CMM and 10 dataset representing form data
DOI: 10.17632/wctk2nth2g.1
title: Decoding the Impacts of Space and Time on Honey Bees: GIS Based Fuzzy AHP and Fuzzy Overlay to Assess Land Suitability for Apiary Sites in Queensland, Australia 

description: The aim of this study was to map and assess the suitability of an area for beekeeping with respect to spatial and temporal variations in melliferous floral resources and other biophysical factors using GIS based fuzzy AHP and fuzzy overlay. Eleven criteria including regional ecosystems, land cover, land use, slope, aspect, elevation, distance to water, distance to roads, rainfall, temperature, and solar radiation were used. Regional ecosystem, land use and distance to roads maps were downloaded from Queensland Spatial Catalogue: Queensland Government (https://qldspatial.information.qld.gov.au) while land cover map was obtained from Esri Land Cover – ArcGIS Living Atlas of the World (https://livingatlas.arcgis.com/landcover/). GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3, Geoscience Australia (https://ecat.ga.gov.au) was the source of DEM data whereas slope and aspect were derived from the DEM layer. Distance to water map was created using Drainage, GEODATA TOPO2.5M from the Geoscience Australia (https://ecat.ga.gov.au) and the climate data (temperature, solar radiation and rainfall) were downloaded from New South Wales (NSW) and Australian Capital Territory (ACT) Regional Climate Modelling (NARCliM) (Hutchinson & Xu, 2015). All the maps were resampled to 25x25 and projected to GDA2020 MGA Zone 56. 
Fuzzy AHP calculations are provided in excel sheets. 
Final maps were generated using fuzzy overlay and fuzzy AHP seperately.
DOI: 10.17632/x4hd28jh6c.1
title: Human rights' raw data and fuzzy set matrix of European and African countries

description: This is the data of the performance of each of the countries examined in the study and the result of the processed data by creating a matrix for each group of countries using fuzzy set software (fsQCA).
DOI: 10.17632/tf9dtfz9m6.2
title: chilli dataset

description: Chilli dataset for detection and classification
DOI: 10.17632/cr6jp278vc.1
title: Financial dataset of Indonesia Manufacturing Industry

description: The dataset spans a period of nine years, from 2013 to 2021, and encompasses financial information from firms listed on the Indonesia Capital Market. A total of 128 manufacturing firms are represented in this dataset, culminating in a dataset size of 1024 data points
DOI: 10.17632/v9892ppf46.1
title: Smuggling of Pesticides in Brazil (2008-2018)

description: This dataset has information extracted from forensic reports of confiscated pesticides. These reports were prepared by Brazil's Federal Police between 2008 and 2018. The dataset has information about dates, places and volumes of confiscation, as well as characteristics of confiscated products. It demonstrates that the market of smuggled pesticides is probably small, there is no evidence that smuggled pesticides are substantially more toxic than legally-traded ones (although they may be of greater environmental risk), smuggled pesticides are rarely counterfeit, and organized groups may be involved with this crime, but petty smugglers prevail.
DOI: 10.17632/n92vwbg8zt.1
title: vbICA code

description: The independent component analysis (ICA) is a popular technique adopted to approach the so-called blind source separation (BSS) problem, i.e., the problem of recovering and separating the original sources that generate the observed data. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. Here we provide a MATLAB code which implement a modified variational Bayesian ICA (vbICA) method for the analysis GNSS time series. The vbICA method models the probability density function (pdf) of each source signal using a mix of Gaussian distributions, allowing for more flexibility in the description of the pdf of the sources with respect to standard ICA, and giving a more reliable estimate of them. In particular, this method allows to recover the multiple sources of ground deformation even in the presence of missing data. This material is based on the original work of Choudrey (2002) and Choudrey and Roberts (2003), subsequently adapted by Gualandi et al. (2016) and Serpelloni et al. (2018) for the study of GNSS position time series.
DOI: 10.17632/kdvrdjvz7d.1
title: Structural mechanism of endonucleolytic processing of blocked DNA ends and hairpins by Mre11-Rad50. Gut et al.

description: Deposition of unprocessed, raw gel images.
DOI: 10.17632/dfh8s3m8yk.1
title: When The Markets get CO.V.I.D.

description: All codes and (simulated) data required to replicate this manuscript. Our abstract follows:

We quantify the exposure of major financial markets to news shocks about global contagion risk while accounting for local epidemic conditions. For a wide cross section of countries, we construct a novel dataset comprising (i) announcements related to COVID19 and (ii) high-frequency data on epidemic news diffused through Twitter (Hassan et al. 2019's methodology). We provide novel empirical evidence about financial dynamics both around epidemic announcements and at daily/intra-daily frequencies. Analysis of contagion data and social media activity about COVID19 suggest that the market price of contagion risk is significant.
DOI: 10.17632/yh42r43cpy.1
title: PETOOL: MATLAB-based one-way and two-way split-step parabolic equation tool for radiowave propagation over variable terrain

description: Abstract A MATLAB-based one-way and two-way split-step parabolic equation software tool (PETOOL) has been developed with a user-friendly graphical user interface (GUI) for the analysis and visualization of radio-wave propagation over variable terrain and through homogeneous and inhomogeneous atmosphere. The tool has a unique feature over existing one-way parabolic equation (PE)-based codes, because it utilizes the two-way split-step parabolic equation (SSPE) approach with wide-angle propagator, which ... Title of program: PETOOL (Parabolic Equation Toolbox) Catalogue Id: AEJS_v1_0 Nature of problem Simulation of radio-wave propagation over variable terrain on the Earth's surface, and through homogeneous and inhomogeneous atmosphere. Versions of this program held in the CPC repository in Mendeley Data AEJS_v1_0; PETOOL (Parabolic Equation Toolbox); 10.1016/j.cpc.2011.07.017 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/5p453xysrh.1
title: Data for: Estimating Retail Gasoline Price Dynamics: The Effects of Sample Characteristics and Research Design

description: This data provides STATA data files, STATA do files, and STATA log files that reproduce the results in the submitted paper. A read_me file in the zipped folder provides additional information.
DOI: 10.17632/4pw8vfsnpx.2
title: Clouds-1000

description: Clouds-1000 is a dataset of 1000 sky images captured with cameras directed towards the horizon in the north and south directions in an area with a good view of the sky in the UFSC Photovoltaic Laboratory at the Federal University of Santa Catarina, in the city of Florianópolis/SC-Brazil. The images were collected every minute over the period of March–October of 2021. Each image was annotated with a polygon tool and classified using 4 cloud types: Cirriform, Cumuliform, Stratiform, and Stratocumuliform, and 1 class representing trees and buildings. This classification is based on the solar radiation absorption characteristics of clouds. 

For the task of image annotation, our research team was divided into 3 Data Analysts responsible for analyzing and labeling the images, and 2 meteorologists responsible for supervision and validation. Sylvio Mantelli is a PhD from INPE, working on our research team and helped with data labeling mentoring and several analysis throughout development of the dataset. Maurici Amantino Monteiro, professor and currently climatologist at Aqueris Engenharia e Soluções Ambientais. With several years of experience in synoptic observation, he helped us to understand the nature of clouds and associate them with their corresponding classes.

The annotations were handmade using the Supervisely tool. The tool was created for image annotation and data management in which it's possible to create the annotations via interface available, similar to other image editors. Each image was annotated with the polygon tool and classified using 4 cloud types: Cirriform, Cumuliform, Stratiform, Stratocumuliform and 1 class representing trees and buildings. This classification is based on solar radiation absorption characteristics. Due to the humid climate of the region, the Cumulonimbus (Cb) cloud seldom forms. This type of cloud usually form in dryer regions, thus we won't find any occurrence of this cloud in the dataset.

The dataset faced several validations and during an inspection we found 4 images that were either partially annotated or missing annotation entirely. Therefore, the latest and current version of the Clouds-1000 dataset is composed of 996 fully hand-annotated images.

For more information see the github repository.