cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11848962.v2
title: Data supporting my manuscript 1 from Diversity of arthropods on <i>Acacia mangium</i> (Fabaceae) and production of this plant with dehydrated sewage sludge in degraded area

description: Sewage sludge is an organic matter-rich material with abundant fractions of nitrogen and other macro and micronutrients, essential for plant growth and development such as <i>Acacia mangium</i> Willd. (Fabales: Fabaceae) used in recovering actions of degraded areas. The objective of this study was to evaluate over 24 months the abundance and diversity of chewing and pollinator insects and arthropod predators on <i>A. mangium</i> plants and the mass production and soil coverage by this plant, fertilized with dehydrated sewage sludge, in a degraded area. The experimental design was in randomized blocks with two treatments (with and without dehydrated sewage sludge) and 24 replications. The number of leaves per branch and branches per plant, defoliation percentage by chewing insects, soil cover and abundance of chewing and pollinator insects and arthropod predators were higher on <i>A. mangium</i> plants fertilized with dehydrated sewage sludge. <i>Nasutitermes</i> sp. (Blattodea: Termitidae) and <i>Trigona spinipes</i> F. (Hymenoptera: Apidae) were the most observed insects on trunks and leaves, respectively, of <i>A. mangium</i> plants fertilized with dehydrated sewage sludge. The <i>A. mangium</i> fertilization increases the populations of different insect and spider groups on this plant.
DOI: 10.6084/m9.figshare.11849157.v2
title: River and Infrastructure Connectivity Network (RICON)

description: River and Infrastructure Connectivity Network (RICON) – shows the dependency between streamgages and reservoirs as a concise edge list for the Colorado River Basin (CRB). The RICON dataset provides (1) a complete list of edges for the unidirectional network connecting streamgages, reservoirs and NHDPlusflowline features for CRB and (2) attributes of all nodes (reservoirs and streamgages) including their geospatial locations, unique identifiers, immediate upstream and downstream nodes, etc. The RICON data archive available at figshare contains the dataset tables in comma-separated values (CSV) format. Input files are 'sites_df.csv', 'nid_df.csv' and 'NHD_data.RData'. Output file is 'Edge_List.csv' <br>
DOI: 10.6084/m9.figshare.11848962.v1
title: Data supporting my manuscript 2 from Diversity of arthropods on <i>Acacia mangium</i> (Fabaceae) and production of this plant with dehydrated sewage sludge in degraded area

description: Sewage sludge is an organic matter-rich material with abundant fractions of nitrogen and other macro and micronutrients, essential for the plant growth and development such as <i>Acacia mangium</i> Willd. (Fabales: Fabaceae) used in recovering actions of degraded areas. The objective of this study was to evaluate over 24 months the abundance and diversity of chewing and pollinator insects and arthropod predators on <i>A. mangium</i> plants and the mass production and soil coverage by this plant, fertilized with dehydrated sewage sludge, in a degraded area. The experimental design was in randomized blocks with two treatments (with and without dehydrated sewage sludge) and 24 replications. The number of leaves/branch and branches/plant, defoliation percentage by chewing insects, soil cover and abundance of chewing and pollinator insects and arthropod predators were higher on <i>A. mangium</i> plants fertilized with dehydrated sewage sludge. <i>Nasutitermes</i> sp. (Isoptera: Termitidae) and <i>Trigona spinipes</i> F. (Hymenoptera: Apidae) were the most observed insects on trunks and leaves, respectively, of <i>A. mangium</i> plants fertilized with dehydrated sewage sludge. The <i>A. mangium</i> fertilization increases the populations of different insect and spider groups on this plant.
DOI: 10.6084/m9.figshare.11848965.v2
title: Raw NanoSIMS data for symbiont enrichment from autotrophy from Intracellular competition for nitrogen controls dinoflagellate population density in corals

description: The density of dinoflagellate microalgae in the tissue of symbiotic corals is an important determinant for health and productivity of the coral animal. Yet, the specific mechanism for their regulation and the consequence for coral nutrition are insufficiently understood due to past methodological limitations to resolve the fine-scale metabolic consequences of fluctuating densities. Here, we characterized the physiological and nutritional consequences of symbiont density variations on the colony and tissue level in <i>Stylophora pistillata</i> from the Red Sea. Alterations in symbiont photophysiology maintained coral productivity and host nutrition across a broad range of symbiont densities. However, we demonstrate that density-dependent nutrient competition between individual symbiont cells, manifested as reduced nitrogen assimilation and cell biomass, likely creates the negative feedback mechanism for symbiont population growth that ultimately defines the steady-state density. Despite fundamental changes in symbiont nitrogen assimilation, we found no density-related metabolic optimum beyond which host nutrient assimilation or tissue biomass declined, indicating that host nutrient demand is sufficiently met across the typically observed range of symbiont densities under ambient conditions.
DOI: 10.6084/m9.figshare.11849157.v3
title: River and Infrastructure Connectivity Network (RICON)

description: River and Infrastructure Connectivity Network (RICON) – shows the dependency between streamgages and reservoirs as a concise edge list for the Colorado River Basin (CRB). The RICON dataset provides (1) a complete list of edges for the unidirectional network connecting streamgages, reservoirs and NHDPlusflowline features for CRB and (2) attributes of all nodes (reservoirs and streamgages) including their geospatial locations, unique identifiers, immediate upstream and downstream nodes, etc. The RICON data archive available at figshare contains the dataset tables in comma-separated values (CSV) format. Input files are 'sites_df.csv', 'nid_df.csv' and 'NHD_data.RData'. Output file is 'Edge_List.csv' <br>
DOI: 10.6084/m9.figshare.11848965.v3
title: Raw NanoSIMS data for host enrichment from autotrophy from Intracellular competition for nitrogen controls dinoflagellate population density in corals

description: The density of dinoflagellate microalgae in the tissue of symbiotic corals is an important determinant for health and productivity of the coral animal. Yet, the specific mechanism for their regulation and the consequence for coral nutrition are insufficiently understood due to past methodological limitations to resolve the fine-scale metabolic consequences of fluctuating densities. Here, we characterized the physiological and nutritional consequences of symbiont density variations on the colony and tissue level in <i>Stylophora pistillata</i> from the Red Sea. Alterations in symbiont photophysiology maintained coral productivity and host nutrition across a broad range of symbiont densities. However, we demonstrate that density-dependent nutrient competition between individual symbiont cells, manifested as reduced nitrogen assimilation and cell biomass, likely creates the negative feedback mechanism for symbiont population growth that ultimately defines the steady-state density. Despite fundamental changes in symbiont nitrogen assimilation, we found no density-related metabolic optimum beyond which host nutrient assimilation or tissue biomass declined, indicating that host nutrient demand is sufficiently met across the typically observed range of symbiont densities under ambient conditions.
DOI: 10.6084/m9.figshare.11849157.v4
title: River and Infrastructure Connectivity Network (RICON)

description: River and Infrastructure Connectivity Network (RICON) – shows the dependency between streamgages and reservoirs as a concise edge list for the Colorado River Basin (CRB). The RICON dataset provides (1) a complete list of edges for the unidirectional network connecting streamgages, reservoirs and NHDPlusflowline features for CRB and (2) attributes of all nodes (reservoirs and streamgages) including their geospatial locations, unique identifiers, immediate upstream and downstream nodes, etc. The RICON data archive available at figshare contains the dataset tables in comma-separated values (CSV) format. Input files are 'sites_df.csv', 'nid_df.csv' and 'NHD_data.RData'. Output file is 'Edge_List.csv' <br>
DOI: 10.6084/m9.figshare.11848965.v4
title: Raw data coral physiology from Intracellular competition for nitrogen controls dinoflagellate population density in corals

description: The density of dinoflagellate microalgae in the tissue of symbiotic corals is an important determinant for health and productivity of the coral animal. Yet, the specific mechanism for their regulation and the consequence for coral nutrition are insufficiently understood due to past methodological limitations to resolve the fine-scale metabolic consequences of fluctuating densities. Here, we characterized the physiological and nutritional consequences of symbiont density variations on the colony and tissue level in <i>Stylophora pistillata</i> from the Red Sea. Alterations in symbiont photophysiology maintained coral productivity and host nutrition across a broad range of symbiont densities. However, we demonstrate that density-dependent nutrient competition between individual symbiont cells, manifested as reduced nitrogen assimilation and cell biomass, likely creates the negative feedback mechanism for symbiont population growth that ultimately defines the steady-state density. Despite fundamental changes in symbiont nitrogen assimilation, we found no density-related metabolic optimum beyond which host nutrient assimilation or tissue biomass declined, indicating that host nutrient demand is sufficiently met across the typically observed range of symbiont densities under ambient conditions.
DOI: 10.25392/leicester.data.11848548
title: validator_2020-02-13.sql

description: Database containing VariantValidator data for use with https://github.com/openvar/variantValidator .
DOI: 10.6084/m9.figshare.11848533
title: Reitsma-AJPCell-11FEB20_Supplemental

description: AJP-Cell physiology Supplemental data (Feb2020)
DOI: 10.25392/leicester.data.11848548.v1
title: validator_2020-02-13.sql

description: Database containing VariantValidator data for use with https://github.com/openvar/variantValidator .
DOI: 10.6084/m9.figshare.11848533.v2
title: Reitsma-AJPCell-11FEB20_Supplemental

description: AJP-Cell physiology Supplemental data (Feb2020)
DOI: 10.6084/m9.figshare.11848533.v1
title: Reitsma-AJPCell-11FEB20_Supplemental

description: AJP-Cell physiology Supplemental data (Feb2020)
DOI: 10.6084/m9.figshare.11848371
title: Regression Modeling for Size-and-Shape Data Based on a Gaussian Model for Landmarks

description: In this article, we propose a regression model for size-and-shape response data. So far as we are aware, few such models have been explored in the literature to date. We assume a Gaussian model for labeled landmarks; these landmarks are used to represent the random objects under study. The regression structure, assumed in this article to be linear in the ambient space, enters through the landmark means. Two approaches to parameter estimation are considered. The first approach is based directly on the marginal likelihood for the landmark-based shapes. In the second approach, we treat the orientations of the landmarks as missing data, and we set up a model-consistent estimation procedure for the parameters using the EM algorithm. Both approaches raise challenging computational issues which we explain how to deal with. The usefulness of this regression modeling framework is demonstrated through real-data examples. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11848347
title: Fast Calibrated Additive Quantile Regression

description: We propose a novel framework for fitting additive quantile regression models, which provides well-calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diverse as those usable with distributional generalized additive models, while maintaining equivalent numerical efficiency and stability. The proposed methods are at once statistically rigorous and computationally efficient, because they are based on the general belief updating framework of Bissiri, Holmes, and Walker to loss based inference, but compute by adapting the stable fitting methods of Wood, Pya, and Säfken. We show how the pinball loss is statistically suboptimal relative to a novel smooth generalization, which also gives access to fast estimation methods. Further, we provide a novel calibration method for efficiently selecting the “learning rate” balancing the loss with the smoothing priors during inference, thereby obtaining reliable quantile uncertainty estimates. Our work was motivated by a probabilistic electricity load forecasting application, used here to demonstrate the proposed approach. The methods described here are implemented by the qgam R package, available on the Comprehensive R Archive Network (CRAN). Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11848371.v2
title: Regression Modeling for Size-and-Shape Data Based on a Gaussian Model for Landmarks

description: In this article, we propose a regression model for size-and-shape response data. So far as we are aware, few such models have been explored in the literature to date. We assume a Gaussian model for labeled landmarks; these landmarks are used to represent the random objects under study. The regression structure, assumed in this article to be linear in the ambient space, enters through the landmark means. Two approaches to parameter estimation are considered. The first approach is based directly on the marginal likelihood for the landmark-based shapes. In the second approach, we treat the orientations of the landmarks as missing data, and we set up a model-consistent estimation procedure for the parameters using the EM algorithm. Both approaches raise challenging computational issues which we explain how to deal with. The usefulness of this regression modeling framework is demonstrated through real-data examples. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11848284
title: Confidence at 100% Replication Dataset and Code

description: This is the replication dataset for https://doi.org/10.1111/acem.13930
DOI: 10.6084/m9.figshare.11848347.v2
title: Fast Calibrated Additive Quantile Regression

description: We propose a novel framework for fitting additive quantile regression models, which provides well-calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diverse as those usable with distributional generalized additive models, while maintaining equivalent numerical efficiency and stability. The proposed methods are at once statistically rigorous and computationally efficient, because they are based on the general belief updating framework of Bissiri, Holmes, and Walker to loss based inference, but compute by adapting the stable fitting methods of Wood, Pya, and Säfken. We show how the pinball loss is statistically suboptimal relative to a novel smooth generalization, which also gives access to fast estimation methods. Further, we provide a novel calibration method for efficiently selecting the “learning rate” balancing the loss with the smoothing priors during inference, thereby obtaining reliable quantile uncertainty estimates. Our work was motivated by a probabilistic electricity load forecasting application, used here to demonstrate the proposed approach. The methods described here are implemented by the qgam R package, available on the Comprehensive R Archive Network (CRAN). Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11848278.v1
title: Data associated with "Low-cost microphysiological systems: Feasibility study of a tape-based barrier-on-chip for small intestine modeling"

description: This repository contains the LC-MS data and processing described in our paper. Please cite the original article when using these data (DOI 10.1039/D0LC00009D )
DOI: 10.6084/m9.figshare.11848224
title: Extended data for 2019-nCoV

description: The data in this dataset support the findings in the paper entitled "Genomic and protein structure modelling analysis depicts the origin and pathogenicity of 2019-nCoV, a new coronavirus which caused a pneumonia outbreak in Wuhan, China"
DOI: 10.6084/m9.figshare.11848224.v1
title: Extended data for 2019-nCoV

description: The data in this dataset support the findings in the paper entitled "Genomic and protein structure modelling analysis depicts the origin and pathogenicity of 2019-nCoV, a new coronavirus which caused a pneumonia outbreak in Wuhan, China"
DOI: 10.6084/m9.figshare.11848137
title: Allelic differences of clustered terpene synthases contribute to correlated intra-specific variation of floral and herbivory-induced volatiles in a wild tobacco

description: This dataset contains raw data from a manuscript entitled: Allelic differences of clustered terpene synthases contribute to correlated intra-specific variation of floral and herbivory-induced volatiles in a wild tobacco by Xu et al.In this study, we characterized intra-specific variation of herbivory-induced plant volatiles (HIPVs), the key components of indirect defence against herbivores, and floral volatiles in the wild tobacco <i>Nicotiana attenuata</i>. We found that variation of (<i>E</i>)-β-ocimene and (<i>E</i>)-α-bergamotene contributed to the correlated changes in HIPVs and floral volatiles among <i>N. attenuata</i> natural accessions. Intra-specific variations of (<i>E</i>)-α-bergamotene and of (<i>E</i>)-β-ocimene emission resulted from allelic variation of two genetically co-localized terpene synthase genes, <i>NaTPS38</i> and <i>NaTPS25</i>, respectively. Analyzing haplotypes of <i>NaTPS38 </i>and<i> NaTPS25</i> revealed that allelic variations of <i>NaTPS25</i> and <i>NaTPS38</i> resulted in correlated changes of (<i>E</i>)-β-ocimene and (<i>E</i>)-α-bergamotene emission in HIPVs and floral volatiles in <i>N. attenuata</i>. Together, these results provide evidence that pleiotropy and genetic linkage can result in correlated changes in floral signals and defences in natural populations.
DOI: 10.6084/m9.figshare.11848137.v1
title: Allelic differences of clustered terpene synthases contribute to correlated intra-specific variation of floral and herbivory-induced volatiles in a wild tobacco

description: This dataset contains raw data from a manuscript entitled: Allelic differences of clustered terpene synthases contribute to correlated intra-specific variation of floral and herbivory-induced volatiles in a wild tobacco by Xu et al.In this study, we characterized intra-specific variation of herbivory-induced plant volatiles (HIPVs), the key components of indirect defence against herbivores, and floral volatiles in the wild tobacco <i>Nicotiana attenuata</i>. We found that variation of (<i>E</i>)-β-ocimene and (<i>E</i>)-α-bergamotene contributed to the correlated changes in HIPVs and floral volatiles among <i>N. attenuata</i> natural accessions. Intra-specific variations of (<i>E</i>)-α-bergamotene and of (<i>E</i>)-β-ocimene emission resulted from allelic variation of two genetically co-localized terpene synthase genes, <i>NaTPS38</i> and <i>NaTPS25</i>, respectively. Analyzing haplotypes of <i>NaTPS38 </i>and<i> NaTPS25</i> revealed that allelic variations of <i>NaTPS25</i> and <i>NaTPS38</i> resulted in correlated changes of (<i>E</i>)-β-ocimene and (<i>E</i>)-α-bergamotene emission in HIPVs and floral volatiles in <i>N. attenuata</i>. Together, these results provide evidence that pleiotropy and genetic linkage can result in correlated changes in floral signals and defences in natural populations.
DOI: 10.24431/rw1k46t
title: Growth data of Alaska SeaLife Center captive Steller's and spectacled eider ducklings in summers of 2015-2017

description: Data include Steller’s eider (Polysticta stelleri) and spectacled eider (Somateria fischeri) duckling growth data collected from birds reared at the Alaska SeaLife Center in Seward, Alaska during summers 2015-2017. Ducklings were weighed twice daily (09:00 and 21:00) during Days 1-14, daily (09:00) during Days 15-30, and every 3 days from Day 31-45 (Steller’s eiders) and 31-60 (spectacled eiders). Morphometric measurements (culmen, tarsus, 9th primary length) were taken every 3 days. Data are presented as two CSV files: 2016-2017_20SPEI_20mass_20morph_20data_March2018.csv 2015-2016_20STEI_20mass_20morph_20data_March2018.csv This dataset was generated as part of NPRB project 1518
DOI: 10.6084/m9.figshare.11847660
title: абитуриенты ВУЗов по ИИ.xlsx

description: bl a nblka
DOI: 10.6084/m9.figshare.11847660.v1
title: абитуриенты ВУЗов по ИИ.xlsx

description: bl a nblka
DOI: 10.6084/m9.figshare.11847633
title: HBCx_95_CapaR_scChIPseq_mm10.bam.bai

description: The samples correspond to the mouse cells from patient-derived xenograft (PDX) originating from two different human donors. The HBCx-22 and HBCx-22-TamR datasets correspond to mouse cells from a pair of luminal ER<sup>+</sup> breast PDXs: HBCx-22, responsive to Tamoxifen and HBCx-22-TamR, resistant to Tamoxifen. The HBCx-95 and HBCx-95-CapaR correspond to a triple-negative breast cancer (TNBC) tumor model of acquired resistance to chemotherapy. Row names of the matrices are 50,000-bp binned regions; Column names are barcodes corresponding to single cell; Cells contains raw counts, in mm10 reference. The BAM file were produced by a in-house pipeline, available at https://github.com/vallotlab/scChIPseq_DataEngineering
DOI: 10.6084/m9.figshare.11847636
title: HBCx_22_TamR_scChIPseq_mm10.bam.bai

description: The samples correspond to the mouse cells from patient-derived xenograft (PDX) originating from two different human donors. The HBCx-22 and HBCx-22-TamR datasets correspond to mouse cells from a pair of luminal ER<sup>+</sup> breast PDXs: HBCx-22, responsive to Tamoxifen and HBCx-22-TamR, resistant to Tamoxifen. The HBCx-95 and HBCx-95-CapaR correspond to a triple-negative breast cancer (TNBC) tumor model of acquired resistance to chemotherapy. Row names of the matrices are 50,000-bp binned regions; Column names are barcodes corresponding to single cell; Cells contains raw counts, in mm10 reference. The BAM file were produced by a in-house pipeline, available at https://github.com/vallotlab/scChIPseq_DataEngineering
DOI: 10.6084/m9.figshare.11847633.v1
title: HBCx_95_CapaR_scChIPseq_mm10.bam.bai

description: The samples correspond to the mouse cells from patient-derived xenograft (PDX) originating from two different human donors. The HBCx-22 and HBCx-22-TamR datasets correspond to mouse cells from a pair of luminal ER<sup>+</sup> breast PDXs: HBCx-22, responsive to Tamoxifen and HBCx-22-TamR, resistant to Tamoxifen. The HBCx-95 and HBCx-95-CapaR correspond to a triple-negative breast cancer (TNBC) tumor model of acquired resistance to chemotherapy. Row names of the matrices are 50,000-bp binned regions; Column names are barcodes corresponding to single cell; Cells contains raw counts, in mm10 reference. The BAM file were produced by a in-house pipeline, available at https://github.com/vallotlab/scChIPseq_DataEngineering