cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8194044
title: Supplementary material/Organic carbon dynamics in clay soils: impact of management practices on microorganism structure and abundance under semi-arid conditions

description: Proper management of soil organic matter in arid and semi-arid regions improves organic carbon storage in the soil, helps in compact soil degradation, and mitigates climate change impacts, and preserves ecosystem functionality and sustainability food security. This study aims to provide a better insight into the biogeochemical processes that drive the organic carbon dynamics of saline clay soil in a semi-arid climate. The study is not intended to be exhaustive but contributes to analyzing the relationship between bacterial microflora, physicochemical properties, and organic carbon dynamics as a function of different soil management modes. The monitoring was carried out on three different plots located at the National Institute of Agronomic Research of Algeria. A physicochemical characterization of the soils was performed. A metagenomic study was also conducted to identify bacterial biodiversity using PCR-amplified DNA sequencing. The study results show that the control plot has the highest average organic carbon stock value at 47 Mg ha<sup>-1</sup>. This was followed by the amended plot and the conventional plot, respectively, with 43 Mg ha<sup>-1</sup> and 38 Mg ha<sup>-1</sup>. In the context of this study, organic carbon dynamics would appear to depend on the interaction of several biotic and abiotic factors. Soil management methods would impact the density and diversity of bacterial microflora. This, in turn, affects the soil's physicochemical properties and, more specifically, organic carbon dynamics and storage.
DOI: 10.5281/zenodo.8188007
title: Supporting data for: Quantitative visualization of two-phase flow in a fractured porous medium, Water Resources Research

description: This dataset includes experimental images and data processing scripts used to generate the results detailed in the paper titled: Quantitative visualization of two-phase flow in a fractured porous medium and submitted to Water Resources Research.
DOI: 10.5281/zenodo.8188006
title: Supporting data for: Quantitative visualization of two-phase flow in a fractured porous medium, Water Resources Research

description: This dataset includes experimental images and data processing scripts used to generate the results detailed in the paper titled: Quantitative visualization of two-phase flow in a fractured porous medium and submitted to Water Resources Research.
DOI: 10.5281/zenodo.8194050
title: E3SMv2 source codes

description: This archive contains the E3SMv2 source codes and use license for the manuscript submitted to GMD journal.
DOI: 10.5281/zenodo.8194049
title: E3SMv2 source codes

description: This archive contains the E3SMv2 source codes and use license for the manuscript submitted to GMD journal.
DOI: 10.5281/zenodo.8192801
title: LAC-IPC Study Data

description: This repository contains the data sets relevant to a study of LIDAR-assisted feedforward wind turbine pitch control.
DOI: 10.5281/zenodo.8192800
title: LAC-IPC Study Data

description: This repository contains the data sets relevant to a study of LIDAR-assisted feedforward wind turbine pitch control.
DOI: 10.6084/m9.figshare.23802882
title: Relative energies of increasingly large [n]helicenes by means of high-level quantum chemical methods Item

description: A Database of relative energies for [<i>n</i>]helicenes calculated at the CCSD(T) level via the G4(MP2) thermochemical protocol. This work is published in: A. Karton. Relative energies of increasingly large [<i>n</i>]helicenes by means of high-level quantum chemical methods. <i>Molecular Physics</i>, <i>in press</i> (2023). https://doi.org/10.1080/00268976.2023.2241927<br>
DOI: 10.6084/m9.figshare.23802882.v1
title: Relative energies of increasingly large [n]helicenes by means of high-level quantum chemical methods Item

description: A Database of relative energies for [<i>n</i>]helicenes calculated at the CCSD(T) level via the G4(MP2) thermochemical protocol. This work is published in: A. Karton. Relative energies of increasingly large [<i>n</i>]helicenes by means of high-level quantum chemical methods. <i>Molecular Physics</i>, <i>in press</i> (2023). https://doi.org/10.1080/00268976.2023.2241927<br>
DOI: 10.5281/zenodo.7566416
title: ULtrahigh TEmperature Refractory Alloys (ULTERA) Database of High Entropy Alloys

description: ULTERA database, developed under the ARPA-E's ULTIMATE program, is aimed at collecting literature data on high entropy alloys (HEAs) to facilitate rapid discovery of new ones using forward and inverse design, with the primary focus on creep behavior, yield stress, ductility, and hardness. As of July 2022, ULTERA contains over 6,200 property-datapoints, corresponding to 2,485 unique HEAs, collected from 455 source DOIs. All data is available through a high-performance API, following FAIR principles, while statistics on it can be found at our phaseslab.com/ultera web page. The database architecture is designed to automatically integrate starting literature data in real-time with methods such as experiments, generative modeling, predictive modeling, and validations.
DOI: 10.5281/zenodo.8194051
title: ULtrahigh TEmperature Refractory Alloys (ULTERA) Database of High Entropy Alloys

description: ULTERA database, developed under the ARPA-E's ULTIMATE program, is aimed at collecting literature data on high entropy alloys (HEAs) to facilitate rapid ML-based discovery of new ones using forward and inverse design. The main scope of this dataset is collecting data on compositionally complex alloys (CCAs), also known as high entropy alloys (HEAs) and multi-principle-element alloys (MPEAs), with extra attention given to (1) high-temperature (refractory) mechanical data, (2) phases present under different processing conditions. Although low-entropy alloys (incl. binaries) are typically not presented to the end-user (or counted in statistics), some are present and used in ML efforts; thus, all high-quality alloy data contributions are welcome! You can set up a contribution in as little as few minutes with this contribution repository at contribute.ultera.org As of July 2023, ULTERA contains over: 6,830 property-datapoints, corresponding to 2,850 unique HEAs, collected from 536 unique DOIs. All data is available through a high-performance API, following FAIR principles, while statistics on it can be found at our ultera.org project web page. The database architecture is designed to automatically integrate starting literature data in real time with methods such as experiments, generative modeling, predictive modeling, and validations. Beyond large size, ULTERA has further advantage of being highly curated with many steps of data validation and then processed through our abnormal data detection tools (pyqalloy.ultera.org).
DOI: 10.3886/e113035v1-140484
title: Replication data for: The Agricultural Origins of Time Preference

description: This research explores the origins of observed differences in time preference across countries and regions. Exploiting a natural experiment associated with the expansion of suitable crops for cultivation in the course of the Columbian Exchange, the research establishes that pre-industrial agro-climatic characteristics which were conducive to higher return to agricultural investment triggered selection, adaptation, and learning processes that generated a persistent positive effect on the prevalence of long-term orientation in the contemporary era. Furthermore, the research establishes that these agro-climatic characteristics have had a culturally embodied impact on economic behavior such as technological adoption, education, saving, and smoking.
description: Multiple samples.
description: See paper for sources and processing
DOI: 10.5281/zenodo.8191032
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191031
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191048
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191047
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191052
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191051
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191055
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.
DOI: 10.5281/zenodo.8191054
title: Genomic atlas of the human proteome from brain, CSF and plasma: Improvement with TOPMed imputed genomics

description: Abstract Comprehensive expression quantitative trait loci (eQTL) studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated GWAS loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein QTL (pQTL) in neurologically relevant tissues. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high-quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in CSF, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 pQTL in brain, 30 pQTL in CSF, and 22 pQTL in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These pQTL findings are assessable through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer (ONTIME) for use by the scientific community.
description: We thank all the participants and their families from Knight ADRC and DIAN studies. This work was supported by grants from the National Institutes of Health (RF1AG074007 (YJS), R01AG044546 (CC), P01AG003991 (CC), RF1AG053303 (CC), RF1AG058501 (CC), and U01AG058922 (CC), and the Chan Zuckerberg Initiative (CZI). This work was supported by access to equipment made possible by the Hope Center for Neurological Disorders, the Neurogenomics and Informatics Center (NGI: https://neurogenomics.wustl.edu/) and the Departments of Neurology and Psychiatry at Washington University School of Medicine.