cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/t255cjz787.1
title: Multiomics picture of obesity in young adults: part I

description: The proteomic data obtained for plasma samples of patients with different BMIs

This dataset presents the results of SearchGUI/PeptideShaker processing of HPLC-MS/MS profiling of plasma samples of patients with different BMIs. This dataset contains information about the proteins and peptides detected in the plasma samples, allowing researchers to gain insights into the proteomic profiles associated with different BMI categories. The dataset includes details about the identified proteins and peptides, such as their abundance levels and potential biological functions. 
Additionally, the dataset provides information on the quality of the analysis, including metrics such as false discovery rates and confidence scores for the identified proteins and peptides. 
In order to view the visualized results of proteomic analysis, one need to utilize the PeptideShaker package (http://compomics.github.io/projects/peptide-shaker). PeptideShaker is a comprehensive platform for analyzing and interpreting experimental data, offering insights into the quality of identified hits, the performance of mass spectrometry, and the effectiveness of search engines. 
Description of the experiment (as well as raw data and mgf files) is available as well (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912072/).
DOI: 10.17632/sy828c7v85.1
title: Imported Intermediate Goods and Product Innovation

description: This page shares the supplementary package for the article titled “Imported Intermediate Goods and Product Innovation”
DOI: 10.17632/v346r3jky8.1
title: CTCF-5

description: CTCF-RNA-seq-5
DOI: 10.17632/dfnm76y5pb.1
title: CTCF-4

description: CTCF-RNA-seq-4
DOI: 10.17632/7ww5t454fv.1
title: CTCF-3

description: CTCF-RNA-seq-3
DOI: 10.17632/7fkktknnm8.1
title: CTCF-2

description: CTCF-RNA-seq-2
DOI: 10.17632/s9bgnzgbkf.1
title: Procrastination and risky health behaviors: a possible way to nurture health promotion among young adults in Italy

description: he dataset was used in a cross-sectional study aimed at examining the relationship between EI and sleep quality among undergraduate university students in Southern Italy. This study took place between the 13th and 28th of February 2023 in a representative sample of Italian university students of one public university in the Calabria Region. The information is collected through an online questionnaire that is filled in by respondents. The online survey was sent via institutional email. An anonymous and structured questionnaire was used, comprising four sections.
The survey comprised five sections. Four questions were included in the questionnaire's initial part (1) to examine social and demographic variables. The Pure Procrastination Scale (PPS) was used in the second segment (2) to assess levels of procrastination. In the survey’s third component (3), which examined tobacco use, participants were asked if they had ever smoked at least 100 cigarettes and, if so, how often on average they did it (daily, sometimes, or not at all). Using the classification provided by the Centre for Disease Control and Prevention, people were categorized as non-smokers, former smokers, occasional smokers, or daily smokers 12. The Fagerström Test for Nicotine Dependence (FTND) was administered to everyone who had been classified as current smokers (daily and occasional smokers). The fourth section (4) examined unhealthy alcohol intake, using the screening tool known as the Alcohol Use Disorders Identification Tool (AUDIT). In the last section (5) the item "How many days a week do you eat breakfast?" was utilized as a proxy measure of unhealthy dietary patterns. The response options varied from 0 to 7 days a week, and those who skipped breakfast more than three times per week were defined as breakfast skippers.
DOI: 10.34740/kaggle/dsv/8009195
title: Mahanagar Yatayat Transport Dataset
DOI: 10.17632/x5f67vn7v8.1
title: Development and Validation of an Aggression Questionnaire for Iranian Adolescents: A Case Study of 14 to 18-Year-Olds in Tehran

description: A cluster sampling method was employed for the quantitative phase. From Tehran's 22 educational districts, six (Districts 1, 5, 9, 13, 17, and 20) were randomly selected. Within each district, one girls' school and one boys' school were chosen at random. From each school, two classes ranging from seventh to eleventh grades were randomly selected. All students in these classes were considered potential participants. If any student or their parent opted out, another student from the same class was selected. In total, 1100 adolescents participated, with 1051 questionnaires completed. Demographic data collected included gender, age, parents' marital status, education, and occupation.
DOI: 10.17632/kr33mvtw63.1
title: Survey Data on Ranking of Musculoskeletal Disorder Risk Factors

description: The survey sought input from experts on how serious each risk factor was perceived to be. Using a scale from 1 to 25, where 1 meant the highest severity and 25 the lowest, participants could rate the seriousness of each factor numerically. They were presented with a list of 25 risk factors and asked to assign a severity rating to each, with the design ensuring clear understanding and informed ranking based on perception.
DOI: 10.15468/aud8m7
title: Sample study on Avian diversity of Chupi Oxbow Lake, Purbasthali, Purba Bardhaman, West Bengal

description: The Nature Mates Nature Club has released a dataset entitled "Sample study on Avian diversity of Chupi Oxbow Lake, Purbasthali, Purba Bardhaman, West Bengal" 
The Purbasthali, also known as Chupir Char or beel locally, covers 2.19 km of water and stretches from 23°25′54′′ to 23°27′54′′N and 88°19′45′′ to 88°21′54′′E. (Mandal et al. 2018). In West Bengal’s lower Gangetic delta, the wetland is situated between the districts of Nadia and Purba Barddhaman (Mandal & Siddique, 2018). Due to its link with the river at its southern end across a narrow strait, this water body has a distinctive combination of lacustrine (lentic) and riverine (lotic) habitats (Ganesan & Khan 2007). The lake’s crescent-shaped shape was created between 1989 and 1991 as a result of the lateral displacement of the river stream and concurrent erosion and deposition processes (Mandal & Siddique, 2018).
According to the Ramsar classification, the wetland of Purbasthali (Chupir Char), which is physiographically an oxbow lake, is designated as a marsh (jheel) of Gangetic Alluvial Plains (Mandal & Siddique 2018). The habitat of an oxbow lake is typically Adjacent to a river and favorable for the establishment of numerous species of fauna and plants (Ward et al. 1999; Stella et al. 2011). This lake is connected to the River Bhagirathi by a little waterway. As usual, this oxbow lake offers a good habitat for various water bird species.
The lake is currently threatened by habitat loss due to the overgrowing of Water Hyacinth.
Large numbers of birds in and around Chupi Lake were studied. This dataset includes all the water birds recorded on the 21st of January 2024.
All the birds are identified up to the species level. 32 species of birds belonging to 10 orders and 15 families were recorded from this oxbow lake.
DOI: 10.17632/g7z242sngr.1
title: Supplemental Material: Barriers to care in patients with skin of colour who have hidradenitis suppurativa: A systematic review

description: Supplemental Material: Barriers to care in patients with skin of colour who have hidradenitis suppurativa: A systematic review
DOI: 10.17632/5k56n7sbry.1
title: Behavioural Model on solving mental depression

description: This code performs an analysis of the dataset containing information about root causes of depression among college students. Here's a breakdown of what each part of the code does:

Loading the Dataset:

The code uses Pandas to read a CSV file named 'root_causes_depression_data.csv' into a DataFrame named df. This dataset likely contains information about various factors contributing to depression among college students.
Computing the Correlation Matrix:

The code computes the correlation matrix of the DataFrame df using the corr() method. This matrix provides insights into the relationships between different variables in the dataset.
Plotting the Correlation Matrix:

It uses Seaborn and Matplotlib to create a heatmap visualization of the correlation matrix. The heatmap annotates each cell with the correlation coefficient, providing a visual representation of the strength and direction of correlations between pairs of variables.
Generating Scatter Plots:

For each pair of variables in the dataset, the code generates scatter plots using Seaborn's scatterplot function. These scatter plots visually represent the relationship between each pair of variables, helping to identify potential patterns or trends.
Performing Statistical Analysis:

Finally, the code conducts statistical analysis for each pair of variables. It calculates correlation coefficients and p-values using the pearsonr function from the scipy.stats module. These values quantify the strength and significance of the linear relationship between pairs of variables.
Overall, this code provides a comprehensive analysis of the dataset, including visualizations of correlations and scatter plots, as well as statistical insights into the relationships between different root causes of depression among college students.
DOI: 10.17632/nm4j6vjtdm.1
title: Base Saturation Flow Rate (BSFR) and Its Effect on Performance of Pretimed Signalized Intersection with Non-lane Based Urban Heterogeneous Traffic

description: This data set is employed to model the Base Saturation Flow Rate (BSFR) by comparing newly obtained PCEs and previously existing PCEs from the IHCM 1997.
DOI: 10.15468/dl.qvn266
title: Occurrence Download

description: A dataset listing the 1674 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is The Fungarium of Yugra State University"
 ]
}

 The dataset's 1674 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0083628-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/b2xnxxmx8c.1
title: Data from "Dynamic mechanical analysis of asphalt mortar samples containing millimetre-size capsules for self-healing purposes"

description: These folders contain the experimental data from "Dynamic mechanical analysis of asphalt mortar samples containing millimetre-size capsules for self-healing purposes"
You can visualise all the Origin files with .opju extension by downloading the free software Origin Viewer in the following link:
https://www.originlab.com/viewer/dl.aspx
DOI: 10.17632/s3h6gjktmp.1
title: Spike rate modulation of locus coeruleus neurons associated with visual spatial attention in monkeys

description: Spike rate modulation of locus coeruleus neurons associated with visual spatial attention in monkeys. We trained two rhesus monkeys to selectively attend one of two visual stimulus locations while performing a visual orientation change detection task. Once the animal fixated, two Gabor sample stimuli appeared for 200 ms, one in each hemifield. After a brief delay (200-300 ms), a Gabor test stimulus appeared in one of the locations. The monkey had to report whether the test stimulus had a different orientation than the sample that had appeared in that location by making a saccade to one of two colored saccade targets after the fixation spot went off. The locations of the saccade targets were interchanged randomly across trials. Spatially selective attention was controlled in blocks of trials by different reward sizes and by varying the test stimulus probability for the two locations. While the monkeys did the attention task, we recorded simultaneously from populations of LC neurons (monkey S, n = 229; monkey P, n = 185). Recorded neurons were classified as phasic responsive to visual stimulus (phasic, monkey S, n = 89/229; monkey P, n = 74/185), pre-stimulus fixation responsive (non-phasic, monkey S, n = 88/229; monkey P, n = 53/185) or saccade related (saccade, monkey S, n = 104/229; monkey P, n = 124/185).
DOI: 10.17632/6842v4h573.1
title: Pulmonary health in lactating mothers

description: This study shows the effect of home based exercise program on pulmonary function, functional capacity and quality of life among lactating mothers.
DOI: 10.15468/dl.vs3cwv
title: Occurrence Download

description: A dataset containing 95718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 95718 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0083607-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8j44j8xn9y.1
title: SATO_BBC_SM

description: Data and codes to replicate the analysis and results reported in the paper "A Behavioral Business Cycle Model: A Unified Framework Using Prospect Theory"'
DOI: 10.17632/4p3rw53dgb.1
title: Thermal Ablation late NSCLC

description: Survival Analysis for Patients with and without thermal ablation for late stage NSCLC
DOI: 10.17632/9dnjb57fxn.1
title: Supplemental Material: Barriers to care in patients with skin of color who have hidradenitis suppurativa: A systematic review

description: Barriers to care in patients with skin of color who have hidradenitis suppurativa: A systematic review
DOI: 10.25919/t4fm-2567
title: Parkes observations for project P1050 semester 2023OCTS_13

description: This is a request for the observation time for the timing campaign of new pulsars discovered in the reprocessing of the low-latitude Galactic plane section of the HTRU-S survey (HTRU-S LowLat) and the Parkes Multibeam Pulsar Survey (PMPS). We have completed 90 % of the HTRU-S LowLat survey and completed zero acceleration PMPS search with GPU-based coherent acceleration search, template bank, and fast folding algorithm pipelines and now have discovered 112 previously unknown pulsars among which 18 were found in the PMPS. Interesting science can usually only be derived from a new pulsar after confirmation, and a follow-up timing campaign is carried out. At least 1-2 year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, and spin-down rate, as well as for detecting any unexpected behaviour of the pulsar which might result from emission instabilities. This project is necessary for the timing of several interesting pulsars, including binary pulsars, high DM pulsars, scattered profile pulsars, and bright ones that show emissions in larger bandwidths in the UWL band. Apart from this, finding the nature of a unique binary pulsar system via a dedicated observing campaign is also another goal. The follow-up timing in semester 2023OCTS will assist in completing many exciting large-term science goals.
DOI: 10.17632/3nf7mpbmw6.1
title: BALF mNGS data of Treponema denticola

description: A 58-year-old female with inadequate oral hygiene complained of persistent cough and intermittent hemoptysis for one month. Initially diagnosed with community-acquired pneumonia and oral trichomoniasis infection, the administered moxifloxacin and metronidazole proved ineffective in alleviating symptoms. Subsequent mNGS analysis of bronchoalveolar lavage fluid confirmed pneumonia caused by Treponema denticola, prompting the initiation of doxycycline hydrochloride treatment. Follow-up assessments revealed symptom relief and lesion absorption. Pulmonary infection attributable to T. denticola is infrequent and lacks specific clinical manifestations, which make the diagnostic process quite difficult and time-consuming. mNGS is a useful tool for detecting rare pathogen of infectious diseases.
DOI: 10.17632/99376px5mn.1
title: Supplementary Materials- A prospective cohort study of factors associated with the digital cushion thickness in dairy cattle

description: Supplementary Table S1. Descriptive Statistics of explanatory variables at each time point. Continuous variables are presented alongside the mean, standard deviation (SD), range and number of missing values (%). Categorical variables are presented alongside the frequency within each level (%).

Supplementary Table S2. Descriptive Statistics of explanatory variables at each time point grouped by farm. Continuous variables are presented alongside the mean, standard deviation (SD), range and number of missing values (%). Categorical variables are presented alongside the frequency within each level (%).

Supplementary Table S3. Results from univariable analysis of explanatory variables with DCT as an outcome. 

Supplementary Table S4. Estimates and 95% confidence intervals presented from the mixed effect linear regression model (Model 1) examining the association between explanatory variables, lesion presence at the time of measurement and the digital cushion thickness. These estimates and confidence intervals are presented in Figure 1a) The interaction between farm and stage of lactation on the digital cushion thickness (mm) and Figure 1b) The interaction between parity and stage of lactation on the digital cushion thickness (mm). 

Supplementary Table S5. Estimates and 95% confidence intervals presented from the mixed effect linear regression model (Model 2) examining the association between explanatory variables, lesion presence at the time of measurement and the digital cushion thickness. These estimates and confidence intervals are presented in Figure 2a) The interaction between farm and stage of lactation on the digital cushion thickness (mm) and Figure 2b) The interaction between parity and stage of lactation on the digital cushion thickness (mm).

Supplementary Table S6. Estimates and 95% confidence intervals presented from the mixed effect linear regression model (Model 3a, 3b and 3c) examining explanatory variables and lesions present at the time of measurement on the thickness of the digital cushion, focusing on each parity group in turn. These estimates and confidence intervals for the interaction between farm and stage of lactation on the digital cushion thickness (mm) in Figure 3; a) first parity, b) second parity and c) third or higher parity.
DOI: 10.17632/nj7w7g8nft.1
title: Assignment Markets

description: These are the Matlab codes and experimental data to replicate the main results and tables in "Assignment Markets: Theory and Experiments". 

-Code-

There are 5 separate stages to produce the results in the paper. Running them in this order should replicate the main tables in LaTeX format (printed to Matlab output), both for experimental subjects and simulated data points.

All files assume that YALMIP* is installed, added to Matlab path (see https://yalmip.github.io/) and that a mixed-integer solver is setup. Currently all files assume gurobi is installed. For CPLEX or other solvers, please edit the sdpsettings lines in the .m files.

* Lofberg, J. (2004, September). YALMIP: A toolbox for modeling and optimization in MATLAB. In 2004 IEEE international conference on robotics and automation (IEEE Cat. No. 04CH37508) (pp. 284-289). IEEE.

1. main.m
This file processes the experimental data, producing the main tables (Tables 6, 11-13) printing the results and saving them to experimentaldata.mat

2. simulations.m
This file runs the main simulations (Tables 3, 11-13), printing the results and saving them to powersimulations.mat

3. simulate_nbs.m
Additional simulations for the Nash bargaining solution (Table 4).

4. simulate_pncore.m
Additional simulations for the Pairwise Nash core (Table 5).

5. find_psi.m
Produces the Predictive Success Indices (Table 14), assuming that powersimulations.mat and experimentaldata.mat were already produced by stages 1 and 2.

Remaining matlab files contain function definitions used in the process.

-Data-

The same experimental data is in matlab format (raw_data.mat) and in csv format (raw_data.csv). 
Every matched group of six participants is uniquely identified by a code in the total_group column, which consists of session id and group number within session.
Rounds from 1 to 15 are identified by subsession__round_number variable.
The treatments are "double_auction" (DA), "minimum_price" (MP), "complete_info" (CI), and "telephone_pit" (PT). Treatment information is in the subsession_treatment variable.
For bargaining treatments, the offers are recorded in offers_to_player and player_offer variables.
For auction treatments, the standing bids and asks (minimum prices for the sellers) at the end of the round are stored in group_asks and group_bids variables.
For every buyer, the player_object_traded variable records the index of the good that the buyer had bought. NaN indicates that the buyer bought nothing in that round.
DOI: 10.17632/nj7w7g8nft.2
title: Assignment Markets

description: These are the Matlab codes and experimental data to replicate the main results and tables in "Assignment Markets: Theory and Experiments". 

-Code-

There are 3 separate stages to produce the results in the paper. Running them in this order will replicate the main tables in LaTeX format (printed to Matlab output), both for experimental subjects and simulated data points.

All files assume that YALMIP* is installed and added to Matlab path (see https://yalmip.github.io/) and a mixed-integer solver is setup. Currently all files assume gurobi is installed. For CPLEX or other solvers, please edit the sdpsettings lines in the files.

* Lofberg, J. (2004, September). YALMIP: A toolbox for modeling and optimization in MATLAB. In 2004 IEEE international conference on robotics and automation (IEEE Cat. No. 04CH37508) (pp. 284-289). IEEE.

1. main.m
This file processes the experimental data, producing the main tables (Table 2 and left sides of H.10-12) printing the results and saving them to experimentaldata.mat

2. simulations.m
This file runs the main simulations (Table F.7 and right sides of H.10-12), printing the results and saving them to powersimulations.mat

3. find_psi.m
Produces the Predictive Success Indices (Table F.8), assuming that powersimulations.mat and experimentaldata.mat were already produced by stages 1 and 2.

Remaining matlab files are function definitions used in the process.

Additionally, the bargaining solutions can also be simulated:

a. simulate_nbs.m
Additional simulations for the Nash bargaining solution.

b. simulate_pncore.m
Additional simulations for the Pairwise Nash core.

-Data-

The same experimental data is in matlab format (raw_data.mat) and in csv format (raw_data.csv). 
Every matched group of six participants is uniquely identified by a code in the total_group column, which consists of session id and group number within session.
Rounds from 1 to 15 are identified by subsession__round_number variable.
For bargaining treatments, the offers are recorded in offers_to_player and player_offer variables.
For auction treatments, the standing bids and asks (minimum prices for the sellers) at the end of the round are stored in group_asks and group_bids variables.