cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8367864
title: GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47

description: <strong>This is a file of all raw data and processed data concerned in the article "GcForest-based Compound-Protein Interaction Prediction Model and Its Application in Discovering Small-Molecule Drugs Targeting CD47", this file contain 6 sub-files, namely GCVec——humans, GCVec——celegans, GCVec——challenging dataset, GCVec——latest BindingDB, GCVec——known CD47 inhibitors, GCVec——specs, respectively, fully cover all parts of the article.</strong>
DOI: 10.5519/qd.qujby4wf
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5669969 records)
DOI: 10.5281/zenodo.8369911
title: Insights on the coupling between vibronically active molecular vibrations and lattice phonons in molecular nanomagnets

description: Spin–lattice relaxation is a key open problem to understand the spin dynamics of single-molecule magnets and molecular spin qubits. While modelling the coupling between spin states and local vibrations allows to determine the more relevant molecular vibrations for spin relaxation, this is not sufficient to explain how energy is dissipated towards the thermal bath. Herein, we employ a simple and efficient model to examine the coupling of local vibrational modes with long-wavelength longitudinal and transverse phonons in the clock-like spin qubit [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup>. We find that in crystals of this polyoxometalate the vibrational mode previously found to be vibronically active at low temperature does not couple significantly to lattice phonons. This means that further intramolecular energy transfer <em>via</em> anharmonic vibrations is necessary for spin relaxation in this system. Finally, we discuss implications for the spin–phonon coupling of [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup> deposited on a MgO (001) substrate, offering a simple methodology that can be extrapolated to estimate the effects on spin relaxation of different surfaces, including 2D materials.
DOI: 10.5281/zenodo.8369912
title: Insights on the coupling between vibronically active molecular vibrations and lattice phonons in molecular nanomagnets

description: Spin–lattice relaxation is a key open problem to understand the spin dynamics of single-molecule magnets and molecular spin qubits. While modelling the coupling between spin states and local vibrations allows to determine the more relevant molecular vibrations for spin relaxation, this is not sufficient to explain how energy is dissipated towards the thermal bath. Herein, we employ a simple and efficient model to examine the coupling of local vibrational modes with long-wavelength longitudinal and transverse phonons in the clock-like spin qubit [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup>. We find that in crystals of this polyoxometalate the vibrational mode previously found to be vibronically active at low temperature does not couple significantly to lattice phonons. This means that further intramolecular energy transfer <em>via</em> anharmonic vibrations is necessary for spin relaxation in this system. Finally, we discuss implications for the spin–phonon coupling of [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup> deposited on a MgO (001) substrate, offering a simple methodology that can be extrapolated to estimate the effects on spin relaxation of different surfaces, including 2D materials.
DOI: 10.5281/zenodo.8370011
title: Insights on the coupling between vibronically active molecular vibrations and lattice phonons in molecular nanomagnets

description: Spin–lattice relaxation is a key open problem to understand the spin dynamics of single-molecule magnets and molecular spin qubits. While modelling the coupling between spin states and local vibrations allows to determine the more relevant molecular vibrations for spin relaxation, this is not sufficient to explain how energy is dissipated towards the thermal bath. Herein, we employ a simple and efficient model to examine the coupling of local vibrational modes with long-wavelength longitudinal and transverse phonons in the clock-like spin qubit [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup>. We find that in crystals of this polyoxometalate the vibrational mode previously found to be vibronically active at low temperature does not couple significantly to lattice phonons. This means that further intramolecular energy transfer <em>via</em> anharmonic vibrations is necessary for spin relaxation in this system. Finally, we discuss implications for the spin–phonon coupling of [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup> deposited on a MgO (001) substrate, offering a simple methodology that can be extrapolated to estimate the effects on spin relaxation of different surfaces, including 2D materials.
DOI: 10.5281/zenodo.8369917
title: Impacts of invasive alien species on riparian plant communities in South-African savanna - data to the article

description: Data on plant species richness, Shannon's diversity, Pielou's evenness, and abundance (cover) of individual plant species in the plots.
DOI: 10.5281/zenodo.8369916
title: Impacts of invasive alien species on riparian plant communities in South-African savanna - data to the article

description: Data on plant species richness, Shannon's diversity, Pielou's evenness, and abundance (cover) of individual plant species in the plots.
DOI: 10.18112/openneuro.ds004670.v1.0.1
title: Visual Illusion Reconstruction
DOI: 10.5281/zenodo.8369932
title: Data from the parametric analysis of multi-ring masonry arches using a limit analysis approach for the span of 3m

description: The dataset is produced by running a series of 360 simulations using the in-house code ALMA (<em>Analisi Limite Murature Attritive</em>) that implements the upper bound approach of limit analysis to detect the collapse multiplier and mechanism for masonry structures. This set of data contains the results of 120 simulations achieved for the multi-ring masonry arches for span of 3m with different level of parameters considered, namely size of blocks, span of the arch, ring number, interlocking coefficient and the friction angle. In order to simplify references to figures an acronym system is used and it follows a sequence of "<em>size_span_ring_interlock_friction</em>". Size takes attributes as <strong>S</strong>-small and <strong>B</strong>-big while span takes number attributes based on the span like <strong>S3</strong>, <strong>S5</strong>, <strong>S7</strong> for spans of <strong>3</strong>, <strong>5</strong> and <strong>7</strong> meters, respectively. Ring number similarly is based on the number of rings as <strong>R2</strong>, <strong>R3</strong>, <strong>R4</strong> and <strong>R5</strong> and interlock takes the following attributes, I<strong>00</strong>, <strong>I15</strong>, <strong>I35</strong> and <strong>I50</strong> for the interlocking percentage considered such that <strong>00</strong>-stacked, <strong>15%</strong>, <strong>35%</strong> and <strong>50%</strong>, respectively. Finally friction takes attributes following the angle of friction such as <strong>F25</strong>—low level, <strong>F30</strong>—medium level, and <strong>F35</strong>—high level. The acronym used for the equivalent one-ring arches is used as simply <strong>EQ</strong>. For example, the acronym “<em><strong>S_S7_R4_I35_F30</strong></em>" refers to the arch with small blocks, span of 7 meters, consisting of 4 rings and by blocks interlocked at 35% with a joint friction of 30<sup>o</sup>. This database contains a <strong>*.txt</strong>, a <strong>*.vtk</strong> and a <strong>*.png</strong> file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained.
DOI: 10.5281/zenodo.8369933
title: Data from the parametric analysis of multi-ring masonry arches using a limit analysis approach for the span of 3m

description: The dataset is produced by running a series of 360 simulations using the in-house code ALMA (<em>Analisi Limite Murature Attritive</em>) that implements the upper bound approach of limit analysis to detect the collapse multiplier and mechanism for masonry structures. This set of data contains the results of 120 simulations achieved for the multi-ring masonry arches for span of 3m with different level of parameters considered, namely size of blocks, span of the arch, ring number, interlocking coefficient and the friction angle. In order to simplify references to figures an acronym system is used and it follows a sequence of "<em>size_span_ring_interlock_friction</em>". Size takes attributes as <strong>S</strong>-small and <strong>B</strong>-big while span takes number attributes based on the span like <strong>S3</strong>, <strong>S5</strong>, <strong>S7</strong> for spans of <strong>3</strong>, <strong>5</strong> and <strong>7</strong> meters, respectively. Ring number similarly is based on the number of rings as <strong>R2</strong>, <strong>R3</strong>, <strong>R4</strong> and <strong>R5</strong> and interlock takes the following attributes, I<strong>00</strong>, <strong>I15</strong>, <strong>I35</strong> and <strong>I50</strong> for the interlocking percentage considered such that <strong>00</strong>-stacked, <strong>15%</strong>, <strong>35%</strong> and <strong>50%</strong>, respectively. Finally friction takes attributes following the angle of friction such as <strong>F25</strong>—low level, <strong>F30</strong>—medium level, and <strong>F35</strong>—high level. The acronym used for the equivalent one-ring arches is used as simply <strong>EQ</strong>. For example, the acronym “<em><strong>S_S7_R4_I35_F30</strong></em>" refers to the arch with small blocks, span of 7 meters, consisting of 4 rings and by blocks interlocked at 35% with a joint friction of 30<sup>o</sup>. This database contains a <strong>*.txt</strong>, a <strong>*.vtk</strong> and a <strong>*.png</strong> file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained.
DOI: 10.5281/zenodo.8365865
title: Atlas of the Finnish Literature project dataset

description: This dataset contains data for the project <em>Atlas of the Finnish Literature</em>. The data contains original plain text files containing Finnish literature from the late 19th and early 20th century, TEI/XML-versions of these same files converted by the project, and the same TEI/XML files with named entity recognition and named entity linking data added. In addition, there are JSON-exported, simplified versions of the final data files.
DOI: 10.5281/zenodo.8365866
title: Atlas of the Finnish Literature project dataset

description: This dataset contains data for the project <em>Atlas of the Finnish Literature</em>. The data contains original plain text files containing Finnish literature from the late 19th and early 20th century, TEI/XML-versions of these same files converted by the project, and the same TEI/XML files with named entity recognition and named entity linking data added. In addition, there are JSON-exported, simplified versions of the final data files.
DOI: 10.17894/ucph.d71a6a5a-8107-4fd9-9440-bdafdfe81455
title: Genotype data from "Population Genomics of Postglacial Western Eurasia"
DOI: 10.5281/zenodo.8370053
title: Data from the parametric analysis of multi-ring masonry arches using a limit analysis approach for the span of 7m

description: The dataset is produced by running a series of 360 simulations using the in-house code ALMA (<em>Analisi Limite Murature Attritive</em>) that implements the upper bound approach of limit analysis to detect the collapse multiplier and mechanism for masonry structures. This set of data contains the results of 120 simulations achieved for the multi-ring masonry arches for span of 7m with different level of parameters considered, namely size of blocks, span of the arch, ring number, interlocking coefficient and the friction angle. In order to simplify references to figures an acronym system is used and it follows a sequence of "<em>size_span_ring_interlock_friction</em>". Size takes attributes as <strong>S</strong>-small and <strong>B</strong>-big while span takes number attributes based on the span like <strong>S3</strong>, <strong>S5</strong>, <strong>S7</strong> for spans of <strong>3</strong>, <strong>5</strong> and <strong>7</strong> meters, respectively. Ring number similarly is based on the number of rings as <strong>R2</strong>, <strong>R3</strong>, <strong>R4</strong> and <strong>R5</strong> and interlock takes the following attributes, I<strong>00</strong>, <strong>I15</strong>, <strong>I35</strong> and <strong>I50</strong> for the interlocking percentage considered such that <strong>00</strong>-stacked, <strong>15%</strong>, <strong>35%</strong> and <strong>50%</strong>, respectively. Finally friction takes attributes following the angle of friction such as <strong>F25</strong>—low level, <strong>F30</strong>—medium level, and <strong>F35</strong>—high level. The acronym used for the equivalent one-ring arches is used as simply <strong>EQ</strong>. For example, the acronym “<em><strong>S_S7_R4_I35_F30</strong></em>" refers to the arch with small blocks, span of 7 meters, consisting of 4 rings and by blocks interlocked at 35% with a joint friction of 30<sup>o</sup>. This database contains a <strong>*.txt</strong>, a <strong>*.vtk</strong> and a <strong>*.png</strong> file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained.
DOI: 10.5281/zenodo.8370052
title: Data from the parametric analysis of multi-ring masonry arches using a limit analysis approach for the span of 7m

description: The dataset is produced by running a series of 360 simulations using the in-house code ALMA (<em>Analisi Limite Murature Attritive</em>) that implements the upper bound approach of limit analysis to detect the collapse multiplier and mechanism for masonry structures. This set of data contains the results of 120 simulations achieved for the multi-ring masonry arches for span of 7m with different level of parameters considered, namely size of blocks, span of the arch, ring number, interlocking coefficient and the friction angle. In order to simplify references to figures an acronym system is used and it follows a sequence of "<em>size_span_ring_interlock_friction</em>". Size takes attributes as <strong>S</strong>-small and <strong>B</strong>-big while span takes number attributes based on the span like <strong>S3</strong>, <strong>S5</strong>, <strong>S7</strong> for spans of <strong>3</strong>, <strong>5</strong> and <strong>7</strong> meters, respectively. Ring number similarly is based on the number of rings as <strong>R2</strong>, <strong>R3</strong>, <strong>R4</strong> and <strong>R5</strong> and interlock takes the following attributes, I<strong>00</strong>, <strong>I15</strong>, <strong>I35</strong> and <strong>I50</strong> for the interlocking percentage considered such that <strong>00</strong>-stacked, <strong>15%</strong>, <strong>35%</strong> and <strong>50%</strong>, respectively. Finally friction takes attributes following the angle of friction such as <strong>F25</strong>—low level, <strong>F30</strong>—medium level, and <strong>F35</strong>—high level. The acronym used for the equivalent one-ring arches is used as simply <strong>EQ</strong>. For example, the acronym “<em><strong>S_S7_R4_I35_F30</strong></em>" refers to the arch with small blocks, span of 7 meters, consisting of 4 rings and by blocks interlocked at 35% with a joint friction of 30<sup>o</sup>. This database contains a <strong>*.txt</strong>, a <strong>*.vtk</strong> and a <strong>*.png</strong> file. In the .txt file the elapsed time and the collapse multiplier of each simulation can be found. The .vtk file contains all the geometry and displacement values of every masonry panel. Finally, the .png file presents the collapse mechanism obtained.
DOI: 10.6084/m9.figshare.24183009
title: KEGG_build_2023-09-22

description: An archived version of the KEGG data directory for use in anvi'o. Can be set up on a computer with an anvi'o installation using the command `anvi-setup-kegg-kofams --kegg-archive KEGG_build_2023-09-18_a2b5bde358bb.tar.gz` (specify a --kegg-data-dir to avoid overriding the default KEGG data directory, if one exists). This is the first KEGG snapshot for anvi'o that contains the KEGG Orthology database for use in metabolic modeling. It is also the default KEGG snapshot for anvi'o v8.Contains MODULES.db version 4.<br>Hash value of the database is a2b5bde358bb
DOI: 10.6084/m9.figshare.24064098
title: Supplementary Material for: Violation of the constant genetic effect assumption can result in biased estimates for non-linear Mendelian randomization

description: Introduction: Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly-used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice. Methods: We use the recently developed doubly-ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D [25(OH)D] used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality. Results: The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method, but not for the doubly-ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures, and less reasonable for others. If the doubly-ranked method indicates that this assumption is violated, then estimates from both the residual and doubly-ranked methods can be biased, although bias was smaller on average in the doubly-ranked method. Conclusion: Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly-ranked methods, as well as considering transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.
DOI: 10.6084/m9.figshare.24064098.v1
title: Supplementary Material for: Violation of the constant genetic effect assumption can result in biased estimates for non-linear Mendelian randomization

description: Introduction: Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly-used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice. Methods: We use the recently developed doubly-ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D [25(OH)D] used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality. Results: The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method, but not for the doubly-ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures, and less reasonable for others. If the doubly-ranked method indicates that this assumption is violated, then estimates from both the residual and doubly-ranked methods can be biased, although bias was smaller on average in the doubly-ranked method. Conclusion: Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly-ranked methods, as well as considering transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.
DOI: 10.6084/m9.figshare.24145455.v1
title: Supplementary Material for: A single-institution retrospective series of SARs-Cov-2 infection in adult glioma patients

description: A subset of cancer patients is particularly vulnerable to SARS-Cov-2 infection; however, real-world outcomes-based data on primary central nervous system tumor patients is sparse. This retrospective series describes a cohort of adult glioma patients seen at Stanford Cancer Center between 1/1/2020 through 6/30/2022 who contracted SARS-Cov-2, which, to our knowledge, currently represents the largest single-institution comprehensive analysis of this patient population. We performed a retrospective search of patients seen in the Stanford Neuro-Oncology clinic, identifying 29 cases of COVID-19 amongst glioma patients and extracted clinical data via individual chart review. At the time of COVID-19 diagnosis, 15 patients had been vaccinated against SARS-Cov-2, 8 patients were taking dexamethasone, and 8 were undergoing cancer-specific treatment. Obesity, prior tobacco use, and diabetes were the most common comorbidities. Cough, sore throat, and congestion were the most common symptoms. Five patients were admitted to the hospital and two received COVID-19-specific treatment. None died from Covid-related causes or complications. Our data suggest that glioma patients seen at Stanford Cancer Center do not experience an exceptionally high COVID-19 infectivity, hospitalization, or mortality rate, especially when compared to other vulnerable populations such as lung cancer patients. High vaccination rates, adherence to COVID-19 guidelines, and low prevalence of comorbidities may have contributed to these results.
DOI: 10.6084/m9.figshare.24155586.v1
title: Supplementary Material for: Isolated Pancreatic Metastasis From a Lung Adenocarcinoma Primary: A Case Report and Literature Review

description: Isolated pancreatic metastasis is a rare occurrence and is commonly misdiagnosed as primary pancreatic malignancy. We present a case of a 65-year-old female patient with a history of stage IIIA lung adenocarcinoma, who developed significant epigastric pain 27 months after diagnosis and treatment of a primary lung adenocarcinoma. This patient was found to have a pancreatic head lesion initially suspected to be a primary pancreatic neoplasm but eventually discovered to be a metastatic lesion from the previously treated primary lung adenocarcinoma.