cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.kdbm5d
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thunnus alalunga (Bonnaterre, 1788)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 18 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032275-241126133413365/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.c.3639404_d4
title: Additional file 2: Online Resource 2. of Six-month quality-of-life and functional status of acute respiratory distress syndrome survivors compared to patients at risk: a population-based study

description: a Butterfly (stream) plot illustrates the changes in the mental component score of the 12-item Short Form survey (SF-12) of each individual patient from baseline (middle line) to 6Â months follow up (lateral line). b Butterfly (stream) plot illustrates the changes in the physical component score of the SF-12 of each individual patient from baseline (middle line) to 6Â months follow up (lateral line). c. Butterfly (stream) plots illustrate the changes in Barthel index score of each individual patient from baseline (middle line) to 6Â months follow up (lateral lines). (ZIP 264 kb)
DOI: 10.6084/m9.figshare.25568780
title: Association of land surface temperature anomalies from GOES/ABI, MSG/SEVIRI, and Himawari-8/AHI with land earthquakes between 2010 and 2021

description: Every year, earthquakes cause numerous casualties and billions of dollars in economic damages, and so far, it is impossible to predict them. Many researchers have studied the land surface temperature (LST) anomalies as promising potential earthquake precursors. In this work, more than 30,000 land earthquakes with a Magnitude (M<sub>w</sub>) larger than 4 have been studied from 2010 to 2021. Global LST nighttime (0–6 am) data from Meteosat Second Generation (MSG), Himawari-8, and the Geostationary Operational Environmental Satellite (GOES) satellites have been used to evaluate the LST anomalies in the zones affected by earthquakes with spatial resolutions of 1, 2, and 4 km, respectively. The time series moving standard deviation (STD) and Interquartile (IQT) have been used to estimate the LST anomalies. The Confusion Matrix (CM), the receiver operating curve (ROC), and some other figures of merit are computed to assess the goodness of positive LST anomalies and detection thresholds as potential proxies of earthquake occurrence. A positive LST anomaly is typically observed a few days [1–7 d] before the earthquake’s occurrence, followed by a negative LST anomaly afterwards [1–3 d].
DOI: 10.6084/m9.figshare.25568780.v1
title: Association of land surface temperature anomalies from GOES/ABI, MSG/SEVIRI, and Himawari-8/AHI with land earthquakes between 2010 and 2021

description: Every year, earthquakes cause numerous casualties and billions of dollars in economic damages, and so far, it is impossible to predict them. Many researchers have studied the land surface temperature (LST) anomalies as promising potential earthquake precursors. In this work, more than 30,000 land earthquakes with a Magnitude (M<sub>w</sub>) larger than 4 have been studied from 2010 to 2021. Global LST nighttime (0–6 am) data from Meteosat Second Generation (MSG), Himawari-8, and the Geostationary Operational Environmental Satellite (GOES) satellites have been used to evaluate the LST anomalies in the zones affected by earthquakes with spatial resolutions of 1, 2, and 4 km, respectively. The time series moving standard deviation (STD) and Interquartile (IQT) have been used to estimate the LST anomalies. The Confusion Matrix (CM), the receiver operating curve (ROC), and some other figures of merit are computed to assess the goodness of positive LST anomalies and detection thresholds as potential proxies of earthquake occurrence. A positive LST anomaly is typically observed a few days [1–7 d] before the earthquake’s occurrence, followed by a negative LST anomaly afterwards [1–3 d].
DOI: 10.6084/m9.figshare.26458488
title: Assessing the efficacy of adaptive capacity-building strategies in earthquake-prone communities

description: Despite advances in science and technology enhancing earthquake prediction capabilities, effective management strategies are crucial to mitigate adverse impacts and protect vulnerable communities’ lives and livelihoods. Therefore, developing community-based disaster management strategies that integrate community participation, coordination, and adaptive capacity within disaster organisations is crucial for effective disaster management. This study uses the importance-performance analysis (IPA) method to assess the efficacy of adaptive capacity-building strategies in earthquake-prone communities. The IPA results highlight the significance of adopting a collaborative and community-centred approach to disaster management. Specifically, the study indicates that both urban and suburban residents prioritise establishing community disaster crisis teams and empowerin
g non-governmental organisations to enhance preparedness and recovery efforts. Meanwhile, suburban residents emphasise the need for community disaster management structures, along with regular prevention lectures, courses, training, and drills to improve residents’ disaster preparedness and awareness. The collaboration between governments and non- governmental organisations plays a crucial role in strengthening communities’ resilience against disasters. These findings offer valuable insights into theoretical design and decision-making processes for implementing adaptive capacity-building strategies in earthquake-prone communities.
DOI: 10.6084/m9.figshare.26458488.v1
title: Assessing the efficacy of adaptive capacity-building strategies in earthquake-prone communities

description: Despite advances in science and technology enhancing earthquake prediction capabilities, effective management strategies are crucial to mitigate adverse impacts and protect vulnerable communities’ lives and livelihoods. Therefore, developing community-based disaster management strategies that integrate community participation, coordination, and adaptive capacity within disaster organisations is crucial for effective disaster management. This study uses the importance-performance analysis (IPA) method to assess the efficacy of adaptive capacity-building strategies in earthquake-prone communities. The IPA results highlight the significance of adopting a collaborative and community-centred approach to disaster management. Specifically, the study indicates that both urban and suburban residents prioritise establishing community disaster crisis teams and empowerin
g non-governmental organisations to enhance preparedness and recovery efforts. Meanwhile, suburban residents emphasise the need for community disaster management structures, along with regular prevention lectures, courses, training, and drills to improve residents’ disaster preparedness and awareness. The collaboration between governments and non- governmental organisations plays a crucial role in strengthening communities’ resilience against disasters. These findings offer valuable insights into theoretical design and decision-making processes for implementing adaptive capacity-building strategies in earthquake-prone communities.
DOI: 10.6084/m9.figshare.26479740
title: Agricultural drought risk assessments: a comprehensive review of indicators, algorithms, and validation for informed adaptations

description: This literature review discusses specific challenges associated with drought risk assessments (DRA) within agricultural systems, particularly concerning the justification for indicator selection, aggregation methods, and DRA-informed adaptation strategies. Employing a multifaceted approach combining quantitative and qualitative methods, we systematically reviewed existing DRA literature. The PRISMA methodology and bibliometric analysis were employed to quantitatively reveal trends, key contributors, and publication patterns in DRA research, offering insights into the research evolution in the field. Simultaneously, the qualitative aspect of this review involved an examination of selected papers to identify critical gaps. Our analysis reveals that 67% of the studies lack validation for their research methodology, underscoring the need for rigorous validation of DRA results to enhance research credibility among decision-makers. Additionally, a significant 88% of the reviewed papers primarily focus on risk identification, with less emphasis on adaptation strategies derived from DRA results. Therefore, we emphasize the imperative of bridging the gap between DRA research and practical applications, advocating for linking drought risk findings to adaptation strategies. This targeted approach allows for the identification of sector-specific indicators, methodologies, and adaptation strategies to address the unique vulnerabilities of agriculture, ultimately enhancing the effectiveness of drought risk management and adaptation efforts in agricultural contexts.
DOI: 10.6084/m9.figshare.26341490
title: Robustness of machine learning algorithms to generate flood susceptibility maps for watersheds in Jordan

description: The study examined three machine learning algorithms (MLAs): random forest (RF), support vector machine (SVM), and artificial neural networks (ANN) for generating flood susceptibility maps in two watersheds in Jordan. Both were selected because they represent two climatic regimes: desert and mountainous areas. Because of a shortage of past floods location, a physical model was utilized to generate them based on simulations of 100-year rainfall. 10,000 of them were selected randomly and used for MLAs training and testing. During training, thirteen flood influential factors were identified. Out of them, the distance to stream, elevation, and topographic wetness index have shown an overwhelming effect in Zarqa Ma’in watershed (they gained 50% of IGR), while the distance to stream, stream density, and elevation have an overwhelming effect in Al-Buaida watershed (they gained 44% of IGR). For flood susceptibility mapping, RF outperformed the other two algorithms for both watersheds and was thus selected for susceptibility mapping. The maps were classified into five classes, and 11% of Al-Buaida watershed fell into high to very high classes, while 5.2% of Zarqa Ma’in watershed fell within these classes. In conclusion, MLAs were able to produce susceptibility maps efficiently, and they can form an alternative to physical modeling.
DOI: 10.6084/m9.figshare.26341490.v1
title: Robustness of machine learning algorithms to generate flood susceptibility maps for watersheds in Jordan

description: The study examined three machine learning algorithms (MLAs): random forest (RF), support vector machine (SVM), and artificial neural networks (ANN) for generating flood susceptibility maps in two watersheds in Jordan. Both were selected because they represent two climatic regimes: desert and mountainous areas. Because of a shortage of past floods location, a physical model was utilized to generate them based on simulations of 100-year rainfall. 10,000 of them were selected randomly and used for MLAs training and testing. During training, thirteen flood influential factors were identified. Out of them, the distance to stream, elevation, and topographic wetness index have shown an overwhelming effect in Zarqa Ma’in watershed (they gained 50% of IGR), while the distance to stream, stream density, and elevation have an overwhelming effect in Al-Buaida watershed (they gained 44% of IGR). For flood susceptibility mapping, RF outperformed the other two algorithms for both watersheds and was thus selected for susceptibility mapping. The maps were classified into five classes, and 11% of Al-Buaida watershed fell into high to very high classes, while 5.2% of Zarqa Ma’in watershed fell within these classes. In conclusion, MLAs were able to produce susceptibility maps efficiently, and they can form an alternative to physical modeling.
DOI: 10.6084/m9.figshare.26480917
title: Exploring the relationship between drought-flood abrupt alternation and soil erosion over Guangdong, China through a convection-permitting model

description: Climate change has caused a more heterogeneous distribution of extreme precipitation, leading to the deterioration of drought-flood abrupt alternation (DFAA) events and soil erosion. The security and sustainable utilization of water and soil resources are severely threatened. Previous studies have focused separately on these two aspects, failing to comprehensively consider their interrelationship. Furthermore, these studies often rely on climate models with convection parameterization, resulting in substantial uncertainties. We use a 4 km convective permitting model (CPM) to generate reliable outputs for extreme precipitation. By incorporating the long-cycle drought-flood abrupt transition index and the Revised Universal Soil Loss Equation model, we analyze the changes in DFAA events and soil erosion, as well as their interconnectedness. The results show that the CPM outperforms coarse-resolution climate models in reproducing erosive rainfall and simulating the heterogeneous distribution of rainfall by capturing convection processes effectively. Projections indicate an escalation in the occurrence of DFAA events and soil erosion due to the more uneven distribution of precipitation. Specifically, the frequency of flood-to-drought (FTD) events within DFAA is projected to rise from 3.8 to 4.7 per decade. Soil loss is projected to increase 61 t·hm<sup>−2</sup>·a<sup>−1</sup>, with 73% of the area experiencing more severe soil erosion intensity. A positive correlation between FTD events and soil erosion is found throughout most of Guangdong. This correlation will be further amplified with an increase in the frequency of FTD events. Consequently, existing soil conservation measures are rendered inadequate, presenting substantial challenges for climate change adaptation and ecological protection in the region.
DOI: 10.6084/m9.figshare.26480917.v1
title: Exploring the relationship between drought-flood abrupt alternation and soil erosion over Guangdong, China through a convection-permitting model

description: Climate change has caused a more heterogeneous distribution of extreme precipitation, leading to the deterioration of drought-flood abrupt alternation (DFAA) events and soil erosion. The security and sustainable utilization of water and soil resources are severely threatened. Previous studies have focused separately on these two aspects, failing to comprehensively consider their interrelationship. Furthermore, these studies often rely on climate models with convection parameterization, resulting in substantial uncertainties. We use a 4 km convective permitting model (CPM) to generate reliable outputs for extreme precipitation. By incorporating the long-cycle drought-flood abrupt transition index and the Revised Universal Soil Loss Equation model, we analyze the changes in DFAA events and soil erosion, as well as their interconnectedness. The results show that the CPM outperforms coarse-resolution climate models in reproducing erosive rainfall and simulating the heterogeneous distribution of rainfall by capturing convection processes effectively. Projections indicate an escalation in the occurrence of DFAA events and soil erosion due to the more uneven distribution of precipitation. Specifically, the frequency of flood-to-drought (FTD) events within DFAA is projected to rise from 3.8 to 4.7 per decade. Soil loss is projected to increase 61 t·hm<sup>−2</sup>·a<sup>−1</sup>, with 73% of the area experiencing more severe soil erosion intensity. A positive correlation between FTD events and soil erosion is found throughout most of Guangdong. This correlation will be further amplified with an increase in the frequency of FTD events. Consequently, existing soil conservation measures are rendered inadequate, presenting substantial challenges for climate change adaptation and ecological protection in the region.
DOI: 10.6084/m9.figshare.26482112
title: Unravelling flash flood dynamics of Song watershed, Doon Valley: key insights for floodplain management

description: The Himalayan foothills are highly prone to rainfall induced flash floods. This research focuses on the August 19–20, 2022 flash flood event in Song watershed of Doon valley, Uttarakhand caused significant damages to buildings and a road bridge. The study aims to assess the flood intensity through flood simulation in a semi-distributed hydrological model by utilizing rainfall data, land use and soil data. Further, the flood hydrographs generated through hydrological modelling were used to simulate hydrodynamic model to estimate flood depth. Pre and post-flood inundation assessments were conducted using PlanetScope and Sentinel-1 imagery. Furthermore, development activities on river courses were analyzed utilizing Google earth and Bing maps high resolution imagery. Cumulative rainfall observations revealed 344 mm rainfall in Rishikesh and 225 mm in Sahastradhara on 19–20 August for the 24 hrs, contributed in a peak flood discharge 2679 m<sup>3</sup>/s at the Rishikesh outlet. The simulated flood depth depicted 4.81 m flood depth at the damaged Thano-Bhogpur bridge. The PlanetScope satellite imagery showed 182 m expansion in the cross-sectional width of river at Maldevta after the flood. A 5.36 sq. km. flood area observed throughout the entire Song catchment in two days post event Sentinel-1 imagery. Analysis of high-resolution imageries revealed increasing development activities in floodplains of the catchment, which got affected by flood. The findings indicate urgent need of floodplain management by implementing comprehensive flood risk management plans including early warning systems, land-use regulations based on flood hazard zonation and flood resilient infrastructure to mitigate future flood exposure to society.
DOI: 10.6084/m9.figshare.26482112.v1
title: Unravelling flash flood dynamics of Song watershed, Doon Valley: key insights for floodplain management

description: The Himalayan foothills are highly prone to rainfall induced flash floods. This research focuses on the August 19–20, 2022 flash flood event in Song watershed of Doon valley, Uttarakhand caused significant damages to buildings and a road bridge. The study aims to assess the flood intensity through flood simulation in a semi-distributed hydrological model by utilizing rainfall data, land use and soil data. Further, the flood hydrographs generated through hydrological modelling were used to simulate hydrodynamic model to estimate flood depth. Pre and post-flood inundation assessments were conducted using PlanetScope and Sentinel-1 imagery. Furthermore, development activities on river courses were analyzed utilizing Google earth and Bing maps high resolution imagery. Cumulative rainfall observations revealed 344 mm rainfall in Rishikesh and 225 mm in Sahastradhara on 19–20 August for the 24 hrs, contributed in a peak flood discharge 2679 m<sup>3</sup>/s at the Rishikesh outlet. The simulated flood depth depicted 4.81 m flood depth at the damaged Thano-Bhogpur bridge. The PlanetScope satellite imagery showed 182 m expansion in the cross-sectional width of river at Maldevta after the flood. A 5.36 sq. km. flood area observed throughout the entire Song catchment in two days post event Sentinel-1 imagery. Analysis of high-resolution imageries revealed increasing development activities in floodplains of the catchment, which got affected by flood. The findings indicate urgent need of floodplain management by implementing comprehensive flood risk management plans including early warning systems, land-use regulations based on flood hazard zonation and flood resilient infrastructure to mitigate future flood exposure to society.
DOI: 10.15468/dl.8jfr8z
title: Occurrence Download

description: A dataset containing 94329 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Cynanthus latirostris Swainson, 1827"
 ]
}

 The dataset includes 94329 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032273-241126133413365/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.3198715.v4
title: Skafte - Standardized reporting SOC.doc

description: Standardized reporting protocol for
long-term SOC tests, as suggested in T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.3198715.v3
title: Skafte - Standardized reporting SOC.doc

description: Standardized reporting protocol for
long-term SOC tests, as suggested in T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.1607410.v2
title: SOC tests database v0.72 (open-access).xlsx

description: A collection of tests reported in the solid oxide cell devices community. SOFC cell, SOFC stack, SOEC cell and SOEC stack tests are included. Originally published in relation to T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.3126481.v1
title: BL Flickr image dataset: User Submitted Tags (til March 2016)
DOI: 10.15468/dl.gq77cu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scomber alalunga Bonnaterre, 1788",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032276-241126133413365/datasets/export for details.
DOI: 10.6084/m9.figshare.3198715.v2
title: Skafte - Standardized reporting SOC.doc

description: Standardized reporting protocol for
long-term SOC tests, as suggested in T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.3181072.v1
title: A #comicsforum15 Archive [09/11/215 17:30:10 - 18/11/2015 15:01:05 GMT]
DOI: 10.15468/dl.hdxk5p
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amphibia",
 "Geometry POLYGON ((-99.4145 19.55474, -99.32015 19.55474, -99.32015 19.64505, -99.4145 19.64505, -99.4145 19.55474))",
 "Year is greater than or equal to 1900",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material citation)"
 ]
 }
 }
 ]
}

 The dataset includes 24 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032277-241126133413365/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.3181072
title: A #comicsforum15 Archive [09/11/215 17:30:10 - 18/11/2015 15:01:05 GMT]
DOI: 10.6084/m9.figshare.3198715
title: Skafte - Standardized reporting SOC.doc

description: Standardized reporting protocol for
long-term SOC tests, as suggested in T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.3198715.v1
title: Skafte - Standardized reporting SOC.doc

description: Standardized reporting protocol for
long-term SOC tests, as suggested in T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.1607410
title: SOC tests database v1.00 (open-access).xlsx

description: A collection of tests reported in the solid oxide cell devices community. SOFC cell, SOFC stack, SOEC cell and SOEC stack tests are included. Originally published in relation to T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.1607410.v1
title: SOC tests database 0.71 (open-access).xlsx

description: A collection of tests reported in the solid oxide cell devices community. SOFC cell, SOFC stack, SOEC cell and SOEC stack tests are included. Originally published in relation to T. Skafte et al., EFCF 2016, B0501 (2016).
DOI: 10.6084/m9.figshare.3180979
title: An #ICAF2016 Archive [13/04/2016 15:02:02-17/04/2016 17:44:39 BST]