cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15028245
title: Gradient model simulations

description: For each simulation type there is one .fishexp pickle file which contains per-frame position data across the simulations and one _bouts.pkl file which contains swim bout information for the simulation. Each file contains a pickled (via Python pickle module) dictionary. Keys within this dictionary identify the gradient type. For each gradient type there is a sub-dictionary with keys for each individual simulation that was run (200 each).

The different names are for the following content:



Experiment_fish_model_constant: Simulations using swim kinematics binned from uniform (constant) temperature experiments

Experiment_fish_model_gradient: Simulatins using swim kineamtics binned according to tempeature and previous bout temperautre change from gradient experiments

Fish_model_x: x order Navigation model simulations

3rdorderFish_model_3: Same as Fish_model_3 however contains a full range gradient simulation


For each individual simulation the .fishexp file contains a matrix with n-simulation frames rows (at simulated 100 Hz same as in actual experiments) and 2 columns, the x-coordinate in pixels and the y-coordinate in pixels (resolution is 7 px/mm as in the experiments).

For each simulation the _bouts.pkl file contains a dataframe with the following structure:




State
Original index
Start
Stop
Displacement
Angle change
IBI


The annotated swim mode
The original index of the bout (since bouts close to the arena edge were filtered out)
The start simulation frame of the bout
The end simulationframe of the bout
The displacement of the bout in pixels
The angle change of the bout in radians
The waiting time since the previous bout (interbout interval) in frames


Temperature
Prev Delta T
Delta X
Delta Y
X Position
Y Position
Heading


The temperature at the start of the bout
The temperature change across the previous bout
The movement in the X direction in pixels
The movement in the Y direction in pixels
The x position at the start of the bout
The y position at the start of the bout
The fish heading at the start of the bout
DOI: 10.15468/dl.g6fdjv
title: Occurrence Download

description: A dataset containing 33243 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.69292 77.2635,17.16419 77.2635,17.16419 78.00453,13.69292 78.00453,13.69292 77.2635))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 33243 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012984-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15040287
title: Numerical data for publication "Nonlinear-response theory for lossy superconducting quantum circuits"

description: Numerical data and plotting scripts for Figures in publication "Nonlinear-response theory for lossy superconducting quantum circuits", Phys. Rev. Research
DOI: 10.5281/zenodo.15039647
title: Data for "Behaviour of the order of Tate-Shafarevich groups for the quadratic twists of elliptic curves"

description: This dataset contains data for the article: Andrzej Dąbrowski, Lucjan Szymaszkiewicz, Behavior of the order of Tate-Shafarevich groups for the quadratic twists of elliptic curves.

Description of the files:A.txt - data for the curve y^2 = x^3-x (denoted by A in the article)B.txt - data for the curve y^2 = x^3-1 (denoted by B in the article)C.txt - data for the curve y^2 = x^3+4*x^2-16 (denoted by C in the article)D.txt - data for the curve y^2 = x^3-x^2-8*x-16 (denoted by D in the article)

Each file contains three columns (separated by tabs).

In the first column we find the value d by which we twist the given curve. In the second column the value of the coefficient a(d). In the third the value sqrt(|Sha(E_d)|) if a(d) != 0, otherwise 0.

The files contain all considered d values for d less than a billion.
DOI: 10.5281/zenodo.15039648
title: Data for "Behaviour of the order of Tate-Shafarevich groups for the quadratic twists of elliptic curves"

description: This dataset contains data for the article: Andrzej Dąbrowski, Lucjan Szymaszkiewicz, Behavior of the order of Tate-Shafarevich groups for the quadratic twists of elliptic curves.

Description of the files:A.txt - data for the curve y^2 = x^3-x (denoted by A in the article)B.txt - data for the curve y^2 = x^3-1 (denoted by B in the article)C.txt - data for the curve y^2 = x^3+4*x^2-16 (denoted by C in the article)D.txt - data for the curve y^2 = x^3-x^2-8*x-16 (denoted by D in the article)

Each file contains three columns (separated by tabs).

In the first column we find the value d by which we twist the given curve. In the second column the value of the coefficient a(d). In the third the value sqrt(|Sha(E_d)|) if a(d) != 0, otherwise 0.

The files contain all considered d values for d less than a billion.
DOI: 10.5281/zenodo.15034046
title: Personalized Finance Management

description: Personalized Finance Management System

In today’s digital age, managing personal finances efficiently is crucial yet challenging. This project presents a web-based Personalized Finance Management System that helps users track their income, monitor expenses, set budgets, and receive intelligent financial insights.

The system features a chatbot interface that provides financial advice, automated expense categorization, bill reminders, and personalized budget recommendations based on spending patterns. It simplifies financial management by integrating real-time analytics, visual reports, and smart notifications.

Technologies Used:



Backend: Python (Flask)

Frontend: HTML, CSS, JavaScript, Bootstrap

Database: SQLite

Libraries: Pandas, NumPy, Matplotlib

Security: User authentication with encryption


This project promotes financial awareness, responsible spending habits, and long-term financial stability. The source code and documentation are included for reference.
DOI: 10.5281/zenodo.15034047
title: Personalized Finance Management

description: Personalized Finance Management System

In today’s digital age, managing personal finances efficiently is crucial yet challenging. This project presents a web-based Personalized Finance Management System that helps users track their income, monitor expenses, set budgets, and receive intelligent financial insights.

The system features a chatbot interface that provides financial advice, automated expense categorization, bill reminders, and personalized budget recommendations based on spending patterns. It simplifies financial management by integrating real-time analytics, visual reports, and smart notifications.

Technologies Used:



Backend: Python (Flask)

Frontend: HTML, CSS, JavaScript, Bootstrap

Database: SQLite

Libraries: Pandas, NumPy, Matplotlib

Security: User authentication with encryption


This project promotes financial awareness, responsible spending habits, and long-term financial stability. The source code and documentation are included for reference.
DOI: 10.5281/zenodo.15034168
title: Personalized Finance Management

description: Personalized Finance Management System

In today’s digital age, managing personal finances efficiently is crucial yet challenging. This project presents a web-based Personalized Finance Management System that helps users track their income, monitor expenses, set budgets, and receive intelligent financial insights.

The system features a chatbot interface that provides financial advice, automated expense categorization, bill reminders, and personalized budget recommendations based on spending patterns. It simplifies financial management by integrating real-time analytics, visual reports, and smart notifications.

Technologies Used:



Backend: Python (Flask)

Frontend: HTML, CSS, JavaScript, Bootstrap

Database: SQLite

Libraries: Pandas, NumPy, Matplotlib

Security: User authentication with encryption


This project promotes financial awareness, responsible spending habits, and long-term financial stability. The source code and documentation are included for reference.
DOI: 10.25835/dx0rtmlv
title: Portfolio of Capability Constraint Network

description: The data represent a Portfolio of Capability Constraint Network of a multimaterial shaft from the Collaborative Research Center 1153.
DOI: 10.15468/dl.xyph9j
title: Occurrence Download

description: A dataset containing 1911 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dolichopus rupestris Haliday, 1833",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1911 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012986-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15040278
title: Training, Validation and Test data for "On the accuracy of posterior recovery with neural network emulators"

description: The repo includes the training, test and validation data used in the paper "On the accuracy of posterior recovery with neural network emulators". Note that due to the convention employed by the emulator framework in the paper the test data is the data used for early stopping and the validation data is used to measure the accuracy of the emulator after training. This is the opposite convention to most machine learning literature.

The corresponding code used in the paper is found at: https://github.com/htjb/validating_posteriors.

`_data.txt` corresponds to the ARES parameters used to generate the signals in `_labels.txt`.
DOI: 10.5281/zenodo.15040279
title: Training, Validation and Test data for "On the accuracy of posterior recovery with neural network emulators"

description: The repo includes the training, test and validation data used in the paper "On the accuracy of posterior recovery with neural network emulators". Note that due to the convention employed by the emulator framework in the paper the test data is the data used for early stopping and the validation data is used to measure the accuracy of the emulator after training. This is the opposite convention to most machine learning literature.

The corresponding code used in the paper is found at: https://github.com/htjb/validating_posteriors.

`_data.txt` corresponds to the ARES parameters used to generate the signals in `_labels.txt`.
DOI: 10.25976/1a6b-g984
title: A Comparative Assessment of Ecological Conditions for Atlantic Salmon in the Northern Minas Basin

description: The Comparative Assessment of Ecological Conditions for Atlantic Salmon in the Northern Minas Basin Rivers, colloquially the “Atlantic Salmon Comparative Assessment Project” is a multi-year initiative funded through the aquatic Aboriginal Fund for Species at Risk (AFSAR) by Fisheries and Oceans Canada (DFO), to investigate the survival of the endangered inner Bay of Fundy (iBoF) Atlantic salmon fry in Critical Habitat rivers (Debert, Folly, Great Village, Portapique, and Economy Rivers) in the Cobequid Bay, of the Northern Minas Basin, Nova Scotia.
description: A YSI PRO DSS handheld multiparameter water quality unit© is used to collect the physio-chemical data for all sites. A 2-in-1 flowometer and meter stick helps determine the flow rate, bankfull height, and  cross sectional channel measurements (depths). A retractable measuring tape measures wetted width and bankfull width.
DOI: 10.15468/dl.bt83nt
title: Occurrence Download

description: A dataset containing 2126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-23.43250 29.83777,102.43250 29.83777,102.43250 80.16223,-23.43250 80.16223,-23.43250 29.83777))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dolomedes plantarius (Clerck, 1757)"
 ]
}

 The dataset includes 2126 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012988-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pfc9dp
title: Occurrence Download

description: A dataset containing 5473 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Andira inermis (W.Wright) DC.)"
 ]
}

 The dataset includes 5473 records from 303 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012989-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28608248
title: Paper: Trends in cardiometabolic risk factors according to body mass index in Peru between 2015 and 2023

description: Analytical code and analytical dataset.Paper: <b>Trends in cardiometabolic risk factors according to body mass index in Peru between 2015 and 2023</b>https://www.sciencedirect.com/science/article/pii/S1047279725000559<br>
DOI: 10.15468/dl.cxdrhk
title: Occurrence Download

description: A dataset containing 117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Lepus capensis Linnaeus, 1758"
 ]
}

 The dataset includes 117 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012990-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rfgppk
title: Occurrence Download

description: A dataset containing 827 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipterocarpus grandiflorus (Blanco) Blanco"
 ]
}

 The dataset includes 827 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012992-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15040026
title: Ancestral Lighting: Sequences input and output

description: SEED_BetaBarrel_FPs.fasta: Sequences of fluorescencent proteins (FPs) with desirable features used as a seed to look for a bigger data set.

SEED_BetaBarrel_FP_Maffted.fas: Aligned SEED sequences using MAFFT with the command "mafft --reorder --maxiterate 0 --globalpair input". From this file, a Hidden Markov Model (HMM) can be generated using tools like HMMER (http://hmmer.org/). The HMM can then be used to look for sequences that satisfy it out of an expanded database, like UniREF100. In this casem, the UniRef100 used was version available by August 3rd, 2022 at https://www.uniprot.org/uniref

final_pasted.fas: Sequence Alignment of the best matches to the HMM after filtering by 90% redundancy and minimal sequence length of 200 residues. The filtering was done with CD-HIT (https://bioinformatics.org/cd-hit/).

AC_tree_structure_wASR.txt: Text/Graphic version of the ANCESCON output from the MPI-Toolkit (https://toolkit.tuebingen.mpg.de/tools/ancescon) after using final_pasted.fas as input. The nodes of this tree represent the ancestral proteins.
DOI: 10.5281/zenodo.15040027
title: Ancestral Lighting: Sequences input and output

description: SEED_BetaBarrel_FPs.fasta: Sequences of fluorescencent proteins (FPs) with desirable features used as a seed to look for a bigger data set.

SEED_BetaBarrel_FP_Maffted.fas: Aligned SEED sequences using MAFFT with the command "mafft --reorder --maxiterate 0 --globalpair input". From this file, a Hidden Markov Model (HMM) can be generated using tools like HMMER (http://hmmer.org/). The HMM can then be used to look for sequences that satisfy it out of an expanded database, like UniREF100. In this casem, the UniRef100 used was version available by August 3rd, 2022 at https://www.uniprot.org/uniref

final_pasted.fas: Sequence Alignment of the best matches to the HMM after filtering by 90% redundancy and minimal sequence length of 200 residues. The filtering was done with CD-HIT (https://bioinformatics.org/cd-hit/).

AC_tree_structure_wASR.txt: Text/Graphic version of the ANCESCON output from the MPI-Toolkit (https://toolkit.tuebingen.mpg.de/tools/ancescon) after using final_pasted.fas as input. The nodes of this tree represent the ancestral proteins.
DOI: 10.15468/dl.ede8vz
title: Occurrence Download

description: A dataset containing 54 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dolichomiris linearis Reuter, 1882",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 54 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012993-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8edt8z
title: Occurrence Download

description: A dataset containing 827 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipterocarpus grandiflorus (Blanco) Blanco"
 ]
}

 The dataset includes 827 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012994-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15040439
title: AuroraFlow Evaluation Data

description: Evaluation data and artefacts for the publication "AuroraFlow, an Easy-to-Use, Low-Latency FPGA Communication Solution Demonstrated on Multi-FPGA Neural Network Inference" by Gerrit Pape, Bjarne Wintermann, Linus Jungemann, Michael Laß, Marius Meyer, Heinrich Riebler and Christian Plessl.
DOI: 10.5281/zenodo.15040440
title: AuroraFlow Evaluation Data

description: Evaluation data and artefacts for the publication "AuroraFlow, an Easy-to-Use, Low-Latency FPGA Communication Solution Demonstrated on Multi-FPGA Neural Network Inference" by Gerrit Pape, Bjarne Wintermann, Linus Jungemann, Michael Laß, Marius Meyer, Heinrich Riebler and Christian Plessl.
DOI: 10.15468/dl.sut6pz
title: Occurrence Download

description: A dataset containing 827 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipterocarpus grandiflorus (Blanco) Blanco"
 ]
}

 The dataset includes 827 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012996-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rt7ggk
title: Occurrence Download

description: A dataset containing 299 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is one of (United States of America, United States Minor Outlying Islands, American Samoa, Micronesia (Federated States of), Guam, Marshall Islands, Northern Mariana Islands, Puerto Rico, Palau, Virgin Islands (U.S.))",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Cambarus girardianus Faxon, 1884)"
 ]
}

 The dataset includes 299 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012997-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.49nk26
title: Occurrence Download

description: A dataset containing 365 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "DatasetKey is one of (Observations Regelink Ecology and Landscape, iNaturalist Research-grade Observations, Natural History Museum Rotterdam - Specimens, NABU|naturgucker, Naturalis Biodiversity Center (NL) - Mammalia, Mammal records for Europe via the iMammalia app, MICA - Muskrat and coypu camera trap observations in Belgium, the Netherlands and Germany)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Meles meles (Linnaeus, 1758)",
 "Year 1990-2025"
 ]
}

 The dataset includes 365 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012999-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wcbeez
title: Occurrence Download

description: A dataset containing 8169589 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is UK Butterfly Monitoring Scheme (UKBMS)"
 ]
}

 The dataset includes 8169589 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012991-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wsxsnw
title: Occurrence Download

description: A dataset containing 317 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ectopsocus pumilis (Banks, 1920)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 317 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013001-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21954/ou.rd.28582448
title: Supporting data for Education Doctorate thesis: 'Exploring customisation of blended learning for multinational diving instructors: a longitudinal case study'

description: Supporting data for the Education Doctorate thesis published via ORO in February 2025, available at https://oro.open.ac.uk/103060/Thesis title: Exploring customisation of blended learning for multinational diving instructors: a longitudinal case studyThis thesis explores in what ways globalised blended learning for diving instructors is locally customised, which multinational learner characteristics this customisation accommodates and how training outcomes may be affected.The README file contains a description of each file contained within this dataset.
DOI: 10.15468/dl.r83a6w
title: Occurrence Download

description: A dataset containing 9926 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rapateaceae"
 ]
}

 The dataset includes 9926 records from 232 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013005-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4su3zp
title: Occurrence Download

description: A dataset containing 9926 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rapateaceae"
 ]
}

 The dataset includes 9926 records from 232 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013004-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11339509
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.25549/whit-c170-78552
title: Edward selling "Times", Southern California, 1935

description: 12 photographs of Edward selling "Times", Southern California, 1935. "Subject: Edward selling 'Times'; Agency: Dana Jones; Client: L[os] A[ngeles] Times; Size: proofs, 10x14; Re-order: 1#1, 1#2, 1#1,2; 6 inches tall as shown in sample; paper to size as above; Size: 4x5, 4 1/8 in length; Finish: gl[ossy] to size; Job: 56-20-114; Year: 1935" -- on envelope front. "1 Original Photographs--At Studio: 8x10; Amount: 20.00" -- on envelope back.