cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/d5f3e988108f340a24f1cac11f44a02f
title: North Temperate Lakes LTER: High Frequency Data: Meteorological, Dissolved Oxygen, Chlorophyll, Phycocyanin - Lake Mendota Buoy 2006 - current

description: The instrumented buoy on Lake Mendota is equipped with limnological and meteorological sensors that provide fundamental information on lake thermal structure, weather conditions, and lake metabolism. Data are collected every minute. Hourly and daily averages are derived from the high resolution (1 minute) data. Hourly and daily values may not be current with high resolution data as they are calculated at the end of the season.
 Meteorological sensors measure wind speed, wind direction, relative humidity, air temperature, and photosynthetically active radiation (PAR). Not all sensors are deployed each season. A list of sensors used since the first deployment in 2006 is provided as a downloadable CSV file. The buoy is removed during the winter when the lake is ice-covered (typically Dec-Apr). Lake temperature data collected at the same buoy site can be found in an ancillary dataset.
 Number of sites: 1. Location lat/long: 43.0995, -89.4045
 Notable events:
 2017 - A boating mishap caused the loss of air temperature, relative humidity, and wind sensors between May 28 and July 11. The dissolved oxygen sensor had significant biofouling from algae and zebra mussels.
 2019 - A YSI EXO2 sonde was added to the buoy and includes DO, chlorophyll, phycocyanin, specific conductance, pH, fDOM, and turbidity sensors. The chlorophyll and phycocyanin sensors replace Turner Cyclops 7 fluorometers that had been in use in prior years. Both sets of sensors output RFU, but have significant magnitude differences. The YSI pH, DO, and specific conductance sensors were cleaned and recalibrated every two weeks. 
 2020 - Cleaning and calibration of the YSI sensors occurred nearly every week. The dissolved CO2 sensor was not operating between July 2 and September 17.
 2021 - Due to power and communications issues, the buoy was not operating August 22-31, and data is intermittent between November 8 and December 3. An effective method to keep the underwater PAR sensor mostly free of biofouling algae has been employed.
 2022 - Buoy was not operating June 6-9 and July 2-5 due to power issues. Underwater PAR sensor unusable after October 1.
 2023 - Conductivity sensor was not operational Apr 27 - May 24. The sensor was replaced. The wiper for the YSI sonde had failed Nov 4 - 14, which significantly affected four sensors: chlorophyll, phycocyanin, conductivity, and turbidity.
DOI: 10.6084/m9.figshare.25477441
title: A new statistical method for analyzing point collocations

description: This paper proposes a new method for analyzing the collocation of spatial objects represented as points.
DOI: 10.6084/m9.figshare.25477441.v1
title: A new statistical method for analyzing point collocations

description: This paper proposes a new method for analyzing the collocation of spatial objects represented as points.
DOI: 10.21227/sg7q-8w28
title: Dataset for OFBG-BIWS

description: This is the experimental data of the OFBG-BIWS for underwater applications. The efficient perception of the underwater flow field is of great significance to the development of underwater intelligent equipment. Driven by unique whisker receptors of the harbor seals, this study proposes and demonstrates a bio-inspired whisker sensor based on orthometric Fiber Bragg Grating (OFBG-BIWS). Four FBGs are deployed around an artificial whisker as basic sensing units. The hydrodynamic information is encoded as the wavelength evolution of the FBGs. In the underwater experiment, OFBG-BIWS obtains the vortex street distribution in the bionic fishtail wake. It realizes frequency locking with RMSE of 0.0208 Hz and rotation direction recognition of the vortex with a maximum detection distance of 300 mm. Based on the theoretical model, we further give the calibrated function to express the relationship between wavelength shift and steady flow velocity. The suggested device provides a new framework for the design of bionic whisker sensors. Replacing integrated circuits with optical fiber sensing units will greatly enhance the adaptability of sensors in extreme application scenarios.
DOI: 10.5281/zenodo.10584167
title: Linked collectors and determiners for: Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species.

description: Natural history specimen data linked to collectors and determiners held within, "Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10704530
title: Linked collectors and determiners for: Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species.

description: Natural history specimen data linked to collectors and determiners held within, "Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10872381
title: Linked collectors and determiners for: Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species.

description: Natural history specimen data linked to collectors and determiners held within, "Two new genera of Australian dung beetles (Coleoptera: Scarabaeidae: Scarabaeinae) with the description of six new species and transfer of six described species". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/43ebda6c-201a-46af-8b54-e7980b8d79e1. Formatted as a Frictionless Data package.
DOI: 10.26179/rxqa-7n62
title: Aurora Australis Voyage V3 2006/07 (SAZ-SENSE) Track and Underway Data
DOI: 10.26179/n7xp-3r68
title: Aurora Australis Voyage V2 2006/07 Track and Underway Data
DOI: 10.26179/8gxj-2q90
title: Aurora Australis Voyage V1.1 2006/07 Track and Underway Data
DOI: 10.26179/yfqz-eb89
title: Aurora Australis Voyage V1 2006/07 Track and Underway Data
DOI: 10.26179/y73k-z565
title: Aurora Australis Voyage 5 2005-2006 Underway Data
DOI: 10.26179/chfe-zc50
title: Aurora Australis Voyage 3 2005-2006 (BROKE-West) Underway Data
DOI: 10.5281/zenodo.10584200
title: Linked collectors and determiners for: Realización de fichas de 12 especies de anfibios y 2 de reptiles.

description: Natural history specimen data linked to collectors and determiners held within, "Realización de fichas de 12 especies de anfibios y 2 de reptiles". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10584201
title: Linked collectors and determiners for: Realización de fichas de 12 especies de anfibios y 2 de reptiles.

description: Natural history specimen data linked to collectors and determiners held within, "Realización de fichas de 12 especies de anfibios y 2 de reptiles". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10704560
title: Linked collectors and determiners for: Realización de fichas de 12 especies de anfibios y 2 de reptiles.

description: Natural history specimen data linked to collectors and determiners held within, "Realización de fichas de 12 especies de anfibios y 2 de reptiles". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10872397
title: Linked collectors and determiners for: Realización de fichas de 12 especies de anfibios y 2 de reptiles.

description: Natural history specimen data linked to collectors and determiners held within, "Realización de fichas de 12 especies de anfibios y 2 de reptiles". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/45347233-6a4f-4843-b4f2-9573eef8dea0. Formatted as a Frictionless Data package.
DOI: 10.26179/pyf2-h775
title: Aurora Australis Voyage 2 2005-2006 Underway Data
DOI: 10.26179/a9pn-3j59
title: Aurora Australis Voyage 1 2005-2006 Underway Data
DOI: 10.26179/zpsa-0g55
title: Aurora Australis Voyage 5 2004-2005 Underway Data
DOI: 10.6084/m9.figshare.25477654
title: Data matrix used in this meta-analysis

description: Data matrix used in this meta-analysis.
DOI: 10.34740/kaggle/dsv/7942974
title: Barcode & QR Codes
DOI: 10.5281/zenodo.10584384
title: Linked collectors and determiners for: Collection of various insect orders, Natural History Museum, University of Oslo.

description: Natural history specimen data linked to collectors and determiners held within, "Collection of various insect orders, Natural History Museum, University of Oslo". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10704704
title: Linked collectors and determiners for: Collection of various insect orders, Natural History Museum, University of Oslo.

description: Natural history specimen data linked to collectors and determiners held within, "Collection of various insect orders, Natural History Museum, University of Oslo". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10584383
title: Linked collectors and determiners for: Collection of various insect orders, Natural History Museum, University of Oslo.

description: Natural history specimen data linked to collectors and determiners held within, "Collection of various insect orders, Natural History Museum, University of Oslo". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10872492
title: Linked collectors and determiners for: Collection of various insect orders, Natural History Museum, University of Oslo.

description: Natural history specimen data linked to collectors and determiners held within, "Collection of various insect orders, Natural History Museum, University of Oslo". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/4cfd80a7-d630-4d7f-89fb-d2d1e749a418. Formatted as a Frictionless Data package.
DOI: 10.26179/qm0h-4q64
title: Aurora Australis Voyage 6 2011/12 Track and Underway Data
DOI: 10.26179/hnb3-5v48
title: Aurora Australis Voyage 1 2012/13 Track and Underway Data
DOI: 10.26179/1zvb-0q26
title: Aurora Australis Voyage 2 2012/13 Track and Underway Data
DOI: 10.13026/1wf7-pm14
title: Asclepius-R : Clinical Large Language Model Built On MIMIC-III Discharge Summaries

description: The development of large language models tailored for handling patients'
clinical notes is often hindered by the limited accessibility and usability of
these notes due to strict privacy regulations. To address these challenges, we
first create synthetic large-scale clinical notes using publicly available
case reports extracted from biomedical literature. We then use these synthetic
notes to train our specialized clinical large language model, Asclepius. While
Asclepius is trained on synthetic data, we assess its potential performance in
real-world applications by evaluating it using real clinical notes. We
benchmark Asclepius against several other large language models, including
GPT-3.5-turbo and other open-source alternatives. To further validate our
approach using synthetic notes, we also compare Asclepius with its variants
trained on real clinical notes. Our findings convincingly demonstrate that
synthetic clinical notes can serve as viable substitutes for real ones when
constructing high-performing clinical language models. This conclusion is
supported by detailed evaluations conducted by both GPT-4 and medical
professionals. All resources--including weights, codes, and data--used in the
development of Asclepius are made publicly accessible for future research.
Specifically, this repository contains Asclepius-R, a variant of Asclepius
that was trained on MIMIC-III discharge summaries. All other resource are also
publicly accessible.
DOI: 10.13026/ckbf-pt70
title: Asclepius-R : Clinical Large Language Model Built On MIMIC-III Discharge Summaries

description: The development of large language models tailored for handling patients'
clinical notes is often hindered by the limited accessibility and usability of
these notes due to strict privacy regulations. To address these challenges, we
first create synthetic large-scale clinical notes using publicly available
case reports extracted from biomedical literature. We then use these synthetic
notes to train our specialized clinical large language model, Asclepius. While
Asclepius is trained on synthetic data, we assess its potential performance in
real-world applications by evaluating it using real clinical notes. We
benchmark Asclepius against several other large language models, including
GPT-3.5-turbo and other open-source alternatives. To further validate our
approach using synthetic notes, we also compare Asclepius with its variants
trained on real clinical notes. Our findings convincingly demonstrate that
synthetic clinical notes can serve as viable substitutes for real ones when
constructing high-performing clinical language models. This conclusion is
supported by detailed evaluations conducted by both GPT-4 and medical
professionals. All resources--including weights, codes, and data--used in the
development of Asclepius are made publicly accessible for future research.
Specifically, this repository contains Asclepius-R, a variant of Asclepius
that was trained on MIMIC-III discharge summaries. All other resource are also
publicly accessible.
DOI: 10.13026/gwjr-7j25
title: Asclepius-R : Clinical Large Language Model Built On MIMIC-III Discharge Summaries

description: The development of large language models tailored for handling patients'
clinical notes is often hindered by the limited accessibility and usability of
these notes due to strict privacy regulations. To address these challenges, we
first create synthetic large-scale clinical notes using publicly available
case reports extracted from biomedical literature. We then use these synthetic
notes to train our specialized clinical large language model, Asclepius. While
Asclepius is trained on synthetic data, we assess its potential performance in
real-world applications by evaluating it using real clinical notes. We
benchmark Asclepius against several other large language models, including
GPT-3.5-turbo and other open-source alternatives. To further validate our
approach using synthetic notes, we also compare Asclepius with its variants
trained on real clinical notes. Our findings convincingly demonstrate that
synthetic clinical notes can serve as viable substitutes for real ones when
constructing high-performing clinical language models. This conclusion is
supported by detailed evaluations conducted by both GPT-4 and medical
professionals. All resources--including weights, codes, and data--used in the
development of Asclepius are made publicly accessible for future research.
Specifically, this repository contains Asclepius-R, a variant of Asclepius
that was trained on MIMIC-III discharge summaries. All other resource are also
publicly accessible.
DOI: 10.13026/s5rz-1j65
title: Asclepius-R : Clinical Large Language Model Built On MIMIC-III Discharge Summaries

description: The development of large language models tailored for handling patients'
clinical notes is often hindered by the limited accessibility and usability of
these notes due to strict privacy regulations. To address these challenges, we
first create synthetic large-scale clinical notes using publicly available
case reports extracted from biomedical literature. We then use these synthetic
notes to train our specialized clinical large language model, Asclepius. While
Asclepius is trained on synthetic data, we assess its potential performance in
real-world applications by evaluating it using real clinical notes. We
benchmark Asclepius against several other large language models, including
GPT-3.5-turbo and other open-source alternatives. To further validate our
approach using synthetic notes, we also compare Asclepius with its variants
trained on real clinical notes. Our findings convincingly demonstrate that
synthetic clinical notes can serve as viable substitutes for real ones when
constructing high-performing clinical language models. This conclusion is
supported by detailed evaluations conducted by both GPT-4 and medical
professionals. All resources--including weights, codes, and data--used in the
development of Asclepius are made publicly accessible for future research.
Specifically, this repository contains Asclepius-R, a variant of Asclepius
that was trained on MIMIC-III discharge summaries. All other resource are also
publicly accessible.
DOI: 10.13026/sg89-qq52
title: ScientISST MOVE: Annotated Wearable Multimodal Biosignals recorded during Everyday Life Activities in Naturalistic Environments

description: Physiological processes are affected and responsive to daily stimuli, and
their daily monitoring can be key to understanding well-being and detecting
diseases. Since most physiological data is acquired at rest, or in controlled
scenarios, many decision algorithms based on physiological data may not
perform as well during free-living conditions. ScientISST MOVE is a 3-wearable
biosignal dataset recorded during natural everyday activities, including
lifting a chair, greeting, gesticulating, walking and running. The wearable
devices: a chestband, an armband, and the Empatica E4 wristband, recorded a
double view of electrocardiography (ECG), electrodermal activity (EDA), and
photoplethysmography (PPG). Additionally, they also recorded bicep
electromyography (EMG), wrist temperature (TEMP) and chest and wrist
actigraphy (ACC). 17 healthy volunteers participated in the data collection,
resulting in a total of 10.5 sensor-simultaneous useful hours. ScientISST MOVE
enables the study of the full body state in free-living environments, and the
effect of daily activities on physiology. Moreover, the double view of
physiological data herein provided could be used in signal quality comparison
studies.
DOI: 10.13026/0ppk-ha30
title: ScientISST MOVE: Annotated Wearable Multimodal Biosignals recorded during Everyday Life Activities in Naturalistic Environments

description: Existing datasets containing physiological data are mostly acquired at rest or
in controlled scenarios. As a result, algorithms developed using such data may
not perform as well as with biosignals acquired in dynamic and uncontrolled
environments. ScientiSST MOVE is a multimodal dataset recording natural
everyday activities, including lifting a chair, greeting, gesticulating,
walking and running. Data was collected using three wearable devices, namely:
a chestband, an armband, and the Empatica E4 wristband. This setup enabled
recording of multi-channel Electrodermal Activity (EDA), Photoplethysmography
(PPG) and Electrocardiography (ECG). Additionally, recordings were also made
for bicep Electromyography (EMG), wrist temperature and chest and wrist
actigraphy. A total of 17 healthy volunteers participated in the experimental
data acquisition sessions, resulting in an average of 37 useful minutes of
synchronised data from all sensors. ScientISST MOVE has been primarily
designed to study the effect of daily activities on physiological data
acquisition. Having been acquired with multiple wearable devices, some of
which measuring the same modalities, it can also be useful in signal quality
comparison studies.
DOI: 10.13026/hyxq-r919
title: ScientISST MOVE: Annotated Wearable Multimodal Biosignals recorded during Everyday Life Activities in Naturalistic Environments

description: Existing datasets containing physiological data are mostly acquired at rest or
in controlled scenarios. As a result, algorithms developed using such data may
not perform as well as with biosignals acquired in dynamic and uncontrolled
environments. ScientiSST MOVE is a multimodal dataset recording natural
everyday activities, including lifting a chair, greeting, gesticulating,
walking and running. Data was collected using three wearable devices, namely:
a chestband, an armband, and the Empatica E4 wristband. This setup enabled
recording of multi-channel Electrodermal Activity (EDA), Photoplethysmography
(PPG) and Electrocardiography (ECG). Additionally, recordings were also made
for bicep Electromyography (EMG), wrist temperature and chest and wrist
actigraphy. A total of 17 healthy volunteers participated in the experimental
data acquisition sessions, resulting in an average of 37 useful minutes of
synchronised data from all sensors. ScientISST MOVE has been primarily
designed to study the effect of daily activities on physiological data
acquisition. Having been acquired with multiple wearable devices, some of
which measuring the same modalities, it can also be useful in signal quality
comparison studies.
DOI: 10.5281/zenodo.10073708
title: Rocket Launch Emission 2019 Dataset

description: A tabulated emissions inventory for stratospheric rocket launch exhaust products, together with launch vehicle-specific references. An additional NetCDF4 model-ready input file containing geo-located rocket launch events from 2019, for use in control/reference scenarios or for development of future launch scenarios.