cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/s3bzzhbf5p.1
title: Comparative genome analyses and genome annotation of Foc VCGs infecting Cavendish banana in India

description: Fusarium wilt is caused by the fungus Fusarium oxysporum f. sp. cubense (Foc), the most serious disease affecting banana (Musa spp.) classified into Foc race 1 (R1), Foc race 2, and Foc race 4 based on the host specificity. As the rate of spread and the ranges of the devastation of the Foc races are higher than the center of the banana’s origin, even in non-targeted cultivars, there could be a chance of variation in virulence-associated genes. Therefore, the present study investigates the genome assembly of Indian Foc races belonging to the vegetative compatibility group (VCG) 0120 (subtropical race 4), 0124 (race 1), and 01213/16 (tropical race 4) infecting the Cavendish (AAA) banana group in India. The data repository includes annotations of the respective genome in GFF file formate, SIX gene database and alignments with Phylogenetic tree
DOI: 10.17632/t4rysh9rxf.1
title: Eggplant_Hyperspectral_Dataset

description: Eggplant crop hyperspectral data was acquired using a terrestrial hyperspectral imaging spectroradiometer.
DOI: 10.17632/tdp2krwtsf.1
title: Data for Detecting geothermal anomalies using multi-temporal thermal infrared remote sensing data in the Damxung-Yangbajain basin

description: Average winter land surface temperature in Damxung.
DOI: 10.17632/6hgyr25h8d.1
title: Data for: Analysis and modeling of cycle aging of a commercial LiFePO4/graphite cell

description: This data is from a comprehensive cycle aging study on a lithium-ion battery with a test duration of 29 months: Naumann, M. et al.; Analysis and modeling of cycle aging of a commercial LiFePO4/graphite cell; Journal of Power Sources (2020), Volume 451; DOI: 10.1016/j.jpowsour.2019.227666 This aging study presents cycle aging results of a commercial lithium-ion cell from a comprehensive, 29 month aging study and follows up on calendar aging results published previously [1]. We use a widely used commercial LiFePO 4 /graphite cell from Sony/Murata, which promises long calendar and cycle lifetime, that would make it suitable for stationary battery applications. The evolution of the cells’ capacity and impedance are shown in a static cycle aging study for 19 test points with different combinations of temperature, C-rate, depth of discharge and state of charge. Based on the measurement data shown herein and the calendar aging model presented in the previous paper, a semi-empirical combined aging model is presented for the capacity loss and resistance increase. Two dynamic load profiles are used to experimentally validate the combined aging model. Absolute model errors below 1% for the capacity loss and below 2% for the resistance increase in both dynamic load profiles demonstrate that the combined aging model can predict the lifetime of LiFePO 4 /graphite battery cells for different applications and varying operation conditions adequately. In the cycle experiments, an unexpectedly strong, but partly reversible capacity loss is observed with shallow cycles at medium states of charge.
DOI: 10.17632/jnbxwyybcn.2
title: Variable physical drivers of near-surface turbulence in a regulated river

description: This dataset is used to analyze the drivers of near-surface turbulence in large rivers. The data were collected during the measurement campaign conducted at the River Kitinen in Northern Finland (67.3665º N, 26.6230º E) in the summer of 2018. At the study site, the river is 181 m wide, and its flow is regulated by two hydropower stations. These unique data include results of measurements in the river and the atmosphere collected at different locations: a floating platform in the middle of the river, the river bottom, a meteorological mast at the river bank, and a land meteorological tower located at a small distance to the east of the river bank. The river data contain continuous measurements of flow velocity (ADCP, bottom; ADV, platform), water temperature (thermistor chain, river middle), water level (wave recorder, river bank), and photosynthetically active radiation (PAR sensor, platform). The atmospheric data contain continuous measurements of wind speed and direction, air temperature and relative humidity, and incoming shortwave and longwave radiation (river bank mast and land tower). The detailed information about the measurement instruments can be found in the corresponding article “Variable physical drivers of near-surface turbulence in a regulated river”.

Rivers are an important source of the greenhouse gases to the atmosphere. The gas exchange at the air-water interface is largely controlled by the near-surface turbulence, which has not been studied in details for large rivers. The idea behind the analysis of these data is to determine the main drivers of the near-surface turbulence in large rivers and their relative importance. To that end, we computed the dissipation rate of turbulent kinetic energy and compared it with the estimates provided by bulk scaling relations and a one-dimensional numerical turbulence model. The results are two-fold. First, all estimation methods are able to accurately predict the dissipation rate. Second, the two main drivers of the near-surface turbulence, namely the bottom friction and the atmospheric forcing, have comparable relative contributions.
DOI: 10.17632/546t9249bv.1
title: Gridded emissions of CO, NOx, SO2, CO2, NH3, HCl, CH4, PM2.5, PM10, BC and NMVOCs emissions from open municipal waste burning in India

description: This data set contains a new municipal open waste burning emission inventory from India (OWBEII), at a resolution of 0.1° x 0.1°. The data is provided in the format latitude, longitude, CO2, CO, H2, NO, NO2, SO2, NH3, CH4, NMOC, BIGALD, BIGALK, BIGENE, C0H6, C2H4, C2H5OH, C2H6, C3H6, C3H8, CH2O,CH3CHO, CH3COCH3, CH3COCHO, CH3COOH, CH3OH, PHENOL, CRESOL, GLYALD, HYAC, ISOP, MACR, MEK, MVK, HCN, CH3CN, BENZENE, TOLUENE, XYLENES, PM25, OC, BC, PM0,HCOOH, C2H2. All emissions are given in the unit tonne per year per grid cell. The latitude and longitude value given refers to the lower left (southeast) corner of the grid cell. The emission inventory is valid for the year 2015. A detailed description of the method used to compile the dataset can be found in Sharma et al (under review in ES&T). Kindly insert the following citation when using this data set: Gaurav Sharma, Baerbel Sinha , Pallavi, Haseeb Hakim, Boggarapu Praphulla Chandra, Ashish Kumar, Vinayak Sinha, Gridded emissions of CO, NOx, SO2, CO2, NH3, HCl, CH4, PM2.5, PM10, BC and NMVOCs emissions from open municipal waste burning in India, under review in ES&T, 2019.
DOI: 10.17632/jgv5hmzc44.1
title: Urban census tract and HOLC polygon grade summaries and scripts from Chakraborty et al. 2023

description: All data and code required to generate census tract and HOLC polygon level heat stress indices, as well as the urban-scale segregation indices can be found here. 

Urbanized_CT_summer_env.csv includes the 2014-2018 average maximum summer skin temperature (TSKINmax), air temperature (ATmax), and minimum and maximum specific humidity (QTmax and QTmin) from the model simulations, as well as the corresponding derived land surface temperature from the MODIS Aqua daytime overpass (MODIS_LST_day), for each urban census tract in the continental US. 

Urbanized_CT_sociodemo.csv includes socioeconomic information from the 5-year 2017 American Community Survey, including population (Pop), income (Income), and number of people who are white (White), black (Black), American Indian (AmInNat), asian (Asian), hawaiian (Hawaiin), or of another race (Other) for each urban census tract in the continental US. 

Urban_census_tracts.geojson includes the spatial extent of all urban census tracts in the continental US. 

The three datasets above can be linked using the 'Census_geoid' column.

Redlining_summer_env.csv is similar to Urbanized_CT_summer_env.csv, but corresponding to the Home Owners’ Loan Corporation grades, the polygons for which were digitized by University of Richmond’s Digital Scholarship Lab.

Within the Scripts folder, there are two scripts:

Calculate heat indices.ipynb is a Jupyter Notebook for estimating the lower and upper bound for average maximum summer relative humidity (RH_min and RH_max) and heat index (HI_min and HI_max), as well as the lower bound for Humidex (HUMIDEX).

Segregation_calculate.R is an R script for calculating various inequality indices, including entropy index, dissimilarity index, gini coefficient, and concentration indices against race and income for the heat index.
DOI: 10.17632/nm9hn3k53f.1
title: Dark Tourism Scopus database (1996-2022)

description: Dark Tourism Scopus dataset for bibliometric analysis from the year 1996 to 2022 after duplication od similar title removed.
DOI: 10.17632/wrrc55c44f.1
title: Data for: Zircon constraints on granite provenance in the northern North China Craton

description: These are supplementary datasets for article ‘Zircon constraints on granite provenance in the northern North China Craton’
DOI: 10.17632/5thy2mcwn7.1
title: Data for Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

description: Data underlying figures and relative risk curves within the article. Provides readers the mean value and uncertainty intervals for prevalence of current drinking, drinks per day by location, relative risks by outcome and dose, along with results for the weighted all-cause relative risk curve used to justify TMREL within the study. Based off sources mentioned in Appendix I. From Abstract in linked paper: Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health
DOI: 10.17632/vfg8jyxn7j.2
title: Data for: The Impact of Autonomous Trucks on Business Models in the Automotive and Logistics Industry - A Delphi-Based Scenario Study

description: eAppendix for the research paper "The Impact of Autonomous Trucks on Business Models in the Automotive and Logistics Industry - A Delphi-Based Scenario Study" E-Appendix 1: Delphi Study: Questionnaire Round 1 E-Appendix 2: Delphi Study: Questionnaire Round 2 E-Appendix 3: Analysis of Delphi Study E-Appendix 4: Slide Deck Delphi Study
DOI: 10.17632/8g4wfwtd43.1
title: SYNBIOCHEM Design-Build-Test-Learn pipeline

description: Quantified titers and peak values measured through different rounds of the SYNBIOCHEM Design-Build-Test-Learn (DBTL) pipeline for microbial production of fine chemicals. The pipeline was applied for the production of flavonoids and alkaloids in Escherichia coli. The flavonoids data contains cinnamate and (2S)-pinocembrin measurements for combinatorial libraries for: a) DBT round 1; b) DBT round 2; c) Chassis selection; d) Media screening; e) Optimization. The alkaloids data provides (S)-reticuline and (S)-scoulerine measurements for a combinatorial library corresponding to one DBTL round.
DOI: 10.17632/vz6z64nwby.1
title: WaterHyacinth: A Comprehensive Image Dataset of Various Water Hyacinth Species From Different Regions of Bangladesh.

description: The newly created dataset "WaterHyacinth" contains information on numerous kinds of water hyacinth that are often found in different parts of Bangladesh. There are four different species of water hyacinth represented in this dataset. Lemna minor, Eichornia crassipes, Monochoria korsakowii, and Pistia stratiotes are the four separate species. There are 1,790 original images in the entire collection. We gathered these photographs over a period of three months, from July 2023 to September 2023, from separate locations of Sirajganj and Pabna zilla under a variety of outdoor lighting situations as well as inside lighting with acceptable backgrounds. The file also includes 4,050 extra augmented photos. This extensive dataset offers enormous potential for researchers to contribute to environmental science, aquatic science, remote sensing, and water condition monitoring using different Machine Learning and Deep Learning techniques. It is an invaluable asset for future work, including remote sensing with satellite imagery, managing water quality, and conserving biodiversity domains.
DOI: 10.17632/hstr2397fx.1
title: Data for: Preparation and characterization of cinnamon essential oil nano-capsules and comparison of volatile components and antibacterial ability of cinnamon essential oil before and after embedding

description: These datas include: preparation and characterization of cinnamon essential oil nanocapsules, changes of volatile components and antibacterial properties in cinnamon essential oil before and after embedding.
DOI: 10.17632/mw2mmpdz3g.1
title: Mearns_et_al_2019

description: Processed behavioral data from 7-8 dpf zebrafish larvae performing prey capture behavior.
DOI: 10.17632/g46n66frrh.1
title: Dataset for Evaluating Hair Hall Causes Using Machine Learning Techniques

description: This dataset provides comprehensive information on various factors contributing to hair fall. The dataset contains 717 responses from a survey designed to capture details about individual hair care practices, lifestyle choices, and genetic predispositions.

Features:

1. Age
2. Gender
3. Usage of hair products
4. Water quality
5. Stress levels
6. Late-night activities
7. Presence of anemia
8. Family history of hair fall
9. Personal health conditions

Potential Uses:
Researchers, data scientists, and healthcare professionals can use this dataset to analyze the factors influencing hair fall. It is particularly useful for:

-- Identifying patterns and correlations among various factors contributing to hair fall.
-- Developing predictive models to forecast the likelihood of hair fall based on individual attributes.
-- Designing personalized hair care and treatment plans.
-- Conducting exploratory data analysis to uncover new insights about hair health.

Future Predictions:
From this dataset, future predictions can be made regarding:

-- The impact of lifestyle choices on hair fall severity.
-- The likelihood of hair fall based on genetic predispositions and family history.
-- The effectiveness of different hair care products and practices.
-- The relationship between stress levels and hair fall.

This dataset serves as a valuable resource for advancing the understanding of hair fall causes and developing targeted solutions to mitigate this common issue.
DOI: 10.17632/zj3237z56k.1
title: Supplementary data for "How Does Competition Affect Retail Banking? Quasi-Experimental Evidence From Bank Mergers"

description: Supplementary data for "How Does Competition Affect Retail Banking? Quasi-Experimental Evidence From Bank Mergers" by Jack Liebersohn (Journal of Financial Economics, 2024).
DOI: 10.17632/34dzth4ynm.1
title: Temporal changes in the stress regime on the seismogenic zone of the 2015 Gorkha Earthquake

description: Data collection: 1988/08/20 to 2016/11/27

Contact information: Bishal Maharjan, Central Department of Geology, Tribhuvan University, Kirtipur, Kathmandu, Nepal, bishalmaharjan85@gmail.com

This repository contains the following datasets:
1. COMPILED FOCAL MECHANISM DATASETS (compiled after: see original manuscript)
2. WEIGHTED DATASETS FOR PRE-SEISMIC PERIOD AND POST-SEISMIC PERIOD (for weighting procedure: see original manuscript)
3. RESULTS OF STRESS INVERSION FOR PRE-SEISMIC PERIOD AND POST-SEISMIC PERIOD
4. SUPPLEMENTARY TABLES
DOI: 10.17632/c2cv8pg5d8.2
title: Energetically accessible structures of xMgCl2/yTiCl4 clusters (x = 6–19, y = 0–4)

description: Dataset of energetically accessible structures of xMgCl2/yTiCl4 clusters (x = 6–19, y = 0–4) obtained by non-empirical structure determination based on combination of the genetic algorithm and DFT calculations. The dataset was uploaded for a article "Dataset of energetically accessible structures of xMgCl2/yTiCl4 clusters (x = 6–19, y = 0–4) obtained by non-empirical structure determination based on combination of the genetic algorithm and DFT calculations" in Data in Brief.
DOI: 10.17632/jdbfy6crpn.1
title: Comparative analysis of lucid dream deepening techniques by practitioners

description: Results of performing of eight techniques for increasing perception vividness, or deepening techniques (DTs) in lucid dreams (LDs) by practitioners from December 23, 2018, to November 11, 2022. 

Experimental task

Each DT corresponded to a specific task. Volunteers could participate in one or more tasks. A separate LD experience was required to perform each DT. Participants were instructed to initiate LD by any method and immediately perform a DT corresponding to the task without using other techniques that could affect perception vividness. Then, participants were to pay attention to how perception vividness changed.
Regardless of the result, participants were allowed to perform each experiment only once before submitting their reports on the website. Also each participant reported which LD induction method they used, all the LD events, the LD termination type, and the number of LDs experienced in their lifetime.

Tested DTs

This study compared eight DTs: imagining wakefulness, spinning, falling upside down, warming up, verbal command, vibrations, obscene expressions, and palpation. For each DT, except for palpation, tasks were provided in Russian. For palpation DT, the task was presented in English.

Statistical analysis

Eight DTs correspond to the five principles on which they are based (DT types): sensory, motor, vestibular, emotional, and suggestion types.
Sensory - palpation, vibration;
Motor - warming up;
Vestibular - falling upside down, spinning;
Emotional - obscene expressions;
Suggestion - imagining wakefulness, verbal command;

Rows:
1) DT name - imagining wakefulness, spinning, falling upside down, warming up, verbal command, vibrations, obscene expressions, palpation;
2) DT type - sensory, motor, vestibular, emotional, suggestion;
3) STATUS  yes/no (did the technique lead to an increase in perception vividness in LD) - yes, no, n/a (other or unclear);
4) STATUS (specific result of DT performing) - Same (real) (perception vividness remained at a high level), worked (perception vividness increased without exceeding that experienced during wakefulness), hyper (DT led to perception vividness exceeding that experienced during wakefulness), foul (LD termination), decrease (decrease in perception vividness), Same (low) (perception vividness remained at a low level), n/a (other or unclear);
5) GENDER - m, w;
6) LDs number (the number of LDs in a practitioner's lifetime) - 1(<4), 2(4-10), 3(11-30), 4(31-100), 5(101-500), 6(>500);
7) METHOD (LD induction method) - indirect (upon awakening), direct (without sleeping, upon falling asleep, or immediately after falling asleep), ld (becoming conscious during a dream), n/a (other or unclear);
8) END (LD termination type) - force (unintentional natural awakening), dream (unintentionally falling asleep or getting lost in a dream plot), outer (awakening due to external factors), self (intentional awakening), fake (unrecognized false awakening), n/a (other or unclear).
DOI: 10.17632/rmk89k4rhb.16
title: Appointment Wait Times for Primary and Specialty Care in Veterans Health Administration Facilities vs. Community Medical Centers

description: These deidentified datasets have been approved for public release by the VA Boston Healthcare System's Institutional Review Board and Privacy Office. Our data include approximately 52 million appointment wait times for both VA & community-based medical professionals from January 1st, 2014 to December 31st, 2022. Special thanks to Erin Beilstein-Wedel for helpful feedback and troubleshooting! 

Please cite the following publication when using this dataset:

Y. Feyman, Legler, A., & K.N. Griffith. (2021). Appointment Wait Time Data for Primary & Specialty Care in Veterans Health Administration Facilities vs. Community Medical Centers. Data in Brief: e107134.


A non-exhaustive list of other peer-reviewed articles using these data:

Griffith, KN, Ndugga, NH, & Pizer, SP. (2020). "Appointment Wait Times for Specialty Care in Veterans Health Administration Facilities vs Community Medical Centers." JAMA Network Open 3(8): e2014313. 

Auty, SG, & Griffith, KN. (2021). “Medicaid Expansion Increased Appointment Wait Times in Maine and Virginia.” Journal of General Internal Medicine 37(10): 2594-2596.

Griffith, KN, Asfaw, DA, Childers, RG, & Wilper, AP. (2022). “Changes in veterans’ access to specialty care during the COVID-19 pandemic.” JAMA Network Open 5(9): e2232515.

Feyman, Y, Asfaw, D, & Griffith, KN. (2022). “Geographic Variation in Appointment Wait Times for U.S. Military Veterans.” JAMA Network Open 5(8): e2228783.

See more on Google Scholar: https://scholar.google.com/scholar?oi=bibs&hl=en&cites=10379915202775127115&as_sdt=5