cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.r4pkdk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melastoma yahudii K.M.Wong"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052121-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dbxrb9
title: Occurrence Download

description: A dataset containing 540 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dermacentor andersoni Stiles, 1908",
 "Year 1950-2024"
 ]
}

 The dataset includes 540 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052122-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hz4szh
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Maesa ambigua C.Y.Wu & C.Chen"
 ]
}

 The dataset includes 23 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052123-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.68934j
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Meryta pandanicarpa Guillaumin"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052124-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5qckyp
title: Occurrence Download

description: A dataset containing 4767 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mallotus oppositifolius (Geiseler) Müll.Arg."
 ]
}

 The dataset includes 4767 records from 121 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052125-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p87tun
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melastoma yiianthum K.M.Wong"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052126-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqxw6b
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Maesa ambrymensis Guillaumin"
 ]
}

 The dataset includes 49 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052127-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qfrg26
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Meryta pastoralis F.Tronchet & Lowry"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052128-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n93nw6
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melastomastrum afzelii (Hook.fil.) A.Fern. & R.Fern."
 ]
}

 The dataset includes 119 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052129-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ek6dt3
title: Occurrence Download

description: A dataset containing 253 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mallotus oreophilus Müll.Arg."
 ]
}

 The dataset includes 253 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052130-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ds7rf5
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Maesa amplexicaulis Utteridge"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052131-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djzp8p
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Meryta pauciflora Hemsl. ex Cheeseman"
 ]
}

 The dataset includes 48 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052132-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uhrvnr
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melastomastrum autranianum (Cogn.) A.Fern. & R.Fern."
 ]
}

 The dataset includes 110 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052133-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22367217.v1
title: ACC_labelled_publication.txt from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: Quantification of activity budgets is pivotal for understanding how animals respond to changes in their environment. Social grooming is a key activity that underpins various social processes with consequences for health and fitness. Traditional methods use direct (focal) observations to calculate grooming rates, providing systematic but sparse data. Accelerometers, in contrast, can quantify activity budgets continuously but have not been used to quantify social grooming. We test whether grooming can be accurately identified using machine learning (random forest model) trained on labelled acceleration data from wild chacma baboons (<i>Papio ursinus</i>). We successfully identified giving and receiving grooming with high precision (81% and 91%) and recall (87% and 79%). Giving grooming was associated with a distinct rhythmical signal along the surge axis. Receiving grooming had similar acceleration signal to resting, and thus was more difficult to assign. We applied our machine learning model to <i>n</i> = 680 collar data days from <i>n</i> = 12 baboons and found that grooming rates obtained from accelerometers were significantly and positively correlated with direct observation rates for giving but not receiving grooming. The ability to collect continuous grooming data in wild populations will allow researchers to re-examine and expand upon long-standing questions regarding the formation and function of grooming bonds.
DOI: 10.6084/m9.figshare.22367220
title: RF&focal_rates_publication from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: Rates of behaviour for each baboon based on accelerometer data and focal data for the study period
DOI: 10.6084/m9.figshare.22367220.v1
title: RF&focal_rates_publication from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: Rates of behaviour for each baboon based on accelerometer data and focal data for the study period
DOI: 10.6084/m9.figshare.22367223.v1
title: ACC_training_publication from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: The portion (70%) of the labelled accelerometer data used to train the Random Forest model
DOI: 10.6084/m9.figshare.22367223
title: ACC_training_publication from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: The portion (70%) of the labelled accelerometer data used to train the Random Forest model
DOI: 10.6084/m9.figshare.22367226
title: Random Forest model R code from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: R code to run random forest model and obtain the confusion matrix, precision and recall
DOI: 10.6084/m9.figshare.22367226.v1
title: Random Forest model R code from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: R code to run random forest model and obtain the confusion matrix, precision and recall
DOI: 10.6084/m9.figshare.22367229
title: ACC_training_publication.txt from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: Quantification of activity budgets is pivotal for understanding how animals respond to changes in their environment. Social grooming is a key activity that underpins various social processes with consequences for health and fitness. Traditional methods use direct (focal) observations to calculate grooming rates, providing systematic but sparse data. Accelerometers, in contrast, can quantify activity budgets continuously but have not been used to quantify social grooming. We test whether grooming can be accurately identified using machine learning (random forest model) trained on labelled acceleration data from wild chacma baboons (<i>Papio ursinus</i>). We successfully identified giving and receiving grooming with high precision (81% and 91%) and recall (87% and 79%). Giving grooming was associated with a distinct rhythmical signal along the surge axis. Receiving grooming had similar acceleration signal to resting, and thus was more difficult to assign. We applied our machine learning model to <i>n</i> = 680 collar data days from <i>n</i> = 12 baboons and found that grooming rates obtained from accelerometers were significantly and positively correlated with direct observation rates for giving but not receiving grooming. The ability to collect continuous grooming data in wild populations will allow researchers to re-examine and expand upon long-standing questions regarding the formation and function of grooming bonds.
DOI: 10.6084/m9.figshare.22367229.v1
title: ACC_training_publication.txt from Quantifying allo-grooming in wild chacma baboons (<i>Papio ursinus</i>) using tri-axial acceleration data and machine learning

description: Quantification of activity budgets is pivotal for understanding how animals respond to changes in their environment. Social grooming is a key activity that underpins various social processes with consequences for health and fitness. Traditional methods use direct (focal) observations to calculate grooming rates, providing systematic but sparse data. Accelerometers, in contrast, can quantify activity budgets continuously but have not been used to quantify social grooming. We test whether grooming can be accurately identified using machine learning (random forest model) trained on labelled acceleration data from wild chacma baboons (<i>Papio ursinus</i>). We successfully identified giving and receiving grooming with high precision (81% and 91%) and recall (87% and 79%). Giving grooming was associated with a distinct rhythmical signal along the surge axis. Receiving grooming had similar acceleration signal to resting, and thus was more difficult to assign. We applied our machine learning model to <i>n</i> = 680 collar data days from <i>n</i> = 12 baboons and found that grooming rates obtained from accelerometers were significantly and positively correlated with direct observation rates for giving but not receiving grooming. The ability to collect continuous grooming data in wild populations will allow researchers to re-examine and expand upon long-standing questions regarding the formation and function of grooming bonds.
DOI: 10.35078/ghn5mc
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha | Município: Lagoa Dourada

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.35078/5c1omo
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha| Município: Leandro Ferreira

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.6084/m9.figshare.22110987
title: Effect of a barrier on spatial distribution of respiratory particles in a room

description: Barriers have been widely used to mitigate transmission of Covid-19 and other diseases. Their efficacy for aerosol particles is not well established. The objective of this study was to quantify the impact of a barrier on the spatial distribution of particles released by speaking in a room with a low air-change rate (0.6 ± 0.2 h<sup>−1</sup>). The source was a nebulizer that released fluorescent microspheres of diameters 0.5, 1, 6, 10, or 20 µm for 20 min, and the room was outfitted with 108 passive sampling sites. We counted the number of microspheres deposited on slides at sampling locations after &gt;1 h. The presence of a barrier 0.46 m in front of the source resulted in an increase in 0.5 µm particles deposited on the source-side of the barrier and an increase in 0.5 µm particles around the sides of the barrier laterally and at certain locations 4–6 m from the source. The barrier had a minor effect on the distribution of 1 µm particles. There was no observable effect of the barrier on the distribution of 6, 10, and 20 µm particles. Most 10 and 20 µm particles deposited within 0.3 m of the source, although some were found at locations &gt;3 m from the source. These results indicate that barriers may not serve as adequate protection to others in the room, depending on their location relative to the barrier and the exposure timescale. A limitation is that our study utilized only one barrier configuration at one air-change rate.
DOI: 10.6084/m9.figshare.22110987.v1
title: Effect of a barrier on spatial distribution of respiratory particles in a room

description: Barriers have been widely used to mitigate transmission of Covid-19 and other diseases. Their efficacy for aerosol particles is not well established. The objective of this study was to quantify the impact of a barrier on the spatial distribution of particles released by speaking in a room with a low air-change rate (0.6 ± 0.2 h<sup>−1</sup>). The source was a nebulizer that released fluorescent microspheres of diameters 0.5, 1, 6, 10, or 20 µm for 20 min, and the room was outfitted with 108 passive sampling sites. We counted the number of microspheres deposited on slides at sampling locations after &gt;1 h. The presence of a barrier 0.46 m in front of the source resulted in an increase in 0.5 µm particles deposited on the source-side of the barrier and an increase in 0.5 µm particles around the sides of the barrier laterally and at certain locations 4–6 m from the source. The barrier had a minor effect on the distribution of 1 µm particles. There was no observable effect of the barrier on the distribution of 6, 10, and 20 µm particles. Most 10 and 20 µm particles deposited within 0.3 m of the source, although some were found at locations &gt;3 m from the source. These results indicate that barriers may not serve as adequate protection to others in the room, depending on their location relative to the barrier and the exposure timescale. A limitation is that our study utilized only one barrier configuration at one air-change rate.
DOI: 10.35078/tabypm
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Varginha| Município: Luz

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.17909/aq6f-df31
title: TESS data
DOI: 10.5281/zenodo.7786602
title: tyrannus_vociferans_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7786601
title: tyrannus_vociferans_decontaminated_gx.fasta.gz

description: .
DOI: 10.6084/m9.figshare.22370320
title: PROKKA output

description: Prokka output
DOI: 10.6084/m9.figshare.22370320.v1
title: PROKKA output

description: Prokka output
DOI: 10.25824/redu/ipyw7f
title: CAETE_Rius_etal_2023.zip
DOI: 10.25824/redu/zgth17
title: Codes and results of the CAETÊ trait-based vegetation model

description: CAETÊ (Carbon and Ecosystem functional Trait Evaluation model) Repository containing codes and results for the study published in the Ecological Modelling journal RIUS, B. F; DARELA FILHO, J. P.; FLEISCHER, K.; HOFHANSL, F.; BLANCO, C. C.; RAMMIG, A.; DOMINGUES, T.; LAPOLA, D. M. (2023) Higher functional diversity improves modeling of Amazon forest carbon storage. Ecological Modelling, in press.
DOI: 10.3886/icpsr38627.v1
title: Federal Justice Statistics Program: Criminal Appeals Cases Filed in Courts of Appeals, 2021
title: Version 1

description: The data contain records of criminal appeals cases filed in United States Courts of Appeals during fiscal year 2021. The data were constructed from the Administrative Office of the United States Courts' (AOUSC) Court of Appeals file. These contain variables on the nature of the criminal appeal, the underlying offense, and the disposition of the appeal. An appeal can be filed by the government or the offender, and the appellant can appeal the sentence, the verdict, or both sentence and verdict. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute through 2012. Data from 2013 on were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Criminal Appeals Cases Filed in Courts of Appeals, 2021
description: Criminal appeals cases filed in United States Courts of Appeals during fiscal year 2021.
DOI: 10.3886/icpsr38627
title: Federal Justice Statistics Program: Criminal Appeals Cases Filed in Courts of Appeals, 2021
title: Archival Version

description: The data contain records of criminal appeals cases filed in United States Courts of Appeals during fiscal year 2021. The data were constructed from the Administrative Office of the United States Courts' (AOUSC) Court of Appeals file. These contain variables on the nature of the criminal appeal, the underlying offense, and the disposition of the appeal. An appeal can be filed by the government or the offender, and the appellant can appeal the sentence, the verdict, or both sentence and verdict. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute through 2012. Data from 2013 on were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Criminal Appeals Cases Filed in Courts of Appeals, 2021
description: Criminal appeals cases filed in United States Courts of Appeals during fiscal year 2021.