cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28251846.v1
title: <i>The Schoolyard I’d Like</i>: an ideas competition for Australian school children ages 12 to 17

description: Restorative outdoor environments are places that allow a person to rest and rebuild their capacity to function. Schoolyard design provides an ideal opportunity to create spaces that provide respite for students during the school day. However, the outdoor environmental preferences of adolescents have not been fully explored. This Australian-based study uses qualitative methods to analyse the schoolyard designs of thirty-eight students ages 12 to 17 through the lens of restorative environment theories. The aim is to identify and define indicators of schoolyard design quality and impact as defined by students themselves. Findings reveal that students desire schoolyards which are an antidote to daily academic and social stresses. Of particular focus are spaces designed for peer engagement and self-renewal. Student measures of schoolyard quality are framed through attributes of beauty, agency and social connection. Schoolyard design is often driven by industry standards of minimising risk, cost and without input from students. Our analysis suggests that these outdoor spaces should be more responsive to end-user aesthetic preferences, social values, and environmental concerns that promote student restoration. Such information would benefit designers, managers and users of schoolyard spaces to ensure co-designed spaces meet student restorative needs.
DOI: 10.34740/kaggle/dsv/10840169
title: Daily Public Opinion on Israel-Palestine War
DOI: 10.15468/dl.fy4zgf
title: Occurrence Download

description: A dataset containing 69 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Orchis purpurea Huds.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 69 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002956-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qznvu5
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Guadeloupe",
 "OccurrenceStatus is Present",
 "TaxonKey is Scaevola plumieri (L.) Vahl"
 ]
}

 The dataset includes 14 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002957-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8njcj2
title: Occurrence Download

description: A dataset containing 12320 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scleractinia",
 "Year 2015-2020"
 ]
}

 The dataset includes 12320 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002960-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.suagx9
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "StateProvince is RIO GRaNdE dO SUL",
 "TaxonKey is Agelasticus cyanopus (Vieillot, 1819)"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002958-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w7vx44
title: Occurrence Download

description: A dataset containing 615 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syngnathus tenuirostris Rathke, 1837",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 615 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002959-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sjbu9j
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dactylorhiza sambucina (L.) Soó",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 17 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002961-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5525/gla.researchdata.1880
title: Sub-organellar mitochondrial hydrogen peroxide observed using a SNAP tag targeted coumarin-based fluorescent reporter
DOI: 10.34740/kaggle/dsv/10840213
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.5281/zenodo.14917256
title: PHT
DOI: 10.5281/zenodo.14917257
title: PHT
DOI: 10.21227/w17r-xx75
title: LSApp: Large dataset of Sequential mobile App usage

description: During the study period, with the help of 292 participants, we were able to collect 599,635 app usage records. Here, we summarize the main characteristics of the participants based on the submitted surveys. 59% of the participants were female and 50% aged between 25 and 34. Participants were from all kinds of educational backgrounds ranging from high school diploma to PhD. In particular, 32% of them had a college degree, followed by 30% with a bachelor's degree. Smartphone was the main device used for connecting to the Internet for 53% of the participants, followed by laptop (25%). Among the participants, 67% used their smartphones more often for personal reasons rather than work. Finally, half of the participants stated that they use their smartphones 4 hours a day or more
DOI: 10.17632/zxcxd4zsp2.1
title: Large-scale genomic variation analysis reveals evolutionary patterns and adaptive mechanisms across 98 insects

description: Background: Insects represent the most diverse group of animals and have achieved remarkable evolutionary success across a wide array of ecological niches. Their adaptability is largely attributed to extensive genomic variation. However, the evolutionary forces shaping this variation remain inadequately understood. 
Results: Here, we perform a large-scale comparative analysis of genomic variation across six orders (Coleoptera, Diptera, Hymenoptera, Lepidoptera, Hemiptera, and Phasmatodea) using 3,187 high-quality resequencing datasets from 98 insects. To uncover the lineage-specific mutation rates and evolutionary constraints, we characterize genome-wide single nucleotide polymorphisms (SNPs) and insertion-deletion variants (InDels). The results showed that Coleoptera exhibits the highest SNP and InDel rates, ranging from 10⁻³ to 10⁻⁷ and 10⁻⁴ to 10⁻⁷, respectively. This partially explains the species richness of this order, whereas domesticated Diptera and Hymenoptera show reduced variation. In addition, transition-transversion ratios vary markedly among insects. Functional analyses of high-diversity genes highlight key orthogroups related to transposon, odorant receptors , and cytochrome P450. 
Conclusions: These findings suggest that transposon dynamics, selective pressures on genomic regions associated with chemoreception and detoxification, and lineage-specific variation collectively drive insect adaptation. Our study offers new insights into the genomic basis of insect diversification and has important implications for predicting adaptive responses to environmental change as well as for developing targeted pest management strategies.
DOI: 10.17632/9mckw4t9f3.1
title: Nuclear Paxillin Modulates Alternative Splicing Programs in Neurons during Sensitive Periods of Brain Development

description: During sensitive postnatal periods, brain neural circuits undergo significant refinement coincident with widespread neuronal alternative splicing events in which h undreds of genes alter their splice site selection to generate isoforms essential for synaptic plasticity. Here, we reveal that neuronal activity-dependent serine119 phosphorylation of paxillin (p-paxillin S119) acts as a molecular switch in the nucleus to modulate alternative splicing during this period. We report that following NMDA receptor activation, nuclear p-paxillin S119 is recruited to nuclear speckles, where it interacts with U2AFs and splicing factors. Neuronal paxillin expression is required for timely alternative splicing of synaptic factors, including Snap25. Consequently, young mice lacking paxillin S119 phosphorylation exhibit significantly reduced levels of Snap25-5b isoforms, impaired presynaptic function at hippocampal Schaffer collateral-CA1 synapses, and deficits in short-term learning and memory. These findings support the idea that nuclear p-paxillin S119 is a critical mediator of alternative splicing programs in postnatal neurons during a sensitive period essential for neural plasticity.
DOI: 10.17632/9mckw4t9f3.2
title: Nuclear Paxillin Modulates Alternative Splicing Programs in Neurons during Sensitive Periods of Brain Development
DOI: 10.17632/hrmwzpbctg
title: Interest Rates, Insecurity and FDI

description: This file is the dataset on Interest rates, insecurity and Foreign direct investment of selected countries in West Africa between 2007 and 2022
DOI: 10.17632/hrmwzpbctg.1
title: Interest Rates, Insecurity and FDI

description: This file is the dataset on Interest rates, insecurity and Foreign direct investment of selected countries in West Africa between 2007 and 2022
DOI: 10.17632/xn9ws8x6j7.1
title: The Economic Bomb: A Strategic Financial Warfare Tactic

description: This dataset provides comprehensive evidence supporting the hypothesis that coordinated institutional shorting, ETF outflows, whale wallet movements, and media sentiment collectively drive Bitcoin’s volatility and price manipulation. The dataset spans from January 2021 to December 2024, capturing daily market activity and key events that impacted Bitcoin’s price movements. 

The dataset consists of the following key components: 

1. BTC_Price_Data.csv: Tracks daily BTC/USD closing prices from major exchanges (Binance, Coinbase, and Bitstamp), serving as the baseline for volatility and return calculations. 
2. ETF_Holdings_Over_Time_Thesis.csv: Monitors daily BTC holdings of major ETFs (Grayscale, BlackRock, and Fidelity), showing cumulative outflows and their impact on market liquidity. 
3. ETF_Outflows_Price_Impact_Data.csv: Correlates daily ETF outflows with BTC price volatility, highlighting the timing and magnitude of price declines. 
4. Institutional_Shorting_Data.csv: Tracks daily BTC short positions and open interest from major exchanges (Binance, BitMEX, Bybit, and OKX), revealing increased shorting activity preceding price drops. 
5. Whale_Wallet_Movements CSV.csv: Documents daily BTC movements of large wallets, demonstrating coordinated sell-offs before major price crashes. 
6. Market_Liquidity_Data.csv: Captures daily BTC trading volume, order book depth, and liquidity ratios, showing reduced liquidity during volatility spikes. 
7. Media_Sentiment_Scores.csv: Measures daily sentiment (positive, neutral, negative) from Twitter, Reddit, Google News, and YouTube, highlighting sentiment shifts during key events. 
8. Monte_Carlo_Simulation_Results.csv: Simulates 1,000 BTC price paths to assess potential volatility under market stress. 
9. VAR_Model_Data.csv: Analyzes the delayed impact of ETF outflows on BTC returns using a vector autoregression model. 
10. Volatility_Clustering_Data.csv: Tracks daily BTC returns and 30-day rolling volatility, showing persistent volatility after institutional actions. 
11. GARCH_Model_Data.csv: Models BTC volatility using the GARCH framework, confirming volatility clustering during market shocks. 

The dataset is structured to enable researchers and analysts to replicate key findings of the doctoral thesis The Economic Bomb: A Strategic Financial Warfare Tactic by Nicolin Decker. Each file includes event-driven adjustments for major market incidents, such as the May 2021 Flash Crash, June 2022 Liquidation Crisis, and March 2023 Banking Crisis, ensuring realistic volatility patterns. This dataset is essential for studying the interconnected effects of institutional actions, market liquidity, and public sentiment on Bitcoin’s volatility. 

Access the full dataset (Upload Could Not Contain All Files): 
https://drive.google.com/drive/folders/1pnwqBTMF_QSJoC5QcNAPSQpVtOST2n8c?usp=drive_link
DOI: 10.17632/xn9ws8x6j7.2
title: The Economic Bomb: A Strategic Financial Warfare Tactic

description: This dataset provides evidence supporting the hypothesis that institutional shorting, ETF outflows, whale wallet movements, and media sentiment drive Bitcoin’s volatility and price manipulation. Central to this dataset is the Decker Sentiment-Short Interest Model (DSSIM)—an original equation developed by Nicolin Decker to quantify the relationship between market sentiment and institutional short interest. By combining sentiment scores from Natural Language Processing (NLP) and short positioning data, DSSIM offers a flexible framework for analyzing volatility in Bitcoin and other assets.

The dataset spans January 2021 to December 2024, capturing daily market activity and key price events. Each file aligns with DSSIM’s variables, enabling replication and further analysis of the findings in the doctoral-level thesis The Economic Bomb: A Strategic Financial Warfare Tactic.

Key Components:
BTC_Price_Data.csv: Daily BTC/USD closing prices from Binance, Coinbase, and Bitstamp, serving as the baseline for volatility and return calculations.

ETF_Holdings_Over_Time_Thesis.csv: Daily BTC holdings of ETFs (Grayscale, BlackRock, and Fidelity), illustrating cumulative outflows and their liquidity impact.

ETF_Outflows_Price_Impact_Data.csv: Correlates ETF outflows with BTC volatility, highlighting timing and magnitude.

Institutional_Shorting_Data.csv: Daily BTC short positions from Binance, BitMEX, Bybit, and OKX, serving as input for DSSIM’s short interest variable.

Whale_Wallet_Movements.csv: Tracks large BTC wallet movements, revealing sell-offs preceding price crashes and influencing DSSIM’s residual noise component.

Market_Liquidity_Data.csv: Daily BTC trading volume, order book depth, and liquidity ratios, validating DSSIM’s predictive capabilities.

Media_Sentiment_Scores.csv: Daily sentiment from Twitter, Reddit, Google News, and YouTube, forming DSSIM’s sentiment variable.

Monte_Carlo_Simulation_Results.csv: Simulates 1,000 BTC price paths to assess potential volatility under market stress.

VAR_Model_Data.csv: Analyzes ETF outflows’ delayed impact on BTC returns using vector autoregression.

Volatility_Clustering_Data.csv: Tracks daily BTC returns and 30-day rolling volatility, confirming persistent volatility after institutional actions.

GARCH_Model_Data.csv: Models BTC volatility using GARCH, validating volatility clustering during market shocks.

The dataset includes adjustments for major market events, such as the May 2021 Flash Crash, June 2022 Liquidation Crisis, and March 2023 Banking Crisis, ensuring realistic volatility patterns aligned with DSSIM’s modeling of sentiment shifts and institutional shorting.

Researchers can use DSSIM’s structure and data to explore similar dynamics in other cryptocurrencies, equities, commodities, and forex markets, advancing financial analysis and predictive modeling.

Access the full dataset: 
https://drive.google.com/drive/folders/1pnwqBTMF_QSJoC5QcNAPSQpVtOST2n8c?usp=drive_link
DOI: 10.15468/dl.qhvjbf
title: Occurrence Download

description: A dataset containing 1512558 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (March, April, May)",
 "OccurrenceStatus is Present",
 "Year 1750-2025"
 ]
}

 The dataset includes 1512558 records from 1123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002951-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xn9ws8x6j7.3
title: The Economic Bomb: A Strategic Financial Warfare Tactic

description: This dataset provides evidence supporting the hypothesis that institutional shorting, ETF outflows, whale wallet movements, and media sentiment drive Bitcoin’s volatility and price manipulation. Central to this dataset is the Decker Sentiment-Short Interest Model (DSSIM)—an original equation developed by Nicolin Decker to quantify the relationship between market sentiment and institutional short interest. By combining sentiment scores from Natural Language Processing (NLP) and short positioning data, DSSIM offers a flexible framework for analyzing volatility in Bitcoin and other assets.

The dataset spans January 2021 to December 2024, capturing daily market activity and key price events. Each file aligns with DSSIM’s variables, enabling replication and further analysis of the findings in the doctoral-level thesis The Economic Bomb: A Strategic Financial Warfare Tactic.

Key Components:
BTC_Price_Data.csv: Daily BTC/USD closing prices from Binance, Coinbase, and Bitstamp, serving as the baseline for volatility and return calculations.

ETF_Holdings_Over_Time_Thesis.csv: Daily BTC holdings of ETFs (Grayscale, BlackRock, and Fidelity), illustrating cumulative outflows and their liquidity impact.

ETF_Outflows_Price_Impact_Data.csv: Correlates ETF outflows with BTC volatility, highlighting timing and magnitude.

Institutional_Shorting_Data.csv: Daily BTC short positions from Binance, BitMEX, Bybit, and OKX, serving as input for DSSIM’s short interest variable.

Whale_Wallet_Movements.csv: Tracks large BTC wallet movements, revealing sell-offs preceding price crashes and influencing DSSIM’s residual noise component.

Market_Liquidity_Data.csv: Daily BTC trading volume, order book depth, and liquidity ratios, validating DSSIM’s predictive capabilities.

Media_Sentiment_Scores.csv: Daily sentiment from Twitter, Reddit, Google News, and YouTube, forming DSSIM’s sentiment variable.

Monte_Carlo_Simulation_Results.csv: Simulates 1,000 BTC price paths to assess potential volatility under market stress.

VAR_Model_Data.csv: Analyzes ETF outflows’ delayed impact on BTC returns using vector autoregression.

Volatility_Clustering_Data.csv: Tracks daily BTC returns and 30-day rolling volatility, confirming persistent volatility after institutional actions.

GARCH_Model_Data.csv: Models BTC volatility using GARCH, validating volatility clustering during market shocks.

The dataset includes adjustments for major market events, such as the May 2021 Flash Crash, June 2022 Liquidation Crisis, and March 2023 Banking Crisis, ensuring realistic volatility patterns aligned with DSSIM’s modeling of sentiment shifts and institutional shorting.

Researchers can use DSSIM’s structure and data to explore similar dynamics in other cryptocurrencies, equities, commodities, and forex markets, advancing financial analysis and predictive modeling.

Access the full dataset: 
https://drive.google.com/drive/folders/1pnwqBTMF_QSJoC5QcNAPSQpVtOST2n8c?usp=drive_link
DOI: 10.15468/dl.xgkkrx
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Osmunda regalis L.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 22 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002962-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9f6yu4
title: Occurrence Download

description: A dataset containing 2210 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Dalea leporina (Aiton) Bullock"
 ]
}

 The dataset includes 2210 records from 158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002965-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f45nvh
title: Occurrence Download

description: A dataset containing 4470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Haplochromis macrops, Haplochromis maculipinna, Haplochromis maisomei, Haplochromis mandibularis, Haplochromis martini, Haplochromis maxillaris, Haplochromis megalops, Haplochromis melanopterus, Haplochromis melanopus, Haplochromis melichrous, Haplochromis mento, Haplochromis michaeli, Haplochromis microdon, Haplochromis mylergates, Haplochromis nanoserranus, Haplochromis nigrescens, Haplochromis nyanzae, Haplochromis obtusidens, Haplochromis oligolepis, Haplochromis pachycephalus, Haplochromis pallidus, Haplochromis paraguiarti, Haplochromis paraplagiostoma, Haplochromis paropius, Haplochromis parvidens, Haplochromis pellegrini, Haplochromis percoides, Haplochromis perrieri, Haplochromis pharyngomylus, Haplochromis phytophagus, Haplochromis piceatus, Haplochromis pitmani, Haplochromis plagiodon, Haplochromis plagiostoma, Haplochromis plutonius, Haplochromis prodromus, Haplochromis prognathus, Haplochromis pseudopellegrini, Haplochromis ptistes, Haplochromis pyrrhopteryx, Haplochromis retrodens, Haplochromis sauvagei, Haplochromis serranus, Haplochromis squamulatus, Haplochromis sulphureus, Haplochromis teegelaari, Haplochromis teunisrasi, Haplochromis thuragnathus, Haplochromis tridens, Haplochromis tyrianthinus, Haplochromis victorianus, Haplochromis xenognathus, Haplochromis xenostoma, Labeo werneri, Lithochromis rubripinnis, Lithochromis rufus, Lithochromis xanthopteryx, Mbipia lutea, Mbipia mbipi, Neochromis gigas, Neochromis greenwoodi, Neochromis omnicaeruleus, Neochromis rufocaudalis, Paralabidochromis victoriae, Pundamilia azurea, Pundamilia igneopinis, Pundamilia macrocephala, Pundamilia nyererei, Pundamilia pundamilia, Pyxichromis parorthostoma, Xenoclarias holobranchus, Haplochromis theliodon, Haplochromis obesus, Gnathonemus longibarbis, Haplochromis riponianus, Haplochromis nuchisquamulatus, Haplochromis humilior, Haplochromis spekii, Haplochromis saxicola, Haplochromis obliquidens, Neochromis nigricans, Enteromius viktorianus, Enteromius loveridgii, Haplochromis nubilus, Haplochromis angustifrons, Haplochromis limax, Haplochromis vicarius, Haplochromis mylodon, Haplochromis nigripinnis, Haplochromis taurinus, Haplochromis elegans, Haplochromis schubotzi, Schubotzia eduardiana, Haplochromis squamipinnis, Haplochromis macropsoides, Dimidiochromis kiwinge, Placidochromis longimanus, Corematodus shiranus, Trematocranus placodon, Nimbochromis livingstonii)",
 "HasCoordinate is true",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 4470 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058163-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.