cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24776863
title: Generative Multi-Purpose Sampler for Weighted M-estimation

description: To overcome computational bottlenecks of various data perturbation procedures such as the bootstrap and cross-validations, we propose the <i>Generative Multi-purpose Sampler</i> (GMS), which directly constructs a generator function to produce solutions of weighted M-estimators from a set of given weights and tuning parameters. The GMS is implemented by a single optimization procedure without having to repeatedly evaluate the minimizers of weighted losses, and is thus capable of significantly reducing the computational time. We demonstrate that the GMS framework enables the implementation of various statistical procedures that would be unfeasible in a conventional framework, such as iterated bootstrap procedures and cross-validation for penalized likelihood. To construct a computationally efficient generator function, we also propose a novel form of neural network called the <i>weight multiplicative multilayer perceptron</i> to achieve fast convergence. An R package called GMS is provided, which runs under Pytorch to implement the proposed methods and allows the user to provide a customized loss function to tailor to their own models of interest. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24776863.v2
title: Generative Multi-Purpose Sampler for Weighted M-estimation

description: To overcome computational bottlenecks of various data perturbation procedures such as the bootstrap and cross-validations, we propose the <i>Generative Multi-purpose Sampler</i> (GMS), which directly constructs a generator function to produce solutions of weighted M-estimators from a set of given weights and tuning parameters. The GMS is implemented by a single optimization procedure without having to repeatedly evaluate the minimizers of weighted losses, and is thus capable of significantly reducing the computational time. We demonstrate that the GMS framework enables the implementation of various statistical procedures that would be unfeasible in a conventional framework, such as iterated bootstrap procedures and cross-validation for penalized likelihood. To construct a computationally efficient generator function, we also propose a novel form of neural network called the <i>weight multiplicative multilayer perceptron</i> to achieve fast convergence. An R package called GMS is provided, which runs under Pytorch to implement the proposed methods and allows the user to provide a customized loss function to tailor to their own models of interest. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.24776863.v1
title: Generative Multi-purpose Sampler for Weighted M-estimation

description: To overcome computational bottlenecks of various data perturbation procedures such as the bootstrap and cross validations, we propose the <i>Generative Multi-purpose Sampler</i> (GMS), which directly constructs a generator function to produce solutions of weighted M-estimators from a set of given weights and tuning parameters. The GMS is implemented by a single optimization procedure without having to repeatedly evaluate the minimizers of weighted losses, and is thus capable of significantly reducing the computational time. We demonstrate that the GMS framework enables the implementation of various statistical procedures that would be unfeasible in a conventional framework, such as iterated bootstrap procedures and cross-validation for penalized likelihood. To construct a computationally efficient generator function, we also propose a novel form of neural network called the <i>weight multiplicative multilayer perceptron</i> to achieve fast convergence. An R package called GMS is provided, which runs under Pytorch to implement the proposed methods and allows the user to provide a customized loss function to tailor to their own models of interest.
DOI: 10.34740/kaggle/dsv/7423113
title: Forex Exchange Rates Since 2004 (Updated Daily)
DOI: 10.34740/kaggle/dsv/7423124
title: Top Spotify Songs in 73 Countries (Daily Updated)
DOI: 10.6084/m9.figshare.25015871
title: sUAV RGB dataset

description: sUAV dataset
DOI: 10.6084/m9.figshare.25015871.v1
title: sUAV RGB dataset

description: sUAV dataset
DOI: 10.6084/m9.figshare.24992766.v1
title: <b>SI data for "</b><b>Quantitative Characterization of Stringency in SELEX</b><b>"</b>

description: The files include the following:Calculation of <i>BNR</i> and <i>R</i> values obtained in SELEX for MutS and thrombin Figures in main text and SI (Origin and png files)
DOI: 10.34740/kaggle/dsv/7423155
title: Full TMDB Movies Dataset 2023 (930K Movies)
DOI: 10.25345/c5ww7799g
title: MassIVE MSV000093879 - Bottini Phos testing if works with phospho data thanks
title: testing if this works for phospho data because this data set has been particularly difficult to upload
DOI: 10.34740/kaggle/dsv/7423181
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.5281/zenodo.10524970
title: Bibliography of S.R. Ranganathan 1961-1961 based on Dasgupta 1967

description: A bibliography of the works of S.R. Ranganathan from 1916 to 1961 produced by Zotero and based on the work Dasgupta, A. K. ed. 1967. An essay in personal bibliography: Ranganathan Festschrift, Volume 2, A bibliography of the writings on and by Dr S R Ranganathan. Bombay: Asia Publishing House.
DOI: 10.5281/zenodo.10524971
title: Bibliography of S.R. Ranganathan 1961-1961 based on Dasgupta 1967

description: A bibliography of the works of S.R. Ranganathan from 1916 to 1961 produced by Zotero and based on the work Dasgupta, A. K. ed. 1967. An essay in personal bibliography: Ranganathan Festschrift, Volume 2, A bibliography of the writings on and by Dr S R Ranganathan. Bombay: Asia Publishing House.
DOI: 10.6084/m9.figshare.25013984
title: physical_interactions_mitab_fb_2023_01.tsv

description: This file is a PSI-MI TAB format molecular interactions file from FlyBase release FB2023_01 reporting pairwise physical interactions between gene products (protein-protein, protein-RNA or RNA-RNA).
DOI: 10.6084/m9.figshare.25013984.v1
title: physical_interactions_mitab_fb_2023_01.tsv

description: This file is a PSI-MI TAB format molecular interactions file from FlyBase release FB2023_01 reporting pairwise physical interactions between gene products (protein-protein, protein-RNA or RNA-RNA).
DOI: 10.6084/m9.figshare.25013978
title: pathway_group_data_fb_2023_01.tsv

description: This file reports all Pathway Gene Groups in FlyBase (release 2023_01), together with their hierarchical relationships (where relevant) and member genes.
DOI: 10.6084/m9.figshare.25013978.v1
title: pathway_group_data_fb_2023_01.tsv

description: This file reports all Pathway Gene Groups in FlyBase (release 2023_01), together with their hierarchical relationships (where relevant) and member genes.
DOI: 10.6084/m9.figshare.25013975
title: gene_group_data_fb_2023_01.tsv

description: This file reports Gene Groups in FlyBase (release 2023_01), together with their hierarchical relationships (where relevant) and member genes.
DOI: 10.6084/m9.figshare.25013975.v1
title: gene_group_data_fb_2023_01.tsv

description: This file reports Gene Groups in FlyBase (release 2023_01), together with their hierarchical relationships (where relevant) and member genes.
DOI: 10.5281/zenodo.10524899
title: Supplementary Data: Diversity of bacterial symbionts associated with the tropical plant bug Monalonion velezangeli (Hemiptera: Miridae) revealed by high-throughput 16S-rRNA sequencing

description: Supplementary data: Tables and Figures
DOI: 10.5281/zenodo.10524999
title: DFT calculations with VASP
DOI: 10.5281/zenodo.10525000
title: DFT calculations with VASP
DOI: 10.5281/zenodo.10524955
title: Life cycle inventory database for consumption in Quebec - Personal hygiene

description: These inventory datasets are essential for calculating the environmental impacts of an individual’s consumption in Quebec.

Led by the CIRAIG, in collaboration with ESG-UQAM, this project aims to develop an inventory database of the life cycle of consumption in Quebec. These inventory datasets are essential for calculating the carbon footprint of an individual’s consumption in Quebec. The inventory is developed with a life cycle approach. Ultimately, it allows for evaluating carbon footprints at every step of the consumption life cycle (extraction of primary sources, transformation, transport, use of goods and services, end of life). The inventory is developed in a modular fashion for the different areas of individual consumption as Food; Transport; Housing; Clothing; Travel; Communications; Entertainment and Culture; Financial and Administrative Management; Health, Hygiene, and Beauty. These areas are developed and detailed as a priority, as they contribute most to an individual’s carbon footprint in Quebec. Other non-priority areas are roughly modelled in order to provide a complete (but more uncertain) portrait of individual consumption. The project is underway and the deliverables will be made available online as things progress. It is not, however, an objective of the project to create a carbon footprint calculation tool at the moment.

https://ciraig.org/index.php/project/life-cycle-inventory-database-for-consumption-in-quebec/
DOI: 10.5281/zenodo.10524954
title: Life cycle inventory database for consumption in Quebec - Personal hygiene

description: These inventory datasets are essential for calculating the environmental impacts of an individual’s consumption in Quebec.

Led by the CIRAIG, in collaboration with ESG-UQAM, this project aims to develop an inventory database of the life cycle of consumption in Quebec. These inventory datasets are essential for calculating the carbon footprint of an individual’s consumption in Quebec. The inventory is developed with a life cycle approach. Ultimately, it allows for evaluating carbon footprints at every step of the consumption life cycle (extraction of primary sources, transformation, transport, use of goods and services, end of life). The inventory is developed in a modular fashion for the different areas of individual consumption as Food; Transport; Housing; Clothing; Travel; Communications; Entertainment and Culture; Financial and Administrative Management; Health, Hygiene, and Beauty. These areas are developed and detailed as a priority, as they contribute most to an individual’s carbon footprint in Quebec. Other non-priority areas are roughly modelled in order to provide a complete (but more uncertain) portrait of individual consumption. The project is underway and the deliverables will be made available online as things progress. It is not, however, an objective of the project to create a carbon footprint calculation tool at the moment.

https://ciraig.org/index.php/project/life-cycle-inventory-database-for-consumption-in-quebec/
DOI: 10.25592/uhhfdm.13933
title: Dataset to: Environmental controls of dark CO2 fixation in wetland microbiomes

description: This dataset supports the paper: "Environmental controls of dark CO<sub>2</sub> fixation in wetland microbiota".

It contains genecluster abundances, annotations, taxonomy and membership for the metagenomic and metatranscriptomic analyses aswell as ASV tables for the 16S rRNA gene analyses.
description: This study was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Research Training Group2530: "Biota-mediated effects on Carbon cycling in Estuaries" (project number 407270017; contribution to Universität Hamburg and Leibniz-Institut für Gewässerökologie und Binnenfischerei im Forschungsverbund Berlin e.V.).
This work was supported by the DFG Research Infrastructure NGS_CC (project 407495230) as part of the Next Generation Sequencing Competence Network (project 423957469) and core funding from ETH Zürich to the Microbiome Research Laboratory headed by S.S. Transcriptome and 16S rRNA sequencing were carried out at the Competence Centre for Genomic Analysis (Kiel).
Peter Mueller was supported by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) in the framework of the Emmy Noether Program (502681570).
DOI: 10.25592/uhhfdm.12482
title: Dataset to: Environmental controls of dark CO2 fixation in wetland microbiomes

description: This dataset supports the paper: "Environmental controls of dark CO<sub>2</sub> fixation in wetland microbiota".

It contains genecluster abundances, annotations, taxonomy and membership for the metagenomic and metatranscriptomic analyses aswell as ASV tables for the 16S rRNA gene analyses.
description: This study was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) within the Research Training Group2530: "Biota-mediated effects on Carbon cycling in Estuaries" (project number 407270017; contribution to Universität Hamburg and Leibniz-Institut für Gewässerökologie und Binnenfischerei im Forschungsverbund Berlin e.V.).
This work was supported by the DFG Research Infrastructure NGS_CC (project 407495230) as part of the Next Generation Sequencing Competence Network (project 423957469) and core funding from ETH Zürich to the Microbiome Research Laboratory headed by S.S. Transcriptome and 16S rRNA sequencing were carried out at the Competence Centre for Genomic Analysis (Kiel).
Peter Mueller was supported by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) in the framework of the Emmy Noether Program (502681570).
DOI: 10.34740/kaggle/dsv/7423236
title: customer_segmentation_total
DOI: 10.5281/zenodo.10524989
title: Dataset of observations of Trichocera maculipennis (Diptera) in Navarino Island (Cape Horn Biosphere Reserve), Chile

description: During the 2022/23 austral winter, large swarms of Trichocera (Saltrichocera) maculipennis Meigen, 1818 (Diptera: Trichoceridae) were observed around house roofs in Puerto Williams (Navarino Island, southern Chile, 54°S). In January 2023, the presence of this species was also confirmed in Punta Arenas (53°S), with specimens collected within Chilean Antarctic Institute (INACH) warehouse facilities. No swarms or individuals have yet been observed in other urban or rural areas around Punta Arenas. Trichocera maculipennis is native to the Holarctic region and became established on King George Island (South Shetland Islands, Maritime Antarctic) over 15 years ago. The source of the King George Island population has not yet been confirmed, although a South American logistics hub is regarded as the most plausible. However, the species has not previously been reported from South America. Taxonomic and molecular identification techniques were used to confirm the identity of the new specimens obtained from Navarino Island and Punta Arenas. Preliminary observations of the fly’s habitat preferences and swarming behavior in Puerto Williams are provided, as well as comparisons in wing morphometrics between flies from Puerto Williams and King George Island. The fly's extensive distribution and high abundance in Puerto Williams are consistent with human-facilitated introduction and several years’ establishment. The most likely source of colonization event(s) to Puerto Williams is/are from an as yet unreported southern Chilean source population, with the new observations of small numbers of individuals in Punta Arenas being consistent with this. Such a source is also most plausible for King George Island. An alternative, less plausible, hypothesis is of ‘back transfer’ from King George Island to continental South America, although this does not give a clear direct link with Puerto Williams. These new observations highlight the urgent need for survey work particularly around human settlements in the Cape Horn archipelago and elsewhere in southern Patagonia and Tierra del Fuego, to better understand the invasive potential and possible routes for colonization of this species. These findings emphasize the importance of implementing robust management strategies and biosecurity measures, particularly during transportation between logistical hubs in southern South America and the remote areas of the Cape Horn Biosphere Reserve and Antarctica.
DOI: 10.5281/zenodo.10524990
title: Dataset of observations of Trichocera maculipennis (Diptera) in Navarino Island (Cape Horn Biosphere Reserve), Chile

description: During the 2022/23 austral winter, large swarms of Trichocera (Saltrichocera) maculipennis Meigen, 1818 (Diptera: Trichoceridae) were observed around house roofs in Puerto Williams (Navarino Island, southern Chile, 54°S). In January 2023, the presence of this species was also confirmed in Punta Arenas (53°S), with specimens collected within Chilean Antarctic Institute (INACH) warehouse facilities. No swarms or individuals have yet been observed in other urban or rural areas around Punta Arenas. Trichocera maculipennis is native to the Holarctic region and became established on King George Island (South Shetland Islands, Maritime Antarctic) over 15 years ago. The source of the King George Island population has not yet been confirmed, although a South American logistics hub is regarded as the most plausible. However, the species has not previously been reported from South America. Taxonomic and molecular identification techniques were used to confirm the identity of the new specimens obtained from Navarino Island and Punta Arenas. Preliminary observations of the fly’s habitat preferences and swarming behavior in Puerto Williams are provided, as well as comparisons in wing morphometrics between flies from Puerto Williams and King George Island. The fly's extensive distribution and high abundance in Puerto Williams are consistent with human-facilitated introduction and several years’ establishment. The most likely source of colonization event(s) to Puerto Williams is/are from an as yet unreported southern Chilean source population, with the new observations of small numbers of individuals in Punta Arenas being consistent with this. Such a source is also most plausible for King George Island. An alternative, less plausible, hypothesis is of ‘back transfer’ from King George Island to continental South America, although this does not give a clear direct link with Puerto Williams. These new observations highlight the urgent need for survey work particularly around human settlements in the Cape Horn archipelago and elsewhere in southern Patagonia and Tierra del Fuego, to better understand the invasive potential and possible routes for colonization of this species. These findings emphasize the importance of implementing robust management strategies and biosecurity measures, particularly during transportation between logistical hubs in southern South America and the remote areas of the Cape Horn Biosphere Reserve and Antarctica.
DOI: 10.6084/m9.figshare.25016108
title: Agent_Based_Indoor

description: COVID_19 Agent Based Modeling Dataset
DOI: 10.6084/m9.figshare.25016108.v1
title: Agent_Based_Indoor

description: COVID_19 Agent Based Modeling Dataset
DOI: 10.5517/ccdc.csd.cc27j2b6
title: CCDC 2071027: Experimental Crystal Structure Determination

description: Related Article: Sourabh Bera, Parthasarathi Dastidar|2023|Chem.-Eur.J.|29|e202203133|doi:10.1002/chem.202203133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d3zn5
title: CCDC 2208367: Experimental Crystal Structure Determination

description: Related Article: Sourabh Bera, Parthasarathi Dastidar|2023|Chem.-Eur.J.|29|e202203133|doi:10.1002/chem.202203133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d45h7
title: CCDC 2208548: Experimental Crystal Structure Determination

description: Related Article: Niklas Grabicki, Sergey Fisher, Oliver Dumele|2023|Angew.Chem.,Int.Ed.|62|e202217917|doi:10.1002/anie.202217917
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d4s6k
title: CCDC 2209128: Experimental Crystal Structure Determination

description: Related Article: Niklas Grabicki, Sergey Fisher, Oliver Dumele|2023|Angew.Chem.,Int.Ed.|62|e202217917|doi:10.1002/anie.202217917
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c4tp1
title: CCDC 2179383: Experimental Crystal Structure Determination

description: Related Article: Jack A. Davies, Andrew Tarzia, Tanya K. Ronson, Florian Auras, Kim E. Jelfs, Jonathan Russell Nitschke|2023|Angew.Chem.,Int.Ed.|62|e202217987|doi:10.1002/anie.202217987
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d5sv7
title: CCDC 2210109: Experimental Crystal Structure Determination

description: Related Article: Apurva A. Pradhan, Madeleine C. Uible, Shubhanshu Agarwal, Jonathan W. Turnley, Shriya Khandelwal, Jonas M. Peterson, Daria D. Blach, Ryan N. Swope, Libai Huang, Suzanne C. Bart, Rakesh Agrawal|2023|Angew.Chem.,Int.Ed.|62|e202301049|doi:10.1002/anie.202301049
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d5syb
title: CCDC 2210112: Experimental Crystal Structure Determination

description: Related Article: Apurva A. Pradhan, Madeleine C. Uible, Shubhanshu Agarwal, Jonathan W. Turnley, Shriya Khandelwal, Jonas M. Peterson, Daria D. Blach, Ryan N. Swope, Libai Huang, Suzanne C. Bart, Rakesh Agrawal|2023|Angew.Chem.,Int.Ed.|62|e202301049|doi:10.1002/anie.202301049
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.