cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2qn996
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tarlmounia elliptica, Tarlmounia elliptica, 185853811, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, Tarlmounia elliptica, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, 2008, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, Tarlmounia elliptica (DC.) H. Rob., S. C. Keeley, Skvarla & R. Chan, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, 2008, Tarlmounia elliptica (DC.) H.Rob. et al., Tarlmounia elliptica H.Rob., S.C.Keeley, Skvarla & R.Chan (DC.), 169254117, Tarlmounia elliptica (DC.) H.Rob., S.C.Keeley, Skvarla & R.Chan, Tarlmounia elliptica (DC.) (DC.) H. Rob., S. C. Keeley, Skvarla & R. Chan, Proc. Biol. Soc. Washington 121 (1): 32. 2008., Cacalia elaeagnifolia (Wall. ex DC.) Kuntze, Eupatorium elaeagnifolium Wall. ex DC., Vernonia elliptica DC., Vernonia elaeagnifolia DC., Strobocalyx elaeagnifolia (DC.) Sch.Bip., Strobocalyx elliptica (DC.) Sch.Bip., Vernonia elliptica DC., Cacalia elaeagnifolia (Wall. ex DC.) Kuntze, 169254119, 169254121, 169254123, Strobocalyx elaeagnifolia (DC.) Sch.Bip., 169250961, 169254126, Cacalia elaeagnifolia Kuntze, Strobocalyx elaeagnifolia Sch.Bip., Cacalia elaeagnifolia Kuntze, 1891, Vernonia elliptica DC., Eupatorium elaeagnifolium DC., Conyza elaeagnifolia Wall., Vernonia elliptica DC., Strobocalyx elliptica (DC.) Sch. Bip., Eupatorium elaeagnifolium Wall. ex DC., Vernonia elaeagnifolia DC., 1836, Vernonia elliptica DC., 169246483, Strobocalyx elliptica (DC.) Sch.Bip., 1863, 169254125, Vernonia elliptica DC., Vernonia elaeagnifolia DC., Eupatorium elaeagnifolium Wall., Cacalia elaeagnifolia Kuntze, Vernonia elliptica DC., Strobocalyx elliptica (DC.) Sch.Bip., Conyza elaeagnifolia Wall., Conyza elaeagnifolia Wall., Vernonia elaeagnifolia DC., Strobocalyx elliptica (DC.) Sch.-Bip., Strobocalyx elliptica (DC.) Sch.Bip., Strobocalyx elaeagnifolia (DC.) Sch.Bip., 1863)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1970"
 ]
}

 The dataset includes 75 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0142440-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rskrjn
title: Occurrence Download

description: A dataset containing 4280 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Bellucia brasiliensis Naudin, Bellucia circumscissa Spruce ex Cogn., Bellucia grossularioides (L.) Triana, Bellucia hostmannii Naudin)"
 ]
}

 The dataset includes 4280 records from 192 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261796-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q2kdt7
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Microsciurus santanderensis (Hernández-Camacho, 1957)"
 ]
}

 The dataset includes 58 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111946-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ycx8ru
title: Occurrence Download

description: A dataset containing 15883915 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ascomycota"
 ]
}

 The dataset includes 15883915 records from 2532 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261829-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j4npaw
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Olea communis",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007929-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17481600
title: Distance and Angle Measurements for Hybrid Localization in IEEE 802.15.4 TSCH Networks

description: Overview

The dataset includes distance and angle measurements obtained from a hybrid localization system integrated with the IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) protocol [1]. The system combines multi-carrier phase difference (MCPD) or phase-based ranging (PBR) for distance estimation [2] with phase-based direction finding technique for angle-of-arrival (AoA) estimation [3], enabling hybrid localization using a single anchor node in an IoT network.

Setup

The measurements were collected in an office environment with a IEEE 802.15.4 TSCH network formed by six low-cost devices. One node, positioned in the center of a 5.1 m by 6.5 m room, acted as the root and performed localization of five surrounding nodes. Each device was built upon the AT86RF215 transceiver, which provides access to the phase of the received signal. To enable angle estimation, the root node was equipped with an RF switch and a uniform circular antenna (UCA) array composed of eight dipole elements spaced equally across 360 degrees. The pictures of the setup, used equipment and configuration are attached in the dataset files along with detailed description.

Measurement Procedure

The root of the node first formed a TSCH network. When all devices joined the network, the root started acting as an initiator, pinging its child devices. Each packet transmission initiated a Phase Measurement Process (PMP) that acquired phase measurements for angle and distance estimation [1]. During each PMP, the initiator captured eight reference phase samples from the first antenna to estimate and correct the carrier frequency offset (CFO), followed by ninety phase samples across the antenna array for AoA estimation. The switching between antenna elements was performed in a Round Robin (RR) pattern. The sampling rate of the system was 8 us per phase sample [3]. For distance estimation, fifteen frequency samples were measured sequentially using the Golomb frequency set to minimize measurement time and spectral overlap [2].

Software Implementation

The software implementation of the modified Contiki-NG stack that supports hybrid localization alongside TSCH communication is available at: https://github.com/9morano/contiki-ng/tree/vesna-atasw

Dataset Structure

The dataset is stored in a single JSON file named `data.json`. It is organized by device, where each entry includes the device address and an array of records. Each record contains the absolute slot number (ASN) corresponding to the TSCH schedule, two arrays of phase samples representing measurements from the initiator and the reflector, an array of eight reference phase values used for frequency offset calibration, and a second array of ninety phase values used for angle estimation. The JSON file can be parsed using Python built-in json module.
DOI: 10.5281/zenodo.17481601
title: Distance and Angle Measurements for Hybrid Localization in IEEE 802.15.4 TSCH Networks

description: Overview

The dataset includes distance and angle measurements obtained from a hybrid localization system integrated with the IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) protocol [1]. The system combines multi-carrier phase difference (MCPD) or phase-based ranging (PBR) for distance estimation [2] with phase-based direction finding technique for angle-of-arrival (AoA) estimation [3], enabling hybrid localization using a single anchor node in an IoT network.

Setup

The measurements were collected in an office environment with a IEEE 802.15.4 TSCH network formed by six low-cost devices. One node, positioned in the center of a 5.1 m by 6.5 m room, acted as the root and performed localization of five surrounding nodes. Each device was built upon the AT86RF215 transceiver, which provides access to the phase of the received signal. To enable angle estimation, the root node was equipped with an RF switch and a uniform circular antenna (UCA) array composed of eight dipole elements spaced equally across 360 degrees. The pictures of the setup, used equipment and configuration are attached in the dataset files along with detailed description.

Measurement Procedure

The root of the node first formed a TSCH network. When all devices joined the network, the root started acting as an initiator, pinging its child devices. Each packet transmission initiated a Phase Measurement Process (PMP) that acquired phase measurements for angle and distance estimation [1]. During each PMP, the initiator captured eight reference phase samples from the first antenna to estimate and correct the carrier frequency offset (CFO), followed by ninety phase samples across the antenna array for AoA estimation. The switching between antenna elements was performed in a Round Robin (RR) pattern. The sampling rate of the system was 8 us per phase sample [3]. For distance estimation, fifteen frequency samples were measured sequentially using the Golomb frequency set to minimize measurement time and spectral overlap [2].

Software Implementation

The software implementation of the modified Contiki-NG stack that supports hybrid localization alongside TSCH communication is available at: https://github.com/9morano/contiki-ng/tree/vesna-atasw

Dataset Structure

The dataset is stored in a single JSON file named `data.json`. It is organized by device, where each entry includes the device address and an array of records. Each record contains the absolute slot number (ASN) corresponding to the TSCH schedule, two arrays of phase samples representing measurements from the initiator and the reflector, an array of eight reference phase values used for frequency offset calibration, and a second array of ninety phase values used for angle estimation. The JSON file can be parsed using Python built-in json module.
DOI: 10.15156/bio/sh1206744.10fu
title: SH1206744.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206748.10fu
title: SH1206748.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206752.10fu
title: SH1206752.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206753.10fu
title: SH1206753.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206756.10fu
title: SH1206756.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206758.10fu
title: SH1206758.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206760.10fu
title: SH1206760.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206761.10fu
title: SH1206761.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1206764.10fu
title: SH1206764.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.17632/pj4cfhmvx5.1
title: Ultrasound and clinical characteristics of photodynamic therapy-resistant patients with probable CM-AVM syndrome: a single center retrospective study.

description: Contents 
Supplementary Fig 1. Clinical photograghs of PDT-resistant patients..................................... 2
Supplementary Fig 2. Ultrasound findings of PMs in PDT-resistant patients using the Mindray Resona 7 device........................................................................................................................ 3
Supplementary Fig 3. High-frequency ultrasound findings of PMs in a PDT-resistant patient using the Paragon XHD device……………………………………………………………................................... 4
Supplementary Fig 4. The blood vessels in the hypodermis of PMs exhibited significant dilation using the Paragon XHD device………………….…………………………………………………………….. 5
Supplementary Fig 5. High-frequency ultrasound findings of PMs in a PDT-resistant patient using Paragon XHD and DUB Skin Scanner devices…………………............................................... 6
Supplementary Table I. PDT-resistant patient demographics................................................. 8
Supplementary Table II. The clinical features of PDT-resistant patients................................. 10
Supplementary Table III. Comparisons of ultrasound characteristics between lesion skin and normal skin in PDT-resistant patients (obtained by Paragon XHD)......................................... 11
DOI: 10.25549/inscriptifact-ouc112033351
title: Cuneiform Tablet 1913.14.1672, Spurlock 1913.14.1672

description: [Text Description:] Administrative tablet ❧ [Text or Publication Number Note:] Spurlock 1913.14.1672; CDLI P421523 ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Yellowish White (10YR 9/1.5) ❧ [Physical Object Note:] 5.9 x 3.9 x 1.9 cm (47 g)
DOI: 10.15468/dl.3ga73e
title: Occurrence Download

description: A dataset containing 56027372 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 56027372 records from 4000 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0259450-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive168608.20240510.9
title: Reyranella terrae Lee et al. 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive168608.20251217.10
title: Reyranella terrae Lee et al. 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.57702/xlnpcn55
title: ICLP 2019 Dataset

description: The dataset contains 122 submissions of abstracts, 92 full submissions, and 30 accepted papers.