cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rgfhzd5mzw.1
title: Potato Viral Disease Dataset on both Foliar and Tuber

description: Potato (Solanum tuberosum) is the main crop that is vegetatively propagated(cloning). It is the third most important food crop after wheat and rice in terms of human consumption. This crop is affected by various types of diseases like bacterial, fungal, and viral diseases. As, a traditional practice some viral disease are identified by visual symptoms and some by laboratory methods like Enzyme-linked immunosorbent assay (ELISA), real time reverse-transcription- polymerase chain reaction (RT-PCR) etc., the above methods are tedious, computational costs along with time will be high and it is requiring a more labor-intensive and controlled lab structure to carry out the experiment. So, there is an urgent need for developing an automated model which employs machine learning, deep learning methodology which are subset of Artificial Intelligence. This model helps agriculturist/ farmers for early detection of viral disease. and take effective measures for huge yield loss. The dataset shows different types of viral diseases that the potato crop foliar and tubers get effected with namley Mosaic Virus, Potato Leaf Roll Virus(PLRV), on foliar, and on tuber Potato Spindle Tuber Viriod (PSTVD), Potato Virus Y(PVY)-tuber cracking. The dataset of foliar and tuber comprises of Nineteen hundred and seventy two images Mosaic(666), PLRV(527), Healthy leaf(135), PSTVD(85), PVY cracking (559). Each image of size in pixels is 4288*2848 and camera employed is Nikon D90,its configuration details include f-stop-f/5.3, ISO speed -ISO-250, focal length-80mm, contrast -medium, No flash. The dataset is collected from potato fields of University of Agricultural Sciences, Dharwad where 3 acres of land is cultivated with certified seeds from modipuram regional Centre and 1 acre is cultivated with uncertified seeds. The scientist from the research institute shared the image data from Indian Council of Agricultural Research- Central Potato Research Institute (ICAR- CPRI) shimla. The data set is captured in the day light by placing the leaf or tuber on black background. The image data collected has different symptoms like plant affected with mosaic virus has yellow color spread throughout the leaf the leaf can be classified as mild, medium and severe mosaic. The color feature plays a major role in classifying the mosaic viral disease the symptoms include yellow color propagated throughout the leaf. The PLRV symptoms are rolling of leaf towards upward direction the texture of the leaf is little crunchy in nature. The main features here are shape and texture for accurately classifying the disease. In tuber PSTVD where the tubers are elongated that is based on shape features the classifier gives the accurate results. PVY cracking it is one of the strains of potato virus Y where the tubers have cracks on external part which is noninfectious. The cracks generally start at bud and extend lengthwise.
DOI: 10.17632/6dcvvvvdrr.1
title: Assessing the impact of bilateral trade policy measures on bilateral FDI using the structural gravity modelling

description: Since the bilateral impact of trade policy variables on bilateral FDI stocks is the main interest here, this article follows the strand of the literature on gravity modelling controlling for multilateral resistances (Anderson and van Wincoop, 2003). Therefore, in order to control for country-level time-variant variables like GDP, country-time fixed effects are used. Therefore, host-time, and home-time fixed effects are used in addition to country-pair fixed effects controlling for any time-invariant relationship between the two countries such as distance, colonial relationship, language and sharing borders. In this FDI model, with these fixed effects, the only correlating variation between the FDI stocks and trade policy measures would be what is left between i and j that changes over time. Bilateral FDI stocks cover many zero values. In fact, 27% of the sample of estimations includes zero FDI stocks. Changing the FDI stocks to logarithms will eliminate 27% of the sample causing biased estimations. In order to have unbiased estimation results, the PPML estimator is used following Silva and Tenreyro. The PPML estimation procedure including multidimensional fixed effects is run using the Stata package implemented by Correia et al., (2019). Robust standard errors are calculated to control for the heteroscedasticity in the error term. Stata codes ran for the estimation results of the manuscript are written in the Stata do.do file for the data_estimation.dta data file. These files are compressed in the following shared .rar file. References: • Anderson, J. E., & van Wincoop, E. (2003). Gravity with Gravitas: A Solution to the Border Puzzle. American Economic Review, 93(1), 170-192. • Silva, J. S., & Tenreyro, S. (2006). The log of gravity. The Review of Economics and statistics, 88(4), 641-658. • Correia, S., Guimarães, P., & Zylkin, T. (2019). PPMLHDFE: Fast poisson estimation with high-dimensional fixed effects. arXiv preprint arXiv:1903.01690.
DOI: 10.17632/6x9srbfp6w.2
title: Gender Classification Using Twitter Data

description: This dataset is an expansion of the Twitter User Gender Classification dataset, which is freely available on Kaggle. The aim of this data for research is to predict user gender based on textual data available on Twitter. 

The original dataset contained 12,894 distinct male and female twitter users with one tweet each. This was significantly expanded to 269,108 tweets by the same 12,894 users where each user had multiple tweets. Expansion method was using Tweepy to access the Twitter API.

The uploaded files contains the Train and Test split used for the experiment. It contains the following:

user_id - a unique id for each user 
gender - male or female
gender:confidence -  a float representing confidence in the provided gender (1 for 100%)
created_at - date and time when the tweet was created
tweet_id - the unique id of the text of a random tweet by the users

Attached also is a simple script on Jupyter Notebook using Tweepy. This is built to retrieve a tweet’s complete information using its ID which is known as the hydration of a tweet ID. Some sample tweet id's are already in the script for testing purposes.
DOI: 10.17632/y49xnnnftc.1
title: Dynamic Palmitoylation of STX11 Facilitates Injury-induced Fatty Acid Uptake to Promote Muscle Regeneration Wang et al

description: Different types of cells uptake fatty acids in response to different stimuli or physiological conditions; however, little is known about context-specific regulation of fatty acid uptake. Here, we show that muscle injury induces fatty acid uptake in muscle stem cells (MuSCs) to promote their proliferation and muscle regeneration. In human and mice, fatty acids are mobilized after muscle injury. Through CD36, fatty acids function as both fuels and growth signals to promote MuSC proliferation. Mechanistically, injury triggers the translocation of CD36 in MuSCs, which relies on dynamic palmitoylation of STX11. Palmitoylation facilitates the formation of STX11/SNAP23/VAMP4 SANRE complex, which stimulates the fusion of CD36- and STX11-containing vesicles. Restricting fatty acids supply, blocking fatty acid uptake, or inhibiting STX11 palmitoylation attenuates muscle regeneration. Our studies have identified a critical role of fatty acids in muscle regeneration and shed light on context-specific regulation of fatty acid sensing and uptake. The uploaded data include the uncropped images of the western blots.
DOI: 10.17632/vytzhmm254.1
title: Ocean acidification metrics (pH and aragonite saturation state) in the Arctic Chukchi Sea from 2002 to 2019

description: This accession includes parameters of ocean acidification metrics (pH and aragonite saturation state) in the water column collected by international cruises as well as CHINARE cruises during 2002 to 2019. These data include measurements/calculations of temperature, salinity, depth, pH, and aragonite saturation state. The interpretation of these data is given in a recently accepted manuscript to Geophysical Research Letters.
DOI: 10.17632/6ym33ymw92.1
title: Data Set Of Mathematical Critical Creative Thinking, And Problem Solving For Elementary School Students

description: Critical and creative thinking is very important to build students' cognitive processes in solving mathematical learning problems that are done logically and can be measured, in this case problem solving becomes very important in helping students think critically because it helps students think at a high level to find solutions in the form the answer to the problem mathematically. Therefore this article explains about critical thinking data, creative personal, with the ability to solve elementary school students' math problem. This research uses a survey method with statistical regression and correlation approaches. an example in this data is 30 students in elementary schools in the city of Yogyakarta. Data collection method is using a validated questionnaire. In this data collection we present several variable / item questions that are included in the data set. In general, the data findings indicate that there is a relationship of critical thinking, creative personality with significant mathematical problem solving abilities. so this data has particular implications for teachers to create examples of problems that build students' critical, creative thinking levels.
DOI: 10.17632/wsgpzfcx3v.1
title: Data for: Ideal Comparisons: Body Ideals Harm Women's Body Image through Social Comparison

description: Experimental data from 200 adult women, majority White, recruited from Prolific Academic. Participants exposed to one of four body messages (curvy ideal, athletic ideal, thin ideal, non-prescriptive body acceptance), then reported state social comparison, four body image outcomes (body surveillance, body appreciation, esteem for body looks, esteem for body function), and trait social comparison.
DOI: 10.17632/zc2scv8sxy.2
title: The impact of delay in time to surgical treatment of Merkel cell carcinoma on overall survival and disease specific survival: a population-based analysis

description: The aim of our study is to determine whether delays between diagnosis and surgical treatment of Merkel Cell Carcinoma (MCC) are associated with changes in overall survival (OS) and disease-specific survival (DSS). Using the Surveillance, Epidemiology, and End Results Program (SEER) database, our data does not show that delays are associated with worse OS or DSS.
DOI: 10.17632/hw4w3n86bt.1
title: Supplementary data of Maternal and infant mortality among the localities of Bogotá D.C. according to poverty tertiles, 2011-2021

description: In this data set, you can access the data from Localities of Bogotá, D.C., related to perinatal mortality, infant mortality, under-5 mortality, and maternal mortality. Also, you can access the calculations of the relative index of inequality by quintiles, quartiles, and tertiles of poverty between localities of Bogotá D.C.
DOI: 10.17632/wy6kyb7dp9.1
title: Data for: Statistical analysis of the dust storms in the United Arab Emirates

description: Dust storm events in the United Arab Emirates during the period 1st of January 2010 -31st of December 2017 and the pivot table for retrieving the data.
DOI: 10.17632/j83f5fsh6c.1
title: Lisbon, Portugal, hotel’s customer dataset with three years of personal, behavioral, demographic, and geographic information

description: Hotel customer dataset with 31 variables describing a total of 83,590 instances (customers). It comprehends three full years of customer behavioral data. In addition to personal and behavioral information, the dataset also contains demographic and geographical information. This dataset contributes to reducing the lack of real-world business data that can be used for educational and research purposes. The dataset can be used in data mining, machine learning, and other analytical field problems in the scope of data science. Due to its unit of analysis, it is a dataset especially suitable for building customer segmentation models, including clustering and RFM (Recency, Frequency, and Monetary value) models, but also be used in classification and regression problems.
DOI: 10.17632/43v3vvkwwf.1
title: FFT-split-operator code for solving the Dirac equation in 2+1 dimensions

description: Abstract The main part of the code presented in this work represents an implementation of the split-operator method [J.A. Fleck, J.R. Morris, M.D. Feit, Appl. Phys. 10 (1976) 129-160; R. Heather, Comput. Phys. Comm. 63 (1991) 446] for calculating the time-evolution of Dirac wave functions. It allows to study the dynamics of electronic Dirac wave packets under the influence of any number of laser pulses and its interaction with any number of charged ion potentials. The initial wave function can be eith... Title of program: Dirac++ or (abbreviated) d++ Catalogue Id: AEAS_v1_0 Nature of problem The relativistic time evolution of wave functions according to the Dirac equation is a challenging numerical task. Especially for an electron in the presence of high intensity laser beams and/or highly charged ions, this type of problem is of considerable interest to atomic physicists. Versions of this program held in the CPC repository in Mendeley Data AEAS_v1_0; Dirac++ or (abbreviated) d++; 10.1016/j.cpc.2008.01.042 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/k5pngh54ry.1
title: Data for: Modeling the impact of spray drying conditions on some Maillard reaction indicators in nano filtered whey

description: This dataset has the raw data, codes and supplemntary material required to completely reproduce the results published in the article "Modeling the impact of spray drying conditions on some Maillard reaction indicators in nano filtered whey".
DOI: 10.17632/54pv8f6ynr.3
title: Participatory Framework for Urban Pluvial Flood Modeling in the Digital Twin Era

description: The recent surge in digital twin technology, which creates virtual replicas of real-world processes, offers an interactive testbed for understanding and predicting environmental changes. Globally, as urban areas face increasing extreme heavy rainfalls and the resulting pluvial floods caused by inadequate drainage systems, collaboration between governments and local residents becomes crucial in managing flood risks. This paper develops a participatory framework for urban pluvial flood modeling, incorporating open source software, virtual reality, minimum viable product, and gamification aspects. This framework engages citizens in every phase of the process, from input data preparation and hydrological model construction to model verification and experiments, leveraging local knowledge and collective action. This paper presents a case study on the recurring pluvial flood damages in South Korea's Gangnam region, demonstrating the practical implications of an interactive, web-based crowdsourcing platform to facilitate citizen participation. The results underscore the evidence of a proactive role for citizens, not merely as recipients of disaster information but as key contributors collaborating with a range of stakeholders in flood modeling and stormwater management. By integrating digital twin technology with community engagement, we can foster informed decision-making and spontaneous participation in the evolving digital era, leading to a disaster-resilient community.
DOI: 10.17632/b33r2dzng8.1
title: Spectral dataset of grapevine diseases

description: Spectral dataset of grapevine diseases for the project VINIoT. This dataset contains spectra from hyperspectral images of grapevine leaves. 
This dataset contains spectra of healthy leaves and leaves showing a set of symptoms (diseases, dehydration, stress ...).
DOI: 10.17632/5kptnn7ycr.1
title: Guava (Psidium guajava) fruit digital and thermal Images

description: The data set contains 600 healthy, 1100 damaged, and 395 different diseased (wilt, Anthracnose, canker, rot) guava fruit ( mature, half-mature, and mature) digital images with a 3000x3000 resolution. In addition, a total of 1821 raw thermal images in the same categories with a resolution of 1440 x 1080 were added. The images are uploaded day-wise, maturity-wise, and drop height-wise.
DOI: 10.17632/y3s9w6wcb4.1
title: Inteligencia Artificial para potencializar los sistemas de gerencia en Servicios de Salud en Panamá

description: Inteligencia Artificial para potencializar los sistemas de gerencia en Servicios de Salud en Panamá
DOI: 10.17632/92ncbyx5h9.1
title: Data for: Micellar enhanced ultrafiltration (MEUF) of mercury-contaminated wastewater: Experimental and artificial neural network modeling

description: Micellar enhanced ultrafiltration (MEUF) of mercury-contaminated wastewater: Experimental and artificial neural network modeling MEUF was applied efficiently to remove mercury (Hg) from simulated wastewater by using polyacrylonitrile membrane and sodium dodecyl sulfate (SDS) as surfactant. In this process leakage of surfactant monomer to permeate water causing a secondary pollution that was addressed by using MEUF followed by activated carbon fiber (MEUF-ACF) process. The effect of operating parameters including, concentration of Hg and pH of feed solution, molar ratio of SDS to Hg, and retentate pressure was explored to optimize MEUF process. Moreover, artificial neural network (ANN) model was proposed to predict Hg removal efficiency to optimize MEUF process without laborious and time-consuming experimental work. ANN model performance was evaluated on the basis of statistical values such as mean square error (MSE) and coefficient of determination (R2). The experimental results presented that optimum operating parameters were 10ppm of Hg concentration, pH 7.0, molar ratio of SDS to Hg 8:1 and retentate pressure was 1.5bar. MEUF results showed 95.75% and 50.91% removal of Hg and SDS, respectively, while 96.83% Hg and 97.15% of SDS rejection was achieved using MEUF-ACF. The statistical values of proposed ANN model presented high degree of agreement between experimental and predicted values (R2 was found greater than 95% for training, validation and testing dataset). MEUF-ACF can eradicate issue of secondary pollution and proposed ANN model can be a competitive, powerful and fast alternate to laborious experimental work for MEUF process optimization.
DOI: 10.17632/2z3m8w9dtx.1
title: Solving the eigenvalue problem of the nuclear Yukawa-folded mean-field Hamiltonian

description: Abstract The nuclear Hamiltonian with a Yukawa-folded mean-field potential is diagonalized within the basis of a deformed harmonic-oscillator in Cartesian coordinates. The nuclear shape is characterized by the equivalent sharp surface described either by the well known Funny–Hills or the Trentalange–Koonin–Sierk parametrizations. They are both able to describe a very vast variety of nuclear deformations, including necked-in shapes, left–right asymmetry and non-axiality. The only imposed limitation on ... Title of program: yukawa Catalogue Id: AEYI_v1_0 Nature of problem The full single-particle nuclear Hamiltonian composed of the Yukawa-folded central, spin-orbit and Coulomb potentials is generated and diagonalized. The only symmetry of the problem is the so called z-signature symmetry which limits the nuclear shapes to those, being invariant with respect to a rotation by an angle π around the z-axis. Versions of this program held in the CPC repository in Mendeley Data AEYI_v1_0; yukawa; 10.1016/j.cpc.2015.09.020 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.17632/4nydhxjymw.1
title: Simulation data for CO2 corrosion rate of oil pipeline

description: This data present the corrosion rates of oil pipelines under harsh conditions (acidic fluid, high temperature, and low efficiency of corrosion inhibitor). The data have been generated by coupling an analytical corrosion rate model – NORSOK M506 – and Monte Carlo simulation. The variables used in the simulation include temperature of fluid, internal pressure, CO2 partial pressure, flow velocity inside the pipe, and corrosion inhibitor efficiency. Since the experimental and field measurements of internal corrosion rates are scarce - due to the cost and difficulty of inspection/monitoring techniques - the generated data can be used in development and validation of numerical and analytical models for predicting the corrosion rate of oil pipelines.
DOI: 10.17632/j8d8pfkvj2.7
title: Vibration and Motor Current Dataset of Rolling Element Bearing Under Varying Speed Conditions for Fault Diagnosis: Subset3

description: This dataset discloses vibration and motor current data for bearing faults under varying speed conditions from 680 RPM to 2460 RPM. The bearing conditions include healthy bearing, bearings with inner race faults, and bearings with outer race faults. For each faulty bearing condition, the three-phase induction motor is operated under randomly varying speed conditions. 
Important: Datasets are divided into three parts because of storage limitations (Subset1, Subset2, and Subset3). 

---- Description of vibration file format ----
Vibration data file contains five columns namely ‘Time Stamp’, ‘x_direction_housing_A’, ‘y_direction_housing_A’, ‘x_direction_housing_B’, and ‘y_direction_housing_B’. The unit of the vibration is ‘gravitational constant (g)’. 
vibration_aaaa_bbbb.csv : This file is "bbbb"-th vibration data includes rotating speed data of the condition of "aaaa".

---- Description of motor current file format ----
Motor current data file contains five columns namely ‘Time Stamp’, ‘R_phase’, ‘S_phase’, and ‘T_phase’. The unit of the motor current is ‘Ampare (A)’.

current_aaaa_bbbb.csv : This file is "bbbb"-th motor current data includes rotating speed data of the condition of "aaaa".

---- Description of rotating speed file format ----
Rotating speed data file contains two columns namely ‘Time Stamp’, and ‘speed’. The unit of the acoustic is revolutions per minute (RPM)’.
rpm_aaaa_bbbb.csv : This file is "bbbb"-th speed data includes rotating speed data of the condition of "aaaa".


For more detailed information, check our published paper.
Title: Vibration, Acoustic, Temperature, and Motor Current Dataset of Rotating Machine Under Varying Operating Conditions for Fault Diagnosis
Link: https://www.sciencedirect.com/journal/data-in-brief
DOI: 10.17632/b93kjpx4f9.1
title: experimental materials

description: experimental materials
DOI: 10.17632/2dzd2k4n2b.1
title: Enterobacter cloacae OMVs
DOI: 10.17632/thsvj4sycn.1
title: Brazilian Championship A-Series

description: This dataset contains the matches from 2003-2019 of the Brazilian Championship A-Series (BCAS). The main file is the matches-2003-2019.txt with self-explanatory columns (header). The other files are complementary to this one, one having average supporter attendance (average-attendance-2003-2019.txt) and the other with official rankings (ranking-2003-2019.txt). A more comprehensive study may be accessed in ResearchGate on the link: https://www.researchgate.net/publication/338595720_Predicting_Brazilian_Football_Championship_first_and_last_four_teams_between_2006_to_2019_since_mid-season All files are in GitHub as well: https://github.com/czekster/BCAS