cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25422/azu.data.24446770
title: Calculated volatilities for all metabolites and their related genomes in the KEGG database

description: Volatility describes the tendency for a compound to partition into the gas phase and volatile metabolites facilitate unique biological interactions which have an influence on Earth's atmospheric physics and chemistry. Estimating which metabolites may be volatile is difficult, especially for those which do not have measured vapor pressures. <i>Volcalc</i> is a newly developed vapor pressure estimation tool which utilizes the SIMPOL.1 method, allowing users to rapidly identify plausible volatile metabolites within the Kyoto Encyclopedia for Genes and Genomes (KEGG) database. Here, we estimate the volatiles of all KEGG metabolites and associate them with KEGG reactions, enzymes, orthologs (KOs) and whole genomes within the KEGG database. This information may be used to identify which genes or species may be linked to particular forms of volatile metabolism, for the purpose hypothesis generation and integration into additional bioinformatics pipelines. This data is listed as a compliment to the publication "Automating methods for estimating metabolite volatility". The column "Paper" indicates whether the listed species is one from the subset analyzed within the data for Figure 3.<br><i>For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu</i>
DOI: 10.25919/6pe2-w392
title: Parkes observations for project P1211 semester 2023OCTS_01

description: Traditional pulsar searching techniques are not sensitive enough to extreme pulsars such as millisecond pulsars (MSPs) in compact binaries (e.g., Pulsar-Blackhole binary systems), extremely fast spinning pulsars (e.g., sub-MSPs), and high dispersion measure (DM) pulsars (e.g., pulsars in Galactic Centre and Galactic Plane). Such a situation is now changed thanks to the development of next generation radio telescope arrays such as Australian Square Kilometer Array Pathfinder (ASKAP). ASKAP is capable of conducting highly sensitive radio continuum surveys with wide sky coverage (e.g, Evolutionary Map of The Universe survey). One of the solutions is to find pulsar candidates in radio continuum surveys such as EMU and then carry out targeted searches. This technique allows us to search over the wide bandwidth with full field of view while avoiding the need for expensive pixel-by-pixel high time resolution searches. In this proposal, we propose to observe 16 MSP candidates identified in the Galactic plane using new ASKAP EMU images. We found 23 candidates by selecting sources with spectral index steeper than -1.90 and compactness less than 1.2. Among them 7 are known pulsars giving us high fraction of pulsars (~33%) and a reasonable number of candidates to follow up (16 sources). Because of the dense ionised medium in the Galactic Plane, MSPs are likely to be missed by previous pulsar surveys carried out at 1.4 GHz. Here, we propose a targeted pulsar search with the Parkes UWL which allow us to search pulsation at higher frequencies and therefore avoid strong DM smearing and scattering effects.
DOI: 10.6084/m9.figshare.24560518
title: 20231115_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24560518.v1
title: 20231115_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.22299847
title: Data and R code for "Supplemental LED lighting improves plant growth without impeding parasitoid biological control of aphids in a tri-trophic greenhouse system"

description: This dataset appears in the article Fraser, J.L., Abram, P.K. & Dorais, M. Supplemental LED lighting improves plant growth without impeding biological control of aphids with parasitoids in a tri-trophic greenhouse system. <i>J Pest Sci</i> (2023). https://doi.org/10.1007/s10340-023-01703-8Young pepper plants were grown under one of three light treatments. Each treatment had 12 hours of broad-spectrum white LED light plus sunlight as a baseline day, with the LED light serving to compensate for low levels of natural light. After this 12 hours, the plants received either an additional six hours of broad-spectrum white LED light or six hours of red and blue LED light, for a total photoperiod of 18 hours, or no additional light as a control, for a total photoperiod of 12 hours. The plants were then exposed to the green peach aphid <i>Myzus persicae</i> with or without its parasitoid <i>Aphidius matricariae</i> for another two weeks under the same light treatments, or to no insects as a control. The plants were then destructively sampled, with their dry mass and other parameters measured, and the insect densities estimated from randomly selected leaves at different heights within the plants.
DOI: 10.48432/aytxtk
title: LiDAR survey on 210.66 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2015.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A03_2015_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/of487i
title: LiDAR survey on 320.47 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2014.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A04_2014_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/gwuwab
title: LiDAR survey on 350.42 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2015.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A05_2015_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/ltv0h0
title: LiDAR survey on 221.94 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2014.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A06_2014_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/wq4x6i
title: LiDAR survey on 192.25 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2014.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A03_2014_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/dmx1mw
title: LiDAR survey on 172.51 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2014.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A02_2014_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/dm96gw
title: LiDAR survey on 228.9 hectares in Saracá-Taquera, Oriximiná, Pará, Brasil in 2015.

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A01a_2015_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/bheruq
title: LiDAR survey in Saracá-Taquera, Oriximiná, Pará, Brasil in 2014

description: The LiDAR data "Floresta Nacional de Saracá-Taquera (FST_A01a_2014_LiDAR)" refers to the survey carried out at Saracá-Taquera National Forest, Pará state, Brazil, as part of the Brazilian Forest Service monitoring program. The partnership between the Brazilian Forest Service and the Brazilian Agricultural Research Corporation (Embrapa) has made available high accuracy LiDAR data for the development of new methodologies and to expand the knowledge about forest management in concession areas. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/cd7kkh
title: LiDAR survey on 992 hectares in São Félix do Xingu, Pará, Brasil in 2012.

description: The LiDAR data São Félix do Xingu (SFX_A01_2012_LiDAR) refers to the survey carried out in São Félix do Xingu municipality, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/1u6jz5
title: LiDAR survey on 87 hectares in Tapajós, Belterra, Pará, Brasil in 2018.

description: The LiDAR data Floresta Nacional do Tapajós (TAP_A06_2018_LiDAR) refers to the survey carried out in Tapajós National Forest, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/y1io9d
title: LiDAR survey on 86.82 hectares in Tapajós, Belterra, Pará, Brasil in 2008.

description: The LiDAR data Floresta Nacional do Tapajos (TAP_A06_2008_LiDAR) refers to initial airborne LiDAR survey carried out in 2008 at Tapajos National Forest, Pará state, Brazil, funded by grants from NASA (#NNX09AI33G to M. Lefsky et al.) and NSF (#0721140 to S. Saleska, G.G. Parker, Y. Shimabukuro et al.). The TAP_A06_2008 survey areas are of a chronosequence of selectively logged forest (PI. Michael Keller) that were used for monitoring the effects of recovery over time from logging on forest structure and carbon balance. These data have been incorporated into the broader integrated effort of Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data – compressed LAS files: LAZ format (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5066/p9qwwz3d
title: Model Archive for indirect discharge computation for a 300-meter reach of Sand Creek, Wyoming, USA, 2023

description: This product includes a model archive using the iRIC-SAC Solver for indirect discharge computation of the spring snowmelt peak flow surveyed on May 27, 2023, and estimated to have occurred in early April 2023. The best-fit discharge for this flood is 3,500 ft3/s. Other data include topographic cross-section data, control points, and high-water marks collected by RTK GPS, and selected photographs of the survey. The location of this survey is a ~300-meter reach of Sand Creek ending at the upstream side of the Shell Creek Stock Trail bridge. Evidence of additional likely coincident floods on tributaries that enter Sand Creek between the Shell Creek Stock Trail bridge and the confluence of Sand Creek with the Little Snake River indicates that this flood peak may have increased by up to an additional ~1,000 ft3/s by the time it reached the Little Snake River.
DOI: 10.48432/c7utqd
title: LiDAR survey on 53 hectares in Tapajós, Belterra, Pará, Brasil in 2018.

description: The LiDAR data Floresta Nacional do Tapajós (TAP_A05_2018_LiDAR) refers to the survey carried out in Tapajós National Forest, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.48432/s4occl
title: LiDAR survey on 580 hectares in Tapajós, Belterra, Pará, Brasil in 2018.

description: The LiDAR data Floresta Nacional do Tapajós (TAP_A04_2018_LiDAR) refers to the survey carried out in Tapajós National Forest, Pará state, Brazil. The data were collected under the project Sustainable Landscapes, a project supported by the United States Agency for International Development (USAID) and US Department of State. The United States Forest Service working in collaboration with the Brazilian Agricultural Research Corporation (Embrapa) have made possible the provision of high accuracy LiDAR data aiming at developing new methods and generating knowledge in the field. This dataset contains: a. Classified LAS formatted point cloud data (vendor delivered); b. Digital Terrain Model (vendor delivered); c. Map of LiDAR coverage area and block boundaries; “Data were acquired by the Sustainable Landscapes Brazil project supported by the Brazilian Agricultural Research Corporation (Embrapa), the US Forest Service, USAID and the US Department of State."
DOI: 10.5519/qd.q9d4nvif
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5725013 records)
DOI: 10.6084/m9.figshare.2082730
title: Bayesian Estimation of Bipartite Matchings for Record Linkage

description: The bipartite record linkage task consists of merging two disparate datafiles containing information on two overlapping sets of entities. This is nontrivial in the absence of unique identifiers and it is important for a wide variety of applications given that it needs to be solved whenever we have to combine information from different sources. Most statistical techniques currently used for record linkage are derived from a seminal article by Fellegi and Sunter in 1969. These techniques usually assume independence in the matching statuses of record pairs to derive estimation procedures and optimal point estimators. We argue that this independence assumption is unreasonable and instead target a bipartite matching between the two datafiles as our parameter of interest. Bayesian implementations allow us to quantify uncertainty on the matching decisions and derive a variety of point estimators using different loss functions. We propose partial Bayes estimates that allow uncertain parts of the bipartite matching to be left unresolved. We evaluate our approach to record linkage using a variety of challenging scenarios and show that it outperforms the traditional methodology. We illustrate the advantages of our methods merging two datafiles on casualties from the civil war of El Salvador. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.2082730.v2
title: Bayesian Estimation of Bipartite Matchings for Record Linkage

description: The bipartite record linkage task consists of merging two disparate datafiles containing information on two overlapping sets of entities. This is nontrivial in the absence of unique identifiers and it is important for a wide variety of applications given that it needs to be solved whenever we have to combine information from different sources. Most statistical techniques currently used for record linkage are derived from a seminal article by Fellegi and Sunter in 1969. These techniques usually assume independence in the matching statuses of record pairs to derive estimation procedures and optimal point estimators. We argue that this independence assumption is unreasonable and instead target a bipartite matching between the two datafiles as our parameter of interest. Bayesian implementations allow us to quantify uncertainty on the matching decisions and derive a variety of point estimators using different loss functions. We propose partial Bayes estimates that allow uncertain parts of the bipartite matching to be left unresolved. We evaluate our approach to record linkage using a variety of challenging scenarios and show that it outperforms the traditional methodology. We illustrate the advantages of our methods merging two datafiles on casualties from the civil war of El Salvador. Supplementary materials for this article are available online.
DOI: 10.5281/zenodo.10125613
title: ¿Qué busca un usuario de Steam?

description: El dataset se compone de información clave sobre videojuegos registrados en la plataforma Steam. Estos datos incluyen el título del juego, la desarrolladora, la distribuidora, la fecha de lanzamiento, las etiquetas asociadas, la calidad conjunta de las reseñas y la cantidad de las mismas. Nuestro objetivo al recopilar estos datos es proporcionar una visión general de las tendencias en el mundo de los videojuegos, permitiendo un análisis de los cambios en las preferencias de los consumidores a lo largo del tiempo.