cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35078/qo1arh/lncazw
title: Cab.Santo Antônio A.jpg

description: :unav
DOI: 10.35078/qo1arh/sch3zw
title: Córrego do Fonseca B.jpg

description: :unav
DOI: 10.35078/qo1arh/k8sksq
title: DICIONARIO_KARDEX_PROGRAMA_CONTROLE_DOENÇA_CHAGAS.pdf

description: Dicionário para interpretação da ficha epidemiologica (Kardex)
DOI: 10.5281/zenodo.6492069
title: Dataset of the paper "An Empirical Characterization of Software Bugs in Open-Source Cyber-Physical Systems"

description: <br> #Dataset Package for the paper "An Empirical Characterization of Software Bugs in Open-Source Cyber-Physical Systems" <br> Description of the content: <br> 1) "1_RQ-CPS-bugs-Taxonomy" folder contains all the main experimental data concerning the issues sampled and analyzed from all the Projects considered in the study,<br> including row-data on the taxonomy validtion steps.<br> <br> - Under "the sub-folder "1_Taxonomy-Raw-data" are reported the row-data concerning the taxonomy validtion steps <br> 2) "2_Scripts" contains all scripts used to generate the issue data and sampled issue raw-data in the previous folders: <br> - "setup.md" file in the folder describes how to set=up and run the script used for collecting and sampling the issues for the validation steps:<br> <br> - runJSONtoCSV.sh<br> - JSONtoCSV.py<br> - generateListOfAllSamples.py<br> - generateAllSamples.r<br> <br> Under "the sub-folder "1_Scripts/1_Data_Collection":<br> <br> <br> 3) "3_Final Taxonomy" folder contains the final Table representation (also reported in the previous folder) and main figures of the CPSs Bugs Taxonomy.
description: We thank Remy Egloff, Jan Willi, Davide Fontanella, Stefano Anzolut for their help in the labeling of GitHub issues. We gratefully acknowledges the Horizon 2020 (EU Commission) support for the project COSMOS (DevOps for Complex Cyber-physical Systems), Project No. 957254-COSMOS.
DOI: 10.5281/zenodo.4478387
title: Dataset of the paper "An Empirical Characterization of Software Bugs in Open-Source Cyber-Physical Systems"

description: <br> #Dataset Package for the paper "An Empirical Characterization of Software Bugs in Open-Source Cyber-Physical Systems" <br> Description of the content: <br> 1) "1_RQ-CPS-bugs-Taxonomy" folder contains all the main experimental data concerning the issues sampled and analyzed from all the Projects considered in the study,<br> including row-data on the taxonomy validtion steps.<br> <br> - Under "the sub-folder "1_Taxonomy-Raw-data" are reported the row-data concerning the taxonomy validtion steps <br> 2) "2_Scripts" contains all scripts used to generate the issue data and sampled issue raw-data in the previous folders: <br> - "setup.md" file in the folder describes how to set=up and run the script used for collecting and sampling the issues for the validation steps:<br> <br> - runJSONtoCSV.sh<br> - JSONtoCSV.py<br> - generateListOfAllSamples.py<br> - generateAllSamples.r<br> <br> Under "the sub-folder "1_Scripts/1_Data_Collection":<br> <br> <br> 3) "3_Final Taxonomy" folder contains the final Table representation (also reported in the previous folder) and main figures of the CPSs Bugs Taxonomy.
description: We thank Remy Egloff, Jan Willi, Davide Fontanella, Stefano Anzolut for their help in the labeling of GitHub issues. We gratefully acknowledges the Horizon 2020 (EU Commission) support for the project COSMOS (DevOps for Complex Cyber-physical Systems), Project No. 957254-COSMOS.
DOI: 10.25921/86wm-b746
title: AZFP Water Column Sonar Data Collected During ar040-jax-5146 Deployment
DOI: 10.5281/zenodo.6490866
title: Optocoder: computational decoding of spatially indexed bead arrays

description: Spatial transcriptomics technologies that can quantify gene expression in space are transforming contemporary biology research. Some of such methods use spatially barcoded bead arrays that are optically sequenced by a microscopy setup to detect bead barcodes in space which can be consecutively matched to cell barcodes from the respective single cell sequencing experiment. To have good quality barcodes and a high number of barcode matches in space, robust and efficient computational pipelines are needed to process raw microscopy images and call the bases of bead barcodes accurately. Here, we present Optocoder, a computational pipeline that takes raw optical sequencing microscopy images as input and outputs bead barcodes in space. Optocoder efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal such as crosstalk and phasing before base calling. Furthermore, we implement a machine learning pipeline that is trained using the signal from the beads that match to illumina barcodes in order to predict non-matching bead barcodes which can boost up the number of barcode matches. We benchmark Optocoder using data from an in-house spatial transcriptomics platform as well as data from the Slide-seq method and we show that it can efficiently process both datasets with minimal modification. Here, the datasets deposited include the following: <strong>optocoder_data:</strong> the imaging and illumina data that are used for Optocoder runs. Folder structure is as following: <strong>imaging:</strong> the images acquired via a two laser microscopy setup during the optical sequencing process . There are four pucks (P1, P2, P3, P4) and for every puck there are 12 images where every image corresponds to one cycle of optical sequencing. Every image is a 6-channel TIFF image. <strong>illumina: </strong>cell barcodes from library sequencing that are used for the matching <strong>external: </strong>bead optical barcodes for the Slide-Seq and Slide-SeqV2 <strong>optocoder_v0.1.1_output: </strong>these are the output files from Optocoder runs for both in-house and Slide-Seq samples , and are used to generate the figures in the publication. Scripts to generate the figures are deposited here: https://github.com/rajewsky-lab/optocoder_scripts
DOI: 10.21227/1jse-9132
title: An Impedance-based Pole-zero Method for Estimating Complex Material Parameters of Piezoceramic Plates

description: Research data and codes
DOI: 10.6084/m9.figshare.19625271.v1
title: Underlying additional data

description: The datasets describe the keywords and search strategy used to find lower limb exercises for AOT, interview guide used to assess the participants' experience of the intervention and the feasibility metrics definitions used for testing AOT administration in stroke survivors.
DOI: 10.5281/zenodo.6492306
title: Optocoder: computational decoding of spatially indexed bead arrays

description: Spatial transcriptomics technologies that can quantify gene expression in space are transforming contemporary biology research. Some of such methods use spatially barcoded bead arrays that are optically sequenced by a microscopy setup to detect bead barcodes in space which can be consecutively matched to cell barcodes from the respective single cell sequencing experiment. To have good quality barcodes and a high number of barcode matches in space, robust and efficient computational pipelines are needed to process raw microscopy images and call the bases of bead barcodes accurately. Here, we present Optocoder, a computational pipeline that takes raw optical sequencing microscopy images as input and outputs bead barcodes in space. Optocoder efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal such as crosstalk and phasing before base calling. Furthermore, we implement a machine learning pipeline that is trained using the signal from the beads that match to illumina barcodes in order to predict non-matching bead barcodes which can boost up the number of barcode matches. We benchmark Optocoder using data from an in-house spatial transcriptomics platform as well as data from the Slide-seq method and we show that it can efficiently process both datasets with minimal modification. Here, the datasets deposited include the following: <strong>optocoder_data:</strong> the imaging and illumina data that are used for Optocoder runs. Folder structure is as following: <strong>imaging:</strong> the images acquired via a two laser microscopy setup during the optical sequencing process . There are four pucks (P1, P2, P3, P4) and for every puck there are 12 images where every image corresponds to one cycle of optical sequencing. Every image is a 6-channel TIFF image. <strong>illumina: </strong>cell barcodes from library sequencing that are used for the matching <strong>external: </strong>bead optical barcodes for the Slide-Seq and Slide-SeqV2 <strong>optocoder_v0.1.1_output: </strong>these are the output files from Optocoder runs for both in-house and Slide-Seq samples , and are used to generate the figures in the publication. Scripts to generate the figures are deposited here: https://github.com/rajewsky-lab/optocoder_scripts <strong>run1_optocoder_v0.1.1_config_files: </strong>example config files for the optocoder run files.
DOI: 10.5281/zenodo.5850813
title: Optocoder: computational decoding of spatially indexed bead arrays

description: Spatial transcriptomics technologies that can quantify gene expression in space are transforming contemporary biology research. Some of such methods use spatially barcoded bead arrays that are optically sequenced by a microscopy setup to detect bead barcodes in space which can be consecutively matched to cell barcodes from the respective single cell sequencing experiment. To have good quality barcodes and a high number of barcode matches in space, robust and efficient computational pipelines are needed to process raw microscopy images and call the bases of bead barcodes accurately. Here, we present Optocoder, a computational pipeline that takes raw optical sequencing microscopy images as input and outputs bead barcodes in space. Optocoder efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal such as crosstalk and phasing before base calling. Furthermore, we implement a machine learning pipeline that is trained using the signal from the beads that match to illumina barcodes in order to predict non-matching bead barcodes which can boost up the number of barcode matches. We benchmark Optocoder using data from an in-house spatial transcriptomics platform as well as data from the Slide-seq method and we show that it can efficiently process both datasets with minimal modification. Here, the datasets deposited include the following: <strong>optocoder_data:</strong> the imaging and illumina data that are used for Optocoder runs. Folder structure is as following: <strong>imaging:</strong> the images acquired via a two laser microscopy setup during the optical sequencing process . There are four pucks (P1, P2, P3, P4) and for every puck there are 12 images where every image corresponds to one cycle of optical sequencing. Every image is a 6-channel TIFF image. <strong>illumina: </strong>cell barcodes from library sequencing that are used for the matching <strong>external: </strong>bead optical barcodes for the Slide-Seq and Slide-SeqV2 <strong>optocoder_v0.1.1_output: </strong>these are the output files from Optocoder runs for both in-house and Slide-Seq samples , and are used to generate the figures in the publication. Scripts to generate the figures are deposited here: https://github.com/rajewsky-lab/optocoder_scripts <strong>run1_optocoder_v0.1.1_config_files: </strong>example config files for the optocoder run files.
DOI: 10.15784/601556
title: Salmon Valley Radiocarbon Data

description: This dataset includes radiocarbon dates of benthic algal mats associated with last glacial maximum Ross Sea drift in Salmon Valley, Royal Society Range.
DOI: 10.14469/hpc/10389
title: BF3.OEt2 in pyridine. wB97XD/aug-cc-pvdz, B Isotropic =

description: Gaussian 16 (C01) calculation
DOI: 10.5281/zenodo.896921
title: IN00005 Vidisa Inscription of Ramagupta on the Image of Candraprabha

description: IN00005 Bhandarkar, Devadatta Ramakrishna, Bahadur Chand Chhabra, and Govind Swamirao Gai., <em>Inscriptions of the Early Gupta Kings</em> (New Delhi: Archaeological Survey of India, 1981): 234.
DOI: 10.5281/zenodo.896917
title: IN00005 Vidisa Inscription of Ramagupta on the Image of Candraprabha

description: IN00005 Bhandarkar, Devadatta Ramakrishna, Bahadur Chand Chhabra, and Govind Swamirao Gai., <em>Inscriptions of the Early Gupta Kings</em> (New Delhi: Archaeological Survey of India, 1981): 234.
DOI: 10.6084/m9.figshare.5738439.v10
title: Tattooed Human Mummies Database, Version 5.0

description: The following presents a global data set identifying naturally- and deliberately preserved tattooed human remains from the archaeological record. The initial version of this list (Version 1.0) was compiled in 2016 for inclusion as Table 1 in the journal article “The World’s Oldest Tattoos” (Deter-Wolf et al. 2016). Benoît Robitaille, Lars Krutak, and Sébastien Galliot all contributed to that initial effort. Changes between versions are detailed below.<b><br></b>Entries in the data table are organized broadly by date, and rely on direct dating wherever possible. Where radiocarbon data is available, dates represent calibrated ranges. Each entry also includes documentation as to the associated archaeological culture, site, and significant source material. Citations are not comprehensive. At the present time, historical European examples, unpublished and/or unprovenienced specimens from museums and private collections, and deliberately-preserved historical skin samples are not generally included in the data set.
DOI: 10.5281/zenodo.996873
title: IN00032 Junagadh Rock Inscription 1 of the Time of Skandagupta

description: IN00032 Bhandarkar, Devadatta Ramakrishna, Bahadur Chand Chhabra, and Govind Swamirao Gai, <em>Inscriptions of the Early Gupta Kings</em> (New Delhi: Archaeological Survey of India, 1981): 302-305.
DOI: 10.5281/zenodo.996865
title: IN00032 Junagadh Rock Inscription 1 of the Time of Skandagupta

description: IN00032 Bhandarkar, Devadatta Ramakrishna, Bahadur Chand Chhabra, and Govind Swamirao Gai, <em>Inscriptions of the Early Gupta Kings</em> (New Delhi: Archaeological Survey of India, 1981): 302-305.
DOI: 10.25824/redu/gjv8ji
title: 2001-2018_obitos_geral_integrado.tab
DOI: 10.25824/redu/wjiuna
title: 2001-2018_obitos_geral_integrado-data-dictionary.pdf

description: Data dictionary
DOI: 10.25824/redu/upcdsk
title: Human death records and environmental parameters of the city of Campinas, state of São Paulo, Brazil, 2001-2018

description: This dataset contains death records from individuals from the city of Campinas, São Paulo, Brazil, during the period from 2001 to 2018, associated to environmental parameters obtained from weather stations in the dates of death. The information related to each death record includes the date, and causes of the death, age, sex, and race of the individuals. The environmental parameters include minimum, maximum and mean values of carbon monoxide (CO), particulate matter size 10 micrometers (PM10), air temperature, relative air humidity, air pressure, and indicators of days under the effect of heat or cold waves.
DOI: 10.6084/m9.figshare.19550761.v2
title: SuicideBD: A Suicidal Dataset for Bangladesh

description: This dataset contains individual details who committed suicide in Bangladesh during the Pandemic between February, 2020 to November, 2020. This dataset includes details of every individuals who committed suicide like personal details, family & social life, profession, financial condition, methods of committing suicide, location and weather info. The dataset is freely available. The major fields included in this dataset are: age group, age, gender, profession group, reason, method, suicide date & time, addiction status, mental status, economic condition, marital status, family details, academic qualification, weather. Apart from the above data this dataset also contains a CSV file of a Bengali wordcloud built on social media posts of the suicide victims.
DOI: 10.25919/bmz0-2898
title: Parkes observations for project P1152 semester 2022APRS_05

description: A large population of millisecond pulsars (MSPs) is expected in the Galactic bulge and is supported, among others, by the existence of a spatially extended gamma-ray excess emission discovered in Fermi-LAT data towards the inner Galaxy. Discovering MSPs in the Galactic bulge, would be a major breakthrough with strong impact onto several fields. In Berteaud et al. [2021a, 2021b], we have designed a new method to select bulge MSP candidates among Chandra X-ray cataloged sources. We also analysed imaging data of the VLA and identified 5 potential bulge MSP candidates, detected both with Chandra and VLA. Here we propose to follow up these 5 sources with the UWL receiver system on Parkes, which has the unique potential of probe their MSP nature thanks to multi-band, deep, observations. With the requested time, for two high-priority candidates, we will be able identify any bulge MSP with a pulse period P &gt; 1 ms. Three targets at lower priority can be identified as bulge MSP if their period is larger than 4 ms. Our goal is to provide the first multi-wavelength diagnostics of bulge MSPs, gather information about the MSP/pulsar ratio among the bulge X-ray candidates, and, finally, unveil the nature of the mysterious Fermi-LAT excess.
DOI: 10.21942/uva.19658910
title: Dataset of "Narrow-line imaging of single strontium atoms in shallow optical tweezers"

description: Dataset of "Narrow-line imaging of single strontium atoms in shallow optical tweezers", arXiv:2202.05727.
DOI: 10.21942/uva.19658910.v1
title: Dataset of "Narrow-line imaging of single strontium atoms in shallow optical tweezers"

description: Dataset of "Narrow-line imaging of single strontium atoms in shallow optical tweezers", arXiv:2202.05727.
DOI: 10.34740/kaggle/dsv/3533200
title: Jigsaw Specialized Rater Pools Dataset
DOI: 10.21227/5mr7-p631
title: Supplementary datasheet (TPWRS12)

description: Supplementary datasheet.
DOI: 10.35078/utxbuc/nyy4ev
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 5.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 5 - Este é o quinto vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação virtual realizada pelo ArticulaFito. O palestrante Mateus Soares da Rocha começa sua participação no módulo esclarecendo as Políticas Públicas de Comercialização para a Agricultura Familiar (PNAE).
DOI: 10.35078/utxbuc/ufgdrz
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 2.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 2 - Este é o segundo vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação realizada pelo projeto ArticulaFito - Cadeias de Valor em Plantas Medicinais. Nesta videoaula, o palestrante Wanderson Henrique do Couto encerra sua participação no módulo explicando o acesso ao Programa Nacional de Fortalecimento da Agricultura Familiar (Pronaf).
DOI: 10.35078/utxbuc/twzkhm
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 4.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 4 - Este é o quarto vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação virtual realizada pelo ArticulaFito - Cadeias de Valor em Plantas Medicinais. O palestrante Ênio Carlos Souza completa sua participação no módulo apresentando os produtos amparados pela Política de Garantia de Preço Mínimo para a Sociobiodiversidade - PGPMBio.
DOI: 10.35078/utxbuc/nobgeq
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 6.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 6 - Este é o sexto e último vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação virtual realizada pelo projeto ArticulaFito - Cadeias de Valor em Plantas Medicinais. O palestrante Mateus Soares da Rocha finaliza sua participação no módulo descrevendo as Políticas Públicas de Comercialização para a Agricultura Familiar (PAA) e os mercados privados.
DOI: 10.35078/utxbuc/zshfn8
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 3.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 3 - Este é o terceiro vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação virtual realizada pelo ArticulaFito - Cadeias de Valor em Plantas Medicinais. O palestrante Ênio Carlos Souza inicia sua atuação no módulo introduzindo a Política de Garantia de Preço Mínimo para a Sociobiodiversidade - PGPMBio.
DOI: 10.35078/utxbuc/xlmuch
title: Políticas Públicas e Acesso a Mercados Diferenciados - Parte 1.mp4

description: I Ciclo de capacitação do ArticulaFito/ Políticas Públicas e Acesso a Mercados Diferenciados - Parte 1 - Este é o primeiro vídeo da oficina Políticas Públicas e Acesso a Mercados Diferenciados, uma capacitação realizada pelo projeto ArticulaFito - Cadeias de Valor em Plantas Medicinais. Nesta videoaula, o palestrante Wanderson Henrique do Couto apresenta o assunto a partir das linhas de crédito do Programa Nacional de Fortalecimento da Agricultura Familiar (Pronaf).
DOI: 10.35078/utxbuc/9se19i
title: Apresentação_Wanderson Couto_PRONAF Bioeconomia.pptx

description: Linhas de crédito do Pronaf para produtos da bioeconomia - Wanderson Henrique do Couto - I Ciclo de capacitação do ArticulaFito
DOI: 10.35078/utxbuc/paknej
title: Apresentação_Mateus Rocha_Politicas Públicas de Comercialização.pptx

description: Políticas Públicas de comercialização para a agricultura familiar - Mateus Soares da Rocha - - I Ciclo de capacitação do ArticulaFito
DOI: 10.35078/utxbuc/wpt1vv
title: Apresentação_Ênio Souza_Sociobiodivercidade. ppt.pptx

description: Política de preços mínimos para produtos da sociobiodiversidade - Ênio Souza - I Ciclo de capacitação do ArticulaFito
DOI: 10.6084/m9.figshare.19646781
title: Local climate zone map at 30-m spatial resolution for the metropolitan city of Milan, Italy

description: Local climate zone map at 30-m spatial resolution for the metropolitan city of Milan, Italy <br> Representative date: 16-08-2019 <br> The maps are in GeoTIFF format and can be visualized and analyzed using Geographic Information Systems (GIS) packages. <br> The maps have the following accuracies: <br> OA for all testing polygons: 67% Kappa coefficient for all testing polygons: 0.61 OA of all built types: 48% OA of all built types (excluding LCZ 3 and 9) = 54% <br> Please refer to and cite the following article when using these maps: <br> Eldesoky, A.H., Colaninno, N., Morello, E., 2019. Improving Local Climate Zones Automatic Classification Based on Physic-Morphological Urban Features. Int Conf Virtual City Territ 0, 0–3. https://doi.org/10.5821/ctv.8663
DOI: 10.35078/bngttr/oshutx
title: Produção de Plantas Medicinais em Sistemas Agroflorestais - Parte 3.mp4

description: II Ciclo de capacitação do ArticulaFito/ Produção de Plantas Medicinais em Sistemas Agroflorestais - Parte 3 - Esta é a terceira e última videoaula do módulo I da oficina “Produção de Plantas Medicinais em Sistemas Florestais”, uma capacitação realizada pelo ArticulaFito - Cadeias de Valor em Plantas Medicinais. A palestrante Conceição Previero trata do mapeamento, da análise e da prospecção das cadeias produtivas de plantas medicinais.
DOI: 10.35078/bngttr/q0nppm
title: Produção de Plantas Medicinais em Sistemas Agroflorestais - Parte 6.mp4

description: II Ciclo de capacitação do ArticulaFito/ Produção de Plantas Medicinais em Sistemas Agroflorestais - Parte 6 - Esta é a terceira vídeoaula do módulo II da oficina “Produção de Plantas Medicinais em Sistemas Florestais”, uma capacitação realizada pelo ArticulaFito - Cadeias de Valor em Plantas Medicinais. A palestrante Conceição Previero exemplifica o aprendizado do curso ao relatar as experiências de dois produtores e seus quintais florestais em Palmas (TO).