cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7182155
title: Synthetic single particle cryo-EM dataset of the SARS-CoV-2 spike protein

description: PDBs were generated using molecular dynamics.
See DESRES_README.txt for more details on molecular dynamics simulation.
PDBs were converted to volumetric data using EMAN2.
The image stack contains 100 000 projection images each 
of the 10 states (see PDBs), at an SNR of 1/10 in the following order:


state00 (closed)
state01 (closed)
state02 (closed)
state10 (intermediate)
state11 (intermediate)
state12 (intermediate)
state13 (intermediate)
state20 (open)
state21 (open)
state22 (open)


Projections were made using relion_project. 
  White gaussian noise with standard deviation 1.0
  CTF multiplied signal
  High signal-to-noise ratio
  Image size 96x96x96
  
MRC-files used for the projections not included, but can be generated using the PDB files.
Final RELION reconstruction resolution is 5.33334 Angstrom (Nyqvist is at 5.33334).


Command line for RELION reconstruction:
relion_refine_mpi --o refine3d/run --auto_refine --split_random_halves --i rot_trans_ctf_noise/stack.star --ref pdb2mrc/state21.mrc --ini_high 20 --dont_combine_weights_via_disc --preread_images --pool 30 --pad 2 --ctf --particle_diameter 130 --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --auto_local_healpix_order 4 --offset_range 5 --offset_step 2 --low_resol_join_halves 40 --norm --scale --j 2 --gpu --fristiter_cc --grad 


This dataset is generated as a testbed for cryo-EM heterogeneity analysis.
DOI: 10.5281/zenodo.7182156
title: Synthetic single particle cryo-EM dataset of the SARS-CoV-2 spike protein

description: PDBs were generated using molecular dynamics.
See DESRES_README.txt for more details on molecular dynamics simulation.
PDBs were converted to volumetric data using EMAN2.
The image stack contains 100 000 projection images each 
of the 10 states (see PDBs), at an SNR of 1/10 in the following order:


state00 (closed)
state01 (closed)
state02 (closed)
state10 (intermediate)
state11 (intermediate)
state12 (intermediate)
state13 (intermediate)
state20 (open)
state21 (open)
state22 (open)


Projections were made using relion_project. 
  White gaussian noise with standard deviation 1.0
  CTF multiplied signal
  High signal-to-noise ratio
  Image size 96x96x96
  
MRC-files used for the projections not included, but can be generated using the PDB files.
Final RELION reconstruction resolution is 5.33334 Angstrom (Nyqvist is at 5.33334).


Command line for RELION reconstruction:
relion_refine_mpi --o refine3d/run --auto_refine --split_random_halves --i rot_trans_ctf_noise/stack.star --ref pdb2mrc/state21.mrc --ini_high 20 --dont_combine_weights_via_disc --preread_images --pool 30 --pad 2 --ctf --particle_diameter 130 --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --auto_local_healpix_order 4 --offset_range 5 --offset_step 2 --low_resol_join_halves 40 --norm --scale --j 2 --gpu --fristiter_cc --grad 


This dataset is generated as a testbed for cryo-EM heterogeneity analysis.
DOI: 10.5281/zenodo.10553452
title: Blush Training Dataset Masks

description: A TAR archive comprising Gzip-compressed MRC files, each containing manually curated binary masks. Part of the training dataset of the inaugural Blush model. Each file is named in accordance with its corresponding EMDB entry ID.
DOI: 10.5281/zenodo.10558275
title: IODP Expedition 390, Hole U1556B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 390: South Atlantic Transect 1
DOI: 10.5281/zenodo.10558276
title: IODP Expedition 390, Hole U1556B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 390: South Atlantic Transect 1
DOI: 10.6073/pasta/ac3e0a79b78b59940d9fcdc94c36e58d
title: Sediment temperature at three depths below sediment surface in intertidal mudflats in Virginia, 2013-2014

description: We logged the sediment temperature at three intertidal mudflat sites between September, 2013 and September, 2014. At each site, three submersible temperature loggers (HOBO Pendant UA-002; Onset Computer Corporation) were buried at 3 cm, 10 cm and 20 cm below the sediment surface. Temperature was recorded in ten minute intervals. Each site was unvegetated with muddy sediment. For sites 1 and 2, data was recorded in two time series. Time series 1 from 09/02/2013 - 12/16/2013 and time series 2 from 12/19/2013 - 09/18/2014. At site 2, 20 cm depth, no data was recorded after 12/16/2013. At site 3, data was recorded at all depths continuously from 09/2/2013 to 08/28/2014. Date and time was recorded as GMT offset by -5 hours (Eastern Standard Time).
DOI: 10.17608/k6.auckland.23734197.v2
title: SurveyOnChineseNewZealanders

description: A survey conducted among ethnic Chinese voters in New Zealand_ 2021
DOI: 10.5281/zenodo.10558479
title: IODP Expedition 393, Hole U1583F - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 393: South Atlantic Transect 2
DOI: 10.5281/zenodo.10558478
title: IODP Expedition 393, Hole U1583F - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 393: South Atlantic Transect 2
DOI: 10.5281/zenodo.10558480
title: IODP Expedition 393, Hole U1560B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 393: South Atlantic Transect 2
DOI: 10.5281/zenodo.10558481
title: IODP Expedition 393, Hole U1560B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: IODP Expedition 393: South Atlantic Transect 2
DOI: 10.7931/nw7q-ph29
title: NZFlora Beever 2024 Pottiaceae subfamily Barbuloideae
DOI: 10.5281/zenodo.10558494
title: Supplementary Materials for "Large language models overcome the challenges of unstructured text data in ecology" - preprint

description: Supplementary Materials for preprint: 

Large language models overcome the challenges of unstructured text data in ecology

Andry Castro1; João Pinto2; Luís Reino3, 4, 5; Pavel Pipek6,7 César Capinha1,8*

 

1Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, Lisboa, Portugal.

2Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.

3CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.

4BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal.

5CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.

6Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic.

7Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic.

8Associated Laboratory Terra, Portugal.

 

*Corresponding author (cesarcapinha@campus.ul.pt)
DOI: 10.5281/zenodo.10558495
title: Supplementary Materials for "Large language models overcome the challenges of unstructured text data in ecology" - preprint

description: Supplementary Materials for preprint: 

Large language models overcome the challenges of unstructured text data in ecology

Andry Castro1; João Pinto2; Luís Reino3, 4, 5; Pavel Pipek6,7 César Capinha1,8*

 

1Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, Lisboa, Portugal.

2Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.

3CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.

4BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal.

5CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal.

6Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic.

7Department of Ecology, Faculty of Science, Charles University, Prague, Czech Republic.

8Associated Laboratory Terra, Portugal.

 

*Corresponding author (cesarcapinha@campus.ul.pt)
DOI: 10.6084/m9.figshare.23802951
title: DataS1_Database_Abundance of Old-growth forest trees in tropical forests.zip

description: Database of old-growth forest seeds, saplings, juveniles and trees in two Mexican rainforests. The database contains .csv files and R Based code to conduct analysis of the the relationship of forest cover and the abundance and species richness of old-growth forest species. There are files for each different life-stage (seeds, saplings, juvenile trees, adult trees) and for each response (abundance, species richness).
DOI: 10.6084/m9.figshare.23802951.v1
title: DataS1_Database_Abundance of Old-growth forest trees in tropical forests.zip

description: Database of old-growth forest seeds, saplings, juveniles and trees in two Mexican rainforests. The database contains .csv files and R Based code to conduct analysis of the the relationship of forest cover and the abundance and species richness of old-growth forest species. There are files for each different life-stage (seeds, saplings, juvenile trees, adult trees) and for each response (abundance, species richness).
DOI: 10.5281/zenodo.10557123
title: Data for "Perturbative Solution of Fermionic Sign Problem in Quantum Monte Carlo Computations"

description: Datasets used to produce figures in the "Perturbative Solution of Fermionic Sign Problem in Quantum Monte Carlo Computations" manuscript.

8x8/U=8.0/G(w).txt contains data for Figs. 2, 3 and 4

8x8/U=8.0/G_dual.txt contains data for Figs. 5 and 6

8x8/U=5.6 directory contains data for Fig. 6

2x2 directory contains data used to generate Fig. 8

4x4 directory contains data for Fig. 9

10x10vs8x8 directory contains data for Fig. 10
DOI: 10.5281/zenodo.10557124
title: Data for "Perturbative Solution of Fermionic Sign Problem in Quantum Monte Carlo Computations"

description: Datasets used to produce figures in the "Perturbative Solution of Fermionic Sign Problem in Quantum Monte Carlo Computations" manuscript.

8x8/U=8.0/G(w).txt contains data for Figs. 2, 3 and 4

8x8/U=8.0/G_dual.txt contains data for Figs. 5 and 6

8x8/U=5.6 directory contains data for Fig. 6

2x2 directory contains data used to generate Fig. 8

4x4 directory contains data for Fig. 9

10x10vs8x8 directory contains data for Fig. 10
DOI: 10.5281/zenodo.10558502
title: SPLASH 10 Meter Eddy Covariance Data for 2021, 2022, and 2023

description: These files contain the 10 meter 30 minute eddy covariance data from the Kettle Ponds site. The data include the fluxes of sensible and latent heat, friction velocity and various turbulence statistics including the unrotated mean wind vectors.
DOI: 10.5281/zenodo.10558503
title: SPLASH 10 Meter Eddy Covariance Data for 2021, 2022, and 2023

description: These files contain the 10 meter 30 minute eddy covariance data from the Kettle Ponds site. The data include the fluxes of sensible and latent heat, friction velocity and various turbulence statistics including the unrotated mean wind vectors.
DOI: 10.6084/m9.figshare.22790615
title: flowsets map .kmz file

description: Flowset maps of the southwestern Laurentide Ice Sheet (available here as a .kml file).
DOI: 10.6084/m9.figshare.22790615.v1
title: flowsets map .kmz file

description: Flowset maps of the southwestern Laurenitde Ice Sheet (available here as a .kml file). Flowsets configuration reflects a highly dynamic system of fast flow caused by multiple reconfigurations in ice sheet drainage.
DOI: 10.5281/zenodo.10462605
title: A Theory of Scientific Programming Efficacy Artifact

description: This data contains the artifact for our paper titled “A Theory of Scientific Programming Efficacy” accepted to ICSE 2024. Our artifact consists of interview questions,  pdf of theory codes (not executable code but data labels),  and anonymized survey results. We are including the artifact in order to further disclose our process of theory construction, by revealing the intermediary steps. While participant confidentiality prevents us from releasing complete transcripts we believe that the codes and memos can be helpful for future replicability of our theory, and can serve as a reference for future researchers conducting grounded theory studies in Computer Science.
DOI: 10.5281/zenodo.10462606
title: A Theory of Scientific Programming Efficacy Artifact

description: This data contains the artifact for our paper titled “A Theory of Scientific Programming Efficacy” accepted to ICSE 2024. Our artifact consists of interview questions,  pdf of theory codes (not executable code but data labels),  and anonymized survey results. We are including the artifact in order to further disclose our process of theory construction, by revealing the intermediary steps. While participant confidentiality prevents us from releasing complete transcripts we believe that the codes and memos can be helpful for future replicability of our theory, and can serve as a reference for future researchers conducting grounded theory studies in Computer Science.
DOI: 10.5281/zenodo.10558321
title: A Theory of Scientific Programming Efficacy Artifact

description: This data contains the artifact for our paper titled “A Theory of Scientific Programming Efficacy” accepted to ICSE 2024. Our artifact consists of interview questions,  pdf of theory codes (not executable code but data labels),  and anonymized survey results. We are including the artifact in order to further disclose our process of theory construction, by revealing the intermediary steps. While participant confidentiality prevents us from releasing complete transcripts we believe that the codes and memos can be helpful for future replicability of our theory, and can serve as a reference for future researchers conducting grounded theory studies in Computer Science.
DOI: 10.6084/m9.figshare.25050527
title: Coping and risk perception in T2D

description: Association between coping styles and risk perception in the COVID-19 pandemic and the change in metabolic parameters in individuals with type 2 diabetes.
DOI: 10.5281/zenodo.10558467
title: Harnessing Deep Learning of Point Clouds for Inverse Control of 3D Shape Morphing

description: This is the training dataset collected from simulation for controlling 3D shape morphing devices
DOI: 10.5281/zenodo.10558468
title: Harnessing Deep Learning of Point Clouds for Inverse Control of 3D Shape Morphing

description: This is the training dataset collected from simulation for controlling 3D shape morphing devices
DOI: 10.7298/2w4q-8j27
title: White Matter Atlas of the Domestic Canine Brain
DOI: 10.34740/kaggle/dsv/7466582
title: Public Opinion Russia Ukraine War (Updated Daily)
DOI: 10.26186/74855
title: Surface Geology of Australia data package 2012 edition

description: The Surface Geology of Australia data package includes:
- Surface Geology of Australia, 1:1M scale (2012 edition) [GeoCat #74619 ]
- Surface Geology of Australia, 1:2.5M scale (2012 edition) [GeoCat #73140 ], and 
- the national Geological Regions dataset [GeoCat #32366 ].
DVD data package of 3 national geological datasets
DOI: 10.5281/zenodo.10558540
title: The effect of testosterone on the gut microbiome

description: Introduction: The microbiota influences metabolism, immunity and even behavior, but the mechanisms by which bacteria affect specific host characteristics remain unknown. One important but understudied mechanism is the role of hormones in gut-brain crosstalk. Although the precise pathways of microbiota-hormonal signaling have not yet been deciphered, specific changes in hormonal levels correlate with the presence of the gut microbiota. The microbiota produces and secretes hormones, responds to host hormones and regulates expression levels of host hormones. An interesting but unstudied area in microbial endocrinology is the interplay between the gut microbiome and sex hormones. The aim of this study is to investigate the effect of testosterone and sex on the mouse gut microbiome.

Methods: We used an in vitro experiment to test the direct effect of testosterone on bacteria in fecal samples collected from male and female mice before and after puberty. Sex specific microbiota and metabolomic differences surrounding puberty, regardless of the testosterone supplementation, were also examined. We then examined the effect of testosterone exposure in vivo, characterizing microbiota and metabolites of both male and female mice.

Results: Sex specific differences were detected in the microbiota and its metabolites of mice post-puberty, but our in vitro experiment revealed that testosterone only affected the microbiota of fecal samples collected before puberty. Testosterone supplementation in vivo affected the gut microbiome and the metabolites in both male and female mice.  

 

Conclusion: Since the change in vitro was only in the prepubertal group, that wasn’t exposed to high testosterone levels before the experiment, we conclude that the shift in the microbiome after puberty is at least partially caused by the higher levels of sex hormones, mainly testosterone.
DOI: 10.5281/zenodo.10558541
title: The effect of testosterone on the gut microbiome

description: Introduction: The microbiota influences metabolism, immunity and even behavior, but the mechanisms by which bacteria affect specific host characteristics remain unknown. One important but understudied mechanism is the role of hormones in gut-brain crosstalk. Although the precise pathways of microbiota-hormonal signaling have not yet been deciphered, specific changes in hormonal levels correlate with the presence of the gut microbiota. The microbiota produces and secretes hormones, responds to host hormones and regulates expression levels of host hormones. An interesting but unstudied area in microbial endocrinology is the interplay between the gut microbiome and sex hormones. The aim of this study is to investigate the effect of testosterone and sex on the mouse gut microbiome.

Methods: We used an in vitro experiment to test the direct effect of testosterone on bacteria in fecal samples collected from male and female mice before and after puberty. Sex specific microbiota and metabolomic differences surrounding puberty, regardless of the testosterone supplementation, were also examined. We then examined the effect of testosterone exposure in vivo, characterizing microbiota and metabolites of both male and female mice.

Results: Sex specific differences were detected in the microbiota and its metabolites of mice post-puberty, but our in vitro experiment revealed that testosterone only affected the microbiota of fecal samples collected before puberty. Testosterone supplementation in vivo affected the gut microbiome and the metabolites in both male and female mice.  

 

Conclusion: Since the change in vitro was only in the prepubertal group, that wasn’t exposed to high testosterone levels before the experiment, we conclude that the shift in the microbiome after puberty is at least partially caused by the higher levels of sex hormones, mainly testosterone.
DOI: 10.58106/0ghq-8793
title: Durvalumab with first-line chemotherapy in previously untreated malignant pleural mesothelioma (DREAM): a multicentre, single-arm, phase 2 trial with a safety run-in

description: 
Dataset includes 54 male and female patients 18 years or over with a histological or cytological diagnosis of malignant pleural mesothelioma (MPM) that was not amendable to curative surgical resection, and with measurable disease as per modified RECIST criteria for assessment of response in malignant pleural mesothelioma. Participants had an ECOG status of 0-1, and brain metastases needed to be controlled in the opinion of the treating clinician. Participants must not have had prior chemotherapy, immunotherapy or other systemic anti-cancer for MPM and not have had prior radiotherapy to disease sites.
•	Baseline patient assessments were blood tests for renal and liver function, haematology, urinalysis, coagulation studies, thyroid function tests, hepatitis B and C serology, and electrocardiography. 
•	Clinical assessments were done at screening, baseline, and then every 3 weeks during study treatment. 
•	Laboratory tests were done every 3 weeks, at the end of treatment, and then every 4 weeks to 90 days from the last dose.
•	Adverse events were recorded from the first dose of study treatment to 90 days following the last dose of study treatment, and were classified and graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 4.03. Survival status was recorded every 3 months after completing study treatment. 
•	Tumour imaging by CT of the chest and upper abdomen was done at baseline and every 6 weeks until week 48, and then every 12 weeks thereafter until disease progression was confirmed. Response and progression were assessed by both mRECIST19 (for malignant pleural mesothelioma) and modified Response Evaluation Criteria in Solid Tumors for immunotherapy (iRECIST) 
•	Archived diagnostic tumour samples were assessed centrally for PDL1 expression
•	Only databased items are available as .csv files. Imaging files are not available.
description: HeSANDA 1.0.0