cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25442/hku.26212658
title: Supporting data for the thesis "Oxidative distress and dipeptidyl peptidase-4 inhibitors mediated Nrf2 redox modulation in murine periodontitis"

description: This supporting data includes schematic diagram, western blotting, flowchart, qRT-PCR, immunofluorescence, alizarin red S staining, Flow cytometric analysis, TRAP staining, H&E staining, GO analysis, micro-CT analysis, SEM images, TEM images and immunohistochemistry staining. Additionally, it presents a comprehensive analysis of the RNA sequencing data obtained from the murine experiments. It details the experimental design, methods used for RNA extraction, sequencing protocols, and data preprocessing steps. The analysis encompasses the identification of differentially expressed genes (DEGs) and their functional annotation. Key signaling pathways and gene networks implicated in periodontitis and its modulation by DPP4 inhibitors are elucidated. Additionally, the study explores the impact of diabetic conditions on gene expression profiles and investigates the role of oxidative stress and inflammation in periodontal tissue.
DOI: 10.25442/hku.26212658.v1
title: Supporting data for the thesis "Oxidative distress and dipeptidyl peptidase-4 inhibitors mediated Nrf2 redox modulation in murine periodontitis"

description: This supporting data includes schematic diagram, western blotting, flowchart, qRT-PCR, immunofluorescence, alizarin red S staining, Flow cytometric analysis, TRAP staining, H&E staining, GO analysis, micro-CT analysis, SEM images, TEM images and immunohistochemistry staining. Additionally, it presents a comprehensive analysis of the RNA sequencing data obtained from the murine experiments. It details the experimental design, methods used for RNA extraction, sequencing protocols, and data preprocessing steps. The analysis encompasses the identification of differentially expressed genes (DEGs) and their functional annotation. Key signaling pathways and gene networks implicated in periodontitis and its modulation by DPP4 inhibitors are elucidated. Additionally, the study explores the impact of diabetic conditions on gene expression profiles and investigates the role of oxidative stress and inflammation in periodontal tissue.
DOI: 10.15468/dl.dt2qym
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.582853 -33.141788, 148.587344 -33.141788, 148.587344 -33.139542, 148.582853 -33.139542, 148.582853 -33.141788)), ((148.582853 -33.141788, 148.580607 -33.141788, 148.580607 -33.144034, 148.582853 -33.144034, 148.582853 -33.141788)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057377-240626123714530/datasets/export for details.
DOI: 10.15468/dl.xgmca9
title: Occurrence Download

description: A dataset containing 68648 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Amazona aestiva (Linnaeus, 1758)"
 ]
}

 The dataset includes 68648 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057376-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jddj3t
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.438502 -33.139542, 149.438502 -33.141788, 149.440748 -33.141788, 149.440748 -33.139542, 149.438502 -33.139542)), ((149.440748 -33.141788, 149.440748 -33.144034, 149.442994 -33.144034, 149.442994 -33.141788, 149.440748 -33.141788)), ((149.440748 -33.144034, 149.438502 -33.144034, 149.438502 -33.148525, 149.440748 -33.148525, 149.440748 -33.144034)), ((149.440748 -33.148525, 149.440748 -33.150771, 149.449731 -33.150771, 149.449731 -33.148525, 149.454223 -33.148525, 149.454223 -33.144034, 149.447485 -33.144034, 149.447485 -33.148525, 149.440748 -33.148525)))"
 ]
}

 The dataset includes 99 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057378-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25442/hku.26362774
title: Supporting data for "Development of Downfolded Configuration Interaction algorithm for molecular electronic structure calculation and computation chemistry application"

description: <pre>Accurately calculating the electronic structure of strongly correlated molecular systems, such as transition metal complexes, actinides, lanthanides, and extended $\pi$-conjugated organic molecules, is a significant challenge in<br>
the field of quantum chemistry. In these systems, strong electron correlations are crucial, and their accurate description is essential for predicting and understanding the properties and reactivity, which includes but is not limited to bond breaking, charge transfer, and excited states.
<br>
Traditional methods often have difficulties in accurately capturing the intricate electron correlations in these<br>
systems, which limits their capacity to produce reliable results. Furthermore, the scaling of high-level methods has significant limitations on their practical use when the system correlation size becomes large, making them computationally prohibitive. As a result, there is a need to develop efficient approximate techniques that can maintain high accuracy while reducing computational cost.<br>
<br>
In an exact diagonalization of benzene in the cc-pVDZ basis, the Hilbert space contains over $10^{45}$ determinants. However, the molecular Hamiltonian in real systems is very sparse, with the vast majority of matrix elements being negligible. This sparsity can be exploited to reduce the effective dimension dramatically.
<br>
This dataset presents the development and application of the Downfolded Configuration Interaction (dCI) algorithm for accurate and efficient calculations of molecules with strong correlations. The dCI, as a branch of the selected CI method, constructs a compact, effective Hamiltonian through an iterative process that captures the essential electron correlations. This is accomplished by carefully selecting significant configurations and applying a local treatment to the model subspace. Building upon the dCI algorithm, the extended-dCI (ext-dCI) method has been developed to further increase the applicability to larger molecular systems by approximating effective Hamiltonian expansion truncation.
<br>
Detailed benchmarks demonstrate the accuracy and efficiency of ext-dCI in calculating challenging systems such as benzene and chromium dimer. Utilizing the sparsity and locality of the electronic structure, the dCI and ext-dCI methods provide an in-depth description of both static and dynamic electron correlation effects. The dCI approach opens new possibilities for studying complex chemical phenomena governed by strong electron correlations.<br>
<br>
Some computational works on supramolecular and $\pi$-carbon chemistry during the candidature period were also included.<br>
<br>
This data set contains several computational projects, including the data from Gaussian/orca/ibo/pyscf/dCI together with other plots.<br>
</pre>
DOI: 10.25442/hku.26362774.v1
title: Supporting data for "Development of Downfolded Configuration Interaction algorithm for molecular electronic structure calculation and computation chemistry application"

description: <pre>Accurately calculating the electronic structure of strongly correlated molecular systems, such as transition metal complexes, actinides, lanthanides, and extended $\pi$-conjugated organic molecules, is a significant challenge in<br>
the field of quantum chemistry. In these systems, strong electron correlations are crucial, and their accurate description is essential for predicting and understanding the properties and reactivity, which includes but is not limited to bond breaking, charge transfer, and excited states.
<br>
Traditional methods often have difficulties in accurately capturing the intricate electron correlations in these<br>
systems, which limits their capacity to produce reliable results. Furthermore, the scaling of high-level methods has significant limitations on their practical use when the system correlation size becomes large, making them computationally prohibitive. As a result, there is a need to develop efficient approximate techniques that can maintain high accuracy while reducing computational cost.<br>
<br>
In an exact diagonalization of benzene in the cc-pVDZ basis, the Hilbert space contains over $10^{45}$ determinants. However, the molecular Hamiltonian in real systems is very sparse, with the vast majority of matrix elements being negligible. This sparsity can be exploited to reduce the effective dimension dramatically.
<br>
This dataset presents the development and application of the Downfolded Configuration Interaction (dCI) algorithm for accurate and efficient calculations of molecules with strong correlations. The dCI, as a branch of the selected CI method, constructs a compact, effective Hamiltonian through an iterative process that captures the essential electron correlations. This is accomplished by carefully selecting significant configurations and applying a local treatment to the model subspace. Building upon the dCI algorithm, the extended-dCI (ext-dCI) method has been developed to further increase the applicability to larger molecular systems by approximating effective Hamiltonian expansion truncation.
<br>
Detailed benchmarks demonstrate the accuracy and efficiency of ext-dCI in calculating challenging systems such as benzene and chromium dimer. Utilizing the sparsity and locality of the electronic structure, the dCI and ext-dCI methods provide an in-depth description of both static and dynamic electron correlation effects. The dCI approach opens new possibilities for studying complex chemical phenomena governed by strong electron correlations.<br>
<br>
Some computational works on supramolecular and $\pi$-carbon chemistry during the candidature period were also included.<br>
<br>
This data set contains several computational projects, including the data from Gaussian/orca/ibo/pyscf/dCI together with other plots.<br>
</pre>
DOI: 10.15468/dl.xd47uu
title: Occurrence Download

description: A dataset containing 358 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alsodes gargola Gallardo, 1970"
 ]
}

 The dataset includes 358 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057380-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a9792s
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.526088 -33.139542, 149.526088 -33.141788, 149.53058 -33.141788, 149.53058 -33.139542, 149.526088 -33.139542)), ((149.53058 -33.141788, 149.53058 -33.144034, 149.532826 -33.144034, 149.532826 -33.141788, 149.53058 -33.141788)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057381-240626123714530/datasets/export for details.
DOI: 10.34740/kaggle/dsv/9137122
title: WallStreetBets 2022
DOI: 10.15468/dl.x54753
title: Occurrence Download

description: A dataset containing 623 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Balsamorhiza serrata A.Nelson & J.F.Macbr."
 ]
}

 The dataset includes 623 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057382-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2y55r
title: Occurrence Download

description: A dataset containing 2902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amphipoda, Cumacea, Decapoda, Euphausiacea, Isopoda, Leptostraca, Lophogastrida, Mysida, Stomatopoda, Tanaidacea, Akentrogonida, Arguloida, Dendrogastrida, Kentrogonida, Laurida, Pedunculata, Pygophora, Sessilia, Myodocopida)",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 "Year is greater than or equal to 1970",
 "CoordinateUncertaintyInMeters is less than 3000"
 ]
}

 The dataset includes 2902 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057383-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zmuq8u
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.562021 -33.13505, 149.562021 -33.141788, 149.550792 -33.141788, 149.550792 -33.139542, 149.548546 -33.139542, 149.548546 -33.148525, 149.562021 -33.148525, 149.562021 -33.144034, 149.564267 -33.144034, 149.564267 -33.148525, 149.571004 -33.148525, 149.571004 -33.139542, 149.568758 -33.139542, 149.568758 -33.13505, 149.562021 -33.13505))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057384-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bufz3f
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.418909 -33.141788, 148.418909 -33.148525, 148.421155 -33.148525, 148.421155 -33.141788, 148.418909 -33.141788))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057385-240626123714530/datasets/export for details.
DOI: 10.15468/dl.6asu6k
title: Occurrence Download

description: A dataset containing 2357093 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phylloscopus trochilus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 2357093 records from 2006 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057379-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/csc2.stk.acisfj1811160m182801_001
title: Chandra X-ray Observatory Stack acisfJ1811160m182801_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1825505m125955_001
title: Chandra X-ray Observatory Stack acisfJ1825505m125955_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2126229p625342_001
title: Chandra X-ray Observatory Stack acisfJ2126229p625342_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2218521m033541_001
title: Chandra X-ray Observatory Stack acisfJ2218521m033541_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1809168m255346_001
title: Chandra X-ray Observatory Stack acisfJ1809168m255346_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1809417m191639_001
title: Chandra X-ray Observatory Stack acisfJ1809417m191639_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1809065m203205_001
title: Chandra X-ray Observatory Stack acisfJ1809065m203205_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2153339p174044_001
title: Chandra X-ray Observatory Stack acisfJ2153339p174044_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2033425p411737_001
title: Chandra X-ray Observatory Stack acisfJ2033425p411737_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2207007p101428_002
title: Chandra X-ray Observatory Stack acisfJ2207007p101428_002

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2127490m220740_001
title: Chandra X-ray Observatory Stack acisfJ2127490m220740_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2220023m025027_001
title: Chandra X-ray Observatory Stack acisfJ2220023m025027_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1811294m192632_001
title: Chandra X-ray Observatory Stack acisfJ1811294m192632_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2217369p001534_001
title: Chandra X-ray Observatory Stack acisfJ2217369p001534_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2129289p272024_001
title: Chandra X-ray Observatory Stack acisfJ2129289p272024_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2140228m231140_002
title: Chandra X-ray Observatory Stack acisfJ2140228m231140_002

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2219106m184250_001
title: Chandra X-ray Observatory Stack acisfJ2219106m184250_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1811280m192550_001
title: Chandra X-ray Observatory Stack acisfJ1811280m192550_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2340462m230224_001
title: Chandra X-ray Observatory Stack acisfJ2340462m230224_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2343313m502235_001
title: Chandra X-ray Observatory Stack acisfJ2343313m502235_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1831248m621644_001
title: Chandra X-ray Observatory Stack acisfJ1831248m621644_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj2257161m432328_001
title: Chandra X-ray Observatory Stack acisfJ2257161m432328_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1832114m103413_001
title: Chandra X-ray Observatory Stack acisfJ1832114m103413_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1830568m253004_001
title: Chandra X-ray Observatory Stack acisfJ1830568m253004_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".