cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14513306
title: Data on Climate-Optimized Aircraft Trajectories in European Airspace for 2022

description: This repository provides the data and Jupyter Notebooks required to reproduce the analyses and figures presented in the paper, available as a preprint at https://doi.org/10.21203/rs.3.rs-4355046/v1. The paper is currently under review in Communications Earth & Environment from Nature Portfolio.

Below is a detailed description of the content included in the `.zip` file, along with the required software dependencies. 

Contents

Data:

There is a folder in the repository (i.e., Data) containing various datasets, including the results of trajectory optimization over one year, such as flight performance variables, emissions, and climate effects, all in pickle file format. These datasets will be used with the Jupyter notebooks described below.

 

Jupyter Notebooks:



Routing_options_0.2%_SOC_different_routing_penalization_limits.ipynb


This notebook analyzes one year of trajectory optimization data, considering a maximum 0.2% increase in operational cost and varying limits on the number of rerouted flights.

 



Routing_options_2.0%_SOC_different_routing_penalization_limits.ipynb


This notebook analyzes one year of trajectory optimization data, considering a maximum 2.0% increase in operational cost and varying limits on the number of rerouted flights.

 



Routing_options_main_paper.ipynb


This notebook analyzes one year of trajectory optimization data for multiple limits on operational cost increases (i.e., 0.0% (cost-optimal), 0.2%, and 2.0%) and different rerouting constraints. It generates the figures currently included in the paper.

 



Routing_options_up_to_3.0%_SOC_unrestricted_rerouting.ipynb


This notebook analyzes one year of trajectory optimization data with operational cost increases of up to 3.0% and no restrictions on rerouted flights.

 



Traffic_scenario_sensitivity_analysis.ipynb


This notebook performs sensitivity analysis for scaled-up traffic scenarios (refer to Figure S8).

 

Solution Picking Algorithm:

The repository also includes a folder named "Solution_Picking," which implements the decision-making algorithm described in the Method section of the paper. An example is provided, corresponding to Supplementary Figure S16.

---

Software Requirements

The following Python packages are required to run the Jupyter Notebooks:






Package



Version





numpy



1.20.3





pandas



1.4.2





matplotlib



3.5.0





pyomo



6.4.3





coopr



4.0.9597





coopr-pyomo



3.6.4





glpk



5.0





seaborn



0.13.2





 

 

Instructions

1.     Ensure Python is installed (Python 3.8.5 is recommended).

2.     Install the required packages using the following command:

```bashpip install numpy==1.20.3 pandas==1.4.2 matplotlib==3.5.0 pyomo==6.4.3 coopr==4.0.9597 seaborn==0.13.2```

3.     Install GLPK for optimization. Instructions for GLPK installation can be found on the official GNU GLPK website [here](https://www.gnu.org/software/glpk/).
DOI: 10.15468/dl.arktap
title: Occurrence Download

description: A dataset containing 171968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2024-11-24",
 "EventDate is less than or equal to 2024-12-24",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 171968 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042330-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tb5vyg
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elymus campestris x repens"
 ]
}

 The dataset includes 11 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042348-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f26n27
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Latvia",
 "OccurrenceStatus is Present",
 "TaxonKey is Buddleja davidii Franch."
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042350-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v9qvqe
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendroctonus micans (J.G.Kugelann, 1794)",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 30 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042351-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14524784
title: RFUds - A Brain Metastases Imaging Dataset of Radiotherapy Follow-Up

description: Brain metastases affect approximately 20% to 40% of cancer patients and their incidence has been increasing over time. Early detection, followed by a timely intervention, plays a critical role in mitigating the impact of this condition and significantly increasing the chances of treatment success. The Radiotherapy Follow-Up dataset (RFUds) contains medical images of 44 patients with brain metastases, whose primary tumors have different locations. Each patient was treated with radiotherapy, either with LINAC or Gamma Knife. RFUds consists of several patients with different number of treatments and follow-up sessions and contains pre-treatment NifTI CT and MRI files, along with volumes concerning each of the structures delineated during each treatment planning phase, and MRIs acquired in follow-up sessions. RFUds is derived from an original dataset after processing to enhance contrast and improve image quality. The CT datasets were subjected to windowing and artifact reduction and the MRI datasets were processed using the CLAHE technique. Image registration was performed between CT and MRI datasets to align all data from the same patient. In addition, a document containing the transformation matrix resulting from the image registration process is included for each MRI dataset.
DOI: 10.5281/zenodo.14524785
title: RFUds - A Brain Metastases Imaging Dataset of Radiotherapy Follow-Up

description: Brain metastases affect approximately 20% to 40% of cancer patients and their incidence has been increasing over time. Early detection, followed by a timely intervention, plays a critical role in mitigating the impact of this condition and significantly increasing the chances of treatment success. The Radiotherapy Follow-Up dataset (RFUds) contains medical images of 44 patients with brain metastases, whose primary tumors have different locations. Each patient was treated with radiotherapy, either with LINAC or Gamma Knife. RFUds consists of several patients with different number of treatments and follow-up sessions and contains pre-treatment NifTI CT and MRI files, along with volumes concerning each of the structures delineated during each treatment planning phase, and MRIs acquired in follow-up sessions. RFUds is derived from an original dataset after processing to enhance contrast and improve image quality. The CT datasets were subjected to windowing and artifact reduction and the MRI datasets were processed using the CLAHE technique. Image registration was performed between CT and MRI datasets to align all data from the same patient. In addition, a document containing the transformation matrix resulting from the image registration process is included for each MRI dataset.
DOI: 10.5281/zenodo.14525197
title: RFUds - A Brain Metastases Imaging Dataset of Radiotherapy Follow-Up

description: Brain metastases affect approximately 20% to 40% of cancer patients and their incidence has been increasing over time. Early detection, followed by a timely intervention, plays a critical role in mitigating the impact of this condition and significantly increasing the chances of treatment success. The Radiotherapy Follow-Up dataset (RFUds) contains medical images of 44 patients with brain metastases, whose primary tumors have different locations. Each patient was treated with radiotherapy, either with LINAC or Gamma Knife. RFUds consists of several patients with different number of treatments and follow-up sessions and contains pre-treatment NifTI CT and MRI files, along with volumes concerning each of the structures delineated during each treatment planning phase, and MRIs acquired in follow-up sessions. RFUds is derived from an original dataset after processing to enhance contrast and improve image quality. The CT datasets were subjected to windowing and artifact reduction and the MRI datasets were processed using the CLAHE technique. Image registration was performed between CT and MRI datasets to align all data from the same patient. In addition, a document containing the transformation matrix resulting from the image registration process is included for each MRI dataset.
DOI: 10.6084/m9.figshare.28057073
title: Supplemental Materials for Tessele et al (2025)

description: Marker information is included in files 'Sub-Genome-A.hmp.txt', 'Sub-Genome-B.hmp.txt', and 'Sub-Genome-D.hmp.txt', for sub-genomes A, B, and D, respectively. Raw phenotypic data is included in file 'Raw Phenotypes.txt' and across location BLUEs is included in file 'BLUEs.txt'. The Var.R, GS.R and Rank.R are the codes used to estimate the variance components, to run the genomic prediction models, and to rank lines according to sub-genome additive effects, respectively.
DOI: 10.6084/m9.figshare.28057073.v1
title: Supplemental Materials for Tessele et al (2025)

description: Marker information is included in files 'Sub-Genome-A.hmp.txt', 'Sub-Genome-B.hmp.txt', and 'Sub-Genome-D.hmp.txt', for sub-genomes A, B, and D, respectively. Raw phenotypic data is included in file 'Raw Phenotypes.txt' and across location BLUEs is included in file 'BLUEs.txt'. The Var.R, GS.R and Rank.R are the codes used to estimate the variance components, to run the genomic prediction models, and to rank lines according to sub-genome additive effects, respectively.
DOI: 10.15468/dl.v9zsmk
title: Occurrence Download

description: A dataset containing 158 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Typhleotris madagascariensis Petit, 1933"
 ]
}

 The dataset includes 158 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042352-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7qj75s
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platytroctes apus Günther, 1878",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 14 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042354-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00010783
title: Can a core set of disease activity domains define response in systemic lupus erythematosus clinical trials? An analysis of two Phase 3 randomised controlled trials of belimumab

description: Systemic lupus erythematosus (SLE) is a disease where the immune system mistakenly attacks the body’s own tissues, causing inflammation and damage. It can affect any part of the body, such as the skin, joints, kidneys, and heart. The symptoms and severity of the disease can vary greatly from one person to another, which makes it difficult to measure disease activity and track how well treatments are working. This is a significant challenge in recent clinical trials for lupus, as it is hard to determine the effectiveness of new treatments due to the variety of symptoms.

Currently, the tools used in clinical trials try to measure almost all of the possible symptoms that can occur in lupus. However, many of these symptoms are rare, not well understood, or hard to measure accurately, which makes it difficult to assess how well a treatment is working. This can lead to confusing results.

We believe that focusing on a smaller, more manageable group of the most common and measurable symptoms of lupus—referred to as a “core set”—might provide a more effective way to measure disease activity and treatment response. Our research aims to test this idea by looking at data from three previous clinical trials of a drug called belimumab. We want to see if we can identify which patients responded well to treatment by focusing on this smaller set of disease features.

If successful, this approach could simplify the way clinical trials are conducted, making it easier to evaluate how well new treatments work. It would also help focus on the most important aspects of lupus that affect patients' daily lives, leading to more accurate and meaningful results for those who participate in future clinical trials.
DOI: 10.15468/dl.kaeb9f
title: Occurrence Download

description: A dataset containing 12873 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "TaxonKey is Geranium carolinianum L."
 ]
}

 The dataset includes 12873 records from 183 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042355-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h22e9k
title: Occurrence Download

description: A dataset containing 12922 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Protium heptaphyllum (Aubl.) Marchand"
 ]
}

 The dataset includes 12922 records from 314 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042353-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.efqavr
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plectobranchus evides Gilbert, 1890",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 15 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042356-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n2rn5j
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Lithuania",
 "OccurrenceStatus is Present",
 "TaxonKey is Buddleja davidii Franch."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042357-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zqxnzj
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plectorhinchus mediterraneus (Guichenot, 1850)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 31 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042358-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.93xezb
title: Occurrence Download

description: A dataset containing 40465 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronectes platessa Linnaeus, 1758",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 40465 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042359-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u48dkr
title: Occurrence Download

description: A dataset containing 656169 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myiopsitta monachus (Boddaert, 1783)"
 ]
}

 The dataset includes 656169 records from 173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042349-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6nc7cf
title: Occurrence Download

description: A dataset containing 1440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-76.72783 3.55422,-76.47696 3.55422,-76.47696 3.72037,-76.72783 3.72037,-76.72783 3.55422))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Amphibia"
 ]
}

 The dataset includes 1440 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042361-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zeyzns
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Typhleotris pauliani Arnoult, 1959"
 ]
}

 The dataset includes 46 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042362-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u4z4bs
title: Occurrence Download

description: A dataset containing 179 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronichthys coenosus Girard, 1854",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 179 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042363-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7u34kc
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pleuronichthys decurrens Jordan & Gilbert, 1881",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 46 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042366-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/tzcbrhd2ny.1
title: Phonocardiogram Signal Dataset Paired with Blood Pressure Measurements

description: This dataset consists of phonocardiogram (PCG) signal recordings and blood pressure measurements together. The PCG signals capture heart sounds, offering valuable insights into the heart cycle and cardiac function. Paired with blood pressure readings, this dataset enables a deeper understanding of the relationship between heart activity and vascular health. It is suitable for use in machine learning, clinical research, and educational purposes.
DOI: 10.17632/8zjkcgyv9n.1
title: included publications for CEBM

description: included publications for CEBM
DOI: 10.17632/vm4wj9mycr.1
title: MV Portfolio via Shrinkage of Large CM

description: The "data" folder includes six real datasets (100IN, 100FF, 100OP, 100SP, 200FS, 235NY, 300CP, and 500CP) and three simulated datasets (ST50, ST100, and ST500).
The "code" file provides functions and instructions for reproducing the tables and figures.
DOI: 10.17632/9zgzj8rmjm.1
title: 360 TEACHING EVALUATION DATASET

description: During the 20232 and 20234 semesters, 360° teaching evaluations at Universiti Teknologi MARA revealed clear patterns across the three main assessments: SuFO by students, PROPENS by teaching peers, and TESA by self-assessment of lecturers.
DOI: 10.17632/9zgzj8rmjm.2
title: 360 TEACHING EVALUATION DATASET

description: During the 20232 and 20234 semesters, 360° teaching evaluations at Universiti Teknologi MARA revealed clear patterns across the three main assessments: SuFO by final-year diploma, Foundation and undergraduate students, PROPENS by teaching peers, and TESA by lecturers' self-assessment. The dataset included the score assessment for each teaching evaluation of the individual lecturer and the average score of the faculty or campus. We have also attached a sample of the 360° teaching evaluation instrument, suitable for reference and testing in other higher learning institutions.
DOI: 10.17632/9zgzj8rmjm.3
title: 360-Degree Teaching Evaluation Dataset

description: During the 20232 and 20234 semesters, 360° teaching evaluations at Universiti Teknologi MARA revealed clear patterns across the three main assessments: SuFO by final-year diploma, Foundation and undergraduate students, PROPENS by teaching peers, and TESA by lecturers' self-assessment. The dataset included the score assessment for each teaching evaluation of the individual lecturer and the average score of the faculty or campus. We have also attached a sample of the 360° teaching evaluation instrument, suitable for reference and testing in other higher learning institutions.
DOI: 10.17632/9zgzj8rmjm.4
title: 360-Degree Teaching Evaluation Dataset

description: During the 20232 and 20234 semesters, 360° teaching evaluations at Universiti Teknologi MARA revealed clear patterns across the three main assessments: SuFO by final-year diploma, Foundation and undergraduate students, PROPENS by teaching peers, and TESA by lecturers' self-assessment. The dataset included the score assessment for each teaching evaluation of the individual lecturer and the average score of the faculty or campus. We have also attached a sample of the 360° teaching evaluation instrument, suitable for reference and testing in other higher learning institutions.