cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wchp3bryrm.2
title: Dataset of Citrus Canker Growth Rate

description: The hypothesis of the research was computer vision, image processing programs could be helpful in early detection and identification of citrus canker. For this purpose, initially the dataset was developed by inoculating healthy citrus leaves with disease causing organism (X. citri pv. citri) under natural field conditions. Inoculation was done on susceptible citrus cultivars, C. paradisi (Grapefruit). The leaves were inoculated by injecting the bacterial suspension into fully expanded, immature leaves with needleless syringes. The images were captured in Crop Diseases Research Institute (C.D.R.I.), National Agricultural Research Centre (NARC), Islamabad Pakistan regularly to measure the growth rate of citrus canker. The dataset is hosted by the Department of Computer Software Engineering, Military College of Signals-NUST Islamabad, Pakistan and acquired under the mutual cooperation of the NUST and C.D.R.I., NARC Pakistan. The inoculated leaves images were further categorized into different stages. It defines the temporal change in citrus canker growth rate. Canker symptoms developed were noted daily (from day 1 to day 21). From this dataset we can estimate and predict the disease prevalence and spread in citrus orchard over a specified time and can develop an alarming system for monitoring and control of the disease before it reaches its maximum loss. The dataset will be helpful for researchers for both plant pathologists and computer vision experts for classifying, detection and identification of citrus canker over specified time. The dataset was developed based on different growth stages thus it will be a novel way to monitor the disease spread and identify the threshold level of the disease and take precautionary measures before it completely damages the whole fruit plant. Additionally, the computer vision experts using implication of image processing, machine learning and deep learning techniques can design and build an early warning system by modeling the different disease stages and thus on site efficient robust online application can be generated which could be very useful both for farmers and agriculture department for warning and early detection system. The dataset has immense potential to be use in various field of application. Plant pathologist can use this data for measuring and identification of citrus canker and further explore the effect of other environmental variable on disease development.
DOI: 10.17632/jk47c38v72.1
title: Co-exposure to polyethylene microplastics and house dust mites aggravates airway epithelial barrier dysfunction and airway inflammation via IL-8 signaling pathway in a mouse model of asthma

description: Background: Environmental pollutants have been found to contribute to the development and acute exacerbation of asthma. Microplastics have received widespread attention as an emerging global pollutant. Airborne MPs can cause various adverse health effects.Due to their hydrophobicity, MPs can act as a carrier for other pollutants, pathogens, and allergens. This carrier effect of MPs may adsorb allergens and thus make the body exposed to MPs and a large number of allergens simultaneously. We hypothesized that co-exposure to inhaled MPs and aeroallergens may promote the development of airway inflammation of asthma by disrupting the airway epithelial barrier. 
Methods: The effects of co-exposure to Polyethylene microplastics (PE-MPs) and allergens on allergic airway inflammation and airway epithelial barrier were examined in a mouse model of asthma. The mice were divided into the following four groups: (i) Control group, treated only with PBS; (ii) MP group, exposed to PE-MPs and PBS; (iii) Asthma group, sensitized and challenged with HDM; (iv) Asthma+MP group, asthma group intranasally exposed to PE-MPs. Histology and ELISA assays were used to evaluate the severity of airway inflammation. FITC-dextran permeability assay, immunofluorescence assay, and RT-PCR were used to evaluate the airway epithelial barrier function and the expression of relevant molecules. Transcriptomics analysis with lung tissue sequencing was conducted to identify possible pathways responsible for the effects of PE-MPs. 
Results: Co-exposure of mice to PE-MPs and HDM induced more inflammatory cell, bronchial goblet cell hyperplasia, collagen deposition, allergen sensitization, and Th2 immune bias than HDM-sensitized mice without PE-MPs treatment. PE-MPs and HDM co-exposure aggravated oxidative stress injury in the lung. The production of airway-derived cytokine IL-33 was also increased in the BALF of mice co-exposed to PE-MPs and HDM. In addition, co-exposure to PE-MPs and HDM reduced the integrity and the expression of relevant molecules of the airway epithelial barrier. Lung tissue transcriptomics analysis revealed that PE-MPs exposure was associated with IL-8 signaling and neutrophil activation in asthmatic mice.
DOI: 10.17632/b6st2pjymv.1
title: Base Datos - ESG Scores and ROA

description: Base datos ESG scores and ROA
DOI: 10.17632/9424skmnrk.1
title: Sugarcane Leaf Disease Dataset

description: Manually collected image dataset of sugarcane leaf disease. It has mainly five categories in it. Healthy, Mosaic, Redrot, Rust and Yellow disease. The dataset has been captured with smart phones of various configuration to maintain the diversity. It contains total 2569 images including all categories. This database has been collected in Maharashtra, India. The database is balanced and contains good variety. The image sizes are not constant as it originates form various capturing devices. All images are in RGB format.
DOI: 10.17632/zz4zw9kyz7.1
title: Data for: Modeling blood flow in viscoelastic vessels: the 1D augmented fluid-structure interaction system

description: Model implementation in MATLAB language and scripts to reproduce test cases described in the paper MODELING BLOOD FLOW IN VISCOELASTIC VESSELS: THE 1D AUGMENTED FLUID-STRUCTURE INTERACTION SYSTEM.
DOI: 10.17632/wc8tmdmsxm.3
title: Spatial architecture of high-grade glioma reveals tumor heterogeneity within distinct domains

description: Background: High-grade gliomas (HGG) are aggressive primary brain cancers with poor response to standard regimens, driven by immense heterogeneity. In isocitrate dehydrogenase (IDH) wild-type high-grade glioma (glioblastoma, GBM), increased intra-tumoral heterogeneity is associated with more aggressive disease. 

Methods: Spatial technologies can dissect complex heterogeneity within the tumor ecosystem by preserving cellular organization in situ. We employed GeoMx® digital spatial profiling, CosMx® spatial molecular imaging, Xenium® in situ mapping and Visium® spatial gene expression in experimental and validation patient cohorts to interrogate the transcriptional landscape in HGG. 

Results: Here, we construct a high-resolution molecular map of heterogeneity in GBM and IDH-mutant patient samples to investigate the cellular communities that compose high-grade glioma. We uncovered striking diversity in the tumor landscape and degree of spatial heterogeneity within the cellular composition of the tumors. The immune distribution was diverse between samples, however consistently correlated spatially with distinct tumor cell phenotypes, validated across tumor cohorts. Reconstructing the tumor architecture revealed two distinct niches, one composed of tumor cells that most closely resemble normal glial cells, associated with microglia; and the other niche populated by monocytes and mesenchymal tumor cells. 

Conclusions: This primary study reveals high levels of intra-tumoral heterogeneity in high-grade gliomas, associated with a diverse immune landscape within spatially localized regions.
DOI: 10.17632/wc87kpk6ks.2
title: Bangladeshi Food Delivery App Restaurant Reviews

description: The dataset "Bangladeshi Restaurant Reviews" is a collection of customer reviews for restaurants in Bangladesh that are available on Foodpanda and Hungrynaki, two major food delivery apps in the country. The reviews were collected to provide insights into the satisfaction levels of customers with the food and service of these restaurants. The dataset includes information such as the reviewer name, review text, rating, and date of review.

The inspiration behind this dataset was to create a comprehensive resource for anyone interested in studying the restaurant industry in Bangladesh, specifically the food delivery sector. The dataset can be used for various purposes, such as sentiment analysis of customer reviews, identifying the most popular restaurants, and analyzing customer feedback to improve the service of restaurants.

The data was collected from the official websites of Foodpanda and Hungrynaki using web scraping techniques. The dataset contains over 15,000 reviews and were translated in English via Google Translator API.

We hope that this dataset will be valuable for researchers, students, and anyone interested in the restaurant industry in Bangladesh. We welcome any feedback or suggestions for improving the dataset in the future.
DOI: 10.17632/g4vgyn8n39.2
title: APK_AIM_Replication_File

description: This zip file contains the replication package for "Do Personal Taxes Affect Investment Decisions and Stock Returns? by Alexander P. Kontoghiorghes.
DOI: 10.17632/ys6d4cvhwz.1
title: A Fuzzy Inference-based Approach for Estimating Power Transformers Risk Index

description: Title: A comprehensive methodology for the optimization of condition-based maintenance in power transformer fleets
Version: 1.0
Date of Release: 14/03/2022
Identifier: 10.17632/ys6d4cvhwz.1

Associated publication: R.D. Medina, D.A. Zaldivar, A.A. Romero, J. Zuñiga, a and E.E. Mombello , "A Fuzzy Inference-based Approach for Estimating Power Transformers Risk Index" 

This directory contains the following datasets and supplementary materials:
Matlab Codes:
papermedina.m : Main code of the methodology
Matlab FIS Codes:
Indice_salud_69_230KV_DP.fis: Fuzzy inference system file containing the inference rules and membership functions for the determination of the health index for power transformers.
FACTOR_CONSECUENCIA_TESIS_v2.fis: Fuzzy inference system file containing the inference rules and membership functions for the determination of the factor of consequence for power transformers.
inidce_riesgo8.fis: Fuzzy inference system file containing the inference rules and membership functions for the determination of the risk index for power transformers.
TransformerData.xlsx: Excel file containing the information of the 15 power transformer units necessary for the calculation of the health index, factor of consequence and risk index.


This dataset includes the fuzzy inference rules created for two FIS that allow determining the consequence factor of the failure of power transformer and its risk index. These rules should be used as a reference of the article "A Fuzzy Inference-based Approach for Estimating Power Transformers Risk Index".
DOI: 10.17632/fj93rrfv2y.1
title: Medicinal Plant Identification Dataset

description: • In our surroundings, there are various types of plants. In our daily lives, we use products derived from these plants in many ways. We depend on a vast kingdom of plants to meet all the needs of life, including food, clothing, shelter, education, and healthcare. We have already gained a lot of knowledge about this relationship. We have seen or heard that when children have a cold or cough at home, they are given a mixture of tulsi (holy basil) leaves and a few drops of honey. As a result, their cold and cough subside, and they feel relieved. If someone suddenly gets a cut on any part of their body, washing the wound with the juice of the aloe vera leaf or applying a poultice of durba grass can be beneficial. This helps stop bleeding, and within two to three days, the wound dries up, and the person recovers. The plants in our environment that are used for the relief or cure of diseases are called medicinal plants. • At one time, Bangladesh was rich in medicinal plants. Fields, riverbanks, roadsides, and forests were abundant with numerous medicinal plants. Due to the increase in population, the diverse use of land has risen. Additionally, due to ignorance, negligence, and lack of attention, the primary habitat of these medicinal plants, natural forest land, has decreased. Consequently, valuable tree resources like these have been diminished. Many species have already become extinct. Despite this, our country still has a sufficient number of medicinal plants scattered across remote and less-explored areas. We are not familiar with all of them. It is crucial for us to be aware of these medicinal plants, recognize them, and understand their uses and properties. As a result, we can play a significant role in the holistic well-being of the general population in our country by contributing to the management and cure of various diseases. • This medicinal plant identification dataset would likely consist of a collection of images and associated metadata related to various medicinal plants. The dataset would serve as a resource for developing and training machine learning models for the automatic identification and classification of medicinal plants. • Six distinct kinds of medicinal plants are shown in this large dataset, which can be used to develop machine vision-based techniques: Arjun Leaf, Curry Leaf, Marsh Pennywort Leaf, Mint Leaf, Neem Leaf, and Rubble Leaf. • In reality, 1160 images of medicinal plants were initially collected from the field. Subsequently, to increase the quantity of data points, various image processing techniques were applied, such as shifting, flipping, zooming, shearing, brightness enhancement, and rotation, resulting in a total of 8120 augmented images derived from the original images.
DOI: 10.17632/68frhzp8kd.1
title: Data for: Efficacy and safety of Cinnamon in Type II Diabetes Mellitus and Pre-diabetes patients: A Meta-analysis and Meta-regression

description: This is Stata data set for the manuscript titled Efficacy and safety of Cinnamon in Type II Diabetes Mellitus and Pre-diabetes patients: A Meta-analysis and Meta-regression
DOI: 10.17632/4fw6v42k5g.1
title: SPIP: A computer program implementing the Interaction Picture method for simulation of light-wave propagation in optical fibre

description: Abstract The computer program spip is aimed at solving the Generalized Non-Linear Schrödinger equation (GNLSE), involved in optics e.g. in the modelling of light-wave propagation in an optical fibre, by the Interaction Picture method, a new efficient alternative method to the Symmetric Split-Step method. In the spip program a dedicated costless adaptive step-size control based on the use of a 4th order embedded Runge–Kutta method is implemented in order to speed up the resolution. Title of program: SPIP Catalogue Id: AEYQ_v1_0 Nature of problem The program solves the Generalized Non-Linear Schrödinger Equation (GNLSE) which occurs in the field of non-linear optics as a model of wave propagation in fibre optics. Versions of this program held in the CPC repository in Mendeley Data AEYQ_v1_0; SPIP; 10.1016/j.cpc.2015.10.012 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/n2zcmcypgb.2
title: uterine fibroid ultrasound images

description: Images used for detection, and their corresponding annotation files.
DOI: 10.17632/bfrkzf5k64.1
title: Worldwide Governance Indicators (WGI) 2012 - 2022

description: The data pertains to Balanced Panel data of Worldwide Governance Indicators (WGI) between 2012 and 2022. It comprises governance indicators such as voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption. The data encompasses 180 countries (1980 datasets) across various regions, including the Middle East and North Africa, South Asia, East Asia and Pacific, Sub-Saharan Africa, Europe and Central Asia, Western Europe, North America, Latin America, and the Caribbean.
DOI: 10.17632/zv66h54b8j.1
title: Dataset of images for model development using transfer-learning and texture features recognition of the conditions of construction materials with small datasets

description: This is the dataset of the images collected by the S.M.A.R.T Construction Research Group at NYUAD from a construction site on campus. The dataset contains the images used for the manuscript titled 'Transfer-learning and texture features for detailed recognition of the conditions of construction materials with small datasets' by Eyob Mengiste, Karunakar Reddy Mannem, Samuel A. Prieto and Borja García de Soto. For any inquiries, contact the corresponding author (eyob.mengiste@nyu.edu).

This database contains a total of 208 images for 7 construction material conditions broken down as follows: 
CMU wall - 24 images, 
Chiseled concrete - 49 images,
Concrete - 18 images, 
Gypsum - 26 images
Mesh - 25 images 
First coat plaster -  37 images
Second coat plaster - 29 images
DOI: 10.17632/2pkxckwgs3.1
title: Arabic Punctuation Dataset

description: This is a curated dataset, specifically designed to facilitate the study of punctuation. It has undergone rigorous manual annotation and verification on the basis of sentence structure, with sentence boundaries clearly marked. The dataset is in three folders:

1. The ABC component of the Arabic Punctuation Dataset: This folder features the manually annotated punctuation gold standard. It consists of one chapter extracted from each of 45 non-fiction books by 36 authors from 19 different fields of study. It contains 45 text files with a total of 149K tokens in 13K sentences. 

2. The CBT component: This folder has 1085 text files in 60 sub-folders, the full text of complete book translations that had been rendered from English into Arabic independently of this project. Their punctuation, we found out, mirrors the English source language texts; i.e., the sentence terminals in these Arabic texts follow the rules of English. In this folder are close to 3M words in more than 170K properly punctuated sentences.

3. The SSAC-UNPC component: This folder constitutes the third part of the Arabic Punctuation Dataset. It has close to 12M disconnected, disordered, complete sentences in 79 text files. These scrambled sentences were extracted from the predominantly legal Arabic subcorpus of the United Nations Parallel Corpus (UNPC). The punctuation here is authentic. It was done by the UN translators as part of their work. We consider this to be an excellent punctuation corpus because it mirrors the rule-governed punctuation of the English source documents, especially in relation to sentence terminals. These scrambled sentences total more than 309M words.
DOI: 10.17632/tpcznh9968.1
title: Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF MS

description: Mass spectra and susceptibility testing results for the article entitled "Predicting Pseudomonas aeruginosa drug resistance using artificial intelligence and clinical MALDI-TOF mass spectra".
DOI: 10.17632/frg22dnw7w.1
title: Excel sheet calculations for showing the effect of grain size distribution on thermal stability of nanocrystalline materials

description: Excel sheet calculations for showing the effect of grain size distribution on thermal stability of nanocrystalline materials
DOI: 10.17632/pntfv9nh4b.1
title: Datasets for shear coupling behavior in FCC Ni and BCC Fe grain boundaires

description: The following datasets are based on the output from the atomistic survey of the shear coupling behavior in 388 FCC Ni and 408 BCC Fe GBs. The GB structures are based on the Olmsted (Acta Materialia 57.13 (2009): 3694-3703; Acta materialia 57.13 (2009): 3704-3713. ) and Ratanaphan (Acta Materialia 88 (2015): 346-354.) dataset for Ni and Fe, respectively. The method used for the atomistic survey is the ramped synthetic driving force (RSDF) method based on molecular dynamics simulations. The surveyed temperature range is 100 - 1000 K for Ni and 100 - 1400 K for Fe. The specific datasets include: 1. List of GBs showing transition in shear coupling behavior. 2. List of GBs showing constant shear coupling factor. 3. List of GBs showing no shear coupling. 4. List of shear coupling factors in Ni GBs between 100-1000K. 5. List of shear coupling factors in Fe GBs between 100-1400K. 6. Total GB and shear displacement in Ni between 100 - 1000K. 7. Total GB and shear displacement in Fe between 100 - 1400K. 8. Fundamental zone plots of total shear in sigma3-11 GBs in Fe between 100 - 1400 K. 9. Fundamental zone plots of total shear in sigma3-13 GBs in Ni between 100 - 1000K. 10. Atomistic files of Ni GBs color-coded to show the shear coupling behavior at 100K. For best visualization, please open each cfg file by Ovitio and choose "color coding" by "type". 11. Atomistic files of Fe GBs color-coded to show the shear coupling behavior at 100K. For best visualization, please open each cfg file by Ovitio and choose "color coding" by "type".
DOI: 10.17632/7y943f6wf8.2
title: OnStove inputs and outputs

description: This repository contains data developed in relation to the first application of OnStove for all of sub-Saharan Africa.

The repository contains:

1.	Inputs – a folder containing all non-GIS inputs of the analysis (socio- and techno-economic specification files. These files are divided per scenario (private and social) and per country.

2.	GIS data – a folder containing all the processed GIS data from the analysis. The folder includes subfolders for all countries included in the analysis.

3.	A word document named “GIS data sources and descriptions of processing steps”. This document includes all the original sources of the GIS data shared on the repository as well as descriptions on how they have been altered from the original sources

4.	Outputs – a folder containing outputs for each country. The outputs are divided per scenario (private and social). Each output folder contains i) A main plot including a bar-plot  indicating  the  stove- split  in  the  scenario, a map of the spatial distribution of stoves with the highest net-benefit across SSA, a box-plot  indicating  the  net-benefit  resulting  from switching to each stove type and a plot showing the total costs and monetized benefits of each stove type, note that salvage costs are incorporated in the investment values (Investment costs = investment – salvage), ii) a .csv file with the summaries of the results and iii) a .pkl file with the full results of the analysis, which can be explored using the OnStove python package.

5.	Example case - Datasets needed in order to replicate the study for one country (Ghana) using the notebook found on the official OnStove repository (https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove/tree/main/example)

6.	Sensitivity files – files used in the sensitivity analysis conducted as part of the manuscript.
DOI: 10.17632/3hv26zgprn.1
title: Database for Cities & Income Inequality Paper

description: Database on Cities & Income Inequality
DOI: 10.17632/fdjnhpmdcm.1
title: Fitness costs in diamondback moth Plutella xylostella: Lufenuron

description: Raw data for Fitness costs in diamondback moth Plutella xylostella to lufenuron from parents and cross populations
DOI: 10.17632/y847gmjp8v.1
title: Data for: A game-theoretic model of reciprocity and trust that incorporates personality traits