cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35077/add-tub
title: InOmBMN_LexA_head_posterior: Posterior head confocal imaging of fly driver line InOmBMN_LexA expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel

description: Confocal z-stacks (.tiff stacks) of transgenic driver lines that express in mechanosensory neurons innervating specific bristle populations on the Drosophila melanogaster head. The neurons that are targeted by each driver line were labeled by expressing mCD8::GFP under control of the UAS or LexAop promotors, and then stained using anti-GFP antibodies (green channel). Autofluorescence from the head cuticle is in the red channel. The processed images are published in Figure 3 and Figure 3 – figure supplement 1 of the manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”. The confocal stacks used to produce these images are organized based on the driver line used in each figure panel.
description: A full protocol describing this work is available in the associated manuscript at manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”.
description: Autofluorescence from the head cuticle is in the red channel DATASET METADATA: title:'InOmBMN_LexA_head_posterior: Posterior head confocal imaging of fly driver line InOmBMN_LexA expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel', GeneralModality:'other', Technique:'other', Other:'GAL4 and LexA expression' SPECIMEN METADATA: LocalID:'InOmBMN_LexA_head_posterior', Species:'Fruit fly', NCBITaxonomy:'NCBI:txid7227', Age:'5 to 8', Ageunit:'Days', Sex:'Male', Genotype:'w; VT017251_LexA (attP40)/+; 20XUAS-IVS- mCD8::GFP (attP2)/+', OrganName:'Peripheral (i.e. bristle mechanosensory neurons)', SampleLocalID:'20211123_VT01571_20x_UAS_GFP_20x_head_1', Locations:'Head peripheral nervous system (i.e. bristle mechanosensory neurons)' INSTRUMENT METADATA: MicroscopeType:'Confocal', MicroscopeManufacturerAndModel:'Zeiss LSM 800 Axio Imager.Z2', ObjectiveName:'Zeiss 20x objective (Plan-Apochromat 20x/0.8)', ObjectiveNA:'0.8', ObjectiveMagnification:'20x' IMAGE METADATA: xAxis:'left-to-right', yAxis:'left-to-right', zAxis:'left-to-right', Number:'1,2,red,green', displayColor:'(1.0, 0.0, 0.0),(0.0, 1.0, 0.0)', stepSizeX:'0.6239', stepSizeY:'0.6239'
DOI: 10.5517/ccdc.csd.cc2gcywp
title: CCDC 2275613: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Carsten Höltke, Roland Fröhlich, Gerhard Erker|2023|CSD Communication|||
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.cc2gfchs
title: CCDC 2276965: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Jens Müller, Roland Fröhlich, Gerhard Erker|2023|CSD Communication|||
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.cc2gg77f
title: CCDC 2277794: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Tuulamari Helaja, Roland Fröhlich, Gerhard Erker|2023|CSD Communication|||
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.cc2gg7gn
title: CCDC 2277801: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Stephan Göttke, Roland Fröhlich, Gerhard Erker|2023|CSD Communication|||
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: 10.21227/0vrd-pb52
title: A Control Architecture for Entanglement Generation Switches in Quantum Networks

description: Entanglement between quantum network nodes is often produced using intermediary devices- such as heralding stations - as a resource. When scaling quantum networks to many nodes, requiringa dedicated intermediary device for every pair of nodes introduces high costs. Here, we propose a cost-effective architecture to connect many quantum network nodes via a central quantum network hub calledan Entanglement Generation Switch (EGS). The EGS allows multiple quantum nodes to be connected at afixed resource cost, by sharing the resources needed to make entanglement. We propose an algorithm calledthe Rate Control Protocol (RCP) which moderates the level of competition for access to the hub’s resourcesbetween sets of users. We proceed to prove a convergence theorem for rates yielded by the algorithm. Toderive the algorithm we work in the framework of Network Utility Maximization (NUM) and make use ofthe theory of Lagrange multipliers and Lagrangian duality. Our EGS architecture lays the groundwork fordeveloping control architectures compatible with other types of quantum network hubs as well as systemmodels of greater complexity.
DOI: 10.5281/zenodo.7775944
title: Texas Ecological Mapping Systems (EMS) for Southern Texas Coastal Counties

description: We mapped 66 Ecological Mapping Systems (EMS) for eight coastal counties in south Texas, from Refugio and Aransas County south to the Mexican border. Land cover (LC), geophysical setting information, and woody vegetation height were all attributed to image objects derived from 10 m Sentinel-2 satellite imagery to model EMS type. A supervised process with training data collected from aerial photographs, aided by quantitative, species-specific, ground-collected virtual plot data, was used to classify LC in a RandomForest framework. Out of bag (OOB) error for LC was 15.24%. Recently collected LiDAR point cloud information was used to map height for woody vegetation, and the height was, in turn, used to distinguish between herbaceous, shrubland, and woodland/forest types via modification of LC results, and to define several canopy &gt;10 m versions of forested EMS types. Geophysical settings were mapped based primarily on the distribution of soil Map Units (MUs) from the national digital soil survey (gSSURGO). Elevation and potential ponding information were derived from analysis of LiDAR-derived digital elevation models (DEMs) as an aid in mapping several EMS types. Heads-up modification of both LC and EMS modeling results using aerial photograph interpretation improved results. The agreement between EMS mapped type and field-collected data (most 10 years old or more) was &gt;75%. The most abundant EMS types included Coastal and Sandsheet: Deep Sand Grassland (10.7% of the region), Native Invasive: Mesquite/Mixed Shrubland (5.0%), Gulf Coast: Coastal Prairie (4.6%), and South Texas: Sandy Mesquite Savanna Grassland (4.4%). The improved land cover, geophysical settings data, vegetation height data, and the use of finer-resolution image objects for modeling enabled mapping of all EMS types more accurately than previous datasets. The new EMS dataset will facilitate analysis and conservation of important habitats and modeling of species of concern that are tied to those habitats.
DOI: 10.5281/zenodo.7775943
title: Texas Ecological Mapping Systems (EMS) for Southern Texas Coastal Counties

description: We mapped 66 Ecological Mapping Systems (EMS) for eight coastal counties in south Texas, from Refugio and Aransas County south to the Mexican border. Land cover (LC), geophysical setting information, and woody vegetation height were all attributed to image objects derived from 10 m Sentinel-2 satellite imagery to model EMS type. A supervised process with training data collected from aerial photographs, aided by quantitative, species-specific, ground-collected virtual plot data, was used to classify LC in a RandomForest framework. Out of bag (OOB) error for LC was 15.24%. Recently collected LiDAR point cloud information was used to map height for woody vegetation, and the height was, in turn, used to distinguish between herbaceous, shrubland, and woodland/forest types via modification of LC results, and to define several canopy &gt;10 m versions of forested EMS types. Geophysical settings were mapped based primarily on the distribution of soil Map Units (MUs) from the national digital soil survey (gSSURGO). Elevation and potential ponding information were derived from analysis of LiDAR-derived digital elevation models (DEMs) as an aid in mapping several EMS types. Heads-up modification of both LC and EMS modeling results using aerial photograph interpretation improved results. The agreement between EMS mapped type and field-collected data (most 10 years old or more) was &gt;75%. The most abundant EMS types included Coastal and Sandsheet: Deep Sand Grassland (10.7% of the region), Native Invasive: Mesquite/Mixed Shrubland (5.0%), Gulf Coast: Coastal Prairie (4.6%), and South Texas: Sandy Mesquite Savanna Grassland (4.4%). The improved land cover, geophysical settings data, vegetation height data, and the use of finer-resolution image objects for modeling enabled mapping of all EMS types more accurately than previous datasets. The new EMS dataset will facilitate analysis and conservation of important habitats and modeling of species of concern that are tied to those habitats.
DOI: 10.5281/zenodo.8186558
title: To Preprint or Not to Preprint: A Global Researcher Survey

description: This data set contains the results of a survey about researchers’ adoption of and attitudes toward preprinting. The survey respondents are authors of journal articles published in 2021 and early 2022 and indexed in the Web of Science database. The questions in the survey are grouped into three sections: adoption of preprinting, attitudes toward preprinting, and demographic questions. The Word document contains the survey form. The Excel spreadsheet contains the raw survey data. Free-text responses are not included in the spreadsheet because they may reveal sensitive information. The "heatmap_Rdata.xlsx" and "heatmap_Rcode.txt" contain data and R code in Figs. 8, 9, 10. For more information about this data set, please see the paper "To Preprint or Not to Preprint: A Global Researcher Survey" by Rong Ni and Ludo Waltman. The paper is available at https://doi.org/10.31235/osf.io/k7reb.
DOI: 10.5281/zenodo.7845665
title: To Preprint or Not to Preprint: A Global Researcher Survey

description: This data set contains the results of a survey about researchers’ adoption of and attitudes toward preprinting. The survey respondents are authors of journal articles published in 2021 and early 2022 and indexed in the Web of Science database. The questions in the survey are grouped into three sections: adoption of preprinting, attitudes toward preprinting, and demographic questions. The Word document contains the survey form. The Excel spreadsheet contains the raw survey data. Free-text responses are not included in the spreadsheet because they may reveal sensitive information. The "heatmap_Rdata.xlsx" and "heatmap_Rcode.txt" contain data and R code in Figs. 8, 9, 10. For more information about this data set, please see the paper "To Preprint or Not to Preprint: A Global Researcher Survey" by Rong Ni and Ludo Waltman. The paper is available at https://doi.org/10.31235/osf.io/k7reb.
DOI: 10.13140/rg.2.2.18473.16484
title: Address of my blog "THE AGE OF MORAL ARIDITY AND INSENSITIVITY" - https://ethicsacademy.co.in/blog-the-creative-impulse/
DOI: 10.5066/p96vpbso
title: Evaluation of DNA yield from various sources for use in single nucleotide polymorphism panels

description: Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, micro-satellites have been the primary method, however, there currently is a shift from micro-satellites to single nucleotide polymorphisms (SNPs). With the DNA requirements being different, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in various panels. We found four sample categories that met the DNA requirements for use in all three panels, three sample categories that only met the DNA requirements for two panels, and one sample category that did not meet any of the three panels requirements. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates, tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction could influence DNA yield.
DOI: 10.5281/zenodo.8136995
title: ERA5 Cutout of the Western United States (y.2019)

description: 2019 ERA5 Cutout for Western United States for use in the pypsa-usa workflow Created Using the Atlite tool: Hofmann et al., (2021). atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series. Journal of Open Source Software, 6(62), 3294, https://doi.org/10.21105/joss.03294
DOI: 10.5281/zenodo.8136996
title: ERA5 Cutout of the Western United States (y.2019)

description: 2019 ERA5 Cutout for Western United States for use in the pypsa-usa workflow Created Using the Atlite tool: Hofmann et al., (2021). atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series. Journal of Open Source Software, 6(62), 3294, https://doi.org/10.21105/joss.03294
DOI: 10.5281/zenodo.8193136
title: ERA5 Cutout of the Western United States (y.2019)

description: 2019 ERA5 Cutout for Western United States for use in the pypsa-usa workflow Created Using the Atlite tool: Hofmann et al., (2021). atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series. Journal of Open Source Software, 6(62), 3294, https://doi.org/10.21105/joss.03294
DOI: 10.35077/add-tug
title: dBMN_spGAL4_head_anterior: Anterior head confocal imaging of fly driver line dBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel

description: Confocal z-stacks (.tiff stacks) of transgenic driver lines that express in mechanosensory neurons innervating specific bristle populations on the Drosophila melanogaster head. The neurons that are targeted by each driver line were labeled by expressing mCD8::GFP under control of the UAS or LexAop promotors, and then stained using anti-GFP antibodies (green channel). Autofluorescence from the head cuticle is in the red channel. The processed images are published in Figure 3 and Figure 3 – figure supplement 1 of the manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”. The confocal stacks used to produce these images are organized based on the driver line used in each figure panel.
description: A full protocol describing this work is available in the associated manuscript at manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”.
description: Autofluorescence from the head cuticle is in the red channel DATASET METADATA: title:'dBMN_spGAL4_head_anterior: Anterior head confocal imaging of fly driver line dBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel', GeneralModality:'other', Technique:'other', Other:'GAL4 and LexA expression' SPECIMEN METADATA: LocalID:'dBMN_spGAL4_head_anterior', Species:'Fruit fly', NCBITaxonomy:'NCBI:txid7227', Age:'5 to 8', Ageunit:'Days', Sex:'Male', Genotype:'w; VT019023_AD (attP40)/+; VT050279_DBD (attP2)/20XUAS-IVS- mCD8::GFP (attP2)', OrganName:'Peripheral (i.e. bristle mechanosensory neurons)', SampleLocalID:'20210906_VT050279_DBD_VT019023_AD_20xUAS_GFP_9_20x_front_head_2a', Locations:'Head peripheral nervous system (i.e. bristle mechanosensory neurons)' INSTRUMENT METADATA: MicroscopeType:'Confocal', MicroscopeManufacturerAndModel:'Zeiss LSM 800 Axio Imager.Z2', ObjectiveName:'Zeiss 20x objective (Plan-Apochromat 20x/0.8)', ObjectiveNA:'0.8', ObjectiveMagnification:'20x' IMAGE METADATA: xAxis:'left-to-right', yAxis:'left-to-right', zAxis:'left-to-right', Number:'1,2,red,green', displayColor:'(1.0, 0.0, 0.0),(0.0, 1.0, 0.0)', stepSizeX:'0.6239', stepSizeY:'0.6239'
DOI: 10.5066/p9i75nrs
title: Point Location of Myotis septentrionalis Echolocation Passes in Eastern North Carolina and Virginia

description: These data are the location and date of collection of endangered northern long-eared bat Myotis septentrionalis echolocation passes when the automated bat identification software assessed species presence at a maximum likelihood estimator p-value of less than or equal to 0.05 consistent with the U.S. Fish and Wildlife Service monitoring guideline standards.
DOI: 10.5517/ccdc.csd.cc2ghd8n
title: CCDC 2278911: Experimental Crystal Structure Determination

description: Related Article: Igor F. Perepichka, Martin R. Bryce, Dmitry S. Yufit|2023|CSD Communication|||
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: 10.35077/add-use
title: dBMN_spGAL4_head_posterior: Posterior head confocal imaging of fly driver line dBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel

description: Confocal z-stacks (.tiff stacks) of transgenic driver lines that express in mechanosensory neurons innervating specific bristle populations on the Drosophila melanogaster head. The neurons that are targeted by each driver line were labeled by expressing mCD8::GFP under control of the UAS or LexAop promotors, and then stained using anti-GFP antibodies (green channel). Autofluorescence from the head cuticle is in the red channel. The processed images are published in Figure 3 and Figure 3 – figure supplement 1 of the manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”. The confocal stacks used to produce these images are organized based on the driver line used in each figure panel.
description: A full protocol describing this work is available in the associated manuscript at manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”.
description: Autofluorescence from the head cuticle is in the red channel DATASET METADATA: title:'dBMN_spGAL4_head_posterior: Posterior head confocal imaging of fly driver line dBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel', GeneralModality:'other', Technique:'other', Other:'GAL4 and LexA expression' SPECIMEN METADATA: LocalID:'dBMN_spGAL4_head_posterior', Species:'Fruit fly', NCBITaxonomy:'NCBI:txid7227', Age:'5 to 8', Ageunit:'Days', Sex:'Male', Genotype:'w; VT019023_AD (attP40)/+; VT050279_DBD (attP2)/20XUAS-IVS- mCD8::GFP (attP2)', OrganName:'Peripheral (i.e. bristle mechanosensory neurons)', SampleLocalID:'20210325_VT050279_DBD_VT019023_AD_20xGFP_head_3', Locations:'Head peripheral nervous system (i.e. bristle mechanosensory neurons)' INSTRUMENT METADATA: MicroscopeType:'Confocal', MicroscopeManufacturerAndModel:'Zeiss LSM 800 Axio Imager.Z2', ObjectiveName:'Zeiss 20x objective (Plan-Apochromat 20x/0.8)', ObjectiveNA:'0.8', ObjectiveMagnification:'20x' IMAGE METADATA: xAxis:'left-to-right', yAxis:'left-to-right', zAxis:'left-to-right', Number:'1,2,red,green', displayColor:'(1.0, 0.0, 0.0),(0.0, 1.0, 0.0)', stepSizeX:'0.6239', stepSizeY:'0.6239'
DOI: 10.35077/add-van
title: pBMN_spGAL4_head_posterior: Posterior head confocal imaging of fly driver line pBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel

description: Confocal z-stacks (.tiff stacks) of transgenic driver lines that express in mechanosensory neurons innervating specific bristle populations on the Drosophila melanogaster head. The neurons that are targeted by each driver line were labeled by expressing mCD8::GFP under control of the UAS or LexAop promotors, and then stained using anti-GFP antibodies (green channel). Autofluorescence from the head cuticle is in the red channel. The processed images are published in Figure 3 and Figure 3 – figure supplement 1 of the manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”. The confocal stacks used to produce these images are organized based on the driver line used in each figure panel.
description: A full protocol describing this work is available in the associated manuscript at manuscript “Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila (https://doi.org/10.1101/2023.02.11.528119)”.
description: Autofluorescence from the head cuticle is in the red channel DATASET METADATA: title:'pBMN_spGAL4_head_posterior: Posterior head confocal imaging of fly driver line pBMN_spGAL4 expressing mCD8::GFP, stained using anti GFP antibodies (green channel) - Autofluorescence from the head cuticle is in the red channel', GeneralModality:'other', Technique:'other', Other:'GAL4 and LexA expression' SPECIMEN METADATA: LocalID:'pBMN_spGAL4_head_posterior', Species:'Fruit fly', NCBITaxonomy:'NCBI:txid7227', Age:'5 to 8', Ageunit:'Days', Sex:'Male', Genotype:'w; 28D07_AD (attP40); VT050279_DBD (attP2)/20XUAS-IVS- mCD8::GFP (attP2)', OrganName:'Peripheral (i.e. bristle mechanosensory neurons)', SampleLocalID:'20210322_VT050279_DBD_28D07_AD_20x_GFP_head_6b', Locations:'Head peripheral nervous system (i.e. bristle mechanosensory neurons)' INSTRUMENT METADATA: MicroscopeType:'Confocal', MicroscopeManufacturerAndModel:'Zeiss LSM 800 Axio Imager.Z2', ObjectiveName:'Zeiss 20x objective (Plan-Apochromat 20x/0.8)', ObjectiveNA:'0.8', ObjectiveMagnification:'20x' IMAGE METADATA: xAxis:'left-to-right', yAxis:'left-to-right', zAxis:'left-to-right', Number:'1,2,red,green', displayColor:'(1.0, 0.0, 0.0),(0.0, 1.0, 0.0)', stepSizeX:'0.6239', stepSizeY:'0.6239'