cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22002/16072-7wx72
title: Agrobacterium tumefaciens

description: C58 wild type
description: <strong>Tilt Series Date:</strong> 2013-08-01</p>
<strong>Data Taken By:</strong> Elitza Tocheva</p>
<strong>Species / Specimen:</strong> Agrobacterium tumefaciens</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.0°, constant angular increment, dosage: 180.0 eV/Å²,  defocus: -10.0 μm,  magnification: 19500x. </p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Pat Zambryski</p>
<strong>Purification / Growth Conditions / Treatment:</strong> 300uM AS inductant</p>
<strong>Sample Preparation:</strong> Janelia</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/etl2013-08-01-32/rawdata/</p>c58_Au_300mM0013.mrc,  Tilt Series (Pixel Size 0.56 nm), 3.3 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/etl2013-08-01-32/rawdata/c58_Au_300mM0013.mrc"
        > <i class="download icon"></i> Download </a></p>

        c58_Au_300mM0013_full.rec,  Reconstruction (Pixel Size 2.24 nm), 688.9 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/etl2013-08-01-32/3dimage_29494/c58_Au_300mM0013_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/1nnbq-7t927
title: magnetosome induced t0.5

description: Raw data files of magnetosome induced t0.5
description: <strong>Tilt Series Date:</strong> 2014-06-19</p>
<strong>Data Taken By:</strong> Poorna Subramanian</p>
<strong>Species / Specimen:</strong> Magnetospirillum magneticum </p>
<strong>Strain:</strong> deltaQ 167</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 100.0 eV/Å²,  defocus: -15.0 μm,  magnification: 18000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
  psa2014-06-19-36_slicer9606.jpg: magnetospirillum magneticum .  parallel filaments
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2014-06-19-36/rawdata/</p>atlas70011.mrc,  Tilt Series (Pixel Size 0.6 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2014-06-19-36/rawdata/atlas70011.mrc"
        > <i class="download icon"></i> Download </a></p>

        atlas70011_full.rec,  Reconstruction (Pixel Size 2.4 nm), 445.4 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2014-06-19-36/3dimage_43818/atlas70011_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.17632/v8wck7hhnr
title: Replication Package for: Investor Learning about Monetary-Policy Transmission and the Stock Market

description: This replication package contains the data, code, and instructions to reproduce all results in the paper "Investor Learning about Monetary-Policy Transmission and the Stock Market" by Daniel Andrei and Michael Hasler, forthcoming in the Journal of Financial Economics.

Paper Abstract: We model how investor learning about monetary-policy transmission impacts asset prices. In an asset-pricing model, investors learn from realized inflation surprises how effectively monetary policy steers future inflation. Downward revisions in perceived effectiveness raise expected inflation persistence, increasing return volatility and risk premia. These effects intensify when policy deviates significantly from neutral or monetary-transmission uncertainty is high. We estimate the model using U.S. macro and policy data from 1954 to 2023. The resulting dynamics align with observed patterns in equity returns and volatility. Empirical tests support the model's core prediction: investor learning turns central-bank credibility into a priced risk factor.

This package contains all the data and code necessary to reproduce the figures and tables in the paper and its internet appendix. The data include U.S. macroeconomic time series (real GDP, CPI, Federal funds rate, output gap) from 1954 to 2023, sourced from FRED and NIPA, as well as financial market data. The code includes a Mathematica notebook for solving the theoretical model and other Matlab scripts for the maximum likelihood estimation and all empirical tests. A README file is included with detailed, step-by-step instructions for replication.
DOI: 10.17632/v8wck7hhnr.3
title: Replication Package for: Investor Learning about Monetary-Policy Transmission and the Stock Market

description: This replication package contains the data, code, and instructions to reproduce all results in the paper "Investor Learning about Monetary-Policy Transmission and the Stock Market" by Daniel Andrei and Michael Hasler, forthcoming in the Journal of Financial Economics.

Paper Abstract: We model how investor learning about monetary-policy transmission impacts asset prices. In an asset-pricing model, investors learn from realized inflation surprises how effectively monetary policy steers future inflation. Downward revisions in perceived effectiveness raise expected inflation persistence, increasing return volatility and risk premia. These effects intensify when policy deviates significantly from neutral or monetary-transmission uncertainty is high. We estimate the model using U.S. macro and policy data from 1954 to 2023. The resulting dynamics align with observed patterns in equity returns and volatility. Empirical tests support the model's core prediction: investor learning turns central-bank credibility into a priced risk factor.

This package contains all the data and code necessary to reproduce the figures and tables in the paper and its internet appendix. The data include U.S. macroeconomic time series (real GDP, CPI, Federal funds rate, output gap) from 1954 to 2023, sourced from FRED and NIPA, as well as financial market data. The code includes a Mathematica notebook for solving the theoretical model and other Matlab scripts for the maximum likelihood estimation and all empirical tests. A README file is included with detailed, step-by-step instructions for replication.
DOI: 10.22002/trtm6-rwv94
title: lysed E.coli minicells M259Q

description: lysed E.coli minicells M259Qtotal dose of tilt series too low
description: <strong>Tilt Series Date:</strong> 2013-03-22</p>
<strong>Data Taken By:</strong> Ariane Briegel</p>
<strong>Species / Specimen:</strong> Escherichia coli</p>
<strong>Strain:</strong> RP 437</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 160.0 eV/Å²,  defocus: -8.0 μm,  magnification: 19500x. </p>
<strong>Acquisition Software:</strong> FEIbatchtomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> John S. Parkinson</p>
<strong>Purification / Growth Conditions / Treatment:</strong> succrose gradients for isolation, Lysis with Lysozyme</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2013-03-22-13/rawdata/</p>new13.st,  Tilt Series (Pixel Size 0.4171 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2013-03-22-13/rawdata/new13.st"
        > <i class="download icon"></i> Download </a></p>

        new13_full.rec,  Reconstruction (Pixel Size 0.8342 nm), 2.8 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2013-03-22-13/3dimage_26014/new13_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/zm6tr-qrv05
title: 5ug chloramphenicol

description: There may be bacteriophage contamination
description: <strong>Tilt Series Date:</strong> 2013-11-29</p>
<strong>Data Taken By:</strong> Poorna Subramanian</p>
<strong>Species / Specimen:</strong> Caulobacter crescentus</p>
<strong>Strain:</strong> NA1000</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 160.0 eV/Å²,  defocus: -10.0 μm,  magnification: 22500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
  psa2013-11-29-10_slicer5504.jpg: Budding vesicle and granule psa2013-11-29-10_slicer5508.jpg: Vesicle
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2013-11-29-10/rawdata/</p>atlas20010.mrc,  Tilt Series (Pixel Size 0.48 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2013-11-29-10/rawdata/atlas20010.mrc"
        > <i class="download icon"></i> Download </a></p>

        atlas20010_part121_3.rec,  Reconstruction (Pixel Size 1.92 nm), 445.4 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2013-11-29-10/3dimage_35234/atlas20010_part121_3.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.17632/zfrs99j8z6
title: Early Detection of Infant Common Illnesses (0–3 Years): Symptom-Based Dataset from Bangladesh

description: The data consists of 2,553 responses obtained through a survey from the parents and primary caregivers of the children under the age of three in Bangladesh. It provides detailed demographic information (like age and gender), symptom reports (including respiratory problems, diarrhea, fever, skin rashes, and ear infections), the concerns of caregivers and final names of illnesses. The survey was also designed to capture early markers of frequent infant illnesses, and to reflect observations made in real-world care.

The dataset aims to advance studies on early detection, monitoring and management of common childhood illness. It is a base for public health research, pediatric health studies and decision support systems both for parents and HCP. Moreover, it can be applied to machine learning purposes, such as symptom-based illness prediction and pattern analysis for the pediatric health records. Based on the provision of trustworthy and well-organized information, this dataset hopes to help in the timely diagnosis, intervention, and care of children outcomes in Bangladesh.
Keywords: Infant health; childhood illnesses; symptom dataset; healthcare dataset; machine learning; ARI; diarrhea; fever; Bangladesh
DOI: 10.17632/zfrs99j8z6.2
title: Early Detection of Infant Common Illnesses (0–3 Years): Symptom-Based Dataset from Bangladesh

description: The data consists of 2,553 responses obtained through a survey from the parents and primary caregivers of the children under the age of three in Bangladesh. It provides detailed demographic information (like age and gender), symptom reports (including respiratory problems, diarrhea, fever, skin rashes, and ear infections), the concerns of caregivers and final names of illnesses. The survey was also designed to capture early markers of frequent infant illnesses, and to reflect observations made in real-world care.

The dataset aims to advance studies on early detection, monitoring and management of common childhood illness. It is a base for public health research, pediatric health studies and decision support systems both for parents and HCP. Moreover, it can be applied to machine learning purposes, such as symptom-based illness prediction and pattern analysis for the pediatric health records. Based on the provision of trustworthy and well-organized information, this dataset hopes to help in the timely diagnosis, intervention, and care of children outcomes in Bangladesh.
Keywords: Infant health; childhood illnesses; symptom dataset; healthcare dataset; machine learning; ARI; diarrhea; fever; Bangladesh
DOI: 10.22002/ddtxt-a0210
title: Vesicle CF4Q 4111V

description: Sample Vesicle CF4Q 4111V
description: <strong>Tilt Series Date:</strong> 2014-12-10</p>
<strong>Data Taken By:</strong> Ariane Briegel</p>
<strong>Species / Specimen:</strong> Escherichia coli in vitro</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 160.0 eV/Å²,  defocus: -10.0 μm,  magnification: 34000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Lynmarie Thompson</p>
<strong>Sample Preparation:</strong> samples were frozen on 11/07/14</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-12-10-10/rawdata/</p>Vesicle411VNEW0010.mrc,  Tilt Series (Pixel Size 0.32 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-12-10-10/rawdata/Vesicle411VNEW0010.mrc"
        > <i class="download icon"></i> Download </a></p>

        Vesicle411VNEW0010_full.rec,  Reconstruction (Pixel Size 1.28 nm), 712.7 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-12-10-10/3dimage_48706/Vesicle411VNEW0010_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.17632/pp73w2g349.2
title: Geochemical results of the studied authigenic carbonates at seeps

description: The supplementary material is a Table including the site information and geochemical results of the studied authigenic carbonates at seeps.
DOI: 10.22002/gr5zw-0by28
title: Vibrio LB + Ca-HEPES

description: Vibrio cholerae, 37°C, LB + Ca-HEPES
description: <strong>Tilt Series Date:</strong> 2014-01-03</p>
<strong>Data Taken By:</strong> Ariane Briegel</p>
<strong>Species / Specimen:</strong> Vibrio cholerae</p>
<strong>Strain:</strong> TRH7000</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 160.0 eV/Å²,  defocus: -10.0 μm,  magnification: 34000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Purification / Growth Conditions / Treatment:</strong> MKW1383 grown overnight in LB + Ca-HEPES at 37°C</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-01-03-10/rawdata/</p>VibrioBdellomediumJan0010.mrc,  Tilt Series (Pixel Size 0.32 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-01-03-10/rawdata/VibrioBdellomediumJan0010.mrc"
        > <i class="download icon"></i> Download </a></p>

        VibrioBdellomediumJan0010_part121_50.rec,  Reconstruction (Pixel Size 1.28 nm), 445.4 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/aba2014-01-03-10/3dimage_37459/VibrioBdellomediumJan0010_part121_50.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.15468/dl.asfjka
title: Occurrence Download

description: A dataset containing 2489 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cephalopterus glabricollis"
 ]
}

 The dataset includes 2489 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047189-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/3fcpn5zp8r
title: Pistachio leaf waste transformed into a gut-targeted bioactive phytocomplex

description: This dataset supports the study "Pistachio leaf waste transformed into a gut-targeted bioactive phytocomplex" published in iScience Journal (https://doi.org/10.1016/j.isci.2025.113345). 

The human gut microbiota is integral to host physiology, influencing immune responses, metabolic regulation, and digestion. Disruptions in this microbial community are linked to inflammatory and metabolic disorders. In this study, we explored the potential of Pistachio Leaf Extract (PLE), a polyphenol-rich natural product, to support gut health. The extract, obtained from Pistacia vera leaves harvested in Sicily, was chemically characterized and assessed for prebiotic-like, antimicrobial, antioxidant, and anti-inflammatory effects. It promoted the growth of beneficial gut bacteria, inhibited pathogenic strains, and exhibited marked antioxidant activity. In patient-derived intestinal organoids, the extract reduced inflammation and enhanced antioxidant defenses, with no detectable cytotoxicity in human colon cells. These results suggested that PLE is a safe and multifunctional compound that may contribute to intestinal homeostasis, offering promise for its inclusion in future functional food formulations aimed at promoting gastrointestinal health.
DOI: 10.17632/3fcpn5zp8r.1
title: Pistachio leaf waste transformed into a gut-targeted bioactive phytocomplex

description: This dataset supports the study "Pistachio leaf waste transformed into a gut-targeted bioactive phytocomplex" published in iScience Journal (https://doi.org/10.1016/j.isci.2025.113345). 

The human gut microbiota is integral to host physiology, influencing immune responses, metabolic regulation, and digestion. Disruptions in this microbial community are linked to inflammatory and metabolic disorders. In this study, we explored the potential of Pistachio Leaf Extract (PLE), a polyphenol-rich natural product, to support gut health. The extract, obtained from Pistacia vera leaves harvested in Sicily, was chemically characterized and assessed for prebiotic-like, antimicrobial, antioxidant, and anti-inflammatory effects. It promoted the growth of beneficial gut bacteria, inhibited pathogenic strains, and exhibited marked antioxidant activity. In patient-derived intestinal organoids, the extract reduced inflammation and enhanced antioxidant defenses, with no detectable cytotoxicity in human colon cells. These results suggested that PLE is a safe and multifunctional compound that may contribute to intestinal homeostasis, offering promise for its inclusion in future functional food formulations aimed at promoting gastrointestinal health.
DOI: 10.22002/2jzgd-k8d44
title: HUVECs 24h PI pNLBglI

description: Whole cells were grown on Au finder grids and infected with pNLGFPBglI. Sample frozen 24h post infection
description: <strong>Tilt Series Date:</strong> 2013-05-11</p>
<strong>Data Taken By:</strong> Cora Woodward</p>
<strong>Species / Specimen:</strong> HUVECs</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.0°, constant angular increment, dosage: 150.0 eV/Å²,  defocus: -6.0 μm,  magnification: 19000x. </p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Whole cells were grown on Au finder grids and infected with pNLGFPBglI. Sample frozen 24h post infection</p>
<strong>Sample Preparation:</strong> manual blotting</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/cwl2013-05-11-5/rawdata/</p>C161-4ATC0005.mrc,  Tilt Series (Pixel Size 0.6 nm), 3.3 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/cwl2013-05-11-5/rawdata/C161-4ATC0005.mrc"
        > <i class="download icon"></i> Download </a></p>

        C161-4ATC0005_full.rec,  Reconstruction (Pixel Size 2.4 nm), 516.7 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/cwl2013-05-11-5/3dimage_26751/C161-4ATC0005_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.17632/b9nm452g7h
title: Model & data for CDN article: Designing culturally acceptable, nutritious and low environmental impact Finnish diets with mycoprotein: a novel optimization approach

description: The model is designed for optimizing populational level diets with novel meat alternatives. Specifically, the model minimizes the weighted distance from the current diet (objective function), with meat alternative introduced as a new food within the meat group. We provide the R scripts and datasets to illustrate the operation of the model, the example results show the optimized Finnish diet with mycoprotein. You can easily adapt the model for your own research.

The R scripts for two models with different objective functional forms (quadratic & piecewise-linear) and scenarios: 
1. "CDN_female_QPsd_NUTR_GHGE" R scirpt: quadratic form of objective function, can simulate for an average female of: 
 (1) Nutritionally adequate diet (“NUTR” diet) – results stored in “RESULT1_female_QP_NUTR_myco.xlsx”
 (2) NUTR+GHGE-% diet (% of GHGE reduced diet, with meat fixed at NUTR diet) - results stored in “RESULT2_female_QP_NUTR+GHGE_myco.xlsx”

2. "CDN_male_LPsd_NUTR_loop_GHGE" R script: piecewise-linear form of objective function, can simulate for an average male of: 
 (1) Nutritionally adequate diet (“NUTR” diet) – results stored in “RESULT1_male_LP_NUTR_myco.xlsx”
 (2) NUTR + [1-50%] stepwise GHGE reduced diets (with meat fixed at NUTR scenario) – results stored in “RESULT2_male_LP_NUTR+GHGEloop_myco.xlsx”

Three excel datasets are provided to run the model (the same data used in the article): 
1. “INPUT_female_all_data_R_2025” for the first R script
2. “INPUT_male_all_data_R_2025” for the second R script
3. “INPUT_mycoprotein_data_R_2025” for both R scripts

The results generated in excel sheet includes: average intake (by food category and food group), cost of diets (by food category), GHGE of diets (by food category), nutrient intake of diets.

citation to the original article is recommended.