cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.uuru8r
title: Occurrence Download

description: A dataset containing 8151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus palustris Mill."
 ]
}

 The dataset includes 8151 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000264-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9yxjqd
title: Occurrence Download

description: A dataset containing 8151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus palustris Mill."
 ]
}

 The dataset includes 8151 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000265-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mm9a6h
title: Occurrence Download

description: A dataset containing 3922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anemonoides altaica (Fisch. ex C.A.Mey.) Holub)"
 ]
}

 The dataset includes 3922 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000266-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2x9usb
title: Occurrence Download

description: A dataset containing 8151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus palustris Mill."
 ]
}

 The dataset includes 8151 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000267-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44j7xd
title: Occurrence Download

description: A dataset containing 8151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus palustris Mill."
 ]
}

 The dataset includes 8151 records from 215 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000268-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25621506
title: Financial Inclusion Conjoint

description: Slum dwellers continue to face exclusion from mainstream social, economic and financial activities due to their lack of education and low income, leaving them vulnerable to income shocks and persistent poverty. The absence of empowerment compounds their challenges, highlighting the urgent need to address their financial inclusion. In this context, designing an inclusive deposit product is imperative to ensure financial inclusion for slum dwellers. We conducted a randomized conjoint experiment, gathering 2500 choice responses from 250 respondents in slum households in Khulna, an industrial city of Bangladesh. Our study estimates the influence of each attribute on slum dwellers’ choice of deposit product, measures willingness to pay for proposed inclusive deposit product, identifies heterogeneity in their preferences and examines the impact of financial literacy on their preferences. Our hypothetical financial inclusion product provides valuable insights for policy makers in formulating comprehensive policy to ensure financial inclusion of slum dwellers.
DOI: 10.6084/m9.figshare.25621506.v1
title: Financial Inclusion Conjoint

description: Slum dwellers continue to face exclusion from mainstream social, economic and financial activities due to their lack of education and low income, leaving them vulnerable to income shocks and persistent poverty. The absence of empowerment compounds their challenges, highlighting the urgent need to address their financial inclusion. In this context, designing an inclusive deposit product is imperative to ensure financial inclusion for slum dwellers. We conducted a randomized conjoint experiment, gathering 2500 choice responses from 250 respondents in slum households in Khulna, an industrial city of Bangladesh. Our study estimates the influence of each attribute on slum dwellers’ choice of deposit product, measures willingness to pay for proposed inclusive deposit product, identifies heterogeneity in their preferences and examines the impact of financial literacy on their preferences. Our hypothetical financial inclusion product provides valuable insights for policy makers in formulating comprehensive policy to ensure financial inclusion of slum dwellers.
DOI: 10.15468/dl.febffb
title: Occurrence Download

description: A dataset containing 1338 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Diadema mexicanum A.Agassiz, 1863"
 ]
}

 The dataset includes 1338 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000269-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x3pwgy
title: Occurrence Download

description: A dataset containing 194 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anetanthus gracilis Hiern, Anetanthus gracilis subsp. munchiquensis Fern.Alonso, Anetanthus gracilis subsp. gracilis)"
 ]
}

 The dataset includes 194 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000270-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26107831
title: Development of a resilience safety culture model for the hazardous materials processing industry

description: Many previous cases have demonstrated that hazardous materials processing industry (HMPI) accidents always result in huge losses and HMPI companies which suffer accidents are difficult to quickly restore. This has demanded an effective way to solve the two problems. Resilience safety culture (RSC) combines conventional safety culture and resilience engineering. It aims at giving an organization the abilities of continually operating or timely recovering during or after a major unexpected event. RSC fits the safety demands of the HMPI well. The present study develops a RSC model for the HMPI. Firstly, through literature review, 12 model elements with 16 hypothesized relationships are developed. These hypothesis are then tested by 618 samples with structural equation modelling. Finally, an HMPI RSC model with 12 elements and 12 relationships is established. Model validity is verified by a comparison study on the proposed model and two existing models with the fuzzy analytic hierarchy process.
DOI: 10.6084/m9.figshare.26107831.v1
title: Development of a resilience safety culture model for the hazardous materials processing industry

description: Many previous cases have demonstrated that hazardous materials processing industry (HMPI) accidents always result in huge losses and HMPI companies which suffer accidents are difficult to quickly restore. This has demanded an effective way to solve the two problems. Resilience safety culture (RSC) combines conventional safety culture and resilience engineering. It aims at giving an organization the abilities of continually operating or timely recovering during or after a major unexpected event. RSC fits the safety demands of the HMPI well. The present study develops a RSC model for the HMPI. Firstly, through literature review, 12 model elements with 16 hypothesized relationships are developed. These hypothesis are then tested by 618 samples with structural equation modelling. Finally, an HMPI RSC model with 12 elements and 12 relationships is established. Model validity is verified by a comparison study on the proposed model and two existing models with the fuzzy analytic hierarchy process.
DOI: 10.6084/m9.figshare.25871337
title: Population-Level Balance in Signed Networks

description: Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for <i>signed networks</i> have been largely unexplored. In signed networks, there exist both positive (e.g., like, trust) and negative (e.g., dislike, distrust) edges, which are commonly seen in real-world scenarios. The positive and negative edges in signed networks lead to unique structural patterns, which pose challenges for statistical modeling. In this article, we introduce a statistically principled latent space approach for modeling signed networks and accommodating the well-known <i>balance theory</i>, that is, “the enemy of my enemy is my friend” and “the friend of my friend is my friend.” The proposed approach treats both edges and their signs as random variables, and characterizes the balance theory with a novel and natural notion of population-level balance. This approach guides us towards building a class of balanced inner-product models, and toward developing scalable algorithms via projected gradient descent to estimate the latent variables. We also establish non-asymptotic error rates for the estimates, which are further verified through simulation studies. In addition, we apply the proposed approach to an international relation network, which provides an informative and interpretable model-based visualization of countries during World War II. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.25871337.v1
title: Population-level Balance in Signed Networks

description: Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for <i>signed networks</i> have been largely unexplored. In signed networks, there exist both positive (e.g., like, trust) and negative (e.g., dislike, distrust) edges, which are commonly seen in real-world scenarios. The positive and negative edges in signed networks lead to unique structural patterns, which pose challenges for statistical modeling. In this paper, we introduce a statistically principled latent space approach for modeling signed networks and accommodating the well-known <i>balance theory</i>, i.e., “the enemy of my enemy is my friend” and “the friend of my friend is my friend”. The proposed approach treats both edges and their signs as random variables, and characterizes the balance theory with a novel and natural notion of population-level balance. This approach guides us towards building a class of balanced inner-product models, and towards developing scalable algorithms via projected gradient descent to estimate the latent variables. We also establish non-asymptotic error rates for the estimates, which are further verified through simulation studies. In addition, we apply the proposed approach to an international relation network, which provides an informative and interpretable model-based visualization of countries during World War II.
DOI: 10.6084/m9.figshare.25871337.v2
title: Population-Level Balance in Signed Networks

description: Statistical network models are useful for understanding the underlying formation mechanism and characteristics of complex networks. However, statistical models for <i>signed networks</i> have been largely unexplored. In signed networks, there exist both positive (e.g., like, trust) and negative (e.g., dislike, distrust) edges, which are commonly seen in real-world scenarios. The positive and negative edges in signed networks lead to unique structural patterns, which pose challenges for statistical modeling. In this article, we introduce a statistically principled latent space approach for modeling signed networks and accommodating the well-known <i>balance theory</i>, that is, “the enemy of my enemy is my friend” and “the friend of my friend is my friend.” The proposed approach treats both edges and their signs as random variables, and characterizes the balance theory with a novel and natural notion of population-level balance. This approach guides us towards building a class of balanced inner-product models, and toward developing scalable algorithms via projected gradient descent to estimate the latent variables. We also establish non-asymptotic error rates for the estimates, which are further verified through simulation studies. In addition, we apply the proposed approach to an international relation network, which provides an informative and interpretable model-based visualization of countries during World War II. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.25872451
title: Joint Tensor Modeling of Single Cell 3D Genome and Epigenetic Data with Muscle

description: Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with the epigenome at the single cell level. While methods to analyze data from single cell high throughput chromatin conformation capture (scHi-C) experiments are maturing, methods that can jointly analyze multiple single cell modalities with scHi-C data are lacking. Here, we introduce Muscle, a semi-nonnegative joint decomposition of Multiple single cell tensors, to jointly analyze 3D conformation and DNA methylation data at the single cell level. Muscle takes advantage of the inherent tensor structure of the scHi-C data, and integrates this modality with DNA methylation. We developed an alternating least squares algorithm for estimating Muscle parameters and established its optimality properties. Parameters estimated by Muscle directly align with the key components of the downstream analysis of scHi-C data in a cell type specific manner. Evaluations with data-driven experiments and simulations demonstrate the advantages of the joint modeling framework of Muscle over single modality modeling and a baseline multi modality modeling for cell type delineation and elucidating associations between modalities. Muscle is publicly available at https://github.com/keleslab/muscle. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.25872451.v1
title: Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle

description: Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with the epigenome at the single cell level. While methods to analyze data from single cell high throughput chromatin conformation capture (scHi-C) experiments are maturing, methods that can jointly analyze multiple single cell modalities with scHi-C data are lacking. Here, we introduce Muscle, a semi-nonnegative joint decomposition of Multiple single cell tensors, to jointly analyze 3D conformation and DNA methylation data at the single cell level. Muscle takes advantage of the inherent tensor structure of the scHi-C data, and integrates this modality with DNA methylation. We developed an alternating least squares algorithm for estimating Muscle parameters and established its optimality properties. Parameters estimated by Muscle directly align with the key components of the downstream analysis of scHi-C data in a cell type specific manner. Evaluations with data-driven experiments and simulations demonstrate the advantages of the joint modeling framework of Muscle over single modality modeling and a baseline multi modality modeling for cell type delineation and elucidating associations between modalities. Muscle is publicly available at https://github.com/keleslab/muscle.
DOI: 10.6084/m9.figshare.25872451.v2
title: Joint Tensor Modeling of Single Cell 3D Genome and Epigenetic Data with Muscle

description: Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with the epigenome at the single cell level. While methods to analyze data from single cell high throughput chromatin conformation capture (scHi-C) experiments are maturing, methods that can jointly analyze multiple single cell modalities with scHi-C data are lacking. Here, we introduce Muscle, a semi-nonnegative joint decomposition of Multiple single cell tensors, to jointly analyze 3D conformation and DNA methylation data at the single cell level. Muscle takes advantage of the inherent tensor structure of the scHi-C data, and integrates this modality with DNA methylation. We developed an alternating least squares algorithm for estimating Muscle parameters and established its optimality properties. Parameters estimated by Muscle directly align with the key components of the downstream analysis of scHi-C data in a cell type specific manner. Evaluations with data-driven experiments and simulations demonstrate the advantages of the joint modeling framework of Muscle over single modality modeling and a baseline multi modality modeling for cell type delineation and elucidating associations between modalities. Muscle is publicly available at https://github.com/keleslab/muscle. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.26035870
title: Constraints of alkaline magmatic evolution on the enrichment and mineralisation of rare-earth elements in the eastern part of the northern margin of the North China Craton: a case study of the Baerzhe and Saima deposits

description: The eastern part of the northern margin of the North China Craton is a key metal metallogenic province in China, hosting many important rare metal and rare earth element (REE) deposits and having great resource potential. This study investigated the Saima deposit, a niobium (Nb) and tantalum (Ta) deposit and the Baerzhe deposit hosting zirconium (Zr), Nb and REEs. Based on previous LA-ICP-MS zircon U–Pb dating results obtained by the authors’ team, this study compared the whole-rock geochemistry and whole-rock Sr–Nd–Pb isotopes of an orebody with its surrounding rocks. The geochemical characteristics of both deposits are used to systematically review the evolution of the alkaline magma and the differences in the physical and chemical conditions for enrichment and mineralisation of late-stage rare elements and REEs such as Nb, Ta and Zr. Comparing the mineralisation of the Saima and Baerzhe deposits, the alkaline magmatic evolution plays a crucial role in the enrichment of rare-earth elements, which are generally formed in the late stage of alkaline magmatic evolution. The Saima deposit, which has a metallogenic age of 224.40 ± 6.10 Ma, formed in nepheline syenites with high alkali (Na<sub>2</sub>O + K<sub>2</sub>O) and low MgO and CaO contents, with high TFeO/MgO ratios. The A-type granites formed in an extensional tectonic setting after the closure of the Paleo-Asian Ocean. The Baerzhe deposit, which has a metallogenic age of 125.2–122.15 Ma, formed in A-type alkali granites (orebody and surrounding rocks) that have high alkali (Na<sub>2</sub>O + K<sub>2</sub>O) and low MgO and CaO contents with high TFeO/MgO ratios, strong uranium (U) depletion and typical V-shaped distribution of REE. The mineralisation is controlled by melt–fluid interactions in the later stage of highly evolved magmas. The enrichment and mineralisation of rare elements and REEs in the eastern part of the north margin of the North China Craton are mainly associated with the high degree of evolution of alkaline magmas.
DOI: 10.6084/m9.figshare.26035870.v1
title: Constraints of alkaline magmatic evolution on the enrichment and mineralisation of rare-earth elements in the eastern part of the northern margin of the North China Craton: a case study of the Baerzhe and Saima deposits

description: The eastern part of the northern margin of the North China Craton is a key metal metallogenic province in China, hosting many important rare metal and rare earth element (REE) deposits and having great resource potential. This study investigated the Saima deposit, a niobium (Nb) and tantalum (Ta) deposit and the Baerzhe deposit hosting zirconium (Zr), Nb and REEs. Based on previous LA-ICP-MS zircon U–Pb dating results obtained by the authors’ team, this study compared the whole-rock geochemistry and whole-rock Sr–Nd–Pb isotopes of an orebody with its surrounding rocks. The geochemical characteristics of both deposits are used to systematically review the evolution of the alkaline magma and the differences in the physical and chemical conditions for enrichment and mineralisation of late-stage rare elements and REEs such as Nb, Ta and Zr. Comparing the mineralisation of the Saima and Baerzhe deposits, the alkaline magmatic evolution plays a crucial role in the enrichment of rare-earth elements, which are generally formed in the late stage of alkaline magmatic evolution. The Saima deposit, which has a metallogenic age of 224.40 ± 6.10 Ma, formed in nepheline syenites with high alkali (Na<sub>2</sub>O + K<sub>2</sub>O) and low MgO and CaO contents, with high TFeO/MgO ratios. The A-type granites formed in an extensional tectonic setting after the closure of the Paleo-Asian Ocean. The Baerzhe deposit, which has a metallogenic age of 125.2–122.15 Ma, formed in A-type alkali granites (orebody and surrounding rocks) that have high alkali (Na<sub>2</sub>O + K<sub>2</sub>O) and low MgO and CaO contents with high TFeO/MgO ratios, strong uranium (U) depletion and typical V-shaped distribution of REE. The mineralisation is controlled by melt–fluid interactions in the later stage of highly evolved magmas. The enrichment and mineralisation of rare elements and REEs in the eastern part of the north margin of the North China Craton are mainly associated with the high degree of evolution of alkaline magmas.